Object/Edit Dialog in
the menu just above this text, which will open this documentation in a separate window that you can more easily come back to. If your screen is small, you may also want to make this new window \"Always on Top\": e.g., in Linux, Emergent-logo-at-top-left-> Advanced-> Keep Above Others). Alternatively, you can always return to this document by clicking on the ProjectDocs tab at the top of this middle panel.
This project replicates the effect described in Frank (2005), in which a basal ganglia network can learn via pure reinforcement learning to select between complex probabilistic stimulus-response mappings in the \"weather prediction\" task, while networks with simulated Parkinson's disease are impaired.
Each of the four possible 'cues' in the task are represented by a column of units in the Input layer, and anywhere from one to three cues are presented at a time.
The relationship between particular cues present and probability of a given response (sun or rain, represented by R1 and R2 in the model) is highly probabilistic and combinatorial. For those interested in the specific probabilistic weather prediction input-output mappings and the frequency of occurrence of each cue, see Knowlton et al (1994) Learning & Memory
which is represented in the \"Train_WeatherPred\" input data table in the tree on the left.
The project is set up to run four epochs, consisting of one hundred trials each, for a total of 400 trials. Networks are tested before training, and after each epoch of training, by testing for optimal performance
(using the TestWP_Optimal InputData). Performance on this test is monitored in the [[.T3Tab.EpochOutputData]] graph, counting the number of errors made out of a total of 12 possible (so chance performance of 50% is 6 errors). In this measure, errors are counted not as a function of feedback in each trial during training itself (which is probabilistic) but rather in terms of the best (most optimal) choice.
Note that this test is also administered to the model at the very beginning, prior to any training, as a measure of baseline performance (should be chance on average), and that during this test there is no 'feedback' (DA bursts or dips which would otherwise drive learning).
For intact network performance, make sure the number of intact SNc units is set to 4 (out of 4 units), the DA burst value is set to 1 (corresponding to maximal phasic burst firing rate) and the DA dip value is set to 0 (minimum phasic dip DA firing rate). These values are set in the [[.PanelTab.MasterControl]] panel.
To run a set of networks on the task, hit Init and Run on the [[.PanelTab.MasterControl]] panel (say yes to initializing weights). This will run a set of 25 networks, and store the raw data in data->OutputData->EpochOutputData.
(To speed things up when running a batch of networks, turn off the display of the network by clicking on the appropriate tab that you want to view and check off the Display! box on the top left.)
The output in the cnt_err column of the [[.PanelTab.EpochOutputData]] log file is the number of errors (out of 12) made in the optimal test environment, plotted as a function of epoch number, for each run of the network in the batch. Because the data are noisy (probabilistic rewards combined with random input weights which could by chance lead to particularly good or bad performance), we need to average across multiple networks with different sets of initial weights. In the project, this is done automatically, and saved in the AnalysisData subgroup of the data folder in the 'tree' in the far left panel. These data are plotted in the EpochOutputData_Group panel to the far right. To analyze the raw data manually, in the [[.PanelTab.EpochOutputData]] tab, click on DataProc->Group Mean SEM. In the dialog box that pops up, make sure the dest_data is set to NULL; this will create a new output data log under the AnalysisData subgroup in the left frame, called EpochOutputData_Group. Also set the first gp_col1 to \"epoch\" so that the script can analyze performance as a function of each epoch, averaged across all networks. Set all other fields to NULL and click Ok. Now open the new analysis EpochOutputData_Group log. You should see the statistics (mean, standard error) for each variable that was monitored in the EpochOutputData log. The relevant ones are cnt_err_mean and cnt_err_sem.
You should see that intact networks learn to discriminate between the complex probabilistic contingencies in the weather prediction task as training progresses (error decreases within 2-4 epochs, corresponding to 200-400 trials of training). They usually don't achieve perfectly optimal performance in the task, still making on average 20-25% errors, but this is also the case for healthy humans performing the task! (Also remember the network is learning using pure reinforcement learning and not error-driven learning).
To simulate PD, set the number of intact DA units to 1 in the [[.PanelTab.MasterControl]] control panel. This sets the number of SNc units that are connected to the Striatum to 1 (out of 4). This reduction in number of intact DA units leads to effectively reduced tonic and phasic DA levels in the Striatum.
Hit Init and Run to run a batch. When it's done, analyze the group mean and standard error as above. You should see that Parkinson's networks are impaired at learning compared with intact networks, due to a reduced dynamic range of DA signals for resolving Go/NoGo differences in stimulus-response-reward probabilities. If you run the network with more graded DA damage (number of intact units set to 2 or 3) you should see graded degradations in performance, suggesting that as DA levels drop, the ability to finely resolve probabilistic associations drops accordingly.
Finally, it was shown in Frank (2005) that the indirect \"NoGo\" pathway is critical for robust learning, in that networks without this pathway, even controlling for other parameters in the resulting network, were reliably impaired compared to the full model. These results demonstrate that the combined Go/NoGo learning system is required for learning from the full dynamic range of DA signals and for enhancing the contrast between subtly different probabilistic reinforcement values in this complex task. For other manipulations of D2 receptors in the NoGo pathway specifically, see the other projects (in particular of the probabilistic selection task).
= PD Tremor, and Oscillations =
With very low DA levels, you may also see some oscillations in STN and GP layers on some trials (these correspond to Parkinson's tremor; see Frank, 2006 for detailed discussion). You can look at these more carefully in the [[.T3Tab.CycleOutputData]] graph logs where activity levels of the various layers are recorded. The easiest way to see this is to set the number of intact snc units to 0 on the [[.PanelTab.MasterControl]] panel. This will eliminate all DA unit activity during response selection. Then increase the number of cycles that the network processes in each test trial so that you have more room to see oscillations -- change the \"test cycles\" value to 200. Next, open the LeabraTestEpoch program from the tree on the left. This will allow you to step through some test trials with the test cycles set to this new value and to observe the resulting activity levels.
Press Init and TstTrial on the Control panel a few times while watching the activity levels of the STN in the [[.T3Tab.CycleOutputData]] graph log. You might have to step through a few trials to see the oscillations, which should not (or only rarely) be seen in the intact state. In Frank 2006, it was shown that these oscillations are more apparent when the model is faced with response conflict.
";
html_text="
Object/Edit Dialog in
the menu just above this text, which will open this documentation in a separate window that you can more easily come back to. If your screen is small, you may also want to make this new window \"Always on Top\": e.g., in Linux, Emergent-logo-at-top-left-> Advanced-> Keep Above Others). Alternatively, you can always return to this document by clicking on the ProjectDocs tab at the top of this middle panel.
This project replicates the effect described in Frank (2005), in which a basal ganglia network can learn via pure reinforcement learning to select between complex probabilistic stimulus-response mappings in the \"weather prediction\" task, while networks with simulated Parkinson's disease are impaired.
Each of the four possible 'cues' in the task are represented by a column of units in the Input layer, and anywhere from one to three cues are presented at a time. The relationship between particular cues present and probability of a given response (sun or rain, represented by R1 and R2 in the model) is highly probabilistic and combinatorial. For those interested in the specific probabilistic weather prediction input-output mappings and the frequency of occurrence of each cue, see Knowlton et al (1994) Learning & Memory which is represented in the \"Train_WeatherPred\" input data table in the tree on the left.
The project is set up to run four epochs, consisting of one hundred trials each, for a total of 400 trials. Networks are tested before training, and after each epoch of training, by testing for optimal performance (using the TestWP_Optimal InputData). Performance on this test is monitored in the EpochOutputData graph, counting the number of errors made out of a total of 12 possible (so chance performance of 50% is 6 errors). In this measure, errors are counted not as a function of feedback in each trial during training itself (which is probabilistic) but rather in terms of the best (most optimal) choice.
Note that this test is also administered to the model at the very beginning, prior to any training, as a measure of baseline performance (should be chance on average), and that during this test there is no 'feedback' (DA bursts or dips which would otherwise drive learning).
For intact network performance, make sure the number of intact SNc units is set to 4 (out of 4 units), the DA burst value is set to 1 (corresponding to maximal phasic burst firing rate) and the DA dip value is set to 0 (minimum phasic dip DA firing rate). These values are set in the MasterControl panel.
To run a set of networks on the task, hit Init and Run on the MasterControl panel (say yes to initializing weights). This will run a set of 25 networks, and store the raw data in data->OutputData->EpochOutputData.
(To speed things up when running a batch of networks, turn off the display of the network by clicking on the appropriate tab that you want to view and check off the Display! box on the top left.)
The output in the cnt_err column of the EpochOutputData log file is the number of errors (out of 12) made in the optimal test environment, plotted as a function of epoch number, for each run of the network in the batch. Because the data are noisy (probabilistic rewards combined with random input weights which could by chance lead to particularly good or bad performance), we need to average across multiple networks with different sets of initial weights. In the project, this is done automatically, and saved in the AnalysisData subgroup of the data folder in the 'tree' in the far left panel. These data are plotted in the EpochOutputData_Group panel to the far right. To analyze the raw data manually, in the EpochOutputData tab, click on DataProc->Group Mean SEM. In the dialog box that pops up, make sure the dest_data is set to NULL; this will create a new output data log under the AnalysisData subgroup in the left frame, called EpochOutputData_Group. Also set the first gp_col1 to \"epoch\" so that the script can analyze performance as a function of each epoch, averaged across all networks. Set all other fields to NULL and click Ok. Now open the new analysis EpochOutputData_Group log. You should see the statistics (mean, standard error) for each variable that was monitored in the EpochOutputData log. The relevant ones are cnt_err_mean and cnt_err_sem.
You should see that intact networks learn to discriminate between the complex probabilistic contingencies in the weather prediction task as training progresses (error decreases within 2-4 epochs, corresponding to 200-400 trials of training). They usually don't achieve perfectly optimal performance in the task, still making on average 20-25% errors, but this is also the case for healthy humans performing the task! (Also remember the network is learning using pure reinforcement learning and not error-driven learning).
To simulate PD, set the number of intact DA units to 1 in the MasterControl control panel. This sets the number of SNc units that are connected to the Striatum to 1 (out of 4). This reduction in number of intact DA units leads to effectively reduced tonic and phasic DA levels in the Striatum.
Hit Init and Run to run a batch. When it's done, analyze the group mean and standard error as above. You should see that Parkinson's networks are impaired at learning compared with intact networks, due to a reduced dynamic range of DA signals for resolving Go/NoGo differences in stimulus-response-reward probabilities. If you run the network with more graded DA damage (number of intact units set to 2 or 3) you should see graded degradations in performance, suggesting that as DA levels drop, the ability to finely resolve probabilistic associations drops accordingly.
Finally, it was shown in Frank (2005) that the indirect \"NoGo\" pathway is critical for robust learning, in that networks without this pathway, even controlling for other parameters in the resulting network, were reliably impaired compared to the full model. These results demonstrate that the combined Go/NoGo learning system is required for learning from the full dynamic range of DA signals and for enhancing the contrast between subtly different probabilistic reinforcement values in this complex task. For other manipulations of D2 receptors in the NoGo pathway specifically, see the other projects (in particular of the probabilistic selection task).
LeabraTestEpoch program from the tree on the left. This will allow you to step through some test trials with the test cycles set to this new value and to observe the resulting activity levels.
Press Init and TstTrial on the Control panel a few times while watching the activity levels of the STN in the CycleOutputData graph log. You might have to step through a few trials to see the oscillations, which should not (or only rarely) be seen in the intact state. In Frank 2006, it was shown that these oscillations are more apparent when the model is faced with response conflict.
";
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el_def=0;
UserDataItem @["NO_CLIP"] {
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value 1 0=1;
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name="LeabraWizard_2";
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ctrl_panels {
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ControlPanel @["MasterControl"] {
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mbrs {
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EditMbrItem @[0] {
label="DA_burst_val";
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cust_desc=0;
base=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["DA_burst_val"]$$;
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EditMbrItem @[1] {
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cust_desc=0;
base=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["DA_dip_val"]$$;
mbr=ProgVar::real_val;
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EditMbrItem @[2] {
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cust_desc=0;
base=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["num_intact_snc_units"]$$;
mbr=ProgVar::int_val;
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EditMbrItem @[3] {
label="test_cycles";
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: enter the expression here -- use Ctrl-L to pull up a lookup dialog for members, methods, types, etc -- or you can just type in names of program variables or literal values. enclose strings in double quotes. variable names will be checked and automatically updated
var lookup: lookup a program variable and add it to the current expression (this field then returns to empty/NULL)";
cust_desc=0;
base=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].prog_code[5].else_code[0]$$;
mbr=MemberAssign::expr;
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mths {
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EditMthItem @[0] {
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cust_desc=0;
base=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"]$$;
mth=Program::Init;
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EditMthItem @[1] {
label="Run";
desc=" run the program -- if not yet Init, will run Init first";
cust_desc=0;
base=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"]$;
mth=Program::Run_Gui;
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EditMthItem @[2] {
label="Step";
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cust_desc=0;
base=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"]$;
mth=Program::Step_Gui;
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EditMthItem @[3] {
label="Stop";
desc=" stop the current program at its next natural stopping point (i.e., cleanly stopping when appropriate chunks of computation have completed)";
cust_desc=0;
base=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"]$;
mth=Program::Stop;
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ControlPanel @["UnitInhib"] {
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mbrs {
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EditMbrItem @[0] {
label="excite_dt";
desc=" time constants (rate of updating): membrane potential (vm) and net input (net)
integ: [Default: 1;0.5;0.001;0.0005] overall rate constant for numerical integration -- affected by the timescale of the parameters and numerical stability issues -- typically 1 cycle = 1 ms, and if using ms normed units, this should be 1, otherwise 0.001 (1 ms in seconds) or possibly .5 or .0005 if there are stability issues
vm: [Default: 0.1:0.357] membrane potential rate constant -- reflects the capacitance of the neuron in principle -- biological default for AeEx spiking model C = 281 pF = 2.81 normalized = .356 rate constant
net: [Default: 0.7] net input time constant -- how fast to update net input (damps oscillations) -- generally reflects time constants associated with synaptic channels which are not modeled in the most abstract rate code models (set to 1 for detailed spiking models with more realistic synaptic currents)
midpoint: use the midpoint method in computing the vm value -- better avoids oscillations and allows a larger dt.vm parameter to be used -- this is critical to use with SPIKE mode
d vm max: [Default: 100] maximum change in vm at any timestep (limits blowup) -- this is a crude but effective safety valve for numerical integration problems (no longer necessary in gelin-based compuation)
vm eq cyc: [Default: 0] number of cycles to compute the vm as equilibirium potential given current inputs: set to 1 to quickly activate input layers; set to 100 to always use this computation
vm eq dt: [Default: 1] time constant for integrating the vm_eq values: how quickly to move toward the current eq value from previous vm value
integ time: 1/integ rate constant = time constant for each cycle of updating for numerical integration
vm time: 1/vm rate constant = time in cycles for vm to reach 1/e of asymptotic value
net time: 1/net rate constant = time in cycles for net to reach 1/e of asymptotic value";
cust_desc=0;
base=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].specs.gp["Units"]["FixedBiasUnitSpec"]$$;
mbr=LeabraUnitSpec::dt;
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param_search {
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EditMbrItem @[1] {
label="inhib_dt";
desc=" time constants (rate of updating): membrane potential (vm) and net input (net)
integ: [Default: 1;0.5;0.001;0.0005] overall rate constant for numerical integration -- affected by the timescale of the parameters and numerical stability issues -- typically 1 cycle = 1 ms, and if using ms normed units, this should be 1, otherwise 0.001 (1 ms in seconds) or possibly .5 or .0005 if there are stability issues
vm: [Default: 0.1:0.357] membrane potential rate constant -- reflects the capacitance of the neuron in principle -- biological default for AeEx spiking model C = 281 pF = 2.81 normalized = .356 rate constant
net: [Default: 0.7] net input time constant -- how fast to update net input (damps oscillations) -- generally reflects time constants associated with synaptic channels which are not modeled in the most abstract rate code models (set to 1 for detailed spiking models with more realistic synaptic currents)
midpoint: use the midpoint method in computing the vm value -- better avoids oscillations and allows a larger dt.vm parameter to be used -- this is critical to use with SPIKE mode
d vm max: [Default: 100] maximum change in vm at any timestep (limits blowup) -- this is a crude but effective safety valve for numerical integration problems (no longer necessary in gelin-based compuation)
vm eq cyc: [Default: 0] number of cycles to compute the vm as equilibirium potential given current inputs: set to 1 to quickly activate input layers; set to 100 to always use this computation
vm eq dt: [Default: 1] time constant for integrating the vm_eq values: how quickly to move toward the current eq value from previous vm value
integ time: 1/integ rate constant = time constant for each cycle of updating for numerical integration
vm time: 1/vm rate constant = time in cycles for vm to reach 1/e of asymptotic value
net time: 1/net rate constant = time in cycles for net to reach 1/e of asymptotic value";
cust_desc=0;
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l: Constant leak (potassium, K+) channel
i: inhibitory
h: hysteresis (Ca)
a: accomodation (k)";
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EditMbrItem @[3] {
label="to_inhib_rnd";
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type: type of random variable to generate
* UNIFORM: uniform with var = range on either side of the mean
* BINOMIAL: binomial with var = p, par = n
* POISSON: poisson with lambda = var
* GAMMA: gamma with var scaling parameter and par = k stages
* GAUSSIAN: normal with var
* BETA: beta with var = a and par = b shape parameters
* NONE: just the mean
mean: mean of random distribution
var: 'varibility' parameter for the random numbers (gauss = standard deviation, not variance; uniform = half-range)
par: extra parameter for distribution (depends on each one)";
cust_desc=0;
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type: type of random variable to generate
* UNIFORM: uniform with var = range on either side of the mean
* BINOMIAL: binomial with var = p, par = n
* POISSON: poisson with lambda = var
* GAMMA: gamma with var scaling parameter and par = k stages
* GAUSSIAN: normal with var
* BETA: beta with var = a and par = b shape parameters
* NONE: just the mean
mean: mean of random distribution
var: 'varibility' parameter for the random numbers (gauss = standard deviation, not variance; uniform = half-range)
par: extra parameter for distribution (depends on each one)";
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* NONE: don't adapt anything
* KWTA PT: adapt kwta point (i_kwta_pt) based on running-average layer activation as compared to target value
* G BAR I: adapt g_bar.i for unit inhibition values based on layer activation at any point in time
* G BAR IL: adapt g_bar.i and g_bar.l for unit inhibition & leak values based on layer activation at any point in time
tol: [Default: 0.02] tolerance around target avg act before changing parameter
p dt: [Default: 0.1] time constant for changing the parameter (i_kwta_pt or g_bar.i)
mx d: [Default: 0.9] maximum deviation (proportion) from initial parameter setting allowed
l: proportion of difference from target activation to allocate to the leak in G_BAR_IL mode
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UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["user_pinned"] {
name="user_pinned";
value 1 0=1;
val_type_fixed=0;
};
};
name="ClusterRun";
updt_while_running=0;
desc=;
mbrs {
name="mbrs";
el_typ=EditMbrItem;
el_def=0;
};
mths {
name="mths";
el_typ=EditMthItem;
el_def=0;
group_type=GT_BUTTONS;
};
jobs_running {
name="jobs_running";
desc=;
data {
name="data";
el_typ=String_Data;
el_def=0;
String_Data @["cluster"] {
name="cluster";
desc="name of cluster to run job on";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["user"] {
name="user";
desc="user who ran this job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["tag"] {
name="tag";
desc="unique tag id for this job -- all files etc are named according to this tag";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["status"] {
name="status";
desc="status of job: REQUESTED, CANCELLED, SUBMITTED, QUEUED, RUNNING, DONE, KILLED";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["label"] {
name="label";
desc="label for the job -- a brief description that you can use to label this job's results on your graph -- in general notes should have more general info and then label should JUST describe what is unique about the current run";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["notes"] {
name="notes";
desc="notes for the job -- describe any specific information about the model configuration etc -- can use this for searching and sorting results";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["filename"] {
name="filename";
desc="name of the specific project used for this job -- because multiple versions of a model are often run under the same project name";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["params"] {
name="params";
desc="emergent parameters based on currently selected items in the ClusterRun";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["status_info"] {
name="status_info";
desc="more detailed information about status";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_time"] {
name="submit_time";
desc="when was the job submitted (tracks time from emergent client submission)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["start_time"] {
name="start_time";
desc="when did the job actually start running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["end_time"] {
name="end_time";
desc="when did the job finish running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["running_time"] {
name="running_time";
desc="total running time in days/hours/minutes";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_no"] {
name="job_no";
desc="job number on cluster -- assigned once the job is submitted to the cluster";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_out"] {
name="job_out";
desc="job output information -- contains (top of) the job standard output and standard error output as the job is running (truncated to top 2048 characters if longer than that) -- full information available in job_out_file";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_out_file"] {
name="job_out_file";
desc="job output file -- file name containing full job output information -- file name should be tag.out";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["dat_files"] {
name="dat_files";
desc="list of data table output (results) files generated by model (space separated) -- these files have the tag in their name, and end in .dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["other_files"] {
name="other_files";
desc="list of other output (results) files generated by model (space separated) -- these files have the tag in their name but do not end in .dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["command_id"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="command_id";
desc="id for this command, assigned by the search algorithm in an algorithm-specific manner (optional)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["command"] {
name="command";
desc="emergent command line, up to point of parameters";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["repo_url"] {
name="repo_url";
desc="name of repository to run job on";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["queue"] {
name="queue";
desc="if specified, indicate a particular queue on the computing resource";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["run_time"] {
name="run_time";
desc="how long will the jobs take to run -- syntax is number followed by unit indicator -- m=minutes, h=hours, d=days -- e.g., 30m, 12h, or 2d -- typically the job will be killed if it exceeds this amount of time, so be sure to not underestimate";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["ram_gb"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="ram_gb";
desc="how many gigabytes of ram is required? 0 means do not specify this parameter for the job submission -- for large memory jobs, it can be important to specify this to ensure proper allocation of resources";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["n_threads"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="n_threads";
desc="number of parallel threads to use for running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["mpi_nodes"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="mpi_nodes";
desc="number of physical nodes to use for mpi run -- 0 or -1 means not to use mpi";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["mpi_per_node"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="mpi_per_node";
desc="number of processes to use per MPI node to use for mpi run - total nodes is mpi_nodes * mpi_per_node";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["pb_batches"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="pb_batches";
desc="if > 0, use parallel batch mode with this number of batches";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["pb_nodes"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="pb_nodes";
desc="actually pb_n_batches_per -- re-using this parameter that was previously used for a different purpose -- number of batches to run sequentially within a single job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_svn"] {
name="submit_svn";
desc="svn revision for the original job submission";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_job"] {
name="submit_job";
desc="index of job number within a given submission -- equal to the row number of the original set of jobs submitted in submit_svn jobs";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["done_svn"] {
name="done_svn";
desc="svn revision when this job was moved from running to done -- this will contain full set of files generated when running -- for deleted jobs can also recover to this";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["last_svn"] {
name="last_svn";
desc="last svn revision for command submission that affected this job in some significant way -- for deleted jobs, this is the svn revision that we recover to";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
};
data_flags=AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
jobs_done {
name="jobs_done";
desc=;
data {
name="data";
el_typ=String_Data;
el_def=0;
String_Data @["cluster"] {
name="cluster";
desc="name of cluster to run job on";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["user"] {
name="user";
desc="user who ran this job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["tag"] {
name="tag";
desc="unique tag id for this job -- all files etc are named according to this tag";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["status"] {
name="status";
desc="status of job: REQUESTED, CANCELLED, SUBMITTED, QUEUED, RUNNING, DONE, KILLED";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["label"] {
name="label";
desc="label for the job -- a brief description that you can use to label this job's results on your graph -- in general notes should have more general info and then label should JUST describe what is unique about the current run";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["notes"] {
name="notes";
desc="notes for the job -- describe any specific information about the model configuration etc -- can use this for searching and sorting results";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["filename"] {
name="filename";
desc="name of the specific project used for this job -- because multiple versions of a model are often run under the same project name";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["params"] {
name="params";
desc="emergent parameters based on currently selected items in the ClusterRun";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["status_info"] {
name="status_info";
desc="more detailed information about status";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_time"] {
name="submit_time";
desc="when was the job submitted (tracks time from emergent client submission)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["start_time"] {
name="start_time";
desc="when did the job actually start running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["end_time"] {
name="end_time";
desc="when did the job finish running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["running_time"] {
name="running_time";
desc="total running time in days/hours/minutes";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_no"] {
name="job_no";
desc="job number on cluster -- assigned once the job is submitted to the cluster";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_out"] {
name="job_out";
desc="job output information -- contains (top of) the job standard output and standard error output as the job is running (truncated to top 2048 characters if longer than that) -- full information available in job_out_file";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_out_file"] {
name="job_out_file";
desc="job output file -- file name containing full job output information -- file name should be tag.out";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["dat_files"] {
name="dat_files";
desc="list of data table output (results) files generated by model (space separated) -- these files have the tag in their name, and end in .dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["other_files"] {
name="other_files";
desc="list of other output (results) files generated by model (space separated) -- these files have the tag in their name but do not end in .dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["command_id"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="command_id";
desc="id for this command, assigned by the search algorithm in an algorithm-specific manner (optional)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["command"] {
name="command";
desc="emergent command line, up to point of parameters";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["repo_url"] {
name="repo_url";
desc="name of repository to run job on";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["queue"] {
name="queue";
desc="if specified, indicate a particular queue on the computing resource";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["run_time"] {
name="run_time";
desc="how long will the jobs take to run -- syntax is number followed by unit indicator -- m=minutes, h=hours, d=days -- e.g., 30m, 12h, or 2d -- typically the job will be killed if it exceeds this amount of time, so be sure to not underestimate";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["ram_gb"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="ram_gb";
desc="how many gigabytes of ram is required? 0 means do not specify this parameter for the job submission -- for large memory jobs, it can be important to specify this to ensure proper allocation of resources";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["n_threads"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="n_threads";
desc="number of parallel threads to use for running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["mpi_nodes"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="mpi_nodes";
desc="number of physical nodes to use for mpi run -- 0 or -1 means not to use mpi";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["mpi_per_node"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="mpi_per_node";
desc="number of processes to use per MPI node to use for mpi run - total nodes is mpi_nodes * mpi_per_node";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["pb_batches"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="pb_batches";
desc="if > 0, use parallel batch mode with this number of batches";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["pb_nodes"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="pb_nodes";
desc="actually pb_n_batches_per -- re-using this parameter that was previously used for a different purpose -- number of batches to run sequentially within a single job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_svn"] {
name="submit_svn";
desc="svn revision for the original job submission";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_job"] {
name="submit_job";
desc="index of job number within a given submission -- equal to the row number of the original set of jobs submitted in submit_svn jobs";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["done_svn"] {
name="done_svn";
desc="svn revision when this job was moved from running to done -- this will contain full set of files generated when running -- for deleted jobs can also recover to this";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["last_svn"] {
name="last_svn";
desc="last svn revision for command submission that affected this job in some significant way -- for deleted jobs, this is the svn revision that we recover to";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
};
data_flags=AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
jobs_deleted {
name="jobs_deleted";
desc=;
data {
name="data";
el_typ=String_Data;
el_def=0;
String_Data @["cluster"] {
name="cluster";
desc="name of cluster to run job on";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["user"] {
name="user";
desc="user who ran this job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["tag"] {
name="tag";
desc="unique tag id for this job -- all files etc are named according to this tag";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["status"] {
name="status";
desc="status of job: REQUESTED, CANCELLED, SUBMITTED, QUEUED, RUNNING, DONE, KILLED";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["label"] {
name="label";
desc="label for the job -- a brief description that you can use to label this job's results on your graph -- in general notes should have more general info and then label should JUST describe what is unique about the current run";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["notes"] {
name="notes";
desc="notes for the job -- describe any specific information about the model configuration etc -- can use this for searching and sorting results";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["filename"] {
name="filename";
desc="name of the specific project used for this job -- because multiple versions of a model are often run under the same project name";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["params"] {
name="params";
desc="emergent parameters based on currently selected items in the ClusterRun";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["status_info"] {
name="status_info";
desc="more detailed information about status";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_time"] {
name="submit_time";
desc="when was the job submitted (tracks time from emergent client submission)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["start_time"] {
name="start_time";
desc="when did the job actually start running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["end_time"] {
name="end_time";
desc="when did the job finish running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["running_time"] {
name="running_time";
desc="total running time in days/hours/minutes";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_no"] {
name="job_no";
desc="job number on cluster -- assigned once the job is submitted to the cluster";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_out"] {
name="job_out";
desc="job output information -- contains (top of) the job standard output and standard error output as the job is running (truncated to top 2048 characters if longer than that) -- full information available in job_out_file";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_out_file"] {
name="job_out_file";
desc="job output file -- file name containing full job output information -- file name should be tag.out";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["dat_files"] {
name="dat_files";
desc="list of data table output (results) files generated by model (space separated) -- these files have the tag in their name, and end in .dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["other_files"] {
name="other_files";
desc="list of other output (results) files generated by model (space separated) -- these files have the tag in their name but do not end in .dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["command_id"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="command_id";
desc="id for this command, assigned by the search algorithm in an algorithm-specific manner (optional)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["command"] {
name="command";
desc="emergent command line, up to point of parameters";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["repo_url"] {
name="repo_url";
desc="name of repository to run job on";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["queue"] {
name="queue";
desc="if specified, indicate a particular queue on the computing resource";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["run_time"] {
name="run_time";
desc="how long will the jobs take to run -- syntax is number followed by unit indicator -- m=minutes, h=hours, d=days -- e.g., 30m, 12h, or 2d -- typically the job will be killed if it exceeds this amount of time, so be sure to not underestimate";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["ram_gb"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="ram_gb";
desc="how many gigabytes of ram is required? 0 means do not specify this parameter for the job submission -- for large memory jobs, it can be important to specify this to ensure proper allocation of resources";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["n_threads"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="n_threads";
desc="number of parallel threads to use for running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["mpi_nodes"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="mpi_nodes";
desc="number of physical nodes to use for mpi run -- 0 or -1 means not to use mpi";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["mpi_per_node"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="mpi_per_node";
desc="number of processes to use per MPI node to use for mpi run - total nodes is mpi_nodes * mpi_per_node";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["pb_batches"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="pb_batches";
desc="if > 0, use parallel batch mode with this number of batches";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["pb_nodes"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="pb_nodes";
desc="actually pb_n_batches_per -- re-using this parameter that was previously used for a different purpose -- number of batches to run sequentially within a single job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_svn"] {
name="submit_svn";
desc="svn revision for the original job submission";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_job"] {
name="submit_job";
desc="index of job number within a given submission -- equal to the row number of the original set of jobs submitted in submit_svn jobs";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["done_svn"] {
name="done_svn";
desc="svn revision when this job was moved from running to done -- this will contain full set of files generated when running -- for deleted jobs can also recover to this";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["last_svn"] {
name="last_svn";
desc="last svn revision for command submission that affected this job in some significant way -- for deleted jobs, this is the svn revision that we recover to";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
};
data_flags=AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
jobs_archive {
name="jobs_archive";
desc=;
data {
name="data";
el_typ=String_Data;
el_def=0;
String_Data @["cluster"] {
name="cluster";
desc="name of cluster to run job on";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["user"] {
name="user";
desc="user who ran this job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["tag"] {
name="tag";
desc="unique tag id for this job -- all files etc are named according to this tag";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["status"] {
name="status";
desc="status of job: REQUESTED, CANCELLED, SUBMITTED, QUEUED, RUNNING, DONE, KILLED";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["label"] {
name="label";
desc="label for the job -- a brief description that you can use to label this job's results on your graph -- in general notes should have more general info and then label should JUST describe what is unique about the current run";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["notes"] {
name="notes";
desc="notes for the job -- describe any specific information about the model configuration etc -- can use this for searching and sorting results";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["filename"] {
name="filename";
desc="name of the specific project used for this job -- because multiple versions of a model are often run under the same project name";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["params"] {
name="params";
desc="emergent parameters based on currently selected items in the ClusterRun";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["status_info"] {
name="status_info";
desc="more detailed information about status";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_time"] {
name="submit_time";
desc="when was the job submitted (tracks time from emergent client submission)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["start_time"] {
name="start_time";
desc="when did the job actually start running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["end_time"] {
name="end_time";
desc="when did the job finish running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["running_time"] {
name="running_time";
desc="total running time in days/hours/minutes";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_no"] {
name="job_no";
desc="job number on cluster -- assigned once the job is submitted to the cluster";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_out"] {
name="job_out";
desc="job output information -- contains (top of) the job standard output and standard error output as the job is running (truncated to top 2048 characters if longer than that) -- full information available in job_out_file";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_out_file"] {
name="job_out_file";
desc="job output file -- file name containing full job output information -- file name should be tag.out";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["dat_files"] {
name="dat_files";
desc="list of data table output (results) files generated by model (space separated) -- these files have the tag in their name, and end in .dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["other_files"] {
name="other_files";
desc="list of other output (results) files generated by model (space separated) -- these files have the tag in their name but do not end in .dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["command_id"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="command_id";
desc="id for this command, assigned by the search algorithm in an algorithm-specific manner (optional)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["command"] {
name="command";
desc="emergent command line, up to point of parameters";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["repo_url"] {
name="repo_url";
desc="name of repository to run job on";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["queue"] {
name="queue";
desc="if specified, indicate a particular queue on the computing resource";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["run_time"] {
name="run_time";
desc="how long will the jobs take to run -- syntax is number followed by unit indicator -- m=minutes, h=hours, d=days -- e.g., 30m, 12h, or 2d -- typically the job will be killed if it exceeds this amount of time, so be sure to not underestimate";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["ram_gb"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="ram_gb";
desc="how many gigabytes of ram is required? 0 means do not specify this parameter for the job submission -- for large memory jobs, it can be important to specify this to ensure proper allocation of resources";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["n_threads"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="n_threads";
desc="number of parallel threads to use for running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["mpi_nodes"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="mpi_nodes";
desc="number of physical nodes to use for mpi run -- 0 or -1 means not to use mpi";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["mpi_per_node"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="mpi_per_node";
desc="number of processes to use per MPI node to use for mpi run - total nodes is mpi_nodes * mpi_per_node";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["pb_batches"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="pb_batches";
desc="if > 0, use parallel batch mode with this number of batches";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["pb_nodes"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="pb_nodes";
desc="actually pb_n_batches_per -- re-using this parameter that was previously used for a different purpose -- number of batches to run sequentially within a single job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_svn"] {
name="submit_svn";
desc="svn revision for the original job submission";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["submit_job"] {
name="submit_job";
desc="index of job number within a given submission -- equal to the row number of the original set of jobs submitted in submit_svn jobs";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["done_svn"] {
name="done_svn";
desc="svn revision when this job was moved from running to done -- this will contain full set of files generated when running -- for deleted jobs can also recover to this";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["last_svn"] {
name="last_svn";
desc="last svn revision for command submission that affected this job in some significant way -- for deleted jobs, this is the svn revision that we recover to";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
};
data_flags=AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
file_list {
name="file_list";
desc=;
data {
name="data";
el_typ=String_Data;
el_def=0;
String_Data @["cluster"] {
name="cluster";
desc="cluster where this job was submitted / run";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["user"] {
name="user";
desc="user who ran this job";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["file_name"] {
name="file_name";
desc="name of file -- does not include any path information";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["tag"] {
name="tag";
desc="job tag associated with this file";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["size"] {
name="size";
desc="size of file -- with typical suffixes (K = kilobytes, M = megabytes, G = gigabytes)";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["kind"] {
name="kind";
desc="type of file";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["date_modified"] {
name="date_modified";
desc="timestamp for when the file was last modified";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["date_created"] {
name="date_created";
desc="timestamp for when the file was first created";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["svn_file_path"] {
name="svn_file_path";
desc="path to file in SVN repository, relative to root of svn_repo repository";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["proj_file_path"] {
name="proj_file_path";
desc="path to file relative to the parent project directory -- e.g., results/filename.dat";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["file_path"] {
name="file_path";
desc="full path to file on local file system, including all parent directories and name of file -- takes you directly to the file";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
};
data_flags=AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
cluster_info {
name="cluster_info";
desc=;
data {
name="data";
el_typ=String_Data;
el_def=0;
String_Data @["queue"] {
name="queue";
desc="queue that this info relates to";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["job_no"] {
name="job_no";
desc="job number or total number of actve jobs";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["user"] {
name="user";
desc="user name";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["state"] {
name="state";
desc="current scheduler state -- or description of global state info";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["procs"] {
name="procs";
desc="number of processors for this job or for global state info";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["start_time"] {
name="start_time";
desc="timestamp for when the job was submitted or started running";
col_flags=SAVE_DATA|READ_ONLY;
is_matrix=0;
cell_geom{ };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
};
data_flags=AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
search_algos {
name="search_algos";
el_typ=ParamSearchAlgo;
el_def=0;
};
use_search_algo=0;
cur_search_algo=NULL;
set_proj_name=0;
proj_name=;
auto_updt_interval=10;
auto_updt_timeout=30;
cluster=;
clusters=;
users=;
last_submit_time=;
notes=;
label=;
extra_files=;
svn_repo=;
repo_url=;
queue=;
run_time=;
exe_cmd="emergent7";
ram_gb=0;
n_threads=1;
use_mpi=0;
mpi_nodes=10;
mpi_per_node=1;
parallel_batch=0;
pb_batches=10;
pb_n_batches_per=1;
nowin_x=0;
enable_kill=0;
enable_load=0;
enable_notes=0;
};
};
param_sets {
name="param_sets";
el_typ=ParamSet;
el_def=0;
};
data {
name="data";
el_typ=DataTable;
el_def=0;
save_tables=1;
DataTable_Group @.gp["InputData"] {
name="InputData";
el_typ=DataTable;
el_def=0;
save_tables=1;
DataTable @["Train_WeatherPred"] {
name="Train_WeatherPred";
desc=;
data {
name="data";
el_typ=String_Data;
el_def=0;
String_Data @["Name"] {
name="Name";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[100] "Event_1";"Event_2";"Event_3";"Event_4";"Event_5";"Event_6";"Event_7";"Event_8";"Event_9";"Event_10";
"Event_11";"Event_12";"Event_13";"Event_14";"Event_15";"Event_16";"Event_17";"Event_18";"Event_19";"Event_20";
"Event_21";"Event_22";"Event_23";"Event_24";"Event_25";"Event_26";"Event_27";"Event_28";"Event_29";"Event_30";
"Event_31";"Event_32";"Event_33";"Event_34";"Event_35";"Event_36";"Event_37";"Event_38";"Event_39";"Event_40";
"Event_41";"Event_42";"Event_43";"Event_44";"Event_45";"Event_46";"Event_47";"Event_48";"Event_49";"Event_50";
"Event_51";"Event_52";"Event_53";"Event_54";"Event_55";"Event_56";"Event_57";"Event_58";"Event_59";"Event_60";
"Event_61";"Event_62";"Event_63";"Event_64";"Event_65";"Event_66";"Event_67";"Event_68";"Event_69";"Event_70";
"Event_71";"Event_72";"Event_73";"Event_74";"Event_75";"Event_76";"Event_77";"Event_78";"Event_79";"Event_80";
"Event_81";"Event_82";"Event_83";"Event_84";"Event_85";"Event_86";"Event_87";"Event_88";"Event_89";"Event_90";
"Event_91";"Event_92";"Event_93";"Event_94";"Event_95";"Event_96";"Event_97";"Event_98";"Event_99";"Event_1";
};
};
float_Data @["Input"] {
name="Input";
col_flags=SAVE_DATA;
is_matrix=1;
cell_geom{ 5;5; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[2] ;; };
width=0;
ar {
name="ar";
[5 5 100] 0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;0.5;0.5;0;0;0;0.5;0.5;0;
0;0;0.5;0.5;0;0;0;0.5;0.5;0;
0;0;0.5;0.5;0;0;1;0;0;0;
0;1;0;0;0;0;1;0;0;0;
0;1;0;0;0;0;1;0;0;0;
0;0.5;0;0.5;0;0;0.5;0;0.5;0;
0;0.5;0;0.5;0;0;0.5;0;0.5;0;
0;0.5;0;0.5;0;0;0.5;0.5;0;0;
0;0.5;0.5;0;0;0;0.5;0.5;0;0;
0;0.5;0.5;0;0;0;0.5;0.5;0;0;
0;0.33333299;0.33333299;0.33333299;0;0;0.33333299;0.33333299;0.33333299;0;
0;0.33333299;0.33333299;0.33333299;0;0;0.33333299;0.33333299;0.33333299;0;
0;0.33333299;0.33333299;0.33333299;0;1;0;0;0;0;
1;0;0;0;0;1;0;0;0;0;
1;0;0;0;0;1;0;0;0;0;
0.5;0;0;0.5;0;0.5;0;0;0.5;0;
0.5;0;0;0.5;0;0.5;0;0;0.5;0;
0.5;0;0;0.5;0;0.5;0;0.5;0;0;
0.5;0;0.5;0;0;0.5;0;0.5;0;0;
0.5;0;0.5;0;0;0.5;0;0.5;0;0;
0.33333299;0;0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0;
0.33333299;0;0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0;
0.33333299;0;0.33333299;0.33333299;0;0.5;0.5;0;0;0;
0.5;0.5;0;0;0;0.5;0.5;0;0;0;
0.5;0.5;0;0;0;0.5;0.5;0;0;0;
0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0;0.33333299;0;
0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0;0.33333299;0;
0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0.33333299;0;0;
0.33333299;0.33333299;0.33333299;0;0;0.33333299;0.33333299;0.33333299;0;0;
0.33333299;0.33333299;0.33333299;0;0;0.33333299;0.33333299;0.33333299;0;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
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0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
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1;0;1;0;1;0;1;0;1;0;
1;0;0;1;0;1;1;0;1;0;
1;0;1;0;1;0;1;0;1;0;
1;0;0;1;0;1;1;0;1;0;
};
};
};
data_flags=SAVE_ROWS|AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
row_indexes {
name="row_indexes";
[100] 0;1;2;3;4;5;6;7;8;9;
10;11;12;13;14;15;16;17;18;19;
20;21;22;23;24;25;26;27;28;29;
30;31;32;33;34;35;36;37;38;39;
40;41;42;43;44;45;46;47;48;49;
50;51;52;53;54;55;56;57;58;59;
60;61;62;63;64;65;66;67;68;69;
70;71;72;73;74;75;76;77;78;79;
80;81;82;83;84;85;86;87;88;89;
90;91;92;93;94;95;96;97;98;99;
};
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
DataTable @["TestWP_Optimal"] {
name="TestWP_Optimal";
desc=;
data {
name="data";
el_typ=String_Data;
el_def=0;
String_Data @["Name"] {
name="Name";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[12] "0001_14_143";"0010_08_375";"0011_09_111";"0100_08_625";"0101_06_167";"0111_04_250";"1000_14_857";"1010_06_833";"1011_03_333";"1100_09_889";
"1101_03_667";"1110_04_750"; };
};
float_Data @["Input"] {
name="Input";
col_flags=SAVE_DATA;
is_matrix=1;
cell_geom{ 5;5; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[2] ;; };
width=0;
ar {
name="ar";
[5 5 12] 0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;0;1;0;
0;0;0;1;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;1;0;0;0;0;1;0;0;
0;0;0.5;0.5;0;0;0;0.5;0.5;0;
0;0;0.5;0.5;0;0;0;0.5;0.5;0;
0;0;0.5;0.5;0;0;1;0;0;0;
0;1;0;0;0;0;1;0;0;0;
0;1;0;0;0;0;1;0;0;0;
0;0.5;0;0.5;0;0;0.5;0;0.5;0;
0;0.5;0;0.5;0;0;0.5;0;0.5;0;
0;0.5;0;0.5;0;0;0.33333299;0.33333299;0.33333299;0;
0;0.33333299;0.33333299;0.33333299;0;0;0.33333299;0.33333299;0.33333299;0;
0;0.33333299;0.33333299;0.33333299;0;0;0.33333299;0.33333299;0.33333299;0;
1;0;0;0;0;1;0;0;0;0;
1;0;0;0;0;1;0;0;0;0;
1;0;0;0;0;0.5;0;0.5;0;0;
0.5;0;0.5;0;0;0.5;0;0.5;0;0;
0.5;0;0.5;0;0;0.5;0;0.5;0;0;
0.33333299;0;0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0;
0.33333299;0;0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0;
0.33333299;0;0.33333299;0.33333299;0;0.5;0.5;0;0;0;
0.5;0.5;0;0;0;0.5;0.5;0;0;0;
0.5;0.5;0;0;0;0.5;0.5;0;0;0;
0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0;0.33333299;0;
0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0;0.33333299;0;
0.33333299;0.33333299;0;0.33333299;0;0.33333299;0.33333299;0.33333299;0;0;
0.33333299;0.33333299;0.33333299;0;0;0.33333299;0.33333299;0.33333299;0;0;
0.33333299;0.33333299;0.33333299;0;0;0.33333334;0.33333299;0.33333299;0;0;
};
};
float_Data @["Output"] {
name="Output";
col_flags=SAVE_DATA;
is_matrix=1;
cell_geom{ 2;1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[2] ;; };
width=0;
ar {
name="ar";
[2 1 12] 1;0;1;0;1;0;0;1;1;0;
1;0;0;1;0;1;1;0;0;1;
0;1;0;1; };
};
float_Data @["SNc"] {
name="SNc";
col_flags=SAVE_DATA;
is_matrix=1;
cell_geom{ 2;2; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[2] ;; };
width=0;
ar {
name="ar";
[2 2 12] 0;0;0;0;2000;2000;2000;2000;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;2000;2000;2000;2000;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0; };
};
float_Data @["Motor_Cortex"] {
name="Motor_Cortex";
col_flags=SAVE_DATA;
is_matrix=1;
cell_geom{ 2;1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[2] ;; };
width=0;
ar {
name="ar";
[2 1 12] 0;1;0;1;0;1;0;1;0;1;
0;1;0;1;0;1;0;1;1;0;
0;1;0;1; };
};
float_Data @["GP_Int"] {
name="GP_Int";
col_flags=SAVE_DATA;
is_matrix=1;
cell_geom{ 2;2; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[2] ;; };
width=0;
ar {
name="ar";
[2 2 12] 0;1;0;1;1;0;1;0;0;1;
0;1;0;1;0;1;0;1;0;1;
0;1;0;1;1;0;1;0;0;1;
0;1;0;1;0;1;1;0;1;0;
0;1;0;1;0;1;0;1; };
};
};
data_flags=SAVE_ROWS|AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
row_indexes {
name="row_indexes";
[12] 0;1;2;3;4;5;6;7;8;9;
10;11; };
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
};
DataTable_Group @.gp["OutputData"] {
name="OutputData";
el_typ=DataTable;
el_def=0;
save_tables=1;
DataTable @["TrialOutputData"] {
name="TrialOutputData";
desc=;
data {
name="data";
el_typ=int_Data;
el_def=0;
int_Data @["batch"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_83";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="batch";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] 0;0;0; };
};
int_Data @["epoch"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_84";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="epoch";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] 0;0;0; };
};
int_Data @["trial"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_85";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="trial";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] 0;1;2; };
};
String_Data @["trial_name"] {
name="trial_name";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] "1011_03_333";"1000_14_857";"0010_08_375"; };
};
String_Data @["group_name"] {
name="group_name";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] ;;; };
};
int_Data @["phase_no"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_86";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
};
name="phase_no";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] 1;1;1; };
};
float_Data @["minus_cycles"] {
name="minus_cycles";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] 200;200;200; };
};
float_Data @["sse"] {
name="sse";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] 0.39565247;0;0.95950067; };
};
float_Data @["ext_rew"] {
name="ext_rew";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] 0;0;0; };
};
float_Data @["Output_sse"] {
name="Output_sse";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[3] 0.39565247;0;0.95950067; };
};
};
data_flags=SAVE_ROWS|AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
row_indexes {
name="row_indexes";
[3] 0;1;2; };
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
DataTable @["TrnTestTrialOutputData"] {
name="TrnTestTrialOutputData";
desc=;
data {
name="data";
el_typ=int_Data;
el_def=0;
int_Data @["batch"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItemBase;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2666666805744171;
val_type_fixed=0;
};
};
name="batch";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[1100] 0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;1;1;1;1;1;1;
1;1;1;1;1;1;1;1;1;1;
1;1;1;1;1;1;1;1;1;1;
1;1;1;1;1;1;1;1;1;1;
1;1;1;1;1;1;1;1;2;2;
2;2;2;2;2;2;2;2;2;2;
2;2;2;2;2;2;2;2;2;2;
2;2;2;2;2;2;2;2;2;2;
2;2;2;2;2;2;2;2;2;2;
2;2;3;3;3;3;3;3;3;3;
3;3;3;3;3;3;3;3;3;3;
3;3;3;3;3;3;3;3;3;3;
3;3;3;3;3;3;3;3;3;3;
3;3;3;3;3;3;4;4;4;4;
4;4;4;4;4;4;4;4;4;4;
4;4;4;4;4;4;4;4;4;4;
4;4;4;4;4;4;4;4;4;4;
4;4;4;4;4;4;4;4;4;4;
5;5;5;5;5;5;5;5;5;5;
5;5;5;5;5;5;5;5;5;5;
5;5;5;5;5;5;5;5;5;5;
5;5;5;5;5;5;5;5;5;5;
5;5;5;5;6;6;6;6;6;6;
6;6;6;6;6;6;6;6;6;6;
6;6;6;6;6;6;6;6;6;6;
6;6;6;6;6;6;6;6;6;6;
6;6;6;6;6;6;6;6;7;7;
7;7;7;7;7;7;7;7;7;7;
7;7;7;7;7;7;7;7;7;7;
7;7;7;7;7;7;7;7;7;7;
7;7;7;7;7;7;7;7;7;7;
7;7;8;8;8;8;8;8;8;8;
8;8;8;8;8;8;8;8;8;8;
8;8;8;8;8;8;8;8;8;8;
8;8;8;8;8;8;8;8;8;8;
8;8;8;8;8;8;9;9;9;9;
9;9;9;9;9;9;9;9;9;9;
9;9;9;9;9;9;9;9;9;9;
9;9;9;9;9;9;9;9;9;9;
9;9;9;9;9;9;9;9;9;9;
10;10;10;10;10;10;10;10;10;10;
10;10;10;10;10;10;10;10;10;10;
10;10;10;10;10;10;10;10;10;10;
10;10;10;10;10;10;10;10;10;10;
10;10;10;10;11;11;11;11;11;11;
11;11;11;11;11;11;11;11;11;11;
11;11;11;11;11;11;11;11;11;11;
11;11;11;11;11;11;11;11;11;11;
11;11;11;11;11;11;11;11;12;12;
12;12;12;12;12;12;12;12;12;12;
12;12;12;12;12;12;12;12;12;12;
12;12;12;12;12;12;12;12;12;12;
12;12;12;12;12;12;12;12;12;12;
12;12;13;13;13;13;13;13;13;13;
13;13;13;13;13;13;13;13;13;13;
13;13;13;13;13;13;13;13;13;13;
13;13;13;13;13;13;13;13;13;13;
13;13;13;13;13;13;14;14;14;14;
14;14;14;14;14;14;14;14;14;14;
14;14;14;14;14;14;14;14;14;14;
14;14;14;14;14;14;14;14;14;14;
14;14;14;14;14;14;14;14;14;14;
15;15;15;15;15;15;15;15;15;15;
15;15;15;15;15;15;15;15;15;15;
15;15;15;15;15;15;15;15;15;15;
15;15;15;15;15;15;15;15;15;15;
15;15;15;15;16;16;16;16;16;16;
16;16;16;16;16;16;16;16;16;16;
16;16;16;16;16;16;16;16;16;16;
16;16;16;16;16;16;16;16;16;16;
16;16;16;16;16;16;16;16;17;17;
17;17;17;17;17;17;17;17;17;17;
17;17;17;17;17;17;17;17;17;17;
17;17;17;17;17;17;17;17;17;17;
17;17;17;17;17;17;17;17;17;17;
17;17;18;18;18;18;18;18;18;18;
18;18;18;18;18;18;18;18;18;18;
18;18;18;18;18;18;18;18;18;18;
18;18;18;18;18;18;18;18;18;18;
18;18;18;18;18;18;19;19;19;19;
19;19;19;19;19;19;19;19;19;19;
19;19;19;19;19;19;19;19;19;19;
19;19;19;19;19;19;19;19;19;19;
19;19;19;19;19;19;19;19;19;19;
20;20;20;20;20;20;20;20;20;20;
20;20;20;20;20;20;20;20;20;20;
20;20;20;20;20;20;20;20;20;20;
20;20;20;20;20;20;20;20;20;20;
20;20;20;20;21;21;21;21;21;21;
21;21;21;21;21;21;21;21;21;21;
21;21;21;21;21;21;21;21;21;21;
21;21;21;21;21;21;21;21;21;21;
21;21;21;21;21;21;21;21;22;22;
22;22;22;22;22;22;22;22;22;22;
22;22;22;22;22;22;22;22;22;22;
22;22;22;22;22;22;22;22;22;22;
22;22;22;22;22;22;22;22;22;22;
22;22;23;23;23;23;23;23;23;23;
23;23;23;23;23;23;23;23;23;23;
23;23;23;23;23;23;23;23;23;23;
23;23;23;23;23;23;23;23;23;23;
23;23;23;23;23;23;24;24;24;24;
24;24;24;24;24;24;24;24;24;24;
24;24;24;24;24;24;24;24;24;24;
24;24;24;24;24;24;24;24;24;24;
24;24;24;24;24;24;24;24;24;24;
};
};
int_Data @["epoch"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItemBase;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2666666805744171;
val_type_fixed=0;
};
};
name="epoch";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[1100] 0;0;0;0;1;1;1;1;2;2;
2;2;3;3;3;3;4;4;4;4;
5;5;5;5;6;6;6;6;7;7;
7;7;8;8;8;8;9;9;9;9;
10;10;10;10;0;0;0;0;1;1;
1;1;2;2;2;2;3;3;3;3;
4;4;4;4;5;5;5;5;6;6;
6;6;7;7;7;7;8;8;8;8;
9;9;9;9;10;10;10;10;0;0;
0;0;1;1;1;1;2;2;2;2;
3;3;3;3;4;4;4;4;5;5;
5;5;6;6;6;6;7;7;7;7;
8;8;8;8;9;9;9;9;10;10;
10;10;0;0;0;0;1;1;1;1;
2;2;2;2;3;3;3;3;4;4;
4;4;5;5;5;5;6;6;6;6;
7;7;7;7;8;8;8;8;9;9;
9;9;10;10;10;10;0;0;0;0;
1;1;1;1;2;2;2;2;3;3;
3;3;4;4;4;4;5;5;5;5;
6;6;6;6;7;7;7;7;8;8;
8;8;9;9;9;9;10;10;10;10;
0;0;0;0;1;1;1;1;2;2;
2;2;3;3;3;3;4;4;4;4;
5;5;5;5;6;6;6;6;7;7;
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6;6;6;6;7;7;7;7;8;8;
8;8;9;9;9;9;10;10;10;10;
};
};
int_Data @["trial"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItemBase;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2666666805744171;
val_type_fixed=0;
};
};
name="trial";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
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0;1;2;3;0;1;2;3;0;1;
2;3;0;1;2;3;0;1;2;3;
};
};
String_Data @["trial_name"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_73";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2666666805744171;
val_type_fixed=0;
};
};
name="trial_name";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
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0;0;1.6396344;0;0;0;0;0;0;0;
0;0;0;0;0;1.685771;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
1.3627989;0;0.29579818;0;0;0;0;1.9748722;0;1.0040085;
0;0;0;0;1.9802531;1.9806778;0.90905821;1.9805551;0.89332616;1.9825155;
0.7320931;1.9798163;1.9791253;0;0;0.52577996;1.9815524;0;0.70801616;0;
1.9637372;1.0662836;0.29171032;0.42090333;1.9539844;0.98375845;1.964601;0.26952979;1.0116061;0;
0.8407557;0.93357646;0.98000568;0.94515574;0.62979394;0.72362423;1.3186498;0;0.78698123;1.058659;
0.3627049;1.9776851;0;0;0.93569541;0.75045705;1.973475;1.9796369;0;0;
1.9784286;1.9820309;1.9807314;0;0;1.9778707;0;1.9818881;1.974736;0.81155169;
0;1.9801605;1.9807246;0;1.9739385;0;0;1.9544797;0;1.9741969;
0;1.9820273;0;1.9804938;1.8459011;0;1.9743159;0;0;1.9697158;
0.80593884;0;0;0;0;1.9815544;0.91461658;0;0;0;
1.9764812;1.9785516;1.9814811;1.979717;0;1.0912124;1.9798;1.9770032;1.6943219;0.5939703;
1.966116;0;0.60986114;1.9717035;0.82408965;1.9803602;0;1.972271;0.89167917;0;
0.78436732;0.9087323;0.83627152;0;0.39500916;0.25121453;1.1243052;0.40158552;0.86634576;0.54196888;
1.9646468;0.28842759;0;0.59348452;0.90268248;1.225915;0.76489389;1.9671223;0;0.38808328;
0.9636929;1.0492399;0;0.9226011;0;1.9806767;1.9829721;1.9822836;0;1.9825101;
1.9784757;1.9813578;1.9806633;1.981566;0;0;0;0;1.9808481;1.9820366;
1.9700935;0;1.9828875;1.9807298;0;1.9801228;0;1.9822149;0;1.9821535;
0;1.9761542;0;1.9807541;1.9800752;0;1.9758531;0;1.980499;0;
1.5018991;1.9751363;0;1.9792562;0;1.6777246;1.2450498;1.9738176;1.979455;0;
0;1.8474307;0;0;1.9717635;0;0;0;1.9826984;0;
0;0;1.9781997;0;0.26347107;0;0;0;0;0;
1.7131939;0;0;0.80702418;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;1.9727447;
0;0;1.9817734;1.9808891;0;0;0;1.9780228;0;1.9789393;
0.37714061;0.29799235;0;0;0;0;1.9807901;0;1.1174591;1.9727298;
0;0;1.9812781;0;0;0.76513678;1.9810739;0;0;0.9054023;
0;1.0632391;0;1.9788024;0;0;1.9254396;0;1.9781144;1.9185665;
0;0;1.9005085;0;0;0.83399773;0;1.9824893;1.9828495;1.9820628;
1.9813991;1.9805734;1.9824835;1.9823644;0;0.3003431;1.950747;1.9803835;0.65227079;1.9816678;
0.47018865;1.98107;1.7128286;0.90648305;1.9696517;0;1.981719;0;0.81615663;0;
0;0.26468703;0.88555425;0;0;0.39374435;0;0.77472031;0.42278996;0.38371745;
0;0;0.9546926;1.9796207;0;0.58494008;1.9807832;0;0.35661912;0.72558951;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;1.9811239;0;0;0;0;
0;1.9828055;0;1.9832211;0;0;0;0;1.9820631;0;
0;0;0;1.9816592;0;0;1.9827397;0;0;0;
1.9825534;0.4116303;0;1.9830801;0;0;0;0;0;1.9822212;
0;0;0;1.9825735;0;0;1.9827844;0;0;0;
1.9826081;0;0;1.9829204;0;0;0;0;0;1.9828262;
1.9821532;0;0;0;0;1.9805779;0;0;0;1.9794012;
0;0;0.77641249;0;0;0;0;0;1.8758166;0;
0;1.9513004;0;0;0;0;1.0265657;0;0;0;
0.36111999;0;1.9697809;0;1.9830534;1.9676421;0;1.9803152;0.6806308;1.9810315;
0;1.9789833;0.83504927;1.9752264;1.0451612;0;0;0.31337661;1.231461;1.9677312;
0;0;0.3325716;0.26211053;0;0;1.6328082;0;1.0898209;0;
0.85967237;0.38569289;0;0;0;0;0;0.86198705;0;0.39511922;
0.76233262;0;0;1.9309186;1.1368728;0;1.9824016;0.28427994;1.4993562;1.9837691;
1.9820428;0.82340074;1.9825978;0;1.9832478;0;1.9831281;1.9809732;1.9836426;1.9822681;
0;0.89026541;1.9825721;0;0.86605138;1.9826487;1.2062835;1.9809496;1.9821808;0;
1.9745418;1.9823664;0.62582314;1.0443763;1.9822305;0.31065288;1.9776348;0.75765014;1.9818664;0;
1.0030169;1.9687777;0;1.981883;0.63046014;0;1.9280211;1.3094795;1.9822261;0;
0;1.9828277;0;0;0;0;1.9819386;0;0;0;
1.98312;0;1.9817106;0;0;0;0;0;0;1.9827533;
1.98142;0;0;0.28275195;1.981564;0;0;0;0;1.9821568;
0;0;0;1.981988;0;0.77968287;0;0.88445234;0;1.9828126;
0.96508902;0;1.9817722;0;0;0;1.9826152;0;0;0;
1.9812348;0;1.0935234;0;1.9798636;0;0;1.979717;0;0;
0;1.2037888;0;1.9824002;0;0;0;1.9800061;1.9805386;0;
0;0;1.9771495;0;0;0;0;1.2613473;0;0;
0.86832255;0;1.9797871;0;0;1.0557308;0;1.5747266;1.4158909;1.9776326;
0;0;0;0;0;1.9747145;0;0;1.9802791;1.9746568;
0;1.9686337;0;1.9818077;0;0;0;1.980929;0.68864858;0;
0;0;0;0;0;1.9818451;0;0;0;0;
0;0;0;0;0;0;1.970612;1.9812236;0;0;
1.9737523;0;1.9835078;0;1.9810998;0;0;0;0.26398751;1.983085;
1.9807235;1.9823238;0;0;0;0;1.9828945;0;0;0;
1.9818954;0;0;0;1.9819126;0;1.9829795;0;0;0;
1.9817636;0;0;0;1.9824262;0.44470382;0;0;0;0;
1.9819133;0;0;1.9818604;0;0;0;1.9809805;1.9826937;1.9821889;
1.981107;1.9822135;1.9829512;1.9824405;0;1.9783568;1.9820049;0.3632822;1.980829;0.4039323;
0;1.9801803;0;1.9548154;1.9103482;1.1110712;1.0584505;0;1.980927;0.85029972;
0;0.45029572;1.9783273;0.33223438;0;0.64858103;0;0.92627776;0.81619215;0.60473394;
0.87223887;0.98093885;1.0420434;0;0.73186213;0.72915393;0.92624938;1.0626855;0.32333234;0;
0;0;1.9805708;1.9804473;1.9809699;1.9774375;0;1.9798098;0;1.9704713;
1.9749532;0;0;0;0;0;0;0;0;1.9708852;
0;0;0;0;0;0;0;0.29862228;0;0;
0;0;0;1.9712869;0;0;0;0;1.4138267;0;
0;0;0.33053163;0;1.9827497;0;0;1.9801084;1.9734645;0;
1.9790741;0;0;1.9799302;0;0;0;1.9805334;0;0;
0;0;0.2724781;1.975863;0;0;0;0.60217941;0;0;
0;0.92541206;0;0;1.9663504;0;0;0;0;0.62270343;
0;0.41838145;0;0.29699999;0;0;0;0;0;1.3214476;
1.981984;0;0;1.1695337;0;0.26273963;0;1.9593806;0;1.9819279;
0;0;1.9797132;0.35448283;0;1.5077307;0;1.8388309;0.30490103;0;
0.73987412;1.9820051;0;0;0.70894128;0.87616324;0;0;0;0;
0;0.32818833;0;0.7433542;0;0;0.33883378;0.25784218;1.9778329;0;
0.34705469;0;0;0;0;1.9803119;0;1.9819402;0;1.980258;
0;0;1.9786543;0;1.9722072;1.9826101;0;0;0;1.9784176;
0;1.9800906;1.384624;1.9739162;0;0;1.199195;0;1.9655218;0;
0;0;1.9820362;0;1.0251167;1.9789768;0;0;0.60845846;0;
0;0.67971563;0;1.9792511;0;1.7529769;0;1.9823217;0.90310276;1.9785874;
0;0;1.9805657;1.9806662;0;1.9824312;1.9765766;0;0;1.9818871;
1.9750972;0;0;0;1.9754119;1.9780346;0.2843715;1.9807863;0;0;
0;0;1.9729073;1.2320673;0;1.9783623;0;1.9727962;0;1.9761672;
0;0.26964697;0.90261829;0;1.9763267;0;1.9796898;0.82891262;0;0;
};
};
};
data_flags=SAVE_ROWS|AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
row_indexes {
name="row_indexes";
[1100] 0;1;2;3;4;5;6;7;8;9;
10;11;12;13;14;15;16;17;18;19;
20;21;22;23;24;25;26;27;28;29;
30;31;32;33;34;35;36;37;38;39;
40;41;42;43;44;45;46;47;48;49;
50;51;52;53;54;55;56;57;58;59;
60;61;62;63;64;65;66;67;68;69;
70;71;72;73;74;75;76;77;78;79;
80;81;82;83;84;85;86;87;88;89;
90;91;92;93;94;95;96;97;98;99;
100;101;102;103;104;105;106;107;108;109;
110;111;112;113;114;115;116;117;118;119;
120;121;122;123;124;125;126;127;128;129;
130;131;132;133;134;135;136;137;138;139;
140;141;142;143;144;145;146;147;148;149;
150;151;152;153;154;155;156;157;158;159;
160;161;162;163;164;165;166;167;168;169;
170;171;172;173;174;175;176;177;178;179;
180;181;182;183;184;185;186;187;188;189;
190;191;192;193;194;195;196;197;198;199;
200;201;202;203;204;205;206;207;208;209;
210;211;212;213;214;215;216;217;218;219;
220;221;222;223;224;225;226;227;228;229;
230;231;232;233;234;235;236;237;238;239;
240;241;242;243;244;245;246;247;248;249;
250;251;252;253;254;255;256;257;258;259;
260;261;262;263;264;265;266;267;268;269;
270;271;272;273;274;275;276;277;278;279;
280;281;282;283;284;285;286;287;288;289;
290;291;292;293;294;295;296;297;298;299;
300;301;302;303;304;305;306;307;308;309;
310;311;312;313;314;315;316;317;318;319;
320;321;322;323;324;325;326;327;328;329;
330;331;332;333;334;335;336;337;338;339;
340;341;342;343;344;345;346;347;348;349;
350;351;352;353;354;355;356;357;358;359;
360;361;362;363;364;365;366;367;368;369;
370;371;372;373;374;375;376;377;378;379;
380;381;382;383;384;385;386;387;388;389;
390;391;392;393;394;395;396;397;398;399;
400;401;402;403;404;405;406;407;408;409;
410;411;412;413;414;415;416;417;418;419;
420;421;422;423;424;425;426;427;428;429;
430;431;432;433;434;435;436;437;438;439;
440;441;442;443;444;445;446;447;448;449;
450;451;452;453;454;455;456;457;458;459;
460;461;462;463;464;465;466;467;468;469;
470;471;472;473;474;475;476;477;478;479;
480;481;482;483;484;485;486;487;488;489;
490;491;492;493;494;495;496;497;498;499;
500;501;502;503;504;505;506;507;508;509;
510;511;512;513;514;515;516;517;518;519;
520;521;522;523;524;525;526;527;528;529;
530;531;532;533;534;535;536;537;538;539;
540;541;542;543;544;545;546;547;548;549;
550;551;552;553;554;555;556;557;558;559;
560;561;562;563;564;565;566;567;568;569;
570;571;572;573;574;575;576;577;578;579;
580;581;582;583;584;585;586;587;588;589;
590;591;592;593;594;595;596;597;598;599;
600;601;602;603;604;605;606;607;608;609;
610;611;612;613;614;615;616;617;618;619;
620;621;622;623;624;625;626;627;628;629;
630;631;632;633;634;635;636;637;638;639;
640;641;642;643;644;645;646;647;648;649;
650;651;652;653;654;655;656;657;658;659;
660;661;662;663;664;665;666;667;668;669;
670;671;672;673;674;675;676;677;678;679;
680;681;682;683;684;685;686;687;688;689;
690;691;692;693;694;695;696;697;698;699;
700;701;702;703;704;705;706;707;708;709;
710;711;712;713;714;715;716;717;718;719;
720;721;722;723;724;725;726;727;728;729;
730;731;732;733;734;735;736;737;738;739;
740;741;742;743;744;745;746;747;748;749;
750;751;752;753;754;755;756;757;758;759;
760;761;762;763;764;765;766;767;768;769;
770;771;772;773;774;775;776;777;778;779;
780;781;782;783;784;785;786;787;788;789;
790;791;792;793;794;795;796;797;798;799;
800;801;802;803;804;805;806;807;808;809;
810;811;812;813;814;815;816;817;818;819;
820;821;822;823;824;825;826;827;828;829;
830;831;832;833;834;835;836;837;838;839;
840;841;842;843;844;845;846;847;848;849;
850;851;852;853;854;855;856;857;858;859;
860;861;862;863;864;865;866;867;868;869;
870;871;872;873;874;875;876;877;878;879;
880;881;882;883;884;885;886;887;888;889;
890;891;892;893;894;895;896;897;898;899;
900;901;902;903;904;905;906;907;908;909;
910;911;912;913;914;915;916;917;918;919;
920;921;922;923;924;925;926;927;928;929;
930;931;932;933;934;935;936;937;938;939;
940;941;942;943;944;945;946;947;948;949;
950;951;952;953;954;955;956;957;958;959;
960;961;962;963;964;965;966;967;968;969;
970;971;972;973;974;975;976;977;978;979;
980;981;982;983;984;985;986;987;988;989;
990;991;992;993;994;995;996;997;998;999;
1000;1001;1002;1003;1004;1005;1006;1007;1008;1009;
1010;1011;1012;1013;1014;1015;1016;1017;1018;1019;
1020;1021;1022;1023;1024;1025;1026;1027;1028;1029;
1030;1031;1032;1033;1034;1035;1036;1037;1038;1039;
1040;1041;1042;1043;1044;1045;1046;1047;1048;1049;
1050;1051;1052;1053;1054;1055;1056;1057;1058;1059;
1060;1061;1062;1063;1064;1065;1066;1067;1068;1069;
1070;1071;1072;1073;1074;1075;1076;1077;1078;1079;
1080;1081;1082;1083;1084;1085;1086;1087;1088;1089;
1090;1091;1092;1093;1094;1095;1096;1097;1098;1099;
};
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
DataTable @["EpochOutputData"] {
name="EpochOutputData";
desc=;
data {
name="data";
el_typ=int_Data;
el_def=0;
int_Data @["batch"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_81";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.234299510717392;
val_type_fixed=0;
};
};
name="batch";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=97;
ar {
name="ar";
[0] };
};
int_Data @["epoch"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_82";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.234299510717392;
val_type_fixed=0;
};
};
name="epoch";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=97;
ar {
name="ar";
[0] };
};
float_Data @["avg_sse"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_83";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.234299510717392;
val_type_fixed=0;
};
};
name="avg_sse";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=97;
ar {
name="ar";
[0] };
};
float_Data @["cnt_err"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_84";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.234299510717392;
val_type_fixed=0;
};
};
name="cnt_err";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=97;
ar {
name="ar";
[0] };
};
float_Data @["avg_ext_rew"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_85";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.234299510717392;
val_type_fixed=0;
};
};
name="avg_ext_rew";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=97;
ar {
name="ar";
[0] };
};
float_Data @["Output_sse"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_86";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.234299510717392;
val_type_fixed=0;
};
};
name="Output_sse";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=97;
ar {
name="ar";
[0] };
};
};
data_flags=SAVE_ROWS|AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
row_indexes {
name="row_indexes";
[0] };
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
DataTable @["TrnTestEpochOutputData"] {
name="TrnTestEpochOutputData";
desc=;
data {
name="data";
el_typ=int_Data;
el_def=0;
int_Data @["batch"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItemBase;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.1502347439527512;
val_type_fixed=0;
};
};
name="batch";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=64;
ar {
name="ar";
[275] 0;0;0;0;0;0;0;0;0;0;
0;1;1;1;1;1;1;1;1;1;
1;1;2;2;2;2;2;2;2;2;
2;2;2;3;3;3;3;3;3;3;
3;3;3;3;4;4;4;4;4;4;
4;4;4;4;4;5;5;5;5;5;
5;5;5;5;5;5;6;6;6;6;
6;6;6;6;6;6;6;7;7;7;
7;7;7;7;7;7;7;7;8;8;
8;8;8;8;8;8;8;8;8;9;
9;9;9;9;9;9;9;9;9;9;
10;10;10;10;10;10;10;10;10;10;
10;11;11;11;11;11;11;11;11;11;
11;11;12;12;12;12;12;12;12;12;
12;12;12;13;13;13;13;13;13;13;
13;13;13;13;14;14;14;14;14;14;
14;14;14;14;14;15;15;15;15;15;
15;15;15;15;15;15;16;16;16;16;
16;16;16;16;16;16;16;17;17;17;
17;17;17;17;17;17;17;17;18;18;
18;18;18;18;18;18;18;18;18;19;
19;19;19;19;19;19;19;19;19;19;
20;20;20;20;20;20;20;20;20;20;
20;21;21;21;21;21;21;21;21;21;
21;21;22;22;22;22;22;22;22;22;
22;22;22;23;23;23;23;23;23;23;
23;23;23;23;24;24;24;24;24;24;
24;24;24;24;24; };
};
int_Data @["epoch"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItemBase;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.1502347439527512;
val_type_fixed=0;
};
};
name="epoch";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=64;
ar {
name="ar";
[275] 0;1;2;3;4;5;6;7;8;9;
10;0;1;2;3;4;5;6;7;8;
9;10;0;1;2;3;4;5;6;7;
8;9;10;0;1;2;3;4;5;6;
7;8;9;10;0;1;2;3;4;5;
6;7;8;9;10;0;1;2;3;4;
5;6;7;8;9;10;0;1;2;3;
4;5;6;7;8;9;10;0;1;2;
3;4;5;6;7;8;9;10;0;1;
2;3;4;5;6;7;8;9;10;0;
1;2;3;4;5;6;7;8;9;10;
0;1;2;3;4;5;6;7;8;9;
10;0;1;2;3;4;5;6;7;8;
9;10;0;1;2;3;4;5;6;7;
8;9;10;0;1;2;3;4;5;6;
7;8;9;10;0;1;2;3;4;5;
6;7;8;9;10;0;1;2;3;4;
5;6;7;8;9;10;0;1;2;3;
4;5;6;7;8;9;10;0;1;2;
3;4;5;6;7;8;9;10;0;1;
2;3;4;5;6;7;8;9;10;0;
1;2;3;4;5;6;7;8;9;10;
0;1;2;3;4;5;6;7;8;9;
10;0;1;2;3;4;5;6;7;8;
9;10;0;1;2;3;4;5;6;7;
8;9;10;0;1;2;3;4;5;6;
7;8;9;10;0;1;2;3;4;5;
6;7;8;9;10; };
};
float_Data @["avg_sse"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_85";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.1502347439527512;
val_type_fixed=0;
};
};
name="avg_sse";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=64;
ar {
name="ar";
[275] 0.98862904;0.28612643;0.14454098;0;0.43543702;0.50232571;0.3640728;0.24798357;0.27205533;0.10277869;
0.17137444;0.99093211;1.4856459;0.90938413;0.49526483;0.49326754;0.26449192;0.2601766;0.31865689;0.32383049;
0.32773328;0.28812212;0.39596814;0.40990859;0;0;0.42144275;0;0;0;
0.41464928;0.49371806;0.25100213;0.99023271;1.4413637;1.1727586;0.62683308;0.93450928;0.91258913;0.81143427;
0.92487335;0.66801697;1.0465076;0.42153811;0.98827797;1.4852977;0.98993969;1.191612;0.98866576;0.98216915;
0.99063027;0.95505428;0.6939137;0.4953886;0.22865415;1.9790578;1.2620039;1.063602;1.3465036;0.71598756;
0.63234282;0.54302859;0.91534728;0.68052047;0.78002483;0.7338835;1.4864831;1.4855859;0.99055731;0.99072117;
1.4834278;0.99058443;0.98957694;0.99020731;0.98908806;1.3640729;1.224148;0.95672143;0.49294087;0.49567461;
0.49454993;0.065867767;0.42829847;0.20175605;0;0;0;0.49318618;0.99066561;0.98924053;
0.16878325;0.49519753;0.77254725;0.68660372;0.72161901;0.76051039;0.4813599;0.97417021;0.68362653;1.4868504;
1.9817052;1.0578684;1.2712994;1.1472409;0.69946891;0.28756031;0.29211617;0.20162685;0.87981331;0.76574796;
0;0;0;0;0;0;0;0;0;0;
0;0.49528098;0.49570137;0.49580526;0.49551576;0.49541479;0.49568492;0.59854591;0.49577004;0.49555531;
0.49564338;0.4956961;0.49565202;0.4957301;0.49570656;0.49553829;0.49514449;0.49485031;0.19410312;0.46895415;
0.4878251;0.25664142;0.090279996;1.4801191;1.1604943;1.1973147;0.33963448;0.79979807;0.14867052;0.68065727;
0.31134132;0.21549676;0.28936297;0.76694787;1.4374517;1.1970103;1.4868373;1.214044;1.207818;1.2923534;
1.4067769;1.2570422;1.2384152;0.65308583;1.3049316;0.49570692;0.49548465;0.49577999;0.49542764;0.49568832;
0.56604302;0.49539101;0.49553919;0.69041771;0.71681625;0.73671532;0.49565381;0.4953087;0.76834679;0.49492925;
0.79654723;0.49500152;0.49513465;0.49428737;0.31533682;0.71202743;0.65761435;0.84838092;0.49367863;0.98873401;
0.98761034;0.49523225;0.17216215;0.49546129;0;0;0.98795891;0.49343807;0.99115193;0.56176811;
0.99076182;0.49572363;0.49547386;0.49547815;0.49574488;0.4954409;0.6067825;0.49547833;0.4954651;1.4864657;
1.9821781;1.0809109;1.0912354;1.2440587;0.97241926;0.69021434;0.3937147;0.81852597;0.62576485;0.57806683;
0.99025452;1.4845543;0.98635614;0;0.49272129;0;0.07465557;0;0.49282172;0.35345668;
0.082632907;0.99071455;0.98813462;0.49498254;0.49513334;0.56208527;0.15054485;0.23135301;0.49158761;0.15567586;
0.17884536;0;0.82585788;0.35806835;0.98532712;0.58354902;0.83664042;0.75669503;0.39627612;0;
0.26788563;0.149169;0.58122188;0.49507797;0.99054956;0.49466357;0.98870432;0.98962706;0.83963501;0.79117918;
0.49550906;0.75102341;0.32204354;0.93305701;1.2160029;0.99030793;0.98975194;0.98924607;0.9883616;0.56628942;
0.80124366;0.98778963;0.56145352;0.71973622;0.70215058; };
};
float_Data @["avg_ext_rew"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_86";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.1502347439527512;
val_type_fixed=0;
};
};
name="avg_ext_rew";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=64;
ar {
name="ar";
[275] 0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0;0;0;0;0;0;
0;0;0;0;0; };
};
float_Data @["avg_cycles"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_87";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.1502347439527512;
val_type_fixed=0;
};
};
name="avg_cycles";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=64;
ar {
name="ar";
[275] 100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100;100;100;100;100;100;
100;100;100;100;100; };
};
float_Data @["cnt_err"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_88";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.1502347439527512;
val_type_fixed=0;
};
};
name="cnt_err";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=64;
ar {
name="ar";
[275] 2;1;0;0;1;2;0;0;1;0;
0;2;3;2;1;1;1;1;1;1;
1;1;1;1;0;0;1;0;0;0;
1;1;1;2;4;2;1;2;2;2;
4;1;3;2;2;3;2;3;2;2;
2;2;2;1;1;4;3;2;3;2;
3;1;2;2;2;3;3;3;2;2;
3;2;2;2;2;3;3;2;1;1;
1;0;1;1;0;0;0;1;2;2;
0;1;2;2;2;2;1;2;2;3;
4;2;2;3;2;1;1;0;2;1;
0;0;0;0;0;0;0;0;0;0;
0;1;1;1;1;1;1;1;1;1;
1;1;1;1;1;1;1;1;1;1;
1;1;0;3;2;3;1;2;0;2;
1;1;1;2;3;3;3;3;3;3;
3;3;3;1;3;1;1;1;1;1;
1;1;1;2;2;2;1;1;2;1;
2;1;1;1;1;2;2;2;1;2;
2;1;0;1;0;0;2;1;2;1;
2;1;1;1;1;1;1;1;1;3;
4;2;2;3;3;1;1;3;1;2;
2;3;2;0;1;0;0;0;1;1;
0;2;2;1;1;1;0;1;1;0;
0;0;2;1;2;1;2;1;1;0;
0;0;1;1;2;1;2;2;2;2;
1;2;0;2;3;2;2;2;2;1;
2;2;1;2;2; };
};
};
data_flags=SAVE_ROWS|AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
row_indexes {
name="row_indexes";
[275] 0;1;2;3;4;5;6;7;8;9;
10;11;12;13;14;15;16;17;18;19;
20;21;22;23;24;25;26;27;28;29;
30;31;32;33;34;35;36;37;38;39;
40;41;42;43;44;45;46;47;48;49;
50;51;52;53;54;55;56;57;58;59;
60;61;62;63;64;65;66;67;68;69;
70;71;72;73;74;75;76;77;78;79;
80;81;82;83;84;85;86;87;88;89;
90;91;92;93;94;95;96;97;98;99;
100;101;102;103;104;105;106;107;108;109;
110;111;112;113;114;115;116;117;118;119;
120;121;122;123;124;125;126;127;128;129;
130;131;132;133;134;135;136;137;138;139;
140;141;142;143;144;145;146;147;148;149;
150;151;152;153;154;155;156;157;158;159;
160;161;162;163;164;165;166;167;168;169;
170;171;172;173;174;175;176;177;178;179;
180;181;182;183;184;185;186;187;188;189;
190;191;192;193;194;195;196;197;198;199;
200;201;202;203;204;205;206;207;208;209;
210;211;212;213;214;215;216;217;218;219;
220;221;222;223;224;225;226;227;228;229;
230;231;232;233;234;235;236;237;238;239;
240;241;242;243;244;245;246;247;248;249;
250;251;252;253;254;255;256;257;258;259;
260;261;262;263;264;265;266;267;268;269;
270;271;272;273;274; };
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
DataTable @["CycleOutputData"] {
name="CycleOutputData";
desc=;
data {
name="data";
el_typ=int_Data;
el_def=0;
int_Data @["batch"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_82";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="batch";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["epoch"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_83";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="epoch";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["trial"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_84";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="trial";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["trial_name"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_87";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="trial_name";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
String_Data @["group_name"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_88";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="group_name";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["phase_no"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_85";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="phase_no";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
int_Data @["cycle"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_86";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="cycle";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
float_Data @["sse"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_89";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="sse";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
float_Data @["ext_rew"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_90";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="ext_rew";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
float_Data @["STN_acts_avg"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_91";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="STN_acts_avg";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
float_Data @["Motor__acts_avg"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_92";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="Motor__acts_avg";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
float_Data @["Thalam_acts_avg"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_93";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="Thalam_acts_avg";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
float_Data @["GP_Int_acts_avg"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_94";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="GP_Int_acts_avg";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
float_Data @["GP_Ext_acts_avg"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_95";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="GP_Ext_acts_avg";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
float_Data @["Output_act"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_96";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="Output_act";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=1;
cell_geom{ 2;1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[2] ;; };
width=0;
};
float_Data @["Output_units_0_act"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_97";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
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};
name="Output_units_0_act";
col_flags=MARK|PIN|SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
};
};
data_flags=AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
};
DataTable_Group @.gp["AnalysisData"] {
name="AnalysisData";
el_typ=DataTable;
el_def=0;
save_tables=1;
DataTable @["EpochOutputData_Group"] {
name="EpochOutputData_Group";
desc=;
data {
name="data";
el_typ=int_Data;
el_def=0;
int_Data @["epoch_group"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_82";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["NARROW"] {
name="NARROW";
value 1 0=1;
val_type_fixed=0;
};
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="epoch_group";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[5] 0;1;2;3;4; };
};
float_Data @["cnt_err_mean"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_83";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="cnt_err_mean";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[5] 5.8000002;4.8800001;4.1599998;3.3199999;2.4000001; };
};
float_Data @["cnt_err_sem"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_84";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="cnt_err_sem";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[5] 0.12951522;0.13276222;0.14740773;0.14305425;0.12181424; };
};
float_Data @["avg_sse_mean"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_85";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="avg_sse_mean";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[5] 0.79276961;0.62282288;0.52733159;0.43509698;0.29532102; };
};
float_Data @["Output_sse_mean"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_86";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_wd"] {
name="view_panel_wd";
value 6 0=0.2347417771816254;
val_type_fixed=0;
};
};
name="Output_sse_mean";
col_flags=SAVE_DATA;
is_matrix=0;
cell_geom{ 1; };
calc_expr {
expr=;
};
dim_names {
name="dim_names";
[0] };
width=0;
ar {
name="ar";
[5] 0.71948797;0.66363496;0.29635888;0.52278715;0.17648138; };
};
};
data_flags=SAVE_ROWS|AUTO_CALC;
auto_load=NO_AUTO_LOAD;
auto_load_file=;
row_height=0;
keygen 4 0=0;
row_indexes {
name="row_indexes";
[5] 0;1;2;3;4; };
last_sort_spec {
name="last_sort_spec";
ops {
name="ops";
el_typ=DataSortEl;
el_def=0;
};
};
control_panel_cells {
name="control_panel_cells";
el_typ=DataTableCell;
el_def=0;
};
};
};
};
programs {
name="programs";
el_typ=Program;
el_def=0;
tags=;
desc=;
debug_mode=0;
Program_Group @.gp["LeabraAll_Std"] {
name="LeabraAll_Std";
el_typ=Program;
el_def=0;
tags=;
desc="The full set of programs for training a standard Leabra network";
debug_mode=0;
Program @["LeabraBatch"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"].doc$$;
};
};
name="LeabraBatch";
short_nm="Batch";
tags="Leabra, Std";
desc="Iterate over training runs (a batch of training runs) -- just a simple loop that calls training program";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to operate on -- updates batch counter on network and passes it to train program";
init_from=NULL;
};
ProgVar @["input_data"] {
name="input_data";
var_type=T_Object;
object_type=DataTable;
object_val=.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="datatable with training patterns -- not used by this program, but passed to train program";
init_from=NULL;
};
ProgVar @["max_batch"] {
name="max_batch";
var_type=T_Int;
int_val=25;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="maximum number of batch runs to perform";
init_from=NULL;
};
ProgVar @["TrainWP"] {
name="TrainWP";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="datatable with training patterns";
init_from=NULL;
};
ProgVar @["TestWP"] {
name="TestWP";
var_type=T_Object;
object_type=DataTable;
object_val=.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["TestWP_Optimal"]$$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["epoch_out"] {
name="epoch_out";
var_type=T_Object;
object_type=DataTable;
object_val=.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["EpochOutputData"]$$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["batch"] {
name="batch";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="batch counter";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initializes local batch counter and batch field on network";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: batch";
pre_compile_code_string="Net Counter Init: batch";
network_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"].args["network"]$$;
local_ctr_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"].vars["batch"]$$;
counter=Network::batch;
update_after=0;
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initializes local batch counter and batch field on network";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: batch";
pre_compile_code_string="Net Counter Init: batch";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"].vars["batch"]$;
counter=Network::batch;
update_after=0;
};
WhileLoop @[1] {
desc="the main loop over training runs";
flags=CAN_REVERT_TO_CODE;
code_string="while (batch < max_batch)";
pre_compile_code_string="while (batch < max_batch)";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
ProgramCall @[0] {
desc="run the training program -- sets the network and input_data args";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraTrain(network, input_data, TrainWP, true, TestWP)";
pre_compile_code_string="LeabraTrain(network, input_data, TrainWP, true, TestWP)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="input_data";
required=1;
def_val=;
prev_expr=;
expr {
expr="input_data";
};
};
ProgArg @[2] {
arg_type=DataTable;
type="DataTable*";
name="TrainWP";
required=1;
def_val=;
prev_expr=;
expr {
expr="TrainWP";
};
};
ProgArg @[3] {
arg_type=bool;
type="bool";
name="no_prompts";
required=1;
def_val=;
prev_expr=;
expr {
expr="true";
};
};
ProgArg @[4] {
arg_type=DataTable;
type="DataTable*";
name="TestWP";
required=1;
def_val=;
prev_expr=;
expr {
expr="TestWP";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"]$$;
targ_ld_init="*LeabraTrain*";
};
NetCounterIncr @[1] {
desc="increment the local batch counter and copy to network";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Incr: batch";
pre_compile_code_string="Net Counter Incr: batch";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"].vars["batch"]$;
counter=Network::batch;
update_after=0;
};
};
test {
expr="batch < max_batch";
};
};
DataGroupProg @[2] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Group from: src table = epoch_out dest table = ?";
pre_compile_code_string="Group from: src table = epoch_out dest table = ?";
src_data_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraBatch"].args["epoch_out"]$$;
dest_data_var=NULL;
group_spec {
name="group_spec";
ops {
name="ops";
el_typ=DataGroupEl;
el_def=0;
DataGroupEl @["epoch_GROUP_0"] {
col_name="epoch";
name="epoch_GROUP_0";
agg {name="AggregateSpec_33": op=GROUP: rel={name="Relation_33": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
};
DataGroupEl @["cnt_err_MEAN_1"] {
col_name="cnt_err";
name="cnt_err_MEAN_1";
agg {name="AggregateSpec_35": op=MEAN: rel={name="Relation_35": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
};
DataGroupEl @["cnt_err_SEM_2"] {
col_name="cnt_err";
name="cnt_err_SEM_2";
agg {name="AggregateSpec_35": op=SEM: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
};
DataGroupEl @["avg_sse_MEAN_3"] {
col_name="avg_sse";
name="avg_sse_MEAN_3";
agg {name="AggregateSpec_34": op=MEAN: rel={name="Relation_34": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
};
DataGroupEl @["Output_sse_MEAN_4"] {
col_name="Output_sse";
name="Output_sse_MEAN_4";
agg {name="AggregateSpec_37": op=MEAN: rel={name="Relation_37": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
};
};
append_agg_name=1;
};
};
PrintExpr @[3] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Print \"finished\"";
pre_compile_code_string="Print \"finished\"";
expr {
expr="\"finished\"";
};
debug=0;
};
};
step_prog=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"]$$;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraTrain"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].doc$$;
};
};
name="LeabraTrain";
short_nm="Train";
tags="Leabra, Std";
desc="A complete training run of a Leabra network: iterating over epochs until the network has learned the task";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=RndSeed;
el_def=0;
RndSeed @["rnd_seed"] {
name="rnd_seed";
rnd_seed=53668462;
};
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
DynEnumType @["RndInitType"] {
name="RndInitType";
desc=;
enums {
name=;
el_typ=DynEnumItem;
el_def=0;
DynEnumItem @["OLD_SEED"] {
name="OLD_SEED";
value=0;
desc="use stored random seed value (recreates same sequence every time)";
};
DynEnumItem @["NEW_SEED"] {
name="NEW_SEED";
value=1;
desc="generate new random seed (new sequence of random numbers)";
};
};
bits=0;
};
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to train";
init_from=NULL;
};
ProgVar @["input_data"] {
name="input_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="datatable with training patterns";
init_from=NULL;
};
ProgVar @["TrainWP"] {
name="TrainWP";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|EDIT_VAL|PGRM_ARG;
reference=0;
desc="datatable with training patterns";
init_from=NULL;
};
ProgVar @["no_prompts"] {
name="no_prompts";
var_type=T_Bool;
bool_val=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="If train is called by other programs (e.g., Batch), they should set this to true -- otherwise it is reset to false in Init";
init_from=NULL;
};
ProgVar @["TestWP"] {
name="TestWP";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["TestWP_Optimal"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["max_epoch"] {
name="max_epoch";
var_type=T_Int;
int_val=4;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="maximum number of epochs to run";
init_from=NULL;
};
ProgVar @["train_mode"] {
name="train_mode";
var_type=T_HardEnum;
int_val=1;
hard_enum_type=Network::TrainMode;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="TRAIN = update weights (learn), TEST = just record network's responses but don't learn";
init_from=NULL;
};
ProgVar @["test_mode"] {
name="test_mode";
var_type=T_HardEnum;
int_val=0;
hard_enum_type=Network::TrainMode;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="TRAIN = update weights (learn), TEST = just record network's responses but don't learn";
init_from=NULL;
};
ProgVar @["rnd_init"] {
name="rnd_init";
var_type=T_DynEnum;
dyn_enum_val {
user_data_=NULL;
enum_type=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].types["RndInitType"]$$;
value=0;
};
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="how to initialize the random numbers when the Init button is pressed";
init_from=NULL;
};
ProgVar @["epoch"] {
name="epoch";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="current epoch -- local copy, which is used to update network's epoch counter";
init_from=NULL;
};
ProgVar @["err_stopcrit"] {
name="err_stopcrit";
var_type=T_Real;
real_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="stopping criterion -- when error measure (count of trials with a non-zero error by defult)
goes <= this value, stop training (set to -1 to disable stopping criterion, and always train to max_epoch epochs)";
init_from=NULL;
};
ProgVar @["training_tonic_DA"] {
name="training_tonic_DA";
var_type=T_Real;
real_val=0.026;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="stopping criterion -- when error measure (count of trials with a non-zero error by defult)
goes <= this value, stop training (set to -1 to disable stopping criterion, and always train to max_epoch epochs)";
init_from=NULL;
};
ProgVar @["testing_tonic_DA"] {
name="testing_tonic_DA";
var_type=T_Real;
real_val=0.026;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="stopping criterion -- when error measure (count of trials with a non-zero error by defult)
goes <= this value, stop training (set to -1 to disable stopping criterion, and always train to max_epoch epochs)";
init_from=NULL;
};
ProgVar @["tonic_DA"] {
name="tonic_DA";
var_type=T_Real;
real_val=0.026;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="stopping criterion -- when error measure (count of trials with a non-zero error by defult)
goes <= this value, stop training (set to -1 to disable stopping criterion, and always train to max_epoch epochs)";
init_from=NULL;
};
ProgVar @["rnd_seed"] {
name="rnd_seed";
var_type=T_Object;
object_type=RndSeed;
object_val=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].objs["rnd_seed"]$$;
objs_ptr=1;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="random seed that is used at start of training -- if OldSeed is called";
init_from=NULL;
};
ProgVar @["train_timer"] {
name="train_timer";
var_type=T_Object;
object_type=TimeUsed;
object_val=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].train_time$$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="records time used to train network (object lives on network -- this is a pointer to it)";
init_from=NULL;
};
ProgVar @["j"] {
name="j";
var_type=T_Int;
int_val=0;
flags=NULL_CHECK|SAVE_VAL|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["i"] {
name="i";
var_type=T_Int;
int_val=1;
flags=NULL_CHECK|SAVE_VAL|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["num_intact_snc_units"] {
name="num_intact_snc_units";
var_type=T_Int;
int_val=4;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["active_da_units"] {
name="active_da_units";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["snc_size"] {
name="snc_size";
var_type=T_Int;
int_val=4;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["SNc"] {
name="SNc";
var_type=T_Object;
object_type=LeabraLayer;
object_val=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["SNc"]$$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["Go"] {
name="Go";
var_type=T_Object;
object_type=LeabraLayer;
object_val=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers.gp["Striatum"]["Go"]$$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
AssignExpr @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="no_prompts = false";
pre_compile_code_string="no_prompts = false";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["no_prompts"]$$;
expr {
expr="false";
};
};
MethodCall @[1] {
desc="check network to make sure it is ready to be run";
flags=CAN_REVERT_TO_CODE;
code_string="network->CheckConfig(false)";
pre_compile_code_string="network->CheckConfig(false)";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$$;
method=taBase::CheckConfig;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="quiet";
required=0;
def_val="false";
prev_expr=;
expr {
expr="false";
};
};
};
meth_sig="bool CheckConfig(bool quiet = false)";
meth_desc=" check the configuration of this object and all its children (defaults to no confirm of success)";
};
AssignExpr @[2] {
desc="get our pointer to the network training time object";
flags=CAN_REVERT_TO_CODE;
code_string="train_timer = network.train_time";
pre_compile_code_string="train_timer = network.train_time";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["train_timer"]$$;
expr {
expr="network.train_time";
};
};
NetCounterInit @[3] {
desc="initialize epoch counter ";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: epoch";
pre_compile_code_string="Net Counter Init: epoch";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
local_ctr_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["epoch"]$$;
counter=Network::epoch;
update_after=0;
};
If @[4] {
desc="initialize random seed (either old or new)";
flags=CAN_REVERT_TO_CODE;
code_string="if (rnd_init == OLD_SEED)";
pre_compile_code_string="if (rnd_init == OLD_SEED)";
cond {
expr="rnd_init == OLD_SEED";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="restore previous random seed (all runs produce same results)";
flags=CAN_REVERT_TO_CODE;
code_string="rnd_seed->OldSeed()";
pre_compile_code_string="rnd_seed->OldSeed()";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["rnd_seed"]$$;
method=RndSeed::OldSeed;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void OldSeed()";
meth_desc=" restore current seed to random num generator";
};
};
};
Else @[5] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="else";
pre_compile_code_string="else";
else_code {
name="else_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="new random numbers each time";
flags=CAN_REVERT_TO_CODE;
code_string="rnd_seed->NewSeed()";
pre_compile_code_string="rnd_seed->NewSeed()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["rnd_seed"]$;
method=RndSeed::NewSeed;
meth_args {
name="meth_args";
el_typ=ProgArg;
el_def=0;
};
meth_sig="void NewSeed()";
meth_desc=" set the seed to a new random value (based on time and process id)";
};
};
};
IfGuiPrompt @[6] {
desc="don't initialize weights without checking";
flags=CAN_REVERT_TO_CODE;
code_string="if (gui && \"Do you want to Initialize Network Weights\")";
pre_compile_code_string="if (gui && \"Do you want to Initialize Network Weights\")";
prompt="Do you want to Initialize Network Weights";
yes_label="Yes";
no_label="No";
yes_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="initialize network weights: could also load pre-set weights or something else here";
flags=CAN_REVERT_TO_CODE;
code_string="network->Init_Weights()";
pre_compile_code_string="network->Init_Weights()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
method=Network::Init_Weights;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Init_Weights()";
meth_desc=" Initialize the weights -- also inits acts, counters and stats";
};
PrintExpr @[1] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Print network.name << \" Weights Initialized\"";
pre_compile_code_string="Print network.name << \" Weights Initialized\"";
expr {
expr="network.name << \" Weights Initialized\"";
};
debug=0;
};
};
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
LocalVars @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="LocalVars (0 vars)";
pre_compile_code_string="LocalVars (0 vars)";
local_vars {
name="local_vars";
el_typ=ProgVar;
el_def=0;
};
};
AssignExpr @[1] {
desc="get our pointer to the network training time object";
flags=CAN_REVERT_TO_CODE;
code_string="train_timer = network.train_time";
pre_compile_code_string="train_timer = network.train_time";
result_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["train_timer"]$;
expr {
expr="network.train_time";
};
};
MethodCall @[2] {
desc="start timer to keep track of how long it takes to run entire training run";
flags=CAN_REVERT_TO_CODE;
code_string="train_timer->StartTimer(true)";
pre_compile_code_string="train_timer->StartTimer(true)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["train_timer"]$;
method=TimeUsed::StartTimer;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="reset_used";
required=0;
def_val="true";
prev_expr=;
expr {
expr="true";
};
};
};
meth_sig="void StartTimer(bool reset_used = true)";
meth_desc=" record the current time as the starting time, and optionally reset the time used information";
};
NetCounterInit @[3] {
desc="initialize epoch counter (both our local copy and network's epoch counter)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: epoch";
pre_compile_code_string="Net Counter Init: epoch";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["epoch"]$;
counter=Network::epoch;
update_after=0;
};
MemberAssign @[4] {
desc="set network's training mode to our local value";
flags=CAN_REVERT_TO_CODE;
code_string="network.train_mode = train_mode";
pre_compile_code_string="network.train_mode = train_mode";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
path="train_mode";
expr {
expr="train_mode";
};
update_after=0;
};
If @[5] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="if (no_prompts)";
pre_compile_code_string="if (no_prompts)";
cond {
expr="no_prompts";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="initialize network weights: could also load pre-set weights or something else here";
flags=CAN_REVERT_TO_CODE;
code_string="network->Init_Weights()";
pre_compile_code_string="network->Init_Weights()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
method=Network::Init_Weights;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Init_Weights()";
meth_desc=" Initialize the weights -- also inits acts, counters and stats";
};
PrintExpr @[1] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Print network.name << \" Weights Initialized\"";
pre_compile_code_string="Print network.name << \" Weights Initialized\"";
expr {
expr="network.name << \" Weights Initialized\"";
};
debug=0;
};
};
};
AssignExpr @[6] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="snc_size = SNc.units.size";
pre_compile_code_string="snc_size = SNc.units.size";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["snc_size"]$$;
expr {
expr="SNc.units.size";
};
};
MemberAssign @[7] {
desc="set network's training mode to our local value";
flags=CAN_REVERT_TO_CODE;
code_string="network.train_mode = test_mode";
pre_compile_code_string="network.train_mode = test_mode";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
path="train_mode";
expr {
expr="test_mode";
};
update_after=0;
};
AssignExpr @[8] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="active_da_units = num_intact_snc_units";
pre_compile_code_string="active_da_units = num_intact_snc_units";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["active_da_units"]$$;
expr {
expr="num_intact_snc_units";
};
};
OtherProgramVar @[9] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Vars To: program=DA_Rew_Punish set=to var_1=num_intact_snc_units var_2=active_da_units var_3=? var_4=? ";
pre_compile_code_string="Vars To: program=DA_Rew_Punish set=to var_1=num_intact_snc_units var_2=active_da_units var_3=? var_4=? ";
other_prog=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"]$$;
set_other=1;
var_1=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["num_intact_snc_units"]$;
var_2=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["active_da_units"]$;
var_3=NULL;
var_4=NULL;
};
AssignExpr @[10] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="tonic_DA = testing_tonic_DA";
pre_compile_code_string="tonic_DA = testing_tonic_DA";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["tonic_DA"]$$;
expr {
expr="testing_tonic_DA";
};
};
OtherProgramVar @[11] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Vars To: program=DA_Rew_Punish set=to var_1=tonic_DA var_2=? var_3=? var_4=? ";
pre_compile_code_string="Vars To: program=DA_Rew_Punish set=to var_1=tonic_DA var_2=? var_3=? var_4=? ";
other_prog=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"]$;
set_other=1;
var_1=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["tonic_DA"]$;
var_2=NULL;
var_3=NULL;
var_4=NULL;
};
OtherProgramVar @[12] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Vars To: program=LeabraTestEpoch set=to var_1=num_intact_snc_units var_2=? var_3=? var_4=? ";
pre_compile_code_string="Vars To: program=LeabraTestEpoch set=to var_1=num_intact_snc_units var_2=? var_3=? var_4=? ";
other_prog=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"]$$;
set_other=1;
var_1=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["num_intact_snc_units"]$;
var_2=NULL;
var_3=NULL;
var_4=NULL;
};
ProgramCall @[13] {
desc="run the epoch program (one epoch), passes our network and input_data";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraTestEpoch(network, TestWP)";
pre_compile_code_string="LeabraTestEpoch(network, TestWP)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="TestWP";
required=1;
def_val=;
prev_expr=;
expr {
expr="TestWP";
};
};
};
target=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"]$;
targ_ld_init="*LeabraTestEpoch*";
};
WhileLoop @[14] {
desc="main loop over epochs of training";
flags=CAN_REVERT_TO_CODE;
code_string="while (epoch < max_epoch)";
pre_compile_code_string="while (epoch < max_epoch)";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="set network's training mode to our local value";
flags=CAN_REVERT_TO_CODE;
code_string="network.train_mode = train_mode";
pre_compile_code_string="network.train_mode = train_mode";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
path="train_mode";
expr {
expr="train_mode";
};
update_after=0;
};
AssignExpr @[1] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="tonic_DA = training_tonic_DA";
pre_compile_code_string="tonic_DA = training_tonic_DA";
result_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["tonic_DA"]$;
expr {
expr="training_tonic_DA";
};
};
OtherProgramVar @[2] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Vars To: program=DA_Rew_Punish set=to var_1=tonic_DA var_2=? var_3=? var_4=? ";
pre_compile_code_string="Vars To: program=DA_Rew_Punish set=to var_1=tonic_DA var_2=? var_3=? var_4=? ";
other_prog=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"]$;
set_other=1;
var_1=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["tonic_DA"]$;
var_2=NULL;
var_3=NULL;
var_4=NULL;
};
ProgramCall @[3] {
desc="run the epoch program (one epoch), passes our network and input_data";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraEpoch(network, input_data)";
pre_compile_code_string="LeabraEpoch(network, input_data)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="input_data";
required=1;
def_val=;
prev_expr=;
expr {
expr="input_data";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"]$$;
targ_ld_init="*LeabraEpoch*";
};
NetCounterIncr @[4] {
desc="increment the epoch counter (locally and on network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Incr: epoch";
pre_compile_code_string="Net Counter Incr: epoch";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["epoch"]$;
counter=Network::epoch;
update_after=0;
};
IfBreak @[5] {
desc="stop if errors go below stopping criterion (note: could use sse or avg_sse here instead)";
flags=CAN_REVERT_TO_CODE;
code_string="if(network.cnt_err <= err_stopcrit) break";
pre_compile_code_string="if(network.cnt_err <= err_stopcrit) break";
cond {
expr="network.cnt_err <= err_stopcrit";
};
};
MemberAssign @[6] {
desc="set network's training mode to our local value";
flags=CAN_REVERT_TO_CODE;
code_string="network.train_mode = test_mode";
pre_compile_code_string="network.train_mode = test_mode";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].args["network"]$;
path="train_mode";
expr {
expr="test_mode";
};
update_after=0;
};
AssignExpr @[7] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="tonic_DA = testing_tonic_DA";
pre_compile_code_string="tonic_DA = testing_tonic_DA";
result_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["tonic_DA"]$;
expr {
expr="testing_tonic_DA";
};
};
OtherProgramVar @[8] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Vars To: program=DA_Rew_Punish set=to var_1=tonic_DA var_2=? var_3=? var_4=? ";
pre_compile_code_string="Vars To: program=DA_Rew_Punish set=to var_1=tonic_DA var_2=? var_3=? var_4=? ";
other_prog=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"]$;
set_other=1;
var_1=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["tonic_DA"]$;
var_2=NULL;
var_3=NULL;
var_4=NULL;
};
ProgramCall @[9] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="LeabraTestEpoch(network, TestWP)";
pre_compile_code_string="LeabraTestEpoch(network, TestWP)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="TestWP";
required=1;
def_val=;
prev_expr=;
expr {
expr="TestWP";
};
};
};
target=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"]$;
targ_ld_init="*LeabraTestEpoch*";
};
};
test {
expr="epoch < max_epoch";
};
};
MethodCall @[15] {
desc="stop the timer -- time elapsed is now recorded in this object, and can be displayed or recorded to a data table";
flags=CAN_REVERT_TO_CODE;
code_string="train_timer->EndTimer()";
pre_compile_code_string="train_timer->EndTimer()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrain"].vars["train_timer"]$;
method=TimeUsed::EndTimer;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void EndTimer()";
meth_desc=" record the current time as the ending time, and compute difference as the time used";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraEpoch"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].doc$$;
};
};
name="LeabraEpoch";
short_nm="Epoch";
tags="Leabra, Std";
desc="iterates over all of the items in a data table and calls LeabraTrial process on them";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to operate on";
init_from=NULL;
};
ProgVar @["input_data"] {
name="input_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="table of patterns to present to the network, one row at a time";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["data_loop_order"] {
name="data_loop_order";
var_type=T_HardEnum;
int_val=1;
hard_enum_type=DataLoop::Order;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="controls the order in which events (rows of the input data datatable) are presented to the network
(SEQUENTIAL, PERMUTED, RANDOM)";
init_from=NULL;
};
ProgVar @["trial"] {
name="trial";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="current trial (event) within the epoch -- increments automatically";
init_from=NULL;
};
ProgVar @["trial_mon_data"] {
name="trial_mon_data";
var_type=T_Object;
object_type=DataTable;
object_val=.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["TrialOutputData"]$$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="trial-level output data -- we reset it every epoch by default, so it just contains last epoch of data";
init_from=NULL;
};
ProgVar @["epoch_timer"] {
name="epoch_timer";
var_type=T_Object;
object_type=TimeUsed;
object_val=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].epoch_time$$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="timer to record time required to perform one epoch of processing (object is on network -- this is a pointer to it)";
init_from=NULL;
};
ProgVar @["data_loop_index"] {
name="data_loop_index";
var_type=T_Int;
int_val=6;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="index counter for the looping over items in the input_data datatable (not always the same as trial counter, depending on distributed memory computation)";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize trial counter (local variable and in the network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: trial";
pre_compile_code_string="Net Counter Init: trial";
network_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].args["network"]$$;
local_ctr_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["trial"]$$;
counter=Network::trial;
update_after=0;
};
AssignExpr @[1] {
desc="get pointer to epoch timer object on network";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer = network.epoch_time";
pre_compile_code_string="epoch_timer = network.epoch_time";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["epoch_timer"]$$;
expr {
expr="network.epoch_time";
};
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize trial counter (local variable and in the network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: trial";
pre_compile_code_string="Net Counter Init: trial";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["trial"]$;
counter=Network::trial;
update_after=0;
};
AssignExpr @[1] {
desc="get pointer to epoch timer object on network";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer = network.epoch_time";
pre_compile_code_string="epoch_timer = network.epoch_time";
result_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["epoch_timer"]$;
expr {
expr="network.epoch_time";
};
};
MethodCall @[2] {
desc="start the epoch timer to record computation time per epoch";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer->StartTimer(true)";
pre_compile_code_string="epoch_timer->StartTimer(true)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["epoch_timer"]$;
method=TimeUsed::StartTimer;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="reset_used";
required=0;
def_val="true";
prev_expr=;
expr {
expr="true";
};
};
};
meth_sig="void StartTimer(bool reset_used = true)";
meth_desc=" record the current time as the starting time, and optionally reset the time used information";
};
MethodCall @[3] {
desc="reset trial-level monitor data every epoch, so it reflects only the most recent epoch's worth of data (turn flags OFF to accumulate trial data across entire training run)";
flags=CAN_REVERT_TO_CODE;
code_string="trial_mon_data->ResetData()";
pre_compile_code_string="trial_mon_data->ResetData()";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["trial_mon_data"]$$;
method=DataTable::ResetData;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void ResetData()";
meth_desc=" deletes all the data (rows), but keeps the column structure -- this cannot be undone!";
};
NetDataLoop @[4] {
desc="iterates over the events/rows of input_data, according to data_loop_order variable";
flags=CAN_REVERT_TO_CODE;
code_string="Net Data Loop (PERMUTED): table=input_data index=data_loop_index order_var=data_loop_order ";
pre_compile_code_string="Net Data Loop (PERMUTED): table=input_data index=data_loop_index order_var=data_loop_order ";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
ProgramCall @[0] {
desc="run the trial program, passing network and input_data";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraTrial(network, input_data)";
pre_compile_code_string="LeabraTrial(network, input_data)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="input_data";
required=1;
def_val=;
prev_expr=;
expr {
expr="input_data";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"]$$;
targ_ld_init="*LeabraTrial*";
};
If @[1] {
desc="test if it is time to update the weight values from delta weights (dWt) computed over trials";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.Compute_Weights_Test(trial+1))";
pre_compile_code_string="if (network.Compute_Weights_Test(trial+1))";
cond {
expr="network.Compute_Weights_Test(trial+1)";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="update the weight values based on changes computed by trial program";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_Weights()";
pre_compile_code_string="network->Compute_Weights()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].args["network"]$;
method=Network::Compute_Weights;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_Weights()";
meth_desc=" update weights for whole net: calls DMem_SumDWts before doing update if in dmem mode";
};
};
};
};
data_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].args["input_data"]$$;
index_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["data_loop_index"]$$;
order_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["data_loop_order"]$$;
order=PERMUTED;
update_after=0;
dmem_nprocs=1;
dmem_this_proc=0;
grouped=0;
group_col 9 0="Group";
group_index_var=NULL;
group_order_var=NULL;
group_order=PERMUTED;
group_idx_list{ };
};
If @[5] {
desc="if full batch mode, update only at end of epoch";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.wt_update == Network::BATCH)";
pre_compile_code_string="if (network.wt_update == Network::BATCH)";
cond {
expr="network.wt_update == Network::BATCH";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="final update of weights based on accumulated changes";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_Weights()";
pre_compile_code_string="network->Compute_Weights()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].args["network"]$;
method=Network::Compute_Weights;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_Weights()";
meth_desc=" update weights for whole net: calls DMem_SumDWts before doing update if in dmem mode";
};
};
};
MethodCall @[6] {
desc="network accumulates some core statistics over the epoch -- this finalizes that process and computes summary stats";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_EpochStats()";
pre_compile_code_string="network->Compute_EpochStats()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].args["network"]$;
method=LeabraNetwork::Compute_EpochStats;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_EpochStats()";
meth_desc=" compute epoch-level statistics; calls DMem_ComputeAggs (if dmem) and EpochSSE -- specific algos may add more compute epoch-level statistics, including SSE, AvgExtRew and AvgCycles";
};
ProgramCall @[7] {
desc="run program that records data from network and possibly other sources about the epoch";
flags=OFF|CAN_REVERT_TO_CODE;
code_string="LeabraEpochMonitor(network)";
pre_compile_code_string="LeabraEpochMonitor(network)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=Network;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"]$$;
targ_ld_init="*LeabraEpochMonitor*";
};
MethodCall @[8] {
desc="done with the computation in the epoch -- record time it took";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer->EndTimer()";
pre_compile_code_string="epoch_timer->EndTimer()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpoch"].vars["epoch_timer"]$;
method=TimeUsed::EndTimer;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void EndTimer()";
meth_desc=" record the current time as the ending time, and compute difference as the time used";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraTestEpoch"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].doc$$;
};
};
name="LeabraTestEpoch";
short_nm="Tstpch";
tags=;
desc="iterates over all of the items in a data table and calls LeabraTrial process on them";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to operate on";
init_from=NULL;
};
ProgVar @["TestWP"] {
name="TestWP";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["TestWP_Optimal"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["data_loop_order"] {
name="data_loop_order";
var_type=T_HardEnum;
int_val=1;
hard_enum_type=DataLoop::Order;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="controls the order in which events (rows of the input data datatable) are presented to the network
(SEQUENTIAL, PERMUTED, RANDOM)";
init_from=NULL;
};
ProgVar @["trial"] {
name="trial";
var_type=T_Int;
int_val=3;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="current trial (event) within the epoch -- increments automatically";
init_from=NULL;
};
ProgVar @["trial_mon_data"] {
name="trial_mon_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["TrialOutputData"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="trial-level output data -- we reset it every epoch by default, so it just contains last epoch of data";
init_from=NULL;
};
ProgVar @["epoch_timer"] {
name="epoch_timer";
var_type=T_Object;
object_type=TimeUsed;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].epoch_time$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="timer to record time required to perform one epoch of processing (object is on network -- this is a pointer to it)";
init_from=NULL;
};
ProgVar @["data_loop_index"] {
name="data_loop_index";
var_type=T_Int;
int_val=3;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="index counter for the looping over items in the input_data datatable (not always the same as trial counter, depending on distributed memory computation)";
init_from=NULL;
};
ProgVar @["num_intact_snc_units"] {
name="num_intact_snc_units";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["snc_size"] {
name="snc_size";
var_type=T_Int;
int_val=4;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["k"] {
name="k";
var_type=T_Real;
real_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["SNc"] {
name="SNc";
var_type=T_Object;
object_type=LeabraLayer;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["SNc"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize trial counter (local variable and in the network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: trial";
pre_compile_code_string="Net Counter Init: trial";
network_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].args["network"]$$;
local_ctr_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["trial"]$$;
counter=Network::trial;
update_after=0;
};
AssignExpr @[1] {
desc="get pointer to epoch timer object on network";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer = network.epoch_time";
pre_compile_code_string="epoch_timer = network.epoch_time";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["epoch_timer"]$$;
expr {
expr="network.epoch_time";
};
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize trial counter (local variable and in the network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: trial";
pre_compile_code_string="Net Counter Init: trial";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["trial"]$;
counter=Network::trial;
update_after=0;
};
AssignExpr @[1] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="snc_size = SNc.units.size";
pre_compile_code_string="snc_size = SNc.units.size";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["snc_size"]$$;
expr {
expr="SNc.units.size";
};
};
AssignExpr @[2] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="k = (float)num_intact_snc_units/ snc_size";
pre_compile_code_string="k = (float)num_intact_snc_units/ snc_size";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["k"]$$;
expr {
expr="(float)num_intact_snc_units/ snc_size";
};
};
AssignExpr @[3] {
desc="get pointer to epoch timer object on network";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer = network.epoch_time";
pre_compile_code_string="epoch_timer = network.epoch_time";
result_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["epoch_timer"]$;
expr {
expr="network.epoch_time";
};
};
MethodCall @[4] {
desc="start the epoch timer to record computation time per epoch";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer->StartTimer(true)";
pre_compile_code_string="epoch_timer->StartTimer(true)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["epoch_timer"]$;
method=TimeUsed::StartTimer;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="reset_used";
required=0;
def_val="true";
prev_expr=;
expr {
expr="true";
};
};
};
meth_sig="void StartTimer(bool reset_used = true)";
meth_desc=" record the current time as the starting time, and optionally reset the time used information";
};
MethodCall @[5] {
desc="reset trial-level monitor data every epoch, so it reflects only the most recent epoch's worth of data (turn flags OFF to accumulate trial data across entire training run)";
flags=CAN_REVERT_TO_CODE;
code_string="trial_mon_data->ResetData()";
pre_compile_code_string="trial_mon_data->ResetData()";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["trial_mon_data"]$$;
method=DataTable::ResetData;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void ResetData()";
meth_desc=" deletes all the data (rows), but keeps the column structure -- this cannot be undone!";
};
NetDataLoop @[6] {
desc="iterates over the events/rows of input_data, according to data_loop_order variable";
flags=CAN_REVERT_TO_CODE;
code_string="Net Data Loop (PERMUTED): table=TestWP index=data_loop_index order_var=data_loop_order ";
pre_compile_code_string="Net Data Loop (PERMUTED): table=TestWP index=data_loop_index order_var=data_loop_order ";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
ProgramCall @[0] {
desc="run the trial program, passing network and input_data";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraTestTrial(network, TestWP)";
pre_compile_code_string="LeabraTestTrial(network, TestWP)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="TestWP";
required=1;
def_val=;
prev_expr=;
expr {
expr="TestWP";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"]$$;
targ_ld_init="*LeabraTestTrial*";
};
If @[1] {
desc="test if it is time to update the weight values from delta weights (dWt) computed over trials";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.Compute_Weights_Test(trial+1))";
pre_compile_code_string="if (network.Compute_Weights_Test(trial+1))";
cond {
expr="network.Compute_Weights_Test(trial+1)";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="update the weight values based on changes computed by trial program";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_Weights()";
pre_compile_code_string="network->Compute_Weights()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].args["network"]$;
method=Network::Compute_Weights;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_Weights()";
meth_desc=" update weights for whole net: calls DMem_SumDWts before doing update if in dmem mode";
};
};
};
};
data_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].args["TestWP"]$$;
index_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["data_loop_index"]$$;
order_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["data_loop_order"]$$;
order=PERMUTED;
update_after=0;
dmem_nprocs=1;
dmem_this_proc=0;
grouped=0;
group_col 9 0="Group";
group_index_var=NULL;
group_order_var=NULL;
group_order=PERMUTED;
group_idx_list{ };
};
If @[7] {
desc="if full batch mode, update only at end of epoch";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.wt_update == Network::BATCH)";
pre_compile_code_string="if (network.wt_update == Network::BATCH)";
cond {
expr="network.wt_update == Network::BATCH";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="final update of weights based on accumulated changes";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_Weights()";
pre_compile_code_string="network->Compute_Weights()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].args["network"]$;
method=Network::Compute_Weights;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_Weights()";
meth_desc=" update weights for whole net: calls DMem_SumDWts before doing update if in dmem mode";
};
};
};
MethodCall @[8] {
desc="network accumulates some core statistics over the epoch -- this finalizes that process and computes summary stats";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_EpochStats()";
pre_compile_code_string="network->Compute_EpochStats()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].args["network"]$;
method=LeabraNetwork::Compute_EpochStats;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_EpochStats()";
meth_desc=" compute epoch-level statistics; calls DMem_ComputeAggs (if dmem) and EpochSSE -- specific algos may add more compute epoch-level statistics, including SSE, AvgExtRew and AvgCycles";
};
ProgramCall @[9] {
desc="run program that records data from network and possibly other sources about the epoch";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraEpochMonitor(network)";
pre_compile_code_string="LeabraEpochMonitor(network)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=Network;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
target=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"]$;
targ_ld_init="*LeabraEpochMonitor*";
};
MethodCall @[10] {
desc="done with the computation in the epoch -- record time it took";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer->EndTimer()";
pre_compile_code_string="epoch_timer->EndTimer()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestEpoch"].vars["epoch_timer"]$;
method=TimeUsed::EndTimer;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void EndTimer()";
meth_desc=" record the current time as the ending time, and compute difference as the time used";
};
};
step_prog=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"]$;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraTrial"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].doc$$;
};
};
name="LeabraTrial";
short_nm="Trial";
tags="Leabra, Std";
desc="Leabra processing of a single input/toutput event or external information: typically runs a minus and a plus phase, then learns (unless testing)";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to operate on -- typically set by higher-level calling programs";
init_from=NULL;
};
ProgVar @["input_data"] {
name="input_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="datatable containing training input/output patterns";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["phase_no"] {
name="phase_no";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="local phase counting variable (0 is typically minus phase, 1 is typically plus -- depends on network settings)";
init_from=NULL;
};
ProgVar @["update_net_view"] {
name="update_net_view";
var_type=T_Bool;
bool_val=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="determines whether to update any network view displays after trial is completed";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize the local phase_no counter, and corresponding network one";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: phase_no";
pre_compile_code_string="Net Counter Init: phase_no";
network_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].args["network"]$$;
local_ctr_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].vars["phase_no"]$$;
counter=LeabraNetwork::phase_no;
update_after=0;
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize the local phase_no counter, and corresponding network one";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: phase_no";
pre_compile_code_string="Net Counter Init: phase_no";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].vars["phase_no"]$;
counter=LeabraNetwork::phase_no;
update_after=0;
};
MethodCall @[1] {
desc="initializes various counters at start of trial";
flags=CAN_REVERT_TO_CODE;
code_string="network->Trial_Init()";
pre_compile_code_string="network->Trial_Init()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].args["network"]$;
method=LeabraNetwork::Trial_Init;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Trial_Init()";
meth_desc=" initialize at start of trial (SetCurLrate, set phase_max, Decay state)";
};
WhileLoop @[2] {
desc="loop over phases of settling in the network";
flags=CAN_REVERT_TO_CODE;
code_string="while (phase_no < network.phase_max)";
pre_compile_code_string="while (phase_no < network.phase_max)";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
ProgramCall @[0] {
desc="run the settle program (which iterates over cyles of network activation updating) for each phase";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraSettle(network, input_data)";
pre_compile_code_string="LeabraSettle(network, input_data)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="input_data";
required=1;
def_val=;
prev_expr=;
expr {
expr="input_data";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"]$$;
targ_ld_init="*LeabraSettle*";
};
NetCounterIncr @[1] {
desc="increment the phase number (also on network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Incr: phase_no";
pre_compile_code_string="Net Counter Incr: phase_no";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].vars["phase_no"]$;
counter=LeabraNetwork::phase_no;
update_after=0;
};
MethodCall @[2] {
desc="increments other phase state information to prepare for the next phase of settling";
flags=CAN_REVERT_TO_CODE;
code_string="network->Trial_UpdatePhase()";
pre_compile_code_string="network->Trial_UpdatePhase()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].args["network"]$;
method=LeabraNetwork::Trial_UpdatePhase;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Trial_UpdatePhase()";
meth_desc=" update phase based on phase_no -- typically called by program in Trial loop over settling";
};
};
test {
expr="phase_no < network.phase_max";
};
};
MethodCall @[3] {
desc="after the trial is over, do final computations: Compute_dWt (learn weights), compute stats";
flags=CAN_REVERT_TO_CODE;
code_string="network->Trial_Final()";
pre_compile_code_string="network->Trial_Final()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].args["network"]$;
method=LeabraNetwork::Trial_Final;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Trial_Final()";
meth_desc=" do final processing after trial (Compute_dWt, EncodeState)";
};
ProgramCall @[4] {
desc="records data about the trial-level processing to a datatable for graphing/processing";
flags=OFF|CAN_REVERT_TO_CODE;
code_string="LeabraTrialMonitor(network)";
pre_compile_code_string="LeabraTrialMonitor(network)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=Network;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"]$$;
targ_ld_init="*LeabraTrialMonitor*";
};
NetUpdateView @[5] {
desc="update the network view(s) (only if update_net_view is true)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Update View";
pre_compile_code_string="Net Update View";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].args["network"]$;
update_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrial"].vars["update_net_view"]$$;
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraTestTrial"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].doc$$;
};
};
name="LeabraTestTrial";
short_nm="TstTrl";
tags=;
desc="Leabra processing of a single input/toutput event or external information: typically runs a minus and a plus phase, then learns (unless testing)";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to operate on -- typically set by higher-level calling programs";
init_from=NULL;
};
ProgVar @["TestWP"] {
name="TestWP";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["TestWP_Optimal"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="datatable containing training input/output patterns";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["phase_no"] {
name="phase_no";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="local phase counting variable (0 is typically minus phase, 1 is typically plus -- depends on network settings)";
init_from=NULL;
};
ProgVar @["update_net_view"] {
name="update_net_view";
var_type=T_Bool;
bool_val=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="determines whether to update any network view displays after trial is completed";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize the local phase_no counter, and corresponding network one";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: phase_no";
pre_compile_code_string="Net Counter Init: phase_no";
network_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].args["network"]$$;
local_ctr_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].vars["phase_no"]$$;
counter=LeabraNetwork::phase_no;
update_after=0;
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize the local phase_no counter, and corresponding network one";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: phase_no";
pre_compile_code_string="Net Counter Init: phase_no";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].vars["phase_no"]$;
counter=LeabraNetwork::phase_no;
update_after=0;
};
MethodCall @[1] {
desc="initializes various counters at start of trial";
flags=CAN_REVERT_TO_CODE;
code_string="network->Trial_Init()";
pre_compile_code_string="network->Trial_Init()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].args["network"]$;
method=LeabraNetwork::Trial_Init;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Trial_Init()";
meth_desc=" initialize at start of trial (SetCurLrate, set phase_max, Decay state)";
};
WhileLoop @[2] {
desc="loop over phases of settling in the network";
flags=CAN_REVERT_TO_CODE;
code_string="while (phase_no < network.phase_max)";
pre_compile_code_string="while (phase_no < network.phase_max)";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
ProgramCall @[0] {
desc="run the settle program (which iterates over cyles of network activation updating) for each phase";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraTestSettle(network, TestWP)";
pre_compile_code_string="LeabraTestSettle(network, TestWP)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="TestWP";
required=1;
def_val=;
prev_expr=;
expr {
expr="TestWP";
};
};
};
target=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"]$;
targ_ld_init="*LeabraTestSettle*";
};
NetCounterIncr @[1] {
desc="increment the phase number (also on network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Incr: phase_no";
pre_compile_code_string="Net Counter Incr: phase_no";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].vars["phase_no"]$;
counter=LeabraNetwork::phase_no;
update_after=0;
};
MethodCall @[2] {
desc="increments other phase state information to prepare for the next phase of settling";
flags=CAN_REVERT_TO_CODE;
code_string="network->Trial_UpdatePhase()";
pre_compile_code_string="network->Trial_UpdatePhase()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].args["network"]$;
method=LeabraNetwork::Trial_UpdatePhase;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Trial_UpdatePhase()";
meth_desc=" update phase based on phase_no -- typically called by program in Trial loop over settling";
};
};
test {
expr="phase_no < network.phase_max";
};
};
MethodCall @[3] {
desc="after the trial is over, do final computations: Compute_dWt (learn weights), compute stats";
flags=CAN_REVERT_TO_CODE;
code_string="network->Trial_Final()";
pre_compile_code_string="network->Trial_Final()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].args["network"]$;
method=LeabraNetwork::Trial_Final;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Trial_Final()";
meth_desc=" do final processing after trial (Compute_dWt, EncodeState)";
};
ProgramCall @[4] {
desc="records data about the trial-level processing to a datatable for graphing/processing";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraTrialMonitor(network)";
pre_compile_code_string="LeabraTrialMonitor(network)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=Network;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
target=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"]$;
targ_ld_init="*LeabraTrialMonitor*";
};
NetUpdateView @[5] {
desc="update the network view(s) (only if update_net_view is true)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Update View";
pre_compile_code_string="Net Update View";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].args["network"]$;
update_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestTrial"].vars["update_net_view"]$$;
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraSettle"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].doc$$;
};
};
name="LeabraSettle";
short_nm="Settle";
tags="Leabra, Std";
desc="iterates over cycles of updating until network has settled into a stable state, or output activations have exceeded a threshold";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["input_data"] {
name="input_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["cycle"] {
name="cycle";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="current cycle of settling (local loop counter)";
init_from=NULL;
};
ProgVar @["min_cycles"] {
name="min_cycles";
var_type=T_Int;
int_val=150;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="IMPORTANT: this value is obtained from the network min_cycles and min_cycles_phase2 -- change the value on the network object, not here in this program!
sets the minimum number of cycles to settle for, regardless of network state changes, etc";
init_from=NULL;
};
ProgVar @["update_net_view"] {
name="update_net_view";
var_type=T_Bool;
bool_val=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="if true, will update network views at end of settling";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize local cycle counter and corresponding counter on network";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: cycle";
pre_compile_code_string="Net Counter Init: cycle";
network_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$$;
local_ctr_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].vars["cycle"]$$;
counter=Network::cycle;
update_after=0;
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize local cycle counter and corresponding counter on network";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: cycle";
pre_compile_code_string="Net Counter Init: cycle";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].vars["cycle"]$;
counter=Network::cycle;
update_after=0;
};
MethodCall @[1] {
desc="resets input data, before getting new external inputs data from apply inputs call";
flags=CAN_REVERT_TO_CODE;
code_string="network->Init_InputData()";
pre_compile_code_string="network->Init_InputData()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
method=Network::Init_InputData;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Init_InputData()";
meth_desc=" Initializes external and target inputs";
};
ProgramCall @[2] {
desc="apply external input activations from the input_data table to the network
this program can be extended to do arbitrary things to generate data and apply it to network layers";
flags=CAN_REVERT_TO_CODE;
code_string="ApplyInputs(network, input_data)";
pre_compile_code_string="ApplyInputs(network, input_data)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=Network;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="input_data";
required=1;
def_val=;
prev_expr=;
expr {
expr="input_data";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputs"]$$;
targ_ld_init="*ApplyInputs*";
};
ProgramCall @[3] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="DA_Rew_Punish(network, input_data)";
pre_compile_code_string="DA_Rew_Punish(network, input_data)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="input_data";
required=1;
def_val=;
prev_expr=;
expr {
expr="input_data";
};
};
};
target=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"]$;
targ_ld_init="*DA_Rew_Punish*";
};
If @[4] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase == LeabraNetwork::PLUS_PHASE)";
pre_compile_code_string="if (network.phase == LeabraNetwork::PLUS_PHASE)";
cond {
expr="network.phase == LeabraNetwork::PLUS_PHASE";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="network.cycle_max = 30";
pre_compile_code_string="network.cycle_max = 30";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
path="cycle_max";
expr {
expr="30";
};
update_after=0;
};
};
};
Else @[5] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="else";
pre_compile_code_string="else";
else_code {
name="else_code";
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="number of cycles to run in minus phase";
flags=CAN_REVERT_TO_CODE;
code_string="network.cycle_max = 100";
pre_compile_code_string="network.cycle_max = 100";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
path="cycle_max";
expr {
expr="100";
};
update_after=0;
};
};
};
MethodCall @[6] {
desc="initializes various counters at start of settling";
flags=CAN_REVERT_TO_CODE;
code_string="network->Settle_Init()";
pre_compile_code_string="network->Settle_Init()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
method=LeabraNetwork::Settle_Init;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Settle_Init()";
meth_desc=" initialize network for settle-level processing (decay, active k, hard clamp, netscale)";
};
If @[7] {
desc="get appropriate min_cycles value depending on which phase we're in";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase_no <= 1)";
pre_compile_code_string="if (network.phase_no <= 1)";
cond {
expr="network.phase_no <= 1";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
AssignExpr @[0] {
desc="get minimum number of cycles from parameter on network (which is where you should change this value!)";
flags=CAN_REVERT_TO_CODE;
code_string="min_cycles = network.min_cycles";
pre_compile_code_string="min_cycles = network.min_cycles";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].vars["min_cycles"]$$;
expr {
expr="network.min_cycles";
};
};
};
};
Else @[8] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="else";
pre_compile_code_string="else";
else_code {
name="else_code";
el_typ=ProgCode;
el_def=0;
AssignExpr @[0] {
desc="get minimum number of cycles from parameter on network (which is where you should change this value!)";
flags=CAN_REVERT_TO_CODE;
code_string="min_cycles = network.min_cycles_phase2";
pre_compile_code_string="min_cycles = network.min_cycles_phase2";
result_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].vars["min_cycles"]$;
expr {
expr="network.min_cycles_phase2";
};
};
};
};
WhileLoop @[9] {
desc="the main loop over cycles of updating";
flags=CAN_REVERT_TO_CODE;
code_string="while (cycle < network.cycle_max)";
pre_compile_code_string="while (cycle < network.cycle_max)";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
ProgramCall @[0] {
desc="run the cycle program, which computes one cycle of activations";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraCycle(network)";
pre_compile_code_string="LeabraCycle(network)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraCycle"]$$;
targ_ld_init="*LeabraCycle*";
};
NetCounterIncr @[1] {
desc="increment cycle counter (also on network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Incr: cycle";
pre_compile_code_string="Net Counter Incr: cycle";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].vars["cycle"]$;
counter=Network::cycle;
update_after=0;
};
IfContinue @[2] {
desc="avoid subsequent stopping criteria if below min_cycles";
flags=CAN_REVERT_TO_CODE;
code_string="if(cycle < min_cycles) continue";
pre_compile_code_string="if(cycle < min_cycles) continue";
cond {
expr="cycle < min_cycles";
};
};
IfBreak @[3] {
desc="stopping criterion for settling: based either on maximum change in activation (maxda) or on the maximum activation value in the network getting over threshold (which ever comes first). Set either parmeter to values that are always false (e.g., trg_max_act_stopcrit = -1) to eliminate associated source of criterion for stopping settling.";
flags=CAN_REVERT_TO_CODE;
code_string="if((network.maxda < network.maxda_stopcrit) ||
(network.trg_max_act > network.trg_max_act_stopcrit)) break";
pre_compile_code_string="if((network.maxda < network.maxda_stopcrit) ||
(network.trg_max_act > network.trg_max_act_stopcrit)) break";
cond {
expr="(network.maxda < network.maxda_stopcrit) ||
(network.trg_max_act > network.trg_max_act_stopcrit)";
};
};
};
test {
expr="cycle < network.cycle_max";
};
};
MethodCall @[10] {
desc="perform final operations at end of settling (storing final activations, etc)";
flags=CAN_REVERT_TO_CODE;
code_string="network->Settle_Final()";
pre_compile_code_string="network->Settle_Final()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
method=LeabraNetwork::Settle_Final;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Settle_Final()";
meth_desc=" do final processing after settling (postsettle, Compute_dWt if needed)";
};
If @[11] {
desc="only run trial-level statistics in minus phase (otherwise network may have correct answer clamped on!). IMPORTANT: this assumes that you've got target activation values for output layers already
presented in the minus phase -- if this is not the case (values are computed on the fly), you may want to run this instead at the start of the plus phase, after ApplyInputs";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase == LeabraNetwork::MINUS_PHASE)";
pre_compile_code_string="if (network.phase == LeabraNetwork::MINUS_PHASE)";
cond {
expr="network.phase == LeabraNetwork::MINUS_PHASE";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="compute trial-level statistics";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_TrialStats()";
pre_compile_code_string="network->Compute_TrialStats()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
method=LeabraNetwork::Compute_TrialStats;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_TrialStats()";
meth_desc=" compute trial-level statistics (SSE and others defined by specific algorithms) compute trial-level statistics, including SSE and minus cycles -- to be called at end of minus phase -- use Compute_TrialStats_Test() to determine when -- HOWEVER: it is much better to call Compute_PhaseStats(), which calls Compute_MinusStats() and Compute_PlustStats() separately at end of each phase (respectively) to get the appropriate stats at each point";
};
};
};
If @[12] {
desc="this stat must be called in plus phase when reward information is avail";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase_no == 1)";
pre_compile_code_string="if (network.phase_no == 1)";
cond {
expr="network.phase_no == 1";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="get external reward information";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_ExtRew()";
pre_compile_code_string="network->Compute_ExtRew()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
method=LeabraNetwork::Compute_ExtRew;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_ExtRew()";
meth_desc=" compute external reward information: Must be called in plus phase (phase_no == 1)";
};
};
};
NetUpdateView @[13] {
desc="update network views, if update_net_view == true";
flags=CAN_REVERT_TO_CODE;
code_string="Net Update View";
pre_compile_code_string="Net Update View";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].args["network"]$;
update_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraSettle"].vars["update_net_view"]$$;
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraTestSettle"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].doc$$;
};
};
name="LeabraTestSettle";
short_nm="TsSttl";
tags=;
desc="iterates over cycles of updating until network has settled into a stable state, or output activations have exceeded a threshold";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["TestWP"] {
name="TestWP";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["TestWP_Optimal"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["cycle"] {
name="cycle";
var_type=T_Int;
int_val=200;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="current cycle of settling (local loop counter)";
init_from=NULL;
};
ProgVar @["min_cycles"] {
name="min_cycles";
var_type=T_Int;
int_val=150;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="IMPORTANT: this value is obtained from the network min_cycles and min_cycles_phase2 -- change the value on the network object, not here in this program!
sets the minimum number of cycles to settle for, regardless of network state changes, etc";
init_from=NULL;
};
ProgVar @["update_net_view"] {
name="update_net_view";
var_type=T_Bool;
bool_val=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="if true, will update network views at end of settling";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize local cycle counter and corresponding counter on network";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: cycle";
pre_compile_code_string="Net Counter Init: cycle";
network_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$$;
local_ctr_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].vars["cycle"]$$;
counter=Network::cycle;
update_after=0;
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
NetCounterInit @[0] {
desc="initialize local cycle counter and corresponding counter on network";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Init: cycle";
pre_compile_code_string="Net Counter Init: cycle";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].vars["cycle"]$;
counter=Network::cycle;
update_after=0;
};
MethodCall @[1] {
desc="resets input data, before getting new external inputs data from apply inputs call";
flags=CAN_REVERT_TO_CODE;
code_string="network->Init_InputData()";
pre_compile_code_string="network->Init_InputData()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
method=Network::Init_InputData;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Init_InputData()";
meth_desc=" Initializes external and target inputs";
};
ProgramCall @[2] {
desc="apply external input activations from the input_data table to the network
this program can be extended to do arbitrary things to generate data and apply it to network layers";
flags=CAN_REVERT_TO_CODE;
code_string="ApplyInputsTest(network, TestWP)";
pre_compile_code_string="ApplyInputsTest(network, TestWP)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=Network;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="TestWP";
required=1;
def_val=;
prev_expr=;
expr {
expr="TestWP";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputsTest"]$$;
targ_ld_init="*ApplyInputsTest*";
};
ProgramCall @[3] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="DA_Rew_Punish(network, TestWP)";
pre_compile_code_string="DA_Rew_Punish(network, TestWP)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
ProgArg @[1] {
arg_type=DataTable;
type="DataTable*";
name="input_data";
required=1;
def_val=;
prev_expr=;
expr {
expr="TestWP";
};
};
};
target=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"]$;
targ_ld_init="*DA_Rew_Punish*";
};
If @[4] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase == LeabraNetwork::PLUS_PHASE)";
pre_compile_code_string="if (network.phase == LeabraNetwork::PLUS_PHASE)";
cond {
expr="network.phase == LeabraNetwork::PLUS_PHASE";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="network.cycle_max = 30";
pre_compile_code_string="network.cycle_max = 30";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
path="cycle_max";
expr {
expr="30";
};
update_after=0;
};
};
};
Else @[5] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="else";
pre_compile_code_string="else";
else_code {
name="else_code";
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="number of cycles to run in minus phase";
flags=CAN_REVERT_TO_CODE;
code_string="network.cycle_max = 100";
pre_compile_code_string="network.cycle_max = 100";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
path="cycle_max";
expr {
expr="100";
};
update_after=0;
};
};
};
MethodCall @[6] {
desc="initializes various counters at start of settling";
flags=CAN_REVERT_TO_CODE;
code_string="network->Settle_Init()";
pre_compile_code_string="network->Settle_Init()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
method=LeabraNetwork::Settle_Init;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Settle_Init()";
meth_desc=" initialize network for settle-level processing (decay, active k, hard clamp, netscale)";
};
If @[7] {
desc="get appropriate min_cycles value depending on which phase we're in";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase_no <= 1)";
pre_compile_code_string="if (network.phase_no <= 1)";
cond {
expr="network.phase_no <= 1";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
AssignExpr @[0] {
desc="get minimum number of cycles from parameter on network (which is where you should change this value!)";
flags=CAN_REVERT_TO_CODE;
code_string="min_cycles = network.min_cycles";
pre_compile_code_string="min_cycles = network.min_cycles";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].vars["min_cycles"]$$;
expr {
expr="network.min_cycles";
};
};
};
};
Else @[8] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="else";
pre_compile_code_string="else";
else_code {
name="else_code";
el_typ=ProgCode;
el_def=0;
AssignExpr @[0] {
desc="get minimum number of cycles from parameter on network (which is where you should change this value!)";
flags=CAN_REVERT_TO_CODE;
code_string="min_cycles = network.min_cycles_phase2";
pre_compile_code_string="min_cycles = network.min_cycles_phase2";
result_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].vars["min_cycles"]$;
expr {
expr="network.min_cycles_phase2";
};
};
};
};
WhileLoop @[9] {
desc="the main loop over cycles of updating";
flags=CAN_REVERT_TO_CODE;
code_string="while (cycle < network.cycle_max)";
pre_compile_code_string="while (cycle < network.cycle_max)";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
ProgramCall @[0] {
desc="run the cycle program, which computes one cycle of activations";
flags=CAN_REVERT_TO_CODE;
code_string="LeabraTestCycle(network)";
pre_compile_code_string="LeabraTestCycle(network)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=LeabraNetwork;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestCycle"]$$;
targ_ld_init="*LeabraTestCycle*";
};
NetCounterIncr @[1] {
desc="increment cycle counter (also on network)";
flags=CAN_REVERT_TO_CODE;
code_string="Net Counter Incr: cycle";
pre_compile_code_string="Net Counter Incr: cycle";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
local_ctr_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].vars["cycle"]$;
counter=Network::cycle;
update_after=0;
};
IfContinue @[2] {
desc="avoid subsequent stopping criteria if below min_cycles";
flags=CAN_REVERT_TO_CODE;
code_string="if(cycle < min_cycles) continue";
pre_compile_code_string="if(cycle < min_cycles) continue";
cond {
expr="cycle < min_cycles";
};
};
IfBreak @[3] {
desc="stopping criterion for settling: based either on maximum change in activation (maxda) or on the maximum activation value in the network getting over threshold (which ever comes first). Set either parmeter to values that are always false (e.g., trg_max_act_stopcrit = -1) to eliminate associated source of criterion for stopping settling.";
flags=CAN_REVERT_TO_CODE;
code_string="if((network.maxda < network.maxda_stopcrit) ||
(network.trg_max_act > network.trg_max_act_stopcrit)) break";
pre_compile_code_string="if((network.maxda < network.maxda_stopcrit) ||
(network.trg_max_act > network.trg_max_act_stopcrit)) break";
cond {
expr="(network.maxda < network.maxda_stopcrit) ||
(network.trg_max_act > network.trg_max_act_stopcrit)";
};
};
};
test {
expr="cycle < network.cycle_max";
};
};
MethodCall @[10] {
desc="perform final operations at end of settling (storing final activations, etc)";
flags=CAN_REVERT_TO_CODE;
code_string="network->Settle_Final()";
pre_compile_code_string="network->Settle_Final()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
method=LeabraNetwork::Settle_Final;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Settle_Final()";
meth_desc=" do final processing after settling (postsettle, Compute_dWt if needed)";
};
If @[11] {
desc="only run trial-level statistics in minus phase (otherwise network may have correct answer clamped on!). IMPORTANT: this assumes that you've got target activation values for output layers already
presented in the minus phase -- if this is not the case (values are computed on the fly), you may want to run this instead at the start of the plus phase, after ApplyInputs";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase == LeabraNetwork::MINUS_PHASE)";
pre_compile_code_string="if (network.phase == LeabraNetwork::MINUS_PHASE)";
cond {
expr="network.phase == LeabraNetwork::MINUS_PHASE";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="compute trial-level statistics";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_TrialStats()";
pre_compile_code_string="network->Compute_TrialStats()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
method=LeabraNetwork::Compute_TrialStats;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_TrialStats()";
meth_desc=" compute trial-level statistics (SSE and others defined by specific algorithms) compute trial-level statistics, including SSE and minus cycles -- to be called at end of minus phase -- use Compute_TrialStats_Test() to determine when -- HOWEVER: it is much better to call Compute_PhaseStats(), which calls Compute_MinusStats() and Compute_PlustStats() separately at end of each phase (respectively) to get the appropriate stats at each point";
};
};
};
If @[12] {
desc="this stat must be called in plus phase when reward information is avail";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase_no == 1)";
pre_compile_code_string="if (network.phase_no == 1)";
cond {
expr="network.phase_no == 1";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="get external reward information";
flags=CAN_REVERT_TO_CODE;
code_string="network->Compute_ExtRew()";
pre_compile_code_string="network->Compute_ExtRew()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
method=LeabraNetwork::Compute_ExtRew;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Compute_ExtRew()";
meth_desc=" compute external reward information: Must be called in plus phase (phase_no == 1)";
};
};
};
NetUpdateView @[13] {
desc="update network views, if update_net_view == true";
flags=CAN_REVERT_TO_CODE;
code_string="Net Update View";
pre_compile_code_string="Net Update View";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].args["network"]$;
update_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestSettle"].vars["update_net_view"]$$;
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraCycle"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraCycle"].doc$$;
};
};
name="LeabraCycle";
short_nm="Cycle";
tags="Leabra, Std";
desc="runs one cycle of leabra processing (updating net inputs and activations)";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["update_net_view"] {
name="update_net_view";
var_type=T_Bool;
bool_val=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="determines whether network views will be updated on a cycle-by-cycle basis (slow, but often quite useful for seeing how processing is proceeding)";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="this does all the standard leabra processing for one cycle of activation updating";
flags=CAN_REVERT_TO_CODE;
code_string="network->Cycle_Run()";
pre_compile_code_string="network->Cycle_Run()";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraCycle"].args["network"]$$;
method=LeabraNetwork::Cycle_Run;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Cycle_Run()";
meth_desc=" compute one cycle of updating: netinput, inhibition, activations";
};
NetUpdateView @[1] {
desc="update network views if update_net_view == true";
flags=CAN_REVERT_TO_CODE;
code_string="Net Update View";
pre_compile_code_string="Net Update View";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraCycle"].args["network"]$;
update_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraCycle"].vars["update_net_view"]$$;
};
ProgramCall @[2] {
desc=;
flags=NON_STD|CAN_REVERT_TO_CODE;
code_string="Cycle_Monitor(network)";
pre_compile_code_string="Cycle_Monitor(network)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=Network;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
target=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"]$$;
targ_ld_init="*Cycle_Monitor*";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraTestCycle"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestCycle"].doc$$;
};
};
name="LeabraTestCycle";
short_nm="TsCycl";
tags=;
desc="runs one cycle of leabra processing (updating net inputs and activations)";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["update_net_view"] {
name="update_net_view";
var_type=T_Bool;
bool_val=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="determines whether network views will be updated on a cycle-by-cycle basis (slow, but often quite useful for seeing how processing is proceeding)";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="this does all the standard leabra processing for one cycle of activation updating";
flags=CAN_REVERT_TO_CODE;
code_string="network->Cycle_Run()";
pre_compile_code_string="network->Cycle_Run()";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestCycle"].args["network"]$$;
method=LeabraNetwork::Cycle_Run;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void Cycle_Run()";
meth_desc=" compute one cycle of updating: netinput, inhibition, activations";
};
NetUpdateView @[1] {
desc="update network views if update_net_view == true";
flags=CAN_REVERT_TO_CODE;
code_string="Net Update View";
pre_compile_code_string="Net Update View";
network_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestCycle"].args["network"]$;
update_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTestCycle"].vars["update_net_view"]$$;
};
ProgramCall @[2] {
desc=;
flags=NON_STD|CAN_REVERT_TO_CODE;
code_string="Cycle_Monitor(network)";
pre_compile_code_string="Cycle_Monitor(network)";
prog_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=Network;
type="LeabraNetwork*";
name="network";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
target=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"]$;
targ_ld_init="*Cycle_Monitor*";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["ApplyInputs"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputs"].doc$$;
};
};
name="ApplyInputs";
short_nm="pplynp";
tags="Network, InputData, Apply";
desc="apply the current input data to the network as external input and target values";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=NO_STOP_STEP;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=LayerWriter;
el_def=0;
LayerWriter @["LayerWriter_0"] {
name="LayerWriter_0";
data=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$;
network=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
layer_data {
name="layer_data";
el_typ=LayerWriterEl;
el_def=0;
LayerWriterEl @[0] {
col_name="Input";
net_target=LAYER;
layer_name="Input";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=EXT;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
LayerWriterEl @[1] {
col_name="Output";
net_target=LAYER;
layer_name="Output";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=TARG;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
LayerWriterEl @[2] {
col_name="SNc";
net_target=LAYER;
layer_name="SNc";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=EXT;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
LayerWriterEl @[3] {
col_name="Motor_Cortex";
net_target=LAYER;
layer_name="Motor_Cortex";
offset {x=0: y=0: };
use_layer_type=0;
quiet=0;
na_by_range=0;
ext_flags=COMP;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
LayerWriterEl @[4] {
col_name="Name";
net_target=TRIAL_NAME;
layer_name="Name";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=0;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
};
};
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=Network;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to apply inputs to -- typically set by calling program";
init_from=NULL;
};
ProgVar @["input_data"] {
name="input_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["Train_WeatherPred"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="input datatable containing input/output patterns";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["LayerWriter_0"] {
name="LayerWriter_0";
var_type=T_Object;
object_type=LayerWriter;
object_val=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputs"].objs["LayerWriter_0"]$$;
objs_ptr=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="this is a pointer to the LayerWriter object in objs -- edit that object to determine how information is presented to the network";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="sets the datatable and network for the layer writer, so it knows what to write to";
flags=CAN_REVERT_TO_CODE;
code_string="LayerWriter_0->SetDataNetwork(input_data, network)";
pre_compile_code_string="LayerWriter_0->SetDataNetwork(input_data, network)";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputs"].vars["LayerWriter_0"]$$;
method=LayerWriter::SetDataNetwork;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=DataTable_ptr;
type="DataTable*";
name="db";
required=1;
def_val=;
prev_expr=;
expr {
expr="input_data";
};
};
ProgArg @[1] {
arg_type=Network_ptr;
type="Network*";
name="net";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
meth_sig="void SetDataNetwork(DataTable* db, Network* net)";
meth_desc=" set the data table and network pointers -- convenience function for programs ";
};
MethodCall @[1] {
desc="check the configuration of the layer writer -- will emit warnings and errors for missing or misconfigured items";
flags=CAN_REVERT_TO_CODE;
code_string="LayerWriter_0->CheckConfig(false)";
pre_compile_code_string="LayerWriter_0->CheckConfig(false)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputs"].vars["LayerWriter_0"]$;
method=taList_impl::CheckConfig;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="quiet";
required=0;
def_val="false";
prev_expr=;
expr {
expr="false";
};
};
};
meth_sig="bool CheckConfig(bool quiet = false)";
meth_desc=" check the configuration of this object and all its children (defaults to no confirm of success)";
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="apply inputs to the network! layer writer has all the key specs";
flags=CAN_REVERT_TO_CODE;
code_string="LayerWriter_0->ApplyInputData()";
pre_compile_code_string="LayerWriter_0->ApplyInputData()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputs"].vars["LayerWriter_0"]$;
method=LayerWriter::ApplyInputData;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="bool ApplyInputData()";
meth_desc=" apply data to the layers, using the network's current context settings (TEST,TRAIN,etc) -- returns success";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["ApplyInputsTest"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputsTest"].doc$$;
};
};
name="ApplyInputsTest";
short_nm="pplTst";
tags=;
desc="apply the current input data to the network as external input and target values";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=NO_STOP_STEP;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=LayerWriter;
el_def=0;
LayerWriter @["LayerWriter_0"] {
name="LayerWriter_0";
data=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["TestWP_Optimal"]$;
network=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
layer_data {
name="layer_data";
el_typ=LayerWriterEl;
el_def=0;
LayerWriterEl @[0] {
col_name="Input";
net_target=LAYER;
layer_name="Input";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=EXT;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
LayerWriterEl @[1] {
col_name="Output";
net_target=LAYER;
layer_name="Output";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=TARG;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
LayerWriterEl @[2] {
col_name="SNc";
net_target=LAYER;
layer_name="SNc";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=EXT;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
LayerWriterEl @[3] {
col_name="Motor_Cortex";
net_target=LAYER;
layer_name="Motor_Cortex";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=TARG;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
LayerWriterEl @[4] {
col_name="Name";
net_target=TRIAL_NAME;
layer_name="Name";
offset {x=0: y=0: };
use_layer_type=1;
quiet=0;
na_by_range=0;
ext_flags=0;
noise {name="noise": type=NONE: mean=0: var=0.5: par=1: };
};
};
};
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=Network;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to apply inputs to -- typically set by calling program";
init_from=NULL;
};
ProgVar @["TestWP"] {
name="TestWP";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["TestWP_Optimal"]$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="input datatable containing input/output patterns";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["LayerWriter_0"] {
name="LayerWriter_0";
var_type=T_Object;
object_type=LayerWriter;
object_val=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputsTest"].objs["LayerWriter_0"]$$;
objs_ptr=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="this is a pointer to the LayerWriter object in objs -- edit that object to determine how information is presented to the network";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="sets the datatable and network for the layer writer, so it knows what to write to";
flags=CAN_REVERT_TO_CODE;
code_string="LayerWriter_0->SetDataNetwork(TestWP, network)";
pre_compile_code_string="LayerWriter_0->SetDataNetwork(TestWP, network)";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputsTest"].vars["LayerWriter_0"]$$;
method=LayerWriter::SetDataNetwork;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=DataTable_ptr;
type="DataTable*";
name="db";
required=1;
def_val=;
prev_expr=;
expr {
expr="TestWP";
};
};
ProgArg @[1] {
arg_type=Network_ptr;
type="Network*";
name="net";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
meth_sig="void SetDataNetwork(DataTable* db, Network* net)";
meth_desc=" set the data table and network pointers -- convenience function for programs ";
};
MethodCall @[1] {
desc="check the configuration of the layer writer -- will emit warnings and errors for missing or misconfigured items";
flags=CAN_REVERT_TO_CODE;
code_string="LayerWriter_0->CheckConfig(false)";
pre_compile_code_string="LayerWriter_0->CheckConfig(false)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputsTest"].vars["LayerWriter_0"]$;
method=taList_impl::CheckConfig;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="quiet";
required=0;
def_val="false";
prev_expr=;
expr {
expr="false";
};
};
};
meth_sig="bool CheckConfig(bool quiet = false)";
meth_desc=" check the configuration of this object and all its children (defaults to no confirm of success)";
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="apply inputs to the network! layer writer has all the key specs";
flags=CAN_REVERT_TO_CODE;
code_string="LayerWriter_0->ApplyInputData()";
pre_compile_code_string="LayerWriter_0->ApplyInputData()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["ApplyInputsTest"].vars["LayerWriter_0"]$;
method=LayerWriter::ApplyInputData;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="bool ApplyInputData()";
meth_desc=" apply data to the layers, using the network's current context settings (TEST,TRAIN,etc) -- returns success";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraTrialMonitor"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].doc$$;
};
};
name="LeabraTrialMonitor";
short_nm="TrMntr";
tags="Leabra, Std, Monitor";
desc="monitor trial-level data from the network (and potentially other sources) -- stores results in datatable (TrialOutputData typically) that can be used for graph/grid views and further analysis ";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=NO_STOP_STEP;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=NetMonitor;
el_def=0;
NetMonitor @["trial_netmon"] {
name="trial_netmon";
items {
name="items";
el_typ=NetMonItem;
el_def=0;
NetMonItem @["batch"] {
name="batch";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="batch";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["epoch"] {
name="epoch";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="epoch";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["trial"] {
name="trial";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="trial";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["trial_name"] {
name="trial_name";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="trial_name";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["group_name"] {
name="group_name";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="group_name";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["phase_no"] {
name="phase_no";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="phase_no";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["minus_cycles"] {
name="minus_cycles";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="minus_cycles";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["sse"] {
name="sse";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="sse";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["ext_rew"] {
name="ext_rew";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="ext_rew";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["Output_sse"] {
name="Output_sse";
computed=0;
object_type=LeabraLayer;
object=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["Output"]$$;
variable="sse";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
};
network=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
data=$.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["TrialOutputData"]$;
rmv_orphan_cols=1;
};
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=Network;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to record data from";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["trial_mon_data"] {
name="trial_mon_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["TrialOutputData"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="data table to record trial-level data to (this program writes new data to this table!)";
init_from=NULL;
};
ProgVar @["trial_netmon"] {
name="trial_netmon";
var_type=T_Object;
object_type=NetMonitor;
object_val=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].objs["trial_netmon"]$$;
objs_ptr=1;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="pointer to the NetMonitor object in objs secton of this program that contains configuration for what to record and where to get it";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="set the network and datatable for the NetMonitor";
flags=CAN_REVERT_TO_CODE;
code_string="trial_netmon->SetDataNetwork(trial_mon_data, network)";
pre_compile_code_string="trial_netmon->SetDataNetwork(trial_mon_data, network)";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].vars["trial_netmon"]$$;
method=NetMonitor::SetDataNetwork;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=DataTable_ptr;
type="DataTable*";
name="dt";
required=1;
def_val=;
prev_expr=;
expr {
expr="trial_mon_data";
};
};
ProgArg @[1] {
arg_type=Network_ptr;
type="Network*";
name="net";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
meth_sig="void SetDataNetwork(DataTable* dt, Network* net)";
meth_desc=" set both the data table and network -- convenient for programs -- calls ResetDataTableCols too -- don't call if columns are manually added or this is adding additional rows to a table";
};
MethodCall @[1] {
desc="check the configuration of the network monitor -- will emit warnings and errors for misconfigurations";
flags=CAN_REVERT_TO_CODE;
code_string="trial_netmon->CheckConfig(false)";
pre_compile_code_string="trial_netmon->CheckConfig(false)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].vars["trial_netmon"]$;
method=taBase::CheckConfig;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="quiet";
required=0;
def_val="false";
prev_expr=;
expr {
expr="false";
};
};
};
meth_sig="bool CheckConfig(bool quiet = false)";
meth_desc=" check the configuration of this object and all its children (defaults to no confirm of success)";
};
MethodCall @[2] {
desc="update the monitor items and data schema based on current settings of the NetMonitor object";
flags=CAN_REVERT_TO_CODE;
code_string="trial_netmon->UpdateMonitors(true)";
pre_compile_code_string="trial_netmon->UpdateMonitors(true)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].vars["trial_netmon"]$;
method=NetMonitor::UpdateMonitors;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="reset_first";
required=0;
def_val="false";
prev_expr=;
expr {
expr="true";
};
};
};
meth_sig="void UpdateMonitors(bool reset_first = false)";
meth_desc=" old name for UpdateDataTable";
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="add a new blank row to the data";
flags=CAN_REVERT_TO_CODE;
code_string="trial_mon_data->AddBlankRow()";
pre_compile_code_string="trial_mon_data->AddBlankRow()";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].vars["trial_mon_data"]$$;
method=DataTable::AddBlankRow;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="int AddBlankRow()";
meth_desc=" add a new row to the data table, sets read (source) and write (sink) index to this last row (as in ReadItem or WriteItem), so that subsequent data routines refer to this new row, and returns row ";
};
MethodCall @[1] {
desc="get the new monitor data from the network and other sources -- this does the main work";
flags=CAN_REVERT_TO_CODE;
code_string="trial_netmon->GetMonVals()";
pre_compile_code_string="trial_netmon->GetMonVals()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].vars["trial_netmon"]$;
method=NetMonitor::GetMonVals;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void GetMonVals()";
meth_desc=" get all the values and store in current row of data table -- call in program to get new data";
};
MethodCall @[2] {
desc="update views and other things after writing new data to monitor data table";
flags=CAN_REVERT_TO_CODE;
code_string="trial_mon_data->WriteClose()";
pre_compile_code_string="trial_mon_data->WriteClose()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].vars["trial_mon_data"]$;
method=DataTable::WriteClose;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void WriteClose()";
meth_desc=" closes up a write operation -- call when done writing data -- performs any post-writing cleanup/closing of files, etc";
};
MethodCall @[3] {
desc="only functional for dmem projects: synchronizes trial data across processes so that all distributed memory processors have the same trial-level data, despite having run only a subset of them each";
flags=CAN_REVERT_TO_CODE;
code_string="network->DMem_ShareTrialData(trial_mon_data, 1)";
pre_compile_code_string="network->DMem_ShareTrialData(trial_mon_data, 1)";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraTrialMonitor"].args["network"]$$;
method=Network::DMem_ShareTrialData;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=DataTable_ptr;
type="DataTable*";
name="dt";
required=1;
def_val=;
prev_expr=;
expr {
expr="trial_mon_data";
};
};
ProgArg @[1] {
arg_type=int;
type="int";
name="n_rows";
required=0;
def_val="1";
prev_expr=;
expr {
expr="1";
};
};
};
meth_sig="void DMem_ShareTrialData(DataTable* dt, int n_rows = 1)";
meth_desc=" share trial data from given datatable across the trial-level dmem communicator (outer loop) -- each processor gets data from all other processors; if called every trial with n_rows = 1, data will be identical to non-dmem; if called at end of epoch with n_rows = -1 data will be grouped by processor but this is more efficient";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["Cycle_Monitor"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].doc$$;
};
};
name="Cycle_Monitor";
short_nm="CycMnt";
tags=;
desc="monitor trial-level data from the network (and potentially other sources) -- stores results in datatable (TrialOutputData typically) that can be used for graph/grid views and further analysis ";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=NO_STOP_STEP;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=NetMonitor;
el_def=0;
NetMonitor @["cycle_netmon"] {
name="cycle_netmon";
items {
name="items";
el_typ=NetMonItem;
el_def=0;
NetMonItem @["batch"] {
name="batch";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="batch";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["epoch"] {
name="epoch";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="epoch";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["trial"] {
name="trial";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="trial";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["trial_name"] {
name="trial_name";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="trial_name";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["group_name"] {
name="group_name";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="group_name";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["phase_no"] {
name="phase_no";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="phase_no";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["cycle"] {
name="cycle";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="cycle";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["sse"] {
name="sse";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="sse";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["ext_rew"] {
name="ext_rew";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="ext_rew";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["STN_acts_avg"] {
name="STN_acts_avg";
computed=0;
object_type=LeabraLayer;
object=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["STN"]$$;
variable="acts.avg";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["Motor__acts_avg"] {
name="Motor__acts_avg";
computed=0;
object_type=LeabraLayer;
object=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["Motor_Cortex"]$$;
variable="acts.avg";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["Thalam_acts_avg"] {
name="Thalam_acts_avg";
computed=0;
object_type=LeabraLayer;
object=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["Thalamus"]$$;
variable="acts.avg";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["GP_Int_acts_avg"] {
name="GP_Int_acts_avg";
computed=0;
object_type=LeabraLayer;
object=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["GP_Int"]$$;
variable="acts.avg";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["GP_Ext_acts_avg"] {
name="GP_Ext_acts_avg";
computed=0;
object_type=LeabraLayer;
object=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["GP_Ext"]$$;
variable="acts.avg";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["Output_act"] {
name="Output_act";
computed=0;
object_type=LeabraLayer;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["Output"]$;
variable="act";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["Output_units_0_act"] {
name="Output_units_0_act";
computed=0;
object_type=LeabraLayer;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["Output"]$;
variable="units[0].act";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
};
network=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
data=.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["CycleOutputData"]$$;
rmv_orphan_cols=1;
};
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=Network;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to record data from";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["cycle_mon_data"] {
name="cycle_mon_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["CycleOutputData"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="data table to record trial-level data to (this program writes new data to this table!)";
init_from=NULL;
};
ProgVar @["cycle_netmon"] {
name="cycle_netmon";
var_type=T_Object;
object_type=NetMonitor;
object_val=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].objs["cycle_netmon"]$$;
objs_ptr=1;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="pointer to the NetMonitor object in objs secton of this program that contains configuration for what to record and where to get it";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="set the network and datatable for the NetMonitor";
flags=CAN_REVERT_TO_CODE;
code_string="cycle_netmon->SetDataNetwork(cycle_mon_data, network)";
pre_compile_code_string="cycle_netmon->SetDataNetwork(cycle_mon_data, network)";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].vars["cycle_netmon"]$$;
method=NetMonitor::SetDataNetwork;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=DataTable_ptr;
type="DataTable*";
name="dt";
required=1;
def_val=;
prev_expr=;
expr {
expr="cycle_mon_data";
};
};
ProgArg @[1] {
arg_type=Network_ptr;
type="Network*";
name="net";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
meth_sig="void SetDataNetwork(DataTable* dt, Network* net)";
meth_desc=" set both the data table and network -- convenient for programs -- calls ResetDataTableCols too -- don't call if columns are manually added or this is adding additional rows to a table";
};
MethodCall @[1] {
desc="check the configuration of the network monitor -- will emit warnings and errors for misconfigurations";
flags=CAN_REVERT_TO_CODE;
code_string="cycle_netmon->CheckConfig(false)";
pre_compile_code_string="cycle_netmon->CheckConfig(false)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].vars["cycle_netmon"]$;
method=taBase::CheckConfig;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="quiet";
required=0;
def_val="false";
prev_expr=;
expr {
expr="false";
};
};
};
meth_sig="bool CheckConfig(bool quiet = false)";
meth_desc=" check the configuration of this object and all its children (defaults to no confirm of success)";
};
MethodCall @[2] {
desc="update the monitor items and data schema based on current settings of the NetMonitor object";
flags=CAN_REVERT_TO_CODE;
code_string="cycle_netmon->UpdateMonitors(true)";
pre_compile_code_string="cycle_netmon->UpdateMonitors(true)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].vars["cycle_netmon"]$;
method=NetMonitor::UpdateMonitors;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="reset_first";
required=0;
def_val="false";
prev_expr=;
expr {
expr="true";
};
};
};
meth_sig="void UpdateMonitors(bool reset_first = false)";
meth_desc=" old name for UpdateDataTable";
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
IfReturn @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="if(network.phase_no>0) return";
pre_compile_code_string="if(network.phase_no>0) return";
cond {
expr="network.phase_no>0";
};
};
MethodCall @[1] {
desc="add a new blank row to the data";
flags=CAN_REVERT_TO_CODE;
code_string="cycle_mon_data->AddBlankRow()";
pre_compile_code_string="cycle_mon_data->AddBlankRow()";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].vars["cycle_mon_data"]$$;
method=DataTable::AddBlankRow;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="int AddBlankRow()";
meth_desc=" add a new row to the data table, sets read (source) and write (sink) index to this last row (as in ReadItem or WriteItem), so that subsequent data routines refer to this new row, and returns row ";
};
MethodCall @[2] {
desc="get the new monitor data from the network and other sources -- this does the main work";
flags=CAN_REVERT_TO_CODE;
code_string="cycle_netmon->GetMonVals()";
pre_compile_code_string="cycle_netmon->GetMonVals()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].vars["cycle_netmon"]$;
method=NetMonitor::GetMonVals;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void GetMonVals()";
meth_desc=" get all the values and store in current row of data table -- call in program to get new data";
};
MethodCall @[3] {
desc="update views and other things after writing new data to monitor data table";
flags=CAN_REVERT_TO_CODE;
code_string="cycle_mon_data->WriteClose()";
pre_compile_code_string="cycle_mon_data->WriteClose()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].vars["cycle_mon_data"]$;
method=DataTable::WriteClose;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void WriteClose()";
meth_desc=" closes up a write operation -- call when done writing data -- performs any post-writing cleanup/closing of files, etc";
};
MethodCall @[4] {
desc="only functional for dmem projects: synchronizes trial data across processes so that all distributed memory processors have the same trial-level data, despite having run only a subset of them each";
flags=CAN_REVERT_TO_CODE;
code_string="network->DMem_ShareTrialData(cycle_mon_data, 1)";
pre_compile_code_string="network->DMem_ShareTrialData(cycle_mon_data, 1)";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["Cycle_Monitor"].args["network"]$$;
method=Network::DMem_ShareTrialData;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=DataTable_ptr;
type="DataTable*";
name="dt";
required=1;
def_val=;
prev_expr=;
expr {
expr="cycle_mon_data";
};
};
ProgArg @[1] {
arg_type=int;
type="int";
name="n_rows";
required=0;
def_val="1";
prev_expr=;
expr {
expr="1";
};
};
};
meth_sig="void DMem_ShareTrialData(DataTable* dt, int n_rows = 1)";
meth_desc=" share trial data from given datatable across the trial-level dmem communicator (outer loop) -- each processor gets data from all other processors; if called every trial with n_rows = 1, data will be identical to non-dmem; if called at end of epoch with n_rows = -1 data will be grouped by processor but this is more efficient";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["LeabraEpochMonitor"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].doc$$;
};
};
name="LeabraEpochMonitor";
short_nm="pcMntr";
tags="Leabra, Std, Monitor";
desc="monitor epoch-level data from the network to a datatable (EpochOutputData typically) for use in graphing and viewing and further analysis";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=NO_STOP_STEP;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=NetMonitor;
el_def=0;
NetMonitor @["epoch_netmon"] {
name="epoch_netmon";
items {
name="items";
el_typ=NetMonItem;
el_def=0;
NetMonItem @["batch"] {
name="batch";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="batch";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["epoch"] {
name="epoch";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="epoch";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["avg_sse"] {
name="avg_sse";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="avg_sse";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["cnt_err"] {
name="cnt_err";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="cnt_err";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["avg_ext_rew"] {
name="avg_ext_rew";
computed=0;
object_type=LeabraNetwork;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
variable="avg_ext_rew";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
NetMonItem @["Output_sse"] {
name="Output_sse";
computed=0;
object_type=LeabraLayer;
object=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["Output"]$;
variable="sse";
var_label=;
name_style=AUTO_NAME;
max_name_len=6;
val_type=VT_FLOAT;
matrix=0;
matrix_geom{ };
data_agg=0;
data_src=NULL;
agg_col {
col_name=;
};
agg {name="agg": op=NONE: rel={name="rel": rel=LESSTHANOREQUAL: val=0: val_string="": use_var=0: var=NULL: }: };
select_rows=0;
select_spec {
col_name=;
name="_EQUAL_";
on=1;
rel=EQUAL;
use_var=0;
cmp 0 1;
var=NULL;
enable_var=NULL;
};
pre_proc_1 {name="pre_proc_1": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_2 {name="pre_proc_2": opr=NONE: arg=0: lw=-1: hi=1: };
pre_proc_3 {name="pre_proc_3": opr=NONE: arg=0: lw=-1: hi=1: };
};
};
network=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
data=$.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["EpochOutputData"]$;
rmv_orphan_cols=1;
};
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=Network;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to get data from";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["epoch_mon_data"] {
name="epoch_mon_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["OutputData"]["EpochOutputData"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="data table to write the epoch data to";
init_from=NULL;
};
ProgVar @["epoch_netmon"] {
name="epoch_netmon";
var_type=T_Object;
object_type=NetMonitor;
object_val=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].objs["epoch_netmon"]$$;
objs_ptr=1;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="network monitor object that contains full specs for what to record and where to get it";
init_from=NULL;
};
ProgVar @["epoch_timer"] {
name="epoch_timer";
var_type=T_Object;
object_type=TimeUsed;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].epoch_time$;
objs_ptr=0;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="pointer to the network's epoch-level timer, to record how long it took to process an epoch";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
AssignExpr @[0] {
desc="get the epoch timer from current network";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer = network.epoch_time";
pre_compile_code_string="epoch_timer = network.epoch_time";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].vars["epoch_timer"]$$;
expr {
expr="network.epoch_time";
};
};
MethodCall @[1] {
desc="set data and network on NetMonitor object";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_netmon->SetDataNetwork(epoch_mon_data, network)";
pre_compile_code_string="epoch_netmon->SetDataNetwork(epoch_mon_data, network)";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].vars["epoch_netmon"]$$;
method=NetMonitor::SetDataNetwork;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=DataTable_ptr;
type="DataTable*";
name="dt";
required=1;
def_val=;
prev_expr=;
expr {
expr="epoch_mon_data";
};
};
ProgArg @[1] {
arg_type=Network_ptr;
type="Network*";
name="net";
required=1;
def_val=;
prev_expr=;
expr {
expr="network";
};
};
};
meth_sig="void SetDataNetwork(DataTable* dt, Network* net)";
meth_desc=" set both the data table and network -- convenient for programs -- calls ResetDataTableCols too -- don't call if columns are manually added or this is adding additional rows to a table";
};
MethodCall @[2] {
desc="check configuration and emit errors/warnings for problems";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_netmon->CheckConfig(false)";
pre_compile_code_string="epoch_netmon->CheckConfig(false)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].vars["epoch_netmon"]$;
method=taBase::CheckConfig;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="quiet";
required=0;
def_val="false";
prev_expr=;
expr {
expr="false";
};
};
};
meth_sig="bool CheckConfig(bool quiet = false)";
meth_desc=" check the configuration of this object and all its children (defaults to no confirm of success)";
};
MethodCall @[3] {
desc="update the monitor items and data schema based on current settings of NetMonitor";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_netmon->UpdateMonitors(true)";
pre_compile_code_string="epoch_netmon->UpdateMonitors(true)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].vars["epoch_netmon"]$;
method=NetMonitor::UpdateMonitors;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=bool;
type="bool";
name="reset_first";
required=0;
def_val="false";
prev_expr=;
expr {
expr="true";
};
};
};
meth_sig="void UpdateMonitors(bool reset_first = false)";
meth_desc=" old name for UpdateDataTable";
};
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
MethodCall @[0] {
desc="add a new blank row to the data";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_mon_data->AddBlankRow()";
pre_compile_code_string="epoch_mon_data->AddBlankRow()";
result_var=NULL;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].vars["epoch_mon_data"]$$;
method=DataTable::AddBlankRow;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="int AddBlankRow()";
meth_desc=" add a new row to the data table, sets read (source) and write (sink) index to this last row (as in ReadItem or WriteItem), so that subsequent data routines refer to this new row, and returns row ";
};
MethodCall @[1] {
desc="get the new monitor data and stor it into the data table -- this does the main job here";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_netmon->GetMonVals()";
pre_compile_code_string="epoch_netmon->GetMonVals()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].vars["epoch_netmon"]$;
method=NetMonitor::GetMonVals;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void GetMonVals()";
meth_desc=" get all the values and store in current row of data table -- call in program to get new data";
};
AssignExpr @[2] {
desc="get the epoch timer from current network";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_timer = network.epoch_time";
pre_compile_code_string="epoch_timer = network.epoch_time";
result_var=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].vars["epoch_timer"]$;
expr {
expr="network.epoch_time";
};
};
MethodCall @[3] {
desc="update after writing new data to monitor data table";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_mon_data->WriteClose()";
pre_compile_code_string="epoch_mon_data->WriteClose()";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["LeabraEpochMonitor"].vars["epoch_mon_data"]$;
method=DataTable::WriteClose;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
};
meth_sig="void WriteClose()";
meth_desc=" closes up a write operation -- call when done writing data -- performs any post-writing cleanup/closing of files, etc";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["SaveWeights"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["SaveWeights"].doc$$;
};
};
name="SaveWeights";
short_nm="SWghts";
tags="Network, Weights";
desc="save network's current weight values to file using WriteWeights function, with file name based on project name + batch + epoch values";
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=NO_STOP_STEP;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=Network;
object_val=NULL;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc=;
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["tag"] {
name="tag";
var_type=T_String;
string_val=;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="user-provided tag (startup script will set this!)";
init_from=NULL;
};
ProgVar @["wts_subdir"] {
name="wts_subdir";
var_type=T_String;
string_val=;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="user-provided subdirectory to save weights in";
init_from=NULL;
};
ProgVar @["fname"] {
name="fname";
var_type=T_String;
string_val=;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="final generated file name -- do not edit!";
init_from=NULL;
};
ProgVar @["epoch_str"] {
name="epoch_str";
var_type=T_String;
string_val="0036";
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="string rep of epoch with leading zeros";
init_from=NULL;
};
ProgVar @["batch_str"] {
name="batch_str";
var_type=T_String;
string_val="03";
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="string rep of batch with leading zeros";
init_from=NULL;
};
ProgVar @["final_tag"] {
name="final_tag";
var_type=T_String;
string_val=".03_0036";
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc="batch + epoch";
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
IfReturn @[0] {
desc="do not save if not the first dmem process (only relevant for dmem = distributed memory processing)";
flags=CAN_REVERT_TO_CODE;
code_string="if(taMisc::dmem_proc > 0) return";
pre_compile_code_string="if(taMisc::dmem_proc > 0) return";
cond {
expr="taMisc::dmem_proc > 0";
};
};
MiscCall @[1] {
desc="get current batch counter for file name, with leading zeros to length 3";
flags=CAN_REVERT_TO_CODE;
code_string="batch_str = taMisc::LeadingZeros(network.batch, 2)";
pre_compile_code_string="batch_str = taMisc::LeadingZeros(network.batch, 2)";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["SaveWeights"].vars["batch_str"]$$;
object_type=taMisc;
method=taMisc::LeadingZeros;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=int;
type="int";
name="num";
required=1;
def_val=;
prev_expr=;
expr {
expr="network.batch";
};
};
ProgArg @[1] {
arg_type=int;
type="int";
name="len";
required=1;
def_val=;
prev_expr=;
expr {
expr="2";
};
};
};
};
MiscCall @[2] {
desc="get current epoch counter with leading zeros to length 4";
flags=CAN_REVERT_TO_CODE;
code_string="epoch_str = taMisc::LeadingZeros(network.epoch, 4)";
pre_compile_code_string="epoch_str = taMisc::LeadingZeros(network.epoch, 4)";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["SaveWeights"].vars["epoch_str"]$$;
object_type=taMisc;
method=taMisc::LeadingZeros;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=int;
type="int";
name="num";
required=1;
def_val=;
prev_expr=;
expr {
expr="network.epoch";
};
};
ProgArg @[1] {
arg_type=int;
type="int";
name="len";
required=1;
def_val=;
prev_expr=;
expr {
expr="4";
};
};
};
};
AssignExpr @[3] {
desc="string 'tag' to identify the batch, epoch, and other user id info for the weights";
flags=CAN_REVERT_TO_CODE;
code_string="final_tag = tag + \".\" + batch_str + \"_\" + epoch_str";
pre_compile_code_string="final_tag = tag + \".\" + batch_str + \"_\" + epoch_str";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["SaveWeights"].vars["final_tag"]$$;
expr {
expr="tag + \".\" + batch_str + \"_\" + epoch_str";
};
};
MethodCall @[4] {
desc="get a file name based on the project's current file name, for saving the weights";
flags=CAN_REVERT_TO_CODE;
code_string="fname = network->GetFileNameFmProject(\".wts.gz\", final_tag, wts_subdir, false)";
pre_compile_code_string="fname = network->GetFileNameFmProject(\".wts.gz\", final_tag, wts_subdir, false)";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["SaveWeights"].vars["fname"]$$;
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["SaveWeights"].args["network"]$$;
method=taBase::GetFileNameFmProject;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=const_taString_ref;
type="taString&";
name="ext";
required=1;
def_val=;
prev_expr=;
expr {
expr="\".wts.gz\"";
};
};
ProgArg @[1] {
arg_type=const_taString_ref;
type="taString&";
name="tag";
required=0;
def_val="\"\"";
prev_expr=;
expr {
expr="final_tag";
};
};
ProgArg @[2] {
arg_type=const_taString_ref;
type="taString&";
name="subdir";
required=0;
def_val="\"\"";
prev_expr=;
expr {
expr="wts_subdir";
};
};
ProgArg @[3] {
arg_type=bool;
type="bool";
name="dmem_proc_no";
required=0;
def_val="false";
prev_expr=;
expr {
expr="false";
};
};
};
meth_sig="taString GetFileNameFmProject(taString& ext, taString& tag, taString& subdir, bool dmem_proc_no = false)";
meth_desc=" get file name from project file name -- useful for saving files associated with the project; ext = extension; tag = additional tag; subdir = additional directory after any existing in project name; fname = proj->base_name (subdir) + tag + ext; if dmem_proc_no, add dmem proc no to file name. empty if project not found";
};
MethodCall @[5] {
desc="save the weights to that file name";
flags=CAN_REVERT_TO_CODE;
code_string="network->SaveWeights(fname, Network::NET_FMT)";
pre_compile_code_string="network->SaveWeights(fname, Network::NET_FMT)";
result_var=NULL;
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["SaveWeights"].args["network"]$;
method=Network::SaveWeights;
meth_args {
name=;
el_typ=ProgArg;
el_def=0;
ProgArg @[0] {
arg_type=const_taString_ref;
type="taString&";
name="fname";
required=0;
def_val="\"\"";
prev_expr=;
expr {
expr="fname";
};
};
ProgArg @[1] {
arg_type=Network::WtSaveFormat;
type="Network::WtSaveFormat";
name="fmt";
required=0;
def_val="Network::NET_FMT";
prev_expr=;
expr {
expr="Network::NET_FMT";
};
};
};
meth_sig="void SaveWeights(taString& fname, Network::WtSaveFormat fmt = NET_FMT)";
meth_desc=" write weight values out in a simple ordered list of weights (optionally in binary fmt) (leave fname empty to pull up file chooser)";
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
Program @["DA_Rew_Punish"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserData_DocLink;
el_def=0;
UserData_DocLink @["DocLink"] {
name="DocLink";
doc=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].doc$$;
};
};
name="DA_Rew_Punish";
short_nm="DRwPns";
tags=;
desc=;
version {
major=0;
minor=0;
step=0;
};
author=;
email=;
flags=0;
stop_step_cond {
expr=;
};
objs {
name="objs";
el_typ=taNBase;
el_def=0;
};
types {
name="types";
el_typ=DynEnumType;
el_def=0;
};
args {
name="args";
el_typ=ProgVar;
el_def=0;
ProgVar @["network"] {
name="network";
var_type=T_Object;
object_type=LeabraNetwork;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL|PGRM_ARG;
reference=0;
desc="network to train";
init_from=NULL;
};
ProgVar @["input_data"] {
name="input_data";
var_type=T_Object;
object_type=DataTable;
object_val=$.projects["BG_WeatherPred_inhib_e7"].data.gp["InputData"]["TestWP_Optimal"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|EDIT_VAL|PGRM_ARG;
reference=0;
desc="datatable with training patterns";
init_from=NULL;
};
};
vars {
name="vars";
el_typ=ProgVar;
el_def=0;
ProgVar @["num_intact_snc_units"] {
name="num_intact_snc_units";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["active_da_units"] {
name="active_da_units";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["snc_size"] {
name="snc_size";
var_type=T_Int;
int_val=4;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["k"] {
name="k";
var_type=T_Real;
real_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["sse"] {
name="sse";
var_type=T_Real;
real_val=0.9595006704330444;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["act0"] {
name="act0";
var_type=T_Real;
real_val=0.4079793691635132;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["act1"] {
name="act1";
var_type=T_Real;
real_val=0.3317588567733765;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["SNc"] {
name="SNc";
var_type=T_Object;
object_type=LeabraLayer;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["SNc"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["Output"] {
name="Output";
var_type=T_Object;
object_type=LeabraLayer;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["Output"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["Motor_Cortex"] {
name="Motor_Cortex";
var_type=T_Object;
object_type=LeabraLayer;
object_val=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].layers["Motor_Cortex"]$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["matrisom_unitspec"] {
name="matrisom_unitspec";
var_type=T_Object;
object_type=LeabraUnitSpec;
object_val=.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"].specs.gp["Units"]["FixedBiasUnitSpec"].children["LearnBiasUnitSpec"].children["matrisom_unitspec"]$$;
objs_ptr=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["i"] {
name="i";
var_type=T_Int;
int_val=4;
flags=NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["tonic_DA"] {
name="tonic_DA";
var_type=T_Real;
real_val=0.026;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["op_sse"] {
name="op_sse";
var_type=T_Int;
int_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["DA_dip_val"] {
name="DA_dip_val";
var_type=T_Real;
real_val=0;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
ProgVar @["DA_burst_val"] {
name="DA_burst_val";
var_type=T_Real;
real_val=1;
flags=CTRL_PANEL|NULL_CHECK|SAVE_VAL|USED|EDIT_VAL;
reference=0;
desc=;
init_from=NULL;
};
};
functions {
name="functions";
el_typ=Function;
el_def=0;
};
init_code {
name="init_code";
el_typ=ProgCode;
el_def=0;
};
prog_code {
name="prog_code";
el_typ=ProgCode;
el_def=0;
AssignExpr @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="snc_size = SNc.units.size";
pre_compile_code_string="snc_size = SNc.units.size";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["snc_size"]$$;
expr {
expr="SNc.units.size";
};
};
AssignExpr @[1] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="k = (float)num_intact_snc_units/ snc_size";
pre_compile_code_string="k = (float)num_intact_snc_units/ snc_size";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["k"]$$;
expr {
expr="(float)num_intact_snc_units/ snc_size";
};
};
AssignExpr @[2] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="sse = network.sse";
pre_compile_code_string="sse = network.sse";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["sse"]$$;
expr {
expr="network.sse";
};
};
ForLoop @[3] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="for (i = 0; i < snc_size; i++)";
pre_compile_code_string="for (i = 0; i < snc_size; i++)";
loop_code {
name="ProgEl_List_177";
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="set DA value to 0, then update for intact units after";
flags=CAN_REVERT_TO_CODE;
code_string="SNc.units[i].ext = 0";
pre_compile_code_string="SNc.units[i].ext = 0";
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["SNc"]$$;
path="units[i].ext";
expr {
expr="0";
};
update_after=0;
};
};
init {
expr="i = 0";
};
test {
expr="i < snc_size";
};
iter {
expr="i++";
};
};
If @[4] {
desc="apply phasic DA in plus phase";
flags=CAN_REVERT_TO_CODE;
code_string="if (network.phase==LeabraNetwork::PLUS_PHASE)";
pre_compile_code_string="if (network.phase==LeabraNetwork::PLUS_PHASE)";
cond {
expr="network.phase==LeabraNetwork::PLUS_PHASE";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
If @[0] {
desc="if error is below threshold, given DA burst";
flags=CAN_REVERT_TO_CODE;
code_string="if (k>0&&Output.sse<0.5)";
pre_compile_code_string="if (k>0&&Output.sse<0.5)";
cond {
expr="k>0&&Output.sse<0.5";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
ForLoop @[0] {
desc="loop over snc units";
flags=CAN_REVERT_TO_CODE;
code_string="for (i = 0; i < active_da_units; i++)";
pre_compile_code_string="for (i = 0; i < active_da_units; i++)";
loop_code {
name=;
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="set external input on SNC to high value for DA burst";
flags=CAN_REVERT_TO_CODE;
code_string="SNc.units[i].ext = DA_burst_val";
pre_compile_code_string="SNc.units[i].ext = DA_burst_val";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["SNc"]$;
path="units[i].ext";
expr {
expr="DA_burst_val";
};
update_after=0;
};
};
init {
expr="i = 0";
};
test {
expr="i < active_da_units";
};
iter {
expr="i++";
};
};
MemberAssign @[1] {
desc="set striatal gain in proportion to DA and # intact Snc units (contrast enhancement with DA)";
flags=CAN_REVERT_TO_CODE;
code_string="matrisom_unitspec.act.gain = k*10000";
pre_compile_code_string="matrisom_unitspec.act.gain = k*10000";
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["matrisom_unitspec"]$$;
path="act.gain";
expr {
expr="k*10000";
};
update_after=0;
};
};
};
Else @[1] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="else";
pre_compile_code_string="else";
else_code {
name="else_code";
el_typ=ProgCode;
el_def=0;
ForLoop @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="for (i = 0; i < active_da_units; i++)";
pre_compile_code_string="for (i = 0; i < active_da_units; i++)";
loop_code {
name="loop_code";
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="set DA units to 0 for DA dip";
flags=CAN_REVERT_TO_CODE;
code_string="SNc.units[i].ext = DA_dip_val";
pre_compile_code_string="SNc.units[i].ext = DA_dip_val";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["SNc"]$;
path="units[i].ext";
expr {
expr="DA_dip_val";
};
update_after=0;
};
};
init {
expr="i = 0";
};
test {
expr="i < active_da_units";
};
iter {
expr="i++";
};
};
MemberAssign @[1] {
desc="set striatal gain to be lower for DA dip (less D1 contrast enhancement)";
flags=CAN_REVERT_TO_CODE;
code_string="matrisom_unitspec.act.gain = 600-k*300";
pre_compile_code_string="matrisom_unitspec.act.gain = 600-k*300";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["matrisom_unitspec"]$;
path="act.gain";
expr {
expr="600-k*300";
};
update_after=0;
};
};
};
AssignExpr @[2] {
desc="store minus phase activation of motor ctx unit 0";
flags=CAN_REVERT_TO_CODE;
code_string="act0 = Motor_Cortex.units[0].act_m";
pre_compile_code_string="act0 = Motor_Cortex.units[0].act_m";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["act0"]$$;
expr {
expr="Motor_Cortex.units[0].act_m";
};
};
AssignExpr @[3] {
desc="store minus phase act of motor unit 1";
flags=CAN_REVERT_TO_CODE;
code_string="act1 = Motor_Cortex.units[1].act_m";
pre_compile_code_string="act1 = Motor_Cortex.units[1].act_m";
result_var=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["act1"]$$;
expr {
expr="Motor_Cortex.units[1].act_m";
};
};
ForLoop @[4] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="for (i = 0; i < 4; i++)";
pre_compile_code_string="for (i = 0; i < 4; i++)";
loop_code {
name="ProgEl_List_189";
el_typ=ProgCode;
el_def=0;
CssExpr @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex->units[i].bias.SetCnValName(0,0,\"wt\");";
pre_compile_code_string="Motor_Cortex->units[i].bias.SetCnValName(0,0,\"wt\");";
expr {
expr="Motor_Cortex->units[i].bias.SetCnValName(0,0,\"wt\");";
};
};
};
init {
expr="i = 0";
};
test {
expr="i < 4";
};
iter {
expr="i++";
};
};
If @[5] {
desc="if model selected R1, clamp that same choice on motor cortex in plus phase so that BG can learn about it";
flags=CAN_REVERT_TO_CODE;
code_string="if (act0>act1)";
pre_compile_code_string="if (act0>act1)";
cond {
expr="act0>act1";
};
true_code {
name=;
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="set plus phase acts to reflect minus phase response";
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex.units[0].ext = 1.0";
pre_compile_code_string="Motor_Cortex.units[0].ext = 1.0";
obj=.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["Motor_Cortex"]$$;
path="units[0].ext";
expr {
expr="1.0";
};
update_after=0;
};
MemberAssign @[1] {
desc="set plus phase acts to reflect minus phase response";
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex.units[1].ext = 0.0";
pre_compile_code_string="Motor_Cortex.units[1].ext = 0.0";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["Motor_Cortex"]$;
path="units[1].ext";
expr {
expr="0.0";
};
update_after=0;
};
MemberAssign @[2] {
desc="set plus phase acts to reflect minus phase response";
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex.units[2].ext = 1.0";
pre_compile_code_string="Motor_Cortex.units[2].ext = 1.0";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["Motor_Cortex"]$;
path="units[2].ext";
expr {
expr="1.0";
};
update_after=0;
};
MemberAssign @[3] {
desc="set plus phase acts to reflect minus phase response";
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex.units[3].ext = 0";
pre_compile_code_string="Motor_Cortex.units[3].ext = 0";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["Motor_Cortex"]$;
path="units[3].ext";
expr {
expr="0";
};
update_after=0;
};
CssExpr @[4] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex->units[0].bias.SetCnValName(10,0,\"wt\");";
pre_compile_code_string="Motor_Cortex->units[0].bias.SetCnValName(10,0,\"wt\");";
expr {
expr="Motor_Cortex->units[0].bias.SetCnValName(10,0,\"wt\");";
};
};
CssExpr @[5] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex->units[2].bias.SetCnValName(10,0,\"wt\");";
pre_compile_code_string="Motor_Cortex->units[2].bias.SetCnValName(10,0,\"wt\");";
expr {
expr="Motor_Cortex->units[2].bias.SetCnValName(10,0,\"wt\");";
};
};
};
};
Else @[6] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="else";
pre_compile_code_string="else";
else_code {
name="else_code";
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="set plus phase acts to reflect minus phase response";
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex.units[0].ext = 0";
pre_compile_code_string="Motor_Cortex.units[0].ext = 0";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["Motor_Cortex"]$;
path="units[0].ext";
expr {
expr="0";
};
update_after=0;
};
MemberAssign @[1] {
desc="set plus phase acts to reflect minus phase response";
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex.units[1].ext = 1.0";
pre_compile_code_string="Motor_Cortex.units[1].ext = 1.0";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["Motor_Cortex"]$;
path="units[1].ext";
expr {
expr="1.0";
};
update_after=0;
};
MemberAssign @[2] {
desc="set plus phase acts to reflect minus phase response";
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex.units[2].ext = 0";
pre_compile_code_string="Motor_Cortex.units[2].ext = 0";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["Motor_Cortex"]$;
path="units[2].ext";
expr {
expr="0";
};
update_after=0;
};
MemberAssign @[3] {
desc="set plus phase acts to reflect minus phase response";
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex.units[3].ext = 1.0";
pre_compile_code_string="Motor_Cortex.units[3].ext = 1.0";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["Motor_Cortex"]$;
path="units[3].ext";
expr {
expr="1.0";
};
update_after=0;
};
CssExpr @[4] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex->units[1].bias.SetCnValName(10,0,\"wt\");";
pre_compile_code_string="Motor_Cortex->units[1].bias.SetCnValName(10,0,\"wt\");";
expr {
expr="Motor_Cortex->units[1].bias.SetCnValName(10,0,\"wt\");";
};
};
CssExpr @[5] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex->units[3].bias.SetCnValName(10,0,\"wt\");";
pre_compile_code_string="Motor_Cortex->units[3].bias.SetCnValName(10,0,\"wt\");";
expr {
expr="Motor_Cortex->units[3].bias.SetCnValName(10,0,\"wt\");";
};
};
};
};
};
};
Else @[5] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="else";
pre_compile_code_string="else";
else_code {
name="else_code";
el_typ=ProgCode;
el_def=0;
ForLoop @[0] {
desc="loop over snc units";
flags=CAN_REVERT_TO_CODE;
code_string="for (i = 0; i < active_da_units; i++)";
pre_compile_code_string="for (i = 0; i < active_da_units; i++)";
loop_code {
name="loop_code";
el_typ=ProgCode;
el_def=0;
MemberAssign @[0] {
desc="set tonic DA val";
flags=CAN_REVERT_TO_CODE;
code_string="SNc.units[i].ext = tonic_DA";
pre_compile_code_string="SNc.units[i].ext = tonic_DA";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["SNc"]$;
path="units[i].ext";
expr {
expr="tonic_DA";
};
update_after=0;
};
MemberAssign @[1] {
desc="set striatal gain in proportion to DA and # intact Snc units";
flags=CAN_REVERT_TO_CODE;
code_string="matrisom_unitspec.act.gain = k*2500";
pre_compile_code_string="matrisom_unitspec.act.gain = k*2500";
obj=$.projects["BG_WeatherPred_inhib_e7"].programs.gp["LeabraAll_Std"]["DA_Rew_Punish"].vars["matrisom_unitspec"]$;
path="act.gain";
expr {
expr="k*2500";
};
update_after=0;
};
};
init {
expr="i = 0";
};
test {
expr="i < active_da_units";
};
iter {
expr="i++";
};
};
ForLoop @[1] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="for (i = 0; i < 4; i++)";
pre_compile_code_string="for (i = 0; i < 4; i++)";
loop_code {
name="loop_code";
el_typ=ProgCode;
el_def=0;
CssExpr @[0] {
desc=;
flags=CAN_REVERT_TO_CODE;
code_string="Motor_Cortex->units[i].bias.SetCnValName(0,0,\"wt\");";
pre_compile_code_string="Motor_Cortex->units[i].bias.SetCnValName(0,0,\"wt\");";
expr {
expr="Motor_Cortex->units[i].bias.SetCnValName(0,0,\"wt\");";
};
};
};
init {
expr="i = 0";
};
test {
expr="i < 4";
};
iter {
expr="i++";
};
};
};
};
};
step_prog=NULL;
step_n=1;
doc {
name="doc";
desc=;
web_doc=0;
wiki=;
url="local";
full_url="local";
text_size=1;
text=;
html_text=;
};
};
};
};
viewers {
name="viewers";
el_typ=MainWindowViewer;
el_def=0;
MainWindowViewer @["Browser"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_win_lft"] {
name="view_win_lft";
value 8 0=0;
val_type_fixed=0;
};
UserDataItem @["view_win_top"] {
name="view_win_top";
value 8 0=0.1749095;
val_type_fixed=0;
};
UserDataItem @["view_win_wd"] {
name="view_win_wd";
value 8 0=0.9826389;
val_type_fixed=0;
};
UserDataItem @["view_win_ht"] {
name="view_win_ht";
value 8 0=0.7937274;
val_type_fixed=0;
};
UserDataItem @["view_win_iconified"] {
name="view_win_iconified";
value 1 0=0;
val_type_fixed=0;
};
UserDataItem @["view_splitter_state"] {
name="view_splitter_state";
value 9 0="AAAA/wAAAAEAAAADAAABZAAAAaIAAAIoAQAAAAYBAAAAAQE=";
val_type_fixed=0;
};
};
name="Browser";
m_data=.projects["BG_WeatherPred_inhib_e7"]$$;
cur_font_size=12;
visible=1;
win_name=".projects[\"BG_WeatherPred_inhib_e7\"] - BG_WeatherPred_inhib_e7.proj";
m_is_root=0;
m_is_viewer_xor_browser=0;
m_is_proj_viewer=1;
m_is_dialog=0;
toolbars {
name="toolbars";
el_typ=ToolBar;
el_def=0;
ToolBar @["Application"] {
UserDataItem_List @*(.user_data_) {
name=;
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_win_visible"] {
name="view_win_visible";
value 1 0=1;
val_type_fixed=0;
};
};
name="Application";
m_data=NULL;
cur_font_size=12;
visible=0;
lft=0;
top=0;
o=Horizontal;
};
};
frames {
name="frames";
el_typ=BrowseViewerTaBase;
el_def=0;
BrowseViewerTaBase @["Navigator"] {
name="Navigator";
m_data=NULL;
cur_font_size=12;
visible=1;
root_typ=LeabraProject;
root_md=NULL;
m_root=$.projects["BG_WeatherPred_inhib_e7"]$;
};
PanelViewer @["Editor"] {
name="Editor";
m_data=NULL;
cur_font_size=12;
visible=1;
};
T3PanelViewer @["T3Frames"] {
UserDataItem_List @*(.user_data_) {
name="UserDataItem_List_215";
el_typ=UserDataItem;
el_def=0;
UserDataItem @["view_panel_selected"] {
name="view_panel_selected";
value 1 0=1;
val_type_fixed=0;
};
};
name="T3Frames";
m_data=NULL;
cur_font_size=12;
visible=1;
panels {
name="panels";
el_typ=T3Panel;
el_def=0;
T3Panel @["BGnet"] {
name="BGnet";
m_data=NULL;
cur_font_size=12;
visible=1;
root_view {
name="root_view";
m_data=NULL;
cur_font_size=12;
m_transform=NULL;
children {
name="children";
el_typ=NetView;
el_def=0;
NetView @["BGNet_View"] {
name="BGNet_View";
m_data=$.projects["BG_WeatherPred_inhib_e7"].networks["BGNet"]$;
cur_font_size=12;
taTransform @*(.m_transform) {scale={x=0.962418: y=0.9624187: z=0.9624187: }: rotate={x=1: y=0: z=0: rot=0.35: }: translate={x=3.067723e-8: y=-9.349009e-9: z=2.074376e-8: }: };
main_xform {scale={x=0.962418: y=0.9624187: z=0.9624187: }: rotate={x=1: y=0: z=0: rot=0.35: }: translate={x=3.067723e-8: y=-9.349009e-9: z=2.074376e-8: }: };
annotations {
name="annotations";
el_typ=T3Annotation;
el_def=0;
};
annote_children {
name="annote_children";
el_typ=T3DataView;
el_def=0;
};
display=1;
lay_layout=THREE_D;
lay_mv=1;
net_text=1;
show_iconified=0;
net_text_xform {scale={x=0: y=0: z=0: }: rotate={x=1: y=0: z=0: rot=0: }: translate={x=0: y=-0.5: z=0: }: };
net_text_rot=0;
cur_unit_vals{ act; };
unit_src_path=".layers.gp[0][1].units[2]";
con_type=ANY_CON;
hist_idx=0;
hist_save=1;
hist_max=100;
hist_ff=5;
unit_disp_mode=UDM_CYLINDER;
unit_text_disp=UTD_NONE;
max_size {x=14: y=9: z=13.07143: };
max_size2d {x=10: y=38: z=1: };
eff_max_size {x=14: y=9: z=13.07143: };
font_sizes {
net_name=0.05;
net_vals=0.05;
layer=0.045;
layer_min=0.01;
layer_vals=0.03;
prjn=0.01;
unit=0.0185;
un_nm_len=3;
};
view_params {
xy_square=0;
unit_spacing=0.05;
prjn_disp=L_R_F;
prjn_name=0;
prjn_width=0.0014;
prjn_trans=0.5;
lay_trans=0.4;
unit_trans=0.4;
laygp_width=1;
show_laygp=1;
};
wt_line_disp=0;
wt_line_width=3;
wt_line_thr=0.5;
wt_line_swt=1;
wt_prjn_k_un=4;
wt_prjn_k_gp=1;
wt_prjn_lay=NULL;
snap_bord_disp=0;
snap_bord_width=4;
scale {
name="scale";
chunks=133;
min=-1;
max=1;
last_min=0;
last_max=0;
range=1;
zero=0;
spec=.colorspecs["C_ColdHot"]$$