generate_graphs_autocorr works from the command line

fixed a bug in mcmc.py where it did not count the number of new variables when using transforms like keq (this makes it so isotherm MCMC should work correctly now)
set the names correctly for the input_headers for autocorr graphs

.gitignore

@@ -325,3 +325,4 @@ __pycache__/
 /Examples/MCMC/Dextran/nsga3_mcmc_6_emcee12_new
 /Examples/MCMC/Dextran/nsga3_mcmc_6_emcee6_new
 /Examples/MCMC/NonBinding/fit_delay
+/Examples/MCMC/Linear/fit

CADETMatch.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: CADETMatch
-Version: 0.5.26
+Version: 0.5.27
 Summary: CADETMatch is a parameter estimation and error modeling library for CADET
 Home-page: https://github.com/modsim/CADET-Match
 Author: William Heymann

CADETMatch.egg-info/SOURCES.txt

@@ -11,6 +11,7 @@ CADETMatch/de_snooker.py
 CADETMatch/evo.py
 CADETMatch/fitness.py
 CADETMatch/ga_simple.py
+CADETMatch/generate_autocorr_graphs.py
 CADETMatch/generate_corner_graphs.py
 CADETMatch/generate_graphs.py
 CADETMatch/grad.py

CADETMatch/CADETMatch.pyproj

@@ -4,7 +4,7 @@
     <SchemaVersion>2.0</SchemaVersion>
     <ProjectGuid>0067cb6f-0de6-4dd6-8086-20ea899a691d</ProjectGuid>
     <ProjectHome>.</ProjectHome>
-    <StartupFile>generate_autocorr_graphs.py</StartupFile>
+    <StartupFile>match.py</StartupFile>
     <SearchPath>
     </SearchPath>
     <WorkingDirectory>..</WorkingDirectory>
@@ -14,7 +14,7 @@
     <IsWindowsApplication>False</IsWindowsApplication>
     <InterpreterId>CondaEnv|CondaEnv|CADETMatch</InterpreterId>
     <LaunchProvider>Standard Python launcher</LaunchProvider>
-    <CommandLineArguments>"C:\Users\kosh_000\Documents\Visual Studio 2017\Projects\CADETMatch\Examples\MCMC\Dextran\nsga3_mcmc_6_emcee12_new\mcmc_refine\MCMC_dextran_nsga3.json" 1</CommandLineArguments>
+    <CommandLineArguments>"C:\Users\kosh_000\Documents\Visual Studio 2017\Projects\CADETMatch\Examples\MCMC\Linear\fit\mcmc_refine\MCMC_linear.json" 6</CommandLineArguments>
     <EnableNativeCodeDebugging>False</EnableNativeCodeDebugging>
     <InterpreterArguments>
     </InterpreterArguments>

CADETMatch/__main__.py

@@ -81,7 +81,7 @@ def run_command(module, json, number_of_jobs, additional=None):
     if args.generate_corner:
         sys.exit(run_command('CADETMatch.generate_corner_graphs', args.json, args.n))
     if args.generate_graphs_autocorr:
-        sys.exit(run_command('CADETMatch.generate_graphs_autocorr', args.json, args.n))
+        sys.exit(run_command('CADETMatch.generate_autocorr_graphs', args.json, args.n))
     if args.generate_graphs:
         sys.exit(run_command('CADETMatch.generate_graphs', args.json, args.n, ['1']))
     if args.generate_graphs_all:

CADETMatch/generate_autocorr_graphs.py

@@ -80,7 +80,7 @@ def main(map_function):
 
         graph_dir = cache.settings['resultsDirSpace'] / "mcmc"
 
-        input_headers = cache.parameter_headers
+        input_headers = cache.parameter_headers_actual
 
         for chain in ("full_chain", "train_full_chain", "bounds_full_chain"):
             if chain in mcmc_store.root:

CADETMatch/search/mcmc.py

@@ -279,7 +279,15 @@ def sampler_auto_bounds(cache, checkpoint, sampler, checkpointFile, mcmc_store):
 
     parameters = len(cache.MIN_VALUE)
 
-    new_parameters = len(cache.settings['parameters']) - len(cache.settings.get('parameters_mcmc', []))
+    if 'mcmc_h5' in cache.settings:
+        data = cadet.H5()
+        data.filename = cache.settings['mcmc_h5']
+        data.load(paths='/bounds_change/center_trans')
+        previous_parameters = data.root.bounds_change.center_trans.shape[1]
+    else:
+        previous_parameters = 0
+
+    new_parameters = parameters - previous_parameters
 
     finished = False
 
@@ -324,6 +332,7 @@ def sampler_auto_bounds(cache, checkpoint, sampler, checkpointFile, mcmc_store):
             converged, lb, ub = converged_bounds(bounds_chain[:,:,:new_parameters], 200, 1e-3)
 
             if converged:
+                #sys.exit()
                 finished = True
 
                 new_min_value, center, new_max_value = rescale(cache, lb, ub, numpy.array(cache.MIN_VALUE), numpy.array(cache.MAX_VALUE), mcmc_store)

Examples/MCMC/Linear/MCMC_linear.json

@@ -4,15 +4,37 @@
   "resultsDir": "fit/",
   "CSV": "linear_MCMC.csv",
   "checkpointFile": "check",
-  "searchMethod": "MCMC",
-  "population": 100,
-  "roundParameters": 6,
-  "roundScores": 6,
+  "stopAverage": 1.1,
+  "stopBest": 1.1,
+  "gradCheck": 1.1,
+  "gradVector": 1,
+  "searchMethod": "NSGA3",
+  "mutationRate": 1.0,
+  "crossoverRate": 1.0,
+  "generations": 1000,
+  "population": 24,
   "metaResultsOnly": 1,
   "sobolGeneration":1,
-  "scoreMCMC":"score",
-  "graphSpearman": 0,
+  "stallGenerations": 50,
   "normalizeOutput":1,
+  "graphMetaTime": 600,
+  "finalGradRefinement": 1,
+  "continueMCMC": 1,
+  "MCMCpopulationSet": 24,
+  "kde_synthetic": [
+		{
+			"file_path": "linear_pulse.h5",
+			"experimental_csv": "linear_pulse.csv",
+			"name": "main",
+			"units": [2],
+            "delay": [0.0, 2.0],
+            "flow": [1.0,0.007],
+            "load": [1.0,0.007],
+            "uv_noise": [0.0,1e-8],
+            "base": 100.0,
+            "count": 4000
+		}
+	],
 	"parameters": [
 		{
 			"transform": "norm_keq",
@@ -30,19 +52,15 @@
 	],
 	"experiments": [
 		{
-			"CSV": "F:/CADET_ParameterEstimation/adsorption/lrmp/linear/linear_pulse.csv",
+			"CSV": "linear_pulse.csv",
 			"isotherm": "/output/solution/unit_001/SOLUTION_OUTLET_COMP_000",
-			"HDF5": "F:/CADET_ParameterEstimation/adsorption/lrmp/linear/linear_pulse.h5",
+			"HDF5": "linear_pulse.h5",
 			"name": "main",
 			"timeout": 3.785061836242676,
 			"features": [
 				{
 					"name": "Pulse",
-					"type": "similarityHybrid2"
-				},
-				{
-					"name": "Deriv",
-					"type": "derivative_similarity_hybrid2"
+					"type": "ShapeDecay"
 				}
 			]
 		}