updated script to plot true process posterior across multiple tempera…

…tures and pressures and deleted unneeded comment on test 9

linfa/plot_disc.py

@@ -4,6 +4,8 @@
 import numpy as np
 import os
 import argparse
+from numpy import random
+import array
 
 def scale_limits(min,max,factor):
  if(min>max):
@@ -14,21 +16,69 @@ def scale_limits(min,max,factor):
  range = max - min
  return center - factor*0.5*range, center + factor*0.5*range
 
-def plot_disr_histograms(lf_file,lf_dicr_file,lf_discr_noise_file):
+def plot_disr_histograms(lf_file, lf_dicr_file, lf_discr_noise_file, data_file, sample_size = 500):
 
  # Read result files
  lf_model = np.loadtxt(lf_file)
  lf_model_plus_disc = np.loadtxt(lf_dicr_file)
  lf_model_plus_disc_plus_noise = np.loadtxt(lf_discr_noise_file)
+ data = np.loadtxt(data_file)
 
- # Plot histograms
- plt.hist(lf_model, label = 'LF', alpha =0.5)
- plt.hist(lf_model_plus_disc, label = 'LF + disc', alpha =0.5)
- plt.hist(lf_model_plus_disc_plus_noise, label = 'LF + disc + noise', alpha = 0.5)
- plt.xlabel('Coverage')
- plt.ylabel('Frequency')
- plt.legend()
- plt.show()
+ # Check for multiple TP-pairs
+ ## shape : no. var inputs pairs x no. batches
+ num_dim = len(np.shape(lf_model))
+
+ if num_dim == 1:
+ # Plot histograms
+ plt.hist(lf_model, label = 'LF', alpha = 0.5, density = True)
+ plt.hist(lf_model_plus_disc, label = 'LF + disc', alpha = 0.5, density = True)
+ plt.hist(lf_model_plus_disc_plus_noise, label = 'LF + disc + noise', alpha = 0.5, density = True)
+ plt.xlabel('Coverage')
+ plt.ylabel('Density')
+ plt.legend()
+ plt.show()
+
+ else:
+
+ batch_size = len(lf_model_plus_disc[0])
+ temps = np.unique(data[:, 0])
+ pressures = np.unique(data[:, 1])
+
+ ## Prepare for random sampling of batches
+ lf_model_plus_disc = lf_model_plus_disc.reshape(len(temps), len(pressures), batch_size)
+ random_array = np.random.randint(low = 0, high = batch_size, size = sample_size) # Randomly sample batch numbers without replacement
+ sample = np.zeros([len(temps), len(pressures), sample_size]) # Initialize
+
+ # For plotting
+ clrs = ['b', 'm', 'r'] # Line colors for each temperature
+ lines = [] # List to store Line2D objects for legend lines
+
+ # Loop over temperatures
+ for loopA, temp in enumerate(temps):
+
+ # Loop over pressures
+ for loopB, pressure in enumerate(pressures):
+
+ # Evalute random sample of true process posterior
+ sample[loopA, loopB] = lf_model_plus_disc[loopA, loopB, random_array]
+
+ # Plot function & save line properties for legend
+ line = plt.plot(np.tile(pressures, (sample_size, 1)).transpose(),
+ sample[loopA],
+ linewidth=0.05,
+ color=clrs[loopA])[0]
+ lines.append(line)
+
+ # Manually create the legend with custom linewidth
+ legend = plt.legend(lines, ['{} K'.format(temp) for temp in temps])
+
+ # Set the linewidth for the legend lines
+ for line in legend.get_lines():
+ line.set_linewidth(2.0) # Adjust the linewidth as needed
+
+ plt.xlabel('Pressure, [Pa]')
+ plt.ylabel('Coverage, [ ]')
+ plt.show()
 
 def plot_discr_surface_2d(file_path,data_file,num_1d_grid_points,data_limit_factor):
 
@@ -217,7 +267,7 @@ def eval_discrepancy_custom_grid(file_path,train_grid_in,train_grid_out,test_gri
  # out_info = args.exp_name + '_' + str(args.step_num)
 
  if(args.result_mode == 'histograms'):
- plot_disr_histograms(lf_file,lf_dicr_file,lf_discr_noise_file)
+ plot_disr_histograms(lf_file,lf_dicr_file,lf_discr_noise_file,data_file)
  elif(args.result_mode == 'discr_surface'):
  plot_discr_surface_2d(discr_sur_file,data_file,args.num_1d_grid_points,args.data_limit_factor)
  else:

linfa/tests/test_discr_09_prior_TP15.py

@@ -24,7 +24,7 @@ def run_test():
  exp.input_size = 2 # int: Dimensionalty of input (default 2)
  exp.batch_size = 200 # int: Number of samples generated (default 100)
  exp.true_data_num = 2 # double: Number of true model evaluted (default 2)
- exp.n_iter = 25001 # int: Number of iterations (default 25001)
+ exp.n_iter = 2501 # int: Number of iterations (default 25001)
  exp.lr = 0.001 # float: Learning rate (default 0.003)
  exp.lr_decay = 0.9999 # float: Learning rate decay (default 0.9999)
  exp.log_interal = 10 # int: How often to show loss stat (default 10)

linfa/tests/test_plot_discr.sh

@@ -1,16 +1,16 @@
  # discr_surface
-# python3 -m linfa.plot_disc --folder results/ \
-# --name test_lf_with_disc_hf_data_prior_TP15 \
-# --iter 2000 \
-# --mode histograms \
-# --num_points 10 \
-# --limfactor 1.0 \
-
-
-
 python3 -m linfa.plot_disc --folder results/ \
  --name test_lf_with_disc_hf_data_prior_TP15 \
  --iter 2000 \
- --mode discr_surface \
- --num_points 40 \
- --limfactor 2.0 \
+ --mode histograms \
+ --num_points 10 \
+ --limfactor 1.0 \
+
+
+
+# python3 -m linfa.plot_disc --folder results/ \
+# --name test_lf_with_disc_hf_data_prior_TP15 \
+# --iter 2000 \
+# --mode discr_surface \
+# --num_points 40 \
+# --limfactor 2.0 \