fix some plotting errors

Author: mathematicalmichael

src/mud_examples/experiments.py

@@ -122,19 +122,21 @@ def plot_experiment_equipment(tolerances, res, prefix, fsize=32, linewidth=5,
         plt.show()
 
 
-def plot_experiment_measurements(measurements, res, prefix,
+def plot_experiment_measurements(res, prefix,
                                  fsize=32, linewidth=5,
                                  xlabel='Number of Measurements',
                                  save=True, legend=False):
     print("Plotting experiments involving increasing # of measurements.")
     plt.figure(figsize=(10, 10))
     for _res in res:
         _prefix, _in, _rm, _re = _res
+        solutions = _in[-1]
+        measurements = list(solutions.keys())
         regression_mean, slope_mean, \
             regression_vars, slope_vars, \
             means, variances = _rm
         plt.plot(measurements[:len(regression_mean)], regression_mean,
-                 label=f"{_prefix:10s} slope: {slope_mean:1.4f}",
+                 label=f"{_prefix:4s} slope: {slope_mean:1.4f}",
                  lw=linewidth)
         plt.scatter(measurements[:len(means)], means, marker='x', lw=20)
     plt.xscale('log')
@@ -163,7 +165,7 @@ def plot_experiment_measurements(measurements, res, prefix,
             regression_vars, slope_vars, \
             means, variances = _rm
         plt.plot(measurements[:len(regression_vars)], regression_vars,
-                 label=f"{_prefix:10s} slope: {slope_vars:1.4f}",
+                 label=f"{_prefix:4s} slope: {slope_vars:1.4f}",
                  lw=linewidth)
         plt.scatter(measurements[:len(variances)], variances,
                     marker='x', lw=20)
@@ -172,7 +174,7 @@ def plot_experiment_measurements(measurements, res, prefix,
     plt.Axes.set_aspect(plt.gca(), 1)
 #     if not len(np.unique(variances)) == 1:
 #         plt.ylim(0.9 * min(variances), 1.3 * max(variances))
-    plt.ylim(1E-5, 1E-3)
+    plt.ylim(5E-6, 5E-4)
     plt.xlabel(xlabel, fontsize=fsize)
     if legend:
         plt.legend(fontsize=fsize * 0.8)

src/mud_examples/ode.py

@@ -63,7 +63,7 @@ def main_ode(num_trials=20,
 
     for example in example_list:
         print(f"Running example: {example}")
-        if example == 'ode-mud-alt':
+        if example == 'mud-alt':
             sensors = generate_sensors_ode(measurement_hertz=200, start_time=t_min, end_time=t_max)
         else:
             sensors = generate_sensors_ode(measurement_hertz=100, start_time=t_min, end_time=t_max)
@@ -79,15 +79,16 @@ def main_ode(num_trials=20,
         lam = np.random.rand(int(1E3)).reshape(-1,1)
         qoi = model(lam)
 
-        if example == 'ode-map':
+        if example == 'map':
             def wrapper(num_obs, sd):
                 return map_problem(domain=domain, lam=lam, qoi=qoi,
                                    sd=sd, qoi_true=qoi_true, num_obs=num_obs)
-        else:
+        elif example == 'mud':
             def wrapper(num_obs, sd):
                 return mud_problem(domain=domain, lam=lam, qoi=qoi,
                                    sd=sd, qoi_true=qoi_true, num_obs=num_obs)
-
+        else:
+            raise ValueError("Unknown example type")
 
         _logger.info("Increasing Measurements Quantity Study")
         experiments, solutions = experiment_measurements(num_measurements=measurements,
@@ -97,8 +98,8 @@ def wrapper(num_obs, sd):
                                                  fun=wrapper)
 
         means, variances = extract_statistics(solutions, lam_true)
-        regression_mean, slope_mean = fit_log_linear_regression(time_ratios, means)
-        regression_vars, slope_vars = fit_log_linear_regression(time_ratios, variances)
+        regression_mean, slope_mean = fit_log_linear_regression(measurements, means)
+        regression_vars, slope_vars = fit_log_linear_regression(measurements, variances)
 
         ##########
 
@@ -123,7 +124,7 @@ def wrapper(num_obs, sd):
         # TO DO clean all this up
         _in = (lam, qoi, sensors, qoi_true, experiments, solutions)
         _rm = (regression_mean, slope_mean, regression_vars, slope_vars, means, variances)
-        example_name = '-'.join(example.split('-')[1:]).upper()
+        example_name = example.upper()
         res.append((example_name, _in, _rm, _re))
 
         # TODO check for existence of save directory, grab subset of measurements properly.

src/mud_examples/runner.py

@@ -103,7 +103,7 @@ def main(in_args):
             pass
 
         if len(measurements) > 1 and inputdim == 1:
-            plot_experiment_measurements(measurements, res,
+            plot_experiment_measurements(res,
                                          f'figures/pde_{inputdim}D/' + example, fsize,
                                          linewidth, save=save)
 
@@ -122,7 +122,7 @@ def main(in_args):
                          time_ratios=time_ratios)
 
         if len(time_ratios) > 1:
-            plot_experiment_measurements(time_ratios, res,
+            plot_experiment_measurements(res,
                                          'figures/ode/' + example,
                                          fsize, linewidth,
                                          save=save, legend=True)
@@ -185,7 +185,7 @@ def run_ode():
     0
     """
     run_cmd = """--example ode --bayes --save \
-    --num-trials 20 -r 0.1 0.5 1 -t 0.1
+    --num-trials 20 -r 0.1 0.25 0.5 1 -t 0.1
     """.replace('    ','').replace('\n','').split(' ')
     main(run_cmd + sys.argv[1:])