linting

Author: mathematicalmichael

src/mud_examples/experiments.py

@@ -8,31 +8,27 @@
 
 from mud_examples.utils import check_dir
 
-plt.rcParams['figure.figsize'] = 10, 10
-plt.rcParams['font.size'] = 16
+plt.rcParams["figure.figsize"] = 10, 10
+plt.rcParams["font.size"] = 16
 
 
 __author__ = "Mathematical Michael"
 __copyright__ = "Mathematical Michael"
 __license__ = "mit"
 
 _logger = logging.getLogger(__name__)
-_mpl_logger = logging.getLogger('matplotlib')
+_mpl_logger = logging.getLogger("matplotlib")
 _mpl_logger.setLevel(logging.WARNING)
 
 
-def experiment_measurements(fun,
-                            num_measurements,
-                            sd,
-                            num_trials,
-                            seed=21):
+def experiment_measurements(fun, num_measurements, sd, num_trials, seed=21):
     """
     Fixed sensors, varying how much data is incorporated into the solution.
     """
     experiments = {}
     solutions = {}
     for ns in num_measurements:
-        _logger.debug(f'Measurement experiment. Num measurements: {ns}')
+        _logger.debug(f"Measurement experiment. Num measurements: {ns}")
         discretizations = []
         estimates = []
         for t in range(num_trials):
@@ -47,18 +43,14 @@ def experiment_measurements(fun,
     return experiments, solutions
 
 
-def experiment_equipment(fun,
-                         num_measure,
-                         sd_vals,
-                         num_trials,
-                         seed=21):
+def experiment_equipment(fun, num_measure, sd_vals, num_trials, seed=21):
     """
     Fixed number of sensors, varying the quality of equipment.
     """
     experiments = {}
     solutions = {}
     for sd in sd_vals:
-        _logger.debug(f'Equipment Experiment. Std Dev: {sd}')
+        _logger.debug(f"Equipment Experiment. Std Dev: {sd}")
         discretizations = []
         estimates = []
         for t in range(num_trials):
@@ -73,82 +65,117 @@ def experiment_equipment(fun,
     return experiments, solutions
 
 
-def plot_experiment_equipment(tolerances, res, prefix, fsize=32, linewidth=5,
-                              title="Variance of MUD Error", save=True):
+def plot_experiment_equipment(
+    tolerances,
+    res,
+    prefix,
+    fsize=32,
+    linewidth=5,
+    title="Variance of MUD Error",
+    save=True,
+):
     print("Plotting experiments involving equipment differences...")
     plt.figure(figsize=(10, 10))
     for _res in res:
         _example, _in, _rm, _re, _fname = _res
-        regression_err_mean, slope_err_mean, \
-            regression_err_vars, slope_err_vars, \
-            sd_means, sd_vars, num_sensors = _re
-        plt.plot(tolerances, regression_err_mean,
-                 label=f"{_example.upper()} slope: {slope_err_mean:1.4f}",
-                 lw=linewidth)
-        plt.scatter(tolerances, sd_means, marker='x', lw=20)
-
-    plt.yscale('log')
-    plt.xscale('log')
+        (
+            regression_err_mean,
+            slope_err_mean,
+            regression_err_vars,
+            slope_err_vars,
+            sd_means,
+            sd_vars,
+            num_sensors,
+        ) = _re
+        plt.plot(
+            tolerances,
+            regression_err_mean,
+            label=f"{_example.upper()} slope: {slope_err_mean:1.4f}",
+            lw=linewidth,
+        )
+        plt.scatter(tolerances, sd_means, marker="x", lw=20)
+
+    plt.yscale("log")
+    plt.xscale("log")
     plt.Axes.set_aspect(plt.gca(), 1)
     # plt.ylim(2E-3, 2E-2)
     # plt.ylabel("Absolute Error", fontsize=fsize)
-    plt.xlabel('Tolerance', fontsize=fsize)
+    plt.xlabel("Tolerance", fontsize=fsize)
     plt.legend()
     plt.title(f"Mean of MUD Error for N={num_sensors}", fontsize=1.25 * fsize)
     if save:
-        fdir = ''.join(prefix.split('/')[::-1])
-        check_dir(f'figures/{_fname}/{fdir}')
+        fdir = "".join(prefix.split("/")[::-1])
+        check_dir(f"figures/{_fname}/{fdir}")
         _logger.info("Saving equipment experiments: mean convergence.")
-        plt.savefig(f'figures/{_fname}/{prefix}_convergence_mud_std_mean.png',
-                    bbox_inches='tight')
+        plt.savefig(
+            f"figures/{_fname}/{prefix}_convergence_mud_std_mean.png",
+            bbox_inches="tight",
+        )
     else:
         plt.show()
 
     plt.figure(figsize=(10, 10))
     for _res in res:
         _example, _in, _rm, _re, _fname = _res
-        regression_err_mean, slope_err_mean, \
-            regression_err_vars, slope_err_vars, \
-            sd_means, sd_vars, num_sensors = _re
-        plt.plot(tolerances, regression_err_vars,
-                 label=f"{_example.upper()} slope: {slope_err_vars:1.4f}",
-                 lw=linewidth)
-        plt.scatter(tolerances, sd_vars, marker='x', lw=20)
-    plt.xscale('log')
-    plt.yscale('log')
+        (
+            regression_err_mean,
+            slope_err_mean,
+            regression_err_vars,
+            slope_err_vars,
+            sd_means,
+            sd_vars,
+            num_sensors,
+        ) = _re
+        plt.plot(
+            tolerances,
+            regression_err_vars,
+            label=f"{_example.upper()} slope: {slope_err_vars:1.4f}",
+            lw=linewidth,
+        )
+        plt.scatter(tolerances, sd_vars, marker="x", lw=20)
+    plt.xscale("log")
+    plt.yscale("log")
     # plt.ylim(2E-5, 2E-4)
     plt.Axes.set_aspect(plt.gca(), 1)
     # plt.ylabel("Absolute Error", fontsize=fsize)
-    plt.xlabel('Tolerance', fontsize=fsize)
+    plt.xlabel("Tolerance", fontsize=fsize)
     plt.legend()
     plt.title(title, fontsize=1.25 * fsize)
     if save:
         _logger.info("Saving equipment experiments: variance convergence.")
-        plt.savefig(f'figures/{_fname}/{prefix}_convergence_mud_std_var.png',
-                    bbox_inches='tight')
+        plt.savefig(
+            f"figures/{_fname}/{prefix}_convergence_mud_std_var.png",
+            bbox_inches="tight",
+        )
     else:
         plt.show()
 
 
-def plot_experiment_measurements(res, prefix,
-                                 fsize=32, linewidth=5,
-                                 xlabel='Number of Measurements',
-                                 save=True, legend=True):
+def plot_experiment_measurements(
+    res,
+    prefix,
+    fsize=32,
+    linewidth=5,
+    xlabel="Number of Measurements",
+    save=True,
+    legend=True,
+):
     print("Plotting experiments involving increasing # of measurements.")
     plt.figure(figsize=(10, 10))
     for _res in res:
         _example, _in, _rm, _re, _fname = _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"{_example.upper()} slope: {slope_mean:1.4f}",
-                 lw=linewidth)
-        plt.scatter(measurements[:len(means)], means, marker='x', lw=20)
-    plt.xscale('log')
-    plt.yscale('log')
+        regression_mean, slope_mean, regression_vars, slope_vars, means, variances = _rm
+        plt.plot(
+            measurements[: len(regression_mean)],
+            regression_mean,
+            label=f"{_example.upper()} slope: {slope_mean:1.4f}",
+            lw=linewidth,
+        )
+        plt.scatter(measurements[: len(means)], means, marker="x", lw=20)
+    plt.xscale("log")
+    plt.yscale("log")
     plt.Axes.set_aspect(plt.gca(), 1)
     # plt.ylim(0.9 * min(means), 1.3 * max(means))
     # plt.ylim(2E-3, 2E-1)
@@ -159,38 +186,43 @@ def plot_experiment_measurements(res, prefix,
     title = "$\\mathrm{\\mathbb{E}}(|\\lambda^* - \\lambda^\\dagger|)$"  # noqa E501
     plt.title(title, fontsize=1.25 * fsize)
     if save:
-        fdir = '/'.join(prefix.split('/')[:-1])
-        check_dir(f'figures/{_fname}/{fdir}')
+        fdir = "/".join(prefix.split("/")[:-1])
+        check_dir(f"figures/{_fname}/{fdir}")
         _logger.info("Saving measurement experiments: mean convergence.")
-        plt.savefig(f'figures/{_fname}/{prefix}_convergence_obs_mean.png', bbox_inches='tight')
+        plt.savefig(
+            f"figures/{_fname}/{prefix}_convergence_obs_mean.png", bbox_inches="tight"
+        )
     else:
         plt.show()
 
     plt.figure(figsize=(10, 10))
     for _res in res:
         _example, _in, _rm, _re, _fname = _res
-        regression_mean, slope_mean, \
-            regression_vars, slope_vars, \
-            means, variances = _rm
-        plt.plot(measurements[:len(regression_vars)], regression_vars,
-                 label=f"{_example.upper()} slope: {slope_vars:1.4f}",
-                 lw=linewidth)
-        plt.scatter(measurements[:len(variances)], variances,
-                    marker='x', lw=20)
-    plt.xscale('log')
-    plt.yscale('log')
+        regression_mean, slope_mean, regression_vars, slope_vars, means, variances = _rm
+        plt.plot(
+            measurements[: len(regression_vars)],
+            regression_vars,
+            label=f"{_example.upper()} slope: {slope_vars:1.4f}",
+            lw=linewidth,
+        )
+        plt.scatter(measurements[: len(variances)], variances, marker="x", lw=20)
+    plt.xscale("log")
+    plt.yscale("log")
     plt.Axes.set_aspect(plt.gca(), 1)
-#     if not len(np.unique(variances)) == 1:
-#         plt.ylim(0.9 * min(variances), 1.3 * max(variances))
+    #     if not len(np.unique(variances)) == 1:
+    #         plt.ylim(0.9 * min(variances), 1.3 * max(variances))
     # plt.ylim(5E-6, 5E-4)
     plt.xlabel(xlabel, fontsize=fsize)
     if legend:
         plt.legend(fontsize=fsize * 0.8)
     # plt.ylabel('Absolute Error in MUD', fontsize=fsize)
-    plt.title("$\\mathrm{Var}(|\\lambda^* - \\lambda^\\dagger|)$",
-              fontsize=1.25 * fsize)
+    plt.title(
+        "$\\mathrm{Var}(|\\lambda^* - \\lambda^\\dagger|)$", fontsize=1.25 * fsize
+    )
     if save:
         _logger.info("Saving measurement experiments: variance convergence.")
-        plt.savefig(f'figures/{_fname}/{prefix}_convergence_obs_var.png', bbox_inches='tight')
+        plt.savefig(
+            f"figures/{_fname}/{prefix}_convergence_obs_var.png", bbox_inches="tight"
+        )
     else:
         plt.show()