fixing postproc.py for python3

BenjaminRodenberg · BenjaminRodenberg · commit 12ee51f43320 · 2018-03-29T16:37:36.000+02:00
diff --git a/postproc.py b/postproc.py
@@ -1,152 +1,152 @@
-import numpy as np
-import argparse
-
-import matplotlib.pyplot as plt
-import itertools
-import json, glob
-from numpy import nan as NAN
-
-parser = argparse.ArgumentParser(description='Postprocessing')
-parser.add_argument('foldername', type=str, help='enter folder with experimental data here')
-
-plt.rc('font', **{'family': 'sans-serif', 'sans-serif': ['lmodern'], 'size'   : 15})
-plt.rc('text', usetex=True)
-
-legends = []
-lines = []
-name = parser.parse_args().foldername
-plottingdir = r'./' + name
-filenames = glob.glob(plottingdir+"/*.json")
-print("reading from")
-print(filenames)
-
-marker_collection = ('o','x','d','s','^','<','>','v','.')
-
-marker_left = itertools.cycle(marker_collection)
-
-plot_right = True
-if plot_right:
-    marker_right = itertools.cycle(marker_collection)
-
-if plot_right:
-    f, (ax1, ax2) = plt.subplots(1, 2, sharey=True, figsize=(12,9))
-else:
-    f, (ax1) = plt.subplots(1, 1, sharey=True, figsize=(12,9))
-
-data_left = np.empty(shape=(0,0))
-data_right = np.empty(shape=(0,0))
-data_header = []
-
-
-def concat_w_zero_padding(a,b):
-    if len(a.shape) > 1 and a.shape[1] == 0:  # a has no entries
-        return b
-    elif len(b.shape) > 1 and b.shape[1] == 0:  # b has no entries
-        return a
-    else:  # both arrays have entries
-        la = a.shape[0]
-        lb = b.shape[0]
-        if la < lb:  # padding a
-            a = np.pad(a, (0, lb-la), 'constant')
-        elif la > lb:  # padding b
-            b = np.pad(b, (0, la-lb), 'constant')
-        else:  # no padding needed if la = lb
-            pass
-        return np.c_[a,b]
-
-
-for filename in filenames:
-    print("---")
-    print(filename)
-    with open(filename) as data_file:
-
-        data = json.load(data_file)
-        taus = np.array(data['temporal_resolution'])
-
-        if data.has_key('errors_left'):
-            errors_left = np.array(data['errors_left'])
-            errors_left[errors_left > 10.0] = NAN
-            ax1.dataLim._set_x1(taus.max())
-            line = ax1.loglog(taus, errors_left, ':',marker=marker_left.next(),markerfacecolor="none",markersize=10,markeredgewidth=2)
-            data_left = concat_w_zero_padding(data_left, errors_left)
-        elif data.has_key('errors'):
-            errors = np.array(data['errors'])
-            errors[errors > 10.0] = NAN
-            line = ax1.loglog(taus, errors, marker=marker_left.next(),markerfacecolor="none")
-            data_left = concat_w_zero_padding(data_left, errors)
-
-        if plot_right and data.has_key('errors_right'):
-            errors_right = np.array(data['errors_right'])
-            errors_right[errors_right > 10.0] = NAN
-            ax2.loglog(taus, errors_right, ':',marker=marker_right.next(),markerfacecolor="none",markersize=10,markeredgewidth=2)
-            data_right = concat_w_zero_padding(data_right, errors_right)
-        elif plot_right and data.has_key('errors'):
-            errors = np.array(data['errors'])
-            errors[errors > 10.0] = NAN
-            ax2.loglog(taus, errors, marker=marker_right.next())
-            data_right = concat_w_zero_padding(data_right, errors)
-
-        if data['numerical_parameters'].has_key('neumann coupling scheme'):
-            legends.append(data['experiment_name'])
-        elif data['numerical_parameters'].has_key('neumann coupling order'):
-            legends.append(data['experiment_name']+" - FD order: "+ str(data['numerical_parameters']['neumann coupling order']))
-        else:
-            legends.append(data['experiment_name'])
-
-        data_header.append(data['experiment_name'])
-
-        lines.append(line[0])
-
-data_left = concat_w_zero_padding(data_left, taus)
-data_right = concat_w_zero_padding(data_right, taus)
-data_header.append('taus')
-
-def plot_order_line(order, ax, x_min, x_max, y_min, y_max):
-    x = np.zeros(2)
-    y = np.zeros(2)
-
-    size = 10.0
-    x[0], y[0] = x_max, y_min * size**order * .1
-    x[1], y[1] = 1.0/size*x_max, y_min * .1
-    x *= .5
-    legend = r" $\mathcal{O}(\tau^{"+str(order)+"})$"
-    ax.loglog(x,y,'k')
-    ax.annotate(legend, xy=(x[0]*1.1, y[0]), horizontalalignment='left', verticalalignment='center')
-    return
-
-ax1.grid()
-ax1.set_title(r"error in left domain $\Omega_L$")
-ax1.set_xlabel(r"time step $\tau$")
-ax1.set_ylabel(r"error $\epsilon$")
-x_min, y_min = ax1.dataLim._get_min()
-x_max, y_max = ax1.dataLim._get_max()
-plot_order_line(1, ax1, x_min, x_max, y_min, y_max)
-plot_order_line(2, ax1, x_min, x_max, y_min, y_max)
-plot_order_line(4, ax1, x_min, x_max, y_min, y_max)
-
-if plot_right:
-    x_min, y_min = ax2.dataLim._get_min()
-    x_max, y_max = ax2.dataLim._get_max()
-    plot_order_line(1, ax2, x_min, x_max, y_min, y_max)
-    plot_order_line(2, ax2, x_min, x_max, y_min, y_max)
-    plot_order_line(4, ax2, x_min, x_max, y_min, y_max)
-
-box = ax1.get_position()
-ax1.set_position([box.x0, box.y0 + box.height * 0.2,
-                 box.width, box.height * 0.8])
-
-if plot_right:
-    ax2.grid()
-    ax2.set_title(r"error in right domain $\Omega_R$")
-    ax2.set_xlabel(r"time step $\tau$")
-    box = ax2.get_position()
-    ax2.set_position([box.x0, box.y0 + box.height * 0.2,
-                     box.width, box.height * 0.8])
-
-f.legend(lines, legends, 'lower center',bbox_to_anchor=(0.5, 0.05),prop={'size': 15})
-f.set_size_inches(6,6)
-plt.subplots_adjust(left=0.15, bottom=0.4, right=0.90, top=0.93, wspace=None, hspace=None)
-plt.savefig(plottingdir + '//' + name+'.pdf')
-np.savetxt(plottingdir + '//data_left.csv', data_left, header=', '.join(data_header),delimiter=',')
-np.savetxt(plottingdir + '//data_right.csv', data_right, header=', '.join(data_header),delimiter=',')
-plt.show()
+import numpy as np
+import argparse
+
+import matplotlib.pyplot as plt
+import itertools
+import json, glob
+from numpy import nan as NAN
+
+parser = argparse.ArgumentParser(description='Postprocessing')
+parser.add_argument('foldername', type=str, help='enter folder with experimental data here')
+
+plt.rc('font', **{'family': 'sans-serif', 'sans-serif': ['lmodern'], 'size'   : 15})
+plt.rc('text', usetex=True)
+
+legends = []
+lines = []
+name = parser.parse_args().foldername
+plottingdir = r'./' + name
+filenames = glob.glob(plottingdir+"/*.json")
+print("reading from")
+print(filenames)
+
+marker_collection = ('o','x','d','s','^','<','>','v','.')
+
+marker_left = itertools.cycle(marker_collection)
+
+plot_right = True
+if plot_right:
+    marker_right = itertools.cycle(marker_collection)
+
+if plot_right:
+    f, (ax1, ax2) = plt.subplots(1, 2, sharey=True, figsize=(12,9))
+else:
+    f, (ax1) = plt.subplots(1, 1, sharey=True, figsize=(12,9))
+
+data_left = np.empty(shape=(0,0))
+data_right = np.empty(shape=(0,0))
+data_header = []
+
+
+def concat_w_zero_padding(a,b):
+    if len(a.shape) > 1 and a.shape[1] == 0:  # a has no entries
+        return b
+    elif len(b.shape) > 1 and b.shape[1] == 0:  # b has no entries
+        return a
+    else:  # both arrays have entries
+        la = a.shape[0]
+        lb = b.shape[0]
+        if la < lb:  # padding a
+            a = np.pad(a, (0, lb-la), 'constant')
+        elif la > lb:  # padding b
+            b = np.pad(b, (0, la-lb), 'constant')
+        else:  # no padding needed if la = lb
+            pass
+        return np.c_[a,b]
+
+
+for filename in filenames:
+    print("---")
+    print(filename)
+    with open(filename) as data_file:
+
+        data = json.load(data_file)
+        taus = np.array(data['temporal_resolution'])
+
+        if 'errors_left' in data:
+            errors_left = np.array(data['errors_left'])
+            errors_left[errors_left > 10.0] = NAN
+            #ax1.dataLim._set_x1(taus.max())
+            line = ax1.loglog(taus, errors_left, ':',marker=next(marker_left),markerfacecolor="none",markersize=10,markeredgewidth=2)
+            data_left = concat_w_zero_padding(data_left, errors_left)
+        elif 'errors' in data:
+            errors = np.array(data['errors'])
+            errors[errors > 10.0] = NAN
+            line = ax1.loglog(taus, errors, marker=next(marker_left),markerfacecolor="none")
+            data_left = concat_w_zero_padding(data_left, errors)
+
+        if plot_right and 'errors_right' in data:
+            errors_right = np.array(data['errors_right'])
+            errors_right[errors_right > 10.0] = NAN
+            ax2.loglog(taus, errors_right, ':',marker=next(marker_right),markerfacecolor="none",markersize=10,markeredgewidth=2)
+            data_right = concat_w_zero_padding(data_right, errors_right)
+        elif plot_right and 'errors' in data:
+            errors = np.array(data['errors'])
+            errors[errors > 10.0] = NAN
+            ax2.loglog(taus, errors, marker=next(marker_right))
+            data_right = concat_w_zero_padding(data_right, errors)
+
+        if 'neumann coupling scheme' in data['numerical_parameters']:
+            legends.append(data['experiment_name'])
+        elif 'neumann coupling order' in data['numerical_parameters']:
+            legends.append(data['experiment_name']+" - FD order: "+ str(data['numerical_parameters']['neumann coupling order']))
+        else:
+            legends.append(data['experiment_name'])
+
+        data_header.append(data['experiment_name'])
+
+        lines.append(line[0])
+
+data_left = concat_w_zero_padding(data_left, taus)
+data_right = concat_w_zero_padding(data_right, taus)
+data_header.append('taus')
+
+def plot_order_line(order, ax, x_min, x_max, y_min, y_max):
+    x = np.zeros(2)
+    y = np.zeros(2)
+
+    size = 2.0    
+    x[0], y[0] = x_max, y_min * size**order * .1
+    x[1], y[1] = 1.0/size*x_max, y_min * .1
+    x *= .5
+    legend = r" $\mathcal{O}(\tau^{"+str(order)+"})$"
+    ax.loglog(x,y,'k')
+    ax.annotate(legend, xy=(x[0]*1.1, y[0]), horizontalalignment='left', verticalalignment='center')
+    return
+
+ax1.grid()
+ax1.set_title(r"error in left domain $\Omega_L$")
+ax1.set_xlabel(r"time step $\tau$")
+ax1.set_ylabel(r"error $\epsilon$")
+x_min, x_max = ax1.get_xlim()
+y_min, y_max = ax1.get_ylim()
+plot_order_line(1, ax1, x_min, x_max, y_min, y_max)
+plot_order_line(2, ax1, x_min, x_max, y_min, y_max)
+plot_order_line(4, ax1, x_min, x_max, y_min, y_max)
+
+if plot_right:
+    x_min, x_max = ax2.get_xlim()
+    y_min, y_max = ax2.get_ylim()
+    plot_order_line(1, ax2, x_min, x_max, y_min, y_max)
+    plot_order_line(2, ax2, x_min, x_max, y_min, y_max)
+    plot_order_line(4, ax2, x_min, x_max, y_min, y_max)
+
+box = ax1.get_position()
+ax1.set_position([box.x0, box.y0 + box.height * 0.2,
+                 box.width, box.height * 0.8])
+
+if plot_right:
+    ax2.grid()
+    ax2.set_title(r"error in right domain $\Omega_R$")
+    ax2.set_xlabel(r"time step $\tau$")
+    box = ax2.get_position()
+    ax2.set_position([box.x0, box.y0 + box.height * 0.2,
+                     box.width, box.height * 0.8])
+
+f.legend(lines, legends, 'lower center',bbox_to_anchor=(0.5, 0.05),prop={'size': 15})
+f.set_size_inches(6,6)
+plt.subplots_adjust(left=0.15, bottom=0.4, right=0.90, top=0.93, wspace=None, hspace=None)
+plt.savefig(plottingdir + '//' + name+'.pdf')
+np.savetxt(plottingdir + '//data_left.csv', data_left, header=', '.join(data_header),delimiter=',')
+np.savetxt(plottingdir + '//data_right.csv', data_right, header=', '.join(data_header),delimiter=',')
+plt.show()
