toward v014

Author: paudetseis

Diff for: obstools/__init__.py

@@ -109,7 +109,7 @@
 
 """
 
-__version__ = '0.1.3'
+__version__ = '0.1.4'
 
 __author__ = 'Pascal Audet & Helen Janiszewski'
 

Diff for: obstools/atacr/plotting.py

@@ -436,22 +436,41 @@ def fig_comply(f, day_comps, day_list, sta_comps, sta_list, skey=None,
         ax.yaxis.get_offset_text().set_fontsize(8)
 
         if day_list[key]:
+            compliance_list = []
+            coherence_list = []
             for i in range(len(day_comps)):
                 compliance = np.abs(day_comps[i][key][0])
+                coherence = np.abs(day_comps[i][key][1])
+                if not np.isnan(compliance).any():
+                    compliance_list.append(compliance)
+                    coherence_list.append(coherence)
+            compliance_mean = np.mean(np.array(compliance_list), axis=0)
+            compliance_std = np.std(np.array(compliance_list), axis=0)
+            coherence_mean = np.mean(np.array(coherence_list), axis=0)
+            coherence_std = np.std(np.array(coherence_list), axis=0)
+
+            ax.fill_between(
+                f[faxis], 
+                compliance_mean[faxis]-compliance_std[faxis], 
+                compliance_mean[faxis]+compliance_std[faxis], 
+                fc='royalblue', alpha=0.3, label=r'$\pm$ Std daily'
+                )
+            ax.plot(
+                f[faxis], compliance_mean[faxis], c='royalblue', 
+                lw=0.5, label='Mean daily')
+            ax.set_xlim(f_0, f_c)
+            ytop = 1.2*np.max(compliance_mean[(f > f_0) & (f < f_c)])
+            ybot = 0/8*np.min(compliance_mean[(f > f_0) & (f < f_c)])
+            ax.set_ylim(ybot, ytop)
+
+        if sta_list[key]:
+            for i in range(len(sta_comps)):
+                compliance = np.abs(sta_comps[i][key][0])
                 ax.plot(
                     f[faxis],
                     compliance[faxis],
-                    'gray', alpha=0.3, lw=0.5)
-                ax.set_xlim(f_0, f_c)
-                ytop = np.max(compliance[(f > f_0) & (f < f_c)])
-                ybot = np.min(compliance[(f > f_0) & (f < f_c)])
-                ax.set_ylim(ybot, ytop)
-
-        if sta_list[key]:
-            ax.plot(
-                f[faxis],
-                np.abs(sta_comps[key][0][faxis]),
-                'k', lw=0.5)
+                    'red', lw=0.5, alpha=0.5,
+                    label='Sta average')
 
         if key == 'ZP':
             ax.set_title(skey+' Compliance: ZP',
@@ -467,20 +486,32 @@ def fig_comply(f, day_comps, day_list, sta_comps, sta_list, skey=None,
             ax.axvline(f_0, ls='--', c='k', lw=0.75)
         ax.axvline(f_c, ls='--', c='k', lw=0.75)
 
+        handles, labels = ax.get_legend_handles_labels()
+        by_label = dict(zip(labels, handles))
+        ax.legend(by_label.values(), by_label.keys(), fontsize=6)
+
         ax = fig.add_subplot(ncomps, 2, j*2+2)
         ax.tick_params(labelsize=8)
 
         if day_list[key]:
-            for i in range(len(day_comps)):
-                ax.semilogx(
-                    f[faxis],
-                    np.abs(day_comps[i][key][1][faxis]),
-                    'gray', alpha=0.3, lw=0.5)
+            # for i in range(len(day_comps)):
+            ax.fill_between(
+                f[faxis],
+                coherence_mean[faxis]-coherence_std[faxis],
+                coherence_mean[faxis]+coherence_std[faxis],
+                fc='royalblue', alpha=0.3
+                )
+            ax.plot(
+                f[faxis],
+                coherence_mean[faxis],
+                c='royalblue', lw=0.75)
         if sta_list[key]:
-            ax.semilogx(
-                f[faxis], 
-                np.abs(sta_comps[key][1][faxis]),
-                'k', lw=0.5)
+            for i in range(len(sta_comps)):
+                ax.plot(
+                    f[faxis], 
+                    np.abs(sta_comps[i][key][1][faxis]),
+                    'red', lw=0.5, alpha=0.5)
+        ax.set_xscale('log')
 
         if key == 'ZP':
             ax.set_title(skey+' Coherence: ZP',

Diff for: obstools/scripts/atacr_transfer_functions.py

@@ -361,6 +361,10 @@ def main(args=None):
                 # Save daily transfer functions to file
                 daytransfer.save(filename)
 
+        # Create empty daynoise if not loaded
+        # else:
+        #     XXX
+
         if not args.skip_clean:
 
             # Cycle through available files
@@ -395,6 +399,10 @@ def main(args=None):
                 # Save average transfer functions to file
                 statransfer.save(filename)
 
+        # Create empty stanoise if not loaded
+        # else:
+            # XXX
+
         if args.fig_TF:
             fname = stkey + '.' + 'transfer_functions'
             plot = plotting.fig_TF(

Diff for: obstools/scripts/comply_calculate.py

@@ -395,6 +395,8 @@ def main(args=None):
 
         if not args.skip_clean:
 
+            sta_comply_functions = []
+
             # Cycle through available files
             for fileavst in average_files:
 
@@ -411,7 +413,7 @@ def main(args=None):
                         # Load Comply object and append to list
                         stacomply = pickle.load(open(filepkl, 'rb'))
                         f = stacomply.f
-                        sta_comply_functions = stacomply.complyfunc
+                        sta_comply_functions.append(stacomply.complyfunc)
                         continue
 
                 print("\n"+"*"*60)
@@ -434,7 +436,7 @@ def main(args=None):
                 f = stacomply.f
 
                 # Extract the transfer functions - for plotting
-                sta_comply_functions = stacomply.complyfunc
+                sta_comply_functions.append(stacomply.complyfunc)
 
                 # Save average transfer functions to file
                 stacomply.save(filename, form=args.saveformat)

Diff for: setup.py

@@ -2,7 +2,7 @@
 import os.path
 from os import listdir
 import re
-from numpy.distutils.core import setup
+from setuptools import setup
 from pathlib import Path
 
 
@@ -26,17 +26,15 @@ def find_version(*paths):
     author_email='[email protected]',
     maintainer='Pascal Audet, Helen Janiszewski',
     maintainer_email='[email protected], [email protected]',
-    url='https://github.com/nfsi-canada/OBStools/archive/OBStools-0.1.3.tar.gz',
+    url='https://github.com/nfsi-canada/OBStools/archive/OBStools-0.1.4.tar.gz',
     classifiers=[
         'Development Status :: 3 - Alpha',
         'License :: OSI Approved :: MIT License',
         'Programming Language :: Python :: 3.6',
         'Programming Language :: Python :: 3.7',
         'Programming Language :: Python :: 3.8',
         'Programming Language :: Python :: 3.9'],
-    install_requires=[
-        'numpy<=1.21.5', 'scipy<=1.8.0',
-        'obspy<=1.2.2', 'stdb==0.2.3', 'pandas<=1.4.1'],
+    install_requires=['numpy', 'obspy', 'stdb', 'scipy', 'pandas'],
     python_requires='>=3.6',
     packages=setuptools.find_packages(),
     include_package_data=True,