adding test for full mfd workflow to ensure with same random seed res…

…ults are the same

openquake/cat/completeness/mfd_eval_plots.py

@@ -69,9 +69,15 @@ def _make_a_b_histos(df_all, df_best, figsdir):
     ax[1].tick_params(axis='y', labelcolor=color)
 
     for ii, idx in enumerate(set(df_all.idx)):
+
         df_sub = df_all[df_all.idx == idx]
-        ax[0].hist(df_sub.agr, bins=binsA, color='gray', alpha=10/num_cats)
-        ax[1].hist(df_sub.bgr, bins=binsB, color='gray', alpha=10/num_cats)
+        if num_cats < 10:
+            alpha = 0.1
+        else: 
+            alpha = 10/num_cats
+
+        ax[0].hist(df_sub.agr, bins=binsA, color='gray', alpha=alpha)
+        ax[1].hist(df_sub.bgr, bins=binsB, color='gray', alpha=alpha)
     ax2a = ax[0].twinx()
     ax2b = ax[1].twinx()
     ax2a.hist(df_best.agr, bins=binsA, color='red', alpha=0.2)
@@ -159,13 +165,18 @@ def plot_best_mfds(df_best, figsdir):
                          linewidth=0.1, zorder=0, label='Cumulative MFD')
 
         else: 
+            if num <= 10:
+                alpha1 = 0.1
+            else:
+                alpha1 = 10/num
+
             plt.scatter(row.mags, row.rates, marker='_', color='r', 
-                        alpha=10/num)
+                        alpha=alpha1)
             plt.scatter(row.mags, row.cm_rates, marker='.', color='b', 
-                        alpha=10/num)
-            plt.semilogy(mfd_m, mfd_r, color='r', alpha=30/num, linewidth=0.1, 
+                        alpha=alpha1)
+            plt.semilogy(mfd_m, mfd_r, color='r', alpha=3*alpha1, linewidth=0.1, 
                          zorder=0)
-            plt.semilogy(mfd_m, mfd_cr, color='b', alpha=50/num, 
+            plt.semilogy(mfd_m, mfd_cr, color='b', alpha=5*alpha1, 
                          linewidth=0.1, zorder=0)
 
     plt.xlabel('Magnitude')
@@ -273,6 +284,8 @@ def plot_weighted_covariance_ellipse(df, figdir, n_std=1.0,
     plt.savefig(fout, dpi=300)
     plt.close()
 
+    return center_x, center_y, major_x1, major_y1, major_x2, major_y2
+
 
 
 def plot_all_mfds(df_all, df_best, figsdir, field='rates', bins=10, bw=0.2, figname=None):
@@ -314,11 +327,16 @@ def plot_all_mfds(df_all, df_best, figsdir, field='rates', bins=10, bw=0.2, fign
         mgrts = mfd.get_annual_occurrence_rates()
         mfd_m = [m[0] for m in mgrts]
         mfd_r = [m[1] for m in mgrts]
+        if len(df_best) <=30:
+            alpha = 0.1
+        else:  
+            alpha=30/len(df_best)
+
         if field == 'cm_rates':
             mfd_cr = [sum(mfd_r[ii:]) for ii in range(len(mfd_r))]
-            plt.semilogy(mfd_m, mfd_cr, color='maroon', linewidth=0.2, zorder=10, alpha=30/len(df_best))
+            plt.semilogy(mfd_m, mfd_cr, color='maroon', linewidth=0.2, zorder=10, alpha=alpha)
         else:
-            plt.semilogy(mfd_m, mfd_r, color='maroon', linewidth=0.2, zorder=10, alpha=30/len(df_best))
+            plt.semilogy(mfd_m, mfd_r, color='maroon', linewidth=0.2, zorder=10, alpha=alpha)
 
     if figname==None:
         figname = f'mfds_all_{field}.png'
@@ -334,6 +352,7 @@ def plot_all_mfds(df_all, df_best, figsdir, field='rates', bins=10, bw=0.2, fign
 
 
 def make_all_plots(resdir_base, compdir, figsdir_base, labels):
+    agrs, bgrs, labs = [], [], []
     for label in labels:
         print(f'Running for {label}')
         resdir = os.path.join(resdir_base, label)
@@ -368,5 +387,11 @@ def make_all_plots(resdir_base, compdir, figsdir_base, labels):
         plot_all_mfds(df_all, df_thresh, figsdir, field='cm_rates', bins=60, 
                       figname='mfds_thresh_cmrates.png')
         print('plotting covariance')
-        plot_weighted_covariance_ellipse(df_best, figsdir)
+        cx, cy, mx1, my1, mx2, my2 = plot_weighted_covariance_ellipse(df_best, figsdir)
         plot_weighted_covariance_ellipse(df_thresh, figsdir, figname=f'{label}-20percent.png')
+
+        labs.extend([f'{label}-center', f'{label}-low', f'{label}-high'])
+        agrs.extend([cx, mx1, mx2])
+        bgrs.extend([cy, my1, my2])
+
+    return labs, agrs, bgrs

openquake/mbi/cat/MFDs_sample_mag_sigma.py

@@ -28,7 +28,7 @@
 import numpy as np
 from openquake.baselib import sap
 
-from openquake.mbt.mfds_sample.make_mfds import make_many_mfds
+from openquake.mbt.tools.mfd_sample.make_mfds import make_many_mfds
 
 
 def main(fname_config):

openquake/mbt/tests/tools/mfd_sample/config/compl.toml

@@ -0,0 +1,21 @@
+name = "CAM test"
+mmin = 4.0
+bin_width = 0.2
+rupture_mesh_spacing = 2.5
+kernel_maximum_distance = 120.0
+kernel_smoothing = [ [ 0.8, 20.0,], [ 0.15, 40.0,], [ 0.05, 80.0,],]
+source_prefix = "L01"
+
+[completeness]
+mags = []
+years = []
+completeness_ref = [  [ 1980.0, 4.0,], [ 1964.0, 5.0,], [ 1904.0, 7.0,],]
+deviation = 1.7
+ref_mag = 2.0
+ref_upp_mag = 10.0
+min_mag_compl = 4.0
+bmin = 0.7
+bmax = 1.3
+flexible = true
+num_steps = 2
+optimization_criterion = "optimize"  

openquake/mbt/tests/tools/mfd_sample/config/dec.toml

@@ -0,0 +1,16 @@
+[main]
+
+catalogue = './data2/sub_cat.pkl'
+tr_file = './data2/classified_test.hdf5'
+
+create_subcatalogues = 'true'
+catalogue_add_defaults = 'true'
+
+[method1]
+name = 'GardnerKnopoffType1'
+params = {'time_distance_window' = 'UhrhammerWindow', 'fs_time_prop' = 0.1}
+label = 'UH'
+
+[case1]
+regions = ['crustal', 'intA']
+label = 'int_cru'

openquake/mbt/tests/tools/mfd_sample/config/test.toml

@@ -0,0 +1,23 @@
+[main]
+catalogue_filename = './data2/sub_cat.pkl' 
+output_directory = 'test'
+
+[catalogues]
+number = 3
+sample_type = 'random'
+create_catalogues = true
+
+[decluster]
+decluster_catalogues = true
+decluster_settings = 'config/dec.toml'
+
+[completeness]
+generate_completeness = true
+completeness_settings = 'config/compl.toml'
+
+[mfds]
+create_mfds = true
+labels = ['intA','crustal']
+
+[plot]
+make_plots = true 

openquake/mbt/tests/tools/mfd_sample/expected2/mfd-results.csv

@@ -0,0 +1,7 @@
+,label,a-values,b-values
+0,intA-center,3.4221566716867344,0.8477886165624219
+1,intA-low,3.3341265324448983,0.8035538508320615
+2,intA-high,3.5101868109285705,0.8920233822927822
+3,crustal-center,3.350288725907407,0.8778145185036605
+4,crustal-low,3.263790223525028,0.8485030837041351
+5,crustal-high,3.436787228289786,0.907125953303186

openquake/mbt/tests/tools/mfd_sample/mfd_sample_test.py

@@ -1,14 +1,16 @@
 import os
+import shutil
 import unittest
 import tempfile
 import numpy as np
 import pandas as pd
 
-from openquake.mbt.tools.mfd_sample.make_mfds import _create_catalogue_versions
+from openquake.mbt.tools.mfd_sample.make_mfds import (_create_catalogue_versions,
+                                                      make_many_mfds)
 
 BASE_PATH = os.path.dirname(__file__)
 
-class TestWorkflow(unittest.TestCase):
+class TestGenCats(unittest.TestCase):
 
     def setUp(self):
         self.catfi = os.path.join(BASE_PATH, 'data', 'catalogue.csv')
@@ -27,3 +29,20 @@ def test_generate_cats(self):
         expected = pd.read_csv(mags_exp_fi)
         output = pd.read_csv(mags_out_fi)
         assert expected.equals(output)
+
+        shutil.rmtree(self.tmpd)
+
+class TestWorkflow(unittest.TestCase):
+
+    def test_full_wkflow(self):
+        config_fi = os.path.join(BASE_PATH, 'config', 'test.toml')
+        make_many_mfds(config_fi)
+
+        expected_fi = os.path.join(BASE_PATH, 'expected2', 'mfd-results.csv')
+        output_fi = os.path.join(BASE_PATH, 'test', 'mfd-results.csv')
+        expected = pd.read_csv(expected_fi)
+        output = pd.read_csv(output_fi)
+        assert expected.equals(output)
+
+        shutil.rmtree('test')
+        os.remove('tmp-config-dcl.toml')