Save simulated observations for regression tests

As a general, these outputs should remain consistent unless we modify
the PRNG, the PRNG seed, or other fundamental components.

tests/simulate_from_model-x.ssv

+date value
+1 1.403933
+2 1.190422
+3 1.477227
+4 0.916595
+5 0.794995
+6 0.585725
+7 0.775698
+8 1.000713
+9 1.463746
+10 1.557791
+11 1.654735
+12 0.794288
+13 0.713317
+14 0.659150
+15 1.126689

tests/simulate_from_model-y.ssv

+date value
+1 0.456042
+2 0.152997
+3 0.668645
+4 0.711037
+5 0.837072
+6 0.673318
+7 0.133188
+8 0.056321
+9 0.264425
+10 0.299256
+11 0.729363
+12 0.803457
+13 0.731722
+14 0.517535
+15 0.215541

tests/simulated_obs.ssv

+fs_date date value
+1 1 x 1.070862
+1 1 x 1.613679
+1 1 y 0.602618
+1 1 y 0.315129
+1 2 x 1.043339
+1 2 x 1.932096
+1 2 y 1.008079
+1 2 y 0.649420
+1 3 x 0.592838
+1 3 x 1.512923
+1 3 y 0.862200
+1 3 y 0.963009
+1 4 x 0.531867
+1 4 x 1.014131
+1 4 y 0.736581
+1 4 y 1.020064
+1 5 x 0.344741
+1 5 x 0.859832
+1 5 y 0.210133
+1 5 y 0.948124
+1 6 x 0.587501
+1 6 x 0.441767
+1 6 y 0.063504
+1 6 y 0.316157
+1 7 x 0.804867
+1 7 x 0.403132
+1 7 y 0.426062
+1 7 y 0.326053
+1 8 x 1.517841
+1 8 x 0.586477
+1 8 y 0.347976
+1 8 y 0.094142
+1 9 x 1.308058
+1 9 x 1.612668
+1 9 y 0.791791
+1 9 y 0.180631
+1 10 x 0.748884
+1 10 x 1.585551
+1 10 y 1.084060
+1 10 y 0.208586
+1 11 x 0.419950
+1 11 x 1.475274
+1 11 y 0.757717
+1 11 y 0.712158
+1 12 x 0.273355
+1 12 x 0.916839
+1 12 y 0.527738
+1 12 y 0.878602
+1 13 x 0.665148
+1 13 x 0.674794
+1 13 y 0.478047
+1 13 y 0.816481
+1 14 x 1.028584
+1 14 x 0.563400
+1 14 y 0.428332
+1 14 y 0.179932
+1 15 x 1.186531
+1 15 x 0.753580
+1 15 y 0.261235
+1 15 y 0.526659
+3 3 x 1.377728
+3 3 x 0.980069
+3 3 y 0.502682
+3 3 y 0.735865
+3 4 x 0.590348
+3 4 x 0.586417
+3 4 y 0.618670
+3 4 y 0.474148
+3 5 x 0.375687
+3 5 x 0.350127
+3 5 y 0.622115
+3 5 y 0.808404
+3 6 x 0.513645
+3 6 x 0.421016
+3 6 y 0.150771
+3 6 y 0.471616
+3 7 x 0.833217
+3 7 x 0.561371
+3 7 y 0.379380
+3 7 y 0.380925
+3 8 x 1.186575
+3 8 x 0.595469
+3 8 y 0.135377
+3 8 y 0.062616
+3 9 x 1.528011
+3 9 x 0.644704
+3 9 y 0.032730
+3 9 y 0.458074
+3 10 x 1.556120
+3 10 x 1.645668
+3 10 y 0.702400
+3 10 y 0.666497
+3 11 x 1.300924
+3 11 x 1.066495
+3 11 y 0.577968
+3 11 y 0.461429
+3 12 x 0.267146
+3 12 x 0.838286
+3 12 y 0.809613
+3 12 y 0.951155
+3 13 x 0.170266
+3 13 x 0.439770
+3 13 y 0.387366
+3 13 y 0.889084
+3 14 x 0.377540
+3 14 x 0.740342
+3 14 y 0.191034
+3 14 y 0.647980
+3 15 x 0.497127
+3 15 x 0.345544
+3 15 y 0.419379
+3 15 y 0.566345
+5 5 x 1.749118
+5 5 x 0.819490
+5 5 y 0.869461
+5 5 y 0.529545
+5 6 x 0.796071
+5 6 x 1.212364
+5 6 y 0.764810
+5 6 y 0.393032
+5 7 x 0.733533
+5 7 x 0.495068
+5 7 y 0.749009
+5 7 y 0.361320
+5 8 x 0.352894
+5 8 x 0.428760
+5 8 y 0.390695
+5 8 y 0.278401
+5 9 x 0.600212
+5 9 x 0.969963
+5 9 y 0.084158
+5 9 y 0.307440
+5 10 x 0.785866
+5 10 x 1.220709
+5 10 y 0.238988
+5 10 y 0.157637
+5 11 x 1.182099
+5 11 x 0.936835
+5 11 y 0.366868
+5 11 y 0.428564
+5 12 x 1.188601
+5 12 x 1.039916
+5 12 y 0.574482
+5 12 y 0.802183
+5 13 x 1.064808
+5 13 x 0.752094
+5 13 y 0.692273
+5 13 y 0.567205
+5 14 x 1.206697
+5 14 x 0.821208
+5 14 y 0.704961
+5 14 y 0.715741
+5 15 x 0.718249
+5 15 x 0.681799
+5 15 y 0.896498
+5 15 y 0.606577
+7 7 x 0.757454
+7 7 x 0.801219
+7 7 y 0.598796
+7 7 y 0.610233
+7 8 x 0.713691
+7 8 x 0.921642
+7 8 y 0.363011
+7 8 y 0.030043
+7 9 x 1.185090
+7 9 x 1.182957
+7 9 y 0.373297
+7 9 y 0.347266
+7 10 x 1.475102
+7 10 x 1.221262
+7 10 y 0.203750
+7 10 y 0.113711
+7 11 x 1.364442
+7 11 x 1.466064
+7 11 y 0.743178
+7 11 y 0.410979
+7 12 x 1.114618
+7 12 x 1.445021
+7 12 y 0.913442
+7 12 y 1.212810
+7 13 x 1.054041
+7 13 x 1.111697
+7 13 y 0.865833
+7 13 y 0.876714
+7 14 x 0.846708
+7 14 x 0.843954
+7 14 y 0.422704
+7 14 y 0.771752
+7 15 x 0.898871
+7 15 x 0.955760
+7 15 y 0.458028
+7 15 y 0.253669
+9 9 x 0.668280
+9 9 x 0.469675
+9 9 y 0.571540
+9 9 y 0.177975
+9 10 x 1.058615
+9 10 x 0.734312
+9 10 y -0.067411
+9 10 y 0.362426
+9 11 x 1.353942
+9 11 x 1.385223
+9 11 y 0.468127
+9 11 y 0.286807
+9 12 x 1.204176
+9 12 x 1.802338
+9 12 y 0.480378
+9 12 y 0.246995
+9 13 x 1.189448
+9 13 x 1.512623
+9 13 y 0.554929
+9 13 y 0.456668
+9 14 x 1.073272
+9 14 x 1.297334
+9 14 y 0.234591
+9 14 y 0.872280
+9 15 x 0.845244
+9 15 x 1.002192
+9 15 y 0.379876
+9 15 y 0.695099

tests/test_predation.py

@@ -373,6 +373,20 @@ def test_simulated_obs():
         num_particles = np.sum(sim_obs['date'] == fs_time)
         assert len(sim_obs) == num_particles * int(t1 - fs_time + 1)
 
+    # Save the simulated observations as plain-text files in the tests
+    # directory, which we can version-track and use for regression tests.
+    all_sim_obs = tuple(state[fs_time]['summary']['simulated_obs']
+                        for fs_time in fs_times)
+    all_sim_obs = np.concatenate(all_sim_obs)
+    all_sim_obs = all_sim_obs[['fs_date', 'date', 'unit', 'value']]
+    # Only retain every 500th row: 2 for each observation type, each day.
+    sim_obs_tbl = all_sim_obs[::500]
+    save_dir = os.path.abspath('tests')
+    sim_obs_file = os.path.join(save_dir, 'simulated_obs.ssv')
+    np.savetxt(sim_obs_file, sim_obs_tbl,
+               fmt='%d %d %s %0.6f',
+               header='fs_date date value', comments='')
+
 
 def simulate_from_model(time_scale, t0, t1, px_count):
     seed = 42
@@ -425,4 +439,16 @@ def test_simulate_from_model():
         assert any(obs_at_t['unit'] == 'x')
         assert any(obs_at_t['unit'] == 'y')
 
-    # pypfilt.examples.predation.save_scalar_observations(sim_obs)
+    # Save the simulated observations as plain-text files in the tests
+    # directory, which we can version-track and use for regression tests.
+    save_dir = os.path.abspath('tests')
+    x_obs_file = os.path.join(save_dir, 'simulate_from_model-x.ssv')
+    y_obs_file = os.path.join(save_dir, 'simulate_from_model-y.ssv')
+    x_tbl = sim_obs[sim_obs['unit'] == 'x'][['date', 'value']]
+    y_tbl = sim_obs[sim_obs['unit'] == 'y'][['date', 'value']]
+    x_tbl = x_tbl[x_tbl['date'] > 0]
+    y_tbl = y_tbl[y_tbl['date'] > 0]
+    np.savetxt(x_obs_file, x_tbl, fmt='%d %0.6f',
+               header='date value', comments='')
+    np.savetxt(y_obs_file, y_tbl, fmt='%d %0.6f',
+               header='date value', comments='')