Python Module for Analysis of Restart Tests (#2493)

* Python Module for Analysis of Restart Tests

* Remove Unused Import

1 files changed, 52 insertions, 0 deletions

diff --git a/Examples/analysis_default_restart.py b/Examples/analysis_default_restart.py
new file mode 100755
index 000000000..a718b1249
--- /dev/null
+++ b/Examples/analysis_default_restart.py
@@ -0,0 +1,52 @@
+#! /usr/bin/env python
+
+import numpy as np
+import yt
+
+def check_restart(filename, tolerance = 1e-12):
+    """
+    Compare output data generated from initial run with output data generated after restart.
+
+    Parameters
+    ----------
+    filename : str
+        Name of the plotfile containing the output data generated after restart.
+    tolerance : float, optional (default = 1e-12)
+        Relative error between restart and original data must be smaller than tolerance.
+    """
+    # Load output data generated after restart
+    ds_restart = yt.load(filename)
+
+    # yt 4.0+ has rounding issues with our domain data:
+    # RuntimeError: yt attempted to read outside the boundaries
+    # of a non-periodic domain along dimension 0.
+    if 'force_periodicity' in dir(ds_restart): ds_restart.force_periodicity()
+
+    ad_restart = ds_restart.covering_grid(level = 0,
+            left_edge = ds_restart.domain_left_edge, dims = ds_restart.domain_dimensions)
+
+    # Load output data generated from initial run
+    benchmark = 'orig_' + filename
+    ds_benchmark = yt.load(benchmark)
+
+    # yt 4.0+ has rounding issues with our domain data:
+    # RuntimeError: yt attempted to read outside the boundaries
+    # of a non-periodic domain along dimension 0.
+    if 'force_periodicity' in dir(ds_benchmark): ds_benchmark.force_periodicity()
+
+    ad_benchmark = ds_benchmark.covering_grid(level = 0,
+            left_edge = ds_benchmark.domain_left_edge, dims = ds_benchmark.domain_dimensions)
+
+    # Loop over all fields (all particle species, all particle attributes, all grid fields)
+    # and compare output data generated from initial run with output data generated after restart
+    print('\ntolerance = {:g}'.format(tolerance))
+    print()
+    for field in ds_benchmark.field_list:
+        dr = ad_restart[field].squeeze().v
+        db = ad_benchmark[field].squeeze().v
+        error = np.amax(np.abs(dr - db))
+        if (np.amax(np.abs(db)) != 0.):
+            error /= np.amax(np.abs(db))
+        print('field: {}; error = {:g}'.format(field, error))
+        assert(error < tolerance)
+    print()