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test: Add CPO strength output for Fraters2021 test #170

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merged 2 commits into from
Feb 29, 2024
Merged

test: Add CPO strength output for Fraters2021 test #170

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61de0a3
test: Add CPO strength output for Fraters2021 test
adigitoleo Feb 29, 2024
cd1907c
Merge branch 'main' into more-diagnostics-Fraters2021
Patol75 Feb 29, 2024
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18 changes: 18 additions & 0 deletions tests/test_simple_shear_3d.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@

from pydrex import core as _core
from pydrex import diagnostics as _diagnostics
from pydrex import geometry as _geo
from pydrex import io as _io
from pydrex import logger as _log
from pydrex import minerals as _minerals
Expand Down Expand Up @@ -138,6 +139,9 @@ def test_direction_change(
olA_from_proj_YX = np.empty_like(olA_from_proj_XZ)
ens_from_proj_XZ = np.empty_like(olA_from_proj_XZ)
ens_from_proj_YX = np.empty_like(olA_from_proj_XZ)
# Output arrays for M-index (CPO strength).
olA_strength = np.empty_like(olA_from_proj_XZ)
ens_strength = np.empty_like(olA_from_proj_XZ)

_id = _io.stringify(switch_time_Ma * 1e6)
optional_logging = cl.nullcontext()
Expand Down Expand Up @@ -181,6 +185,9 @@ def test_direction_change(
for v in olA_mean_vectors
]
)
olA_strength[s, :] = _diagnostics.misorientation_indices(
olA_resampled, _geo.LatticeSystem.orthorhombic, pool=pool
)
del olivine, olA_resampled, olA_mean_vectors

_log.info("%s; # %d; postprocessing enstatite...", _id, _seeds[s])
Expand All @@ -205,6 +212,10 @@ def test_direction_change(
for v in ens_mean_vectors
]
)
ens_strength[s, :] = _diagnostics.misorientation_indices(
ens_resampled, _geo.LatticeSystem.orthorhombic, pool=pool
)
del enstatite, ens_resampled, ens_mean_vectors

_log.info("elapsed CPU time: %s", np.abs(process_time() - clock_start))
_log.info("calculating ensemble averages...")
Expand Down Expand Up @@ -232,3 +243,10 @@ def test_direction_change(
ens_from_proj_YX_mean=ens_from_proj_YX_mean,
ens_from_proj_YX_err=ens_from_proj_YX_err,
)
np.savez(
f"{out_basepath}_strength.npz",
olA_mean=olA_strength.mean(axis=0),
ens_mean=ens_strength.mean(axis=0),
olA_err=olA_strength.std(axis=0),
ens_err=ens_strength.std(axis=0),
)
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