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381 lines (331 loc) · 12.8 KB
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#!/usr/bin/env python
from pathlib import Path
import numpy as np
import pytest
from diffpy.morph.morphapp import create_option_parser, single_morph
from diffpy.morph.morphpy import __get_morph_opts__, morph, morph_arrays
from diffpy.morph.tools import get_rw
thisfile = locals().get("__file__", "file.py")
tests_dir = Path(thisfile).parent.resolve()
testdata_dir = tests_dir.joinpath("testdata")
testsequence_dir = testdata_dir.joinpath("testsequence")
nickel_PDF = testdata_dir.joinpath("nickel_ss0.01.cgr")
serial_JSON = testdata_dir.joinpath("testsequence_serialfile.json")
testsaving_dir = testsequence_dir.joinpath("testsaving")
test_saving_succinct = testsaving_dir.joinpath("succinct")
test_saving_verbose = testsaving_dir.joinpath("verbose")
tssf = testdata_dir.joinpath("testsequence_serialfile.json")
class TestMorphpy:
@pytest.fixture
def setup_morph(self):
self.parser = create_option_parser()
filenames = [
"g_174K.gr",
"f_180K.gr",
"e_186K.gr",
"d_192K.gr",
"c_198K.gr",
"b_204K.gr",
"a_210K.gr",
]
self.testfiles = []
self.morphapp_results = {}
# Parse arguments sorting by field
opts, pargs = self.parser.parse_args(
[
"--scale",
"1",
"--stretch",
"0",
"-n",
"--sort-by",
"temperature",
]
)
for filename in filenames:
self.testfiles.append(testsequence_dir.joinpath(filename))
# Run multiple single morphs
morph_file = self.testfiles[0]
for target_file in self.testfiles[1:]:
pargs = [morph_file, target_file]
# store in same format of dictionary as multiple_targets
self.morphapp_results.update(
{
target_file.name: single_morph(
self.parser, opts, pargs, stdout_flag=False
)[0]
}
)
return
def test_morph_opts(self, setup_morph):
kwargs = {
"verbose": False,
"pearson": False,
"addpearson": False,
"apply": False,
"reverse": False,
"get_diff": False,
"multiple_morphs": False,
"multiple_targets": False,
}
kwargs_copy = kwargs.copy()
opts, _ = __get_morph_opts__(
self.parser, scale=1, stretch=0, smear=0, plot=False, **kwargs_copy
)
# Special set true/false operations should be removed
# when their input value is False
for opt in kwargs:
if opt == "apply":
assert getattr(opts, "refine")
else:
assert getattr(opts, opt) is None or not getattr(opts, opt)
kwargs = {
"verbose": True,
"pearson": True,
"addpearson": True,
"apply": True,
"reverse": True,
"get_diff": True,
"multiple_morphs": True,
"multiple_targets": True,
}
kwargs_copy = kwargs.copy()
opts, _ = __get_morph_opts__(
self.parser, scale=1, stretch=0, smear=0, plot=False, **kwargs_copy
)
for opt in kwargs:
if opt == "apply":
assert not getattr(opts, "refine")
# These options are not enabled in morphpy
elif opt == "multiple_morphs" or opt == "multiple_targets":
assert getattr(opts, opt) is None or not getattr(opts, opt)
# Special set true/false operations should NOT be removed
# when their input value is True
else:
assert getattr(opts, opt)
# Check that morphs can be set as None
kwargs = {
"hshift": None,
"vshift": None,
"squeeze": None,
"funcx": None,
"funcy": None,
"funcxy": None,
"verbose": None,
"addpearson": None,
"apply": None,
"exclude": None,
"reverse": None,
"get_diff": None,
"multiple_morphs": None,
"multiple_targets": None,
}
kwargs_copy = kwargs.copy()
opts, pymorphs = __get_morph_opts__(
self.parser,
scale=1,
stretch=0,
smear=0,
plot=False,
**kwargs_copy,
)
for opt in kwargs:
try:
assert not getattr(opts, opt)
except AttributeError:
pass
def test_morphpy_grid_selection(self, setup_morph):
morph_file = self.testfiles[0]
_, grm = morph(morph_file, morph_file)
# Notice that this is a strict less than, not a less than or equal to.
# This is because xmax is an exclusive function (see MorphRGrid).
grm_truncated_grid = grm[:, 0][grm[:, 0] < 35]
grm_truncated_func = grm[:, 1][grm[:, 0] < 35]
grm_truncated = np.array([grm_truncated_grid, grm_truncated_func]).T
_, grt_default = morph(morph_file, morph_file, xmax=35)
assert np.allclose(grt_default, grm_truncated)
_, grt_original = morph(
morph_file, morph_file, xmax=35, original_grid=True
)
assert np.allclose(grt_original, grm)
def test_morph(self, setup_morph):
morph_results = {}
morph_file = self.testfiles[0]
for target_file in self.testfiles[1:]:
mr, grm = morph(
morph_file,
target_file,
scale=1,
stretch=0,
sort_by="temperature",
)
_, grt = morph(target_file, target_file)
morph_results.update({target_file.name: mr})
class Chain:
xyallout = grm[:, 0], grm[:, 1], grt[:, 0], grt[:, 1]
chain = Chain()
rw = get_rw(chain)
del chain
assert np.allclose(
[rw], [self.morphapp_results[target_file.name]["rw"]]
)
# Check values in dictionaries are approximately equal
for file in morph_results.keys():
morph_params = morph_results[file]
morphapp_params = self.morphapp_results[file]
for key in morph_params.keys():
assert morph_params[key] == pytest.approx(
morphapp_params[key], abs=1e-08
)
def test_exclude(self, setup_morph):
morph_file = self.testfiles[0]
target_file = self.testfiles[-1]
morph_info, _ = morph(
morph_file,
target_file,
scale=1,
stretch=0,
exclude=["scale", "stretch"],
sort_by="temperature",
)
# Nothing should be refined
assert pytest.approx(morph_info["scale"]) == 1
assert pytest.approx(morph_info["stretch"]) == 0
morph_info, _ = morph(
morph_file,
target_file,
scale=1,
stretch=0,
exclude=["scale"],
sort_by="temperature",
)
# Stretch only should be refined
assert pytest.approx(morph_info["scale"]) == 1
assert pytest.approx(morph_info["stretch"]) != 0
morph_info, _ = morph(
morph_file,
target_file,
scale=1,
stretch=0,
exclude=["stretch"],
sort_by="temperature",
)
# Scale only should be refined
assert pytest.approx(morph_info["scale"]) != 1
assert pytest.approx(morph_info["stretch"]) == 0
def test_morphpy(self, setup_morph):
morph_results = {}
morph_file = self.testfiles[0]
for target_file in self.testfiles[1:]:
_, grm0 = morph(morph_file, morph_file)
_, grt = morph(target_file, target_file)
mr, grm = morph_arrays(
grm0, grt, scale=1, stretch=0, sort_by="temperature"
)
morph_results.update({target_file.name: mr})
class Chain:
xyallout = grm[:, 0], grm[:, 1], grt[:, 0], grt[:, 1]
chain = Chain()
rw = get_rw(chain)
del chain
assert np.allclose(
[rw], [self.morphapp_results[target_file.name]["rw"]]
)
# Check values in dictionaries are approximately equal
for file in morph_results.keys():
morph_params = morph_results[file]
morphapp_params = self.morphapp_results[file]
for key in morph_params.keys():
assert morph_params[key] == pytest.approx(
morphapp_params[key], abs=1e-08
)
def test_morphfuncy(self, setup_morph):
def gaussian(x, mu, sigma):
return np.exp(-((x - mu) ** 2) / (2 * sigma**2)) / (
sigma * np.sqrt(2 * np.pi)
)
def gaussian_like_function(x, y, mu):
return gaussian((x + y) / 2, mu, 3)
morph_r = np.linspace(0, 100, 1001)
morph_gr = np.linspace(0, 100, 1001)
target_r = np.linspace(0, 100, 1001)
target_gr = 0.5 * gaussian(target_r, 50, 5) + 0.05
morph_info, _ = morph_arrays(
np.array([morph_r, morph_gr]).T,
np.array([target_r, target_gr]).T,
scale=1,
smear=3.75,
vshift=0.01,
funcy=(gaussian_like_function, {"mu": 47.5}),
tolerance=1e-12,
)
assert pytest.approx(morph_info["scale"]) == 0.5
assert pytest.approx(morph_info["vshift"]) == 0.05
assert pytest.approx(abs(morph_info["smear"])) == 4.0
assert pytest.approx(morph_info["funcy"]["mu"]) == 50.0
# FIXME:
def test_morphfuncx(self, setup_morph):
def gaussian(x, mu, sigma):
return np.exp(-((x - mu) ** 2) / (2 * sigma**2)) / (
sigma * np.sqrt(2 * np.pi)
)
def gaussian_like_function(x, y, mu):
return gaussian((x + y) / 2, mu, 3)
morph_r = np.linspace(0, 100, 1001)
morph_gr = np.linspace(0, 100, 1001)
target_r = np.linspace(0, 100, 1001)
target_gr = 0.5 * gaussian(target_r, 50, 5) + 0.05
morph_info, _ = morph_arrays(
np.array([morph_r, morph_gr]).T,
np.array([target_r, target_gr]).T,
scale=1,
smear=3.75,
vshift=0.01,
funcy=(gaussian_like_function, {"mu": 47.5}),
tolerance=1e-12,
)
assert pytest.approx(morph_info["scale"]) == 0.5
assert pytest.approx(morph_info["vshift"]) == 0.05
assert pytest.approx(abs(morph_info["smear"])) == 4.0
assert pytest.approx(morph_info["funcy"]["mu"]) == 50.0
# FIXME:
def test_morphfuncxy(self, setup_morph):
def gaussian(x, mu, sigma):
return np.exp(-((x - mu) ** 2) / (2 * sigma**2)) / (
sigma * np.sqrt(2 * np.pi)
)
def gaussian_like_function(x, y, mu):
return gaussian((x + y) / 2, mu, 3)
morph_r = np.linspace(0, 100, 1001)
morph_gr = np.linspace(0, 100, 1001)
target_r = np.linspace(0, 100, 1001)
target_gr = 0.5 * gaussian(target_r, 50, 5) + 0.05
morph_info, _ = morph_arrays(
np.array([morph_r, morph_gr]).T,
np.array([target_r, target_gr]).T,
scale=1,
smear=3.75,
vshift=0.01,
funcy=(gaussian_like_function, {"mu": 47.5}),
tolerance=1e-12,
)
assert pytest.approx(morph_info["scale"]) == 0.5
assert pytest.approx(morph_info["vshift"]) == 0.05
assert pytest.approx(abs(morph_info["smear"])) == 4.0
assert pytest.approx(morph_info["funcy"]["mu"]) == 50.0
def test_morphpy_outputs(self, tmp_path):
r = np.linspace(0, 1, 11)
gr = np.linspace(0, 1, 11)
def linear(x, y, s):
return s * (x + y)
morph_info, _ = morph_arrays(
np.array([r, gr]).T,
np.array([r, gr]).T,
squeeze=[1, 2, 3, 4, 5],
funcy=(linear, {"s": 2.5}),
apply=True,
)
print(morph_info)
for i in range(5):
assert pytest.approx(morph_info["squeeze"][f"a{i}"]) == i + 1
assert pytest.approx(morph_info["funcy"]["s"]) == 2.5