def test_model_summary_df(nepc_connect):
"""Verify nepc.model_summary_df returns a dataframe"""
# TODO: check formatting of summary dataframe
# FIXME: randomly sample models
fict = nepc.Model(nepc_connect[1], "fict")
df = fict.summary(lower=0, upper=10)
assert isinstance(df, pd.io.formats.style.Styler)
def test_Model_class(nepc_connect):
"""Verify that the nepc.Model class is a list of CS type and
test the methods within the Class."""
fict = nepc.Model(nepc_connect[1], "fict")
# FIXME: randomly sample the models in the database
# FIXME: randomly sample the cross sections in the model
assert isinstance(fict.cs, list)
assert isinstance(fict.cs[0].metadata, dict)
assert isinstance(fict.cs[0].data, dict)
# test len method
# FIXME use data in .mod files to determine number of CS in Model for assert
assert len(fict) == 30
def test_format_model_write_file(nepc_connect, tmpdir):
file = tmpdir.join('lxcat.txt')
fict = nepc.Model(nepc_connect[1], "fict")
parser.format_model(fict, type='lxcat', filename=str(file))
lines = file.read().splitlines()
assert len(lines) == 1981
assert lines[0] == 'EXCITATION'
assert lines[99] == '1.500000e+03\t1.130000e-20'
assert lines[184] == 'COLUMNS: Energy (eV) | Cross section (m2)'
with open(str(file), 'rb') as f:
fb = f.read()
readable_hash = hashlib.md5(fb).hexdigest()
assert readable_hash == '8f8c7935e3d80ea20ca9fffd98391ade'
def test_format_model_write_file(nepc_connect, tmpdir):
file = tmpdir.join('lxcat.txt')
fict = nepc.Model(nepc_connect[1], "fict")
format_model(fict, type='lxcat', filename=str(file))
lines = file.read().splitlines()
assert len(lines) == 1951
assert lines[0] == 'EXCITATION'
assert lines[99] == '3.000000e+03\t6.300000e-21'
assert lines[179] == 'COLUMNS: Energy (eV) | Cross section (m2)'
with open(str(file), 'rb') as f:
fb = f.read()
readable_hash = hashlib.md5(fb).hexdigest()
assert readable_hash == 'b0c0d9564c3f9c722a27c6e5a4d27260'
def test_model_subset(nepc_connect):
"""Verify that Model.subset returns a proper
subset of cross sections from a model within the NEPC MySQL database"""
# TODO: test for lhsB and rhsB
# FIXME: randomly sample models and cross sections within the model
fict = nepc.Model(nepc_connect[1], "fict")
fict_subset = fict.subset({'process': 'excitation',
'lhsA': 'N2(X1Sigmag+)'})
assert isinstance(fict_subset, list)
assert isinstance(fict_subset[0].metadata, dict)
assert isinstance(fict_subset[0].data, dict)
with pytest.raises(Exception):
assert fict.subset()
pd.set_option('max_colwidth', 100)
# %% [markdown]
# ***NOTE: You may need to modify the `local` argument in the next command.
# `local=True` points to a local copy of the NEPC database.
# `local=False` points to a computer serving a NEPC MySQL database.
# See `nepc.util.config.production()` and set the `$NEPC_PRODUCTION` environment variable.***
# %%
cnx, cursor = nepc.connect(local=False, test=True)
# %% [markdown]
# # Full fict dataset
# %%
fict = nepc.Model(cursor, "fict")
# %%
type(fict.summary())
# %%
fict.summary()
# %% [markdown]
# To inspect the `metadata` or `data` attribute of a particular cross section, use the `Model.subset` method.
# %%
fict.subset(metadata={'cs_id': 10})[0].metadata
# %% [markdown]
# # Electron-impact excitations provided by Model `fict`
