def test_SfrFile():
sfrout = SfrFile('../examples/data/sfr_examples/sfroutput2.txt')
# will be None if pandas is not installed
if sfrout.pd is not None:
df = sfrout.get_dataframe()
assert df.layer.values[0] == 1
assert df.column.values[0] == 169
assert df.Cond.values[0] == 74510.0
assert df.col18.values[3] == 1.288E+03
sfrout = SfrFile('../examples/data/sfr_examples/test1tr.flw')
if sfrout.pd is not None:
df = sfrout.get_dataframe()
assert df.col16.values[-1] == 5.502E-02
assert df.shape == (1080, 20)
def read_sfr_output(mf2005_sfr_outputfile=None,
mf2005_SfrFile_instance=None,
mf6_sfr_stage_file=None,
mf6_sfr_budget_file=None,
model=None):
"""Read MF-2005 or MF-6 style SFR output; return as DataFrame.
"""
if model.version == 'mf6':
# get the budget output
df = aggregate_mf6_stress_budget(mf6_sfr_budget_file)
# get the stage data
if mf6_sfr_stage_file is not None:
stg = read_mf6_dependent_variable_output(mf6_sfr_stage_file,
text='stage')
df.sort_values(by=['kstpkper', 'node'], inplace=True)
stg.sort_values(by=['kstpkper', 'node'], inplace=True)
na_reaches = np.isnan(df.time.values)
df.loc[~na_reaches].to_csv('df.csv')
stg.loc[~na_reaches].to_csv('stg.csv')
#assert np.allclose(df.time.values, stg.time.values)
assert np.allclose(df.loc[~na_reaches].time.values,
stg.loc[~na_reaches].time.values)
assert np.array_equal(df.node.values, stg.node.values)
df['stage'] = stg['stage']
# get the row, column location of SFR cells
if model.sfr is not None:
rd = pd.DataFrame(model.sfr.packagedata.array.copy())
assert rd.rno.min() == 0
assert df.node.min() == 0
if not isinstance(rd.cellid.values[0], int):
rno_cellid = dict(zip(rd.rno, rd.cellid))
for i, dim in enumerate(['k', 'i', 'j']):
df[dim] = pd.to_numeric(
[rno_cellid[rno][i] for rno in df.node.values],
errors='coerce')
df.dropna(subset=['k', 'i', 'j'], axis=0, inplace=True)
# can't convert to integers if nans are present
for dim in ['k', 'i', 'j']:
df[dim] = df[dim].astype(int)
assert 'int' in df[dim].dtype.name
else:
# SFR output
if mf2005_sfr_outputfile is not None:
sfrobj = SfrFile(mf2005_sfr_outputfile)
elif mf2005_SfrFile_instance is not None:
sfrobj = mf2005_SfrFile_instance
else:
print(
'Need path to SFR tabular budget output or FloPy SfrFile instance.'
)
df = sfrobj.df.copy()
df.sort_values(by=['segment', 'reach'], inplace=True)
return df
def import_sfr_out(self, path=None, name=None, ext='.sfr.out'):
"""TODO: Docs
:param path: (Default value = None)
:param name: (Default value = None)
:param ext: (Default value = '.sfr.out')
:returns: DataFrame, SFR data
"""
if path:
sfrout = SfrFile(os.path.join(path, name + ext))
self.sfr_df = sfrout.get_dataframe()
else:
sfrout = SfrFile(os.path.join(self.data_folder, self.name + ext))
self.sfr_df = sfrout.get_dataframe()
# End if
return self.sfr_df
def test_SfrFile():
common_names = [
'layer', 'row', 'column', 'segment', 'reach', 'Qin', 'Qaquifer',
'Qout', 'Qovr', 'Qprecip', 'Qet', 'stage', 'depth', 'width', 'Cond'
]
sfrout = SfrFile('../examples/data/sfr_examples/sfroutput2.txt')
assert sfrout.ncol == 18, sfrout.ncol
assert sfrout.names == common_names + ['Qwt', 'delUzstor', 'gw_head'],\
sfrout.names
assert sfrout.times == [(0, 0), (49, 1)], sfrout.times
# will be None if pandas is not installed
if sfrout.pd is not None:
df = sfrout.get_dataframe()
assert df.layer.values[0] == 1
assert df.column.values[0] == 169
assert df.Cond.values[0] == 74510.0
assert df.gw_head.values[3] == 1.288E+03
sfrout = SfrFile('../examples/data/sfr_examples/test1tr.flw')
assert sfrout.ncol == 16, sfrout.ncol
assert sfrout.names == common_names + ['gradient'], sfrout.names
expected_times = [(0, 0), (4, 0),
(9, 0), (12, 0), (14, 0), (19, 0), (24, 0), (29, 0),
(32, 0), (34, 0), (39, 0), (44, 0), (49, 0), (0, 1),
(4, 1), (9, 1), (12, 1), (14, 1), (19, 1), (24, 1),
(29, 1), (32, 1), (34, 1), (39, 1), (44, 1), (45, 1),
(46, 1), (47, 1), (48, 1), (49, 1)]
assert sfrout.times == expected_times, sfrout.times
if sfrout.pd is not None:
df = sfrout.get_dataframe()
assert df.gradient.values[-1] == 5.502E-02
assert df.shape == (1080, 20)
ml = flopy.modflow.Modflow.load('test1tr.nam',
model_ws=path,
exe_name='mf2005')
ml.change_model_ws(outpath)
ml.write_input()
ml.run_model()
sfrout = SfrFile(os.path.join(outpath, 'test1tr.flw'))
assert sfrout.ncol == 16, sfrout.ncol
assert sfrout.names == common_names + ['gradient'], sfrout.names
expected_times = [(0, 0), (4, 0),
(9, 0), (12, 0), (14, 0), (19, 0), (24, 0), (29, 0),
(32, 0), (34, 0), (39, 0), (44, 0), (49, 0), (0, 1),
(4, 1), (9, 1), (12, 1), (14, 1), (19, 1), (24, 1),
(29, 1), (32, 1), (34, 1), (39, 1), (44, 1), (45, 1),
(46, 1), (47, 1), (48, 1), (49, 1)]
assert sfrout.times == expected_times, sfrout.times
def test_SfrFile():
sfrout = SfrFile('../examples/data/sfr_examples/sfroutput2.txt')
# will be None if pandas is not installed
if sfrout.pd is not None:
df = sfrout.get_dataframe()
assert df.layer.values[0] == 1
assert df.column.values[0] == 169
assert df.Cond.values[0] == 74510.0
assert df.col18.values[3] == 1.288E+03
sfrout = SfrFile('../examples/data/sfr_examples/test1tr.flw')
if sfrout.pd is not None:
df = sfrout.get_dataframe()
assert df.col16.values[-1] == 5.502E-02
assert df.shape == (1080, 20)
def read_sfr_output(mf2005_sfr_outputfile=None,
mf2005_SfrFile_instance=None,
mf6_sfr_stage_file=None,
mf6_sfr_budget_file=None,
mf6_package_data=None,
model=None, grid_type='structured'):
"""Read MF-2005 or MF-6 style SFR output; return as DataFrame.
"""
model_version = None
packagedata = None
if model is not None:
model_version = model.version
if model_version == 'mf6':
packagedata = pd.DataFrame(model.sfr.packagedata.array.copy())
elif mf6_package_data is not None:
model_version = 'mf6'
if isinstance(mf6_package_data, str) or isinstance(mf6_package_data, Path):
skiprows = 0
names = None
with open(mf6_package_data) as src:
for line in src:
if line.strip().startswith('#'):
names = line.strip().split()
skiprows += 1
else:
ncol = len(line.strip().split())
break
if names is None:
if grid_type == 'structured':
names = ['rno', 'k', 'i', 'j', 'rlen', 'rwid', 'rgrd', 'rtp', 'rbth', 'rhk',
'man', 'ncon', 'ustrf', 'ndv']
else:
names = ['rno', 'cellid', 'rlen', 'rwid', 'rgrd', 'rtp', 'rbth', 'rhk',
'man', 'ncon', 'ustrf', 'ndv']
for i, _ in enumerate(range(len(names), ncol)):
names.append(f'aux_col{i+1}')
else:
names[0] = names[0].strip('#')
# read the packagedata as a string to handle "none" values
with open(mf6_package_data) as src:
raw_pd = src.read()
raw_pd = raw_pd.lower().replace('none', '0 0 0')
packagedata = pd.read_csv(io.StringIO(raw_pd), names=names,
skiprows=skiprows, delim_whitespace=True)
for col in ['rno', 'k', 'i', 'j']:
if col in packagedata:
packagedata[col] -= 1
if 'cellid' in packagedata.columns:
if not isinstance(packagedata['cellid'][0], int):
packagedata['cellid'] = [(c[0]-1, c[1] -1, c[2] -1) for c in packagedata['cellid']]
else:
packagedata['cellid'] -=1
else:
# make the dataframe on the .array attribute for flopy objects
# or mf6_package_data is assumed to be array-like
packagedata = pd.DataFrame(getattr(mf6_package_data, 'array', mf6_package_data))
if model_version == 'mf6':
# get the budget output
df = aggregate_mf6_stress_budget(mf6_sfr_budget_file)
# get the stage data
if mf6_sfr_stage_file is not None:
stg = read_mf6_dependent_variable_output(mf6_sfr_stage_file,
text='stage')
df.sort_values(by=['kstpkper', 'node'], inplace=True)
stg.sort_values(by=['kstpkper', 'node'], inplace=True)
df.set_index(['kstpkper', 'node'], inplace=True)
stg.set_index(['kstpkper', 'node'], inplace=True)
na_reaches = np.isnan(df.time.values)
#df.loc[~na_reaches].to_csv('df.csv')
#stg.loc[~na_reaches].to_csv('stg.csv')
#assert np.allclose(df.time.values, stg.time.values)
assert np.allclose(df.loc[~na_reaches].time.values,
stg.loc[~na_reaches].time.values)
assert np.array_equal(df.index, stg.index)
df['stage'] = stg['stage']
df.reset_index(inplace=True)
# get the row, column location of SFR cells;
# compute stream depths
if packagedata is not None:
rd = packagedata
# convert reach number to zero-based
if rd.rno.min() == 1:
rd['rno'] -= 1
assert rd.rno.min() == 0
assert df.node.min() == 0
rno_strtop = dict(zip(rd.rno, rd.rtp))
df['strtop'] = pd.to_numeric([rno_strtop[rno] for rno in df.node.values], errors='coerce')
# fill nan stages with their streambed tops
isna = df['stage'].isna()
df.loc[isna, 'stage'] = df.loc[isna, 'strtop']
df['depth'] = df['stage'] - df['strtop']
if 'cellid' not in rd.columns:
rd['cellid'] = list(zip(rd['k'], rd['i'], rd['j']))
rno_cellid = dict(zip(rd.rno, rd.cellid))
for i, dim in enumerate(['k', 'i', 'j']):
df[dim] = pd.to_numeric([rno_cellid[rno][i] for rno in df.node.values], errors='coerce')
df.dropna(subset=['k', 'i', 'j'], axis=0, inplace=True)
# can't convert to integers if nans are present
for dim in ['k', 'i', 'j']:
df[dim] = df[dim].astype(int)
assert 'int' in df[dim].dtype.name
else:
# SFR output
if mf2005_sfr_outputfile is not None:
sfrobj = SfrFile(mf2005_sfr_outputfile)
elif mf2005_SfrFile_instance is not None:
sfrobj = mf2005_SfrFile_instance
else:
print('Need path to SFR tabular budget output or FloPy SfrFile instance.')
df = sfrobj.df.copy()
df.sort_values(by=['segment', 'reach'], inplace=True)
return df
def test_SfrFile():
common_names = [
"layer",
"row",
"column",
"segment",
"reach",
"Qin",
"Qaquifer",
"Qout",
"Qovr",
"Qprecip",
"Qet",
"stage",
"depth",
"width",
"Cond",
]
sfrout = SfrFile("../examples/data/sfr_examples/sfroutput2.txt")
assert sfrout.ncol == 18, sfrout.ncol
assert sfrout.names == common_names + [
"Qwt",
"delUzstor",
"gw_head",
], sfrout.names
assert sfrout.times == [(0, 0), (49, 1)], sfrout.times
# will be None if pandas is not installed
if sfrout.pd is not None:
df = sfrout.get_dataframe()
assert df.layer.values[0] == 1
assert df.column.values[0] == 169
assert df.Cond.values[0] == 74510.0
assert df.gw_head.values[3] == 1.288e03
sfrout = SfrFile("../examples/data/sfr_examples/test1tr.flw")
assert sfrout.ncol == 16, sfrout.ncol
assert sfrout.names == common_names + ["gradient"], sfrout.names
expected_times = [
(0, 0),
(4, 0),
(9, 0),
(12, 0),
(14, 0),
(19, 0),
(24, 0),
(29, 0),
(32, 0),
(34, 0),
(39, 0),
(44, 0),
(49, 0),
(0, 1),
(4, 1),
(9, 1),
(12, 1),
(14, 1),
(19, 1),
(24, 1),
(29, 1),
(32, 1),
(34, 1),
(39, 1),
(44, 1),
(45, 1),
(46, 1),
(47, 1),
(48, 1),
(49, 1),
]
assert sfrout.times == expected_times, sfrout.times
if sfrout.pd is not None:
df = sfrout.get_dataframe()
assert df.gradient.values[-1] == 5.502e-02
assert df.shape == (1080, 20)
ml = flopy.modflow.Modflow.load("test1tr.nam",
model_ws=path,
exe_name="mf2005")
ml.change_model_ws(outpath)
ml.write_input()
ml.run_model()
sfrout = SfrFile(os.path.join(outpath, "test1tr.flw"))
assert sfrout.ncol == 16, sfrout.ncol
assert sfrout.names == common_names + ["gradient"], sfrout.names
expected_times = [
(0, 0),
(4, 0),
(9, 0),
(12, 0),
(14, 0),
(19, 0),
(24, 0),
(29, 0),
(32, 0),
(34, 0),
(39, 0),
(44, 0),
(49, 0),
(0, 1),
(4, 1),
(9, 1),
(12, 1),
(14, 1),
(19, 1),
(24, 1),
(29, 1),
(32, 1),
(34, 1),
(39, 1),
(44, 1),
(45, 1),
(46, 1),
(47, 1),
(48, 1),
(49, 1),
]
assert sfrout.times == expected_times, sfrout.times