def to_shapefile(self, filename, kper=None):
"""
Export stress period boundary condition (MfList) data for a specified
stress period
Parameters
----------
filename : str
Shapefile name to write
kper : int
MODFLOW zero-based stress period number to return. (default is None)
Returns
----------
None
See Also
--------
Notes
-----
Examples
--------
>>> import flopy
>>> ml = flopy.modflow.Modflow.load('test.nam')
>>> ml.wel.to_shapefile('test_hk.shp', kper=1)
"""
if self.sr is None:
raise Exception("MfList.to_shapefile: SpatialReference not set")
import flopy.utils.flopy_io as fio
if kper is None:
keys = self.data.keys()
keys.sort()
else:
keys = [kper]
array_dict = {}
for kk in keys:
arrays = self.to_array(kk)
for name, array in arrays.items():
for k in range(array.shape[0]):
#aname = name+"{0:03d}_{1:02d}".format(kk, k)
n = fio.shape_attr_name(name, length=4)
aname = "{}{:03d}{:03d}".format(n, k+1, int(kk)+1)
array_dict[aname] = array[k]
fio.write_grid_shapefile(filename, self.sr, array_dict)
def mflist_helper(f, mfl, **kwargs):
""" export helper for MfList instances
Parameters
-----------
f : string (filename) or existing export instance type (NetCdf only for now)
mfl : MfList instance
"""
assert isinstance(mfl, MfList) \
, "mflist_helper only helps MfList instances"
if isinstance(f, str) and f.lower().endswith(".nc"):
f = NetCdf(f, mfl.model)
if isinstance(f, str) and f.lower().endswith(".shp"):
kper = kwargs.get("kper",None)
if mfl.sr is None:
raise Exception("MfList.to_shapefile: SpatialReference not set")
import flopy.utils.flopy_io as fio
if kper is None:
keys = mfl.data.keys()
keys.sort()
else:
keys = [kper]
array_dict = {}
for kk in keys:
arrays = mfl.to_array(kk)
for name, array in arrays.items():
for k in range(array.shape[0]):
#aname = name+"{0:03d}_{1:02d}".format(kk, k)
n = fio.shape_attr_name(name, length=4)
aname = "{}{:03d}{:03d}".format(n, k+1, int(kk)+1)
array_dict[aname] = array[k]
shapefile_utils.write_grid_shapefile(f, mfl.sr, array_dict)
elif isinstance(f, NetCdf) or isinstance(f,dict):
base_name = mfl.package.name[0].lower()
#f.log("getting 4D masked arrays for {0}".format(base_name))
#m4d = mfl.masked_4D_arrays
#f.log("getting 4D masked arrays for {0}".format(base_name))
#for name, array in m4d.items():
for name, array in mfl.masked_4D_arrays_itr():
var_name = base_name + '_' + name
if isinstance(f,dict):
f[var_name] = array
continue
f.log("processing {0} attribute".format(name))
units = None
if var_name in NC_UNITS_FORMAT:
units = NC_UNITS_FORMAT[var_name].format(f.grid_units, f.time_units)
precision_str = NC_PRECISION_TYPE[mfl.dtype[name].type]
if var_name in NC_LONG_NAMES:
attribs = {"long_name":NC_LONG_NAMES[var_name]}
else:
attribs = {"long_name":var_name}
attribs["coordinates"] = "time layer latitude longitude"
attribs["min"] = np.nanmin(array)
attribs["max"] = np.nanmax(array)
if units is not None:
attribs["units"] = units
try:
var = f.create_variable(var_name, attribs, precision_str=precision_str,
dimensions=("time", "layer", "y", "x"))
except Exception as e:
estr = "error creating variable {0}:\n{1}".format(var_name, str(e))
f.logger.warn(estr)
raise Exception(estr)
array[np.isnan(array)] = f.fillvalue
try:
var[:] = array
except Exception as e:
estr = "error setting array to variable {0}:\n{1}".format(var_name, str(e))
f.logger.warn(estr)
raise Exception(estr)
f.log("processing {0} attribute".format(name))
return f
else:
raise NotImplementedError("unrecognized export argument:{0}".format(f))
def mflist_helper(f, mfl, **kwargs):
""" export helper for MfList instances
Parameters
-----------
f : string (filename) or existing export instance type (NetCdf only for now)
mfl : MfList instance
"""
assert isinstance(mfl, MfList) \
, "mflist_helper only helps MfList instances"
if isinstance(f, str) and f.lower().endswith(".nc"):
f = NetCdf(f, mfl.model)
if isinstance(f, str) and f.lower().endswith(".shp"):
sparse = kwargs.get("sparse", False)
kper = kwargs.get("kper", 0)
squeeze = kwargs.get("squeeze", True)
if mfl.sr is None:
raise Exception("MfList.to_shapefile: SpatialReference not set")
import flopy.utils.flopy_io as fio
if kper is None:
keys = mfl.data.keys()
keys.sort()
else:
keys = [kper]
if not sparse:
array_dict = {}
for kk in keys:
arrays = mfl.to_array(kk)
for name, array in arrays.items():
for k in range(array.shape[0]):
# aname = name+"{0:03d}_{1:02d}".format(kk, k)
n = fio.shape_attr_name(name, length=4)
aname = "{}{:03d}{:03d}".format(n, k + 1, int(kk) + 1)
array_dict[aname] = array[k]
shapefile_utils.write_grid_shapefile(f, mfl.sr, array_dict)
else:
from ..export.shapefile_utils import recarray2shp
from ..utils.geometry import Polygon
#if np.isscalar(kper):
# kper = [kper]
sr = mfl.model.sr
df = mfl.get_dataframe(squeeze=squeeze)
if 'kper' in kwargs or df is None:
ra = mfl[kper]
verts = np.array(sr.get_vertices(ra.i, ra.j))
elif df is not None:
verts = sr.get_vertices(df.i.values, df.j.values)
ra = df.to_records(index=False)
# write the projection file
if sr.epsg is None:
epsg = kwargs.get('epsg', None)
else:
epsg = sr.epsg
prj = kwargs.get('prj', None)
polys = np.array([Polygon(v) for v in verts])
recarray2shp(ra, geoms=polys, shpname=f, epsg=epsg, prj=prj)
elif isinstance(f, NetCdf) or isinstance(f, dict):
base_name = mfl.package.name[0].lower()
# f.log("getting 4D masked arrays for {0}".format(base_name))
# m4d = mfl.masked_4D_arrays
# f.log("getting 4D masked arrays for {0}".format(base_name))
# for name, array in m4d.items():
for name, array in mfl.masked_4D_arrays_itr():
var_name = base_name + '_' + name
if isinstance(f, dict):
f[var_name] = array
continue
f.log("processing {0} attribute".format(name))
units = None
if var_name in NC_UNITS_FORMAT:
units = NC_UNITS_FORMAT[var_name].format(f.grid_units,
f.time_units)
precision_str = NC_PRECISION_TYPE[mfl.dtype[name].type]
if var_name in NC_LONG_NAMES:
attribs = {"long_name": NC_LONG_NAMES[var_name]}
else:
attribs = {"long_name": var_name}
attribs["coordinates"] = "time layer latitude longitude"
attribs["min"] = np.nanmin(array)
attribs["max"] = np.nanmax(array)
if np.isnan(attribs["min"]) or np.isnan(attribs["max"]):
raise Exception(
"error processing {0}: all NaNs".format(var_name))
if units is not None:
attribs["units"] = units
try:
var = f.create_variable(var_name, attribs,
precision_str=precision_str,
dimensions=("time", "layer", "y", "x"))
except Exception as e:
estr = "error creating variable {0}:\n{1}".format(var_name,
str(e))
f.logger.warn(estr)
raise Exception(estr)
array[np.isnan(array)] = f.fillvalue
try:
var[:] = array
except Exception as e:
estr = "error setting array to variable {0}:\n{1}".format(
var_name, str(e))
f.logger.warn(estr)
raise Exception(estr)
f.log("processing {0} attribute".format(name))
return f
else:
raise NotImplementedError("unrecognized export argument:{0}".format(f))
def mflist_helper(f, mfl, **kwargs):
""" export helper for MfList instances
Parameters
-----------
f : string (filename) or existing export instance type (NetCdf only for now)
mfl : MfList instance
"""
assert isinstance(mfl, MfList) \
, "mflist_helper only helps MfList instances"
if isinstance(f, str) and f.lower().endswith(".nc"):
f = NetCdf(f, mfl.model)
if isinstance(f, str) and f.lower().endswith(".shp"):
sparse = kwargs.get("sparse", False)
kper = kwargs.get("kper", 0)
squeeze = kwargs.get("squeeze", True)
if mfl.sr is None:
raise Exception("MfList.to_shapefile: SpatialReference not set")
import flopy.utils.flopy_io as fio
if kper is None:
keys = mfl.data.keys()
keys.sort()
else:
keys = [kper]
if not sparse:
array_dict = {}
for kk in keys:
arrays = mfl.to_array(kk)
for name, array in arrays.items():
for k in range(array.shape[0]):
# aname = name+"{0:03d}_{1:02d}".format(kk, k)
n = fio.shape_attr_name(name, length=4)
aname = "{}{:03d}{:03d}".format(n, k + 1, int(kk) + 1)
array_dict[aname] = array[k]
shapefile_utils.write_grid_shapefile(f, mfl.sr, array_dict)
else:
from ..export.shapefile_utils import recarray2shp
from ..utils.geometry import Polygon
#if np.isscalar(kper):
# kper = [kper]
sr = mfl.model.sr
df = mfl.get_dataframe(squeeze=squeeze)
if 'kper' in kwargs or df is None:
ra = mfl[kper]
verts = np.array(sr.get_vertices(ra.i, ra.j))
elif df is not None:
verts = sr.get_vertices(df.i.values, df.j.values)
ra = df.to_records(index=False)
# write the projection file
if sr.epsg is None:
epsg = kwargs.get('epsg', None)
else:
epsg = sr.epsg
prj = kwargs.get('prj', None)
polys = np.array([Polygon(v) for v in verts])
recarray2shp(ra, geoms=polys, shpname=f, epsg=epsg, prj=prj)
elif isinstance(f, NetCdf) or isinstance(f, dict):
base_name = mfl.package.name[0].lower()
# f.log("getting 4D masked arrays for {0}".format(base_name))
# m4d = mfl.masked_4D_arrays
# f.log("getting 4D masked arrays for {0}".format(base_name))
# for name, array in m4d.items():
for name, array in mfl.masked_4D_arrays_itr():
var_name = base_name + '_' + name
if isinstance(f, dict):
f[var_name] = array
continue
f.log("processing {0} attribute".format(name))
units = None
if var_name in NC_UNITS_FORMAT:
units = NC_UNITS_FORMAT[var_name].format(f.grid_units,
f.time_units)
precision_str = NC_PRECISION_TYPE[mfl.dtype[name].type]
if var_name in NC_LONG_NAMES:
attribs = {"long_name": NC_LONG_NAMES[var_name]}
else:
attribs = {"long_name": var_name}
attribs["coordinates"] = "time layer latitude longitude"
attribs["min"] = np.nanmin(array)
attribs["max"] = np.nanmax(array)
if np.isnan(attribs["min"]) or np.isnan(attribs["max"]):
raise Exception(
"error processing {0}: all NaNs".format(var_name))
if units is not None:
attribs["units"] = units
try:
var = f.create_variable(var_name, attribs,
precision_str=precision_str,
dimensions=("time", "layer", "y", "x"))
except Exception as e:
estr = "error creating variable {0}:\n{1}".format(var_name,
str(e))
f.logger.warn(estr)
raise Exception(estr)
array[np.isnan(array)] = f.fillvalue
try:
var[:] = array
except Exception as e:
estr = "error setting array to variable {0}:\n{1}".format(
var_name, str(e))
f.logger.warn(estr)
raise Exception(estr)
f.log("processing {0} attribute".format(name))
return f
else:
raise NotImplementedError("unrecognized export argument:{0}".format(f))
