def pandas_to_matrix(series_or_dataframe):
"""Converts a Series or DataFrame back to a MatrixData object
Args:
series_or_dataframe: Series or DataFrame
Returns:
MatrixData object
"""
data_values = series_or_dataframe.to_numpy(
) if _USE_PD_TO_NUMPY else series_or_dataframe.values
if isinstance(series_or_dataframe, pd.Series):
indices = series_or_dataframe.index.tolist()
md = MatrixData(indices)
md.from_numpy(data_values)
return md
elif isinstance(series_or_dataframe, pd.DataFrame):
indices = series_or_dataframe.index.tolist(
), series_or_dataframe.columns.tolist()
md = MatrixData(indices)
md.from_numpy(data_values)
return md
else:
raise TypeError("Expected a Series or DataFrame, got %s" %
type(series_or_dataframe))
def _Execute(self):
with _m.logbook_trace(name="%s v%s" %(self.__class__.__name__, self.version), \
attributes= self._GetAtts()):
matrix = _util.initializeMatrix(self.MatrixId)
if self.MatrixDescription:
matrix.description = self.MatrixDescription
data = _MatrixData.load(self.ImportFile)
origins, destinations = data.indices
origins = set(origins)
destinations = set(destinations)
if origins ^ destinations:
raise Exception(
"Asymmetrical matrix detected. Matrix must be square.")
if _util.databankHasDifferentZones(_bank):
zones = set(self.Scenario.zone_numbers)
if zones ^ origins:
with _m.logbook_trace(
"Zones in matrix file but not in scenario"):
for index in origins - zones:
_m.logbook_write(index)
with _m.logbook_trace("Zones in scenario but not in file"):
for index in zones - origins:
_m.logbook_write(index)
raise Exception(
"Matrix zones not compatible with scenario %s. Check logbook for details."
% self.Scenario)
matrix.set_data(data, scenario_id=self.Scenario.id)
else:
sc = _bank.scenarios()[0]
zones = set(sc.zone_numbers)
if zones ^ origins:
with _m.logbook_trace(
"Zones in matrix file but not in scenario"):
for index in origins - zones:
_m.logbook_write(index)
with _m.logbook_trace("Zones in scenario but not in file"):
for index in zones - origins:
_m.logbook_write(index)
raise Exception(
"Matrix zones not compatible with emmebank zone system. Check Logbook for details."
)
matrix.set_data(data)
self.TRACKER.completeTask()
def _Execute(self):
with _m.logbook_trace(name="%s v%s" %(self.__class__.__name__, self.version), \
attributes= self._GetAtts()):
matrix = _util.initializeMatrix(self.MatrixId)
if self.MatrixDescription:
matrix.description = self.MatrixDescription
data = _MatrixData.load(self.ImportFile)
origins, destinations = data.indices
origins = set(origins)
destinations = set(destinations)
if origins ^ destinations:
raise Exception("Asymmetrical matrix detected. Matrix must be square.")
if _util.databankHasDifferentZones(_bank):
zones = set(self.Scenario.zone_numbers)
if zones ^ origins:
with _m.logbook_trace("Zones in matrix file but not in scenario"):
for index in origins - zones: _m.logbook_write(index)
with _m.logbook_trace("Zones in scenario but not in file"):
for index in zones - origins: _m.logbook_write(index)
raise Exception("Matrix zones not compatible with scenario %s. Check logbook for details." %self.Scenario)
matrix.set_data(data, scenario_id= self.Scenario.id)
else:
sc = _bank.scenarios()[0]
zones = set(sc.zone_numbers)
if zones ^ origins:
with _m.logbook_trace("Zones in matrix file but not in scenario"):
for index in origins - zones: _m.logbook_write(index)
with _m.logbook_trace("Zones in scenario but not in file"):
for index in zones - origins: _m.logbook_write(index)
raise Exception("Matrix zones not compatible with emmebank zone system. Check Logbook for details.")
matrix.set_data(data)
self.TRACKER.completeTask()
def pandas_to_matrix(series_or_dataframe):
'''
Converts a Series or DataFrame back to a MatrixData object
Args:
series_or_dataframe: Series or DataFrame
Returns: MatrixData object.
'''
if isinstance(series_or_dataframe, pd.Series):
indices = list(series_or_dataframe.index.values)
md = MatrixData(indices)
md.from_numpy(series_or_dataframe.values)
return md
elif isinstance(series_or_dataframe, pd.DataFrame):
indices = list(series_or_dataframe.index.values), list(
series_or_dataframe.columns.values)
md = MatrixData(indices)
md.from_numpy(series_or_dataframe.values)
return md
else:
raise TypeError("Expected a Series or DataFrame, got %s" %
type(series_or_dataframe))
def pandas_to_matrix(series_or_dataframe):
'''
Converts a Series or DataFrame back to a MatrixData object
Args:
series_or_dataframe: Series or DataFrame
Returns: MatrixData object.
'''
if isinstance(series_or_dataframe, pd.Series):
indices = list(series_or_dataframe.index.values)
md = MatrixData(indices)
md.from_numpy(series_or_dataframe.values)
return md
elif isinstance(series_or_dataframe, pd.DataFrame):
indices = list(series_or_dataframe.index.values), list(series_or_dataframe.columns.values)
md = MatrixData(indices)
md.from_numpy(series_or_dataframe.values)
return md
else: raise TypeError("Expected a Series or DataFrame, got %s" %type(series_or_dataframe))
def pandas_to_matrix(series_or_dataframe, mtx_out=None, scenario_id=None):
"""
Converts a Series or DataFrame to an Emme Matrix; either as a MatrixData instance or saved to a Matrix instance.
Args:
series_or_dataframe: The Series or DataFrame to convert.
mtx_out: A Matrix instance (usually retrieved from Emmebank.matrix()) or None. If provided, the resulting matrix
data will be saved to the Emmebank
scenario_id: Optional scenario ID to pass to Matrix.set_data()
Returns:
MatrixData if `mtx_out` is None; None otherwise.
"""
if isinstance(series_or_dataframe, pd.Series):
indices = list(series_or_dataframe.index.values)
md = MatrixData(indices)
array = series_or_dataframe.values
if array.flags.f_contiguous:
array = np.ascontiguousarray(array)
md.from_numpy(array)
elif isinstance(series_or_dataframe, pd.DataFrame):
indices = list(series_or_dataframe.index.values), list(series_or_dataframe.columns.values)
md = MatrixData(indices)
array = series_or_dataframe.values
if array.flags.f_contiguous:
array = np.ascontiguousarray(array)
md.from_numpy(array)
else: raise TypeError("Expected a Series or DataFrame, got %s" % type(series_or_dataframe))
if mtx_out is not None:
mtx_out.set_data(md, scenario_id=scenario_id)
return
return md
def _Execute(self):
with _m.logbook_trace(name="%s v%s" %(self.__class__.__name__, self.version), \
attributes= self._GetAtts()):
if self.MatrixId is None:
matrix = _util.initializeMatrix(
id=self.NewMatrixID,
name=self.NewMatrixName,
description=self.NewMatrixDescription,
matrix_type=self.NewMatrixType)
else:
matrix = _util.initializeMatrix(self.MatrixId)
if self.MatrixDescription:
matrix.description = self.MatrixDescription
if str(self.ImportFile)[-2:] == "gz":
new_file = 'matrix.mtx'
with gzip.open(self.ImportFile,
'rb') as zip_file, open(new_file,
'wb') as non_zip_file:
shutil.copyfileobj(zip_file, non_zip_file)
data = _MatrixData.load(new_file)
os.remove(new_file)
else:
data = _MatrixData.load(self.ImportFile)
self.MatrixType = matrix.type
# 2D matrix
if self.MatrixType == "mf":
origins, destinations = data.indices
origins = set(origins)
destinations = set(destinations)
if origins ^ destinations:
raise Exception(
"Asymmetrical matrix detected. Matrix must be square.")
# 1D matrix
else:
origins = data.indices[0]
origins = set(origins)
if _util.databankHasDifferentZones(_bank):
zones = set(self.Scenario.zone_numbers)
if zones ^ origins:
with _m.logbook_trace(
"Zones in matrix file but not in scenario"):
for index in origins - zones:
_m.logbook_write(index)
with _m.logbook_trace("Zones in scenario but not in file"):
for index in zones - origins:
_m.logbook_write(index)
raise Exception(
"Matrix zones not compatible with scenario %s. Check logbook for details."
% self.Scenario)
matrix.set_data(data, scenario_id=self.Scenario.id)
else:
sc = _bank.scenarios()[0]
zones = set(sc.zone_numbers)
if zones ^ origins:
with _m.logbook_trace(
"Zones in matrix file but not in scenario"):
for index in origins - zones:
_m.logbook_write(index)
with _m.logbook_trace("Zones in scenario but not in file"):
for index in zones - origins:
_m.logbook_write(index)
raise Exception(
"Matrix zones not compatible with emmebank zone system. Check Logbook for details."
)
matrix.set_data(data)
self.TRACKER.completeTask()