def get_mazpairs(self, omaz, dmaz, attribute):
"""
look up attribute values of maz od pairs in sparse maz_to_maz df
Parameters
----------
omaz: array-like list of omaz zone_ids
dmaz: array-like list of omaz zone_ids
attribute: str name of attribute column in maz_to_maz_df
Returns
-------
Numpy.ndarray: list of attribute values for od pairs
"""
# # this is slower
# s = pd.merge(pd.DataFrame({'OMAZ': omaz, 'DMAZ': dmaz}),
# self.maz_to_maz_df,
# how="left")[attribute]
# synthetic index method i : omaz_dmaz
i = np.asanyarray(omaz) * self.maz_ceiling + np.asanyarray(dmaz)
s = util.quick_loc_df(i, self.maz_to_maz_df, attribute)
# FIXME - no point in returning series?
return np.asanyarray(s)
def get_maztappairs(self, maz, tap, attribute):
# synthetic i method : maz_tap
i = np.asanyarray(maz) * self.maz2tap_cardinality + np.asanyarray(tap)
s = quick_loc_df(i, self.maz2tap_df, attribute)
# FIXME - no point in returning series? unless maz and tap have sme index?
return np.asanyarray(s)
def get_mazpairs(self, omaz, dmaz, attribute):
# # this is slower
# s = pd.merge(pd.DataFrame({'OMAZ': omaz, 'DMAZ': dmaz}),
# self.maz2maz_df,
# how="left")[attribute]
# synthetic index method i : omaz_dmaz
i = np.asanyarray(omaz) * self.maz2maz_cardinality + np.asanyarray(dmaz)
s = quick_loc_df(i, self.maz2maz_df, attribute)
# FIXME - no point in returning series? unless maz and tap have same index?
return np.asanyarray(s)
def tour_available(self, window_row_ids, tdds):
"""
test whether time window allows tour with specific tdd alt's time window
Parameters
----------
row_ids : pandas Series
series of window_row_ids indexed by tour_id
tdds : pandas series
series of tdd_alt ids, index irrelevant
Returns
-------
available : pandas Series of bool
with same index as window_row_ids.index (presumably tour_id, but we don't care)
"""
assert len(window_row_ids) == len(tdds)
# t0 = tracing.print_elapsed_time()
# numpy array with one tdd_footprints_df row for tdds
tour_footprints = util.quick_loc_df(
tdds, self.tdd_footprints_df).as_matrix()
# t0 = tracing.print_elapsed_time("tour_footprints", t0, debug=True)
# assert (tour_footprints == self.tdd_footprints_df.loc[tdds].as_matrix()).all
# numpy array with one windows row for each person
windows = self.slice_windows_by_row_id(window_row_ids)
# t0 = tracing.print_elapsed_time("slice_windows_by_row_id", t0, debug=True)
x = tour_footprints + (windows << I_BIT_SHIFT)
available = ~np.isin(x, COLLISION_LIST).any(axis=1)
available = pd.Series(available, index=window_row_ids.index)
# t0 = tracing.print_elapsed_time("available", t0, debug=True)
return available
def get_maz(self, maz_list, attribute):
return quick_loc_df(maz_list, self.maz_df, attribute)
def get_tap(self, tap_list, attribute):
return quick_loc_df(tap_list, self.tap_df, attribute)