def dtype(self) -> np.dtype:
logging.info(f"Accessing '{self.location}' for 'dtype'")
(z_data, z_info) = read(str(self.location))
fields = []
for quant in self.quantity_names:
fields.append((quant, z_data[quant].dtype))
return np.dtype(fields)
def get_data(self, indexing=None, fields=None) -> np.ndarray:
(z_data, z_info) = read(str(self.location))
# create a structured array
dset = np.zeros(self.num_particles, dtype=self.dtype)
# fill the array
for quant in self.quantity_names:
dset[quant] = z_data[quant]
return dset
def get_data(self, indexing=None, fields=None) -> np.ndarray:
logging.info(f"Reading data in '{self.location}'")
(z_data, z_info) = read(str(self.location))
if fields is None:
# create a structured array
dset = np.empty(self.num_particles, dtype=self.dtype)
# fill the array
for quant in self.quantity_names:
dset[quant] = z_data[quant]
else:
if indexing is None:
dset = z_data[fields][:]
else:
dset = z_data[fields][indexing]
return dset
def dtype(self):
logging.info(f"Accessing '{self.location}' for 'dtype'")
(z_data, z_info) = read(str(self.location))
return z_data.dtype
def get_data(self=None, indexing=None):
# TODO: apply indexing here
(z_data, z_info) = read(str(self.location))
return z_data.transpose()
