def from_numpy(self, ndarray):
if len(ndarray.shape) == len(self.loop_range().shape) + 1:
as_vector = True
assert self.m == 1, "This matrix is not a vector"
else:
as_vector = False
assert len(ndarray.shape) == len(self.loop_range().shape) + 2
dim_ext = 1 if as_vector else 2
assert len(ndarray.shape) == len(self.loop_range().shape) + dim_ext
from taichi.lang.meta import ext_arr_to_matrix
ext_arr_to_matrix(ndarray, self, as_vector)
ti.sync()
def from_numpy(self, arr):
if len(arr.shape) == len(self.shape) + 1:
as_vector = True
assert self.m == 1, "This is not a vector field"
else:
as_vector = False
assert len(arr.shape) == len(self.shape) + 2
dim_ext = 1 if as_vector else 2
assert len(arr.shape) == len(self.shape) + dim_ext
from taichi.lang.meta import ext_arr_to_matrix
ext_arr_to_matrix(arr, self, as_vector)
ti.sync()
def from_numpy(self, ndarray):
"""Copy the values of a numpy ndarray to the Matrix.
Args:
ndarray (numpy.ndarray): The numpy array to copy.
"""
if len(ndarray.shape) == len(self.loop_range().shape) + 1:
as_vector = True
assert self.m == 1, "This matrix is not a vector"
else:
as_vector = False
assert len(ndarray.shape) == len(self.loop_range().shape) + 2
dim_ext = 1 if as_vector else 2
assert len(ndarray.shape) == len(self.loop_range().shape) + dim_ext
from taichi.lang.meta import ext_arr_to_matrix
ext_arr_to_matrix(ndarray, self, as_vector)
ti.sync()