cavis/contrib/attic/jumpy/jumpy/matlib.py

68 lines
2.1 KiB
Python

# /* ******************************************************************************
# *
# *
# * This program and the accompanying materials are made available under the
# * terms of the Apache License, Version 2.0 which is available at
# * https://www.apache.org/licenses/LICENSE-2.0.
# *
# * See the NOTICE file distributed with this work for additional
# * information regarding copyright ownership.
# * Unless required by applicable law or agreed to in writing, software
# * distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# * License for the specific language governing permissions and limitations
# * under the License.
# *
# * SPDX-License-Identifier: Apache-2.0
# ******************************************************************************/
################################################################################
#
# This program and the accompanying materials are made available under the
# terms of the Apache License, Version 2.0 which is available at
# https://www.apache.org/licenses/LICENSE-2.0.
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
#
################################################################################
from .ndarray import ndarray
from .java_classes import Nd4j
def zeros(shape):
return ndarray(Nd4j.zeros(*shape))
def ones(shape):
return ndarray(Nd4j.ones(*shape))
def zeros_like(array):
array = ndarray(array).array
return ndarray(Nd4j.zerosLike(array))
def ones_like(array):
array = ndarray(array).array
return ndarray(Nd4j.onesLike(array))
def eye(size):
return ndarray(Nd4j.eye(size))
def arange(m, n=None):
if n is None:
return ndarray(Nd4j.arange(m))
return ndarray(Nd4j.arange(m, n))
def linspace(start, stop, num):
return ndarray(Nd4j.linspace(start, stop, num))