Commit 454f73dc authored by SHodencq's avatar SHodencq
Browse files

[Adding license and copyright information to all the NoLOAD files]: using the...

[Adding license and copyright information to all the NoLOAD files]: using the reuse open source software developed by the Free Software Foundation Europe, the SPDX License Identifier and copyright information have been added as headers for all the relevant files
parent ca9f01f9
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
# Ignore the following files in GIT #
######################################
......@@ -23,6 +27,7 @@
#PyCharm Settings #
#####################
/.idea
.idea
#Unit tests #
......@@ -30,6 +35,7 @@
.cache/
__pycache__/
.coverage
/.pytest_cache
#pip install #
#####################
......
<!--
SPDX-FileCopyrightText: 2020 G2Elab / MAGE
SPDX-License-Identifier: Apache-2.0
-->
Authors:
=======
B. DELINCHANT, L. GERBAUD, F. WURTZ
......
<!--
SPDX-FileCopyrightText: 2020 G2Elab / MAGE
SPDX-License-Identifier: Apache-2.0
-->
How to contribute
#################
......
<!--
SPDX-FileCopyrightText: 2020 G2Elab / MAGE
SPDX-License-Identifier: Apache-2.0
-->
NoLOAD: Non Linear Optimization by Automatic Differentiation
============================================================
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
\ No newline at end of file
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
from noload.optimization.iterationHandler import Iterations
from typing import Callable, Dict, List, Any
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
import matplotlib
#matplotlib.use('TkAgg')
#start all your IPython kernels in inline mode by default by setting the following config options in your config files:
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
from typing import List, AnyStr
import matplotlib
#matplotlib.use('TkAgg')
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
import matplotlib.pyplot as plt
import numpy as np; np.random.seed(1)
xy=[[9953.617734480407,3702.706978407029],
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
import autograd.numpy as np
def flatten(seq):
res = []
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
from typing import List
class Solution:
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
from noload.optimization.wrapper import *
from noload.optimization.specifications import Spec
from noload.optimization.paretoTools import getXorYmid
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
from typing import Dict, Callable
import scipy.optimize as scipyOpt
from dateutil.parser import _resultbase
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
def getXorYmid(xy, normX, normY):
p1, p2, d = maxDist(xy)
dX = abs(p2[0]-p1[0]) #on suppose que p2 est bien plus grand que p1
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
import autograd.numpy as np
from autograd.builtins import isinstance
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
from autograd import make_jvp, jacobian as autograd_jac
import autograd.numpy as np
from noload.optimization.specifications import Spec
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
\ No newline at end of file
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
from numpy.testing import *
from noload.optimization.optimProblem import Spec, OptimProblem
import autograd.numpy as np
......
# SPDX-FileCopyrightText: 2020 G2Elab / MAGE
#
# SPDX-License-Identifier: Apache-2.0
from numpy.testing import *
from noload.optimization.optimProblem import Spec, OptimProblem
import autograd.numpy as np
......
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