mirror of
https://github.com/rdkit/rdkit.git
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1734ef8071
* clean up of python and c++ for-loops
* readd assignement
* Remove misleading walrus operators (#7323)
* Run installed tests if applicable (#7325)
* simpler check for equality
* Revert "simpler check for equality"
py assert does not work pointwise on lists on all platforms,
we need to iterate through all elements
This reverts commit 03cc0ad1a6.
* fix ambiguity on truth value of np arrays
* compare list elementwise
---------
Co-authored-by: Matt Swain <m.swain@me.com>
156 lines
3.7 KiB
Python
Executable File
156 lines
3.7 KiB
Python
Executable File
import random
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import unittest
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import numpy
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from rdkit import DataStructs, RDConfig
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from rdkit.DataManip.Metric import rdMetricMatrixCalc as rdmmc
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def feq(v1, v2, tol2=1e-4):
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return abs(v1 - v2) <= tol2
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class TestCase(unittest.TestCase):
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def setUp(self):
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pass
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def test0DistsArray(self):
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exp = numpy.array([1., 1.414213, 1.0], 'd')
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# initialize a double array and check if get back the expected distances
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desc = numpy.zeros((3, 2), 'd')
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desc[1, 0] = 1.0
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desc[2, 0] = 1.0
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desc[2, 1] = 1.0
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dmat = rdmmc.GetEuclideanDistMat(desc)
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for i in range(numpy.shape(dmat)[0]):
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assert feq(dmat[i], exp[i])
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# repeat with an float array
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desc = numpy.zeros((3, 2), 'f')
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desc[1, 0] = 1.0
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desc[2, 0] = 1.0
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desc[2, 1] = 1.0
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dmat = rdmmc.GetEuclideanDistMat(desc)
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for i in range(numpy.shape(dmat)[0]):
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assert feq(dmat[i], exp[i])
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# finally with an integer array
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desc = numpy.zeros((3, 2), 'i')
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desc[1, 0] = 1
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desc[2, 0] = 1
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desc[2, 1] = 1
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dmat = rdmmc.GetEuclideanDistMat(desc)
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for i in range(numpy.shape(dmat)[0]):
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assert feq(dmat[i], exp[i])
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def ctest1DistsListArray(self):
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exp = numpy.array([1., 1.414213, 1.0], 'd')
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desc = [
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numpy.array([0.0, 0.0], 'd'),
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numpy.array([1.0, 0.0], 'd'),
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numpy.array([1.0, 1.0], 'd')
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]
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dmat = rdmmc.GetEuclideanDistMat(desc)
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for i in range(numpy.shape(dmat)[0]):
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assert feq(dmat[i], exp[i])
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# repeat the test with a list of numpy.arrays of floats
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desc = [
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numpy.array([0.0, 0.0], 'f'),
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numpy.array([1.0, 0.0], 'f'),
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numpy.array([1.0, 1.0], 'f')
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]
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dmat = rdmmc.GetEuclideanDistMat(desc)
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for i in range(numpy.shape(dmat)[0]):
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assert feq(dmat[i], exp[i])
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# repeat the test with a list of numpy.arrays of ints
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desc = [numpy.array([0, 0], 'i'), numpy.array([1, 0], 'i'), numpy.array([1, 1], 'i')]
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dmat = rdmmc.GetEuclideanDistMat(desc)
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for i in range(numpy.shape(dmat)[0]):
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assert feq(dmat[i], exp[i])
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def test2DistListList(self):
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exp = numpy.array([1., 1.414213, 1.0], 'd')
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desc = [[0.0, 0.0], [1.0, 0.0], [1.0, 1.0]]
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dmat = rdmmc.GetEuclideanDistMat(desc)
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for i in range(numpy.shape(dmat)[0]):
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assert feq(dmat[i], exp[i])
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# test with ints
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desc = [[0, 0], [1, 0], [1, 1]]
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dmat = rdmmc.GetEuclideanDistMat(desc)
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for i in range(numpy.shape(dmat)[0]):
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assert feq(dmat[i], exp[i])
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def test3Compare(self):
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n = 30
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m = 5
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dscArr = numpy.random.default_rng().random((n,m))
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dmatArr = rdmmc.GetEuclideanDistMat(dscArr)
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dscLL = []
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for i in range(n):
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row = []
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for j in range(m):
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row.append(dscArr[i, j])
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dscLL.append(row)
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dmatLL = rdmmc.GetEuclideanDistMat(dscLL)
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assert numpy.shape(dmatArr) == numpy.shape(dmatLL)
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for i in range(n * (n - 1) // 2):
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assert feq(dmatArr[i], dmatLL[i])
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def test4ebv(self):
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n = 30
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m = 2048
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dm = 800
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lst = []
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for i in range(n):
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v = DataStructs.ExplicitBitVect(m)
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for j in range(dm):
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v.SetBit(random.randrange(0, m))
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lst.append(v)
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dMat = rdmmc.GetTanimotoDistMat(lst)
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sMat = rdmmc.GetTanimotoSimMat(lst)
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for i in range(n * (n - 1) // 2):
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assert feq(sMat[i] + dMat[i], 1.0)
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def test5sbv(self):
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n = 30
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m = 2048
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dm = 800
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lst = []
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for i in range(n):
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v = DataStructs.SparseBitVect(m)
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for j in range(dm):
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v.SetBit(random.randrange(0, m))
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lst.append(v)
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dMat = rdmmc.GetTanimotoDistMat(lst)
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sMat = rdmmc.GetTanimotoSimMat(lst)
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for i in range(n * (n - 1) // 2):
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assert feq(sMat[i] + dMat[i], 1.0)
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if __name__ == '__main__':
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unittest.main()
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