Initial import: grid-bot — grid trading bot for BTC-USDT on Cifra Markets
This commit is contained in:
Kolp
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from sympy.tensor.array.array_comprehension import ArrayComprehension, ArrayComprehensionMap
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from sympy.tensor.array import ImmutableDenseNDimArray
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from sympy.abc import i, j, k, l
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from sympy.testing.pytest import raises
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from sympy.matrices import Matrix
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def test_array_comprehension():
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a = ArrayComprehension(i*j, (i, 1, 3), (j, 2, 4))
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b = ArrayComprehension(i, (i, 1, j+1))
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c = ArrayComprehension(i+j+k+l, (i, 1, 2), (j, 1, 3), (k, 1, 4), (l, 1, 5))
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d = ArrayComprehension(k, (i, 1, 5))
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e = ArrayComprehension(i, (j, k+1, k+5))
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assert a.doit().tolist() == [[2, 3, 4], [4, 6, 8], [6, 9, 12]]
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assert a.shape == (3, 3)
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assert a.is_shape_numeric == True
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assert a.tolist() == [[2, 3, 4], [4, 6, 8], [6, 9, 12]]
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assert a.tomatrix() == Matrix([
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[2, 3, 4],
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[4, 6, 8],
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[6, 9, 12]])
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assert len(a) == 9
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assert isinstance(b.doit(), ArrayComprehension)
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assert isinstance(a.doit(), ImmutableDenseNDimArray)
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assert b.subs(j, 3) == ArrayComprehension(i, (i, 1, 4))
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assert b.free_symbols == {j}
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assert b.shape == (j + 1,)
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assert b.rank() == 1
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assert b.is_shape_numeric == False
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assert c.free_symbols == set()
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assert c.function == i + j + k + l
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assert c.limits == ((i, 1, 2), (j, 1, 3), (k, 1, 4), (l, 1, 5))
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assert c.doit().tolist() == [[[[4, 5, 6, 7, 8], [5, 6, 7, 8, 9], [6, 7, 8, 9, 10], [7, 8, 9, 10, 11]],
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[[5, 6, 7, 8, 9], [6, 7, 8, 9, 10], [7, 8, 9, 10, 11], [8, 9, 10, 11, 12]],
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[[6, 7, 8, 9, 10], [7, 8, 9, 10, 11], [8, 9, 10, 11, 12], [9, 10, 11, 12, 13]]],
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[[[5, 6, 7, 8, 9], [6, 7, 8, 9, 10], [7, 8, 9, 10, 11], [8, 9, 10, 11, 12]],
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[[6, 7, 8, 9, 10], [7, 8, 9, 10, 11], [8, 9, 10, 11, 12], [9, 10, 11, 12, 13]],
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[[7, 8, 9, 10, 11], [8, 9, 10, 11, 12], [9, 10, 11, 12, 13], [10, 11, 12, 13, 14]]]]
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assert c.free_symbols == set()
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assert c.variables == [i, j, k, l]
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assert c.bound_symbols == [i, j, k, l]
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assert d.doit().tolist() == [k, k, k, k, k]
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assert len(e) == 5
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raises(TypeError, lambda: ArrayComprehension(i*j, (i, 1, 3), (j, 2, [1, 3, 2])))
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raises(ValueError, lambda: ArrayComprehension(i*j, (i, 1, 3), (j, 2, 1)))
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raises(ValueError, lambda: ArrayComprehension(i*j, (i, 1, 3), (j, 2, j+1)))
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raises(ValueError, lambda: len(ArrayComprehension(i*j, (i, 1, 3), (j, 2, j+4))))
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raises(TypeError, lambda: ArrayComprehension(i*j, (i, 0, i + 1.5), (j, 0, 2)))
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raises(ValueError, lambda: b.tolist())
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raises(ValueError, lambda: b.tomatrix())
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raises(ValueError, lambda: c.tomatrix())
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def test_arraycomprehensionmap():
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a = ArrayComprehensionMap(lambda i: i+1, (i, 1, 5))
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assert a.doit().tolist() == [2, 3, 4, 5, 6]
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assert a.shape == (5,)
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assert a.is_shape_numeric
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assert a.tolist() == [2, 3, 4, 5, 6]
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assert len(a) == 5
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assert isinstance(a.doit(), ImmutableDenseNDimArray)
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expr = ArrayComprehensionMap(lambda i: i+1, (i, 1, k))
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assert expr.doit() == expr
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assert expr.subs(k, 4) == ArrayComprehensionMap(lambda i: i+1, (i, 1, 4))
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assert expr.subs(k, 4).doit() == ImmutableDenseNDimArray([2, 3, 4, 5])
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b = ArrayComprehensionMap(lambda i: i+1, (i, 1, 2), (i, 1, 3), (i, 1, 4), (i, 1, 5))
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assert b.doit().tolist() == [[[[2, 3, 4, 5, 6], [3, 5, 7, 9, 11], [4, 7, 10, 13, 16], [5, 9, 13, 17, 21]],
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[[3, 5, 7, 9, 11], [5, 9, 13, 17, 21], [7, 13, 19, 25, 31], [9, 17, 25, 33, 41]],
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[[4, 7, 10, 13, 16], [7, 13, 19, 25, 31], [10, 19, 28, 37, 46], [13, 25, 37, 49, 61]]],
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[[[3, 5, 7, 9, 11], [5, 9, 13, 17, 21], [7, 13, 19, 25, 31], [9, 17, 25, 33, 41]],
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[[5, 9, 13, 17, 21], [9, 17, 25, 33, 41], [13, 25, 37, 49, 61], [17, 33, 49, 65, 81]],
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[[7, 13, 19, 25, 31], [13, 25, 37, 49, 61], [19, 37, 55, 73, 91], [25, 49, 73, 97, 121]]]]
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# tests about lambda expression
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assert ArrayComprehensionMap(lambda: 3, (i, 1, 5)).doit().tolist() == [3, 3, 3, 3, 3]
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assert ArrayComprehensionMap(lambda i: i+1, (i, 1, 5)).doit().tolist() == [2, 3, 4, 5, 6]
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raises(ValueError, lambda: ArrayComprehensionMap(i*j, (i, 1, 3), (j, 2, 4)))
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a = ArrayComprehensionMap(lambda i, j: i+j, (i, 1, 5))
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raises(ValueError, lambda: a.doit())
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+52
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from sympy.core.symbol import symbols
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from sympy.matrices.dense import Matrix
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from sympy.matrices.expressions.matexpr import MatrixSymbol
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from sympy.tensor.array.ndim_array import NDimArray
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from sympy.matrices.matrixbase import MatrixBase
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from sympy.tensor.array.array_derivatives import ArrayDerivative
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x, y, z, t = symbols("x y z t")
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m = Matrix([[x, y], [z, t]])
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M = MatrixSymbol("M", 3, 2)
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N = MatrixSymbol("N", 4, 3)
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def test_array_derivative_construction():
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d = ArrayDerivative(x, m, evaluate=False)
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assert d.shape == (2, 2)
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expr = d.doit()
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assert isinstance(expr, MatrixBase)
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assert expr.shape == (2, 2)
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d = ArrayDerivative(m, m, evaluate=False)
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assert d.shape == (2, 2, 2, 2)
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expr = d.doit()
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assert isinstance(expr, NDimArray)
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assert expr.shape == (2, 2, 2, 2)
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d = ArrayDerivative(m, x, evaluate=False)
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assert d.shape == (2, 2)
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expr = d.doit()
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assert isinstance(expr, MatrixBase)
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assert expr.shape == (2, 2)
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d = ArrayDerivative(M, N, evaluate=False)
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assert d.shape == (4, 3, 3, 2)
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expr = d.doit()
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assert isinstance(expr, ArrayDerivative)
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assert expr.shape == (4, 3, 3, 2)
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d = ArrayDerivative(M, (N, 2), evaluate=False)
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assert d.shape == (4, 3, 4, 3, 3, 2)
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expr = d.doit()
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assert isinstance(expr, ArrayDerivative)
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assert expr.shape == (4, 3, 4, 3, 3, 2)
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d = ArrayDerivative(M.as_explicit(), (N.as_explicit(), 2), evaluate=False)
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assert d.doit().shape == (4, 3, 4, 3, 3, 2)
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expr = d.doit()
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assert isinstance(expr, NDimArray)
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assert expr.shape == (4, 3, 4, 3, 3, 2)
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@@ -0,0 +1,361 @@
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import itertools
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import random
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from sympy.combinatorics import Permutation
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from sympy.combinatorics.permutations import _af_invert
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from sympy.testing.pytest import raises
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from sympy.core.function import diff
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from sympy.core.symbol import symbols
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from sympy.functions.elementary.complexes import (adjoint, conjugate, transpose)
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from sympy.functions.elementary.exponential import (exp, log)
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from sympy.functions.elementary.trigonometric import (cos, sin)
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from sympy.tensor.array import Array, ImmutableDenseNDimArray, ImmutableSparseNDimArray, MutableSparseNDimArray
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from sympy.tensor.array.arrayop import tensorproduct, tensorcontraction, derive_by_array, permutedims, Flatten, \
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tensordiagonal
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def test_import_NDimArray():
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from sympy.tensor.array import NDimArray
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del NDimArray
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def test_tensorproduct():
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x,y,z,t = symbols('x y z t')
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from sympy.abc import a,b,c,d
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assert tensorproduct() == 1
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assert tensorproduct([x]) == Array([x])
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assert tensorproduct([x], [y]) == Array([[x*y]])
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assert tensorproduct([x], [y], [z]) == Array([[[x*y*z]]])
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assert tensorproduct([x], [y], [z], [t]) == Array([[[[x*y*z*t]]]])
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assert tensorproduct(x) == x
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assert tensorproduct(x, y) == x*y
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assert tensorproduct(x, y, z) == x*y*z
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assert tensorproduct(x, y, z, t) == x*y*z*t
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for ArrayType in [ImmutableDenseNDimArray, ImmutableSparseNDimArray]:
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A = ArrayType([x, y])
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B = ArrayType([1, 2, 3])
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C = ArrayType([a, b, c, d])
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assert tensorproduct(A, B, C) == ArrayType([[[a*x, b*x, c*x, d*x], [2*a*x, 2*b*x, 2*c*x, 2*d*x], [3*a*x, 3*b*x, 3*c*x, 3*d*x]],
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[[a*y, b*y, c*y, d*y], [2*a*y, 2*b*y, 2*c*y, 2*d*y], [3*a*y, 3*b*y, 3*c*y, 3*d*y]]])
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assert tensorproduct([x, y], [1, 2, 3]) == tensorproduct(A, B)
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assert tensorproduct(A, 2) == ArrayType([2*x, 2*y])
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assert tensorproduct(A, [2]) == ArrayType([[2*x], [2*y]])
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assert tensorproduct([2], A) == ArrayType([[2*x, 2*y]])
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assert tensorproduct(a, A) == ArrayType([a*x, a*y])
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assert tensorproduct(a, A, B) == ArrayType([[a*x, 2*a*x, 3*a*x], [a*y, 2*a*y, 3*a*y]])
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assert tensorproduct(A, B, a) == ArrayType([[a*x, 2*a*x, 3*a*x], [a*y, 2*a*y, 3*a*y]])
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assert tensorproduct(B, a, A) == ArrayType([[a*x, a*y], [2*a*x, 2*a*y], [3*a*x, 3*a*y]])
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# tests for large scale sparse array
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for SparseArrayType in [ImmutableSparseNDimArray, MutableSparseNDimArray]:
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a = SparseArrayType({1:2, 3:4},(1000, 2000))
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b = SparseArrayType({1:2, 3:4},(1000, 2000))
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assert tensorproduct(a, b) == ImmutableSparseNDimArray({2000001: 4, 2000003: 8, 6000001: 8, 6000003: 16}, (1000, 2000, 1000, 2000))
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def test_tensorcontraction():
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from sympy.abc import a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,q,r,s,t,u,v,w,x
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B = Array(range(18), (2, 3, 3))
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assert tensorcontraction(B, (1, 2)) == Array([12, 39])
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C1 = Array([a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x], (2, 3, 2, 2))
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assert tensorcontraction(C1, (0, 2)) == Array([[a + o, b + p], [e + s, f + t], [i + w, j + x]])
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assert tensorcontraction(C1, (0, 2, 3)) == Array([a + p, e + t, i + x])
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assert tensorcontraction(C1, (2, 3)) == Array([[a + d, e + h, i + l], [m + p, q + t, u + x]])
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def test_derivative_by_array():
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from sympy.abc import i, j, t, x, y, z
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bexpr = x*y**2*exp(z)*log(t)
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sexpr = sin(bexpr)
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cexpr = cos(bexpr)
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a = Array([sexpr])
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assert derive_by_array(sexpr, t) == x*y**2*exp(z)*cos(x*y**2*exp(z)*log(t))/t
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assert derive_by_array(sexpr, [x, y, z]) == Array([bexpr/x*cexpr, 2*y*bexpr/y**2*cexpr, bexpr*cexpr])
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assert derive_by_array(a, [x, y, z]) == Array([[bexpr/x*cexpr], [2*y*bexpr/y**2*cexpr], [bexpr*cexpr]])
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assert derive_by_array(sexpr, [[x, y], [z, t]]) == Array([[bexpr/x*cexpr, 2*y*bexpr/y**2*cexpr], [bexpr*cexpr, bexpr/log(t)/t*cexpr]])
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assert derive_by_array(a, [[x, y], [z, t]]) == Array([[[bexpr/x*cexpr], [2*y*bexpr/y**2*cexpr]], [[bexpr*cexpr], [bexpr/log(t)/t*cexpr]]])
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assert derive_by_array([[x, y], [z, t]], [x, y]) == Array([[[1, 0], [0, 0]], [[0, 1], [0, 0]]])
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assert derive_by_array([[x, y], [z, t]], [[x, y], [z, t]]) == Array([[[[1, 0], [0, 0]], [[0, 1], [0, 0]]],
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[[[0, 0], [1, 0]], [[0, 0], [0, 1]]]])
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assert diff(sexpr, t) == x*y**2*exp(z)*cos(x*y**2*exp(z)*log(t))/t
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assert diff(sexpr, Array([x, y, z])) == Array([bexpr/x*cexpr, 2*y*bexpr/y**2*cexpr, bexpr*cexpr])
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assert diff(a, Array([x, y, z])) == Array([[bexpr/x*cexpr], [2*y*bexpr/y**2*cexpr], [bexpr*cexpr]])
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assert diff(sexpr, Array([[x, y], [z, t]])) == Array([[bexpr/x*cexpr, 2*y*bexpr/y**2*cexpr], [bexpr*cexpr, bexpr/log(t)/t*cexpr]])
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assert diff(a, Array([[x, y], [z, t]])) == Array([[[bexpr/x*cexpr], [2*y*bexpr/y**2*cexpr]], [[bexpr*cexpr], [bexpr/log(t)/t*cexpr]]])
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assert diff(Array([[x, y], [z, t]]), Array([x, y])) == Array([[[1, 0], [0, 0]], [[0, 1], [0, 0]]])
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assert diff(Array([[x, y], [z, t]]), Array([[x, y], [z, t]])) == Array([[[[1, 0], [0, 0]], [[0, 1], [0, 0]]],
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[[[0, 0], [1, 0]], [[0, 0], [0, 1]]]])
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# test for large scale sparse array
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for SparseArrayType in [ImmutableSparseNDimArray, MutableSparseNDimArray]:
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b = MutableSparseNDimArray({0:i, 1:j}, (10000, 20000))
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assert derive_by_array(b, i) == ImmutableSparseNDimArray({0: 1}, (10000, 20000))
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assert derive_by_array(b, (i, j)) == ImmutableSparseNDimArray({0: 1, 200000001: 1}, (2, 10000, 20000))
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#https://github.com/sympy/sympy/issues/20655
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U = Array([x, y, z])
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E = 2
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assert derive_by_array(E, U) == ImmutableDenseNDimArray([0, 0, 0])
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def test_issue_emerged_while_discussing_10972():
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ua = Array([-1,0])
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Fa = Array([[0, 1], [-1, 0]])
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po = tensorproduct(Fa, ua, Fa, ua)
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assert tensorcontraction(po, (1, 2), (4, 5)) == Array([[0, 0], [0, 1]])
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sa = symbols('a0:144')
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po = Array(sa, [2, 2, 3, 3, 2, 2])
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assert tensorcontraction(po, (0, 1), (2, 3), (4, 5)) == sa[0] + sa[108] + sa[111] + sa[124] + sa[127] + sa[140] + sa[143] + sa[16] + sa[19] + sa[3] + sa[32] + sa[35]
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assert tensorcontraction(po, (0, 1, 4, 5), (2, 3)) == sa[0] + sa[111] + sa[127] + sa[143] + sa[16] + sa[32]
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assert tensorcontraction(po, (0, 1), (4, 5)) == Array([[sa[0] + sa[108] + sa[111] + sa[3], sa[112] + sa[115] + sa[4] + sa[7],
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sa[11] + sa[116] + sa[119] + sa[8]], [sa[12] + sa[120] + sa[123] + sa[15],
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sa[124] + sa[127] + sa[16] + sa[19], sa[128] + sa[131] + sa[20] + sa[23]],
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[sa[132] + sa[135] + sa[24] + sa[27], sa[136] + sa[139] + sa[28] + sa[31],
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sa[140] + sa[143] + sa[32] + sa[35]]])
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assert tensorcontraction(po, (0, 1), (2, 3)) == Array([[sa[0] + sa[108] + sa[124] + sa[140] + sa[16] + sa[32], sa[1] + sa[109] + sa[125] + sa[141] + sa[17] + sa[33]],
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[sa[110] + sa[126] + sa[142] + sa[18] + sa[2] + sa[34], sa[111] + sa[127] + sa[143] + sa[19] + sa[3] + sa[35]]])
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def test_array_permutedims():
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sa = symbols('a0:144')
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for ArrayType in [ImmutableDenseNDimArray, ImmutableSparseNDimArray]:
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m1 = ArrayType(sa[:6], (2, 3))
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assert permutedims(m1, (1, 0)) == transpose(m1)
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assert m1.tomatrix().T == permutedims(m1, (1, 0)).tomatrix()
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assert m1.tomatrix().T == transpose(m1).tomatrix()
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assert m1.tomatrix().C == conjugate(m1).tomatrix()
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assert m1.tomatrix().H == adjoint(m1).tomatrix()
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assert m1.tomatrix().T == m1.transpose().tomatrix()
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assert m1.tomatrix().C == m1.conjugate().tomatrix()
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assert m1.tomatrix().H == m1.adjoint().tomatrix()
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raises(ValueError, lambda: permutedims(m1, (0,)))
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raises(ValueError, lambda: permutedims(m1, (0, 0)))
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raises(ValueError, lambda: permutedims(m1, (1, 2, 0)))
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# Some tests with random arrays:
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dims = 6
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shape = [random.randint(1,5) for i in range(dims)]
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elems = [random.random() for i in range(tensorproduct(*shape))]
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ra = ArrayType(elems, shape)
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perm = list(range(dims))
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# Randomize the permutation:
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random.shuffle(perm)
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# Test inverse permutation:
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assert permutedims(permutedims(ra, perm), _af_invert(perm)) == ra
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# Test that permuted shape corresponds to action by `Permutation`:
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assert permutedims(ra, perm).shape == tuple(Permutation(perm)(shape))
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z = ArrayType.zeros(4,5,6,7)
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|
||||
assert permutedims(z, (2, 3, 1, 0)).shape == (6, 7, 5, 4)
|
||||
assert permutedims(z, [2, 3, 1, 0]).shape == (6, 7, 5, 4)
|
||||
assert permutedims(z, Permutation([2, 3, 1, 0])).shape == (6, 7, 5, 4)
|
||||
|
||||
po = ArrayType(sa, [2, 2, 3, 3, 2, 2])
|
||||
|
||||
raises(ValueError, lambda: permutedims(po, (1, 1)))
|
||||
raises(ValueError, lambda: po.transpose())
|
||||
raises(ValueError, lambda: po.adjoint())
|
||||
|
||||
assert permutedims(po, reversed(range(po.rank()))) == ArrayType(
|
||||
[[[[[[sa[0], sa[72]], [sa[36], sa[108]]], [[sa[12], sa[84]], [sa[48], sa[120]]], [[sa[24],
|
||||
sa[96]], [sa[60], sa[132]]]],
|
||||
[[[sa[4], sa[76]], [sa[40], sa[112]]], [[sa[16],
|
||||
sa[88]], [sa[52], sa[124]]],
|
||||
[[sa[28], sa[100]], [sa[64], sa[136]]]],
|
||||
[[[sa[8],
|
||||
sa[80]], [sa[44], sa[116]]], [[sa[20], sa[92]], [sa[56], sa[128]]], [[sa[32],
|
||||
sa[104]], [sa[68], sa[140]]]]],
|
||||
[[[[sa[2], sa[74]], [sa[38], sa[110]]], [[sa[14],
|
||||
sa[86]], [sa[50], sa[122]]], [[sa[26], sa[98]], [sa[62], sa[134]]]],
|
||||
[[[sa[6],
|
||||
sa[78]], [sa[42], sa[114]]], [[sa[18], sa[90]], [sa[54], sa[126]]], [[sa[30],
|
||||
sa[102]], [sa[66], sa[138]]]],
|
||||
[[[sa[10], sa[82]], [sa[46], sa[118]]], [[sa[22],
|
||||
sa[94]], [sa[58], sa[130]]],
|
||||
[[sa[34], sa[106]], [sa[70], sa[142]]]]]],
|
||||
[[[[[sa[1],
|
||||
sa[73]], [sa[37], sa[109]]], [[sa[13], sa[85]], [sa[49], sa[121]]], [[sa[25],
|
||||
sa[97]], [sa[61], sa[133]]]],
|
||||
[[[sa[5], sa[77]], [sa[41], sa[113]]], [[sa[17],
|
||||
sa[89]], [sa[53], sa[125]]],
|
||||
[[sa[29], sa[101]], [sa[65], sa[137]]]],
|
||||
[[[sa[9],
|
||||
sa[81]], [sa[45], sa[117]]], [[sa[21], sa[93]], [sa[57], sa[129]]], [[sa[33],
|
||||
sa[105]], [sa[69], sa[141]]]]],
|
||||
[[[[sa[3], sa[75]], [sa[39], sa[111]]], [[sa[15],
|
||||
sa[87]], [sa[51], sa[123]]], [[sa[27], sa[99]], [sa[63], sa[135]]]],
|
||||
[[[sa[7],
|
||||
sa[79]], [sa[43], sa[115]]], [[sa[19], sa[91]], [sa[55], sa[127]]], [[sa[31],
|
||||
sa[103]], [sa[67], sa[139]]]],
|
||||
[[[sa[11], sa[83]], [sa[47], sa[119]]], [[sa[23],
|
||||
sa[95]], [sa[59], sa[131]]],
|
||||
[[sa[35], sa[107]], [sa[71], sa[143]]]]]]])
|
||||
|
||||
assert permutedims(po, (1, 0, 2, 3, 4, 5)) == ArrayType(
|
||||
[[[[[[sa[0], sa[1]], [sa[2], sa[3]]], [[sa[4], sa[5]], [sa[6], sa[7]]], [[sa[8], sa[9]], [sa[10],
|
||||
sa[11]]]],
|
||||
[[[sa[12], sa[13]], [sa[14], sa[15]]], [[sa[16], sa[17]], [sa[18],
|
||||
sa[19]]], [[sa[20], sa[21]], [sa[22], sa[23]]]],
|
||||
[[[sa[24], sa[25]], [sa[26],
|
||||
sa[27]]], [[sa[28], sa[29]], [sa[30], sa[31]]], [[sa[32], sa[33]], [sa[34],
|
||||
sa[35]]]]],
|
||||
[[[[sa[72], sa[73]], [sa[74], sa[75]]], [[sa[76], sa[77]], [sa[78],
|
||||
sa[79]]], [[sa[80], sa[81]], [sa[82], sa[83]]]],
|
||||
[[[sa[84], sa[85]], [sa[86],
|
||||
sa[87]]], [[sa[88], sa[89]], [sa[90], sa[91]]], [[sa[92], sa[93]], [sa[94],
|
||||
sa[95]]]],
|
||||
[[[sa[96], sa[97]], [sa[98], sa[99]]], [[sa[100], sa[101]], [sa[102],
|
||||
sa[103]]],
|
||||
[[sa[104], sa[105]], [sa[106], sa[107]]]]]], [[[[[sa[36], sa[37]], [sa[38],
|
||||
sa[39]]],
|
||||
[[sa[40], sa[41]], [sa[42], sa[43]]],
|
||||
[[sa[44], sa[45]], [sa[46],
|
||||
sa[47]]]],
|
||||
[[[sa[48], sa[49]], [sa[50], sa[51]]],
|
||||
[[sa[52], sa[53]], [sa[54],
|
||||
sa[55]]],
|
||||
[[sa[56], sa[57]], [sa[58], sa[59]]]],
|
||||
[[[sa[60], sa[61]], [sa[62],
|
||||
sa[63]]],
|
||||
[[sa[64], sa[65]], [sa[66], sa[67]]],
|
||||
[[sa[68], sa[69]], [sa[70],
|
||||
sa[71]]]]], [
|
||||
[[[sa[108], sa[109]], [sa[110], sa[111]]],
|
||||
[[sa[112], sa[113]], [sa[114],
|
||||
sa[115]]],
|
||||
[[sa[116], sa[117]], [sa[118], sa[119]]]],
|
||||
[[[sa[120], sa[121]], [sa[122],
|
||||
sa[123]]],
|
||||
[[sa[124], sa[125]], [sa[126], sa[127]]],
|
||||
[[sa[128], sa[129]], [sa[130],
|
||||
sa[131]]]],
|
||||
[[[sa[132], sa[133]], [sa[134], sa[135]]],
|
||||
[[sa[136], sa[137]], [sa[138],
|
||||
sa[139]]],
|
||||
[[sa[140], sa[141]], [sa[142], sa[143]]]]]]])
|
||||
|
||||
assert permutedims(po, (0, 2, 1, 4, 3, 5)) == ArrayType(
|
||||
[[[[[[sa[0], sa[1]], [sa[4], sa[5]], [sa[8], sa[9]]], [[sa[2], sa[3]], [sa[6], sa[7]], [sa[10],
|
||||
sa[11]]]],
|
||||
[[[sa[36], sa[37]], [sa[40], sa[41]], [sa[44], sa[45]]], [[sa[38],
|
||||
sa[39]], [sa[42], sa[43]], [sa[46], sa[47]]]]],
|
||||
[[[[sa[12], sa[13]], [sa[16],
|
||||
sa[17]], [sa[20], sa[21]]], [[sa[14], sa[15]], [sa[18], sa[19]], [sa[22],
|
||||
sa[23]]]],
|
||||
[[[sa[48], sa[49]], [sa[52], sa[53]], [sa[56], sa[57]]], [[sa[50],
|
||||
sa[51]], [sa[54], sa[55]], [sa[58], sa[59]]]]],
|
||||
[[[[sa[24], sa[25]], [sa[28],
|
||||
sa[29]], [sa[32], sa[33]]], [[sa[26], sa[27]], [sa[30], sa[31]], [sa[34],
|
||||
sa[35]]]],
|
||||
[[[sa[60], sa[61]], [sa[64], sa[65]], [sa[68], sa[69]]], [[sa[62],
|
||||
sa[63]], [sa[66], sa[67]], [sa[70], sa[71]]]]]],
|
||||
[[[[[sa[72], sa[73]], [sa[76],
|
||||
sa[77]], [sa[80], sa[81]]], [[sa[74], sa[75]], [sa[78], sa[79]], [sa[82],
|
||||
sa[83]]]],
|
||||
[[[sa[108], sa[109]], [sa[112], sa[113]], [sa[116], sa[117]]], [[sa[110],
|
||||
sa[111]], [sa[114], sa[115]],
|
||||
[sa[118], sa[119]]]]],
|
||||
[[[[sa[84], sa[85]], [sa[88],
|
||||
sa[89]], [sa[92], sa[93]]], [[sa[86], sa[87]], [sa[90], sa[91]], [sa[94],
|
||||
sa[95]]]],
|
||||
[[[sa[120], sa[121]], [sa[124], sa[125]], [sa[128], sa[129]]], [[sa[122],
|
||||
sa[123]], [sa[126], sa[127]],
|
||||
[sa[130], sa[131]]]]],
|
||||
[[[[sa[96], sa[97]], [sa[100],
|
||||
sa[101]], [sa[104], sa[105]]], [[sa[98], sa[99]], [sa[102], sa[103]], [sa[106],
|
||||
sa[107]]]],
|
||||
[[[sa[132], sa[133]], [sa[136], sa[137]], [sa[140], sa[141]]], [[sa[134],
|
||||
sa[135]], [sa[138], sa[139]],
|
||||
[sa[142], sa[143]]]]]]])
|
||||
|
||||
po2 = po.reshape(4, 9, 2, 2)
|
||||
assert po2 == ArrayType([[[[sa[0], sa[1]], [sa[2], sa[3]]], [[sa[4], sa[5]], [sa[6], sa[7]]], [[sa[8], sa[9]], [sa[10], sa[11]]], [[sa[12], sa[13]], [sa[14], sa[15]]], [[sa[16], sa[17]], [sa[18], sa[19]]], [[sa[20], sa[21]], [sa[22], sa[23]]], [[sa[24], sa[25]], [sa[26], sa[27]]], [[sa[28], sa[29]], [sa[30], sa[31]]], [[sa[32], sa[33]], [sa[34], sa[35]]]], [[[sa[36], sa[37]], [sa[38], sa[39]]], [[sa[40], sa[41]], [sa[42], sa[43]]], [[sa[44], sa[45]], [sa[46], sa[47]]], [[sa[48], sa[49]], [sa[50], sa[51]]], [[sa[52], sa[53]], [sa[54], sa[55]]], [[sa[56], sa[57]], [sa[58], sa[59]]], [[sa[60], sa[61]], [sa[62], sa[63]]], [[sa[64], sa[65]], [sa[66], sa[67]]], [[sa[68], sa[69]], [sa[70], sa[71]]]], [[[sa[72], sa[73]], [sa[74], sa[75]]], [[sa[76], sa[77]], [sa[78], sa[79]]], [[sa[80], sa[81]], [sa[82], sa[83]]], [[sa[84], sa[85]], [sa[86], sa[87]]], [[sa[88], sa[89]], [sa[90], sa[91]]], [[sa[92], sa[93]], [sa[94], sa[95]]], [[sa[96], sa[97]], [sa[98], sa[99]]], [[sa[100], sa[101]], [sa[102], sa[103]]], [[sa[104], sa[105]], [sa[106], sa[107]]]], [[[sa[108], sa[109]], [sa[110], sa[111]]], [[sa[112], sa[113]], [sa[114], sa[115]]], [[sa[116], sa[117]], [sa[118], sa[119]]], [[sa[120], sa[121]], [sa[122], sa[123]]], [[sa[124], sa[125]], [sa[126], sa[127]]], [[sa[128], sa[129]], [sa[130], sa[131]]], [[sa[132], sa[133]], [sa[134], sa[135]]], [[sa[136], sa[137]], [sa[138], sa[139]]], [[sa[140], sa[141]], [sa[142], sa[143]]]]])
|
||||
|
||||
assert permutedims(po2, (3, 2, 0, 1)) == ArrayType([[[[sa[0], sa[4], sa[8], sa[12], sa[16], sa[20], sa[24], sa[28], sa[32]], [sa[36], sa[40], sa[44], sa[48], sa[52], sa[56], sa[60], sa[64], sa[68]], [sa[72], sa[76], sa[80], sa[84], sa[88], sa[92], sa[96], sa[100], sa[104]], [sa[108], sa[112], sa[116], sa[120], sa[124], sa[128], sa[132], sa[136], sa[140]]], [[sa[2], sa[6], sa[10], sa[14], sa[18], sa[22], sa[26], sa[30], sa[34]], [sa[38], sa[42], sa[46], sa[50], sa[54], sa[58], sa[62], sa[66], sa[70]], [sa[74], sa[78], sa[82], sa[86], sa[90], sa[94], sa[98], sa[102], sa[106]], [sa[110], sa[114], sa[118], sa[122], sa[126], sa[130], sa[134], sa[138], sa[142]]]], [[[sa[1], sa[5], sa[9], sa[13], sa[17], sa[21], sa[25], sa[29], sa[33]], [sa[37], sa[41], sa[45], sa[49], sa[53], sa[57], sa[61], sa[65], sa[69]], [sa[73], sa[77], sa[81], sa[85], sa[89], sa[93], sa[97], sa[101], sa[105]], [sa[109], sa[113], sa[117], sa[121], sa[125], sa[129], sa[133], sa[137], sa[141]]], [[sa[3], sa[7], sa[11], sa[15], sa[19], sa[23], sa[27], sa[31], sa[35]], [sa[39], sa[43], sa[47], sa[51], sa[55], sa[59], sa[63], sa[67], sa[71]], [sa[75], sa[79], sa[83], sa[87], sa[91], sa[95], sa[99], sa[103], sa[107]], [sa[111], sa[115], sa[119], sa[123], sa[127], sa[131], sa[135], sa[139], sa[143]]]]])
|
||||
|
||||
# test for large scale sparse array
|
||||
for SparseArrayType in [ImmutableSparseNDimArray, MutableSparseNDimArray]:
|
||||
A = SparseArrayType({1:1, 10000:2}, (10000, 20000, 10000))
|
||||
assert permutedims(A, (0, 1, 2)) == A
|
||||
assert permutedims(A, (1, 0, 2)) == SparseArrayType({1: 1, 100000000: 2}, (20000, 10000, 10000))
|
||||
B = SparseArrayType({1:1, 20000:2}, (10000, 20000))
|
||||
assert B.transpose() == SparseArrayType({10000: 1, 1: 2}, (20000, 10000))
|
||||
|
||||
|
||||
def test_permutedims_with_indices():
|
||||
A = Array(range(32)).reshape(2, 2, 2, 2, 2)
|
||||
indices_new = list("abcde")
|
||||
indices_old = list("ebdac")
|
||||
new_A = permutedims(A, index_order_new=indices_new, index_order_old=indices_old)
|
||||
for a, b, c, d, e in itertools.product(range(2), range(2), range(2), range(2), range(2)):
|
||||
assert new_A[a, b, c, d, e] == A[e, b, d, a, c]
|
||||
indices_old = list("cabed")
|
||||
new_A = permutedims(A, index_order_new=indices_new, index_order_old=indices_old)
|
||||
for a, b, c, d, e in itertools.product(range(2), range(2), range(2), range(2), range(2)):
|
||||
assert new_A[a, b, c, d, e] == A[c, a, b, e, d]
|
||||
raises(ValueError, lambda: permutedims(A, index_order_old=list("aacde"), index_order_new=list("abcde")))
|
||||
raises(ValueError, lambda: permutedims(A, index_order_old=list("abcde"), index_order_new=list("abcce")))
|
||||
raises(ValueError, lambda: permutedims(A, index_order_old=list("abcde"), index_order_new=list("abce")))
|
||||
raises(ValueError, lambda: permutedims(A, index_order_old=list("abce"), index_order_new=list("abce")))
|
||||
raises(ValueError, lambda: permutedims(A, [2, 1, 0, 3, 4], index_order_old=list("abcde")))
|
||||
raises(ValueError, lambda: permutedims(A, [2, 1, 0, 3, 4], index_order_new=list("abcde")))
|
||||
|
||||
|
||||
def test_flatten():
|
||||
from sympy.matrices.dense import Matrix
|
||||
for ArrayType in [ImmutableDenseNDimArray, ImmutableSparseNDimArray, Matrix]:
|
||||
A = ArrayType(range(24)).reshape(4, 6)
|
||||
assert list(Flatten(A)) == [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]
|
||||
|
||||
for i, v in enumerate(Flatten(A)):
|
||||
assert i == v
|
||||
|
||||
|
||||
def test_tensordiagonal():
|
||||
from sympy.matrices.dense import eye
|
||||
expr = Array(range(9)).reshape(3, 3)
|
||||
raises(ValueError, lambda: tensordiagonal(expr, [0], [1]))
|
||||
raises(ValueError, lambda: tensordiagonal(expr, [0, 0]))
|
||||
assert tensordiagonal(eye(3), [0, 1]) == Array([1, 1, 1])
|
||||
assert tensordiagonal(expr, [0, 1]) == Array([0, 4, 8])
|
||||
x, y, z = symbols("x y z")
|
||||
expr2 = tensorproduct([x, y, z], expr)
|
||||
assert tensordiagonal(expr2, [1, 2]) == Array([[0, 4*x, 8*x], [0, 4*y, 8*y], [0, 4*z, 8*z]])
|
||||
assert tensordiagonal(expr2, [0, 1]) == Array([[0, 3*y, 6*z], [x, 4*y, 7*z], [2*x, 5*y, 8*z]])
|
||||
assert tensordiagonal(expr2, [0, 1, 2]) == Array([0, 4*y, 8*z])
|
||||
# assert tensordiagonal(expr2, [0]) == permutedims(expr2, [1, 2, 0])
|
||||
# assert tensordiagonal(expr2, [1]) == permutedims(expr2, [0, 2, 1])
|
||||
# assert tensordiagonal(expr2, [2]) == expr2
|
||||
# assert tensordiagonal(expr2, [1], [2]) == expr2
|
||||
# assert tensordiagonal(expr2, [0], [1]) == permutedims(expr2, [2, 0, 1])
|
||||
|
||||
a, b, c, X, Y, Z = symbols("a b c X Y Z")
|
||||
expr3 = tensorproduct([x, y, z], [1, 2, 3], [a, b, c], [X, Y, Z])
|
||||
assert tensordiagonal(expr3, [0, 1, 2, 3]) == Array([x*a*X, 2*y*b*Y, 3*z*c*Z])
|
||||
assert tensordiagonal(expr3, [0, 1], [2, 3]) == tensorproduct([x, 2*y, 3*z], [a*X, b*Y, c*Z])
|
||||
|
||||
# assert tensordiagonal(expr3, [0], [1, 2], [3]) == tensorproduct([x, y, z], [a, 2*b, 3*c], [X, Y, Z])
|
||||
assert tensordiagonal(tensordiagonal(expr3, [2, 3]), [0, 1]) == tensorproduct([a*X, b*Y, c*Z], [x, 2*y, 3*z])
|
||||
|
||||
raises(ValueError, lambda: tensordiagonal([[1, 2, 3], [4, 5, 6]], [0, 1]))
|
||||
raises(ValueError, lambda: tensordiagonal(expr3.reshape(3, 3, 9), [1, 2]))
|
||||
+452
@@ -0,0 +1,452 @@
|
||||
from copy import copy
|
||||
|
||||
from sympy.tensor.array.dense_ndim_array import ImmutableDenseNDimArray
|
||||
from sympy.core.containers import Dict
|
||||
from sympy.core.function import diff
|
||||
from sympy.core.numbers import Rational
|
||||
from sympy.core.singleton import S
|
||||
from sympy.core.symbol import (Symbol, symbols)
|
||||
from sympy.matrices import SparseMatrix
|
||||
from sympy.tensor.indexed import (Indexed, IndexedBase)
|
||||
from sympy.matrices import Matrix
|
||||
from sympy.tensor.array.sparse_ndim_array import ImmutableSparseNDimArray
|
||||
from sympy.testing.pytest import raises
|
||||
|
||||
|
||||
def test_ndim_array_initiation():
|
||||
arr_with_no_elements = ImmutableDenseNDimArray([], shape=(0,))
|
||||
assert len(arr_with_no_elements) == 0
|
||||
assert arr_with_no_elements.rank() == 1
|
||||
|
||||
raises(ValueError, lambda: ImmutableDenseNDimArray([0], shape=(0,)))
|
||||
raises(ValueError, lambda: ImmutableDenseNDimArray([1, 2, 3], shape=(0,)))
|
||||
raises(ValueError, lambda: ImmutableDenseNDimArray([], shape=()))
|
||||
|
||||
raises(ValueError, lambda: ImmutableSparseNDimArray([0], shape=(0,)))
|
||||
raises(ValueError, lambda: ImmutableSparseNDimArray([1, 2, 3], shape=(0,)))
|
||||
raises(ValueError, lambda: ImmutableSparseNDimArray([], shape=()))
|
||||
|
||||
arr_with_one_element = ImmutableDenseNDimArray([23])
|
||||
assert len(arr_with_one_element) == 1
|
||||
assert arr_with_one_element[0] == 23
|
||||
assert arr_with_one_element[:] == ImmutableDenseNDimArray([23])
|
||||
assert arr_with_one_element.rank() == 1
|
||||
|
||||
arr_with_symbol_element = ImmutableDenseNDimArray([Symbol('x')])
|
||||
assert len(arr_with_symbol_element) == 1
|
||||
assert arr_with_symbol_element[0] == Symbol('x')
|
||||
assert arr_with_symbol_element[:] == ImmutableDenseNDimArray([Symbol('x')])
|
||||
assert arr_with_symbol_element.rank() == 1
|
||||
|
||||
number5 = 5
|
||||
vector = ImmutableDenseNDimArray.zeros(number5)
|
||||
assert len(vector) == number5
|
||||
assert vector.shape == (number5,)
|
||||
assert vector.rank() == 1
|
||||
|
||||
vector = ImmutableSparseNDimArray.zeros(number5)
|
||||
assert len(vector) == number5
|
||||
assert vector.shape == (number5,)
|
||||
assert vector._sparse_array == Dict()
|
||||
assert vector.rank() == 1
|
||||
|
||||
n_dim_array = ImmutableDenseNDimArray(range(3**4), (3, 3, 3, 3,))
|
||||
assert len(n_dim_array) == 3 * 3 * 3 * 3
|
||||
assert n_dim_array.shape == (3, 3, 3, 3)
|
||||
assert n_dim_array.rank() == 4
|
||||
|
||||
array_shape = (3, 3, 3, 3)
|
||||
sparse_array = ImmutableSparseNDimArray.zeros(*array_shape)
|
||||
assert len(sparse_array._sparse_array) == 0
|
||||
assert len(sparse_array) == 3 * 3 * 3 * 3
|
||||
assert n_dim_array.shape == array_shape
|
||||
assert n_dim_array.rank() == 4
|
||||
|
||||
one_dim_array = ImmutableDenseNDimArray([2, 3, 1])
|
||||
assert len(one_dim_array) == 3
|
||||
assert one_dim_array.shape == (3,)
|
||||
assert one_dim_array.rank() == 1
|
||||
assert one_dim_array.tolist() == [2, 3, 1]
|
||||
|
||||
shape = (3, 3)
|
||||
array_with_many_args = ImmutableSparseNDimArray.zeros(*shape)
|
||||
assert len(array_with_many_args) == 3 * 3
|
||||
assert array_with_many_args.shape == shape
|
||||
assert array_with_many_args[0, 0] == 0
|
||||
assert array_with_many_args.rank() == 2
|
||||
|
||||
shape = (int(3), int(3))
|
||||
array_with_long_shape = ImmutableSparseNDimArray.zeros(*shape)
|
||||
assert len(array_with_long_shape) == 3 * 3
|
||||
assert array_with_long_shape.shape == shape
|
||||
assert array_with_long_shape[int(0), int(0)] == 0
|
||||
assert array_with_long_shape.rank() == 2
|
||||
|
||||
vector_with_long_shape = ImmutableDenseNDimArray(range(5), int(5))
|
||||
assert len(vector_with_long_shape) == 5
|
||||
assert vector_with_long_shape.shape == (int(5),)
|
||||
assert vector_with_long_shape.rank() == 1
|
||||
raises(ValueError, lambda: vector_with_long_shape[int(5)])
|
||||
|
||||
from sympy.abc import x
|
||||
for ArrayType in [ImmutableDenseNDimArray, ImmutableSparseNDimArray]:
|
||||
rank_zero_array = ArrayType(x)
|
||||
assert len(rank_zero_array) == 1
|
||||
assert rank_zero_array.shape == ()
|
||||
assert rank_zero_array.rank() == 0
|
||||
assert rank_zero_array[()] == x
|
||||
raises(ValueError, lambda: rank_zero_array[0])
|
||||
|
||||
|
||||
def test_reshape():
|
||||
array = ImmutableDenseNDimArray(range(50), 50)
|
||||
assert array.shape == (50,)
|
||||
assert array.rank() == 1
|
||||
|
||||
array = array.reshape(5, 5, 2)
|
||||
assert array.shape == (5, 5, 2)
|
||||
assert array.rank() == 3
|
||||
assert len(array) == 50
|
||||
|
||||
|
||||
def test_getitem():
|
||||
for ArrayType in [ImmutableDenseNDimArray, ImmutableSparseNDimArray]:
|
||||
array = ArrayType(range(24)).reshape(2, 3, 4)
|
||||
assert array.tolist() == [[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]], [[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]]]
|
||||
assert array[0] == ArrayType([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])
|
||||
assert array[0, 0] == ArrayType([0, 1, 2, 3])
|
||||
value = 0
|
||||
for i in range(2):
|
||||
for j in range(3):
|
||||
for k in range(4):
|
||||
assert array[i, j, k] == value
|
||||
value += 1
|
||||
|
||||
raises(ValueError, lambda: array[3, 4, 5])
|
||||
raises(ValueError, lambda: array[3, 4, 5, 6])
|
||||
raises(ValueError, lambda: array[3, 4, 5, 3:4])
|
||||
|
||||
|
||||
def test_iterator():
|
||||
array = ImmutableDenseNDimArray(range(4), (2, 2))
|
||||
assert array[0] == ImmutableDenseNDimArray([0, 1])
|
||||
assert array[1] == ImmutableDenseNDimArray([2, 3])
|
||||
|
||||
array = array.reshape(4)
|
||||
j = 0
|
||||
for i in array:
|
||||
assert i == j
|
||||
j += 1
|
||||
|
||||
|
||||
def test_sparse():
|
||||
sparse_array = ImmutableSparseNDimArray([0, 0, 0, 1], (2, 2))
|
||||
assert len(sparse_array) == 2 * 2
|
||||
# dictionary where all data is, only non-zero entries are actually stored:
|
||||
assert len(sparse_array._sparse_array) == 1
|
||||
|
||||
assert sparse_array.tolist() == [[0, 0], [0, 1]]
|
||||
|
||||
for i, j in zip(sparse_array, [[0, 0], [0, 1]]):
|
||||
assert i == ImmutableSparseNDimArray(j)
|
||||
|
||||
def sparse_assignment():
|
||||
sparse_array[0, 0] = 123
|
||||
|
||||
assert len(sparse_array._sparse_array) == 1
|
||||
raises(TypeError, sparse_assignment)
|
||||
assert len(sparse_array._sparse_array) == 1
|
||||
assert sparse_array[0, 0] == 0
|
||||
assert sparse_array/0 == ImmutableSparseNDimArray([[S.NaN, S.NaN], [S.NaN, S.ComplexInfinity]], (2, 2))
|
||||
|
||||
# test for large scale sparse array
|
||||
# equality test
|
||||
assert ImmutableSparseNDimArray.zeros(100000, 200000) == ImmutableSparseNDimArray.zeros(100000, 200000)
|
||||
|
||||
# __mul__ and __rmul__
|
||||
a = ImmutableSparseNDimArray({200001: 1}, (100000, 200000))
|
||||
assert a * 3 == ImmutableSparseNDimArray({200001: 3}, (100000, 200000))
|
||||
assert 3 * a == ImmutableSparseNDimArray({200001: 3}, (100000, 200000))
|
||||
assert a * 0 == ImmutableSparseNDimArray({}, (100000, 200000))
|
||||
assert 0 * a == ImmutableSparseNDimArray({}, (100000, 200000))
|
||||
|
||||
# __truediv__
|
||||
assert a/3 == ImmutableSparseNDimArray({200001: Rational(1, 3)}, (100000, 200000))
|
||||
|
||||
# __neg__
|
||||
assert -a == ImmutableSparseNDimArray({200001: -1}, (100000, 200000))
|
||||
|
||||
|
||||
def test_calculation():
|
||||
|
||||
a = ImmutableDenseNDimArray([1]*9, (3, 3))
|
||||
b = ImmutableDenseNDimArray([9]*9, (3, 3))
|
||||
|
||||
c = a + b
|
||||
for i in c:
|
||||
assert i == ImmutableDenseNDimArray([10, 10, 10])
|
||||
|
||||
assert c == ImmutableDenseNDimArray([10]*9, (3, 3))
|
||||
assert c == ImmutableSparseNDimArray([10]*9, (3, 3))
|
||||
|
||||
c = b - a
|
||||
for i in c:
|
||||
assert i == ImmutableDenseNDimArray([8, 8, 8])
|
||||
|
||||
assert c == ImmutableDenseNDimArray([8]*9, (3, 3))
|
||||
assert c == ImmutableSparseNDimArray([8]*9, (3, 3))
|
||||
|
||||
|
||||
def test_ndim_array_converting():
|
||||
dense_array = ImmutableDenseNDimArray([1, 2, 3, 4], (2, 2))
|
||||
alist = dense_array.tolist()
|
||||
|
||||
assert alist == [[1, 2], [3, 4]]
|
||||
|
||||
matrix = dense_array.tomatrix()
|
||||
assert (isinstance(matrix, Matrix))
|
||||
|
||||
for i in range(len(dense_array)):
|
||||
assert dense_array[dense_array._get_tuple_index(i)] == matrix[i]
|
||||
assert matrix.shape == dense_array.shape
|
||||
|
||||
assert ImmutableDenseNDimArray(matrix) == dense_array
|
||||
assert ImmutableDenseNDimArray(matrix.as_immutable()) == dense_array
|
||||
assert ImmutableDenseNDimArray(matrix.as_mutable()) == dense_array
|
||||
|
||||
sparse_array = ImmutableSparseNDimArray([1, 2, 3, 4], (2, 2))
|
||||
alist = sparse_array.tolist()
|
||||
|
||||
assert alist == [[1, 2], [3, 4]]
|
||||
|
||||
matrix = sparse_array.tomatrix()
|
||||
assert(isinstance(matrix, SparseMatrix))
|
||||
|
||||
for i in range(len(sparse_array)):
|
||||
assert sparse_array[sparse_array._get_tuple_index(i)] == matrix[i]
|
||||
assert matrix.shape == sparse_array.shape
|
||||
|
||||
assert ImmutableSparseNDimArray(matrix) == sparse_array
|
||||
assert ImmutableSparseNDimArray(matrix.as_immutable()) == sparse_array
|
||||
assert ImmutableSparseNDimArray(matrix.as_mutable()) == sparse_array
|
||||
|
||||
|
||||
def test_converting_functions():
|
||||
arr_list = [1, 2, 3, 4]
|
||||
arr_matrix = Matrix(((1, 2), (3, 4)))
|
||||
|
||||
# list
|
||||
arr_ndim_array = ImmutableDenseNDimArray(arr_list, (2, 2))
|
||||
assert (isinstance(arr_ndim_array, ImmutableDenseNDimArray))
|
||||
assert arr_matrix.tolist() == arr_ndim_array.tolist()
|
||||
|
||||
# Matrix
|
||||
arr_ndim_array = ImmutableDenseNDimArray(arr_matrix)
|
||||
assert (isinstance(arr_ndim_array, ImmutableDenseNDimArray))
|
||||
assert arr_matrix.tolist() == arr_ndim_array.tolist()
|
||||
assert arr_matrix.shape == arr_ndim_array.shape
|
||||
|
||||
|
||||
def test_equality():
|
||||
first_list = [1, 2, 3, 4]
|
||||
second_list = [1, 2, 3, 4]
|
||||
third_list = [4, 3, 2, 1]
|
||||
assert first_list == second_list
|
||||
assert first_list != third_list
|
||||
|
||||
first_ndim_array = ImmutableDenseNDimArray(first_list, (2, 2))
|
||||
second_ndim_array = ImmutableDenseNDimArray(second_list, (2, 2))
|
||||
fourth_ndim_array = ImmutableDenseNDimArray(first_list, (2, 2))
|
||||
|
||||
assert first_ndim_array == second_ndim_array
|
||||
|
||||
def assignment_attempt(a):
|
||||
a[0, 0] = 0
|
||||
|
||||
raises(TypeError, lambda: assignment_attempt(second_ndim_array))
|
||||
assert first_ndim_array == second_ndim_array
|
||||
assert first_ndim_array == fourth_ndim_array
|
||||
|
||||
|
||||
def test_arithmetic():
|
||||
a = ImmutableDenseNDimArray([3 for i in range(9)], (3, 3))
|
||||
b = ImmutableDenseNDimArray([7 for i in range(9)], (3, 3))
|
||||
|
||||
c1 = a + b
|
||||
c2 = b + a
|
||||
assert c1 == c2
|
||||
|
||||
d1 = a - b
|
||||
d2 = b - a
|
||||
assert d1 == d2 * (-1)
|
||||
|
||||
e1 = a * 5
|
||||
e2 = 5 * a
|
||||
e3 = copy(a)
|
||||
e3 *= 5
|
||||
assert e1 == e2 == e3
|
||||
|
||||
f1 = a / 5
|
||||
f2 = copy(a)
|
||||
f2 /= 5
|
||||
assert f1 == f2
|
||||
assert f1[0, 0] == f1[0, 1] == f1[0, 2] == f1[1, 0] == f1[1, 1] == \
|
||||
f1[1, 2] == f1[2, 0] == f1[2, 1] == f1[2, 2] == Rational(3, 5)
|
||||
|
||||
assert type(a) == type(b) == type(c1) == type(c2) == type(d1) == type(d2) \
|
||||
== type(e1) == type(e2) == type(e3) == type(f1)
|
||||
|
||||
z0 = -a
|
||||
assert z0 == ImmutableDenseNDimArray([-3 for i in range(9)], (3, 3))
|
||||
|
||||
|
||||
def test_higher_dimenions():
|
||||
m3 = ImmutableDenseNDimArray(range(10, 34), (2, 3, 4))
|
||||
|
||||
assert m3.tolist() == [[[10, 11, 12, 13],
|
||||
[14, 15, 16, 17],
|
||||
[18, 19, 20, 21]],
|
||||
|
||||
[[22, 23, 24, 25],
|
||||
[26, 27, 28, 29],
|
||||
[30, 31, 32, 33]]]
|
||||
|
||||
assert m3._get_tuple_index(0) == (0, 0, 0)
|
||||
assert m3._get_tuple_index(1) == (0, 0, 1)
|
||||
assert m3._get_tuple_index(4) == (0, 1, 0)
|
||||
assert m3._get_tuple_index(12) == (1, 0, 0)
|
||||
|
||||
assert str(m3) == '[[[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21]], [[22, 23, 24, 25], [26, 27, 28, 29], [30, 31, 32, 33]]]'
|
||||
|
||||
m3_rebuilt = ImmutableDenseNDimArray([[[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21]], [[22, 23, 24, 25], [26, 27, 28, 29], [30, 31, 32, 33]]])
|
||||
assert m3 == m3_rebuilt
|
||||
|
||||
m3_other = ImmutableDenseNDimArray([[[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21]], [[22, 23, 24, 25], [26, 27, 28, 29], [30, 31, 32, 33]]], (2, 3, 4))
|
||||
|
||||
assert m3 == m3_other
|
||||
|
||||
|
||||
def test_rebuild_immutable_arrays():
|
||||
sparr = ImmutableSparseNDimArray(range(10, 34), (2, 3, 4))
|
||||
densarr = ImmutableDenseNDimArray(range(10, 34), (2, 3, 4))
|
||||
|
||||
assert sparr == sparr.func(*sparr.args)
|
||||
assert densarr == densarr.func(*densarr.args)
|
||||
|
||||
|
||||
def test_slices():
|
||||
md = ImmutableDenseNDimArray(range(10, 34), (2, 3, 4))
|
||||
|
||||
assert md[:] == ImmutableDenseNDimArray(range(10, 34), (2, 3, 4))
|
||||
assert md[:, :, 0].tomatrix() == Matrix([[10, 14, 18], [22, 26, 30]])
|
||||
assert md[0, 1:2, :].tomatrix() == Matrix([[14, 15, 16, 17]])
|
||||
assert md[0, 1:3, :].tomatrix() == Matrix([[14, 15, 16, 17], [18, 19, 20, 21]])
|
||||
assert md[:, :, :] == md
|
||||
|
||||
sd = ImmutableSparseNDimArray(range(10, 34), (2, 3, 4))
|
||||
assert sd == ImmutableSparseNDimArray(md)
|
||||
|
||||
assert sd[:] == ImmutableSparseNDimArray(range(10, 34), (2, 3, 4))
|
||||
assert sd[:, :, 0].tomatrix() == Matrix([[10, 14, 18], [22, 26, 30]])
|
||||
assert sd[0, 1:2, :].tomatrix() == Matrix([[14, 15, 16, 17]])
|
||||
assert sd[0, 1:3, :].tomatrix() == Matrix([[14, 15, 16, 17], [18, 19, 20, 21]])
|
||||
assert sd[:, :, :] == sd
|
||||
|
||||
|
||||
def test_diff_and_applyfunc():
|
||||
from sympy.abc import x, y, z
|
||||
md = ImmutableDenseNDimArray([[x, y], [x*z, x*y*z]])
|
||||
assert md.diff(x) == ImmutableDenseNDimArray([[1, 0], [z, y*z]])
|
||||
assert diff(md, x) == ImmutableDenseNDimArray([[1, 0], [z, y*z]])
|
||||
|
||||
sd = ImmutableSparseNDimArray(md)
|
||||
assert sd == ImmutableSparseNDimArray([x, y, x*z, x*y*z], (2, 2))
|
||||
assert sd.diff(x) == ImmutableSparseNDimArray([[1, 0], [z, y*z]])
|
||||
assert diff(sd, x) == ImmutableSparseNDimArray([[1, 0], [z, y*z]])
|
||||
|
||||
mdn = md.applyfunc(lambda x: x*3)
|
||||
assert mdn == ImmutableDenseNDimArray([[3*x, 3*y], [3*x*z, 3*x*y*z]])
|
||||
assert md != mdn
|
||||
|
||||
sdn = sd.applyfunc(lambda x: x/2)
|
||||
assert sdn == ImmutableSparseNDimArray([[x/2, y/2], [x*z/2, x*y*z/2]])
|
||||
assert sd != sdn
|
||||
|
||||
sdp = sd.applyfunc(lambda x: x+1)
|
||||
assert sdp == ImmutableSparseNDimArray([[x + 1, y + 1], [x*z + 1, x*y*z + 1]])
|
||||
assert sd != sdp
|
||||
|
||||
|
||||
def test_op_priority():
|
||||
from sympy.abc import x
|
||||
md = ImmutableDenseNDimArray([1, 2, 3])
|
||||
e1 = (1+x)*md
|
||||
e2 = md*(1+x)
|
||||
assert e1 == ImmutableDenseNDimArray([1+x, 2+2*x, 3+3*x])
|
||||
assert e1 == e2
|
||||
|
||||
sd = ImmutableSparseNDimArray([1, 2, 3])
|
||||
e3 = (1+x)*sd
|
||||
e4 = sd*(1+x)
|
||||
assert e3 == ImmutableDenseNDimArray([1+x, 2+2*x, 3+3*x])
|
||||
assert e3 == e4
|
||||
|
||||
|
||||
def test_symbolic_indexing():
|
||||
x, y, z, w = symbols("x y z w")
|
||||
M = ImmutableDenseNDimArray([[x, y], [z, w]])
|
||||
i, j = symbols("i, j")
|
||||
Mij = M[i, j]
|
||||
assert isinstance(Mij, Indexed)
|
||||
Ms = ImmutableSparseNDimArray([[2, 3*x], [4, 5]])
|
||||
msij = Ms[i, j]
|
||||
assert isinstance(msij, Indexed)
|
||||
for oi, oj in [(0, 0), (0, 1), (1, 0), (1, 1)]:
|
||||
assert Mij.subs({i: oi, j: oj}) == M[oi, oj]
|
||||
assert msij.subs({i: oi, j: oj}) == Ms[oi, oj]
|
||||
A = IndexedBase("A", (0, 2))
|
||||
assert A[0, 0].subs(A, M) == x
|
||||
assert A[i, j].subs(A, M) == M[i, j]
|
||||
assert M[i, j].subs(M, A) == A[i, j]
|
||||
|
||||
assert isinstance(M[3 * i - 2, j], Indexed)
|
||||
assert M[3 * i - 2, j].subs({i: 1, j: 0}) == M[1, 0]
|
||||
assert isinstance(M[i, 0], Indexed)
|
||||
assert M[i, 0].subs(i, 0) == M[0, 0]
|
||||
assert M[0, i].subs(i, 1) == M[0, 1]
|
||||
|
||||
assert M[i, j].diff(x) == ImmutableDenseNDimArray([[1, 0], [0, 0]])[i, j]
|
||||
assert Ms[i, j].diff(x) == ImmutableSparseNDimArray([[0, 3], [0, 0]])[i, j]
|
||||
|
||||
Mo = ImmutableDenseNDimArray([1, 2, 3])
|
||||
assert Mo[i].subs(i, 1) == 2
|
||||
Mos = ImmutableSparseNDimArray([1, 2, 3])
|
||||
assert Mos[i].subs(i, 1) == 2
|
||||
|
||||
raises(ValueError, lambda: M[i, 2])
|
||||
raises(ValueError, lambda: M[i, -1])
|
||||
raises(ValueError, lambda: M[2, i])
|
||||
raises(ValueError, lambda: M[-1, i])
|
||||
|
||||
raises(ValueError, lambda: Ms[i, 2])
|
||||
raises(ValueError, lambda: Ms[i, -1])
|
||||
raises(ValueError, lambda: Ms[2, i])
|
||||
raises(ValueError, lambda: Ms[-1, i])
|
||||
|
||||
|
||||
def test_issue_12665():
|
||||
# Testing Python 3 hash of immutable arrays:
|
||||
arr = ImmutableDenseNDimArray([1, 2, 3])
|
||||
# This should NOT raise an exception:
|
||||
hash(arr)
|
||||
|
||||
|
||||
def test_zeros_without_shape():
|
||||
arr = ImmutableDenseNDimArray.zeros()
|
||||
assert arr == ImmutableDenseNDimArray(0)
|
||||
|
||||
def test_issue_21870():
|
||||
a0 = ImmutableDenseNDimArray(0)
|
||||
assert a0.rank() == 0
|
||||
a1 = ImmutableDenseNDimArray(a0)
|
||||
assert a1.rank() == 0
|
||||
+374
@@ -0,0 +1,374 @@
|
||||
from copy import copy
|
||||
|
||||
from sympy.tensor.array.dense_ndim_array import MutableDenseNDimArray
|
||||
from sympy.core.function import diff
|
||||
from sympy.core.numbers import Rational
|
||||
from sympy.core.singleton import S
|
||||
from sympy.core.symbol import Symbol
|
||||
from sympy.core.sympify import sympify
|
||||
from sympy.matrices import SparseMatrix
|
||||
from sympy.matrices import Matrix
|
||||
from sympy.tensor.array.sparse_ndim_array import MutableSparseNDimArray
|
||||
from sympy.testing.pytest import raises
|
||||
|
||||
|
||||
def test_ndim_array_initiation():
|
||||
arr_with_one_element = MutableDenseNDimArray([23])
|
||||
assert len(arr_with_one_element) == 1
|
||||
assert arr_with_one_element[0] == 23
|
||||
assert arr_with_one_element.rank() == 1
|
||||
raises(ValueError, lambda: arr_with_one_element[1])
|
||||
|
||||
arr_with_symbol_element = MutableDenseNDimArray([Symbol('x')])
|
||||
assert len(arr_with_symbol_element) == 1
|
||||
assert arr_with_symbol_element[0] == Symbol('x')
|
||||
assert arr_with_symbol_element.rank() == 1
|
||||
|
||||
number5 = 5
|
||||
vector = MutableDenseNDimArray.zeros(number5)
|
||||
assert len(vector) == number5
|
||||
assert vector.shape == (number5,)
|
||||
assert vector.rank() == 1
|
||||
raises(ValueError, lambda: arr_with_one_element[5])
|
||||
|
||||
vector = MutableSparseNDimArray.zeros(number5)
|
||||
assert len(vector) == number5
|
||||
assert vector.shape == (number5,)
|
||||
assert vector._sparse_array == {}
|
||||
assert vector.rank() == 1
|
||||
|
||||
n_dim_array = MutableDenseNDimArray(range(3**4), (3, 3, 3, 3,))
|
||||
assert len(n_dim_array) == 3 * 3 * 3 * 3
|
||||
assert n_dim_array.shape == (3, 3, 3, 3)
|
||||
assert n_dim_array.rank() == 4
|
||||
raises(ValueError, lambda: n_dim_array[0, 0, 0, 3])
|
||||
raises(ValueError, lambda: n_dim_array[3, 0, 0, 0])
|
||||
raises(ValueError, lambda: n_dim_array[3**4])
|
||||
|
||||
array_shape = (3, 3, 3, 3)
|
||||
sparse_array = MutableSparseNDimArray.zeros(*array_shape)
|
||||
assert len(sparse_array._sparse_array) == 0
|
||||
assert len(sparse_array) == 3 * 3 * 3 * 3
|
||||
assert n_dim_array.shape == array_shape
|
||||
assert n_dim_array.rank() == 4
|
||||
|
||||
one_dim_array = MutableDenseNDimArray([2, 3, 1])
|
||||
assert len(one_dim_array) == 3
|
||||
assert one_dim_array.shape == (3,)
|
||||
assert one_dim_array.rank() == 1
|
||||
assert one_dim_array.tolist() == [2, 3, 1]
|
||||
|
||||
shape = (3, 3)
|
||||
array_with_many_args = MutableSparseNDimArray.zeros(*shape)
|
||||
assert len(array_with_many_args) == 3 * 3
|
||||
assert array_with_many_args.shape == shape
|
||||
assert array_with_many_args[0, 0] == 0
|
||||
assert array_with_many_args.rank() == 2
|
||||
|
||||
shape = (int(3), int(3))
|
||||
array_with_long_shape = MutableSparseNDimArray.zeros(*shape)
|
||||
assert len(array_with_long_shape) == 3 * 3
|
||||
assert array_with_long_shape.shape == shape
|
||||
assert array_with_long_shape[int(0), int(0)] == 0
|
||||
assert array_with_long_shape.rank() == 2
|
||||
|
||||
vector_with_long_shape = MutableDenseNDimArray(range(5), int(5))
|
||||
assert len(vector_with_long_shape) == 5
|
||||
assert vector_with_long_shape.shape == (int(5),)
|
||||
assert vector_with_long_shape.rank() == 1
|
||||
raises(ValueError, lambda: vector_with_long_shape[int(5)])
|
||||
|
||||
from sympy.abc import x
|
||||
for ArrayType in [MutableDenseNDimArray, MutableSparseNDimArray]:
|
||||
rank_zero_array = ArrayType(x)
|
||||
assert len(rank_zero_array) == 1
|
||||
assert rank_zero_array.shape == ()
|
||||
assert rank_zero_array.rank() == 0
|
||||
assert rank_zero_array[()] == x
|
||||
raises(ValueError, lambda: rank_zero_array[0])
|
||||
|
||||
def test_sympify():
|
||||
from sympy.abc import x, y, z, t
|
||||
arr = MutableDenseNDimArray([[x, y], [1, z*t]])
|
||||
arr_other = sympify(arr)
|
||||
assert arr_other.shape == (2, 2)
|
||||
assert arr_other == arr
|
||||
|
||||
|
||||
def test_reshape():
|
||||
array = MutableDenseNDimArray(range(50), 50)
|
||||
assert array.shape == (50,)
|
||||
assert array.rank() == 1
|
||||
|
||||
array = array.reshape(5, 5, 2)
|
||||
assert array.shape == (5, 5, 2)
|
||||
assert array.rank() == 3
|
||||
assert len(array) == 50
|
||||
|
||||
|
||||
def test_iterator():
|
||||
array = MutableDenseNDimArray(range(4), (2, 2))
|
||||
assert array[0] == MutableDenseNDimArray([0, 1])
|
||||
assert array[1] == MutableDenseNDimArray([2, 3])
|
||||
|
||||
array = array.reshape(4)
|
||||
j = 0
|
||||
for i in array:
|
||||
assert i == j
|
||||
j += 1
|
||||
|
||||
|
||||
def test_getitem():
|
||||
for ArrayType in [MutableDenseNDimArray, MutableSparseNDimArray]:
|
||||
array = ArrayType(range(24)).reshape(2, 3, 4)
|
||||
assert array.tolist() == [[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]], [[12, 13, 14, 15], [16, 17, 18, 19], [20, 21, 22, 23]]]
|
||||
assert array[0] == ArrayType([[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]])
|
||||
assert array[0, 0] == ArrayType([0, 1, 2, 3])
|
||||
value = 0
|
||||
for i in range(2):
|
||||
for j in range(3):
|
||||
for k in range(4):
|
||||
assert array[i, j, k] == value
|
||||
value += 1
|
||||
|
||||
raises(ValueError, lambda: array[3, 4, 5])
|
||||
raises(ValueError, lambda: array[3, 4, 5, 6])
|
||||
raises(ValueError, lambda: array[3, 4, 5, 3:4])
|
||||
|
||||
|
||||
def test_sparse():
|
||||
sparse_array = MutableSparseNDimArray([0, 0, 0, 1], (2, 2))
|
||||
assert len(sparse_array) == 2 * 2
|
||||
# dictionary where all data is, only non-zero entries are actually stored:
|
||||
assert len(sparse_array._sparse_array) == 1
|
||||
|
||||
assert sparse_array.tolist() == [[0, 0], [0, 1]]
|
||||
|
||||
for i, j in zip(sparse_array, [[0, 0], [0, 1]]):
|
||||
assert i == MutableSparseNDimArray(j)
|
||||
|
||||
sparse_array[0, 0] = 123
|
||||
assert len(sparse_array._sparse_array) == 2
|
||||
assert sparse_array[0, 0] == 123
|
||||
assert sparse_array/0 == MutableSparseNDimArray([[S.ComplexInfinity, S.NaN], [S.NaN, S.ComplexInfinity]], (2, 2))
|
||||
|
||||
# when element in sparse array become zero it will disappear from
|
||||
# dictionary
|
||||
sparse_array[0, 0] = 0
|
||||
assert len(sparse_array._sparse_array) == 1
|
||||
sparse_array[1, 1] = 0
|
||||
assert len(sparse_array._sparse_array) == 0
|
||||
assert sparse_array[0, 0] == 0
|
||||
|
||||
# test for large scale sparse array
|
||||
# equality test
|
||||
a = MutableSparseNDimArray.zeros(100000, 200000)
|
||||
b = MutableSparseNDimArray.zeros(100000, 200000)
|
||||
assert a == b
|
||||
a[1, 1] = 1
|
||||
b[1, 1] = 2
|
||||
assert a != b
|
||||
|
||||
# __mul__ and __rmul__
|
||||
assert a * 3 == MutableSparseNDimArray({200001: 3}, (100000, 200000))
|
||||
assert 3 * a == MutableSparseNDimArray({200001: 3}, (100000, 200000))
|
||||
assert a * 0 == MutableSparseNDimArray({}, (100000, 200000))
|
||||
assert 0 * a == MutableSparseNDimArray({}, (100000, 200000))
|
||||
|
||||
# __truediv__
|
||||
assert a/3 == MutableSparseNDimArray({200001: Rational(1, 3)}, (100000, 200000))
|
||||
|
||||
# __neg__
|
||||
assert -a == MutableSparseNDimArray({200001: -1}, (100000, 200000))
|
||||
|
||||
|
||||
def test_calculation():
|
||||
|
||||
a = MutableDenseNDimArray([1]*9, (3, 3))
|
||||
b = MutableDenseNDimArray([9]*9, (3, 3))
|
||||
|
||||
c = a + b
|
||||
for i in c:
|
||||
assert i == MutableDenseNDimArray([10, 10, 10])
|
||||
|
||||
assert c == MutableDenseNDimArray([10]*9, (3, 3))
|
||||
assert c == MutableSparseNDimArray([10]*9, (3, 3))
|
||||
|
||||
c = b - a
|
||||
for i in c:
|
||||
assert i == MutableSparseNDimArray([8, 8, 8])
|
||||
|
||||
assert c == MutableDenseNDimArray([8]*9, (3, 3))
|
||||
assert c == MutableSparseNDimArray([8]*9, (3, 3))
|
||||
|
||||
|
||||
def test_ndim_array_converting():
|
||||
dense_array = MutableDenseNDimArray([1, 2, 3, 4], (2, 2))
|
||||
alist = dense_array.tolist()
|
||||
|
||||
assert alist == [[1, 2], [3, 4]]
|
||||
|
||||
matrix = dense_array.tomatrix()
|
||||
assert (isinstance(matrix, Matrix))
|
||||
|
||||
for i in range(len(dense_array)):
|
||||
assert dense_array[dense_array._get_tuple_index(i)] == matrix[i]
|
||||
assert matrix.shape == dense_array.shape
|
||||
|
||||
assert MutableDenseNDimArray(matrix) == dense_array
|
||||
assert MutableDenseNDimArray(matrix.as_immutable()) == dense_array
|
||||
assert MutableDenseNDimArray(matrix.as_mutable()) == dense_array
|
||||
|
||||
sparse_array = MutableSparseNDimArray([1, 2, 3, 4], (2, 2))
|
||||
alist = sparse_array.tolist()
|
||||
|
||||
assert alist == [[1, 2], [3, 4]]
|
||||
|
||||
matrix = sparse_array.tomatrix()
|
||||
assert(isinstance(matrix, SparseMatrix))
|
||||
|
||||
for i in range(len(sparse_array)):
|
||||
assert sparse_array[sparse_array._get_tuple_index(i)] == matrix[i]
|
||||
assert matrix.shape == sparse_array.shape
|
||||
|
||||
assert MutableSparseNDimArray(matrix) == sparse_array
|
||||
assert MutableSparseNDimArray(matrix.as_immutable()) == sparse_array
|
||||
assert MutableSparseNDimArray(matrix.as_mutable()) == sparse_array
|
||||
|
||||
|
||||
def test_converting_functions():
|
||||
arr_list = [1, 2, 3, 4]
|
||||
arr_matrix = Matrix(((1, 2), (3, 4)))
|
||||
|
||||
# list
|
||||
arr_ndim_array = MutableDenseNDimArray(arr_list, (2, 2))
|
||||
assert (isinstance(arr_ndim_array, MutableDenseNDimArray))
|
||||
assert arr_matrix.tolist() == arr_ndim_array.tolist()
|
||||
|
||||
# Matrix
|
||||
arr_ndim_array = MutableDenseNDimArray(arr_matrix)
|
||||
assert (isinstance(arr_ndim_array, MutableDenseNDimArray))
|
||||
assert arr_matrix.tolist() == arr_ndim_array.tolist()
|
||||
assert arr_matrix.shape == arr_ndim_array.shape
|
||||
|
||||
|
||||
def test_equality():
|
||||
first_list = [1, 2, 3, 4]
|
||||
second_list = [1, 2, 3, 4]
|
||||
third_list = [4, 3, 2, 1]
|
||||
assert first_list == second_list
|
||||
assert first_list != third_list
|
||||
|
||||
first_ndim_array = MutableDenseNDimArray(first_list, (2, 2))
|
||||
second_ndim_array = MutableDenseNDimArray(second_list, (2, 2))
|
||||
third_ndim_array = MutableDenseNDimArray(third_list, (2, 2))
|
||||
fourth_ndim_array = MutableDenseNDimArray(first_list, (2, 2))
|
||||
|
||||
assert first_ndim_array == second_ndim_array
|
||||
second_ndim_array[0, 0] = 0
|
||||
assert first_ndim_array != second_ndim_array
|
||||
assert first_ndim_array != third_ndim_array
|
||||
assert first_ndim_array == fourth_ndim_array
|
||||
|
||||
|
||||
def test_arithmetic():
|
||||
a = MutableDenseNDimArray([3 for i in range(9)], (3, 3))
|
||||
b = MutableDenseNDimArray([7 for i in range(9)], (3, 3))
|
||||
|
||||
c1 = a + b
|
||||
c2 = b + a
|
||||
assert c1 == c2
|
||||
|
||||
d1 = a - b
|
||||
d2 = b - a
|
||||
assert d1 == d2 * (-1)
|
||||
|
||||
e1 = a * 5
|
||||
e2 = 5 * a
|
||||
e3 = copy(a)
|
||||
e3 *= 5
|
||||
assert e1 == e2 == e3
|
||||
|
||||
f1 = a / 5
|
||||
f2 = copy(a)
|
||||
f2 /= 5
|
||||
assert f1 == f2
|
||||
assert f1[0, 0] == f1[0, 1] == f1[0, 2] == f1[1, 0] == f1[1, 1] == \
|
||||
f1[1, 2] == f1[2, 0] == f1[2, 1] == f1[2, 2] == Rational(3, 5)
|
||||
|
||||
assert type(a) == type(b) == type(c1) == type(c2) == type(d1) == type(d2) \
|
||||
== type(e1) == type(e2) == type(e3) == type(f1)
|
||||
|
||||
z0 = -a
|
||||
assert z0 == MutableDenseNDimArray([-3 for i in range(9)], (3, 3))
|
||||
|
||||
|
||||
def test_higher_dimenions():
|
||||
m3 = MutableDenseNDimArray(range(10, 34), (2, 3, 4))
|
||||
|
||||
assert m3.tolist() == [[[10, 11, 12, 13],
|
||||
[14, 15, 16, 17],
|
||||
[18, 19, 20, 21]],
|
||||
|
||||
[[22, 23, 24, 25],
|
||||
[26, 27, 28, 29],
|
||||
[30, 31, 32, 33]]]
|
||||
|
||||
assert m3._get_tuple_index(0) == (0, 0, 0)
|
||||
assert m3._get_tuple_index(1) == (0, 0, 1)
|
||||
assert m3._get_tuple_index(4) == (0, 1, 0)
|
||||
assert m3._get_tuple_index(12) == (1, 0, 0)
|
||||
|
||||
assert str(m3) == '[[[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21]], [[22, 23, 24, 25], [26, 27, 28, 29], [30, 31, 32, 33]]]'
|
||||
|
||||
m3_rebuilt = MutableDenseNDimArray([[[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21]], [[22, 23, 24, 25], [26, 27, 28, 29], [30, 31, 32, 33]]])
|
||||
assert m3 == m3_rebuilt
|
||||
|
||||
m3_other = MutableDenseNDimArray([[[10, 11, 12, 13], [14, 15, 16, 17], [18, 19, 20, 21]], [[22, 23, 24, 25], [26, 27, 28, 29], [30, 31, 32, 33]]], (2, 3, 4))
|
||||
|
||||
assert m3 == m3_other
|
||||
|
||||
|
||||
def test_slices():
|
||||
md = MutableDenseNDimArray(range(10, 34), (2, 3, 4))
|
||||
|
||||
assert md[:] == MutableDenseNDimArray(range(10, 34), (2, 3, 4))
|
||||
assert md[:, :, 0].tomatrix() == Matrix([[10, 14, 18], [22, 26, 30]])
|
||||
assert md[0, 1:2, :].tomatrix() == Matrix([[14, 15, 16, 17]])
|
||||
assert md[0, 1:3, :].tomatrix() == Matrix([[14, 15, 16, 17], [18, 19, 20, 21]])
|
||||
assert md[:, :, :] == md
|
||||
|
||||
sd = MutableSparseNDimArray(range(10, 34), (2, 3, 4))
|
||||
assert sd == MutableSparseNDimArray(md)
|
||||
|
||||
assert sd[:] == MutableSparseNDimArray(range(10, 34), (2, 3, 4))
|
||||
assert sd[:, :, 0].tomatrix() == Matrix([[10, 14, 18], [22, 26, 30]])
|
||||
assert sd[0, 1:2, :].tomatrix() == Matrix([[14, 15, 16, 17]])
|
||||
assert sd[0, 1:3, :].tomatrix() == Matrix([[14, 15, 16, 17], [18, 19, 20, 21]])
|
||||
assert sd[:, :, :] == sd
|
||||
|
||||
|
||||
def test_slices_assign():
|
||||
a = MutableDenseNDimArray(range(12), shape=(4, 3))
|
||||
b = MutableSparseNDimArray(range(12), shape=(4, 3))
|
||||
|
||||
for i in [a, b]:
|
||||
assert i.tolist() == [[0, 1, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11]]
|
||||
i[0, :] = [2, 2, 2]
|
||||
assert i.tolist() == [[2, 2, 2], [3, 4, 5], [6, 7, 8], [9, 10, 11]]
|
||||
i[0, 1:] = [8, 8]
|
||||
assert i.tolist() == [[2, 8, 8], [3, 4, 5], [6, 7, 8], [9, 10, 11]]
|
||||
i[1:3, 1] = [20, 44]
|
||||
assert i.tolist() == [[2, 8, 8], [3, 20, 5], [6, 44, 8], [9, 10, 11]]
|
||||
|
||||
|
||||
def test_diff():
|
||||
from sympy.abc import x, y, z
|
||||
md = MutableDenseNDimArray([[x, y], [x*z, x*y*z]])
|
||||
assert md.diff(x) == MutableDenseNDimArray([[1, 0], [z, y*z]])
|
||||
assert diff(md, x) == MutableDenseNDimArray([[1, 0], [z, y*z]])
|
||||
|
||||
sd = MutableSparseNDimArray(md)
|
||||
assert sd == MutableSparseNDimArray([x, y, x*z, x*y*z], (2, 2))
|
||||
assert sd.diff(x) == MutableSparseNDimArray([[1, 0], [z, y*z]])
|
||||
assert diff(sd, x) == MutableSparseNDimArray([[1, 0], [z, y*z]])
|
||||
@@ -0,0 +1,73 @@
|
||||
from sympy.testing.pytest import raises
|
||||
from sympy.functions.elementary.trigonometric import sin, cos
|
||||
from sympy.matrices.dense import Matrix
|
||||
from sympy.simplify import simplify
|
||||
from sympy.tensor.array import Array
|
||||
from sympy.tensor.array.dense_ndim_array import (
|
||||
ImmutableDenseNDimArray, MutableDenseNDimArray)
|
||||
from sympy.tensor.array.sparse_ndim_array import (
|
||||
ImmutableSparseNDimArray, MutableSparseNDimArray)
|
||||
|
||||
from sympy.abc import x, y
|
||||
|
||||
mutable_array_types = [
|
||||
MutableDenseNDimArray,
|
||||
MutableSparseNDimArray
|
||||
]
|
||||
|
||||
array_types = [
|
||||
ImmutableDenseNDimArray,
|
||||
ImmutableSparseNDimArray,
|
||||
MutableDenseNDimArray,
|
||||
MutableSparseNDimArray
|
||||
]
|
||||
|
||||
|
||||
def test_array_negative_indices():
|
||||
for ArrayType in array_types:
|
||||
test_array = ArrayType([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])
|
||||
assert test_array[:, -1] == Array([5, 10])
|
||||
assert test_array[:, -2] == Array([4, 9])
|
||||
assert test_array[:, -3] == Array([3, 8])
|
||||
assert test_array[:, -4] == Array([2, 7])
|
||||
assert test_array[:, -5] == Array([1, 6])
|
||||
assert test_array[:, 0] == Array([1, 6])
|
||||
assert test_array[:, 1] == Array([2, 7])
|
||||
assert test_array[:, 2] == Array([3, 8])
|
||||
assert test_array[:, 3] == Array([4, 9])
|
||||
assert test_array[:, 4] == Array([5, 10])
|
||||
|
||||
raises(ValueError, lambda: test_array[:, -6])
|
||||
raises(ValueError, lambda: test_array[-3, :])
|
||||
|
||||
assert test_array[-1, -1] == 10
|
||||
|
||||
|
||||
def test_issue_18361():
|
||||
A = Array([sin(2 * x) - 2 * sin(x) * cos(x)])
|
||||
B = Array([sin(x)**2 + cos(x)**2, 0])
|
||||
C = Array([(x + x**2)/(x*sin(y)**2 + x*cos(y)**2), 2*sin(x)*cos(x)])
|
||||
assert simplify(A) == Array([0])
|
||||
assert simplify(B) == Array([1, 0])
|
||||
assert simplify(C) == Array([x + 1, sin(2*x)])
|
||||
|
||||
|
||||
def test_issue_20222():
|
||||
A = Array([[1, 2], [3, 4]])
|
||||
B = Matrix([[1,2],[3,4]])
|
||||
raises(TypeError, lambda: A - B)
|
||||
|
||||
|
||||
def test_issue_17851():
|
||||
for array_type in array_types:
|
||||
A = array_type([])
|
||||
assert isinstance(A, array_type)
|
||||
assert A.shape == (0,)
|
||||
assert list(A) == []
|
||||
|
||||
|
||||
def test_issue_and_18715():
|
||||
for array_type in mutable_array_types:
|
||||
A = array_type([0, 1, 2])
|
||||
A[0] += 5
|
||||
assert A[0] == 5
|
||||
+22
@@ -0,0 +1,22 @@
|
||||
from sympy.tensor.array import (ImmutableDenseNDimArray,
|
||||
ImmutableSparseNDimArray, MutableDenseNDimArray, MutableSparseNDimArray)
|
||||
from sympy.abc import x, y, z
|
||||
|
||||
|
||||
def test_NDim_array_conv():
|
||||
MD = MutableDenseNDimArray([x, y, z])
|
||||
MS = MutableSparseNDimArray([x, y, z])
|
||||
ID = ImmutableDenseNDimArray([x, y, z])
|
||||
IS = ImmutableSparseNDimArray([x, y, z])
|
||||
|
||||
assert MD.as_immutable() == ID
|
||||
assert MD.as_mutable() == MD
|
||||
|
||||
assert MS.as_immutable() == IS
|
||||
assert MS.as_mutable() == MS
|
||||
|
||||
assert ID.as_immutable() == ID
|
||||
assert ID.as_mutable() == MD
|
||||
|
||||
assert IS.as_immutable() == IS
|
||||
assert IS.as_mutable() == MS
|
||||
Reference in New Issue
Block a user