Python numpy.bmat() Examples
The following are 30
code examples of numpy.bmat().
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Example #1
| Source File: test_defmatrix.py From pySINDy with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #2
| Source File: test_defmatrix.py From auto-alt-text-lambda-api with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #3
| Source File: test_defmatrix.py From lambda-packs with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #4
| Source File: test_defmatrix.py From recruit with Apache License 2.0 | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #5
| Source File: test_defmatrix.py From auto-alt-text-lambda-api with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #6
| Source File: test_defmatrix.py From lambda-packs with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #7
| Source File: test_defmatrix.py From vnpy_crypto with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #8
| Source File: test_defmatrix.py From Computable with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = array([[1, 2], [3, 4]])
B = array([[5, 6], [7, 8]])
Aresult = array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
Bresult = array([[5, 6, 5, 6],
[7, 8, 7, 8],
[5, 6, 5, 6],
[7, 8, 7, 8]])
mixresult = array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(all(bmat("A,A;A,A") == Aresult))
assert_(all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(all(b2 == mixresult))
Example #9
| Source File: test_defmatrix.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #10
| Source File: test_defmatrix.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #11
| Source File: delaunay2D.py From pyDelaunay2D with GNU General Public License v3.0 | 6 votes |
|
def circumcenter(self, tri):
"""Compute circumcenter and circumradius of a triangle in 2D.
Uses an extension of the method described here:
http://www.ics.uci.edu/~eppstein/junkyard/circumcenter.html
"""
pts = np.asarray([self.coords[v] for v in tri])
pts2 = np.dot(pts, pts.T)
A = np.bmat([[2 * pts2, [[1],
[1],
[1]]],
[[[1, 1, 1, 0]]]])
b = np.hstack((np.sum(pts * pts, axis=1), [1]))
x = np.linalg.solve(A, b)
bary_coords = x[:-1]
center = np.dot(bary_coords, pts)
# radius = np.linalg.norm(pts[0] - center) # euclidean distance
radius = np.sum(np.square(pts[0] - center)) # squared distance
return (center, radius)
Example #12
| Source File: test_defmatrix.py From GraphicDesignPatternByPython with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #13
| Source File: test_defmatrix.py From GraphicDesignPatternByPython with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #14
| Source File: test_defmatrix.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #15
| Source File: test_defmatrix.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #16
| Source File: test_defmatrix.py From pySINDy with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #17
| Source File: test_defmatrix.py From mxnet-lambda with Apache License 2.0 | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #18
| Source File: test_defmatrix.py From mxnet-lambda with Apache License 2.0 | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #19
| Source File: test_defmatrix.py From ImageFusion with MIT License | 6 votes |
|
def test_basic(self):
A = array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(all(B.A == D))
assert_(all(C.A == D))
E = array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(all(bmat([A, E]) == AEresult))
vec = arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #20
| Source File: test_defmatrix.py From ImageFusion with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = array([[1, 2], [3, 4]])
B = array([[5, 6], [7, 8]])
Aresult = array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
Bresult = array([[5, 6, 5, 6],
[7, 8, 7, 8],
[5, 6, 5, 6],
[7, 8, 7, 8]])
mixresult = array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(all(bmat("A,A;A,A") == Aresult))
assert_(all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(all(b2 == mixresult))
Example #21
| Source File: delaunay.py From reportgen with MIT License | 6 votes |
|
def Circumcenter(self, tri):
"""Compute Circumcenter and circumradius of a triangle in 2D.
Uses an extension of the method described here:
http://www.ics.uci.edu/~eppstein/junkyard/circumcenter.html
"""
pts = np.asarray([self.coords[v] for v in tri])
pts2 = np.dot(pts, pts.T)
A = np.bmat([[2 * pts2, [[1],
[1],
[1]]],
[[[1, 1, 1, 0]]]])
b = np.hstack((np.sum(pts * pts, axis=1), [1]))
x = np.linalg.solve(A, b)
bary_coords = x[:-1]
center = np.dot(bary_coords, pts)
# radius = np.linalg.norm(pts[0] - center) # euclidean distance
radius = np.sum(np.square(pts[0] - center)) # squared distance
return (center, radius)
Example #22
| Source File: test_defmatrix.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #23
| Source File: test_defmatrix.py From elasticintel with GNU General Public License v3.0 | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #24
| Source File: meshretarget.py From cmt with MIT License | 6 votes |
|
def get_weight_matrix(sp, tp, rbf, radius):
"""Get the weight matrix x in Ax=B
:param sp: Source control point array
:param tp: Target control point aray
:param rbf: Rbf function from class RBF
:param radius: Smoothing parameter
:return: Weight matrix
"""
identity = np.ones((sp.shape[0], 1))
dist = get_distance_matrix(sp, sp, rbf, radius)
# Solve x for Ax=B
dim = 3
a = np.bmat(
[
[dist, identity, sp],
[identity.T, np.zeros((1, 1)), np.zeros((1, dim))],
[sp.T, np.zeros((dim, 1)), np.zeros((dim, dim))],
]
)
b = np.bmat([[tp], [np.zeros((1, dim))], [np.zeros((dim, dim))]])
weights = np.linalg.solve(a, b)
return weights
Example #25
| Source File: test_defmatrix.py From coffeegrindsize with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #26
| Source File: test_defmatrix.py From coffeegrindsize with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #27
| Source File: bayer.py From Skribbl.io-Bot with MIT License | 6 votes |
|
def I(n, transposed=False):
"""Get the index matrix with side of length ``n``.
Will only work if ``n`` is a power of 2.
Reference: http://caca.zoy.org/study/part2.html
:param int n: Power of 2 side length of matrix.
:param bool transposed:
:return: The index matrix.
"""
if n == 2:
if transposed:
return np.array([[0, 3], [2, 1]], 'int')
else:
return np.array([[0, 2], [3, 1]], 'int')
else:
smaller_I = I(n >> 1, transposed)
if transposed:
return np.bmat([[4 * smaller_I, 4 * smaller_I + 3],
[4 * smaller_I + 2, 4 * smaller_I + 1]])
else:
return np.bmat([[4 * smaller_I, 4 * smaller_I + 2],
[4 * smaller_I + 3, 4 * smaller_I + 1]])
Example #28
| Source File: test_defmatrix.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
Example #29
| Source File: test_defmatrix.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 6 votes |
|
def test_bmat_nondefault_str(self):
A = np.array([[1, 2], [3, 4]])
B = np.array([[5, 6], [7, 8]])
Aresult = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
mixresult = np.array([[1, 2, 5, 6],
[3, 4, 7, 8],
[5, 6, 1, 2],
[7, 8, 3, 4]])
assert_(np.all(bmat("A,A;A,A") == Aresult))
assert_(np.all(bmat("A,A;A,A", ldict={'A':B}) == Aresult))
assert_raises(TypeError, bmat, "A,A;A,A", gdict={'A':B})
assert_(
np.all(bmat("A,A;A,A", ldict={'A':A}, gdict={'A':B}) == Aresult))
b2 = bmat("A,B;C,D", ldict={'A':A,'B':B}, gdict={'C':B,'D':A})
assert_(np.all(b2 == mixresult))
Example #30
| Source File: test_defmatrix.py From twitter-stock-recommendation with MIT License | 6 votes |
|
def test_basic(self):
A = np.array([[1, 2], [3, 4]])
mA = matrix(A)
assert_(np.all(mA.A == A))
B = bmat("A,A;A,A")
C = bmat([[A, A], [A, A]])
D = np.array([[1, 2, 1, 2],
[3, 4, 3, 4],
[1, 2, 1, 2],
[3, 4, 3, 4]])
assert_(np.all(B.A == D))
assert_(np.all(C.A == D))
E = np.array([[5, 6], [7, 8]])
AEresult = matrix([[1, 2, 5, 6], [3, 4, 7, 8]])
assert_(np.all(bmat([A, E]) == AEresult))
vec = np.arange(5)
mvec = matrix(vec)
assert_(mvec.shape == (1, 5))
