The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.
Example 1
def field_directions(field):
""" Scene the shows the directions of a vector field.
Parameters
----------
field: array (X, Y, N, 3)
the vector field to plot where N is the number of peaks.
Returns
----------
actors: list of vtkActor
the scene actors.
"""
actors = []
for x in range(field.shape[0]):
for y in range(field.shape[1]):
line = numpy.zeros((2, 3), dtype=numpy.single)
for vector in field[x, y]:
line[1] = vector
actors.append(pvtk.line(line, 0, linewidth=2))
actors[-1].SetPosition((x, y, 0))
return actors Example 2
def do(self, a, b):
d = linalg.det(a)
(s, ld) = linalg.slogdet(a)
if asarray(a).dtype.type in (single, double):
ad = asarray(a).astype(double)
else:
ad = asarray(a).astype(cdouble)
ev = linalg.eigvals(ad)
assert_almost_equal(d, multiply.reduce(ev, axis=-1))
assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))
s = np.atleast_1d(s)
ld = np.atleast_1d(ld)
m = (s != 0)
assert_almost_equal(np.abs(s[m]), 1)
assert_equal(ld[~m], -inf) Example 3
def __init__(self, size=10, dtype=np.single):
self.center = np.zeros([size, size], dtype)
self.water = None
self.sediment = None
self.scour = None
self.flowrate = None
self.sedimentpct = None
self.sedimentpct = None
self.capacity = None
self.avalanced = None
self.minx = None
self.miny = None
self.maxx = None
self.maxy = None
self.zscale = 1
self.maxrss = 0.0
self.sequence = [0, 1, 2, 3]
self.watermax = 1.0
self.flowratemax = 1.0
self.scourmax = 1.0
self.sedmax = 1.0
self.scourmin = 1.0 Example 4
def load(path, dtype=numpy.single):
""" Load an image.
Parameters
----------
path: str
the path to the data to be loaded.
dtype: str
type to which the data will be cast. Passing 'None' will not cast.
Returns
-------
image: Image
the loaded image.
"""
# Load the image
loader = get_loader(path)
image = loader.load(path)
# Cast the image if requested
if dtype:
image.data = image.data.astype(dtype)
return image Example 5
def do(self, a, b):
d = linalg.det(a)
(s, ld) = linalg.slogdet(a)
if asarray(a).dtype.type in (single, double):
ad = asarray(a).astype(double)
else:
ad = asarray(a).astype(cdouble)
ev = linalg.eigvals(ad)
assert_almost_equal(d, multiply.reduce(ev, axis=-1))
assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))
s = np.atleast_1d(s)
ld = np.atleast_1d(ld)
m = (s != 0)
assert_almost_equal(np.abs(s[m]), 1)
assert_equal(ld[~m], -inf) Example 6
def SGD(obj, t=0, lr=1e-2, l2reg=1e-2, momentum=0.0, _=0.0, nesterov=0): obj = regularize(obj, l2reg) lrW = lr #schedule(t, lr, l2reg) if not hasattr(obj, 'V'): obj.V = np.zeros_like(obj.W) nescale(obj.V, np.single(momentum) ) newtadd(obj.V, np.single(lrW ), obj.G) if not nesterov: newtadd(obj.W, -1, obj.V) else : newtadd(obj.W, np.single(-momentum), obj.V); newtadd(obj.W, np.single(-lrW), obj.G) #obj.V *= np.single(momentum) #obj.V -= np.single(lrW) * obj.G #if not nesterov: obj.W += obj.V #else : obj.W += np.single(momentum) * obj.V - np.single(lrW) * obj.G
Example 7
def ADADELTA(obj, t=0, lr=1e-0, l2reg=1e-2, rho=0.95, eps=1e-8): obj = regularize(obj, l2reg) if not hasattr(obj, 'V'): obj.V = np.zeros_like(obj.W) if not hasattr(obj, 'D'): obj.D = np.zeros_like(obj.W) nescale(obj.V, np.single( rho) ) newsadd(obj.V, np.single(1.0-rho), obj.G ) nescale(obj.G, nedivsr(obj.D, np.single(eps), obj.V)) # must be careful later with G nescale(obj.D, np.single( rho) ) newsadd(obj.D, np.single(1.0-rho), obj.G ) newtadd(obj.W, -1, obj.G ) #obj.V = np.single(rho) * obj.V + np.single(1.0 - rho) * obj.G * obj.G #D = np.sqrt((obj.D + eps) / (obj.V + eps)) * obj.G #obj.D = np.single(rho) * obj.D + np.single(1.0 - rho) * D * D #obj.W -= D
Example 8
def ADAM(obj, t=0, lr=1e-3, l2reg=1e-2, beta1=0.9, beta2=0.999, eps=1e-8): obj = regularize(obj, l2reg) lrW = lr #schedule(t, lr, l2reg) if not hasattr(obj, 'M'): obj.M = np.zeros_like(obj.W) if not hasattr(obj, 'V'): obj.V = np.zeros_like(obj.W) nescale(obj.M, np.single( beta1) ) newtadd(obj.M, np.single(1.0-beta1), obj.G ) nescale(obj.V, np.single( beta2) ) newsadd(obj.V, np.single(1.0-beta2), obj.G ) newtadd(obj.W, np.single( -lrW ), nesrdiv(obj.M, np.single(eps), obj.V)) #obj.M = np.single(beta1) * obj.M + np.single(1.0 - beta1) * obj.G #obj.V = np.single(beta2) * obj.V + np.single(1.0 - beta2) * obj.G * obj.G #obj.W -= np.single(lrW) * obj.M / (np.sqrt(obj.V) + np.single(eps))
Example 9
def do(self, a, b):
d = linalg.det(a)
(s, ld) = linalg.slogdet(a)
if asarray(a).dtype.type in (single, double):
ad = asarray(a).astype(double)
else:
ad = asarray(a).astype(cdouble)
ev = linalg.eigvals(ad)
assert_almost_equal(d, multiply.reduce(ev, axis=-1))
assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))
s = np.atleast_1d(s)
ld = np.atleast_1d(ld)
m = (s != 0)
assert_almost_equal(np.abs(s[m]), 1)
assert_equal(ld[~m], -inf) Example 10
def do(self, a, b):
d = linalg.det(a)
(s, ld) = linalg.slogdet(a)
if asarray(a).dtype.type in (single, double):
ad = asarray(a).astype(double)
else:
ad = asarray(a).astype(cdouble)
ev = linalg.eigvals(ad)
assert_almost_equal(d, multiply.reduce(ev, axis=-1))
assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))
s = np.atleast_1d(s)
ld = np.atleast_1d(ld)
m = (s != 0)
assert_almost_equal(np.abs(s[m]), 1)
assert_equal(ld[~m], -inf) Example 11
def do(self, a, b):
d = linalg.det(a)
(s, ld) = linalg.slogdet(a)
if asarray(a).dtype.type in (single, double):
ad = asarray(a).astype(double)
else:
ad = asarray(a).astype(cdouble)
ev = linalg.eigvals(ad)
assert_almost_equal(d, multiply.reduce(ev, axis=-1))
assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))
s = np.atleast_1d(s)
ld = np.atleast_1d(ld)
m = (s != 0)
assert_almost_equal(np.abs(s[m]), 1)
assert_equal(ld[~m], -inf) Example 12
def do(self, a, b):
d = linalg.det(a)
(s, ld) = linalg.slogdet(a)
if asarray(a).dtype.type in (single, double):
ad = asarray(a).astype(double)
else:
ad = asarray(a).astype(cdouble)
ev = linalg.eigvals(ad)
assert_almost_equal(d, multiply.reduce(ev, axis=-1))
assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))
s = np.atleast_1d(s)
ld = np.atleast_1d(ld)
m = (s != 0)
assert_almost_equal(np.abs(s[m]), 1)
assert_equal(ld[~m], -inf) Example 13
def do(self, a, b):
d = linalg.det(a)
(s, ld) = linalg.slogdet(a)
if asarray(a).dtype.type in (single, double):
ad = asarray(a).astype(double)
else:
ad = asarray(a).astype(cdouble)
ev = linalg.eigvals(ad)
assert_almost_equal(d, multiply.reduce(ev, axis=-1))
assert_almost_equal(s * np.exp(ld), multiply.reduce(ev, axis=-1))
s = np.atleast_1d(s)
ld = np.atleast_1d(ld)
m = (s != 0)
assert_almost_equal(np.abs(s[m]), 1)
assert_equal(ld[~m], -inf) Example 14
def test_floats_from_string(self, level=rlevel):
# Ticket #640, floats from string
fsingle = np.single('1.234')
fdouble = np.double('1.234')
flongdouble = np.longdouble('1.234')
assert_almost_equal(fsingle, 1.234)
assert_almost_equal(fdouble, 1.234)
assert_almost_equal(flongdouble, 1.234) Example 15
def test_compress_small_type(self, level=rlevel):
# Ticket #789, changeset 5217.
# compress with out argument segfaulted if cannot cast safely
import numpy as np
a = np.array([[1, 2], [3, 4]])
b = np.zeros((2, 1), dtype=np.single)
try:
a.compress([True, False], axis=1, out=b)
raise AssertionError("compress with an out which cannot be "
"safely casted should not return "
"successfully")
except TypeError:
pass Example 16
def test_trace_subclass(self):
# The class would need to overwrite trace to ensure single-element
# output also has the right subclass.
class MyArray(np.ndarray):
pass
b = np.arange(8).reshape((2, 2, 2)).view(MyArray)
t = b.trace()
assert isinstance(t, MyArray) Example 17
def test_export_record(self):
dt = [('a', 'b'),
('b', 'h'),
('c', 'i'),
('d', 'l'),
('dx', 'q'),
('e', 'B'),
('f', 'H'),
('g', 'I'),
('h', 'L'),
('hx', 'Q'),
('i', np.single),
('j', np.double),
('k', np.longdouble),
('ix', np.csingle),
('jx', np.cdouble),
('kx', np.clongdouble),
('l', 'S4'),
('m', 'U4'),
('n', 'V3'),
('o', '?'),
('p', np.half),
]
x = np.array(
[(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
asbytes('aaaa'), 'bbbb', asbytes(' '), True, 1.0)],
dtype=dt)
y = memoryview(x)
assert_equal(y.shape, (1,))
assert_equal(y.ndim, 1)
assert_equal(y.suboffsets, EMPTY)
sz = sum([np.dtype(b).itemsize for a, b in dt])
if np.dtype('l').itemsize == 4:
assert_equal(y.format, 'T{b:a:=h:b:i:c:l:d:q:dx:B:e:@H:f:=I:g:L:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
else:
assert_equal(y.format, 'T{b:a:=h:b:i:c:q:d:q:dx:B:e:@H:f:=I:g:Q:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
# Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides
if not (np.ones(1).strides[0] == np.iinfo(np.intp).max):
assert_equal(y.strides, (sz,))
assert_equal(y.itemsize, sz) Example 18
def test_singleton(self):
ftype = finfo(single)
ftype2 = finfo(single)
assert_equal(id(ftype), id(ftype2)) Example 19
def get_real_dtype(dtype):
return {single: single, double: double,
csingle: single, cdouble: double}[dtype] Example 20
def get_complex_dtype(dtype):
return {single: csingle, double: cdouble,
csingle: csingle, cdouble: cdouble}[dtype] Example 21
def get_rtol(dtype):
# Choose a safe rtol
if dtype in (single, csingle):
return 1e-5
else:
return 1e-11 Example 22
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
assert_equal(linalg.solve(x, x).dtype, dtype)
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 23
def test_0_size(self):
class ArraySubclass(np.ndarray):
pass
# Test system of 0x0 matrices
a = np.arange(8).reshape(2, 2, 2)
b = np.arange(6).reshape(1, 2, 3).view(ArraySubclass)
expected = linalg.solve(a, b)[:, 0:0, :]
result = linalg.solve(a[:, 0:0, 0:0], b[:, 0:0, :])
assert_array_equal(result, expected)
assert_(isinstance(result, ArraySubclass))
# Test errors for non-square and only b's dimension being 0
assert_raises(linalg.LinAlgError, linalg.solve, a[:, 0:0, 0:1], b)
assert_raises(ValueError, linalg.solve, a, b[:, 0:0, :])
# Test broadcasting error
b = np.arange(6).reshape(1, 3, 2) # broadcasting error
assert_raises(ValueError, linalg.solve, a, b)
assert_raises(ValueError, linalg.solve, a[0:0], b[0:0])
# Test zero "single equations" with 0x0 matrices.
b = np.arange(2).reshape(1, 2).view(ArraySubclass)
expected = linalg.solve(a, b)[:, 0:0]
result = linalg.solve(a[:, 0:0, 0:0], b[:, 0:0])
assert_array_equal(result, expected)
assert_(isinstance(result, ArraySubclass))
b = np.arange(3).reshape(1, 3)
assert_raises(ValueError, linalg.solve, a, b)
assert_raises(ValueError, linalg.solve, a[0:0], b[0:0])
assert_raises(ValueError, linalg.solve, a[:, 0:0, 0:0], b) Example 24
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
assert_equal(linalg.eigvals(x).dtype, dtype)
x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 25
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
w, v = np.linalg.eig(x)
assert_equal(w.dtype, dtype)
assert_equal(v.dtype, dtype)
x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
w, v = np.linalg.eig(x)
assert_equal(w.dtype, get_complex_dtype(dtype))
assert_equal(v.dtype, get_complex_dtype(dtype))
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 26
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
u, s, vh = linalg.svd(x)
assert_equal(u.dtype, dtype)
assert_equal(s.dtype, get_real_dtype(dtype))
assert_equal(vh.dtype, dtype)
s = linalg.svd(x, compute_uv=False)
assert_equal(s.dtype, get_real_dtype(dtype))
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 27
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
assert_equal(np.linalg.det(x).dtype, dtype)
ph, s = np.linalg.slogdet(x)
assert_equal(s.dtype, get_real_dtype(dtype))
assert_equal(ph.dtype, dtype)
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 28
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
w, v = np.linalg.eigh(x)
assert_equal(w.dtype, get_real_dtype(dtype))
assert_equal(v.dtype, dtype)
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 29
def __init__(self):
super(EmptyDataSource, self).__init__()
self._data = np.zeros((2, 2), dtype=np.single)
self._data[0, 0] = -1.0
self._data[1, 1] = 1.0
self._xlines = [0, 1]
self._ilines = [0, 1]
self._samples = [] # changed to allow dims() calculate len(samples) Example 30
def init_water_and_sediment(self):
if self.water is None:
self.water = np.zeros(self.center.shape, dtype=np.single)
if self.sediment is None:
self.sediment = np.zeros(self.center.shape, dtype=np.single)
if self.scour is None:
self.scour = np.zeros(self.center.shape, dtype=np.single)
if self.flowrate is None:
self.flowrate = np.zeros(self.center.shape, dtype=np.single)
if self.sedimentpct is None:
self.sedimentpct = np.zeros(self.center.shape, dtype=np.single)
if self.capacity is None:
self.capacity = np.zeros(self.center.shape, dtype=np.single)
if self.avalanced is None:
self.avalanced = np.zeros(self.center.shape, dtype=np.single) Example 31
def fromFile(filename):
if filename == '-':
filename = sys.stdin
g=Grid()
g.center=np.loadtxt(filename,np.single)
return g Example 32
def _sort(self, expfact):
# keep unique vertices only by creating a set and sort first on x then on y coordinate
# using rather slow python sort but couldn;t wrap my head around np.lexsort
verts = sorted(list({ tuple(t) for t in self.center[::] }))
x = set(c[0] for c in verts)
y = set(c[1] for c in verts)
nx = len(x)
ny = len(y)
self.minx = min(x)
self.maxx = max(x)
self.miny = min(y)
self.maxy = max(y)
xscale = (self.maxx-self.minx)/(nx-1)
yscale = (self.maxy-self.miny)/(ny-1)
# note: a purely flat plane cannot be scaled
if (yscale != 0.0) and (abs(xscale/yscale) - 1.0 > 1e-3):
raise ValueError("Mesh spacing not square %d x %d %.4f x %4.f"%(nx,ny,xscale,yscale))
self.zscale = 1.0
if abs(yscale) > 1e-6 :
self.zscale = 1.0/yscale
# keep just the z-values and null any ofsset
# we might catch a reshape error that will occur if nx*ny != # of vertices (if we are not dealing with a heightfield but with a mesh with duplicate x,y coords, like an axis aligned cube
self.center = np.array([c[2] for c in verts],dtype=np.single).reshape(nx,ny)
self.center = (self.center-np.amin(self.center))*self.zscale
if self.rainmap is not None:
rmscale = np.max(self.center)
self.rainmap = expfact + (1-expfact)*(self.center/rmscale) Example 33
def fromBlenderMesh(me, vg, expfact):
g = Grid()
g.center = np.asarray(list(tuple(v.co) for v in me.vertices), dtype=np.single )
g.rainmap = None
if vg is not None:
for v in me.vertices:
vg.add([v.index],0.0,'ADD')
g.rainmap=np.asarray(list( (v.co[0], v.co[1], vg.weight(v.index)) for v in me.vertices), dtype=np.single )
g._sort(expfact)
return g Example 34
def _set_spacing(self, spacing):
""" Set the image spacing.
Parameters
----------
spacing: uplet
the image spacing.
"""
self._spacing = numpy.asarray(spacing, dtype=numpy.single) Example 35
def _default_spacing(self):
""" Return the default image spacing.
"""
dim = self._get_ndim()
return numpy.ones(dim, dtype=numpy.single) Example 36
def get_scales(min_scale=0.2, max_scale=0.9,num_layers=6):
""" Following the ssd arxiv paper, regarding the calculation of scales & ratios
Parameters
----------
min_scale : float
max_scales: float
num_layers: int
number of layers that will have a detection head
anchor_ratios: list
first_layer_ratios: list
return
------
sizes : list
list of scale sizes per feature layer
ratios : list
list of anchor_ratios per feature layer
"""
# this code follows the original implementation of wei liu
# for more, look at ssd/score_ssd_pascal.py:310 in the original caffe implementation
min_ratio = int(min_scale * 100)
max_ratio = int(max_scale * 100)
step = int(np.floor((max_ratio - min_ratio) / (num_layers - 2)))
min_sizes = []
max_sizes = []
for ratio in xrange(min_ratio, max_ratio + 1, step):
min_sizes.append(ratio / 100.)
max_sizes.append((ratio + step) / 100.)
min_sizes = [int(100*min_scale / 2.0) / 100.0] + min_sizes
max_sizes = [min_scale] + max_sizes
# convert it back to this implementation's notation:
scales = []
for layer_idx in range(num_layers):
scales.append([min_sizes[layer_idx], np.single(np.sqrt(min_sizes[layer_idx] * max_sizes[layer_idx]))])
return scales Example 37
def test_floats_from_string(self, level=rlevel):
# Ticket #640, floats from string
fsingle = np.single('1.234')
fdouble = np.double('1.234')
flongdouble = np.longdouble('1.234')
assert_almost_equal(fsingle, 1.234)
assert_almost_equal(fdouble, 1.234)
assert_almost_equal(flongdouble, 1.234) Example 38
def test_compress_small_type(self, level=rlevel):
# Ticket #789, changeset 5217.
# compress with out argument segfaulted if cannot cast safely
import numpy as np
a = np.array([[1, 2], [3, 4]])
b = np.zeros((2, 1), dtype=np.single)
try:
a.compress([True, False], axis=1, out=b)
raise AssertionError("compress with an out which cannot be "
"safely casted should not return "
"successfully")
except TypeError:
pass Example 39
def test_trace_subclass(self):
# The class would need to overwrite trace to ensure single-element
# output also has the right subclass.
class MyArray(np.ndarray):
pass
b = np.arange(8).reshape((2, 2, 2)).view(MyArray)
t = b.trace()
assert isinstance(t, MyArray) Example 40
def test_export_record(self):
dt = [('a', 'b'),
('b', 'h'),
('c', 'i'),
('d', 'l'),
('dx', 'q'),
('e', 'B'),
('f', 'H'),
('g', 'I'),
('h', 'L'),
('hx', 'Q'),
('i', np.single),
('j', np.double),
('k', np.longdouble),
('ix', np.csingle),
('jx', np.cdouble),
('kx', np.clongdouble),
('l', 'S4'),
('m', 'U4'),
('n', 'V3'),
('o', '?'),
('p', np.half),
]
x = np.array(
[(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
asbytes('aaaa'), 'bbbb', asbytes(' '), True, 1.0)],
dtype=dt)
y = memoryview(x)
assert_equal(y.shape, (1,))
assert_equal(y.ndim, 1)
assert_equal(y.suboffsets, EMPTY)
sz = sum([np.dtype(b).itemsize for a, b in dt])
if np.dtype('l').itemsize == 4:
assert_equal(y.format, 'T{b:a:=h:b:i:c:l:d:q:dx:B:e:@H:f:=I:g:L:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
else:
assert_equal(y.format, 'T{b:a:=h:b:i:c:q:d:q:dx:B:e:@H:f:=I:g:Q:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}')
# Cannot test if NPY_RELAXED_STRIDES_CHECKING changes the strides
if not (np.ones(1).strides[0] == np.iinfo(np.intp).max):
assert_equal(y.strides, (sz,))
assert_equal(y.itemsize, sz) Example 41
def test_singleton(self):
ftype = finfo(single)
ftype2 = finfo(single)
assert_equal(id(ftype), id(ftype2)) Example 42
def get_real_dtype(dtype):
return {single: single, double: double,
csingle: single, cdouble: double}[dtype] Example 43
def get_complex_dtype(dtype):
return {single: csingle, double: cdouble,
csingle: csingle, cdouble: cdouble}[dtype] Example 44
def get_rtol(dtype):
# Choose a safe rtol
if dtype in (single, csingle):
return 1e-5
else:
return 1e-11 Example 45
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
assert_equal(linalg.solve(x, x).dtype, dtype)
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 46
def test_0_size(self):
class ArraySubclass(np.ndarray):
pass
# Test system of 0x0 matrices
a = np.arange(8).reshape(2, 2, 2)
b = np.arange(6).reshape(1, 2, 3).view(ArraySubclass)
expected = linalg.solve(a, b)[:, 0:0, :]
result = linalg.solve(a[:, 0:0, 0:0], b[:, 0:0, :])
assert_array_equal(result, expected)
assert_(isinstance(result, ArraySubclass))
# Test errors for non-square and only b's dimension being 0
assert_raises(linalg.LinAlgError, linalg.solve, a[:, 0:0, 0:1], b)
assert_raises(ValueError, linalg.solve, a, b[:, 0:0, :])
# Test broadcasting error
b = np.arange(6).reshape(1, 3, 2) # broadcasting error
assert_raises(ValueError, linalg.solve, a, b)
assert_raises(ValueError, linalg.solve, a[0:0], b[0:0])
# Test zero "single equations" with 0x0 matrices.
b = np.arange(2).reshape(1, 2).view(ArraySubclass)
expected = linalg.solve(a, b)[:, 0:0]
result = linalg.solve(a[:, 0:0, 0:0], b[:, 0:0])
assert_array_equal(result, expected)
assert_(isinstance(result, ArraySubclass))
b = np.arange(3).reshape(1, 3)
assert_raises(ValueError, linalg.solve, a, b)
assert_raises(ValueError, linalg.solve, a[0:0], b[0:0])
assert_raises(ValueError, linalg.solve, a[:, 0:0, 0:0], b) Example 47
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
assert_equal(linalg.eigvals(x).dtype, dtype)
x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
assert_equal(linalg.eigvals(x).dtype, get_complex_dtype(dtype))
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 48
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
w, v = np.linalg.eig(x)
assert_equal(w.dtype, dtype)
assert_equal(v.dtype, dtype)
x = np.array([[1, 0.5], [-1, 1]], dtype=dtype)
w, v = np.linalg.eig(x)
assert_equal(w.dtype, get_complex_dtype(dtype))
assert_equal(v.dtype, get_complex_dtype(dtype))
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 49
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
u, s, vh = linalg.svd(x)
assert_equal(u.dtype, dtype)
assert_equal(s.dtype, get_real_dtype(dtype))
assert_equal(vh.dtype, dtype)
s = linalg.svd(x, compute_uv=False)
assert_equal(s.dtype, get_real_dtype(dtype))
for dtype in [single, double, csingle, cdouble]:
yield check, dtype Example 50
def test_types(self):
def check(dtype):
x = np.array([[1, 0.5], [0.5, 1]], dtype=dtype)
assert_equal(np.linalg.det(x).dtype, dtype)
ph, s = np.linalg.slogdet(x)
assert_equal(s.dtype, get_real_dtype(dtype))
assert_equal(ph.dtype, dtype)
for dtype in [single, double, csingle, cdouble]:
yield check, dtype 