/opt/imh-python/lib/python3.9/site-packages/numpy/ma
Edit: /opt/imh-python/lib/python3.9/site-packages/numpy/ma/timer_comparison.py (15658B)
import timeit
from functools import reduce
import numpy as np
from numpy import float_
import numpy.core.fromnumeric as fromnumeric
from numpy.testing import build_err_msg
pi = np.pi
class ModuleTester:
def __init__(self, module):
self.module = module
self.allequal = module.allequal
self.arange = module.arange
self.array = module.array
self.concatenate = module.concatenate
self.count = module.count
self.equal = module.equal
self.filled = module.filled
self.getmask = module.getmask
self.getmaskarray = module.getmaskarray
self.id = id
self.inner = module.inner
self.make_mask = module.make_mask
self.masked = module.masked
self.masked_array = module.masked_array
self.masked_values = module.masked_values
self.mask_or = module.mask_or
self.nomask = module.nomask
self.ones = module.ones
self.outer = module.outer
self.repeat = module.repeat
self.resize = module.resize
self.sort = module.sort
self.take = module.take
self.transpose = module.transpose
self.zeros = module.zeros
self.MaskType = module.MaskType
try:
self.umath = module.umath
except AttributeError:
self.umath = module.core.umath
self.testnames = []
def assert_array_compare(self, comparison, x, y, err_msg='', header='',
fill_value=True):
"""
Assert that a comparison of two masked arrays is satisfied elementwise.
"""
xf = self.filled(x)
yf = self.filled(y)
m = self.mask_or(self.getmask(x), self.getmask(y))
x = self.filled(self.masked_array(xf, mask=m), fill_value)
y = self.filled(self.masked_array(yf, mask=m), fill_value)
if (x.dtype.char != "O"):
x = x.astype(float_)
if isinstance(x, np.ndarray) and x.size > 1:
x[np.isnan(x)] = 0
elif np.isnan(x):
x = 0
if (y.dtype.char != "O"):
y = y.astype(float_)
if isinstance(y, np.ndarray) and y.size > 1:
y[np.isnan(y)] = 0
elif np.isnan(y):
y = 0
try:
cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
if not cond:
msg = build_err_msg([x, y],
err_msg
+ f'\n(shapes {x.shape}, {y.shape} mismatch)',
header=header,
names=('x', 'y'))
assert cond, msg
val = comparison(x, y)
if m is not self.nomask and fill_value:
val = self.masked_array(val, mask=m)
if isinstance(val, bool):
cond = val
reduced = [0]
else:
reduced = val.ravel()
cond = reduced.all()
reduced = reduced.tolist()
if not cond:
match = 100-100.0*reduced.count(1)/len(reduced)
msg = build_err_msg([x, y],
err_msg
+ '\n(mismatch %s%%)' % (match,),
header=header,
names=('x', 'y'))
assert cond, msg
except ValueError as e:
msg = build_err_msg([x, y], err_msg, header=header, names=('x', 'y'))
raise ValueError(msg) from e
def assert_array_equal(self, x, y, err_msg=''):
"""
Checks the elementwise equality of two masked arrays.
"""
self.assert_array_compare(self.equal, x, y, err_msg=err_msg,
header='Arrays are not equal')
@np.errstate(all='ignore')
def test_0(self):
"""
Tests creation
"""
x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
m = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
xm = self.masked_array(x, mask=m)
xm[0]
@np.errstate(all='ignore')
def test_1(self):
"""
Tests creation
"""
x = np.array([1., 1., 1., -2., pi/2.0, 4., 5., -10., 10., 1., 2., 3.])
y = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.])
m1 = [1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
m2 = [0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 1]
xm = self.masked_array(x, mask=m1)
ym = self.masked_array(y, mask=m2)
xf = np.where(m1, 1.e+20, x)
xm.set_fill_value(1.e+20)
assert((xm-ym).filled(0).any())
s = x.shape
assert(xm.size == reduce(lambda x, y:x*y, s))
assert(self.count(xm) == len(m1) - reduce(lambda x, y:x+y, m1))
for s in [(4, 3), (6, 2)]:
x.shape = s
y.shape = s
xm.shape = s
ym.shape = s
xf.shape = s
assert(self.count(xm) == len(m1) - reduce(lambda x, y:x+y, m1))
@np.errstate(all='ignore')
def test_2(self):
"""
Tests conversions and indexing.
"""
x1 = np.array([1, 2, 4, 3])
x2 = self.array(x1, mask=[1, 0, 0, 0])
x3 = self.array(x1, mask=[0, 1, 0, 1])
x4 = self.array(x1)
# test conversion to strings, no errors
str(x2)
repr(x2)
# tests of indexing
assert type(x2[1]) is type(x1[1])
assert x1[1] == x2[1]
x1[2] = 9
x2[2] = 9
self.assert_array_equal(x1, x2)
x1[1:3] = 99
x2[1:3] = 99
x2[1] = self.masked
x2[1:3] = self.masked
x2[:] = x1
x2[1] = self.masked
x3[:] = self.masked_array([1, 2, 3, 4], [0, 1, 1, 0])
x4[:] = self.masked_array([1, 2, 3, 4], [0, 1, 1, 0])
x1 = np.arange(5)*1.0
x2 = self.masked_values(x1, 3.0)
x1 = self.array([1, 'hello', 2, 3], object)
x2 = np.array([1, 'hello', 2, 3], object)
# check that no error occurs.
x1[1]
x2[1]
assert x1[1:1].shape == (0,)
# Tests copy-size
n = [0, 0, 1, 0, 0]
m = self.make_mask(n)
m2 = self.make_mask(m)
assert(m is m2)
m3 = self.make_mask(m, copy=1)
assert(m is not m3)
@np.errstate(all='ignore')
def test_3(self):
"""
Tests resize/repeat
"""
x4 = self.arange(4)
x4[2] = self.masked
y4 = self.resize(x4, (8,))
assert self.allequal(self.concatenate([x4, x4]), y4)
assert self.allequal(self.getmask(y4), [0, 0, 1, 0, 0, 0, 1, 0])
y5 = self.repeat(x4, (2, 2, 2, 2), axis=0)
self.assert_array_equal(y5, [0, 0, 1, 1, 2, 2, 3, 3])
y6 = self.repeat(x4, 2, axis=0)
assert self.allequal(y5, y6)
y7 = x4.repeat((2, 2, 2, 2), axis=0)
assert self.allequal(y5, y7)
y8 = x4.repeat(2, 0)
assert self.allequal(y5, y8)
@np.errstate(all='ignore')
def test_4(self):
"""
Test of take, transpose, inner, outer products.
"""
x = self.arange(24)
y = np.arange(24)
x[5:6] = self.masked
x = x.reshape(2, 3, 4)
y = y.reshape(2, 3, 4)
assert self.allequal(np.transpose(y, (2, 0, 1)), self.transpose(x, (2, 0, 1)))
assert self.allequal(np.take(y, (2, 0, 1), 1), self.take(x, (2, 0, 1), 1))
assert self.allequal(np.inner(self.filled(x, 0), self.filled(y, 0)),
self.inner(x, y))
assert self.allequal(np.outer(self.filled(x, 0), self.filled(y, 0)),
self.outer(x, y))
y = self.array(['abc', 1, 'def', 2, 3], object)
y[2] = self.masked
t = self.take(y, [0, 3, 4])
assert t[0] == 'abc'
assert t[1] == 2
assert t[2] == 3
@np.errstate(all='ignore')
def test_5(self):
"""
Tests inplace w/ scalar
"""
x = self.arange(10)
y = self.arange(10)
xm = self.arange(10)
xm[2] = self.masked
x += 1
assert self.allequal(x, y+1)
xm += 1
assert self.allequal(xm, y+1)
x = self.arange(10)
xm = self.arange(10)
xm[2] = self.masked
x -= 1
assert self.allequal(x, y-1)
xm -= 1
assert self.allequal(xm, y-1)
x = self.arange(10)*1.0
xm = self.arange(10)*1.0
xm[2] = self.masked
x *= 2.0
assert self.allequal(x, y*2)
xm *= 2.0
assert self.allequal(xm, y*2)
x = self.arange(10)*2
xm = self.arange(10)*2
xm[2] = self.masked
x /= 2
assert self.allequal(x, y)
xm /= 2
assert self.allequal(xm, y)
x = self.arange(10)*1.0
xm = self.arange(10)*1.0
xm[2] = self.masked
x /= 2.0
assert self.allequal(x, y/2.0)
xm /= self.arange(10)
self.assert_array_equal(xm, self.ones((10,)))
x = self.arange(10).astype(float_)
xm = self.arange(10)
xm[2] = self.masked
x += 1.
assert self.allequal(x, y + 1.)
@np.errstate(all='ignore')
def test_6(self):
"""
Tests inplace w/ array
"""
x = self.arange(10, dtype=float_)
y = self.arange(10)
xm = self.arange(10, dtype=float_)
xm[2] = self.masked
m = xm.mask
a = self.arange(10, dtype=float_)
a[-1] = self.masked
x += a
xm += a
assert self.allequal(x, y+a)
assert self.allequal(xm, y+a)
assert self.allequal(xm.mask, self.mask_or(m, a.mask))
x = self.arange(10, dtype=float_)
xm = self.arange(10, dtype=float_)
xm[2] = self.masked
m = xm.mask
a = self.arange(10, dtype=float_)
a[-1] = self.masked
x -= a
xm -= a
assert self.allequal(x, y-a)
assert self.allequal(xm, y-a)
assert self.allequal(xm.mask, self.mask_or(m, a.mask))
x = self.arange(10, dtype=float_)
xm = self.arange(10, dtype=float_)
xm[2] = self.masked
m = xm.mask
a = self.arange(10, dtype=float_)
a[-1] = self.masked
x *= a
xm *= a
assert self.allequal(x, y*a)
assert self.allequal(xm, y*a)
assert self.allequal(xm.mask, self.mask_or(m, a.mask))
x = self.arange(10, dtype=float_)
xm = self.arange(10, dtype=float_)
xm[2] = self.masked
m = xm.mask
a = self.arange(10, dtype=float_)
a[-1] = self.masked
x /= a
xm /= a
@np.errstate(all='ignore')
def test_7(self):
"Tests ufunc"
d = (self.array([1.0, 0, -1, pi/2]*2, mask=[0, 1]+[0]*6),
self.array([1.0, 0, -1, pi/2]*2, mask=[1, 0]+[0]*6),)
for f in ['sqrt', 'log', 'log10', 'exp', 'conjugate',
# 'sin', 'cos', 'tan',
# 'arcsin', 'arccos', 'arctan',
# 'sinh', 'cosh', 'tanh',
# 'arcsinh',
# 'arccosh',
# 'arctanh',
# 'absolute', 'fabs', 'negative',
# # 'nonzero', 'around',
# 'floor', 'ceil',
# # 'sometrue', 'alltrue',
# 'logical_not',
# 'add', 'subtract', 'multiply',
# 'divide', 'true_divide', 'floor_divide',
# 'remainder', 'fmod', 'hypot', 'arctan2',
# 'equal', 'not_equal', 'less_equal', 'greater_equal',
# 'less', 'greater',
# 'logical_and', 'logical_or', 'logical_xor',
]:
try:
uf = getattr(self.umath, f)
except AttributeError:
uf = getattr(fromnumeric, f)
mf = getattr(self.module, f)
args = d[:uf.nin]
ur = uf(*args)
mr = mf(*args)
self.assert_array_equal(ur.filled(0), mr.filled(0), f)
self.assert_array_equal(ur._mask, mr._mask)
@np.errstate(all='ignore')
def test_99(self):
# test average
ott = self.array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
self.assert_array_equal(2.0, self.average(ott, axis=0))
self.assert_array_equal(2.0, self.average(ott, weights=[1., 1., 2., 1.]))
result, wts = self.average(ott, weights=[1., 1., 2., 1.], returned=1)
self.assert_array_equal(2.0, result)
assert(wts == 4.0)
ott[:] = self.masked
assert(self.average(ott, axis=0) is self.masked)
ott = self.array([0., 1., 2., 3.], mask=[1, 0, 0, 0])
ott = ott.reshape(2, 2)
ott[:, 1] = self.masked
self.assert_array_equal(self.average(ott, axis=0), [2.0, 0.0])
assert(self.average(ott, axis=1)[0] is self.masked)
self.assert_array_equal([2., 0.], self.average(ott, axis=0))
result, wts = self.average(ott, axis=0, returned=1)
self.assert_array_equal(wts, [1., 0.])
w1 = [0, 1, 1, 1, 1, 0]
w2 = [[0, 1, 1, 1, 1, 0], [1, 0, 0, 0, 0, 1]]
x = self.arange(6)
self.assert_array_equal(self.average(x, axis=0), 2.5)
self.assert_array_equal(self.average(x, axis=0, weights=w1), 2.5)
y = self.array([self.arange(6), 2.0*self.arange(6)])
self.assert_array_equal(self.average(y, None), np.add.reduce(np.arange(6))*3./12.)
self.assert_array_equal(self.average(y, axis=0), np.arange(6) * 3./2.)
self.assert_array_equal(self.average(y, axis=1), [self.average(x, axis=0), self.average(x, axis=0) * 2.0])
self.assert_array_equal(self.average(y, None, weights=w2), 20./6.)
self.assert_array_equal(self.average(y, axis=0, weights=w2), [0., 1., 2., 3., 4., 10.])
self.assert_array_equal(self.average(y, axis=1), [self.average(x, axis=0), self.average(x, axis=0) * 2.0])
m1 = self.zeros(6)
m2 = [0, 0, 1, 1, 0, 0]
m3 = [[0, 0, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0]]
m4 = self.ones(6)
m5 = [0, 1, 1, 1, 1, 1]
self.assert_array_equal(self.average(self.masked_array(x, m1), axis=0), 2.5)
self.assert_array_equal(self.average(self.masked_array(x, m2), axis=0), 2.5)
self.assert_array_equal(self.average(self.masked_array(x, m5), axis=0), 0.0)
self.assert_array_equal(self.count(self.average(self.masked_array(x, m4), axis=0)), 0)
z = self.masked_array(y, m3)
self.assert_array_equal(self.average(z, None), 20./6.)
self.assert_array_equal(self.average(z, axis=0), [0., 1., 99., 99., 4.0, 7.5])
self.assert_array_equal(self.average(z, axis=1), [2.5, 5.0])
self.assert_array_equal(self.average(z, axis=0, weights=w2), [0., 1., 99., 99., 4.0, 10.0])
@np.errstate(all='ignore')
def test_A(self):
x = self.arange(24)
x[5:6] = self.masked
x = x.reshape(2, 3, 4)
if __name__ == '__main__':
setup_base = ("from __main__ import ModuleTester \n"
"import numpy\n"
"tester = ModuleTester(module)\n")
setup_cur = "import numpy.ma.core as module\n" + setup_base
(nrepeat, nloop) = (10, 10)
for i in range(1, 8):
func = 'tester.test_%i()' % i
cur = timeit.Timer(func, setup_cur).repeat(nrepeat, nloop*10)
cur = np.sort(cur)
print("#%i" % i + 50*'.')
print(eval("ModuleTester.test_%i.__doc__" % i))
print(f'core_current : {cur[0]:.3f} - {cur[1]:.3f}')