本文整理汇总了Python中numpy.ma.masked方法的典型用法代码示例。如果您正苦于以下问题:Python ma.masked方法的具体用法?Python ma.masked怎么用?Python ma.masked使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类numpy.ma
的用法示例。
在下文中一共展示了ma.masked方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_exotic_formats
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def test_exotic_formats(self):
# Test that 'exotic' formats are processed properly
easy = mrecarray(1, dtype=[('i', int), ('s', '|S8'), ('f', float)])
easy[0] = masked
assert_equal(easy.filled(1).item(), (1, asbytes('1'), 1.))
solo = mrecarray(1, dtype=[('f0', '<f8', (2, 2))])
solo[0] = masked
assert_equal(solo.filled(1).item(),
np.array((1,), dtype=solo.dtype).item())
mult = mrecarray(2, dtype="i4, (2,3)float, float")
mult[0] = masked
mult[1] = (1, 1, 1)
mult.filled(0)
assert_equal_records(mult.filled(0),
np.array([(0, 0, 0), (1, 1, 1)],
dtype=mult.dtype))
示例2: test_set_mask
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def test_set_mask(self):
base = self.base.copy()
mbase = base.view(mrecarray)
# Set the mask to True .......................
mbase.mask = masked
assert_equal(ma.getmaskarray(mbase['b']), [1]*5)
assert_equal(mbase['a']._mask, mbase['b']._mask)
assert_equal(mbase['a']._mask, mbase['c']._mask)
assert_equal(mbase._mask.tolist(),
np.array([(1, 1, 1)]*5, dtype=bool))
# Delete the mask ............................
mbase.mask = nomask
assert_equal(ma.getmaskarray(mbase['c']), [0]*5)
assert_equal(mbase._mask.tolist(),
np.array([(0, 0, 0)]*5, dtype=bool))
#
示例3: _parse_args
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def _parse_args(*args):
X, Y, U, V, C = [None] * 5
args = list(args)
# The use of atleast_1d allows for handling scalar arguments while also
# keeping masked arrays
if len(args) == 3 or len(args) == 5:
C = np.atleast_1d(args.pop(-1))
V = np.atleast_1d(args.pop(-1))
U = np.atleast_1d(args.pop(-1))
if U.ndim == 1:
nr, nc = 1, U.shape[0]
else:
nr, nc = U.shape
if len(args) == 2: # remaining after removing U,V,C
X, Y = [np.array(a).ravel() for a in args]
if len(X) == nc and len(Y) == nr:
X, Y = [a.ravel() for a in np.meshgrid(X, Y)]
else:
indexgrid = np.meshgrid(np.arange(nc), np.arange(nr))
X, Y = [np.ravel(a) for a in indexgrid]
return X, Y, U, V, C
示例4: trim
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def trim(a, limits=None, inclusive=(True,True), relative=False, axis=None):
"""
Trims an array by masking the data outside some given limits.
Returns a masked version of the input array.
%s
Examples
--------
>>> z = [ 1, 2, 3, 4, 5, 6, 7, 8, 9,10]
>>> trim(z,(3,8))
[--,--, 3, 4, 5, 6, 7, 8,--,--]
>>> trim(z,(0.1,0.2),relative=True)
[--, 2, 3, 4, 5, 6, 7, 8,--,--]
"""
if relative:
return trimr(a, limits=limits, inclusive=inclusive, axis=axis)
else:
return trima(a, limits=limits, inclusive=inclusive)
示例5: kurtosis
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def kurtosis(a, axis=0, fisher=True, bias=True):
a, axis = _chk_asarray(a, axis)
m2 = moment(a,2,axis)
m4 = moment(a,4,axis)
olderr = np.seterr(all='ignore')
try:
vals = ma.where(m2 == 0, 0, m4 / m2**2.0)
finally:
np.seterr(**olderr)
if not bias:
n = a.count(axis)
can_correct = (n > 3) & (m2 is not ma.masked and m2 > 0)
if can_correct.any():
n = np.extract(can_correct, n)
m2 = np.extract(can_correct, m2)
m4 = np.extract(can_correct, m4)
nval = 1.0/(n-2)/(n-3)*((n*n-1.0)*m4/m2**2.0-3*(n-1)**2.0)
np.place(vals, can_correct, nval+3.0)
if fisher:
return vals - 3
else:
return vals
示例6: test_get
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def test_get(self):
# Tests fields retrieval
base = self.base.copy()
mbase = base.view(mrecarray)
# As fields..........
for field in ('a', 'b', 'c'):
assert_equal(getattr(mbase, field), mbase[field])
assert_equal(base[field], mbase[field])
# as elements .......
mbase_first = mbase[0]
assert_(isinstance(mbase_first, mrecarray))
assert_equal(mbase_first.dtype, mbase.dtype)
assert_equal(mbase_first.tolist(), (1, 1.1, b'one'))
# Used to be mask, now it's recordmask
assert_equal(mbase_first.recordmask, nomask)
assert_equal(mbase_first._mask.item(), (False, False, False))
assert_equal(mbase_first['a'], mbase['a'][0])
mbase_last = mbase[-1]
assert_(isinstance(mbase_last, mrecarray))
assert_equal(mbase_last.dtype, mbase.dtype)
assert_equal(mbase_last.tolist(), (None, None, None))
# Used to be mask, now it's recordmask
assert_equal(mbase_last.recordmask, True)
assert_equal(mbase_last._mask.item(), (True, True, True))
assert_equal(mbase_last['a'], mbase['a'][-1])
assert_((mbase_last['a'] is masked))
# as slice ..........
mbase_sl = mbase[:2]
assert_(isinstance(mbase_sl, mrecarray))
assert_equal(mbase_sl.dtype, mbase.dtype)
# Used to be mask, now it's recordmask
assert_equal(mbase_sl.recordmask, [0, 1])
assert_equal_records(mbase_sl.mask,
np.array([(False, False, False),
(True, True, True)],
dtype=mbase._mask.dtype))
assert_equal_records(mbase_sl, base[:2].view(mrecarray))
for field in ('a', 'b', 'c'):
assert_equal(getattr(mbase_sl, field), base[:2][field])
示例7: test_set_fields_mask
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def test_set_fields_mask(self):
# Tests setting the mask of a field.
base = self.base.copy()
# This one has already a mask....
mbase = base.view(mrecarray)
mbase['a'][-2] = masked
assert_equal(mbase.a, [1, 2, 3, 4, 5])
assert_equal(mbase.a._mask, [0, 1, 0, 1, 1])
# This one has not yet
mbase = fromarrays([np.arange(5), np.random.rand(5)],
dtype=[('a', int), ('b', float)])
mbase['a'][-2] = masked
assert_equal(mbase.a, [0, 1, 2, 3, 4])
assert_equal(mbase.a._mask, [0, 0, 0, 1, 0])
示例8: test_set_mask
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def test_set_mask(self):
base = self.base.copy()
mbase = base.view(mrecarray)
# Set the mask to True .......................
mbase.mask = masked
assert_equal(ma.getmaskarray(mbase['b']), [1]*5)
assert_equal(mbase['a']._mask, mbase['b']._mask)
assert_equal(mbase['a']._mask, mbase['c']._mask)
assert_equal(mbase._mask.tolist(),
np.array([(1, 1, 1)]*5, dtype=bool))
# Delete the mask ............................
mbase.mask = nomask
assert_equal(ma.getmaskarray(mbase['c']), [0]*5)
assert_equal(mbase._mask.tolist(),
np.array([(0, 0, 0)]*5, dtype=bool))
示例9: test_set_elements
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def test_set_elements(self):
base = self.base.copy()
# Set an element to mask .....................
mbase = base.view(mrecarray).copy()
mbase[-2] = masked
assert_equal(
mbase._mask.tolist(),
np.array([(0, 0, 0), (1, 1, 1), (0, 0, 0), (1, 1, 1), (1, 1, 1)],
dtype=bool))
# Used to be mask, now it's recordmask!
assert_equal(mbase.recordmask, [0, 1, 0, 1, 1])
# Set slices .................................
mbase = base.view(mrecarray).copy()
mbase[:2] = (5, 5, 5)
assert_equal(mbase.a._data, [5, 5, 3, 4, 5])
assert_equal(mbase.a._mask, [0, 0, 0, 0, 1])
assert_equal(mbase.b._data, [5., 5., 3.3, 4.4, 5.5])
assert_equal(mbase.b._mask, [0, 0, 0, 0, 1])
assert_equal(mbase.c._data,
[b'5', b'5', b'three', b'four', b'five'])
assert_equal(mbase.b._mask, [0, 0, 0, 0, 1])
mbase = base.view(mrecarray).copy()
mbase[:2] = masked
assert_equal(mbase.a._data, [1, 2, 3, 4, 5])
assert_equal(mbase.a._mask, [1, 1, 0, 0, 1])
assert_equal(mbase.b._data, [1.1, 2.2, 3.3, 4.4, 5.5])
assert_equal(mbase.b._mask, [1, 1, 0, 0, 1])
assert_equal(mbase.c._data,
[b'one', b'two', b'three', b'four', b'five'])
assert_equal(mbase.b._mask, [1, 1, 0, 0, 1])
示例10: test_view_simple_dtype
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def test_view_simple_dtype(self):
(mrec, a, b, arr) = self.data
ntype = (float, 2)
test = mrec.view(ntype)
assert_(isinstance(test, ma.MaskedArray))
assert_equal(test, np.array(list(zip(a, b)), dtype=float))
assert_(test[3, 1] is ma.masked)
示例11: test_view_flexible_type
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def test_view_flexible_type(self):
(mrec, a, b, arr) = self.data
alttype = [('A', float), ('B', float)]
test = mrec.view(alttype)
assert_(isinstance(test, MaskedRecords))
assert_equal_records(test, arr.view(alttype))
assert_(test['B'][3] is masked)
assert_equal(test.dtype, np.dtype(alttype))
assert_(test._fill_value is None)
##############################################################################
示例12: _chk_asarray
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def _chk_asarray(a, axis):
# Always returns a masked array, raveled for axis=None
a = ma.asanyarray(a)
if axis is None:
a = ma.ravel(a)
outaxis = 0
else:
outaxis = axis
return a, outaxis
示例13: argstoarray
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def argstoarray(*args):
"""
Constructs a 2D array from a group of sequences.
Sequences are filled with missing values to match the length of the longest
sequence.
Parameters
----------
args : sequences
Group of sequences.
Returns
-------
argstoarray : MaskedArray
A ( `m` x `n` ) masked array, where `m` is the number of arguments and
`n` the length of the longest argument.
Notes
-----
`numpy.ma.row_stack` has identical behavior, but is called with a sequence
of sequences.
"""
if len(args) == 1 and not isinstance(args[0], ndarray):
output = ma.asarray(args[0])
if output.ndim != 2:
raise ValueError("The input should be 2D")
else:
n = len(args)
m = max([len(k) for k in args])
output = ma.array(np.empty((n,m), dtype=float), mask=True)
for (k,v) in enumerate(args):
output[k,:len(v)] = v
output[np.logical_not(np.isfinite(output._data))] = masked
return output
示例14: msign
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def msign(x):
"""Returns the sign of x, or 0 if x is masked."""
return ma.filled(np.sign(x), 0)
示例15: linregress
# 需要导入模块: from numpy import ma [as 别名]
# 或者: from numpy.ma import masked [as 别名]
def linregress(x, y=None):
"""
Linear regression calculation
Note that the non-masked version is used, and that this docstring is
replaced by the non-masked docstring + some info on missing data.
"""
if y is None:
x = ma.array(x)
if x.shape[0] == 2:
x, y = x
elif x.shape[1] == 2:
x, y = x.T
else:
msg = ("If only `x` is given as input, it has to be of shape "
"(2, N) or (N, 2), provided shape was %s" % str(x.shape))
raise ValueError(msg)
else:
x = ma.array(x)
y = ma.array(y)
x = x.flatten()
y = y.flatten()
m = ma.mask_or(ma.getmask(x), ma.getmask(y), shrink=False)
if m is not nomask:
x = ma.array(x, mask=m)
y = ma.array(y, mask=m)
if np.any(~m):
slope, intercept, r, prob, sterrest = stats_linregress(x.data[~m],
y.data[~m])
else:
# All data is masked
return None, None, None, None, None
else:
slope, intercept, r, prob, sterrest = stats_linregress(x.data, y.data)
return LinregressResult(slope, intercept, r, prob, sterrest)