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numpy.ma.dstack ma.dstack(*args, **kwargs) = <numpy.ma.extras._fromnxfunction_seq object>
Stack arrays in sequence depth wise (along third axis). This is equivalent to concatenation along the third axis after 2-D arrays of shape (M,N) have been reshaped to (M,N,1) and 1-D arrays of shape (N,) have been reshaped to ... | numpy.reference.generated.numpy.ma.dstack |
numpy.ma.ediff1d ma.ediff1d(arr, to_end=None, to_begin=None)[source]
Compute the differences between consecutive elements of an array. This function is the equivalent of numpy.ediff1d that takes masked values into account, see numpy.ediff1d for details. See also numpy.ediff1d
Equivalent function for ndarrays. | numpy.reference.generated.numpy.ma.ediff1d |
numpy.ma.empty ma.empty(shape, dtype=float, order='C', *, like=None) = <numpy.ma.core._convert2ma object>
Return a new array of given shape and type, without initializing entries. Parameters
shapeint or tuple of int
Shape of the empty array, e.g., (2, 3) or 2.
dtypedata-type, optional
Desired output data-... | numpy.reference.generated.numpy.ma.empty |
numpy.ma.empty_like ma.empty_like(prototype, dtype=None, order='K', subok=True, shape=None) = <numpy.ma.core._convert2ma object>
Return a new array with the same shape and type as a given array. Parameters
prototypearray_like
The shape and data-type of prototype define these same attributes of the returned ar... | numpy.reference.generated.numpy.ma.empty_like |
numpy.ma.expand_dims ma.expand_dims(a, axis)[source]
Expand the shape of an array. Insert a new axis that will appear at the axis position in the expanded array shape. Parameters
aarray_like
Input array.
axisint or tuple of ints
Position in the expanded axes where the new axis (or axes) is placed. Deprec... | numpy.reference.generated.numpy.ma.expand_dims |
numpy.ma.filled ma.filled(a, fill_value=None)[source]
Return input as an array with masked data replaced by a fill value. If a is not a MaskedArray, a itself is returned. If a is a MaskedArray and fill_value is None, fill_value is set to a.fill_value. Parameters
aMaskedArray or array_like
An input object.
f... | numpy.reference.generated.numpy.ma.filled |
numpy.ma.fix_invalid ma.fix_invalid(a, mask=False, copy=True, fill_value=None)[source]
Return input with invalid data masked and replaced by a fill value. Invalid data means values of nan, inf, etc. Parameters
aarray_like
Input array, a (subclass of) ndarray.
masksequence, optional
Mask. Must be convertib... | numpy.reference.generated.numpy.ma.fix_invalid |
numpy.ma.flatnotmasked_contiguous ma.flatnotmasked_contiguous(a)[source]
Find contiguous unmasked data in a masked array along the given axis. Parameters
anarray
The input array. Returns
slice_listlist
A sorted sequence of slice objects (start index, end index). Changed in version 1.15.0: Now returns... | numpy.reference.generated.numpy.ma.flatnotmasked_contiguous |
numpy.ma.flatnotmasked_edges ma.flatnotmasked_edges(a)[source]
Find the indices of the first and last unmasked values. Expects a 1-D MaskedArray, returns None if all values are masked. Parameters
aarray_like
Input 1-D MaskedArray Returns
edgesndarray or None
The indices of first and last non-masked va... | numpy.reference.generated.numpy.ma.flatnotmasked_edges |
numpy.ma.frombuffer ma.frombuffer(buffer, dtype=float, count=- 1, offset=0, *, like=None) = <numpy.ma.core._convert2ma object>
Interpret a buffer as a 1-dimensional array. Parameters
bufferbuffer_like
An object that exposes the buffer interface.
dtypedata-type, optional
Data-type of the returned array; de... | numpy.reference.generated.numpy.ma.frombuffer |
numpy.ma.fromfunction ma.fromfunction(function, shape, **dtype) = <numpy.ma.core._convert2ma object>
Construct an array by executing a function over each coordinate. The resulting array therefore has a value fn(x, y, z) at coordinate (x, y, z). Parameters
functioncallable
The function is called with N paramet... | numpy.reference.generated.numpy.ma.fromfunction |
numpy.ma.getdata ma.getdata(a, subok=True)[source]
Return the data of a masked array as an ndarray. Return the data of a (if any) as an ndarray if a is a MaskedArray, else return a as a ndarray or subclass (depending on subok) if not. Parameters
aarray_like
Input MaskedArray, alternatively a ndarray or a subc... | numpy.reference.generated.numpy.ma.getdata |
numpy.ma.getmask ma.getmask(a)[source]
Return the mask of a masked array, or nomask. Return the mask of a as an ndarray if a is a MaskedArray and the mask is not nomask, else return nomask. To guarantee a full array of booleans of the same shape as a, use getmaskarray. Parameters
aarray_like
Input MaskedArray... | numpy.reference.generated.numpy.ma.getmask |
numpy.ma.getmaskarray ma.getmaskarray(arr)[source]
Return the mask of a masked array, or full boolean array of False. Return the mask of arr as an ndarray if arr is a MaskedArray and the mask is not nomask, else return a full boolean array of False of the same shape as arr. Parameters
arrarray_like
Input Mask... | numpy.reference.generated.numpy.ma.getmaskarray |
numpy.ma.harden_mask ma.harden_mask(self) = <numpy.ma.core._frommethod object>
Force the mask to hard. Whether the mask of a masked array is hard or soft is determined by its hardmask property. harden_mask sets hardmask to True. See also ma.MaskedArray.hardmask | numpy.reference.generated.numpy.ma.harden_mask |
numpy.ma.hsplit ma.hsplit(*args, **kwargs) = <numpy.ma.extras._fromnxfunction_single object>
Split an array into multiple sub-arrays horizontally (column-wise). Please refer to the split documentation. hsplit is equivalent to split with axis=1, the array is always split along the second axis regardless of the array... | numpy.reference.generated.numpy.ma.hsplit |
numpy.ma.hstack ma.hstack(*args, **kwargs) = <numpy.ma.extras._fromnxfunction_seq object>
Stack arrays in sequence horizontally (column wise). This is equivalent to concatenation along the second axis, except for 1-D arrays where it concatenates along the first axis. Rebuilds arrays divided by hsplit. This function... | numpy.reference.generated.numpy.ma.hstack |
numpy.ma.identity ma.identity(n, dtype=None) = <numpy.ma.core._convert2ma object>
Return the identity array. The identity array is a square array with ones on the main diagonal. Parameters
nint
Number of rows (and columns) in n x n output.
dtypedata-type, optional
Data-type of the output. Defaults to floa... | numpy.reference.generated.numpy.ma.identity |
numpy.ma.indices ma.indices(dimensions, dtype=<class 'int'>, sparse=False) = <numpy.ma.core._convert2ma object>
Return an array representing the indices of a grid. Compute an array where the subarrays contain index values 0, 1, … varying only along the corresponding axis. Parameters
dimensionssequence of ints
... | numpy.reference.generated.numpy.ma.indices |
numpy.ma.inner ma.inner(a, b, /)[source]
Inner product of two arrays. Ordinary inner product of vectors for 1-D arrays (without complex conjugation), in higher dimensions a sum product over the last axes. Parameters
a, barray_like
If a and b are nonscalar, their last dimensions must match. Returns
outnd... | numpy.reference.generated.numpy.ma.inner |
numpy.ma.innerproduct ma.innerproduct(a, b, /)[source]
Inner product of two arrays. Ordinary inner product of vectors for 1-D arrays (without complex conjugation), in higher dimensions a sum product over the last axes. Parameters
a, barray_like
If a and b are nonscalar, their last dimensions must match. Re... | numpy.reference.generated.numpy.ma.innerproduct |
numpy.ma.is_mask ma.is_mask(m)[source]
Return True if m is a valid, standard mask. This function does not check the contents of the input, only that the type is MaskType. In particular, this function returns False if the mask has a flexible dtype. Parameters
marray_like
Array to test. Returns
resultbool... | numpy.reference.generated.numpy.ma.is_mask |
numpy.ma.is_masked ma.is_masked(x)[source]
Determine whether input has masked values. Accepts any object as input, but always returns False unless the input is a MaskedArray containing masked values. Parameters
xarray_like
Array to check for masked values. Returns
resultbool
True if x is a MaskedArray... | numpy.reference.generated.numpy.ma.is_masked |
numpy.ma.isarray ma.isarray(x)[source]
Test whether input is an instance of MaskedArray. This function returns True if x is an instance of MaskedArray and returns False otherwise. Any object is accepted as input. Parameters
xobject
Object to test. Returns
resultbool
True if x is a MaskedArray. Se... | numpy.reference.generated.numpy.ma.isarray |
numpy.ma.isMA ma.isMA(x)[source]
Test whether input is an instance of MaskedArray. This function returns True if x is an instance of MaskedArray and returns False otherwise. Any object is accepted as input. Parameters
xobject
Object to test. Returns
resultbool
True if x is a MaskedArray. See also... | numpy.reference.generated.numpy.ma.isma |
numpy.ma.isMaskedArray ma.isMaskedArray(x)[source]
Test whether input is an instance of MaskedArray. This function returns True if x is an instance of MaskedArray and returns False otherwise. Any object is accepted as input. Parameters
xobject
Object to test. Returns
resultbool
True if x is a MaskedAr... | numpy.reference.generated.numpy.ma.ismaskedarray |
numpy.ma.make_mask ma.make_mask(m, copy=False, shrink=True, dtype=<class 'numpy.bool_'>)[source]
Create a boolean mask from an array. Return m as a boolean mask, creating a copy if necessary or requested. The function can accept any sequence that is convertible to integers, or nomask. Does not require that contents... | numpy.reference.generated.numpy.ma.make_mask |
numpy.ma.make_mask_descr ma.make_mask_descr(ndtype)[source]
Construct a dtype description list from a given dtype. Returns a new dtype object, with the type of all fields in ndtype to a boolean type. Field names are not altered. Parameters
ndtypedtype
The dtype to convert. Returns
resultdtype
A dtype ... | numpy.reference.generated.numpy.ma.make_mask_descr |
numpy.ma.make_mask_none ma.make_mask_none(newshape, dtype=None)[source]
Return a boolean mask of the given shape, filled with False. This function returns a boolean ndarray with all entries False, that can be used in common mask manipulations. If a complex dtype is specified, the type of each field is converted to ... | numpy.reference.generated.numpy.ma.make_mask_none |
numpy.ma.mask_cols ma.mask_cols(a, axis=<no value>)[source]
Mask columns of a 2D array that contain masked values. This function is a shortcut to mask_rowcols with axis equal to 1. See also mask_rowcols
Mask rows and/or columns of a 2D array. masked_where
Mask where a condition is met. Examples >>> import n... | numpy.reference.generated.numpy.ma.mask_cols |
numpy.ma.mask_or ma.mask_or(m1, m2, copy=False, shrink=True)[source]
Combine two masks with the logical_or operator. The result may be a view on m1 or m2 if the other is nomask (i.e. False). Parameters
m1, m2array_like
Input masks.
copybool, optional
If copy is False and one of the inputs is nomask, retur... | numpy.reference.generated.numpy.ma.mask_or |
numpy.ma.mask_rowcols ma.mask_rowcols(a, axis=None)[source]
Mask rows and/or columns of a 2D array that contain masked values. Mask whole rows and/or columns of a 2D array that contain masked values. The masking behavior is selected using the axis parameter. If axis is None, rows and columns are masked. If axis is... | numpy.reference.generated.numpy.ma.mask_rowcols |
numpy.ma.mask_rows ma.mask_rows(a, axis=<no value>)[source]
Mask rows of a 2D array that contain masked values. This function is a shortcut to mask_rowcols with axis equal to 0. See also mask_rowcols
Mask rows and/or columns of a 2D array. masked_where
Mask where a condition is met. Examples >>> import nump... | numpy.reference.generated.numpy.ma.mask_rows |
numpy.ma.masked_all ma.masked_all(shape, dtype=<class 'float'>)[source]
Empty masked array with all elements masked. Return an empty masked array of the given shape and dtype, where all the data are masked. Parameters
shapetuple
Shape of the required MaskedArray.
dtypedtype, optional
Data type of the outp... | numpy.reference.generated.numpy.ma.masked_all |
numpy.ma.masked_all_like ma.masked_all_like(arr)[source]
Empty masked array with the properties of an existing array. Return an empty masked array of the same shape and dtype as the array arr, where all the data are masked. Parameters
arrndarray
An array describing the shape and dtype of the required MaskedAr... | numpy.reference.generated.numpy.ma.masked_all_like |
numpy.ma.masked_equal ma.masked_equal(x, value, copy=True)[source]
Mask an array where equal to a given value. This function is a shortcut to masked_where, with condition = (x == value). For floating point arrays, consider using masked_values(x, value). See also masked_where
Mask where a condition is met. maske... | numpy.reference.generated.numpy.ma.masked_equal |
numpy.ma.masked_greater ma.masked_greater(x, value, copy=True)[source]
Mask an array where greater than a given value. This function is a shortcut to masked_where, with condition = (x > value). See also masked_where
Mask where a condition is met. Examples >>> import numpy.ma as ma
>>> a = np.arange(4)
>>> a
a... | numpy.reference.generated.numpy.ma.masked_greater |
numpy.ma.masked_greater_equal ma.masked_greater_equal(x, value, copy=True)[source]
Mask an array where greater than or equal to a given value. This function is a shortcut to masked_where, with condition = (x >= value). See also masked_where
Mask where a condition is met. Examples >>> import numpy.ma as ma
>>>... | numpy.reference.generated.numpy.ma.masked_greater_equal |
numpy.ma.masked_inside ma.masked_inside(x, v1, v2, copy=True)[source]
Mask an array inside a given interval. Shortcut to masked_where, where condition is True for x inside the interval [v1,v2] (v1 <= x <= v2). The boundaries v1 and v2 can be given in either order. See also masked_where
Mask where a condition is ... | numpy.reference.generated.numpy.ma.masked_inside |
numpy.ma.masked_invalid ma.masked_invalid(a, copy=True)[source]
Mask an array where invalid values occur (NaNs or infs). This function is a shortcut to masked_where, with condition = ~(np.isfinite(a)). Any pre-existing mask is conserved. Only applies to arrays with a dtype where NaNs or infs make sense (i.e. floati... | numpy.reference.generated.numpy.ma.masked_invalid |
numpy.ma.masked_less ma.masked_less(x, value, copy=True)[source]
Mask an array where less than a given value. This function is a shortcut to masked_where, with condition = (x < value). See also masked_where
Mask where a condition is met. Examples >>> import numpy.ma as ma
>>> a = np.arange(4)
>>> a
array([0, ... | numpy.reference.generated.numpy.ma.masked_less |
numpy.ma.masked_less_equal ma.masked_less_equal(x, value, copy=True)[source]
Mask an array where less than or equal to a given value. This function is a shortcut to masked_where, with condition = (x <= value). See also masked_where
Mask where a condition is met. Examples >>> import numpy.ma as ma
>>> a = np.a... | numpy.reference.generated.numpy.ma.masked_less_equal |
numpy.ma.masked_not_equal ma.masked_not_equal(x, value, copy=True)[source]
Mask an array where not equal to a given value. This function is a shortcut to masked_where, with condition = (x != value). See also masked_where
Mask where a condition is met. Examples >>> import numpy.ma as ma
>>> a = np.arange(4)
>>... | numpy.reference.generated.numpy.ma.masked_not_equal |
numpy.ma.masked_object ma.masked_object(x, value, copy=True, shrink=True)[source]
Mask the array x where the data are exactly equal to value. This function is similar to masked_values, but only suitable for object arrays: for floating point, use masked_values instead. Parameters
xarray_like
Array to mask
va... | numpy.reference.generated.numpy.ma.masked_object |
numpy.ma.masked_outside ma.masked_outside(x, v1, v2, copy=True)[source]
Mask an array outside a given interval. Shortcut to masked_where, where condition is True for x outside the interval [v1,v2] (x < v1)|(x > v2). The boundaries v1 and v2 can be given in either order. See also masked_where
Mask where a conditi... | numpy.reference.generated.numpy.ma.masked_outside |
numpy.ma.masked_values ma.masked_values(x, value, rtol=1e-05, atol=1e-08, copy=True, shrink=True)[source]
Mask using floating point equality. Return a MaskedArray, masked where the data in array x are approximately equal to value, determined using isclose. The default tolerances for masked_values are the same as th... | numpy.reference.generated.numpy.ma.masked_values |
numpy.ma.masked_where ma.masked_where(condition, a, copy=True)[source]
Mask an array where a condition is met. Return a as an array masked where condition is True. Any masked values of a or condition are also masked in the output. Parameters
conditionarray_like
Masking condition. When condition tests floating... | numpy.reference.generated.numpy.ma.masked_where |
numpy.ma.MaskedArray.__abs__ method ma.MaskedArray.__abs__(self) | numpy.reference.generated.numpy.ma.maskedarray.__abs__ |
numpy.ma.MaskedArray.__add__ method ma.MaskedArray.__add__(other)[source]
Add self to other, and return a new masked array. | numpy.reference.generated.numpy.ma.maskedarray.__add__ |
numpy.ma.MaskedArray.__and__ method ma.MaskedArray.__and__(value, /)
Return self&value. | numpy.reference.generated.numpy.ma.maskedarray.__and__ |
numpy.ma.MaskedArray.__array__ method ma.MaskedArray.__array__([dtype, ]/) → reference if type unchanged, copy otherwise.
Returns either a new reference to self if dtype is not given or a new array of provided data type if dtype is different from the current dtype of the array. | numpy.reference.generated.numpy.ma.maskedarray.__array__ |
numpy.ma.MaskedArray.__array_priority__ attribute ma.MaskedArray.__array_priority__ = 15 | numpy.reference.generated.numpy.ma.maskedarray.__array_priority__ |
numpy.ma.MaskedArray.__array_wrap__ method ma.MaskedArray.__array_wrap__(obj, context=None)[source]
Special hook for ufuncs. Wraps the numpy array and sets the mask according to context. | numpy.reference.generated.numpy.ma.maskedarray.__array_wrap__ |
numpy.ma.MaskedArray.__bool__ method ma.MaskedArray.__bool__(/)
self != 0 | numpy.reference.generated.numpy.ma.maskedarray.__bool__ |
numpy.ma.MaskedArray.__contains__ method ma.MaskedArray.__contains__(key, /)
Return key in self. | numpy.reference.generated.numpy.ma.maskedarray.__contains__ |
numpy.ma.MaskedArray.__copy__ method ma.MaskedArray.__copy__()
Used if copy.copy is called on an array. Returns a copy of the array. Equivalent to a.copy(order='K'). | numpy.reference.generated.numpy.ma.maskedarray.__copy__ |
numpy.ma.MaskedArray.__deepcopy__ method ma.MaskedArray.__deepcopy__(memo, /) → Deep copy of array.[source]
Used if copy.deepcopy is called on an array. | numpy.reference.generated.numpy.ma.maskedarray.__deepcopy__ |
numpy.ma.MaskedArray.__delitem__ method ma.MaskedArray.__delitem__(key, /)
Delete self[key]. | numpy.reference.generated.numpy.ma.maskedarray.__delitem__ |
numpy.ma.MaskedArray.__div__ method ma.MaskedArray.__div__(other)[source]
Divide other into self, and return a new masked array. | numpy.reference.generated.numpy.ma.maskedarray.__div__ |
numpy.ma.MaskedArray.__divmod__ method ma.MaskedArray.__divmod__(value, /)
Return divmod(self, value). | numpy.reference.generated.numpy.ma.maskedarray.__divmod__ |
numpy.ma.MaskedArray.__eq__ method ma.MaskedArray.__eq__(other)[source]
Check whether other equals self elementwise. When either of the elements is masked, the result is masked as well, but the underlying boolean data are still set, with self and other considered equal if both are masked, and unequal otherwise. For... | numpy.reference.generated.numpy.ma.maskedarray.__eq__ |
numpy.ma.MaskedArray.__float__ method ma.MaskedArray.__float__()[source]
Convert to float. | numpy.reference.generated.numpy.ma.maskedarray.__float__ |
numpy.ma.MaskedArray.__floordiv__ method ma.MaskedArray.__floordiv__(other)[source]
Divide other into self, and return a new masked array. | numpy.reference.generated.numpy.ma.maskedarray.__floordiv__ |
numpy.ma.MaskedArray.__ge__ method ma.MaskedArray.__ge__(value, /)
Return self>=value. | numpy.reference.generated.numpy.ma.maskedarray.__ge__ |
numpy.ma.MaskedArray.__getitem__ method ma.MaskedArray.__getitem__(indx)[source]
x.__getitem__(y) <==> x[y] Return the item described by i, as a masked array. | numpy.reference.generated.numpy.ma.maskedarray.__getitem__ |
numpy.ma.MaskedArray.__getstate__ method ma.MaskedArray.__getstate__()[source]
Return the internal state of the masked array, for pickling purposes. | numpy.reference.generated.numpy.ma.maskedarray.__getstate__ |
numpy.ma.MaskedArray.__gt__ method ma.MaskedArray.__gt__(value, /)
Return self>value. | numpy.reference.generated.numpy.ma.maskedarray.__gt__ |
numpy.ma.MaskedArray.__iadd__ method ma.MaskedArray.__iadd__(other)[source]
Add other to self in-place. | numpy.reference.generated.numpy.ma.maskedarray.__iadd__ |
numpy.ma.MaskedArray.__iand__ method ma.MaskedArray.__iand__(value, /)
Return self&=value. | numpy.reference.generated.numpy.ma.maskedarray.__iand__ |
numpy.ma.MaskedArray.__idiv__ method ma.MaskedArray.__idiv__(other)[source]
Divide self by other in-place. | numpy.reference.generated.numpy.ma.maskedarray.__idiv__ |
numpy.ma.MaskedArray.__ifloordiv__ method ma.MaskedArray.__ifloordiv__(other)[source]
Floor divide self by other in-place. | numpy.reference.generated.numpy.ma.maskedarray.__ifloordiv__ |
numpy.ma.MaskedArray.__ilshift__ method ma.MaskedArray.__ilshift__(value, /)
Return self<<=value. | numpy.reference.generated.numpy.ma.maskedarray.__ilshift__ |
numpy.ma.MaskedArray.__imod__ method ma.MaskedArray.__imod__(value, /)
Return self%=value. | numpy.reference.generated.numpy.ma.maskedarray.__imod__ |
numpy.ma.MaskedArray.__imul__ method ma.MaskedArray.__imul__(other)[source]
Multiply self by other in-place. | numpy.reference.generated.numpy.ma.maskedarray.__imul__ |
numpy.ma.MaskedArray.__int__ method ma.MaskedArray.__int__()[source]
Convert to int. | numpy.reference.generated.numpy.ma.maskedarray.__int__ |
numpy.ma.MaskedArray.__ior__ method ma.MaskedArray.__ior__(value, /)
Return self|=value. | numpy.reference.generated.numpy.ma.maskedarray.__ior__ |
numpy.ma.MaskedArray.__ipow__ method ma.MaskedArray.__ipow__(other)[source]
Raise self to the power other, in place. | numpy.reference.generated.numpy.ma.maskedarray.__ipow__ |
numpy.ma.MaskedArray.__irshift__ method ma.MaskedArray.__irshift__(value, /)
Return self>>=value. | numpy.reference.generated.numpy.ma.maskedarray.__irshift__ |
numpy.ma.MaskedArray.__isub__ method ma.MaskedArray.__isub__(other)[source]
Subtract other from self in-place. | numpy.reference.generated.numpy.ma.maskedarray.__isub__ |
numpy.ma.MaskedArray.__itruediv__ method ma.MaskedArray.__itruediv__(other)[source]
True divide self by other in-place. | numpy.reference.generated.numpy.ma.maskedarray.__itruediv__ |
numpy.ma.MaskedArray.__ixor__ method ma.MaskedArray.__ixor__(value, /)
Return self^=value. | numpy.reference.generated.numpy.ma.maskedarray.__ixor__ |
numpy.ma.MaskedArray.__le__ method ma.MaskedArray.__le__(value, /)
Return self<=value. | numpy.reference.generated.numpy.ma.maskedarray.__le__ |
numpy.ma.MaskedArray.__len__ method ma.MaskedArray.__len__(/)
Return len(self). | numpy.reference.generated.numpy.ma.maskedarray.__len__ |
numpy.ma.MaskedArray.__lshift__ method ma.MaskedArray.__lshift__(value, /)
Return self<<value. | numpy.reference.generated.numpy.ma.maskedarray.__lshift__ |
numpy.ma.MaskedArray.__lt__ method ma.MaskedArray.__lt__(value, /)
Return self<value. | numpy.reference.generated.numpy.ma.maskedarray.__lt__ |
numpy.ma.MaskedArray.__mod__ method ma.MaskedArray.__mod__(value, /)
Return self%value. | numpy.reference.generated.numpy.ma.maskedarray.__mod__ |
numpy.ma.MaskedArray.__mul__ method ma.MaskedArray.__mul__(other)[source]
Multiply self by other, and return a new masked array. | numpy.reference.generated.numpy.ma.maskedarray.__mul__ |
numpy.ma.MaskedArray.__ne__ method ma.MaskedArray.__ne__(other)[source]
Check whether other does not equal self elementwise. When either of the elements is masked, the result is masked as well, but the underlying boolean data are still set, with self and other considered equal if both are masked, and unequal otherw... | numpy.reference.generated.numpy.ma.maskedarray.__ne__ |
numpy.ma.MaskedArray.__or__ method ma.MaskedArray.__or__(value, /)
Return self|value. | numpy.reference.generated.numpy.ma.maskedarray.__or__ |
numpy.ma.MaskedArray.__pow__ method ma.MaskedArray.__pow__(other)[source]
Raise self to the power other, masking the potential NaNs/Infs | numpy.reference.generated.numpy.ma.maskedarray.__pow__ |
numpy.ma.MaskedArray.__radd__ method ma.MaskedArray.__radd__(other)[source]
Add other to self, and return a new masked array. | numpy.reference.generated.numpy.ma.maskedarray.__radd__ |
numpy.ma.MaskedArray.__rand__ method ma.MaskedArray.__rand__(value, /)
Return value&self. | numpy.reference.generated.numpy.ma.maskedarray.__rand__ |
numpy.ma.MaskedArray.__rdivmod__ method ma.MaskedArray.__rdivmod__(value, /)
Return divmod(value, self). | numpy.reference.generated.numpy.ma.maskedarray.__rdivmod__ |
numpy.ma.MaskedArray.__reduce__ method ma.MaskedArray.__reduce__()[source]
Return a 3-tuple for pickling a MaskedArray. | numpy.reference.generated.numpy.ma.maskedarray.__reduce__ |
numpy.ma.MaskedArray.__repr__ method ma.MaskedArray.__repr__()[source]
Literal string representation. | numpy.reference.generated.numpy.ma.maskedarray.__repr__ |
numpy.ma.MaskedArray.__rfloordiv__ method ma.MaskedArray.__rfloordiv__(other)[source]
Divide self into other, and return a new masked array. | numpy.reference.generated.numpy.ma.maskedarray.__rfloordiv__ |
numpy.ma.MaskedArray.__rlshift__ method ma.MaskedArray.__rlshift__(value, /)
Return value<<self. | numpy.reference.generated.numpy.ma.maskedarray.__rlshift__ |
numpy.ma.MaskedArray.__rmod__ method ma.MaskedArray.__rmod__(value, /)
Return value%self. | numpy.reference.generated.numpy.ma.maskedarray.__rmod__ |
numpy.ma.MaskedArray.__rmul__ method ma.MaskedArray.__rmul__(other)[source]
Multiply other by self, and return a new masked array. | numpy.reference.generated.numpy.ma.maskedarray.__rmul__ |
numpy.ma.MaskedArray.__ror__ method ma.MaskedArray.__ror__(value, /)
Return value|self. | numpy.reference.generated.numpy.ma.maskedarray.__ror__ |
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