cf.FieldAncillary¶
-
class
cf.
FieldAncillary
(properties=None, data=None, source=None, copy=True, _use_data=True)[source]¶ Bases:
cf.mixin.propertiesdata.PropertiesData
,cfdm.fieldancillary.FieldAncillary
A field ancillary construct of the CF data model.
The field ancillary construct provides metadata which are distributed over the same sampling domain as the field itself. For example, if a data variable holds a variable retrieved from a satellite instrument, a related ancillary data variable might provide the uncertainty estimates for those retrievals (varying over the same spatiotemporal domain).
The field ancillary construct consists of an array of the ancillary data, which is zero-dimensional or which depends on one or more of the domain axes, and properties to describe the data. It is assumed that the data do not depend on axes of the domain which are not spanned by the array, along which the values are implicitly propagated. CF-netCDF ancillary data variables correspond to field ancillary constructs. Note that a field ancillary construct is constrained by the domain definition of the parent field construct but does not contribute to the domain’s definition, unlike, for instance, an auxiliary coordinate construct or domain ancillary construct.
NetCDF interface
{{netcdf variable}}
Initialisation
- Parameters
- properties:
dict
, optional Set descriptive properties. The dictionary keys are property names, with corresponding values. Ignored if the source parameter is set.
Properties may also be set after initialisation with the
set_properties
andset_property
methods.- Parameter example:
properties={'standard_name': 'altitude'}
- data: data_like, optional
Set the data. Ignored if the source parameter is set.
A data_like object is any object that can be converted to a
Data
object, i.e.numpy
array_like objects,Data
objects, and cf instances that containData
objects.The data also may be set after initialisation with the
set_data
method.- source: optional
Initialise the properties and data from those of source.
Note that if source is a
FieldAncillary
instance thencf.FieldAncillary(source=source)
is equivalent tosource.copy()
.- copy:
bool
, optional If False then do not deep copy input parameters prior to initialisation. By default arguments are deep copied.
- properties:
Inspection¶
Methods
A full description of the field ancillary construct. |
|
Return the canonical identity. |
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Return all possible identities. |
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Inspect the object for debugging. |
Attributes
Return a description of the construct type. |
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An identity for the FieldAncillary object. |
Selection¶
Methods
Whether or not the construct identity satisfies conditions. |
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Whether or not the data has a given dimensionality. |
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Whether or not the netCDF variable name satisfies conditions. |
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Whether or not properties satisfy conditions. |
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Whether or not the construct has given units. |
Properties¶
Methods
Remove a property. |
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Get a CF property. |
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Whether a property has been set. |
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Set a property. |
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Return all properties. |
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Remove all properties. |
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Set properties. |
Attributes
The add_offset CF property. |
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The calendar CF property. |
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The comment CF property. |
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The _FillValue CF property. |
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The history CF property. |
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The leap_month CF property. |
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The leap_year CF property. |
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The long_name CF property. |
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The missing_value CF property. |
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The month_lengths CF property. |
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The scale_factor CF property. |
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The standard_name CF property. |
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The units CF property. |
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The valid_max CF property. |
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The valid_min CF property. |
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The valid_range CF property. |
Units¶
Methods
Override the units. |
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Override the calendar of date-time units. |
Attributes
The |
Data¶
Attributes
A numpy array deep copy of the data array. |
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Deprecated at version 3.0.0, use |
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The |
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An independent numpy array of date-time objects. |
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Return an element of the data array as a standard Python scalar. |
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The |
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True if the data array is scalar. |
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The number of dimensions in the data array. |
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A tuple of the data array’s dimension sizes. |
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The number of elements in the data array. |
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A numpy array view of the data array. |
Methods
Return a subspace defined by indices. |
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Remove the data. |
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Return the data. |
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Whether or not the construct has data. |
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Set the data. |
Rearranging elements
Flatten axes of the data. |
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Flip (reverse the direction of) data dimensions. |
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Expand the shape of the data array. |
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Roll the data along an axis. |
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Remove size one axes from the data array. |
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Interchange two axes of an array. |
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Permute the axes of the data array. |
Data array mask
Apply masking as defined by the CF conventions. |
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Count the non-masked elements of the data. |
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Count the masked elements of the data. |
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Return the data array missing data value. |
A binary (0 and 1) missing data mask of the data array. |
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Whether the mask is hard (True) or soft (False). |
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The mask of the data array. |
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Mask the array where invalid values occur. |
Changing data values
Called to implement assignment to x[indices] |
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Expand the data by adding a halo. |
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Mask the array where invalid values occur. |
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Return a new variable whose data is subspaced. |
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Set data array elements depending on a condition. |
Miscellaneous
Partition the data array. |
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Close all files referenced by the construct. |
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Convert reference time data values to have new units. |
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Set the cyclicity of an axis. |
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Return or set the period of the data. |
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Whether or not a given axis is cyclic. |
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True if a given axis is periodic. |
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Return the name of the file or files containing the data. |
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Whether or not there are cell bounds. |
Miscellaneous¶
Methods
Join a sequence of variables together. |
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Return a deep copy. |
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Return the commands that would create the construct. |
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Whether two instances are the same. |
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Uncompress the construct. |
Attributes
|
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Always False. |
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Always False. |
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Always False. |
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An identity for the FieldAncillary object. |
Mathematical operations¶
Methods
Trigonometrical and hyperbolic functions
Take the trigonometric inverse cosine of the data element- wise. |
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Take the inverse hyperbolic cosine of the data element-wise. |
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Take the trigonometric inverse sine of the data element-wise. |
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Take the inverse hyperbolic sine of the data element-wise. |
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Take the trigonometric inverse tangent of the data element- wise. |
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Take the inverse hyperbolic tangent of the data element-wise. |
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Take the trigonometric cosine of the data element-wise. |
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Take the hyperbolic cosine of the data element-wise. |
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Take the trigonometric sine of the data element-wise. |
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Take the hyperbolic sine of the data element-wise. |
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Take the trigonometric tangent of the data element-wise. |
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Take the hyperbolic tangent of the data array. |
Rounding and truncation
The ceiling of the data, element-wise. |
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Limit the values in the data. |
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Floor the data array, element-wise. |
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Round the data to the nearest integer, element-wise. |
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Round the data to the given number of decimals. |
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Truncate the data, element-wise. |
Statistical collapses
Alias for |
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The unweighted mean the data array. |
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The unweighted average of the maximum and minimum of the data array. |
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Alias for |
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The absolute difference between the maximum and minimum of the data array. |
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The number of non-missing data elements in the data array. |
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The sum of the data array. |
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Alias for |
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Alias for |
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The unweighted sample standard deviation of the data array. |
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The unweighted sample variance of the data array. |
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The maximum of the data array. |
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The minimum of the data array. |
Exponential and logarithmic functions
The exponential of the data, element-wise. |
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The logarithm of the data array. |
Date-time operations¶
Attributes
The day of each date-time data array element. |
|
An independent numpy array of date-time objects. |
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The hour of each date-time data array element. |
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The minute of each date-time data array element. |
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The month of each date-time data array element. |
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The reference date-time of units of elapsed time. |
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The second of each date-time data array element. |
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The year of each date-time data array element. |
Logic functions¶
Truth value testing
Test whether all data elements evaluate to True. |
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Test whether any data elements evaluate to True. |
Comparison
Test whether all data are element-wise equal to other, broadcastable data. |
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Whether two instances are the same. |
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True if two constructs are equal, False otherwise. |
Set operations
The unique elements of the data. |
NetCDF¶
Methods
Remove the netCDF variable name. |
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Return the netCDF variable name. |
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Whether the netCDF variable name has been set. |
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Set the netCDF variable name. |
Aliases¶
Methods
Alias for |
Attributes
Alias for |
Arithmetic and comparison operations¶
Arithmetic, bitwise and comparison operations are defined as element-wise operations on the data, which yield a new construct or, for augmented assignments, modify the construct’s data in-place.
Comparison operators
The rich comparison operator |
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The rich comparison operator |
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The rich comparison operator |
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The rich comparison operator |
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The rich comparison operator |
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The rich comparison operator |
Binary arithmetic operators
The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operations |
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The binary arithmetic operation |
Binary arithmetic operators with reflected (swapped) operands
The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operation |
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The binary arithmetic operations |
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The binary arithmetic operation |
Augmented arithmetic assignments
The augmented arithmetic assignment |
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The augmented arithmetic assignment |
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The augmented arithmetic assignment |
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The augmented arithmetic assignment |
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The augmented arithmetic assignment |
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The augmented arithmetic assignment |
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The augmented arithmetic assignment |
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The binary arithmetic operation |
Unary arithmetic operators
The unary arithmetic operation |
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The unary arithmetic operation |
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The unary arithmetic operation |
Binary bitwise operators
The binary bitwise operation |
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The binary bitwise operation |
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The binary bitwise operation |
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The binary bitwise operation |
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The binary bitwise operation |
Binary bitwise operators with reflected (swapped) operands
The binary bitwise operation |
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The binary bitwise operation |
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The binary bitwise operation |
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The binary bitwise operation |
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The binary bitwise operation |
Augmented bitwise assignments
The augmented bitwise assignment |
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The augmented bitwise assignment |
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The augmented bitwise assignment |
|
The augmented bitwise assignment |
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The augmented bitwise assignment |
Unary bitwise operators
The unary bitwise operation |
Groups¶
Methods
Return the netCDF variable group hierarchy. |
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Remove the netCDF variable group hierarchy. |
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Set the netCDF variable group hierarchy. |
Special¶
Methods
Called to implement membership test operators. |
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Called by the |
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Return a subspace defined by indices. |
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Called by the |
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Called to implement assignment to x[indices] |
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Called by the |
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Returns a numpy array representation of the data. |
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Returns a new reference to the data. |
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Implements the “member of set” condition. |
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Implements the “within a range” condition. |
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Implements the “without a range” condition. |
Deprecated¶
Methods
Deprecated at version 3.0.0. |
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Deprecated at version 3.0.0. |
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Deprecated at version 3.0.0. |
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Deprecated at version 3.0.0, use method |
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Deprecated at version 3.0.0. |
|
Deprecated at version 3.0.0, use |
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Deprecated at version 3.0.0, use method |
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Deprecated at version 3.0.0, use |
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Deprecated at version 3.0.0, use |
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Deprecated at version 3.0.0, use method |
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Deprecated at version 3.0.0, use |
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Deprecated at version 3.7.0, use |
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Deprecated at version 3.7.0, use |
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Deprecated at version 3.7.0, use |
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Deprecated at version 3.7.0, use |
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Deprecated at version 3.7.0, use |
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Deprecated at version 3.0.0, use method ‘identity’ instead. |
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Deprecated at version 3.0.0, use method |
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Deprecated at version 3.0.0. |
|
Deprecated at version 3.0.0, use method |
|
Deprecated at version 3.0.0, use |