cfdm.Data¶
-
class
cfdm.
Data
(array=None, units=None, calendar=None, fill_value=None, source=None, copy=True, dtype=None, mask=None, _use_array=True, **kwargs)[source]¶ Bases:
cfdm.mixin.container.Container
,cfdm.mixin.netcdf.NetCDFHDF5
,cfdm.core.data.data.Data
An orthogonal multidimensional array with masked values and units.
New in version 1.7.0.
Initialization
Parameters: - array: numpy array-like or subclass of
Array
, optional The array of values. Ignored if the source parameter is set.
- Parameter example:
array=[34.6]
- Parameter example:
array=[[1, 2], [3, 4]]
- Parameter example:
array=numpy.ma.arange(10).reshape(2, 1, 5)
- units:
str
, optional The physical units of the data. Ignored if the source parameter is set.
The units may also be set after initialisation with the
set_units
method.- Parameter example:
units='km hr-1'
- Parameter example:
units='days since 2018-12-01'
- calendar:
str
, optional The calendar for reference time units. Ignored if the source parameter is set.
The calendar may also be set after initialisation with the
set_calendar
method.- Parameter example:
calendar='360_day'
- fill_value: optional
The fill value of the data. By default, or if set to
None
, thenumpy
fill value appropriate to the array’s data type will be used (seenumpy.ma.default_fill_value
). Ignored if the source parameter is set.The fill value may also be set after initialisation with the
set_fill_value
method.- Parameter example:
fill_value=-999.
- dtype: data-type, optional
The desired data-type for the data. By default the data-type will be inferred form the array parameter.
The data-type may also be set after initialisation with the
dtype
attribute.- Parameter example:
dtype=float
- Parameter example:
dtype='float32'
- Parameter example:
dtype=numpy.dtype('i2')
- mask: optional
Apply this mask to the data given by the array parameter. By default, or if mask is
None
, no mask is applied. May be any scalar or array-like object (such as anumpy
array orData
instance) that is scalar or has the same shape as array. Masking will be carried out where mask elements evaluate toTrue
.This mask will applied in addition to any mask already defined by the array parameter.
- source: optional
Initialize the array, units, calendar and fill value from those of source.
- copy:
bool
, optional If False then do not deep copy input parameters prior to initialization. By default arguments are deep copied.
- kwargs: ignored
Not used. Present to facilitate subclassing.
- array: numpy array-like or subclass of
Inspection¶
Methods
first_element |
Return the first element of the data as a scalar. |
second_element |
Return the second element of the data as a scalar. |
last_element |
Return the last element of the data as a scalar. |
Attributes
array |
Return an independent numpy array containing the data. |
datetime_array |
Return an independent numpy array containing the date-time objects corresponding to time since a reference date. |
dtype |
Data-type of the data elements. |
mask |
The boolean missing data mask of the data array. |
ndim |
Number of data dimensions. |
shape |
Tuple of data dimension sizes. |
size |
Number of elements in the data. |
Units¶
Methods
get_units |
Return the units. |
set_units |
Set the units. |
set_calendar |
Set the calendar. |
get_calendar |
Return the calendar. |
Fill value¶
Methods
get_fill_value |
Return the missing data value. |
set_fill_value |
Set the missing data value. |
Dimensions¶
Methods
insert_dimension |
Expand the shape of the data array. |
squeeze |
Remove size 1 axes from the data. |
transpose |
Permute the axes of the data array. |
Calculation¶
Methods
max |
Return the maximum of an array or the maximum along axes. |
min |
Return the minimum of an array or minimum along axes. |
sum |
Return the sum of an array or the sum along axes. |
unique |
The unique elements of the data. |
Miscellaneous¶
Methods
copy |
Return a deep copy. |
equals |
Whether two data arrays are the same. |
to_memory |
|
source |
Return the underlying array object. |
uncompress |
Uncompress the underlying array in-place. |
Compression¶
Methods
get_compression_type |
Return the type of compression applied to the underlying array. |
get_compressed_axes |
Return the dimensions that have compressed in the underlying array. |
get_compressed_dimension |
Return the position of the compressed dimension in the compressed array. |
uncompress |
Uncompress the underlying array in-place. |
get_count |
Return the count variable for a compressed array. |
get_index |
Return the index variable for a compressed array. |
get_list |
Return the list variable for a compressed array. |
Attributes
compressed_array |
Return an independent numpy array containing the compressed data. |
Special¶
Methods
__array__ |
The numpy array interface. |
__deepcopy__ |
Called by the copy.deepcopy function. |
__getitem__ |
Return a subspace of the data defined by indices |
__repr__ |
Called by the repr built-in function. |
__setitem__ |
Assign to data elements defined by indices. |
__str__ |
Called by the str built-in function. |