Bases: object
An N-dimensional data array with units and masked values.
Indexing
A data array is indexable in a similar way to numpy array:
>>> d.shape
(12, 19, 73, 96)
>>> d[...].shape
(12, 19, 73, 96)
>>> d[slice(0, 9), 10:0:-2, :, :].shape
(9, 5, 73, 96)
There are two important extensions to the numpy indexing functionality:
Size 1 dimensions are never removed bi indexing.
An integer index i takes the i-th element but does not reduce the rank of the output array by one:
>>> d.shape
(12, 19, 73, 96)
>>> d[0, ...].shape
(1, 19, 73, 96)
>>> d[:, 3, slice(10, 0, -2), 95].shape
(12, 1, 5, 1)
Size 1 dimensions may be removed with the squeeze method.
When advanced indexing is used on more than one dimension, the advanced indices work independently.
When more than one dimension’s slice is a 1-d boolean sequence or 1-d sequence of integers, then these indices work independently along each dimension (similar to the way vector subscripts work in Fortran), rather than by their elements:
>>> d.shape
(12, 19, 73, 96)
>>> d[0, :, [0, 1], [0, 13, 27]].shape
(1, 19, 2, 3)
Miscellaneous
A Data object is picklable.
A Data object is hashable, but note that, since it is mutable, its hash value is only valid whilst the data array is not changed in place.
Initialization
Parameters : |
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Examples
>>> d = cf.Data(5)
>>> d = cf.Data([1,2,3], units='K')
>>> import numpy
>>> d = cf.Data(numpy.arange(10).reshape(2,5), units=cf.Units('m/s'), fill_value=-999)
>>> d = cf.Data(tuple('fly'))
array | A numpy array copy the data array. |
data | The data array object as an object identity. |
day | The day of each data array element. |
dtarray | An independent numpy array of date-time objects. |
dtvarray | A numpy array view the data array converted to date-time objects. |
dtype | The numpy data type of the data array. |
fill_value | The data array missing data value. |
hardmask | Whether the mask is hard (True) or soft (False). |
hour | The hour of each data array element. |
ismasked | True if the data array has any masked values. |
isscalar | True if the data array is a 0-d scalar array. |
mask | The boolean missing data mask of the data array. |
minute | The minute of each data array element. |
month | The month of each data array element. |
nbytes | Total bytes consumed by the elements of the array. |
ndim | Number of dimensions in the data array. |
second | The second of each data array element. |
shape | Tuple of the data array’s dimension sizes. |
size | Number of elements in the data array. |
unique | The unique elements of the array. |
Units | The cf.Units object containing the units of the data array. |
varray | A numpy array view the data array. |
year | The year of each data array element. |
all | Test whether all data array elements evaluate to True. |
cf.Data.amax | |
cf.Data.amin | |
any | Test whether any data array elements evaluate to True. |
cf.Data.average | |
asdatetime | Change the internal representation of data array elements from numeric reference times to datatime-like objects. |
asreftime | Change the internal representation of data array elements from datatime-like objects to numeric reference times. |
binary_mask | Return a binary missing data mask of the data array. |
chunk | Partition the data array |
clip | Clip (limit) the values in the data array in place. |
close | Close all files referenced by the data array. |
copy | Return a deep copy. |
cos | Take the trigonometric cosine of the data array in place. |
datum | Return an element of the data array as a standard Python scalar. |
dump | Return a string containing a full description of the instance. |
dumpd | A dictionary serialization of the data array. |
equals | True if two data arrays are logically equal, False otherwise. |
cf.Data.equivalent | |
expand_dims | Expand the shape of the data array in place. |
flat | Return a flat iterator over elements of the data array. |
flip | Flip (reverse the direction of) axes of the data array in place. |
func | Apply an element-wise array operation to the data array in place. |
loadd | Reset the data array in place from a dictionary serialization. |
mask_invalid | Mask the array where invalid values occur (NaNs or infs). |
mid_range | Collapse axes with their mid range. |
ndindex | Return an iterator over the N-dimensional indices of the data array. |
outerproduct | Compute the outer product with another data array. |
override_calendar | Override the data array units in place. |
override_units | Override the data array units in place. |
partition_boundaries | Return the partition boundaries for each partition matrix dimension. |
save_to_disk | |
sd | Collapse axes by calculating their standard deviation. |
setdata | Set data array elements depending on a condition. |
sin | Take the trigonometric sine of the data array in place. |
squeeze | Remove size 1 axes from the data array in place. |
sum | Collapse axes with their sum. |
swapaxes | Interchange two axes of an array. |
tan | Take the trigonometric tangent of the data array element-wise. |
to_disk | Store the data array on disk in place. |
to_memory | Store each partition’s data in memory in place if the master array is smaller than the chunk size. |
transpose | Permute the axes of the data array in place. |
var | Collapse axes with their weighted variance. |
mask_fpe | Masking of floating-point errors in the results of arithmetic operations. |
seterr | Set how floating-point errors in the results of arithmetic operations are handled. |
Arithmetic, bitwise and comparison operations are defined as element-wise data array operations which yield a new cf.Data object or, for augmented assignments, modify the data array in-place.
Comparison operators
__lt__ | The rich comparison operator < |
__le__ | The rich comparison operator <= |
__eq__ | The rich comparison operator == |
__ne__ | The rich comparison operator != |
__gt__ | The rich comparison operator > |
__ge__ | The rich comparison operator >= |
Truth value of an array
__nonzero__ | Truth value testing and the built-in operation bool |
Binary arithmetic operators
__add__ | The binary arithmetic operation + |
__sub__ | The binary arithmetic operation - |
__mul__ | The binary arithmetic operation * |
__div__ | The binary arithmetic operation / |
__truediv__ | The binary arithmetic operation / (true division) |
__floordiv__ | The binary arithmetic operation // |
__pow__ | The binary arithmetic operations ** and pow |
Binary arithmetic operators with reflected (swapped) operands
__radd__ | The binary arithmetic operation + with reflected operands |
__rsub__ | The binary arithmetic operation - with reflected operands |
__rmul__ | The binary arithmetic operation * with reflected operands |
__rdiv__ | The binary arithmetic operation / with reflected operands |
__rtruediv__ | The binary arithmetic operation / (true division) with reflected |
__rfloordiv__ | The binary arithmetic operation // with reflected operands |
__rpow__ | The binary arithmetic operations ** and pow with reflected |
Augmented arithmetic assignments
__iadd__ | The augmented arithmetic assignment += |
__isub__ | The augmented arithmetic assignment -= |
__imul__ | The augmented arithmetic assignment *= |
__idiv__ | The augmented arithmetic assignment /= |
__itruediv__ | The augmented arithmetic assignment /= (true division) |
__ifloordiv__ | The augmented arithmetic assignment //= |
__ipow__ | The augmented arithmetic assignment **= |
Unary arithmetic operators
__neg__ | The unary arithmetic operation - |
__pos__ | The unary arithmetic operation + |
__abs__ | The unary arithmetic operation abs |
Binary bitwise operators
__and__ | The binary bitwise operation & |
__or__ | The binary bitwise operation | |
__xor__ | The binary bitwise operation ^ |
__lshift__ | The binary bitwise operation << |
__rshift__ | The binary bitwise operation >> |
Binary bitwise operators with reflected (swapped) operands
__rand__ | The binary bitwise operation & with reflected operands |
__ror__ | The binary bitwise operation | with reflected operands |
__rxor__ | The binary bitwise operation ^ with reflected operands |
__rlshift__ | The binary bitwise operation << with reflected operands |
__rrshift__ | The binary bitwise operation >> with reflected operands |
Augmented bitwise assignments
__iand__ | The augmented bitwise assignment &= |
__ior__ | The augmented bitwise assignment |= |
__ixor__ | The augmented bitwise assignment ^= |
__ilshift__ | The augmented bitwise assignment <<= |
__irshift__ | The augmented bitwise assignment >>= |
Unary bitwise operators
__invert__ | The unary bitwise operation ~ |
Standard library functions
__deepcopy__ | Used if copy.deepcopy is called |
__hash__ | The built-in function hash |
Container customization
__len__ | The built-in function len |
__getitem__ | x.__getitem__(indices) <==> x[indices] |
__iter__ | Efficient iteration. |
__setitem__ | x.__setitem__(indices, y) <==> x[indices]=y |
__contains__ | Membership test operators |
String representations
__repr__ | The built-in function repr |
__str__ | The built-in function str |