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 three 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.
The indices for each axis 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)
Boolean indices may be any object which exposes the numpy array interface.
>>> d.shape
(12, 19, 73, 96)
>>> d[..., d[0, 0, 0]>d[0, 0, 0].min()]
Cyclic axes
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 number of 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. |
| 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. | ||
| allclose | Returns True if two broadcastable arrays have equal values, False otherwise. | ||
| max | Collapse axes with their maximum. | ||
| min | Collapse axes with their minimum. | ||
| any | Test whether any data array elements evaluate to True. | ||
| 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 | ||
| ceil | Return the ceiling of 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 | Return 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. | ||
| floor | Return the floor of the data array. | ||
| func | Apply an element-wise array operation to the data array in place. | ||
| isclose | Return a boolean data array showing where two broadcastable arrays have equal values within a tolerance. | ||
| loadd | Reset the data array in place from a dictionary serialization. | ||
| mask_invalid | Mask the array where invalid values occur (NaN or inf). | ||
| mean | Collapse axes with their weighted mean. | ||
| mid_range | Collapse axes with the unweighted average of their maximum and minimum values. | ||
| 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. | ||
| override_units | Override the data array units. | ||
| partition_boundaries | Return the partition boundaries for each partition matrix dimension. | ||
| range | Collapse axes with the absolute difference between their maximum and minimum values. | ||
| rint | Round elements of the data array to the nearest integer. | ||
| roll | A lot like numpy.roll | ||
| save_to_disk | |||
| sample_size |
|
||
| sd | Collapse axes by calculating their standard deviation. | ||
| sin | Take the trigonometric sine of the data array in place. | ||
| squeeze | Remove size 1 axes from the data array. | ||
| sum | Collapse axes with their sum. | ||
| sum_of_weights | Missing data array elements are omitted from the calculation. | ||
| sum_of_weights2 | Missing data array elements are omitted from the calculation. | ||
| 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. | ||
| trunc | Return the truncated values of the data array. | ||
| unique | The unique elements of the array. | ||
| var | Collapse axes with their weighted variance. | ||
| where | Set data array elements depending on a condition. |
| 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 |
| __mod__ | The binary arithmetic operation % |
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 |
| __rmod__ | The binary arithmetic operation % with reflected operands |
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 **= |
| __imod__ | The binary arithmetic operation %= |
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__ | Implement indexing |
| __iter__ | Efficient iteration. |
| __setitem__ | Implement indexed assignment |
| __contains__ | Membership test operator in |
String representations
| __repr__ | The built-in function repr |
| __str__ | The built-in function str |