Bases: cf.utils.CfList
Store CF data array. An ordered list of arrays may be stored which, when concatenated form the desired array.
Parameters: | data – Initialize the data from this object, which may be a Data object or a numpy.ndarray or None. Any other type of object returns an empty Data instance. |
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Special attributes:
Attribute | Description |
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_list | |
shape | |
order | |
direction | |
Units | |
adim | |
elements |
Methods and attributes defined here:
Create a numpy array copy of the concatenated data.
Concatenate elements into a Data object with a single element.
Conform data according to its metadata.
Return a deep copy.
Parameters: | data (bool) – Optional. If False then assign the output variable’s data arrays to None, with the expectation that the data will be replaced subsequently. The data object’s metadata are deep copied in any case. |
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Returns: | A deep copy. |
CFL.count(value) -> integer – return number of occurrences of value
Uses numerically tolerant equality.
Data-type of the data’s elements.
Returns: | A numpy dtype object. |
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Return True if the data instance is congruent to another one in that
- They have identical data array. Pointers to data on disk may be converted to numpy arrays in memory if required.
Equality of numbers is to within a tolerance. Refer to cf for details.
Parameters: |
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Returns: | True if the two objects are congruent, False otherwise. |
Examples:
>>> y = x
>>> x.equals(y)
True
CFL.index(value, [start, [stop]]) -> integer – return first index of value
Uses numerically tolerant equality.
D.insert(index, object) – insert Data object before index
Number of dimensions of the data.
Equivalent to the number of elements in shape tuple.
Returns: | A non-negative integer |
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Remove a size 1 dimension fromt the data IN PLACE.
Number of elements in the data
Returns: | A positive integer |
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Return an object which, when indexed, returns a slice of the data.
Create a numpy array view of the concatenated data.