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'''
Template for creating a PyFerret Python External Function (PyEF).
The names of the functions provided should not be changed. By
default, PyFerret uses the name of the module as the function name.
Copy this file using a name that you would like to be the function
name, then modify the contents of these functions and comments as
desired.
'''
import numpy
def ferret_init(efid):
'''
Initialization function for this PyFerret PyEF. Returns
a dictionary describing the features of this PyFerret PyEF.
At a minimum, assigns the number of arguments expected and
a descriptions of the functions. May also provide
descriptions of the arguments and specifications for a
non-standard result grid.
'''
init_dict = { }
init_dict["numargs"] = 1
init_dict["descript"] = "Pass through"
return init_dict
def ferret_result_limits(efid):
'''
Defines the index limits for all abstract axes in the result grid.
Returns an (X,Y,Z,T,E,F)-axis six-tuple of either (low,high) pairs,
for an abstract axis, or None, for a non-abstract axis. The low
and high values are integer values. If the result grid has no
abstract axes, this function will not be called and can be deleted.
'''
axis_limits = (None, None, None, None, None, None)
return axis_limits
def ferret_custom_axes(efid):
'''
Defines all custom axes in ther result grid. Returns a (X,Y,Z,T,E,F)-
axis six-tuple of either a (low, high, delta, unit_name, is_modulo)
tuple, for a custom axis, or None, for a non-custom axis. The low,
high, and delta values are floating-point values in units of the axis
coordinate ("world coordinates"). If the result grid has no custom
axes, this function will not be called and can be deleted.
'''
axis_info = (None, None, None, None, None, None)
return axis_info
def ferret_compute(efid, result, result_bdf, inputs, input_bdfs):
'''
Computation function for this PyFerret PyEF. Assign values to the
elements of result; do not reassign result itself. In other words,
assign values using notation similar to 'result[...] = ...'; do not
use notation similar to 'result = ...' as this will simply define
a new local variable called result, hiding the variable passed into
this function.
If an error is detected, raise an appropriate exception. ValueError
is commonly used for unexpected values. IndexError is commonly used
for unexpected array sizes.
Arguments:
result - numpy float array to be assigned
result_bdf - numpy read-only float array of one element giving the
missing-data value to be used when assigning result
inputs - tuple of numpy read-only float arrays giving the input
values provided by the caller
input_bdfs - numpy read-only float arrays of one element giving the
missing-data value for the corresponding inputs array
'''
# Create masks of values that are undefined and that are defined
bad_mask = ( inputs[0] == input_bdfs[0] )
good_mask = numpy.logical_not(bad_mask)
result[good_mask] = inputs[0][good_mask]
result[bad_mask] = result_bdf
return
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