[ferret_users] Python externat function with several arguments with different shapes.

[Olivier Marti <olivier.marti@xxxxxxxxxxxx>]

Hello everybody,
 
I'm trying to build a python external function (PyEF). It should build an histogram from a list of classes. So the input arguments will be a Ferret array, and a list of classes. With a call like :
 
histo(  SIICECOV[L=1,K=1])         , XSEQUENCE({0., 0.1, 0.2, 1.0, 2.0}) )
or
histo( XSEQUENCE(SIICECOV[L=1,K=1]), XSEQUENCE({0., 0.1, 0.2, 1.0, 2.0}) )
or
histo( XSEQUENCE(SIICECOV[L=1,K=1]), YSEQUENCE({0., 0.1, 0.2, 1.0, 2.0}) )
 
But it always fails. For instance :
 
> STAT histo( XSEQUENCE(SIICECOV[L=1,K=1]), XSEQUENCE({0., 0.1, 0.2, 1.0, 2.0}) )
**ERROR: inconsistent sizes of data regions: X axis
XSEQUENCE({0., 0.1, 0.2, 1.0, 2.0}) has 5 points (I=1:5)
expression has 9216 points (I=0001:9216)
STAT histo( XSEQUENCE(SIICECOV[L=1,K=1]), XSEQUENCE({0., 0.1, 0.2, 1.0, 2.0}) )
Command file, command group, or REPEAT execution aborted
 
 
or 
 
> STAT histo( XSEQUENCE(SIICECOV[L=1,K=1]), XYEQUENCE({0., 0.1, 0.2, 1.0, 2.0}) )
**ERROR: command syntax: XYEQUENCE({0., 0.1, 0.2, 1.0, 2.0})
unknown function "XYEQUENCE"
STAT histo( XSEQUENCE(SIICECOV[L=1,K=1]), XYEQUENCE({0., 0.1, 0.2, 1.0, 2.0}) )
Command file, command group, or REPEAT execution aborted
 
 
 
 
Before performing any computation, I cannot find a way to write an external function that accept two arguments with different shapes. Any hint or exemple ?
 
Thanks,
 
Olivier
 
The python function :
 
Example Ferret external function written in Python
'''
import numpy
import pyferret
 
def ferret_init(id):
'''Creates and returns the initialization dictionary for this PyEF'''
initdict = { "numargs" : 2, "descript": "Test function",
"argnames": ("A", "Histogram boundaries"),
}
return initdict
 
def ferret_compute(id, result, result_bad_flag, inputs, input_bad_flags):
''' Essai d'histogramme
ARG1 is the array. 
ARG2 is the list of class boundaries
'''
 
badmask = ( numpy.fabs(inputs[pyferret.ARG1] - input_bad_flags[pyferret.ARG1]) < 1.0E-5 )
goodmask = numpy.logical_not(badmask)
 
result[badmask]  = input_bad_flags[pyferret.ARG1]
result[goodmask] = inputs[pyferret.ARG1][goodmask]
 
— 
Olivier Marti  - LSCE Bât 714 p. 1049
Tel : +33 1 69 08 77 27
mailto:olivier.marti@xxxxxxxxxxxx

Attachment: smime.p7s
Description: S/MIME cryptographic signature