# py/pyext - python script objects for PD and MaxMSP
#
# Copyright (c) 2002-2012 Thomas Grill (gr@grrrr.org)
# For information on usage and redistribution, and for a DISCLAIMER OF ALL
# WARRANTIES, see the file, "license.txt," in this distribution.  
#

"""This is an example script for the py/pyext object's buffer support.

Pd/Max buffers can be mapped to Python arrays.
Currently, there are three implementations:
Numeric, numarray and numpy (for all of them see http://numeric.scipy.org)
"""

import sys

try:
    import pyext
except:
    print "ERROR: This script must be loaded by the PD/Max py/pyext external"

try:
    # numpy is assumed here... numeric and numarray are considered deprecated
    import numpy as N
except:
    print "Failed importing numpy module:",sys.exc_value

def mul(*args):
    # create buffer objects
    # as long as these variables live the underlying buffers are locked
    c = pyext.Buffer(args[0])
    a = pyext.Buffer(args[1])
    b = pyext.Buffer(args[2])

    commonlen = min(len(a),len(b),len(c))

    # slicing causes Python arrays (mapped to buffers) to be created
    # note the c[:] - to assign contents you must assign to a slice of the buffer
    
    c[:commonlen] = a[:commonlen]*b[:commonlen]  

def add(*args):
    c = pyext.Buffer(args[0])
    a = pyext.Buffer(args[1])
    b = pyext.Buffer(args[2])

    commonlen = min(len(a),len(b),len(c))

    # explicit casting to arrays is also possible
    c[:commonlen] = N.array(a[:commonlen],dtype=N.float32) + N.array(b[:commonlen],dtype=N.float32)

def fadein(target):
    a = pyext.Buffer(target)
    # in place operations are ok
    a *= N.arange(len(a),dtype=N.float32)/len(a)

def neg(target):
    a = pyext.Buffer(target)
    # in place transformation (see Python array ufuncs)
    N.negative(a[:],a[:])
    # must mark buffer content as dirty to update graph
    # (no explicit assignment occurred)
    a.dirty()