[Numpy-discussion] fixed_pt some progress and a question

Neal Becker ndbecker2@gmail....
Tue Sep 29 07:52:55 CDT 2009


I'm starting with a pure python implementation and have some progress.  
AFAICT, the only approach is to subclass ndarray and add the properties and 
behaviors I need.

I ran into one issue though.

In my function 'as_double', I need to get to the underlying 'int' array to 
pass to ldexp.  I tried using view, but it silently fails:

In [40]: obj
Out[40]: fixed_pt_array([  0,  32,  64,  96, 128])

In [41]: obj.view (int)
Out[41]: fixed_pt_array([  0,  32,  64,  96, 128])

How can I get at the underlying int array to pass to ldexp?

Here is the prototype code (far from complete!)
import numpy as np

        
def rnd (x, frac_bits, _max):
    x1 = x >> (frac_bits-1)
    if (x1 == _max):
        return x1 >> 1
    else:
        return (x1+1) >> 1

def shift_left (x, bits):
    return x << bits

def shift_right (x, bits):
    return x >> bits

def shiftup_or_rnddn (x, bits, _max, rnd_policy):
    if (bits > 0):
        return shift_left (x, bits)
    elif (bits < 0):
        return rnd_policy (x, -bits, _max)
    else:
        return x

def clip (x, _min, _max):
    if x > _max:
        return _max
    elif x < _min:
        return _min
    else:
        return x
    
class fixed_pt (object):
    def get_max(self):
        if self.is_signed:
            return (~(self.base_type(-1) << (self.total_bits-1)))
        else:
            return (~(self.base_type (-1) << self.total_bits))
        
    def get_min(self):
        if self.is_signed:
            return ((self.base_type(-1) << (self.total_bits-1)))
        else:
            return 0
        

    def __init__ (self, int_bits, frac_bits, val, scale=True, base_type=int, 
rnd_policy=rnd, overflow_policy=clip, is_signed=True):
        self.is_signed = is_signed
        self.int_bits = int_bits
        self.frac_bits = frac_bits
        self.base_type = base_type
        self.total_bits = int_bits + frac_bits
        self.rnd_policy = rnd_policy
        self._max = self.get_max ()
        self._min = self.get_min ()
        self.overflow_policy = overflow_policy
        
        if scale:
            self.val = self.overflow_policy (self.base_type 
(shiftup_or_rnddn (val, frac_bits, self._max, self.rnd_policy)), self._min, 
self._max)
            

    def as_double (self):
        return np.ldexp (self.val, -self.frac_bits)
    
    def as_base (self):
        return shiftup_or_rnddn (self.val, -self.frac_bits, self._max, 
self.rnd_policy)

    def __repr__(self):
        return "[%s <%s,%s>]" % (self.val, self.int_bits, self.frac_bits)
    
def get_max(is_signed, base_type, total_bits):
    if is_signed:
        return (~(base_type(-1) << (total_bits-1)))
    else:
        return (~(base_type (-1) << total_bits))

def get_min(is_signed, base_type, total_bits):
    if is_signed:
        return ((base_type(-1) << (total_bits-1)))
    else:
        return 0


class fixed_pt_array(np.ndarray):
    def __new__(cls, input_array, int_bits, frac_bits, scale=True, 
base_type=int, rnd_policy=rnd, overflow_policy=clip, is_signed=True):
        # Input array is an already formed ndarray instance
        # We first cast to be our class type
        obj = np.asarray(input_array, dtype=base_type).view(cls)
        # add the new attribute to the created instance
        obj.int_bits = int_bits
        obj.frac_bits = frac_bits
        obj.rnd_policy = rnd_policy
        obj.overflow_policy = overflow_policy
        obj.is_signed = is_signed
        obj.scale = scale
        obj.base_type = base_type
        obj.total_bits = int_bits + frac_bits
        obj._max = get_max(is_signed, base_type, obj.total_bits)
        obj._min = get_min(is_signed, base_type, obj.total_bits)
        if scale:
            def _scale (val):
                return overflow_policy (base_type (shiftup_or_rnddn (val, 
frac_bits, obj._max, rnd_policy)), obj._min, obj._max)
            vecfunc = np.vectorize (_scale)
            obj = vecfunc (obj)
 
        # Finally, we must return the newly created object:
        return obj
    
    def __array_finalize__(self,obj):
        # reset the attribute from passed original object
        if hasattr (obj, 'int_bits'):
            self.int_bits = obj.int_bits
            self.frac_bits = obj.frac_bits
            self.is_signed = obj.is_signed
            self.base_type = obj.base_type
            self.total_bits = obj.total_bits
            self._max = obj._max
            self._min = obj._min
            ## self._max = get_max(self.is_signed, self.base_type, 
self.total_bits)
            ## self._min = get_min(self.is_signed, self.base_type, 
self.total_bits)
        
        
        # We do not need to return anything
    ## def __getitem__ (self, index):
    ##     return fp.fixed_pt_int64_clip (self.int_bits, self.frac_bits, 
int(np.ndarray.__getitem__(self, index)))
    def as_double (self):
        def _as_double (x):
            print type(x)
            return np.ldexp (x, -self.frac_bits)
            
        return _as_double (self.view (self.base_type))
            

fp = fixed_pt (5, 5, 1)

arr = np.arange(5,dtype=int)
obj = fixed_pt_array(arr, int_bits=5, frac_bits=5)
print type(obj)





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