def idwt( cls, input, steps = -1, m = -1, tensor=False ):
if m == -1:
m = input.shape[0]
if len( input.shape ) == 3:
return cls.idwt3d(input,steps,m,tensor=tensor)
elif len( input.shape ) == 2:
return cls.idwt2d(input,steps,m,tensor=tensor)
else:
n = len( input )
output = input.copy()
if n == 1:
return output
if not _is_pow2( n ):
output = np.concatenate((output, [0 for i in range( minimaxpow2(n) - n)]))
if steps < 0:
steps = int(log(minimaxpow2(n), 2))
print "we gaan %i steps terug doen zwa" % steps
for i in range( steps ):
j = steps - i-1
k = len(output)/(2**j)
output[0:k] = cls.prev(output[0:k])
#print "vorige rondeeee"
return output[0:m]
def dwt( cls, input, steps = -1, tensor=False):
if len( input.shape ) == 3:
return cls.dwt3d(input,steps,tensor=tensor)
elif len( input.shape ) == 2:
return cls.dwt2d(input,steps,tensor=tensor)
else:
n = input.shape[0]
output = np.copy( input )
if n == 1:
return output
if not _is_pow2( n ):
output = np.concatenate((output, [0 for i in range( minimaxpow2(n) - n)]))
if steps < 0:
steps = int(log(minimaxpow2(n), 2))
print "we gaat %i steps doen" % steps
for i in range( steps ):
k = len(output)/(2**i)
output[0:k] = cls.next(output[0:k])
return output
def idwt3d( cls, input, steps = -1, m = -1, tensor=False ):
assert len(input.shape) == 3
n = input.shape[0]
output = np.copy( input )
if n == 1:
return output
if m < 0:
m = n
if steps < 0:
steps = int( log( minimaxpow2(n), 2) )
if not tensor:
for i in range( steps ):
j = steps - i - 1
k = len( output ) / ( 2 ** j )
output[ 0:k, 0:k, 0:k ] = cls.prev_3d( output[ 0:k, 0:k, 0:k ] )
else:
for i in range( steps ):
j = steps - i - 1
k = len( output ) / ( 2 ** j )
for p in range( n ):
for q in range( n ):
output[0:k,p,q] = cls.prev( output[0:k,p,q] )
for p in range( n ):
output[p,0:k,0:k] = cls.prev_2d( output[p, 0:k, 0:k] )
return output[ 0:m, 0:m, 0:m ]
def dwt3d( cls, input, steps = -1, tensor = False ):
assert len(input.shape) == 3
for i in input.shape:
assert _is_pow2(i)
n = input.shape[0]
output = np.copy( input )
if n == 1:
return output
if steps < 0:
steps = int( log( minimaxpow2(n), 2) )
if not tensor:
for i in range( steps ):
print "nieuwe ronde %i van %i!" % (i, steps)
k = len( output ) / ( 2 ** i )
output[ 0:k, 0:k, 0:k ] = cls.next_3d( output[ 0:k, 0:k, 0:k ] )
else:
for i in range( steps ):
k = len( output ) / (2**i)
for p in range( n ):
output[p,0:k,0:k] = cls.next_2d( output[p, 0:k, 0:k] )
for p in range( n ):
for q in range( n ):
output[0:k,p,q] = cls.next( output[0:k,p,q] )
return output
def dwt2d( cls, input, steps = -1, tensor=False ):
assert len(input.shape) == 2
n = input.shape[0]
for i in input.shape:
assert _is_pow2(i) #alleen machten van 2 so far
output = np.copy( input )
if n == 1:
return output
if steps < 0:
steps = int( log( minimaxpow2(n), 2))
print "we gaan %i steps doen" % steps
if not tensor:
for i in range( steps ):
k = len( output )/(2**i)
output[0:k,0:k] = cls.next_2d( output[0:k,0:k] )
#print "volgende rondee:)"
else:
for i in range( steps ):
k = len(output ) / (2**i)
for p in range(n):
output[p,0:k] = cls.next( output[p,0:k] )
for p in range(n):
output[0:k,p] = cls.next( output[0:k,p] )
return output
def idwt2d( cls, input, steps = -1, m = -1, tensor=False ):
assert len(input.shape) == 2
n = input.shape[0]
assert _is_pow2(n) #alleen machten van 2 so far
for i in input.shape:
assert i == n #square/cube/etc
output = np.copy( input )
if m<0:
m = n
if n == 1:
return output
if steps < 0:
steps = int(log(minimaxpow2(n), 2))
print "we gaan %i steps terugdoen" % steps
if not tensor:
for i in range( steps ):
j = steps - i - 1
k = len(output ) / (2**j)
output[0:k,0:k] = cls.prev_2d( output[0:k,0:k] )
#print "vorige ronde!"
else:
for i in range( steps ):
j = steps - i - 1
k = len(output ) / (2**j)
for p in range(n):
output[0:k,p] = cls.prev( output[0:k,p] )
for p in range(n):
output[p,0:k] = cls.prev( output[p,0:k] )
return output[0:m,0:m]
