Finishing up freq meas
This commit is contained in:
parent
5effadcbaf
commit
ca01d52a86
14 changed files with 296 additions and 47 deletions
182
controller/fw/src/test_pyldpc_utils.py
Normal file
182
controller/fw/src/test_pyldpc_utils.py
Normal file
|
|
@ -0,0 +1,182 @@
|
|||
"""Conversion tools."""
|
||||
import math
|
||||
import numbers
|
||||
import numpy as np
|
||||
import scipy
|
||||
from scipy.stats import norm
|
||||
pi = math.pi
|
||||
|
||||
|
||||
def int2bitarray(n, k):
|
||||
"""Change an array's base from int (base 10) to binary (base 2)."""
|
||||
binary_string = bin(n)
|
||||
length = len(binary_string)
|
||||
bitarray = np.zeros(k, 'int')
|
||||
for i in range(length - 2):
|
||||
bitarray[k - i - 1] = int(binary_string[length - i - 1])
|
||||
|
||||
return bitarray
|
||||
|
||||
|
||||
def bitarray2int(bitarray):
|
||||
"""Change array's base from binary (base 2) to int (base 10)."""
|
||||
bitstring = "".join([str(i) for i in bitarray])
|
||||
|
||||
return int(bitstring, 2)
|
||||
|
||||
|
||||
def binaryproduct(X, Y):
|
||||
"""Compute a matrix-matrix / vector product in Z/2Z."""
|
||||
A = X.dot(Y)
|
||||
try:
|
||||
A = A.toarray()
|
||||
except AttributeError:
|
||||
pass
|
||||
return A % 2
|
||||
|
||||
|
||||
def gaussjordan(X, change=0):
|
||||
"""Compute the binary row reduced echelon form of X.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
X: array (m, n)
|
||||
change : boolean (default, False). If True returns the inverse transform
|
||||
|
||||
Returns
|
||||
-------
|
||||
if `change` == 'True':
|
||||
A: array (m, n). row reduced form of X.
|
||||
P: tranformations applied to the identity
|
||||
else:
|
||||
A: array (m, n). row reduced form of X.
|
||||
|
||||
"""
|
||||
A = np.copy(X)
|
||||
m, n = A.shape
|
||||
|
||||
if change:
|
||||
P = np.identity(m).astype(int)
|
||||
|
||||
pivot_old = -1
|
||||
for j in range(n):
|
||||
filtre_down = A[pivot_old+1:m, j]
|
||||
pivot = np.argmax(filtre_down)+pivot_old+1
|
||||
|
||||
if A[pivot, j]:
|
||||
pivot_old += 1
|
||||
if pivot_old != pivot:
|
||||
aux = np.copy(A[pivot, :])
|
||||
A[pivot, :] = A[pivot_old, :]
|
||||
A[pivot_old, :] = aux
|
||||
if change:
|
||||
aux = np.copy(P[pivot, :])
|
||||
P[pivot, :] = P[pivot_old, :]
|
||||
P[pivot_old, :] = aux
|
||||
|
||||
for i in range(m):
|
||||
if i != pivot_old and A[i, j]:
|
||||
if change:
|
||||
P[i, :] = abs(P[i, :]-P[pivot_old, :])
|
||||
A[i, :] = abs(A[i, :]-A[pivot_old, :])
|
||||
|
||||
if pivot_old == m-1:
|
||||
break
|
||||
|
||||
if change:
|
||||
return A, P
|
||||
return A
|
||||
|
||||
|
||||
def binaryrank(X):
|
||||
"""Compute rank of a binary Matrix using Gauss-Jordan algorithm."""
|
||||
A = np.copy(X)
|
||||
m, n = A.shape
|
||||
|
||||
A = gaussjordan(A)
|
||||
|
||||
return sum([a.any() for a in A])
|
||||
|
||||
|
||||
def f1(y, sigma):
|
||||
"""Compute normal density N(1,sigma)."""
|
||||
f = norm.pdf(y, loc=1, scale=sigma)
|
||||
return f
|
||||
|
||||
|
||||
def fm1(y, sigma):
|
||||
"""Compute normal density N(-1,sigma)."""
|
||||
|
||||
f = norm.pdf(y, loc=-1, scale=sigma)
|
||||
return f
|
||||
|
||||
|
||||
def bitsandnodes(H):
|
||||
"""Return bits and nodes of a parity-check matrix H."""
|
||||
if type(H) != scipy.sparse.csr_matrix:
|
||||
bits_indices, bits = np.where(H)
|
||||
nodes_indices, nodes = np.where(H.T)
|
||||
else:
|
||||
bits_indices, bits = scipy.sparse.find(H)[:2]
|
||||
nodes_indices, nodes = scipy.sparse.find(H.T)[:2]
|
||||
bits_histogram = np.bincount(bits_indices)
|
||||
nodes_histogram = np.bincount(nodes_indices)
|
||||
|
||||
return bits_histogram, bits, nodes_histogram, nodes
|
||||
|
||||
|
||||
def incode(H, x):
|
||||
"""Compute Binary Product of H and x."""
|
||||
return (binaryproduct(H, x) == 0).all()
|
||||
|
||||
|
||||
def gausselimination(A, b):
|
||||
"""Solve linear system in Z/2Z via Gauss Gauss elimination."""
|
||||
if type(A) == scipy.sparse.csr_matrix:
|
||||
A = A.toarray().copy()
|
||||
else:
|
||||
A = A.copy()
|
||||
b = b.copy()
|
||||
n, k = A.shape
|
||||
|
||||
for j in range(min(k, n)):
|
||||
listedepivots = [i for i in range(j, n) if A[i, j]]
|
||||
if len(listedepivots):
|
||||
pivot = np.min(listedepivots)
|
||||
else:
|
||||
continue
|
||||
if pivot != j:
|
||||
aux = (A[j, :]).copy()
|
||||
A[j, :] = A[pivot, :]
|
||||
A[pivot, :] = aux
|
||||
|
||||
aux = b[j].copy()
|
||||
b[j] = b[pivot]
|
||||
b[pivot] = aux
|
||||
|
||||
for i in range(j+1, n):
|
||||
if A[i, j]:
|
||||
A[i, :] = abs(A[i, :]-A[j, :])
|
||||
b[i] = abs(b[i]-b[j])
|
||||
|
||||
return A, b
|
||||
|
||||
|
||||
def check_random_state(seed):
|
||||
"""Turn seed into a np.random.RandomState instance
|
||||
Parameters
|
||||
----------
|
||||
seed : None | int | instance of RandomState
|
||||
If seed is None, return the RandomState singleton used by np.random.
|
||||
If seed is an int, return a new RandomState instance seeded with seed.
|
||||
If seed is already a RandomState instance, return it.
|
||||
Otherwise raise ValueError.
|
||||
"""
|
||||
if seed is None or seed is np.random:
|
||||
return np.random.mtrand._rand
|
||||
if isinstance(seed, numbers.Integral):
|
||||
return np.random.RandomState(seed)
|
||||
if isinstance(seed, np.random.RandomState):
|
||||
return seed
|
||||
raise ValueError('%r cannot be used to seed a numpy.random.RandomState'
|
||||
' instance' % seed)
|
||||
Loading…
Add table
Add a link
Reference in a new issue