1 files changed, 182 insertions, 0 deletions
diff --git a/controller/fw/test_pyldpc_utils.py b/controller/fw/test_pyldpc_utils.py
new file mode 100644
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+++ b/controller/fw/test_pyldpc_utils.py
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+"""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)