add nrRateMatchPolar() (#72)

* add nrRateMatchPolar(), until now only repetition is supported and ibil has to be disabled
* bump version to 0.4.0

py3gpp/__init__.py

@@ -18,6 +18,7 @@
 from .nrPBCHPRBS import nrPBCHPRBS
 from .nrEqualizeMMSE import nrEqualizeMMSE
 from .nrRateRecoverPolar import nrRateRecoverPolar
+from .nrRateMatchPolar import nrRateMatchPolar
 from .nrPolarDecode import nrPolarDecode
 from .nrPolarEncode import nrPolarEncode
 from .nrCRCEncode import nrCRCEncode

py3gpp/nrRateMatchPolar.py

@@ -0,0 +1,48 @@
+import numpy as np
+
+def subblock_interleaving(u):
+    N = u.shape[-1]
+    assert np.mod(N,32)==0, \
+        "length for sub-block interleaving must be a multiple of 32."
+    y = np.zeros_like(u)    
+    # Permutation according to Tab 5.4.1.1-1 in 38.212
+    perm = np.array([0, 1, 2, 4, 3, 5, 6, 7, 8, 16, 9, 17, 10, 18, 11, 19,
+                     12, 20, 13, 21, 14, 22, 15, 23, 24, 25, 26, 28, 27,
+                     29, 30, 31])
+
+    for n in range(N):
+        i = int(32*n/N)
+        j = int(perm[i] * N/32 + np.mod(n, N/32))
+        y[n] = u[j]
+
+    return y
+
+def nrRateMatchPolar(enc, K, E, ibil=False):
+    # TODO: for what is the parameter K??
+    N = enc.shape[0]
+    d = np.zeros(N, int)
+    d = enc[subblock_interleaving(np.arange(N))]
+    y = np.zeros(E, int)
+    if N <= E:
+        # repetition
+        y[:N] = d[:N]
+        for k in range(N, E):
+            y[k] += d[k%N]
+    else:
+        # TODO: implement shortening und puncturing
+        print("Error!")
+        exit()
+    if ibil == True:
+        print("Error: interleaving of coded bits is not implemented!")
+        exit()
+    return y
+
+if __name__ == '__main__':
+    import py3gpp
+    # input = np.zeros(512, int)
+    # input[0:3] = [1 , 1, 1]
+    input = np.array([1,1,0,0,0,0,1,1,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,1,1,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,0,1,1,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,0,1,1,0,0,0,1,1,1,1,0,1,1,0,0,1,1,1,0,0,1,0,0,0,0,0,1,1,0,0,1,1,0,1,1,1,1,0,0,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,1,0,0,1,0,1,1,1,1,1,0,0,0,0,1,0,1,0,1,1,1,1,0,0,0,0,1,1,1,0,1,0,0,1,1,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,1,1,0,0,1,0,0,0,1,0,0,0,1,1,1,1,1,1,0,0,0,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,1,0,0,0,1,1,0,0,1,0,1,0,1,0,0,0,0,0,1,0,1,0,0,1,1,1,1,0,0,1,0,1,1,0,1,1,0,1,1,0,1,1,1,0,1,1,0,1,0,0,1,0,1,0,1,1,0,1,0,0,0,1,0,1,0,1,0,1,1,1,1,0,1,1,0,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,1,0,1,1,1,0,1,0,0,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,1,0,0,1,0,1,0,1,0,0,1,1,1,1,1,0,0,1,0,0,0,1,0,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,0,0,1,1,1,1,0,1,1,1,0,0,1,0,0,0,0,1,0,1,1,0,1,0,1,1,1,0,0,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,0,1,1,0,1,1,0]).astype(int)
+    # out_desired = np.array([1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]).astype(int)
+    out_desired = np.array([1,1,0,0,0,0,1,1,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,1,1,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,1,1,0,1,1,0,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,0,1,0,0,0,0,0,1,1,0,0,1,1,0,1,1,1,1,0,0,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,1,0,0,1,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,0,0,0,0,1,1,0,1,0,0,0,1,1,0,0,1,0,1,0,1,0,0,1,0,1,0,0,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,0,1,0,0,1,1,1,1,0,0,1,0,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,1,1,0,1,1,0,1,1,1,0,1,1,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,1,0,1,0,1,1,0,1,0,0,0,1,0,1,0,0,1,1,0,0,1,0,0,0,1,0,0,0,1,1,0,1,0,1,1,1,1,0,1,1,0,1,1,1,0,1,1,1,1,1,0,0,0,1,0,0,0,0,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,0,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,1,0,1,1,1,0,1,1,1,0,1,0,0,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,1,0,0,1,0,1,0,1,0,0,1,1,1,1,1,0,0,1,0,0,0,1,0,0,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,1,1,0,0,1,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,0,0,1,0,1,1,0,1,0,1,1,1,0,0,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,0,1,1,0,1,1,0,1,1,0,0,0,0,1,1,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,1,1,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,1,1,0,1,1,0,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,0,1,0,0,0,0,0,1,1,0,0,1,1,0,1,1,1,1,0,0,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,1,0,0,1,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,0,0,0,0,1,1,0,1,0,0,0,1,1,0,0,1,0,1,0,1,0,0,1,0,1,0,0,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,0,1,0,0,1,1,1,1,0,0,1,0,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,1,1,0,1,1,0,1,1,1,0,1,1,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,1,0,1,0,1,1,0,1,0,0,0,1,0,1,0,0,1,1,0,0,1,0,0,0,1,0,0,0,1,1,0,1,0,1,1,1,1,0,1,1,0,1,1,1,0,1,1,1,1,1,0,0,0,1,0,0,0,0,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0]).astype(int)
+    out = nrRateMatchPolar(input, 0, 863, False)
+    assert np.array_equal(out, out_desired)

pyproject.toml

@@ -9,7 +9,7 @@ build-backend = "setuptools.build_meta"
 py3gpp = ["codes/*.csv"]
 
 [project]
-version = "0.3.6"
+version = "0.4.0"
 authors = [
     {name = "Benjamin Menküc", email = "[email protected]"},
 ]

tests/test_nrRateMatchPolar.py

@@ -0,0 +1,8 @@
+import numpy as np
+from py3gpp.nrRateMatchPolar import nrRateMatchPolar
+
+def test_nrRateMatchPolar():
+    input = np.array([1,1,0,0,0,0,1,1,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,1,1,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,1,0,0,0,1,1,0,1,1,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,0,1,1,0,0,0,1,1,1,1,0,1,1,0,0,1,1,1,0,0,1,0,0,0,0,0,1,1,0,0,1,1,0,1,1,1,1,0,0,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,1,0,0,1,0,1,1,1,1,1,0,0,0,0,1,0,1,0,1,1,1,1,0,0,0,0,1,1,1,0,1,0,0,1,1,0,0,0,1,0,0,0,1,1,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,1,1,0,0,1,0,0,0,1,0,0,0,1,1,1,1,1,1,0,0,0,1,0,0,0,0,1,1,0,1,0,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,1,0,0,0,1,1,0,0,1,0,1,0,1,0,0,0,0,0,1,0,1,0,0,1,1,1,1,0,0,1,0,1,1,0,1,1,0,1,1,0,1,1,1,0,1,1,0,1,0,0,1,0,1,0,1,1,0,1,0,0,0,1,0,1,0,1,0,1,1,1,1,0,1,1,0,1,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,1,0,1,1,1,0,1,1,1,0,1,1,1,0,1,0,0,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,1,0,0,1,0,1,0,1,0,0,1,1,1,1,1,0,0,1,0,0,0,1,0,0,1,1,1,1,1,1,1,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,0,0,1,1,1,1,0,1,1,1,0,0,1,0,0,0,0,1,0,1,1,0,1,0,1,1,1,0,0,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,0,1,1,0,1,1,0]).astype(int)
+    out_desired = np.array([1,1,0,0,0,0,1,1,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,1,1,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,1,1,0,1,1,0,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,0,1,0,0,0,0,0,1,1,0,0,1,1,0,1,1,1,1,0,0,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,1,0,0,1,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,0,0,0,0,1,1,0,1,0,0,0,1,1,0,0,1,0,1,0,1,0,0,1,0,1,0,0,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,0,1,0,0,1,1,1,1,0,0,1,0,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,1,1,0,1,1,0,1,1,1,0,1,1,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,1,0,1,0,1,1,0,1,0,0,0,1,0,1,0,0,1,1,0,0,1,0,0,0,1,0,0,0,1,1,0,1,0,1,1,1,1,0,1,1,0,1,1,1,0,1,1,1,1,1,0,0,0,1,0,0,0,0,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,0,0,1,1,1,1,1,1,1,0,0,1,1,1,0,0,1,1,1,0,1,1,1,0,1,1,1,0,1,0,0,1,1,1,0,1,0,0,1,1,0,1,1,1,0,0,1,0,0,1,0,1,0,1,0,0,1,1,1,1,1,0,0,1,0,0,0,1,0,0,1,1,1,1,1,1,1,0,0,1,0,0,1,1,1,1,0,1,1,1,0,0,1,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,0,0,1,0,1,1,0,1,0,1,1,1,0,0,0,0,1,1,0,0,1,1,1,1,0,0,1,1,1,0,0,1,1,1,1,1,1,0,0,1,1,0,1,1,0,1,1,0,1,1,0,0,0,0,1,1,0,0,1,1,1,0,1,0,0,1,1,1,0,1,0,1,1,1,0,0,1,1,1,1,0,1,0,1,1,1,1,1,1,0,1,1,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,1,1,1,1,0,1,1,0,1,1,0,0,0,1,1,0,0,0,1,1,1,1,1,0,0,1,1,1,0,0,1,0,0,0,0,0,1,1,0,0,1,1,0,1,1,1,1,0,0,1,1,1,0,0,0,0,0,1,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,1,0,0,1,0,1,1,1,1,1,0,0,0,1,1,0,0,1,1,1,1,1,1,1,0,0,0,0,0,0,1,0,1,0,1,1,1,1,0,0,0,0,1,1,0,1,0,0,0,1,1,0,0,1,0,1,0,1,0,0,1,0,1,0,0,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,0,1,0,0,1,1,1,1,0,0,1,0,1,1,1,1,1,1,0,0,0,0,1,1,0,0,0,0,1,1,0,1,1,0,1,1,0,1,1,1,0,1,1,0,1,0,0,1,0,0,0,1,1,1,0,0,0,0,1,1,1,0,0,1,0,1,0,1,1,0,1,0,0,0,1,0,1,0,0,1,1,0,0,1,0,0,0,1,0,0,0,1,1,0,1,0,1,1,1,1,0,1,1,0,1,1,1,0,1,1,1,1,1,0,0,0,1,0,0,0,0,1,1,0,1,0,1,1,1,1,1,0,1,1,1,1,1,1,0]).astype(int)
+    out = nrRateMatchPolar(input, 0, 863, False)
+    assert np.array_equal(out, out_desired), "nrRateMatchPolar() failed"