Fix nrPolarDecode() and add more tests (#71)

* fix minsum function in nrPolarDecode()
* fix wrong bpsk mod
* add test_nrPolarDecode.py and test_nrPolarEncode_nrPolarDecode.py
* bump version to 0.3.6

py3gpp/nrPolarDecode.py

@@ -1,18 +1,19 @@
 import numpy as np
-from .helper import generate_5g_ranking
-from .helper import polar_precode_interleave
+from py3gpp.helper import generate_5g_ranking
+from py3gpp.helper import polar_precode_interleave
 
 # very simple successive cancellation decoder
 def Polar_SC_decoder(N, frozen_pos, r):
-    n = np.log2(N).astype("int")
+    n = np.log2(N).astype(int)
     L = np.zeros((n + 1, N))
     ucap = np.zeros((n + 1, N))
-    ns = np.zeros(2 * N - 1, "int")
+    ns = np.zeros(2 * N - 1, int)  # node state vector
     L[0, :] = r
     node = depth = done = 0
     while done == 0:
+        # print(f'd = {depth}, node = {node}')
         if depth == n:
-            ucap[n, node] = 0 if (L[n, node] >= 0 or node in frozen_pos) else 1
+            ucap[n, node] = 0 if ((L[n, node] >= 0) or (node in frozen_pos)) else 1
             if node == N - 1:
                 done = 1
             else:
@@ -31,21 +32,24 @@ def Polar_SC_decoder(N, frozen_pos, r):
                 node = lnode  # go to left node
                 depth += 1
                 L[depth, ctemp * node : ctemp * (node + 1)] = (
-                    (1 - 2 * (a > 0)) * (1 - 2 * (b > 0)) * np.max((np.abs(a), np.abs(b)))
+                    # cannot use np.sign() because np.sign(0) = 0 !!
+                    (1 - 2*(a < 0)) * (1 - 2*(b < 0)) * np.minimum(np.abs(a), np.abs(b))  # minsum-function
                 )
             elif ns[npos] == 1:
                 ucapn = ucap[depth + 1, ctemp * lnode : ctemp * (lnode + 1)]  # incoming decisions from left child
                 node = rnode  # go to right node
                 depth += 1
-                L[depth, ctemp * node : ctemp * (node + 1)] = b + (1 - 2 * ucapn) * a
-            else:
+                L[depth, ctemp * node : ctemp * (node + 1)] = b + (1 - 2 * ucapn) * a # g-function
+            elif ns[npos] == 2:
                 ucapl = ucap[depth + 1, ctemp * lnode : ctemp * (lnode + 1)]
                 ucapr = ucap[depth + 1, ctemp * rnode : ctemp * (rnode + 1)]
                 ucap[depth, temp * node : temp * (node + 1)] = np.append(np.mod(ucapl + ucapr, 2), ucapr)  # combine
                 node = node // 2  # go to parent node
                 depth -= 1
+            else:
+                assert False
             ns[npos] += 1
-    return ucap.astype("int")[n, :]
+    return ucap.astype(int)[n, :]
 
 
 # rec: Rate-recovered input, LLRs, length must be power of two
@@ -69,9 +73,50 @@ def nrPolarDecode(rec, K, E, L, padCRC=False, nmax=9, iil=True, CRClen=24):
     if iil:
         # deinterleave
         p_IL = polar_precode_interleave(K)
-        decoded2 = np.empty(decoded.shape, "int")
+        decoded2 = np.empty(decoded.shape, int)
         np.put(decoded2, p_IL, decoded)
     else:
         decoded2 = decoded
 
     return decoded2
+
+if __name__ == '__main__':
+    import py3gpp
+    import sionna
+    nmax = 9
+    K = 100
+
+    # --- TESTCASE1 ---
+    payload = np.ones(K).astype(int)
+    cw = py3gpp.nrPolarEncode(payload, 512, nmax=nmax, iil=False)
+    cw_desired = np.array([0,1,0,0,0,1,1,0,1,1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,0,0,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,1,1,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,1,0,1,0,1,1,0,1,0,1,0,1,0,1,0,1,1,0,1,1,0,1,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,0,1,0,1,1,0,0,0,0,0,0,1,1,0,1,0,1,0,0,0,0,1,0,1,1,0,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,0,1,1,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,1,1,0,0,0,0,1,0,1,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,1,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,0,1,0,0,1,1,0,0,0,0,0,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,0,0,1,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,0,1,0,1,0,0,1,1,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,1,1,1,0,0,0,0,1,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,1,1,0,1,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,1,0,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1])
+    assert np.array_equal(cw, cw_desired)
+
+    cw_llr = -2*cw.astype(np.float64) + 1
+    cw_llr[100:300] = 0  # introduce some errors
+
+    frozen_pos, info_pos = sionna.fec.polar.utils.generate_5g_ranking(K, 2**nmax)
+    decoder = sionna.fec.polar.decoding.PolarSCLDecoder(frozen_pos, 2**nmax, list_size=8, crc_degree='CRC24C', cpu_only=True, use_fast_scl=False)
+    payload_decoded_sionna = np.array(decoder(np.expand_dims(-cw_llr, 0))[0], 'int')
+    print(payload_decoded_sionna)
+    assert np.array_equal(payload, payload_decoded_sionna)
+
+    payload_decoded = py3gpp.nrPolarDecode(cw_llr, K, 512, 10, nmax = nmax, iil = False)
+    assert payload_decoded.shape[0] == K
+    print(payload_decoded)
+    assert np.array_equal(payload, payload_decoded)
+
+    # --- TESTCASE2 ---
+    payload = np.array([1,0,1,1,0,0,1,0,1,1,0,0,1,1,1,1,1,0,1,0,1,1,0,1,0,1,1,1,1,1,0,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,0,0,0,0,1,1,0,1,0,1,0,0,0,1,1,1,0,0,1,1,0,0,0,1,0,0,1,0,1,1,0,1,0,1,1,0,1,0,0,1,1,1,1,0,1,1,0,1,0,0,1,0,1,1])
+    cw = np.array([0,0,1,1,0,0,1,0,1,0,1,0,0,1,0,0,0,0,0,1,1,1,1,1,1,0,0,1,0,1,0,0,0,1,1,1,1,0,1,1,0,0,0,1,1,0,0,0,1,0,0,0,0,1,0,0,1,1,1,1,1,0,1,0,1,1,1,0,1,0,1,0,0,0,1,0,1,0,0,1,1,0,1,0,1,1,1,0,0,1,1,1,0,0,0,0,1,0,0,1,1,1,1,1,1,0,1,0,1,0,0,1,0,0,0,0,1,0,0,1,0,0,1,0,0,0,1,0,0,1,1,0,0,1,0,0,1,1,0,0,0,0,0,1,1,1,0,1,0,0,0,0,0,1,1,0,1,0,0,0,0,1,1,1,1,0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,1,1,1,0,0,1,0,1,0,0,1,1,1,0,1,1,1,1,0,0,0,1,0,0,1,1,0,0,0,1,1,0,0,0,0,1,1,0,0,0,1,1,0,0,1,0,0,1,1,1,0,0,1,0,0,1,1,0,0,1,1,0,0,1,0,0,1,1,1,0,0,0,1,0,1,1,0,0,0,0,1,1,1,0,1,1,0,0,1,1,0,1,0,0,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,0,0,0,1,0,0,0,1,1,1,0,0,1,0,0,0,1,1,1,0,1,1,0,1,1,0,0,1,1,0,1,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,0,0,1,1,0,0,1,0,1,0,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,0,1,0,1,0,1,0,1,1,0,1,0,0,0,1,0,1,1,0,0,0,1,0,1,0,1,0,0,0,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,0,1,1,1,0,1,1,1,1,1,0,1,1,0,1,1,1,0,1,1,1,0,0,0,1,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,1,0,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,0,1,1,1,1,1,0,0,0,0,1,1,1,1,0,1,0,1,0,0,0,0,0,0,0,1,1,1,0,1])
+    cw_llr = -2*cw.astype(np.float64) + 1
+    cw_llr[100:300] = 0  # introduce some errors
+
+    payload_decoded_sionna = np.array(decoder(np.expand_dims(-cw_llr, 0))[0], 'int')
+    print(payload_decoded_sionna)
+    assert np.array_equal(payload_decoded_sionna, payload)
+
+    payload_decoded = py3gpp.nrPolarDecode(cw_llr, K, 512, 10, nmax = nmax, iil = False)
+    assert payload_decoded.shape[0] == K
+    print(payload_decoded)
+    assert np.array_equal(payload_decoded, payload)

py3gpp/nrPolarEncode.py

@@ -4,6 +4,7 @@
 
 def nrPolarEncode(payload, E, nmax = 9 , iil = False):
     K = payload.shape[0]
+    assert not (iil and K > 164), "iil is not supported for K > 164"
     _, info_pos = generate_5g_ranking(k = K, n = 2 ** nmax)
     N = 2 ** nmax
     u = np.zeros(N).astype(int)

pyproject.toml

@@ -9,7 +9,7 @@ build-backend = "setuptools.build_meta"
 py3gpp = ["codes/*.csv"]
 
 [project]
-version = "0.3.5"
+version = "0.3.6"
 authors = [
     {name = "Benjamin Menküc", email = "benjamin@menkuec.de"},
 ]

tests/test_nrPolarDecode.py

@@ -0,0 +1,31 @@
+import numpy as np
+import pytest
+from py3gpp.nrPolarDecode import nrPolarDecode
+
+def test_nrPolarDecode():
+    nmax = 9
+    K = 100
+
+    # --- TESTCASE1 ---
+    payload = np.ones(K).astype(int)
+    cw = np.array([0,1,0,0,0,1,1,0,1,1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,0,0,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,1,1,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,1,0,1,0,1,1,0,1,0,1,0,1,0,1,0,1,1,0,1,1,0,1,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,0,1,0,1,1,0,0,0,0,0,0,1,1,0,1,0,1,0,0,0,0,1,0,1,1,0,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,0,1,1,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,1,1,0,0,0,0,1,0,1,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,1,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,0,1,0,0,1,1,0,0,0,0,0,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,0,0,1,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,0,1,0,1,0,0,1,1,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,1,1,1,0,0,0,0,1,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,1,1,0,1,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,1,0,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1])
+    cw_llr = -2*cw.astype(np.float64) + 1
+    cw_llr[100:300] = 0  # introduce some errors
+
+    payload_decoded = nrPolarDecode(cw_llr, K, 512, 10, nmax = nmax, iil = False)
+    assert payload_decoded.shape[0] == K
+    assert np.array_equal(payload, payload_decoded)
+
+    # --- TESTCASE2 ---
+    payload = np.array([1,0,1,1,0,0,1,0,1,1,0,0,1,1,1,1,1,0,1,0,1,1,0,1,0,1,1,1,1,1,0,0,0,1,1,1,1,0,0,1,1,0,0,1,1,1,0,0,0,0,1,1,0,1,0,1,0,0,0,1,1,1,0,0,1,1,0,0,0,1,0,0,1,0,1,1,0,1,0,1,1,0,1,0,0,1,1,1,1,0,1,1,0,1,0,0,1,0,1,1])
+    cw = np.array([0,0,1,1,0,0,1,0,1,0,1,0,0,1,0,0,0,0,0,1,1,1,1,1,1,0,0,1,0,1,0,0,0,1,1,1,1,0,1,1,0,0,0,1,1,0,0,0,1,0,0,0,0,1,0,0,1,1,1,1,1,0,1,0,1,1,1,0,1,0,1,0,0,0,1,0,1,0,0,1,1,0,1,0,1,1,1,0,0,1,1,1,0,0,0,0,1,0,0,1,1,1,1,1,1,0,1,0,1,0,0,1,0,0,0,0,1,0,0,1,0,0,1,0,0,0,1,0,0,1,1,0,0,1,0,0,1,1,0,0,0,0,0,1,1,1,0,1,0,0,0,0,0,1,1,0,1,0,0,0,0,1,1,1,1,0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,1,1,1,0,0,1,0,1,0,0,1,1,1,0,1,1,1,1,0,0,0,1,0,0,1,1,0,0,0,1,1,0,0,0,0,1,1,0,0,0,1,1,0,0,1,0,0,1,1,1,0,0,1,0,0,1,1,0,0,1,1,0,0,1,0,0,1,1,1,0,0,0,1,0,1,1,0,0,0,0,1,1,1,0,1,1,0,0,1,1,0,1,0,0,1,0,0,0,1,1,1,1,1,1,1,1,0,1,1,0,1,1,1,0,0,0,1,0,0,0,1,1,1,0,0,1,0,0,0,1,1,1,0,1,1,0,1,1,0,0,1,1,0,1,0,1,1,0,0,1,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,0,0,1,1,0,0,1,0,1,0,1,1,1,0,0,0,0,1,1,1,1,1,1,1,1,0,0,1,0,1,0,1,0,1,1,0,1,0,0,0,1,0,1,1,0,0,0,1,0,1,0,1,0,0,0,1,1,1,0,1,1,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,0,1,1,1,0,1,1,1,1,1,0,1,1,0,1,1,1,0,1,1,1,0,0,0,1,0,1,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,1,0,1,1,1,0,1,1,1,1,0,0,1,0,1,0,1,0,1,1,1,1,1,0,0,0,0,1,1,1,1,0,1,0,1,0,0,0,0,0,0,0,1,1,1,0,1])
+    cw_llr = -2*cw.astype(np.float64) + 1
+    cw_llr[100:300] = 0  # introduce some errors
+
+    payload_decoded = nrPolarDecode(cw_llr, K, 512, 10, nmax = nmax, iil = False)
+    assert payload_decoded.shape[0] == K
+    assert np.array_equal(payload_decoded, payload)
+
+
+if __name__ == '__main__':
+    test_nrPolarDecode()

tests/test_nrPolarEncode_nrPolarDecode.py

@@ -0,0 +1,69 @@
+import numpy as np
+import pytest
+from py3gpp.nrPolarEncode import nrPolarEncode
+from py3gpp.nrPolarDecode import nrPolarDecode
+
+@pytest.mark.parametrize('K', [100, 151, 200])
+@pytest.mark.parametrize('nmax', [9, 10])
+@pytest.mark.parametrize('iil', [True, False])
+def test_nrPolarEncode_nrPolarDecode_generic(K, nmax, iil, repetitions = 100):
+    for _ in np.arange(repetitions):
+        if iil and K > 164:
+            # print("skipping test, because iil is not supported for K > 164")
+            continue
+        payload = np.random.randint(2, size=K)
+        cw = nrPolarEncode(payload, 2**nmax, nmax=nmax, iil=iil)
+
+        cw_llr = -2*cw.astype(np.float64) + 1
+        if K < 150:
+            cw_llr[100:300] = 0  # introduce some errors
+        else:
+            cw_llr[100:200] = 0  # introduce some errors
+
+        payload_decoded = nrPolarDecode(cw_llr, K, 2**nmax, 10, nmax = nmax, iil = iil)
+        assert payload_decoded.shape[0] == K
+        assert np.array_equal(payload, payload_decoded)
+
+def test_nrPolarEncode_nrPolarDecode_fixed():
+    nmax = 9
+    K = 100
+    payload = np.ones(K).astype(int)
+
+    # --- TESTCASE 1 ---
+    for iil in [True, False]:
+        cw = nrPolarEncode(payload, 512, nmax=nmax, iil=iil)
+        if iil:
+            cw_desired = np.array([0,1,0,0,0,1,1,0,1,1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,0,0,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,1,1,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,1,0,1,0,1,1,0,1,0,1,0,1,0,1,0,1,1,0,1,1,0,1,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,0,1,0,1,1,0,0,0,0,0,0,1,1,0,1,0,1,0,0,0,0,1,0,1,1,0,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,0,1,1,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,1,1,0,0,0,0,1,0,1,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,1,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,0,1,0,0,1,1,0,0,0,0,0,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,0,0,1,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,0,1,0,1,0,0,1,1,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,1,1,1,0,0,0,0,1,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,1,1,0,1,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,1,0,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1])
+        else:
+            cw_desired = np.array([0,1,0,0,0,1,1,0,1,1,0,1,0,0,1,0,0,0,1,0,1,0,0,0,0,0,1,1,1,1,0,1,1,1,0,1,1,0,1,1,1,1,1,1,0,0,0,1,1,0,1,0,1,0,1,1,1,1,1,1,1,1,1,1,0,0,1,0,1,1,1,0,0,0,1,0,1,1,0,0,1,1,0,1,0,1,1,0,1,0,1,0,1,0,1,0,1,1,0,1,1,0,1,0,0,1,1,0,0,1,1,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,1,0,0,1,1,1,0,1,0,1,1,0,0,0,0,0,0,1,1,0,1,0,1,0,0,0,0,1,0,1,1,0,0,1,0,1,0,1,0,1,0,0,0,1,0,1,1,0,1,0,1,1,1,1,0,0,1,0,0,0,0,0,0,1,0,0,0,0,1,0,1,0,0,1,1,0,0,0,0,1,0,1,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,0,1,1,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0,0,1,0,1,0,0,1,1,0,0,0,0,0,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,0,0,1,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,0,1,0,1,0,0,1,1,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,1,1,1,0,0,0,0,1,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,1,1,0,1,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,1,0,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1])
+        assert np.array_equal(cw, cw_desired)
+
+        cw_llr = -2*cw.astype(np.float64) + 1
+        cw_llr[100:300] = 0  # introduce some errors
+
+        payload_decoded = nrPolarDecode(cw_llr, K, 512, 10, nmax = nmax, iil = iil)
+        assert payload_decoded.shape[0] == K
+        assert np.array_equal(payload, payload_decoded)
+
+    payload = np.ones(100).astype(int)
+    payload[:10] = 0
+
+    # --- TESTCASE 2 ---
+    for iil in [True, False]:
+        cw = nrPolarEncode(payload, 512, nmax=nmax, iil=iil)
+        if iil:
+            cw_desired = np.array([0,1,0,1,1,1,0,0,0,1,1,0,0,0,1,0,1,1,0,0,1,1,0,1,0,1,1,1,0,0,1,0,1,0,0,1,1,1,1,0,0,0,0,1,1,1,1,0,0,0,0,1,0,0,0,1,1,1,1,0,1,1,1,1,0,1,0,0,1,0,1,1,0,0,0,1,1,1,0,0,0,1,0,0,1,1,0,0,0,1,1,0,0,1,0,1,1,1,1,0,0,0,0,0,0,0,0,0,1,0,0,1,1,1,1,1,1,0,0,1,1,0,0,1,0,0,0,1,1,0,0,0,0,1,1,1,1,1,0,1,0,0,0,0,1,0,0,0,1,1,1,1,0,1,0,1,1,0,0,1,0,0,0,1,0,0,0,0,1,1,1,1,1,0,0,1,0,0,0,0,0,1,1,0,1,0,0,1,0,0,0,1,0,1,1,0,1,1,1,1,0,1,0,1,0,0,0,1,1,1,1,1,0,0,0,1,1,0,1,1,0,0,0,1,1,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,1,0,0,1,1,0,1,0,1,1,1,0,0,1,1,1,1,0,1,1,1,0,0,0,1,1,0,0,0,1,1,1,0,0,0,1,1,1,1,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,0,0,1,0,1,1,0,1,0,0,0,0,0,1,1,0,1,0,1,0,1,1,1,0,1,0,1,1,1,0,1,0,0,1,1,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,0,1,0,1,1,0,1,1,0,0,0,0,0,1,1,0,0,1,1,1,1,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,0,1,0,0,0,0,0,0,1,0,1,1,1,1,0,0,0,0,0,0,0,0,1,1,1,1,1,1,0,0,1,0,0,0,0,0,0,1,1,1,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1])
+        else:
+            cw_desired = np.array([0,1,1,0,1,1,0,1,1,0,1,0,1,1,0,0,1,1,1,1,1,1,0,0,1,0,1,1,1,1,0,0,0,0,0,0,1,1,1,1,0,1,1,1,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,1,0,1,0,1,0,1,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1,0,1,0,1,1,0,0,0,0,1,1,1,0,1,1,1,0,0,1,1,1,0,0,0,1,0,1,1,1,0,1,1,1,1,1,1,1,1,0,1,1,0,1,1,0,0,0,0,1,1,1,1,0,1,0,1,1,1,1,1,0,1,0,0,1,0,1,1,1,1,0,0,0,0,0,0,1,1,0,0,1,0,1,1,1,1,0,0,1,0,1,1,1,1,1,1,1,1,1,1,1,0,0,1,0,0,0,0,1,0,0,0,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,0,1,0,0,1,0,0,1,0,0,1,0,1,0,0,1,1,0,0,0,0,0,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,0,0,1,0,0,0,1,1,1,1,0,1,1,1,1,1,1,1,0,1,1,1,1,1,1,0,1,1,1,1,1,0,1,0,1,0,1,0,1,1,0,1,1,1,1,1,1,1,0,1,1,1,0,1,0,1,0,0,1,1,1,1,0,0,0,1,0,0,0,1,1,0,0,0,1,1,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1,0,0,1,1,1,1,0,0,0,0,1,0,1,0,0,0,0,0,1,0,1,1,0,1,0,0,0,0,1,1,1,1,1,1,0,0,1,1,0,1,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,1,1,1,0,1,1,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1])
+        assert np.array_equal(cw, cw_desired)
+
+        cw_llr = -2*cw.astype(np.float64) + 1
+        cw_llr[100:300] = 0  # introduce some errors
+
+        payload_decoded = nrPolarDecode(cw_llr, K, 512, 10, nmax = nmax, iil = iil)
+        assert payload_decoded.shape[0] == K
+        assert np.array_equal(payload, payload_decoded)
+
+if __name__ == '__main__':
+    # test_nrPolarEncode_nrPolarDecode_fixed()
+    test_nrPolarEncode_nrPolarDecode_generic(K = 200, nmax = 9, iil = False, repetitions = 100)