diff options
| author | Sebastian Koslowski <koslowski@kit.edu> | 2016-04-15 21:02:51 +0200 |
|---|---|---|
| committer | Sebastian Koslowski <koslowski@kit.edu> | 2016-04-15 21:09:19 +0200 |
| commit | 8cfc8b3408916ccb156fc25102bc1d9346bc004b (patch) | |
| tree | 5c38adfedca3f4f4073d0621840ea578dd67ed4d /gr-fec/python/fec/LDPC/Generate_LDPC_matrix_functions.py | |
| parent | 036264ef5c8e2376acd426a99ca42d29390e3e2a (diff) | |
| parent | bdf85171b8a35004cdbf634f48ff696787b5fbde (diff) | |
Merge remote-tracking branch 'upstream/master' into refactoring
Diffstat (limited to 'gr-fec/python/fec/LDPC/Generate_LDPC_matrix_functions.py')
| -rw-r--r-- | gr-fec/python/fec/LDPC/Generate_LDPC_matrix_functions.py | 53 |
1 files changed, 45 insertions, 8 deletions
diff --git a/gr-fec/python/fec/LDPC/Generate_LDPC_matrix_functions.py b/gr-fec/python/fec/LDPC/Generate_LDPC_matrix_functions.py index 28eb5d1b7b..c42fee631f 100644 --- a/gr-fec/python/fec/LDPC/Generate_LDPC_matrix_functions.py +++ b/gr-fec/python/fec/LDPC/Generate_LDPC_matrix_functions.py @@ -432,7 +432,7 @@ def greedy_upper_triangulation(H, verbose=0): if verbose: print '--- Error: nonsingular phi matrix not found.' -def inv_mod2(squareMatrix): +def inv_mod2(squareMatrix, verbose=0): """ Calculates the mod 2 inverse of a matrix. """ @@ -613,7 +613,7 @@ def get_best_matrix(H, numIterations=100, verbose=False): print 'greedy_upper_triangulation error: ', e else: if ret: - [betterH, gap, t] + [betterH, gap, t] = ret else: continue @@ -636,14 +636,18 @@ def get_best_matrix(H, numIterations=100, verbose=False): print 'for encoding.' return -def getSystematicGmatrix(H): +def getSystematicGmatrix(GenMatrix): """ This function finds the systematic form of the generator - matrix G. The form is G = [I P] where I is an identity matrix - and P is the parity submatrix. If the H matrix provided - is not full rank, then dependent rows will be deleted. + matrix GenMatrix. This form is G = [I P] where I is an identity + matrix and P is the parity submatrix. If the GenMatrix matrix + provided is not full rank, then dependent rows will be deleted. + + This function does not convert parity check (H) matrices to the + generator matrix format. Use the function getSystematicGmatrixFromH + for that purpose. """ - tempArray = H.copy() + tempArray = GenMatrix.copy() numRows = tempArray.shape[0] numColumns = tempArray.shape[1] limit = numRows @@ -675,9 +679,42 @@ def getSystematicGmatrix(H): if found == False: # push the row of 0s to the bottom, and move the bottom # rows up (sort of a rotation thing) - tempArray = moveRowToBottom(i,tempArray) + tempArray = move_row_to_bottom(i,tempArray) # decrease limit since we just found a row of 0s limit -= 1 # the rows below i are the dependent rows, which we discard G = tempArray[0:i,:] return G + +def getSystematicGmatrixFromH(H, verbose=False): + """ + If given a parity check matrix H, this function returns a + generator matrix G in the systematic form: G = [I P] + where: I is an identity matrix, size k x k + P is the parity submatrix, size k x (n-k) + If the H matrix provided is not full rank, then dependent rows + will be deleted first. + """ + if verbose: + print 'received H with size: ', H.shape + + # First, put the H matrix into the form H = [I|m] where: + # I is (n-k) x (n-k) identity matrix + # m is (n-k) x k + # This part is just copying the algorithm from getSystematicGmatrix + tempArray = getSystematicGmatrix(H) + + # Next, swap I and m columns so the matrix takes the forms [m|I]. + n = H.shape[1] + k = n - H.shape[0] + I_temp = tempArray[:,0:(n-k)] + m = tempArray[:,(n-k):n] + newH = concatenate((m,I_temp),axis=1) + + # Now the submatrix m is the transpose of the parity submatrix, + # i.e. H is in the form H = [P'|I]. So G is just [I|P] + k = m.shape[1] + G = concatenate((identity(k),m.T),axis=1) + if verbose: + print 'returning G with size: ', G.shape + return G
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