def generateSimpleCoincMatrix(nCoinc=<NUM_LIT:10>, length=<NUM_LIT>, activity=<NUM_LIT:50>):
assert nCoinc*activity<=length, "<STR_LIT>"<EOL>coincMatrix = SM32(<NUM_LIT:0>, length)<EOL>coinc = numpy.zeros(length, dtype='<STR_LIT>')<EOL>for i in range(nCoinc):<EOL><INDENT>coinc[:] = <NUM_LIT:0><EOL>coinc[i*activity:(i+<NUM_LIT:1>)*activity] = <NUM_LIT:1><EOL>coincMatrix.addRow(coinc)<EOL><DEDENT>return coincMatrix<EOL>
Generate a non overlapping coincidence matrix. This is used to generate random
inputs to the temporal learner and to compare the predicted output against.

It generates a matrix of nCoinc rows, each row has length 'length' and has
a total of 'activity' bits on.

Parameters:
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nCoinc:        the number of rows to generate
length:        the length of each row
activity:      the number of ones to put into each row.