def analyzeReceptiveFieldSparseInputs(inputVectors, sp):
numColumns = np.product(sp.getColumnDimensions())
overlapMat = calculateInputOverlapMat(inputVectors, sp)
sortedOverlapMat = np.zeros(overlapMat.shape)
for c in range(numColumns):
sortedOverlapMat[c, :] = np.sort(overlapMat[c, :])
avgSortedOverlaps = np.flipud(np.mean(sortedOverlapMat, 0))
plt.figure()
plt.plot(avgSortedOverlaps, '-o')
plt.xlabel('sorted input vector #')
plt.ylabel('percent overlap')
plt.figure()
plt.imshow(overlapMat[:100, :], interpolation="nearest", cmap="magma")
plt.xlabel("Input Vector #")
plt.ylabel("SP Column #")
plt.colorbar()
plt.title('percent overlap')
def analyzeReceptiveFieldSparseInputs(inputVectors, sp):
numColumns = np.product(sp.getColumnDimensions())
overlapMat = calculateInputOverlapMat(inputVectors, sp)
sortedOverlapMat = np.zeros(overlapMat.shape)
for c in range(numColumns):
sortedOverlapMat[c, :] = np.sort(overlapMat[c, :])
avgSortedOverlaps = np.flipud(np.mean(sortedOverlapMat, 0))
plt.figure()
plt.plot(avgSortedOverlaps, '-o')
plt.xlabel('sorted input vector #')
plt.ylabel('percent overlap')
plt.figure()
plt.imshow(overlapMat[:100, :], interpolation="nearest", cmap="magma")
plt.xlabel("Input Vector #")
plt.ylabel("SP Column #")
plt.colorbar()
plt.title('percent overlap')