An instructive first step is to visualize, given the patch size and image shape, what a higher-dimensional array of patches would look like. We have a 2d array img with shape (254, 319)and a (10, 10) 2d patch. This means our output shape (before taking the mean of each “inner”...
If you have not guaranteed a contiguous and/or aligned array then be sure you understand how to access the data in the array to avoid memory and/or alignment problems. npy_intp *PyArray_DIMS(PyArrayObject *arr ) Returns a pointer to the dimensions/shape of the array. The number of ...
For awkward arrays, the input arguments to a ufunc must all have the same structure or, if shallower, be broadcastable to the deepest structure. (See above for "broadcasting.") The scalar function is applied to elements at the same positions within this structure from different input arrays. ...
channel = sp.asarray(channel)assertlen(correct_features) == channel.shape[0]# Gather mean over each channel, to get mean channel vectorchannel_mean_vec += [sp.mean(channel, axis=0)]# this vector contains mean computed over correct classifications# for each channel separatelychannel_mean_vec...