Changes between Version 34 and Version 35 of coding_rules

Timestamp:

08/21/20 17:02:04 (5 years ago)

Author:

jdquinn

Comment:

Clarification on np.where

coding_rules

@@ -139 +139 @@
 ||= '''MATLAB''' =||= '''!NumPy''' =||= '''Notes''' =||
 || `<<cell_array>>{:}`  || `<<np.ndarray>>.flatten()` || Flatten a MATLAB cell array or !NumPy `ndarray`. ||
-|| `find(a>0.5)` || `np.where(a>0.5)[0]`[[BR]][[BR]]`np.where(a>0.5,a,a)[0]` || Find the indices where (a > 0.5).[[BR]][[BR]]When only the {{{condition}}} parameters is provided, this function is a shorthand for `np.asarray(condition).nonzero()`.[[BR]][[BR]]Note that `a` must be of type `np.array` (or one of its subclasses): a {{{list}}} will not automatically be cast.[[BR]][[BR]]See also: https://numpy.org/doc/stable/reference/generated/numpy.where.html ||
+|| `find(a>0.5)` || `np.where(a>0.5)[0]` || Find the indices where (a > 0.5).[[BR]][[BR]]When only the {{{condition}}} parameter is provided, this function is a shorthand for `np.asarray(condition).nonzero()`.[[BR]][[BR]]See also: https://numpy.org/doc/stable/reference/generated/numpy.where.html[[BR]][[BR]]NOTE:[[BR]]-`a` must be of type `np.array` (or one of its subclasses): a {{{list}}} will not automatically be cast.[[BR]]-Returns a tuple of arrays of indices, one for each dimension of the input array. Thus, when the input array is 1D, the indices can be retrieved simply by addressing the first element of the result (as in the example). ||
 || `find('cond1'&'cond2')` || `np.where(np.logical_and.reduce(('cond1','cond2'))[0]` || Find the indices where `'cond1'` and `'cond2'` are met.[[BR]][[BR]]The same protocol can be followed for MATLAB's `|` by instead using `logical_or`.[[BR]][[BR]]More than two conditions may be compounded. ||
 || `v=nonzeros(A)` || `v=A[np.nonzero(A)]` || Find the values of the nonzero elements ||