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Starting with Pelican

Introduction

Hi!

This is my first rst post!

And this is a link to a page

But does it format Matlab code?

>> y = pitchfilter(d,sr);
>> soundsc(y,sr)
>> soundsc(d,sr)
>> soundsc(y,sr)
>> y = pitchfilter(d,sr);
>> y = pitchfilter(d,sr);
>> soundsc(y,sr)
>> max(abs(y))

ans =

    0.1631

>> max(abs(d))

ans =

    0.2468

>> wavwrite(y, sr, '~/Downloads/progressonhistogramequalization/nr1ex_w+pitchfilt.wav');
>> print -dpdf ~/Downloads/progressonhistogramequalization/nr1ex_w+pitchfilt.pdf

We will see!

Here's an actual matlab function;

function Y = map_vals(X,vmap)
% Y = map_vals(X,vmap)
%     X is a vector, map is two rows indicating input, output pairs
% 2014-04-29 Dan Ellis dpwe@ee.columbia.edu

% Just run on a vector
% figure slopes
gap = diff(vmap, 1, 2);
% repeat final gap on both src and dst rows
gap = [gap, gap(:,end)];
% Don't allow zero (or negative?) gaps
gap(find(gap <= 0)) = eps;
% do mapping.  1+ for Matlab indexing later on
Xix = 1 + max(0, sum(bsxfun(@gt, X', vmap(1,:)), 2)-1);
Xdelta = (X - vmap(1, Xix))./gap(1, Xix);
Y = vmap(2, Xix) + Xdelta.*gap(2, Xix);

How about that?

Does it do nicer with python?

def map_vals(X, vmap):
    """ X is a vector, map is two rows indicating input, output pairs """
    if len(np.shape(X)) > 1:
        # If X is a matrix, run separately on each row
        return np.array([map_vals(XX, vmap) for XX in X])
    else:
        # Just run on a vector
        # figure slopes
        gap = np.diff(vmap)
        # repeat final gap on both src and dst rows
        gap = np.c_[gap, gap[:,-1][:, np.newaxis]]
        # Don't allow zero (or negative?) gaps
        gap[np.nonzero(gap <= 0)] = np.finfo(float).eps
        # do mapping
        Xix = np.maximum(0,
                         np.sum(np.greater.outer(X, vmap[0]), axis=1)
                         - 1 )
        Xdelta = (X - vmap[0, Xix])/gap[0, Xix]
        return vmap[1, Xix] + Xdelta*gap[1, Xix]

So that's a thing.

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