cwindolf

'''Python library for decorrelating and correlating data

Forked from joelouismarino/whiten.py.
Also based on R's rdrr.io/cran/whitening/src/R/whiteningMatrix.R,
and an SAS blog post:
blogs.sas.com/content/iml/2012/02/08/use-the-cholesky-
transformation-to-correlate-and-uncorrelate-variables.html
'''
import numpy as np
import scipy.linalg as la

cwindolf

"""noint: Shield a code block or function from SIGINT.

Based on: http://stackoverflow.com/a/21919644/487556.

Useful for running training loops in Jupyter: if your learning
step is inside a `with noint:`, when you want to interrupt your
training routine, you can do that without getting halfway through
some set of operations and leaving the model state inconsistent,
which would make it impossible to rerun the cell without
restarting the whole training loop.

cwindolf

#!/usr/bin/env python3
r"""teqn

Quickly turn your math mode expression into cropped png, svg, or pdf.
Then you can drag and drop it into slack or illustrator or whatever.
This is basically just a wrapper around the standalone document class.

Pass your math expression (in quotes) on the command line. It will be
typeset in the align* environment by default, unless you pass --nomath,
in which case you can put the environment in the expression too.

cwindolf

import numpy as np


class _redder:
    """Syntactic sugar for reductions in numpy.

    Users interact with the global instance `rdr` defined below rather
    than using this class itself.

    Probably a dumb idea but whatever. Basically a sugar to batch out

cwindolf

import numpy as np
import matplotlib.pyplot as plt


class bwdrawer:
    """Draw one pixel at a time on a black and white canvas.
    
    Usage (in a script or a repl):
    ```
    drawer = bwdrawer(my_width, my_height)

cwindolf

import time

class timer:
    def __init__(self, name="timer", format="{:0.1f}"):
        self.name = name
        self.format = format
 
    def __enter__(self):
        self.start = time.perf_counter()
        return self

cwindolf

<snippet>
 <content><![CDATA[
\$\$\begin{aligned}
$1
\end{aligned}\$\$
]]></content>
 <tabTrigger>ali</tabTrigger>
 <scope>text.html.markdown,text.html.markdown.multimarkdown</scope>
</snippet>

cwindolf

# Translation of the Octave implementation (GPL), which is
# copyright 2014 Benjamin Eltzner. For that code, and license, see:
# hg.code.sf.net/p/octave/image/file/tip/inst/normxcorr2.m
import numpy as np
from scipy.signal import correlate, convolve


def normxcorr(template, x, mode="full", method="auto", assume_centered=False):
    """normxcorr: Normalized cross-correlation

cwindolf

import numpy as np


def argmedian(p, axis=None, check_pmf=True):
    """Compute the median of a pmf or many pmfs

    Here, `p` represents one or many probability mass functions, and
    the index to a median will be returned for each pmf.

        - If `axis=None`, the flattened version of `p` will be considered

cwindolf

import numpy as np

def zroll1d(arr1d, x):
    """np.roll, but not toroidal (backfills with 0s), and only 1d."""
    if x == 0:
        return arr1d
    elif x > 0:
        return np.pad(
            arr1d[:-x],
            ((x, 0),),