Jake Graving jgraving

## angleLerp.js
/*
2D Angle Interpolation (shortest distance)

Parameters:
a0 = start angle
a1 = end angle
t = interpolation factor (0.0=start, 1.0=end)

Benefits:
1. Angles do NOT need to be normalized.

## BlahutArimoto.m
function [C r] = BlahutArimoto(p)

disp('BlahutArimoto')

% Capacity of discrete memoryless channel
% Blahut-Arimoto algorithm

% Input
% p: m x n matrix
% p is the transition matrix for a channel with m inputs and n outputs

## medfilt.py
#!/usr/bin/env python

import numpy as np


def medfilt (x, k):
    """Apply a length-k median filter to a 1D array x.
    Boundaries are extended by repeating endpoints.
    """
    assert k % 2 == 1, "Median filter length must be odd."

## ffmpeg_load_audio.py
import numpy as np
import subprocess as sp
import os
DEVNULL = open(os.devnull, 'w')

# load_audio can not detect the input type
def ffmpeg_load_audio(filename, sr=44100, mono=False, normalize=True, in_type=np.int16, out_type=np.float32):
    channels = 1 if mono else 2
    format_strings = {
        np.float64: 'f64le',

## autoencoder_extra.py
import keras.backend as K
from keras.layers import Layer
from keras.legacy import interfaces
from keras.engine import InputSpec
from keras import activations, initializers, regularizers, constraints


class DenseTransposeTied(Layer):

    @interfaces.legacy_dense_support

## algorithms_openpose.md

      
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                jgraving
                / algorithms_openpose.md
            
            
              Created
              May 2, 2018 12:55
                — forked from alesolano/algorithms_openpose.md
            
              
                OpenPose TensorFlow Alogrithms
              
          
    All code is highly based on Ildoo Kim's code (https://github.com/ildoonet/tf-openpose) and derived from the OpenPose Library (https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/LICENSE)

  
## Readme.md

      
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                jgraving
                / Readme.md
            
            
              Created
              May 24, 2018 12:53
                — forked from dpatschke/Readme.md
            
              
                Numba Ball Tree (ParallelAccelerator)
              
          
    Numba Ball Tree (ParallelAccelerator)

This is a modified gist of Jake Vanderplas wonderful Numba Ball Tree code from the
following gist. This gist basically adds
the 'nopython' parameter in the jit decorators from the original gist and
parallelizes the nearest neighbor query for each of the points.
Timings

With some of the new advances in numba and the modifications

  
## cuda_installation_on_ubuntu_18.04
#!/bin/bash
## This gist contains step by step instructions to install cuda v9.0 and cudnn 7.2 in ubuntu 18.04

### steps ####
# verify the system has a cuda-capable gpu
# download and install the nvidia cuda toolkit and cudnn
# setup environmental variables
# verify the installation
###

## dtw_mse.py
# based on https://github.com/kylerbrown/ezdtw
# with modifications to be fully njit-able

import numpy as np
from numba import njit

@njit
def sqeuclidean(a, b):
    return np.sum((a - b)**2)

## Earth Mover's Distance.ipynb

      
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                jgraving
                / Earth Mover's Distance.ipynb
            
            
              Created
              April 10, 2019 22:56
                — forked from kylemcdonald/Earth Mover's Distance.ipynb
            
              
                Faster 1d Earth Mover's Distance with numpy and numba.
              
          
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	/*
	2D Angle Interpolation (shortest distance)

	Parameters:
	a0 = start angle
	a1 = end angle
	t = interpolation factor (0.0=start, 1.0=end)

	Benefits:
	1. Angles do NOT need to be normalized.
	function [C r] = BlahutArimoto(p)

	disp('BlahutArimoto')

	% Capacity of discrete memoryless channel
	% Blahut-Arimoto algorithm

	% Input
	% p: m x n matrix
	% p is the transition matrix for a channel with m inputs and n outputs
	#!/usr/bin/env python

	import numpy as np


	def medfilt (x, k):
	"""Apply a length-k median filter to a 1D array x.
	Boundaries are extended by repeating endpoints.
	"""
	assert k % 2 == 1, "Median filter length must be odd."
	import numpy as np
	import subprocess as sp
	import os
	DEVNULL = open(os.devnull, 'w')

	# load_audio can not detect the input type
	def ffmpeg_load_audio(filename, sr=44100, mono=False, normalize=True, in_type=np.int16, out_type=np.float32):
	channels = 1 if mono else 2
	format_strings = {
	np.float64: 'f64le',
	import keras.backend as K
	from keras.layers import Layer
	from keras.legacy import interfaces
	from keras.engine import InputSpec
	from keras import activations, initializers, regularizers, constraints


	class DenseTransposeTied(Layer):

	@interfaces.legacy_dense_support
	#!/bin/bash
	## This gist contains step by step instructions to install cuda v9.0 and cudnn 7.2 in ubuntu 18.04

	### steps ####
	# verify the system has a cuda-capable gpu
	# download and install the nvidia cuda toolkit and cudnn
	# setup environmental variables
	# verify the installation
	###
	# based on https://github.com/kylerbrown/ezdtw
	# with modifications to be fully njit-able

	import numpy as np
	from numba import njit

	@njit
	def sqeuclidean(a, b):
	return np.sum((a - b)**2)