Ryan Holbrook ryanholbrook

## cool_script.sh
#!/bin/bash

# TODO: you will need to have conda installed

# create a python environment
conda create -n env_tmp python=3.8.13 -y

# activate environment
conda activate env_tmp

## jaxpr_graph.py
import jax
from jax import core
from graphviz import Digraph
import itertools


styles = {
  'const': dict(style='filled', color='goldenrod1'),
  'invar': dict(color='mediumspringgreen', style='filled'),
  'outvar': dict(style='filled,dashed', fillcolor='indianred1', color='black'),

## matrix_box_notation.tex
%Make sure to have \usepackage{tikz}


%https://tex.stackexchange.com/a/45815/140440 - for grid
%https://tex.stackexchange.com/a/381175/140440 - for alignment in equation

% This function draws a matrix.
\newcommand{\mat}[2]{% cols, rows
\vcenter{\hbox{ %Vertical alignment
\begin{tikzpicture}[scale=0.3, align=center]

## layout.svg

      
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                baptiste
                / layout.svg
            
            
              Last active
              March 3, 2020 03:02
            
          
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## auto_shape_mixin.py
from typing import Any, Mapping, Optional, Sequence, TypeVar, Union

import tensorflow as tf
from tensorflow.keras import layers


T = TypeVar('T')
Nested = Union[T, Sequence[T], Mapping[Any, T]]

class AutoShapeMixin:

## duplicates.py
#!/usr/bin/env python
"""
Fast duplicate file finder.
Usage: duplicates.py <folder> [<folder>...]

Based on https://stackoverflow.com/a/36113168/300783
Modified for Python3 with some small code improvements.
"""
import os
import sys

## maps.org

      
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                behrica
                / maps.org
            
            
              Last active
              August 15, 2021 09:51
            
              
                Proof of concept for htmlwidget integration in org mode
              
          
    renderDeps <- function(widget,dir=".",libdir="lib") {
  rendered <- htmltools::renderTags(widget)

  deps <- lapply(rendered1$dependencies, function(dep) {
    dep <- htmltools::copyDependencyToDir(dep, libdir, FALSE)
    dep <- htmltools::makeDependencyRelative(dep, dir, FALSE)

  
## forecasting_metrics.py
import numpy as np

EPSILON = 1e-10


def _error(actual: np.ndarray, predicted: np.ndarray):
    """ Simple error """
    return actual - predicted


## robust_splines_sklearn.py
#!/usr/bin/env python
"""
Robust B-Spline regression with scikit-learn
"""

import matplotlib.pyplot as plt
import numpy as np
import scipy.interpolate as si
from sklearn.base import TransformerMixin
from sklearn.pipeline import make_pipeline

## .Xresources
 Xft.dpi: 120
 Xft.antialias:  true
 Xft.hinting:    true
 Xft.rgba:       rgb
 Xft.hintstyle:  hintslight

rofi.color-enabled: true
rofi.color-window: #282828, #282828, #268bd2
rofi.color-normal: #282828, #ffffff, #282828, #268bd2, #ffffff
rofi.color-active: #282828, #268bd2, #282828, #268bd2, #205171
	#!/bin/bash

	# TODO: you will need to have conda installed

	# create a python environment
	conda create -n env_tmp python=3.8.13 -y

	# activate environment
	conda activate env_tmp
	import jax
	from jax import core
	from graphviz import Digraph
	import itertools


	styles = {
	'const': dict(style='filled', color='goldenrod1'),
	'invar': dict(color='mediumspringgreen', style='filled'),
	'outvar': dict(style='filled,dashed', fillcolor='indianred1', color='black'),
	%Make sure to have \usepackage{tikz}


	%https://tex.stackexchange.com/a/45815/140440 - for grid
	%https://tex.stackexchange.com/a/381175/140440 - for alignment in equation

	% This function draws a matrix.
	\newcommand{\mat}[2]{% cols, rows
	\vcenter{\hbox{ %Vertical alignment
	\begin{tikzpicture}[scale=0.3, align=center]
	from typing import Any, Mapping, Optional, Sequence, TypeVar, Union

	import tensorflow as tf
	from tensorflow.keras import layers


	T = TypeVar('T')
	Nested = Union[T, Sequence[T], Mapping[Any, T]]

	class AutoShapeMixin:
	#!/usr/bin/env python
	"""
	Fast duplicate file finder.
	Usage: duplicates.py <folder> [<folder>...]

	Based on https://stackoverflow.com/a/36113168/300783
	Modified for Python3 with some small code improvements.
	"""
	import os
	import sys
	import numpy as np

	EPSILON = 1e-10


	def _error(actual: np.ndarray, predicted: np.ndarray):
	""" Simple error """
	return actual - predicted
	#!/usr/bin/env python
	"""
	Robust B-Spline regression with scikit-learn
	"""

	import matplotlib.pyplot as plt
	import numpy as np
	import scipy.interpolate as si
	from sklearn.base import TransformerMixin
	from sklearn.pipeline import make_pipeline
	Xft.dpi: 120
	Xft.antialias: true
	Xft.hinting: true
	Xft.rgba: rgb
	Xft.hintstyle: hintslight

	rofi.color-enabled: true
	rofi.color-window: #282828, #282828, #268bd2
	rofi.color-normal: #282828, #ffffff, #282828, #268bd2, #ffffff
	rofi.color-active: #282828, #268bd2, #282828, #268bd2, #205171