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import matplotlib.pyplot as plt
import mpl_toolkits.axes_grid1.inset_locator

fig, ax = plt.subplots()

matrix = np.random.normal(size=(100, 100))
sm = ax.matshow(matrix)

# Attach a small axes to the lower right of the main axes. It's an "inset"
# placed outside of the plot. The size is 0.02 width x 0.5 height of the

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hi def link cppSTLfunction     Function
hi def link cppSTLfunctional   NONE
hi def link cppSTLconstant     NONE
hi def link cppSTLnamespace    cppNamespaceStd
hi def link cppSTLexception    NONE
hi def link cppSTLiterator     NONE
hi def link cppSTLiterator_tag NONE
hi def link cppSTLenum         NONE
hi def link cppSTLios          NONE
hi def link cppSTLcast         NONE

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plt.style.use("paper")

# Name prop colors. You may need to change it to match your matplotlib style to use.
names = ["nb:blue", "nb:red", "nb:green", "nb:yellow", "nb:cyan", "nb:purple", "nb:magenta", "nb:gray"]
props = plt.rcParams["axes.prop_cycle"]
assert len(names) == len(props)

cc = plt.cm.colors.colorConverter
for name, prop in zip(names, props):
    cc.colors[name] = prop["color"]

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zshrc::rainbow() {
    local i=$1
    #local palette=( 197 220 82 49 33 129 )
    #local size=${#palette}

    local palette=
    set -A palette 197 220 82 49 33 129
    local size=${#palette}

    # Normalize index to a non-negative value by cycling.

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# git clone git@github.com:example/fork.git
# git remote add upstream https://github.com/example/upstream.git

git pull upstream master
git push origin master

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import * as http from "https://deno.land/std@0.91.0/http/mod.ts";

interface RequestData {
  method: string;
  path: string;
  headers: Headers;
  body: ArrayBuffer;
}

interface MockData {

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function asleep(delay: number): Promise<void> {
  return new Promise<void>((resolve, reject) => setTimeout(resolve, delay));
}

console.log(Date.now());
await asleep(100);
console.log(Date.now());

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import matplotlib.pyplot as plt
import numpy as np

from matplotlib.animation import FuncAnimation
from IPython.display import Video

# Make a spiral
step_count = 10000

random = np.random.RandomState(0)

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# Figure
figure.figsize: 3.6, 2.0
figure.dpi: 150
figure.frameon: True
figure.edgecolor: none
figure.facecolor: white

figure.autolayout: False
figure.constrained_layout.use: True

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