Add pre commit game
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.pre-commit-config.yaml
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83
.pre-commit-config.yaml
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default_language_version:
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python: python3.10
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repos:
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v4.4.0
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hooks:
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- id: end-of-file-fixer
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exclude: (.txt$|.ipynb$)
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- id: trailing-whitespace
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exclude: (.txt$|README.md$)
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- id: check-yaml
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- id: check-json
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- id: check-toml
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- id: check-xml
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# - id: check-added-large-files
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# args: [--enforce-all]
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- id: name-tests-test
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- id: detect-private-key
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- id: check-case-conflict
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- id: check-symlinks
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- id: check-docstring-first
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- repo: https://github.com/psf/black
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rev: 22.12.0
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hooks:
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- id: black
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args: [--config=pyproject.toml]
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- id: black-jupyter
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args: [--config=pyproject.toml]
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- repo: https://github.com/seandstewart/pre-commit-poetry-export
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rev: f0501a85959a71c26b964d9542a78d1033af083e
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hooks: []
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# - id: export-requirements
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# - id: export-requirements-dev
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- repo: https://github.com/macisamuele/language-formatters-pre-commit-hooks
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rev: v2.6.0
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hooks:
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- id: pretty-format-ini
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args: [--autofix]
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- id: pretty-format-toml
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args: [--autofix]
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- id: pretty-format-yaml
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args: [--autofix]
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exclude: (docker-compose.yaml$)
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- repo: https://github.com/jendrikseipp/vulture
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rev: v2.7 # or any later Vulture version
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hooks:
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- id: vulture
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- repo: https://github.com/domdfcoding/flake2lint
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rev: v0.4.2
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hooks:
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- id: flake2lint
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- repo: https://github.com/PyCQA/flake8
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rev: 6.0.0
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hooks:
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- id: flake8
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args: [--config=.flake8]
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- repo: https://github.com/pre-commit/mirrors-mypy
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rev: v0.991
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hooks:
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- id: mypy
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- repo: https://github.com/frnmst/md-toc
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rev: 8.1.8
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hooks:
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- id: md-toc
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- repo: https://gitlab.com/smop/pre-commit-hooks
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rev: v1.0.0
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hooks:
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- id: check-poetry
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- repo: https://github.com/Lucas-C/pre-commit-hooks-java
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rev: 1.3.10
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hooks:
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- id: validate-html
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test_main.ipynb
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172
test_main.ipynb
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"outputs": [
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{
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"data": {
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"text/plain": "array([[0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0.],\n [0., 0., 0., 0., 0.]])"
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"a = np.zeros((5,5))\n",
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"a"
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],
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"metadata": {
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"collapsed": false
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}
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"outputs": [
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{
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"data": {
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"text/plain": "array([[ 0., 0., 0., 0., 0.],\n [ 0., 0., 0., 0., 0.],\n [ 0., 0., 10., 0., 0.],\n [ 0., 0., 0., 0., 0.],\n [ 0., 0., 0., 0., 0.]])"
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"a[2,2] = 10\n",
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"a"
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],
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"metadata": {
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"collapsed": false
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}
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"outputs": [],
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"source": [
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"index_array = np.array([2,2], dtype=int)"
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],
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"metadata": {
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"collapsed": false
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}
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"234 ns ± 7.47 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)\n",
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"311 ns ± 2.15 ns per loop (mean ± std. dev. of 7 runs, 1,000,000 loops each)\n"
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]
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}
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],
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"source": [
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"%timeit a[tuple(index_array.tolist())]\n",
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"%timeit a[index_array[0], index_array[1]]"
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],
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"metadata": {
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"collapsed": false
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}
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"outputs": [],
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"source": [
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"def array_change(array):\n",
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" array[1] = 1"
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],
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"metadata": {
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"collapsed": false
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}
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"outputs": [
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{
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"data": {
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"text/plain": "array([[ 0., 0., 0., 0., 0.],\n [ 1., 1., 1., 1., 1.],\n [ 0., 1., 10., 0., 0.],\n [ 1., 1., 1., 1., 1.],\n [ 0., 0., 0., 0., 0.]])"
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"array_change(a[2:])\n",
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"a"
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],
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"metadata": {
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"collapsed": false
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}
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"outputs": [
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{
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"data": {
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"text/plain": "array([[ 0., 0., 0., 0., 0.],\n [ 1., 1., 1., 1., 1.],\n [ 0., 1., 10., 0., 0.],\n [ 0., 0., 0., 0., 0.],\n [ 0., 0., 0., 0., 0.]])"
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"a"
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],
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"metadata": {
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"collapsed": false
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}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"outputs": [],
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"source": [],
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"metadata": {
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"collapsed": false
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}
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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