Make notebooks compatible with both python 2 and python 3
parent
ec681a3174
commit
793c3a2574
15
index.ipynb
15
index.ipynb
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@ -7,31 +7,32 @@
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"# Machine Learning Notebooks\n",
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"\n",
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"Welcome to the Machine Learning Notebooks.\n",
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"**This work is in progress.**\n",
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"\n",
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"## Tools\n",
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"* [NumPy](tools_numpy.ipynb)\n",
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"* [Matplotlib](tools_matplotlib.ipynb)"
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"* [Matplotlib](tools_matplotlib.ipynb)\n",
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"\n",
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"**This work is in progress, more notebooks are coming soon...**"
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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 2",
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"display_name": "Python 3",
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"language": "python",
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"name": "python2"
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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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"version": 3
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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": "2.7.11"
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"pygments_lexer": "ipython3",
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"version": "3.5.1"
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}
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},
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"nbformat": 4,
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@ -20,7 +20,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First we need to import the `matplotlib` library."
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"First let's make sure that this notebook works well in both python 2 and 3:"
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]
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},
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{
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@ -30,6 +30,26 @@
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"from __future__ import division\n",
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"from __future__ import print_function\n",
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"from __future__ import unicode_literals"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"First we need to import the `matplotlib` library."
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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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"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 matplotlib"
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]
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@ -43,7 +63,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 47,
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"execution_count": 3,
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"metadata": {
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"collapsed": false
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},
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@ -62,7 +82,7 @@
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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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"execution_count": 4,
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"metadata": {
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"collapsed": false
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},
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@ -85,7 +105,7 @@
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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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"execution_count": 5,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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@ -105,7 +125,7 @@
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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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"execution_count": 6,
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"metadata": {
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"collapsed": false
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},
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@ -125,7 +145,7 @@
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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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"execution_count": 7,
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"metadata": {
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"collapsed": false
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},
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@ -148,7 +168,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 8,
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"metadata": {
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"collapsed": false
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},
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@ -178,7 +198,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": 9,
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"metadata": {
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"collapsed": false
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},
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@ -199,7 +219,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 10,
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"metadata": {
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"collapsed": false
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},
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@ -221,7 +241,7 @@
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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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"execution_count": 11,
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"metadata": {
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"collapsed": false
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},
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@ -241,7 +261,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 12,
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"metadata": {
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"collapsed": false
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},
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@ -263,7 +283,7 @@
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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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"execution_count": 13,
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"metadata": {
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"collapsed": false
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},
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@ -283,7 +303,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 14,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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@ -308,7 +328,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 15,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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@ -330,7 +350,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 16,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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@ -365,7 +385,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 17,
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"metadata": {
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"collapsed": false
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},
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@ -389,7 +409,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": 18,
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"metadata": {
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"collapsed": false
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},
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@ -423,7 +443,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 19,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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@ -465,7 +485,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 20,
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"metadata": {
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"collapsed": false
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},
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@ -483,7 +503,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"execution_count": 21,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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@ -527,7 +547,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"execution_count": 22,
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"metadata": {
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"collapsed": false
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},
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@ -559,7 +579,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"execution_count": 23,
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"metadata": {
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"collapsed": false
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},
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@ -581,7 +601,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"execution_count": 24,
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"metadata": {
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"collapsed": false,
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"scrolled": false
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@ -608,7 +628,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 24,
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"execution_count": 25,
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"metadata": {
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"collapsed": false
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},
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@ -636,7 +656,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 25,
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"execution_count": 26,
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"metadata": {
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"collapsed": false
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},
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@ -660,7 +680,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 26,
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"execution_count": 27,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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@ -710,7 +730,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"execution_count": 28,
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"metadata": {
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"collapsed": false
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},
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@ -755,7 +775,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"execution_count": 29,
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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": 29,
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"execution_count": 30,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"execution_count": 31,
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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": 31,
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"execution_count": 32,
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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": 32,
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"execution_count": 33,
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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": 33,
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"execution_count": 34,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"execution_count": 35,
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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": 35,
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"execution_count": 36,
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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": 36,
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"execution_count": 37,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"execution_count": 38,
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"metadata": {
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"collapsed": false
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},
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"import matplotlib.image as mpimg\n",
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"\n",
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"img = mpimg.imread('my_square_function.png')\n",
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"print img.shape, img.dtype"
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"print(img.shape, img.dtype)"
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]
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},
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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": 38,
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"execution_count": 39,
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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": 39,
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"execution_count": 40,
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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": 40,
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"execution_count": 41,
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"metadata": {
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"collapsed": false
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},
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"outputs": [],
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"source": [
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"img = np.arange(100*100).reshape(100, 100)\n",
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"print img\n",
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"print(img)\n",
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"plt.imshow(img)\n",
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"plt.show()"
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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": 41,
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"execution_count": 42,
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"metadata": {
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"collapsed": false,
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"scrolled": false
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},
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{
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"cell_type": "code",
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"execution_count": 42,
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"execution_count": 43,
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"metadata": {
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"collapsed": false,
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"scrolled": true
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},
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{
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"cell_type": "code",
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"execution_count": 43,
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"execution_count": 44,
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"metadata": {
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"collapsed": false,
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"scrolled": false
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},
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{
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"cell_type": "code",
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"execution_count": 44,
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"execution_count": 45,
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"metadata": {
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"collapsed": true
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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": 45,
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"execution_count": 46,
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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": 46,
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"execution_count": 47,
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"metadata": {
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"collapsed": false
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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 2",
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"display_name": "Python 3",
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"language": "python",
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"name": "python2"
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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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"version": 3
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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": "2.7.11"
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"pygments_lexer": "ipython3",
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"version": "3.5.1"
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}
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},
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"nbformat": 4,
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1051
tools_numpy.ipynb
1051
tools_numpy.ipynb
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