234 lines
204 KiB
Plaintext
234 lines
204 KiB
Plaintext
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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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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"x = np.linspace(0,10,1001)\n",
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"y = np.power(x,2)\n",
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"\n",
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"plt.plot(x,y)\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": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 640x480 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"import seaborn as sns\n",
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"\n",
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"sns.set_style(\"darkgrid\")\n",
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"plt.tight_layout()\n",
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"\n",
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"x = np.linspace(0,10,1001)\n",
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"y = np.power(x,2)\n",
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"\n",
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"plt.plot(x,y)\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": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"figure, axis = plt.subplots()\n",
|
||
|
|
"\n",
|
||
|
|
"x = np.linspace(0,10,1001)\n",
|
||
|
|
"y = np.power(x,2)\n",
|
||
|
|
"\n",
|
||
|
|
"axis.set_xlim((1,5))\n",
|
||
|
|
"axis.set_ylim((0,30))\n",
|
||
|
|
"\n",
|
||
|
|
"axis.set_xlabel(\"X-Beschriftung\")\n",
|
||
|
|
"axis.set_ylabel(\"Y-Beschriftung\")\n",
|
||
|
|
"\n",
|
||
|
|
"axis.set_title(\"Titel\")\n",
|
||
|
|
"\n",
|
||
|
|
"plt.plot(x,y)\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"figure, axis = plt.subplots()\n",
|
||
|
|
"\n",
|
||
|
|
"x = np.linspace(0,10,1001)\n",
|
||
|
|
"y1 = np.power(x,2)\n",
|
||
|
|
"y2 = np.power(x,3)\n",
|
||
|
|
"y3 = np.power(x,4)\n",
|
||
|
|
"\n",
|
||
|
|
"axis.set_xlim((1,5))\n",
|
||
|
|
"axis.set_ylim((0,30))\n",
|
||
|
|
"\n",
|
||
|
|
"plt.plot(x, y1, label=\"$x^2$\")\n",
|
||
|
|
"plt.plot(x, y2, label=\"$x^3$\")\n",
|
||
|
|
"plt.plot(x, y3, label=\"$x^4$\")\n",
|
||
|
|
"\n",
|
||
|
|
"plt.legend()\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 10,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"data = np.random.randn(1000)\n",
|
||
|
|
"\n",
|
||
|
|
"f, (axis1, axis2) = plt.subplots(1,2)\n",
|
||
|
|
"\n",
|
||
|
|
"axis1.hist(data, bins=30, color=\"b\")\n",
|
||
|
|
"\n",
|
||
|
|
"axis2.hist(data, bins=30, color=\"r\", cumulative=True)\n",
|
||
|
|
"\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"a = np.random.random((100, 100))\n",
|
||
|
|
"\n",
|
||
|
|
"plt.imshow(a)\n",
|
||
|
|
"plt.hot()\n",
|
||
|
|
"plt.colorbar()\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 15,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 500x400 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"samp1 = np.random.normal(loc = 0, scale=1., size=100)\n",
|
||
|
|
"samp2 = np.random.normal(loc = 0, scale=2., size=100)\n",
|
||
|
|
"samp3 = np.random.normal(loc = 0.3, scale=1.2, size=100)\n",
|
||
|
|
"\n",
|
||
|
|
"f,ax = plt.subplots(1,1, figsize=(5,4))\n",
|
||
|
|
"\n",
|
||
|
|
"ax.boxplot((samp1, samp2, samp3))\n",
|
||
|
|
"ax.set_xticklabels([\"Probe 1\", \"Probe 2\", \"Probe 3\"])\n",
|
||
|
|
"\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "Python 3",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.11.3"
|
||
|
|
},
|
||
|
|
"orig_nbformat": 4
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|