compressed validation data from KW Tieferbach
This commit is contained in:
311771
Validation Data/August_1.csv
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Validation Data/August_1.csv
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459531
Validation Data/August_2.csv
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Validation Data/August_2.csv
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Validation Data/August_3.csv
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Validation Data/August_3.csv
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598191
Validation Data/Juli_1.csv
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Validation Data/Juli_1.csv
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Validation Data/Juli_2.csv
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Validation Data/Juli_2.csv
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Validation Data/Juli_3.csv
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Validation Data/Juli_3.csv
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Validation Data/Juni_1.csv
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Validation Data/Juni_1.csv
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Validation Data/Juni_2.csv
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Validation Data/Juni_2.csv
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Validation Data/Juni_3.csv
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Validation Data/Juni_3.csv
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@@ -2,7 +2,7 @@
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"cells": [
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"cells": [
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{
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{
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"cell_type": "code",
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"cell_type": "code",
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"execution_count": 9,
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"execution_count": 57,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@@ -15,7 +15,16 @@
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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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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 58,
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"metadata": {},
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"outputs": [],
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"source": [
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"name = 'August_3'"
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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": 59,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@@ -37,7 +46,7 @@
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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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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 60,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@@ -50,8 +59,10 @@
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"parameter_old = ''\n",
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"parameter_old = ''\n",
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"value_list = []\n",
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"value_list = []\n",
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"timestamp_list = []\n",
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"timestamp_list = []\n",
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"with open('Juni_1_22.txt') as txt_file:\n",
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"with open(name+'.txt') as txt_file:\n",
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" for line in txt_file:\n",
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" for line in txt_file:\n",
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" if line == \"\":\n",
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" break\n",
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" parameter_new, value_new, timestamp_new = unpack_line(line)\n",
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" parameter_new, value_new, timestamp_new = unpack_line(line)\n",
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" if parameter_new != parameter_old:\n",
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" if parameter_new != parameter_old:\n",
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" if 'M1' in parameter_old and 'Stell_Leitapparat' in parameter_old:\n",
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" if 'M1' in parameter_old and 'Stell_Leitapparat' in parameter_old:\n",
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@@ -99,34 +110,7 @@
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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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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 61,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[<matplotlib.lines.Line2D at 0x2e6c96b7430>]"
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]
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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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"fig1=plt.figure()\n",
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"plt.plot(M1_LA_df['M1-LA'])\n",
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"fig2=plt.figure()\n",
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"plt.plot(M1_Druck_df['M1-Druck'])\n",
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"fig3=plt.figure()\n",
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"plt.plot(M2_LA_df['M2-LA'])\n",
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"fig4=plt.figure()\n",
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"plt.plot(M2_Druck_df['M2-Druck'])"
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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": 13,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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@@ -136,66 +120,38 @@
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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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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 62,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[<matplotlib.lines.Line2D at 0x2e6c8733c10>]"
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]
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},
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"execution_count": 14,
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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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"fig1=plt.figure()\n",
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"plt.plot(df['M1-LA'])\n",
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"fig2=plt.figure()\n",
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"plt.plot(df['M1-Druck'])\n",
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"fig3=plt.figure()\n",
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"plt.plot(df['M2-LA'])\n",
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"fig4=plt.figure()\n",
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"plt.plot(df['M2-Druck'])"
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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": 17,
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"t_vec = df.index.to_numpy()\n",
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"# t_vec = df.index.to_numpy()\n",
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"M1_LA = df['M1-LA'].to_numpy() "
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"# M1_LA = df['M1-LA'].to_numpy() \n",
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"# M2_LA = df['M2-LA'].to_numpy() \n",
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"# M1_p = df['M1-Druck'].to_numpy() \n",
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"# M2_p = df['M2-Druck'].to_numpy() \n",
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"# fig1=plt.figure()\n",
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"# plt.plot(t_vec,M1_LA)\n",
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"# fig2=plt.figure()\n",
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"# plt.plot(t_vec,M2_LA)\n",
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"# fig3=plt.figure()\n",
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"# plt.plot(t_vec,M1_p)\n",
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"# fig4=plt.figure()\n",
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"# plt.plot(t_vec,M2_p)"
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]
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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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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 63,
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"metadata": {},
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"metadata": {},
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"outputs": [
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"outputs": [],
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{
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"data": {
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"text/plain": [
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"[<matplotlib.lines.Line2D at 0x2e6c8563340>]"
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]
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},
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"execution_count": 18,
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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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"source": [
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"fig5=plt.figure()\n",
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"df.to_csv(name+'.csv')"
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"plt.plot(t_vec,M1_LA)"
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]
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]
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}
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}
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],
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],
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"metadata": {
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"metadata": {
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"kernelspec": {
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"kernelspec": {
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"display_name": "Python 3.8.13 ('Georg_DT_Slot3')",
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"display_name": "Python 3.8.13 ('DT_Slot_3')",
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"language": "python",
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"language": "python",
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"name": "python3"
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"name": "python3"
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},
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},
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@@ -214,7 +170,7 @@
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"orig_nbformat": 4,
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"orig_nbformat": 4,
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"vscode": {
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"vscode": {
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"interpreter": {
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"interpreter": {
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"hash": "84fb123bdc47ab647d3782661abcbe80fbb79236dd2f8adf4cef30e8755eb2cd"
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"hash": "4a28055eb8a3160fa4c7e4fca69770c4e0a1add985300856aa3fcf4ce32a2c48"
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}
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}
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}
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}
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},
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},
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