Georg_Brantegger/Python-DT_Slot_3
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compressed validation data from KW Tieferbach

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Georg ´Brantegger
2022-09-20 10:08:37 +02:00
parent cec300973a
commit 33ca4dd48e
10 changed files with 4412084 additions and 79 deletions
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114
Validation Data/read_validation_data_long.ipynb
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@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 57,
"metadata": {},
"outputs": [],
"source": [
@@ -15,7 +15,16 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 58,
"metadata": {},
"outputs": [],
"source": [
"name = 'August_3'"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {},
"outputs": [],
"source": [
@@ -37,7 +46,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 60,
"metadata": {},
"outputs": [],
"source": [
@@ -50,8 +59,10 @@
"parameter_old = ''\n",
"value_list = []\n",
"timestamp_list = []\n",
"with open('Juni_1_22.txt') as txt_file:\n",
"with open(name+'.txt') as txt_file:\n",
" for line in txt_file:\n",
" if line == \"\":\n",
" break\n",
" parameter_new, value_new, timestamp_new = unpack_line(line)\n",
" if parameter_new != parameter_old:\n",
" if 'M1' in parameter_old and 'Stell_Leitapparat' in parameter_old:\n",
@@ -99,34 +110,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x2e6c96b7430>]"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fig1=plt.figure()\n",
"plt.plot(M1_LA_df['M1-LA'])\n",
"fig2=plt.figure()\n",
"plt.plot(M1_Druck_df['M1-Druck'])\n",
"fig3=plt.figure()\n",
"plt.plot(M2_LA_df['M2-LA'])\n",
"fig4=plt.figure()\n",
"plt.plot(M2_Druck_df['M2-Druck'])"
]
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 61,
"metadata": {},
"outputs": [],
"source": [
@@ -136,66 +120,38 @@
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x2e6c8733c10>]"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fig1=plt.figure()\n",
"plt.plot(df['M1-LA'])\n",
"fig2=plt.figure()\n",
"plt.plot(df['M1-Druck'])\n",
"fig3=plt.figure()\n",
"plt.plot(df['M2-LA'])\n",
"fig4=plt.figure()\n",
"plt.plot(df['M2-Druck'])"
]
},
{
"cell_type": "code",
"execution_count": 17,
"execution_count": 62,
"metadata": {},
"outputs": [],
"source": [
"t_vec = df.index.to_numpy()\n",
"M1_LA = df['M1-LA'].to_numpy() "
"# t_vec = df.index.to_numpy()\n",
"# M1_LA = df['M1-LA'].to_numpy() \n",
"# M2_LA = df['M2-LA'].to_numpy() \n",
"# M1_p = df['M1-Druck'].to_numpy() \n",
"# M2_p = df['M2-Druck'].to_numpy() \n",
"# fig1=plt.figure()\n",
"# plt.plot(t_vec,M1_LA)\n",
"# fig2=plt.figure()\n",
"# plt.plot(t_vec,M2_LA)\n",
"# fig3=plt.figure()\n",
"# plt.plot(t_vec,M1_p)\n",
"# fig4=plt.figure()\n",
"# plt.plot(t_vec,M2_p)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"execution_count": 63,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x2e6c8563340>]"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"outputs": [],
"source": [
"fig5=plt.figure()\n",
"plt.plot(t_vec,M1_LA)"
"df.to_csv(name+'.csv')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3.8.13 ('Georg_DT_Slot3')",
"display_name": "Python 3.8.13 ('DT_Slot_3')",
"language": "python",
"name": "python3"
},
@@ -214,7 +170,7 @@
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "84fb123bdc47ab647d3782661abcbe80fbb79236dd2f8adf4cef30e8755eb2cd"
"hash": "4a28055eb8a3160fa4c7e4fca69770c4e0a1add985300856aa3fcf4ce32a2c48"
}
}
},