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validation and KW Hammer Lastfälle

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Georg ´Brantegger
2022-09-27 15:31:36 +02:00
parent e1c7bc9d07
commit a951ea9b64
45 changed files with 1378443 additions and 1273749 deletions
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44
Validation Data/consolidated pandas dataframes/consolidate_validation_data.ipynb
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@@ -2,7 +2,7 @@
"cells": [
{
"cell_type": "code",
"execution_count": 9,
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
@@ -14,7 +14,7 @@
},
{
"cell_type": "code",
"execution_count": 10,
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
@@ -37,7 +37,7 @@
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
@@ -46,7 +46,7 @@
},
{
"cell_type": "code",
"execution_count": 12,
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
@@ -56,7 +56,7 @@
},
{
"cell_type": "code",
"execution_count": 13,
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
@@ -71,12 +71,13 @@
"UT_M1_p = UT_df['UL_T1_p'].to_numpy()\n",
"UT_M2_p = UT_df['UL_T2_p'].to_numpy()\n",
"UT_M1_LA = UT_df['UL_T1_LA'].to_numpy()\n",
"UT_M2_LA = UT_df['UL_T2_LA'].to_numpy()"
"UT_M2_LA = UT_df['UL_T2_LA'].to_numpy()\n",
"UT_Ausl = UT_df['Ausl'].to_numpy()\n"
]
},
{
"cell_type": "code",
"execution_count": 21,
"execution_count": 16,
"metadata": {},
"outputs": [
{
@@ -85,7 +86,7 @@
"(1657542740.9878564, 1657553169.3173888)"
]
},
"execution_count": 21,
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
@@ -116,30 +117,21 @@
},
{
"cell_type": "code",
"execution_count": 48,
"execution_count": 21,
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "Cannot construct a dtype from an array",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32mv:\\georg\\Documents\\Persönliche Dokumente\\Arbeit\\Kelag\\Coding\\Python\\DT_Slot_3\\Kelag_DT_Slot_3\\Validation Data\\consolidated pandas dataframes\\consolidate_validation_data.ipynb Cell 7\u001b[0m in \u001b[0;36m<cell line: 7>\u001b[1;34m()\u001b[0m\n\u001b[0;32m <a href='vscode-notebook-cell:/v%3A/georg/Documents/Pers%C3%B6nliche%20Dokumente/Arbeit/Kelag/Coding/Python/DT_Slot_3/Kelag_DT_Slot_3/Validation%20Data/consolidated%20pandas%20dataframes/consolidate_validation_data.ipynb#X10sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m fig \u001b[39m=\u001b[39m plt\u001b[39m.\u001b[39mfigure()\n\u001b[0;32m <a href='vscode-notebook-cell:/v%3A/georg/Documents/Pers%C3%B6nliche%20Dokumente/Arbeit/Kelag/Coding/Python/DT_Slot_3/Kelag_DT_Slot_3/Validation%20Data/consolidated%20pandas%20dataframes/consolidate_validation_data.ipynb#X10sZmlsZQ%3D%3D?line=5'>6</a>\u001b[0m plt\u001b[39m.\u001b[39mplot(UT_t_vec[mask_UT],TB_level[mask_UT])\n\u001b[1;32m----> <a href='vscode-notebook-cell:/v%3A/georg/Documents/Pers%C3%B6nliche%20Dokumente/Arbeit/Kelag/Coding/Python/DT_Slot_3/Kelag_DT_Slot_3/Validation%20Data/consolidated%20pandas%20dataframes/consolidate_validation_data.ipynb#X10sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m validation_data_UT \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39;49marray([UT_t_vec[mask_UT],UT_M1_LA[mask_UT],UT_M2_LA[mask_UT],UT_M1_p[mask_UT],UT_M2_p[mask_UT]],TB_level[mask_UT])\n\u001b[0;32m <a href='vscode-notebook-cell:/v%3A/georg/Documents/Pers%C3%B6nliche%20Dokumente/Arbeit/Kelag/Coding/Python/DT_Slot_3/Kelag_DT_Slot_3/Validation%20Data/consolidated%20pandas%20dataframes/consolidate_validation_data.ipynb#X10sZmlsZQ%3D%3D?line=7'>8</a>\u001b[0m validation_data_TB \u001b[39m=\u001b[39m np\u001b[39m.\u001b[39marray([TB_t_vec[mask_TB],TB_M1_LA[mask_TB],TB_M2_LA[mask_TB],TB_M1_p[mask_TB],TB_M2_p[mask_TB]])\n",
"\u001b[1;31mTypeError\u001b[0m: Cannot construct a dtype from an array"
]
}
],
"outputs": [],
"source": [
"mask_UT = np.logical_and(t1<UT_t_vec,UT_t_vec <t2)\n",
"mask_TB = np.logical_and(t1<TB_t_vec,TB_t_vec <t2)\n",
"\n",
"\n",
"fig = plt.figure()\n",
"plt.plot(UT_t_vec[mask_UT],TB_level[mask_UT])\n",
"validation_data_UT = np.array([UT_t_vec[mask_UT];UT_M1_LA[mask_UT];UT_M2_LA[mask_UT];UT_M1_p[mask_UT];UT_M2_p[mask_UT]];TB_level[mask_UT])\n",
"validation_data_TB = np.array([TB_t_vec[mask_TB];TB_M1_LA[mask_TB];TB_M2_LA[mask_TB];TB_M1_p[mask_TB];TB_M2_p[mask_TB]])"
"\n",
"validation_data_UT = UT_df[mask_UT]\n",
"validation_data_TB = TB_df[mask_TB]\n",
"\n",
"validation_data_UT.to_csv('Validation_data_UT.csv')\n",
"validation_data_TB.to_csv('Validation_data_TB.csv')\n",
"\n"
]
}
],