Georg_Brantegger/Python-DT_Slot_3
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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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61313
Validation Data/raw data Untertweng/AL_SeitAuslPos.txt Normal file
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6
Validation Data/raw data Untertweng/Schnellschluss/Validation_Untertweng_Schnellschluss.ipynb
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@@ -35,7 +35,7 @@
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\georg\\AppData\\Local\\Temp\\ipykernel_29732\\1290488230.py:2: ParserWarning: Length of header or names does not match length of data. This leads to a loss of data with index_col=False.\n",
"C:\\Users\\georg\\AppData\\Local\\Temp\\ipykernel_24336\\3411177260.py:2: ParserWarning: Length of header or names does not match length of data. This leads to a loss of data with index_col=False.\n",
" raw_data = pd.read_csv(\"2015_08_25 15.20 M12 SS100%.csv\",sep=\";\",header=7,index_col=False)\n"
]
}
@@ -53,7 +53,7 @@
"df['M1-LA'] = pd.to_numeric(raw_data['M1-LA'])/100\n",
"df['M2-LA'] = pd.to_numeric(raw_data['M2-LA'])/100\n",
"df['Druck'] = pd.to_numeric(raw_data['P-DRL'])\n",
"df['Pegel'] = pd.to_numeric(raw_data['Pegel-UW'])\n",
"df['Pegel'] = pd.to_numeric(raw_data['PEGEL-UW'])\n",
"\n",
"val_t_vec_raw = np.array(df['timestamp']-df['timestamp'][0])\n",
"val_LA1_vec_raw = np.array(df['M1-LA']) \n",
@@ -501,7 +501,7 @@
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x1e74e242940>]"
"[<matplotlib.lines.Line2D at 0x18a94bcf820>]"
]
},
"execution_count": 10,

15
Validation Data/raw data Untertweng/consolidate_validation_data_Untertweng.ipynb
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@@ -21,7 +21,8 @@
"M1_p_df = pd.read_csv('M1_Druck.txt',delimiter=';')\n",
"M2_p_df = pd.read_csv('M2_Druck.txt',delimiter=';')\n",
"M1_LA_df = pd.read_csv('M1_LA.txt',delimiter=';')\n",
"M2_LA_df = pd.read_csv('M2_LA.txt',delimiter=';')"
"M2_LA_df = pd.read_csv('M2_LA.txt',delimiter=';')\n",
"Ausl_df = pd.read_csv('AL_SeitAuslPos.txt',delimiter=';')"
]
},
{
@@ -34,7 +35,8 @@
"M1_p_df['Timestamp'] = M1_p_df['TIMESTAMP UNIX']+M1_p_df['TIMESTAMP MS']/1000.\n",
"M2_p_df['Timestamp'] = M2_p_df['TIMESTAMP UNIX']+M2_p_df['TIMESTAMP MS']/1000.\n",
"M1_LA_df['Timestamp'] = M1_LA_df['TIMESTAMP UNIX']+M1_LA_df['TIMESTAMP MS']/1000.\n",
"M2_LA_df['Timestamp'] = M2_LA_df['TIMESTAMP UNIX']+M2_LA_df['TIMESTAMP MS']/1000."
"M2_LA_df['Timestamp'] = M2_LA_df['TIMESTAMP UNIX']+M2_LA_df['TIMESTAMP MS']/1000.\n",
"Ausl_df['Timestamp'] = Ausl_df['TIMESTAMP UNIX']+Ausl_df['TIMESTAMP MS']/1000."
]
},
{
@@ -47,7 +49,8 @@
"M1_p_df.set_index('Timestamp',inplace=True)\n",
"M2_p_df.set_index('Timestamp',inplace=True)\n",
"M1_LA_df.set_index('Timestamp',inplace=True)\n",
"M2_LA_df.set_index('Timestamp',inplace=True)"
"M2_LA_df.set_index('Timestamp',inplace=True)\n",
"Ausl_df.set_index('Timestamp',inplace=True)"
]
},
{
@@ -61,12 +64,14 @@
"M2_p_df.drop(columns=['VARIABLE','TIMESTAMP UNIX', 'TIMESTAMP MS'],inplace=True)\n",
"M1_LA_df.drop(columns=['VARIABLE','TIMESTAMP UNIX', 'TIMESTAMP MS'],inplace=True)\n",
"M2_LA_df.drop(columns=['VARIABLE','TIMESTAMP UNIX', 'TIMESTAMP MS'],inplace=True)\n",
"Ausl_df.drop(columns=['VARIABLE','TIMESTAMP UNIX', 'TIMESTAMP MS'],inplace=True)\n",
"\n",
"pegel_df.rename(columns={'VALUE': 'TB-Pegel'},inplace=True)\n",
"M1_p_df.rename(columns={'VALUE': 'M1-Druck'},inplace=True)\n",
"M2_p_df.rename(columns={'VALUE': 'M2-Druck'},inplace=True)\n",
"M1_LA_df.rename(columns={'VALUE': 'M1-LA'},inplace=True)\n",
"M2_LA_df.rename(columns={'VALUE': 'M2-LA'},inplace=True)\n"
"M2_LA_df.rename(columns={'VALUE': 'M2-LA'},inplace=True)\n",
"Ausl_df.rename(columns={'VALUE': 'Ausl'},inplace=True)\n"
]
},
{
@@ -75,7 +80,7 @@
"metadata": {},
"outputs": [],
"source": [
"UT_df = pegel_df.join([M1_LA_df,M1_p_df,M2_LA_df,M2_p_df],how='outer').sort_index()"
"UT_df = pegel_df.join([M1_LA_df,M1_p_df,M2_LA_df,M2_p_df,Ausl_df],how='outer').sort_index()"
]
},
{