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CITT Dortmund läuft, Tests hinzugefügt

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Markus Clauß
2023-02-28 16:11:55 +01:00
parent e861dbf10e
commit e5c9f6904c
7 changed files with 136 additions and 124 deletions
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98
src/paveit/labtest/citt.py
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@@ -5,19 +5,21 @@ from csv import reader
import numpy as np
import pandas as pd
from paveit.labtest import DataSineLoad
from torch import isin
class CITTBase(DataSineLoad):
def _calc(self):
return (self.df.mean().mean(), self.df.max().max())
class CITT_KIT(DataSineLoad):
def _calc(self):
return (self.df.mean().mean(), self.df.max().max())
def _process_data(self):
logger.debug('convert bytes to pandas.DataFrame')
self._logger.debug('convert bytes to pandas.DataFrame')
self.data.seek(0)
with io.TextIOWrapper(self.data, encoding='latin-1') as read_obj:
@@ -82,7 +84,6 @@ class CITT_KIT(DataSineLoad):
idx = t[(t['ZEIT'] >= tmin) & (t['ZEIT'] < tmax)].index
N[idx] = i
t['N'] = N
res.append(t)
@@ -96,8 +97,9 @@ class CITT_KIT(DataSineLoad):
#define in class
self.data = res.reset_index()
class CITT_PTMDortmund(DataSineLoad):
def _define_units(self):
self.unit_s = 1 #mm
@@ -106,15 +108,16 @@ class CITT_PTMDortmund(DataSineLoad):
def update_parameter(self):
self.meta_names_of_parameter = {'sigma': ['Max. Spannung', 'Max Stress'],
'f': ['Frequenz', 'Frequency'],
'T': ['Versuchstemperatur', 'Target Test Temperature'],
'Nfrom': ['Erster Aufzeichnungslastwechsel', 'Start Cycle'],
'Nto': ['Letzer Aufzeichnungslastwechsel', 'Last Cycle'],
't': ['Zeitfolgen', 'Time Series'],
'speciment_diameter': ['Durchmesser (mm)', 'Diameter (mm)'],
'speciment_height': ['Länge (mm)', 'Length (mm)'],
} #list of names
self.meta_names_of_parameter = {
'sigma': ['Max. Spannung', 'Max Stress'],
'f': ['Frequenz', 'Frequency'],
'T': ['Versuchstemperatur', 'Target Test Temperature'],
'Nfrom': ['Erster Aufzeichnungslastwechsel', 'Start Cycle'],
'Nto': ['Letzer Aufzeichnungslastwechsel', 'Last Cycle'],
't': ['Zeitfolgen', 'Time Series'],
'speciment_diameter': ['Durchmesser (mm)', 'Diameter (mm)'],
'speciment_height': ['Länge (mm)', 'Length (mm)'],
} #list of names
self.data_column_names = {
'time': ['Time Series'],
@@ -132,7 +135,6 @@ class CITT_PTMDortmund(DataSineLoad):
diameter = []
height = []
for sheetid in range(num_sheets):
temp = pd.read_excel(self.data, sheetid, skiprows=97)
temp = temp.drop(index=0)
@@ -141,24 +143,23 @@ class CITT_PTMDortmund(DataSineLoad):
for col in temp.columns:
temp[col] = pd.to_numeric(temp[col])
#read metadata from file
meta = pd.read_excel(self.data, sheetid,
skiprows=1,
nrows=80)
meta = pd.read_excel(self.data, sheetid, skiprows=1, nrows=80)
meta = meta[meta.columns[[0, 2]]]
meta = meta.set_index(
meta.columns[0])
meta = meta.set_index(meta.columns[0])
meta = meta.dropna(axis=0)
meta = meta[meta.columns[0]]
meta = meta.to_dict()
#remove whitespace in dict keys:
meta = {x.strip(): v for x, v in meta.items() if isinstance(x, str)}
meta = {
x.strip(): v
for x, v in meta.items() if isinstance(x, str)
}
frequency_test = None
# add metadata to dataframe
@@ -167,21 +168,21 @@ class CITT_PTMDortmund(DataSineLoad):
v = None
for name in names:
try:
v = np.round(float(meta[name]),5)
v = np.round(float(meta[name]), 5)
if par == 'f':
v = np.round(v,2)
v = np.round(v, 2)
break
except:
pass
assert v is not None
temp[par] = v
if par == 'f':
frequency_test = v
# read additional parameters
names = self.meta_names_of_parameter['Nfrom']
for name in names:
@@ -191,7 +192,7 @@ class CITT_PTMDortmund(DataSineLoad):
except:
Nfrom = None
assert Nfrom is not None
names = self.meta_names_of_parameter['Nto']
for name in names:
try:
@@ -209,32 +210,29 @@ class CITT_PTMDortmund(DataSineLoad):
break
except:
time_idx = None
assert time_idx is not None
temp['N'] = 0
assert time_idx is not None
self._logger.info(f'cycles from {Nfrom} to {Nto}')
temp['N'] = 0
#BUG: Ist in Messdatei falsch definiert und wird von PTM angepasst. '''
#for cycle in range(Nfrom, Nto+1):
dt = 1.0/frequency_test
dt = 1.0 / frequency_test
tmax = dt
max_timeindex = max(time_idx)
cycle = 0
while tmax < max_timeindex:
# time window
tmin = (cycle) * dt
tmin = (cycle) * dt
tmax = (cycle + 1) * dt
#filter data
idx = temp[(time_idx >= tmin)
& (time_idx < tmax)].index
idx = temp[(time_idx >= tmin) & (time_idx < tmax)].index
#set cycle number
temp.loc[idx, 'N'] = cycle
cycle += 1
# add diameter and height to list
@@ -247,7 +245,7 @@ class CITT_PTMDortmund(DataSineLoad):
v = None
assert v is not None
diameter.append(v)
names = self.meta_names_of_parameter['speciment_height']
for name in names:
try:
@@ -257,7 +255,7 @@ class CITT_PTMDortmund(DataSineLoad):
v = None
assert v is not None
height.append(v)
#append data to final dataframe
res.append(temp)
@@ -270,13 +268,11 @@ class CITT_PTMDortmund(DataSineLoad):
# self.metadata['speciment_diameter'] = np.mean(diameter)
#if not 'speciment_height' in self.metadata:
# self.metadata['speciment_height'] = np.mean(height)
#define in class
self.data = res.reset_index()
self.metadata.update(meta)
# log infos
self._logger.debug(self.metadata)
self._logger.debug(self.data.head())
self._logger.info(self.metadata)
self._logger.info(self.data.head())