The data analysis Python package for the Pulsating Heat Pipe experimental data
Project description
PulseHeatPipe
PyPulseHeatPipe is a Python Library for data analysis and for data plotting/visualisation specifically for PHP experimental data.
pkg installation
pip install PyPulseHeatPipe
Useage:
imorting the module
from PyPulseHeatPipe import PulsHeatPipe
creating the reference variable
analysis = PulseHaatPipe("datapath")
for a class help
help(analysis)
for a function help
help(analysis.data_etl)
using a function from the class
df, df_conv = analysis.data_etl
list of avilable functions
- data_etl
- gibbs_fe
- data_chop
- data_stat
- data_property_avg
- best_TP
- plot_all_data
- plot_Te_Tc
- plot_eu
Example:
# importing module
from PyPulseHeatPipe import PulseHeatPipe
from PyPulseHeatPipe import DataVisualisation
analysis = PulseHeatPipe("data/al2o3_diwater_exp/60_FR/")
visual = DataVisualisation('Al2O3_DI_60FR')
# calling help
help(analysis.data_etl)
help(visual.plot_all_data)
# using methods eg;
df, df_conv = analysis.data_etl()
visual.plot_all_data(df_gfe)
NOTE: The experimental data file must prepared in '.xlsx' formate. The data must contain atleast following columns with mentioned titles:
** Data.xlsx format**
'Time (Min)' | 'Tc - AVG (oC) | 'Te - AVG (oC)' | 'Pressure (mm of Hg)' | 'Te - Tc (oC)' | 'Q (W)' | 'Resistance (oC/W)' |
---|---|---|---|---|---|---|
1 | 30 | 35 | 700 | 5 | 80 | 0.06 |
--- | --- | --- | --- | --- | --- | --- |
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