PulseHeatPipe

Direction to perform data analysis on the PHP experimental data.

Module for data analysis and for data plotting/visualisation specifically for PHP experimental data.

PulseHeatPipe - Module for Advanced Data Analysis and Machine Learning.

Useage:

imorting the module

from analysis 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

1. data_etl
2. gibbs_fe
3. data_chop
4. data_stat
5. data_property_avg
6. best_TP
7. plot_all_data
8. plot_Te_Tc
9. plot_eu

Example:

# importing module
from analysis import PulseHeatPipe
from analysis 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
---	---	---	---	---	---	---