PyGamLab.Data_Analysis Module

The PyGamLab.Data_Analysis module provides a comprehensive set of tools for handling and analyzing scientific data. With support for both file paths and Pandas DataFrames, it offers the flexibility to work with a wide variety of data formats and perform complex analysis effortlessly.

This module is designed for researchers and engineers who need to quickly generate automated plots, perform calculations, and extract meaningful insights from their datasets. The functions within this module offer an intuitive interface with the ability to customize outputs and calculation methods using the application argument, making it ideal for a wide range of analytical tasks.

### Benefits of the Data_Analysis Module: - Flexible Data Input: Accepts both file paths (e.g., CSV, Excel) and Pandas DataFrames, making it easy to work with data from different sources. - Automated Plotting: Quickly create high-quality, customizable plots with minimal effort, saving time in the data visualization process. - Advanced Calculations: Perform various calculations and property extractions directly from your data, with options to tailor calculations using the application argument. - Easy Integration: Seamlessly integrate into data analysis workflows, enhancing the speed and efficiency of your modeling and simulation tasks. - Customizable: Offers flexibility in how results are presented, enabling you to adjust plots and calculations to meet your specific needs.

The PyGamLab.Data_Analysis module is an invaluable tool for anyone working with experimental or simulation data, offering both the power and flexibility needed for high-performance data analysis in Python.

@author: Ali Pilehvar Meibody (Alipilehvar1999@gmail.com)

@Director of Gamlab: Professor M. Naderi (Mnaderi@aut.ac.ir)

@Graphene Advanced Material Laboratory: https://www.GamLab.Aut.ac.ir

@Co-authors:

PyGamLab.Data_Analysis.Blood_Pressure(data1, operation)

Blood is divided into two main values: systolic blood pressure and diastolic blood pressure. Systolic blood pressure represents the blood pressure at the moment the heart muscle contracts, while diastolic blood pressure represents the blood pressure at the moment the heart muscle relaxes.

This function gives us their average systolic and diastolic blood pressure And it shows us the blood pressure chart of 40-year-old Balinese people

data1int

systolic,diastolic

operation : strig operator Returns ——- None.

PyGamLab.Data_Analysis.Brain_Data_example()

This function prompts the user to input values for sudiom and potasiom along with time increments, creates a DataFrame with the provided data, and returns it.

PyGamLab.Data_Analysis.Brain_Plot_3D(df)

This function takes a DataFrame containing sudiom, potasiom, and time data and plots them in both 2D and 3D. It also compares the mean values of sudiom and potasiom to decide which one to plot in 3D.

PyGamLab.Data_Analysis.CV(data=None, Application=None, is_reversible=None)

Parameters:

• data (DataFrame) – Enter your .csv format file as pd.DataFrame. Data is the potential vs. current density expoted from the potentiostate device to study electrochemical of your fabricated electrode. To use this function correctly, the potential column should named as ‘P’ and your current density column should named as ‘C’

• Application (str) – Please enter the application you want to do for your data, including: plot, maxcurrent, peakpotential, charge, and Diffusion-coefficient.

• is_reversible (bool, optional) – If your reaction id reversible please enter ‘True’, and if the reaction is irreversible enter ‘False’ to calculate the Diffusion coefficient for your reaction.

• potential) (Application=plot (type=plot)--> Plot a cyclic voltammogram (current density vs.)

• maximum. (Application= maxcurrent (type=float)--> the function returns the peak of current that the current density id)

• current. (Application= peakpotential (type=float)--> the function returns the potential which attributed to maxmum current or peak)

• plot. (Application=charge (type=float)--> The function returns the charge corresponding to the integration of the)

• reaction. (Application=Diffusion_coefficient (type=float)--> The function returns the value according the andles-Sevcik aquation depends on reversiblly of irreversibly of)

PyGamLab.Data_Analysis.Color_Feature(filee, kar)

Parameters:

• filee (DataFrame) – data from excel.

• kar (str) – plot or calculate?

• Returns

• delta_E (a number as a)

PyGamLab.Data_Analysis.Compression_Test(Data, Operator, Sample_Name, Density=0)

Parameters:

• Data (DataFrame) – Compression test data including stress and strain.

• Operator (str) – The action that needs to be done on the data (plot or S_max). plot: Plots a stress-strain diagram.

• Sample_Name (str) – Sample name.

• Density (float, optional) – Density of the sample. The default is 0.

Returns:

If the operator is given S_max, it returns maximum strength. If the operator is given S_max/Density, it returns specific maximum strength.

Return type:

float

PyGamLab.Data_Analysis.Conversion(data, app)

This program is related to a chemical reaction laboratory, which has been measured in a table at a certain temperature, pressure and time, with a one-second interval,and gives you the highest conversion percentage at a given temperature and pressure. It also draws graphs of conversion percentage, temperature and pressure in terms of time.

Parameters:

• data (DataFrame of pandas or array of numpy) – please be careful about the inputs: your table should contain about 100 index and 4 columns.

• app (str) – Only write “PLOT_TEMP” if you want to draw the figure tempreturre over time,else if you want to draw pressure on time write ‘PLOT_pressure’ or write ‘PLOT_CONVERSION’ if you want the conversion on time figure. or write “MAXIMUM CONVERSION” if you want the maximum number of conversions at a specific temperature and pressure. Otherwise, you will see the error message below.

• TypeError – The datas or application is not entered correctly

Returns:

index_max_conv – this will gives you the highest convertion index.

Return type:

str

PyGamLab.Data_Analysis.DMTA_Test(Data2, Operator, Sample_Name)

Parameters:

• Data (DataFrame) – DMTA test data including storage modulus, loss modulus and tanδ.

• Operator (str) – The action that needs to be done on the data (storage_max, loss_max, tan_max, plot_storage, plot_loss or plot_tan).

• Sample_Name (str) – Sample name.

Returns:

If the operator is given storage_max, it returns maximum storage modulus. If the operator is given loss_max, it returns maximum loss modulus. If the operator is given Tan_max, it returns maximum Tanδ.

Return type:

float

PyGamLab.Data_Analysis.Desulfurization_Rate(Data, application)

Parameters:

• Data (Data Frame) – experimental data (excel).

• application – 1.plot 2.Max_Removal_With_Ultrasonic 3.Max_Removal_Without_Ultrasonic

• Returns

PyGamLab.Data_Analysis.Diabetes_Dataset(f, work)

Reads a diabetes dataset from a CSV file

Parameters:

• f (str) – The file path of the CSV file containing the diabetes dataset.

• work (str) – The task to perform. Supported values are: - ‘has_diabetes’: Counts the number of individuals who have diabetes. - ‘percent_has_diabetes_25’: Calculates the percentage of individuals under 25 who have diabetes. - ‘percent_has_diabetes_25_to_30’: Calculates the percentage of individuals between 25 to 30 who have diabetes. - ‘percent_has_diabetes_30_to_40’: Calculates the percentage of individuals between 30 to 40 who have diabetes. - ‘percent_has_diabetes_40_and_50’: Calculates the percentage of individuals between 40 to 50 who have diabetes. - ‘percent_has_diabetes_20_to_40’: Calculates the percentage of individuals between 20 to 40 who have diabetes. - ‘percent_has_diabetes_30_to_50’: Calculates the percentage of individuals between 30 to 50 who have diabetes. - ‘percent_has_diabetes_50_80’: Calculates the percentage of individuals between 50 to 80 who have diabetes. - ‘rel_bmi_to_diabetes_30_to_40’: Calculates the percentage of individuals with BMI between 30 to 40 who have diabetes. - ‘rel_bmi_to_diabetes_20_to_30’: Calculates the percentage of individuals with BMI between 20 to 30 who have diabetes. - ‘histo’: Plots a histogram of ages. - ‘max_age’: Finds the maximum age in the dataset. - ‘min_age’: Finds the minimum age in the dataset. - ‘max_age_has_diabetes’: Finds the individuals with the maximum age who have diabetes. - ‘min_age_has_diabetes’: Finds the individuals with the minimum age who have diabetes.

PyGamLab.Data_Analysis.Echelon_Matrix(data, ap)

یک ماتریس 90در 200 داریم که مثلا 200 مولفه را در مورد سلامت نود نفر جمع آوری کردیم و حالا میخواهیم ببینیم که کدوم یکی از این مولفه ها اضافی هستند و اطلاعات خوبی از سلامتی افراد نمیده. هدفمون اینه که ماتریس را به صورت سطری پلکانی در آوریم یعنی بالا مثلثیش کنیم و مولفه های مهم رو پیدا کنیم. :type data: :param data: This is a matrix with more than 50 rows and columns. :type data: float :type ap: :param ap: plot agar bashe, rasm mikoneh, ertebat sotoone 10 , 50 ro ba ham va agar

up bood matrix ra be soorat satri pelekani mikonad.

Returns:

A – This is a triangular matrix.

Return type:

float

PyGamLab.Data_Analysis.Energie(input_file, which)

This is a function to drawing a plot or to calculating the amount of Energie of a Motor to (open/close) a Valve in a cycle, which takes 2.7 secound to open and to close.

whichint

draw : Drawing a Plot calculate : Calculate the Consupmtion Energie in [mWs] please say which work we do ( 1 or 2).

PyGamLab.Data_Analysis.Energie2(input_file, which)

This is a function to drawing a plot or to calculating the amount of Energie of a Motor to (open/close) a Valve in a cycle, which takes 2.7 secound to open and to close.

whichint

1 : Drawing a Plot 2 : Calculate the Consupmtion Energie in [mWs] please say which work we do ( 1 or 2).

PyGamLab.Data_Analysis.FTIR(data1, application, prominence=0.5, distance=10, save=False)

PyGamLab.Data_Analysis.Fatigue_Test_Analysis(data, application)

Parameters:

• data (data is the exel file with the two columns (stress_amplitude column and number_of_cycles column))

• application (plot , max stress amplitude , fatigue strength , fatigue life , stress in one cycle , Sa ,) – fatigue limit , std stress , std cycles

Returns:

• plot (S-N plot)

• fatigue strength (استحکام خستگی)

• fatigue life (عمر خستگی)

• stress in one cycle (Basquin’s equation to define B constant.The B is the value of the stress at one cycle.)

• Sa (max stress amplitude in cycle.)

• fatigue limit (The time of cycle that stress no change.)

• std stress (انحراف معیار تنش‌ها)

• std cycles (انحراف معیارا سیکل‌ها)

PyGamLab.Data_Analysis.Find_Max_Vertical_Velocity(data)

This function gets the data results of flow velocity simulation for natural convection of a molten in a cavity. and as the output, it shows the plot of flow velocity vs x and also it returns the maximum velocity and the location where that velocity belogs to.

PyGamLab.Data_Analysis.Gradient_descent(dataset, which, alpha=0.001)

Parameters:

• dataset (str) – path of your data set .

• which (str) – plot or cost(calculuates how much error is there in the prediction).

• alpha (float, optional) – the learning rate(the size of the baby step that we will take for each of the variables). The default is 0.001.

PyGamLab.Data_Analysis.Imerssion_Test(data, application)

Parameters:

• data (.excel .csv)

• name (columns)

• application – plot:drawing the changes of weight(%) on time(days) More_Bioactive: the sample with more weight gain in result more bioactive Less_Bioactive: the sample with more weight loss in result less bioactive

PyGamLab.Data_Analysis.Import_Data(File_Directory=None)

PyGamLab.Data_Analysis.Income_Developer(file, work)

Reads income data from a CSV file and displays graphs based on the specified task.

Parameters:

• file (str) – The file path of the CSV file containing the income dataset.

• work (str) – The task to perform. Supported values are:

• 'plot_data' (-) – Displays a line plot of income over age for Python and JavaScript developers.

• 'bar_data' (-) – Displays a bar plot of income over age for Python and JavaScript developers.

• 'max_salary_data' (-) – Displays a bar plot showing the maximum income for Python and JavaScript developers.

• 'plot_bar_data' (-) – Displays both bar and line plots of income over age for Python and JavaScript developers.

• 'max_salary_data_by_age' (-) – Displays a bar plot showing the maximum income for Python and JavaScript developers based on age.

• 'alph_data' (-) – Displays a bar plot with different alpha values for Python and JavaScript developers.

• 'show_by_side_by_side_data' (-) – Displays two bar plots side by side for Python and JavaScript developers with age on the x-axis and income on the y-axis.

PyGamLab.Data_Analysis.LN_S_E(df, operation)

This function plots the ELASTIC part of the true stress-strain curve and can also calculate the Young’s Modulus(E). ———- df : DataFrame

It has 2 columns: DL(which is length in mm) & F (which is the force in N).

operation :

It tells the function to whether Plot the curve or calculate the Young’s Modulus(E).

Return type:

The elastic part of the true stress-strain curve or the amount of E

PyGamLab.Data_Analysis.Load_Position_Convertor(Data, Operation, Area, Length)

This function receives an input file containing Load-Position data, as well as the cross-sectional area and gauge length of the part, and according to the user’s needs, it can: 1-Load-Position Curve (LPC) 2-Stress-Strain Calculation (SSCal) 3-Stress-Strain Curve (SSC) 4-Normalized Stress-Strain Calculation (NSSCal) 5-Normalized Stress-Strain Curve (NSSC) 6-Energy Absorption Density Calculation (EADCal)

Parameters:

• Data (xlsx) – Need two columns containing Load-Position information.

• Operation (str) – It specifies the process that should be performed on the entered information.

• Area (float) – The surface examined in the tensile or compression test.

• Length (TYPE) – Gauge length checked in tension or compression test.

Returns:

EAD – Energy absorption desity of meta-materials such as metal foams.

Return type:

float

PyGamLab.Data_Analysis.Membrane_Rejection(Experimental_Datas)

PyGamLab.Data_Analysis.New_Case_Corona_Propotion(data, operation)

Parameters:

• data (Csv File) – data hayi darbare amar corona virus dar keshvar haye mokhtalef

• operation (az beyn "plot" va "nesbat" yeki ra mitavanid entekhab konid) – in tabe nesbat new case haye coronavirus be case haye ghabli ra ba “plot” rasm mikonad va ba “nesbat” return mikonad

PyGamLab.Data_Analysis.Oxygen_Heat_Capacity_Analysis(file_path)

This function reads the temperature and heat capacity information from the Excel file and then calculates the enthalpy and entropy values and draws their graphs.

Parameters: T: Oxygen temperature Cp: Heat capacity at constant pressure in different oxygen temperature ranges

Return: The values of enthalpy, entropy and their graph according to temperature Heat capacity graph according to temperature

PyGamLab.Data_Analysis.Particles_Size(filee1, kar1)

Parameters:

• filee1 (DataFrame) – Data from excel.

• kar1 (str) – plot or calculation.

• Returns

• diagram. (a number as an average size or plot a)

PyGamLab.Data_Analysis.Polarization(b, work)

d: dadehaye azmayeshgah shmele ghegaliye jaryan va potansiel hastand.

PyGamLab.Data_Analysis.Pore_Size(g_loc, A, P, Vis=0.0008900000000000001)

A=shows the membrane effective surface area (m2)

P : indicates the utilized operational pressure (Pa)

Vis : represents the water viscosity (Pa⋅s). The default is 8.9*1e-4.

Returns the Pore Size of membranes in nm

PyGamLab.Data_Analysis.Porosity(e_loc, Density=1)

Ww : weight of wet samples (g)

Wd : weight of dry samples (g)

V : denotes the sample volume (cm3)

Density : is the water density (g/cm3).The default is 1.

Returns the porosity of membranes

PyGamLab.Data_Analysis.Price_BTC(Data, application)

Parameters:

• Data (int) – This function needs an excel with two columns (Price and Date)

• application (str) –

  These are some ways you can use this function :

  plot Max_Price Max_Date Min_Price Min_Price

Returns:

plot of price per date Date of Maximum and minimum Price

Return type:

Plot and int

PyGamLab.Data_Analysis.Price_Change(data, operation)

Parameters:

• data (Csv File) – data ha darbare vizhegi haye gheymat yek saham dar yek rooz mibashad

• descrription

• operation (az beyn "mohasebe" va "plot"yeki ra entekhab konid)

• migirad (in function bishtarin va kamtarin gheymat saham dar yek rooz ra)

• "mohasebe" (va damane taghyirat gheymat ra ba "plot"rasm mikonad va ba)

• mikonad (return)

PyGamLab.Data_Analysis.Product_Of_Vectors(data, app)

do bordar (two vectors) be onvane voroodi migirad, va anha ra baham zarb mikonad.

Parameters:

• data (float) – yek matrix ba do sotoon ast ke sotoone aval, bordar avval, va digari bordar dovvom.

• app (str) – plot agar bashe, rasm mikoneh, ertebat do bordar ro ba ham va agar calculate bood zarb dakheli bordar avval ba tranahadeh bordar dovvom ra mohasebeh mikonad.

Returns:

output – Production of vectors.

Return type:

float

PyGamLab.Data_Analysis.Pulse(data2, operation)

This function gives us the maximum and minimum pulse of people over forty years old in the test and draws the pulse graph of people. And by using the frequency of the pulses, it is obtained

Parameters:

• data2 (int) – Pulse

• operation (string) – operator

Return type:

None.

PyGamLab.Data_Analysis.SI_Calculation(f_loc, P, PC, Density=1)

This function is used for Separation Index Calculation

P : Pressure (bar)

Density : Feed Density(g/cm3)

PC : Pollutant concentration in Feed (g/L)

Returns Separation Index and Flux & Rejection & Rejection Charts

PyGamLab.Data_Analysis.Sakhti_ab(data)

Parameters:

data (exel) – شامل تمامی داده های مورد نیاز برای بررسی سختی آب میباشد.

Returns:

• data (plot) – plot mizan sakhti ab dar nemoone ha.

• arraye – jadval nahayi.

PyGamLab.Data_Analysis.Signal_To_Noise_Ratio(data, application)

Parameters:

• data (DataFrame) –

  consists of your experimental data in 3 columns:

  1- location: the place you’ve measured signal and noise 2- signal strength: the power of signal in dbm 3- noise power: the power of noise in dbm

• application (string) –

  there is 3 application available:

  1- plot signal: plots signal column 2- plot noise: plots noise column 3- plot SNR: plots the signal-to-noise ratio

Returns:

mx – the maximum signal-to-noise ratio in dbm

Return type:

float

PyGamLab.Data_Analysis.Solidification_Start(data, Temp_sol)

This function gets the temperature values of a molten along with its solidus temperature as inputs, and if the solidification process has started it returns true and if not it returns false. it also plots the temperature values in the center line. note that this function has simplified the problem and many other parameters should be taken into consideration.

PyGamLab.Data_Analysis.Statitical_Analysis(data, operation)

this function calculate quantile, IQR, min, max, median,and zscore for each features of data set. also it is presented plot. ———————————————————– :type data: :param data: :type data: data frame :param opertaion: possible values:.

1. statistics

2. histogram

3. correlation 4.pairplot

Returns:

• 1. quantile

• 2. min

• 3. max

• 4. median

• 5. zscore

• 6. determined plot

PyGamLab.Data_Analysis.Stress_Strain1(df, operation, L0=90, D0=9)

This function gets data and an operation . It plots Stress-Strain curve if the oepration is plot and finds the UTS value (which is the ultimate tensile strength) otherwise. —————————— :type df: :param df: It has 2 columns: DL(which is length in mm) & F (which is the force in N). :type df: DataFrame :type operation: :param operation: It tells the function to whether PLOT the curve or find the UTS valu.

L0: initial length of the sample D0: initial diameter of the sample

Return type:

The Stress-Strain curve or the amount of UTS

PyGamLab.Data_Analysis.Stress_Strain2(input_file, which, count)

This function claculates the stress and strain Parameters from load and elongation data ———- input_file : .csv format

the file must be inserted in csv.

whcihstr

please say which work we do ( plot or calculate?).

count: int

please enter the yarn count in Tex

remember: gauge length has been set in 250 mm

PyGamLab.Data_Analysis.Stress_Strain3(input_data, action)

PyGamLab.Data_Analysis.Stress_Strain4(file_path, D0, L0)

This function uses the data file that contains length and force, calculates the engineering, true and yielding stress and strain and also draws a graph of these.

Parameters: D0(mm): First Qatar to calculate stress L0(mm): First Length to canculate strain F(N): The force applied to the object during this test DL(mm): Length changes

Returns: Depending on the operation selected, it returns calculated values, plots, advanced analysis, or saves results.

PyGamLab.Data_Analysis.Stress_Strain5(input_data, action)

PyGamLab.Data_Analysis.Stress_Strain6(data, application)

this function converts F and dD to Stress and Strain by thickness(1.55mm), width(3.2mm) and parallel length(35mm).

Parameters:

• data (DataFrame) – this DataFrame contains F(N) and dD(mm) received from the tensil test machine.

• application (str) – application determines the expected output of Stress_Strain function.

Returns:

return may be elongation at break, strength or a plot.

Return type:

int, float or plot

PyGamLab.Data_Analysis.Tensile_Analysis(dataframe, gauge_length=1, width=1, thickness=1, application='plot-force', save=False)

Parameters: - dataframe: raw data from Excel (Force vs Displacement) - gauge_length: Initial length of the sample in mm - width: Width of the sample in mm - thickness: Thickness of the sample in mm - application: ‘plot-force’ or ‘plot-stress’ - save: True to save the plot - show_peaks: True to annotate peaks (e.g. UTS) - fname: Filename to save if save=True

PyGamLab.Data_Analysis.Tortuosity(e_loc)

Returns the Pore Tortuosity of membranes

PyGamLab.Data_Analysis.Wear_Bar(list_1, work='bar')

PyGamLab.Data_Analysis.Wear_Rate(w, work, S, F)

w : dataframe contains 2 columns bayad shamele 2 soton bashad ke dar yek soton vazn nemoone ghabl az test andazegiri shavad , dar yek soton vazne nemone pas az etmame test.

S haman masate laghzesh hine azmone sayesh ast. S bayad bar hasbe metr bashad.

F barabare niroyee ast ke be pin vared shode ast , azmon ba an anjam shode ast. F bayad bar hasbe newton bashad

PyGamLab.Data_Analysis.XRD4(data, application)

This function plots the XRD curve .

Parameters:

• data (DataFrame) – data is XRD data include Intensity (a.u.) and 2θ (degree).

• application (str) –

  application is the function that you want to apply to your data:

  • plot : ُPlot the XRD curve

  • maxintensity : Determining the maximum intensity.

  • meantheta : Determining the mean of theta angles.

Return type:

plot, maxintensity, meantheta

PyGamLab.Data_Analysis.XRD_Analysis(file, which, peak=0)

Parameters:

• file (str) – the variable in which you saved the .cvs file path

• which (str) – which operation you want to perform on the file

• peak (float, optional) – 2θ for the peak you want to analyse. The default is 0.

Returns:

fwhm – value of FWHM for the peak you specified.

Return type:

float

PyGamLab.Data_Analysis.XRD_Analysis2(file, which, peak=0)

Parameters:

• file (str) – the variable in which you saved the .cvs file path

• which (str) – which operation you want to perform on the file

• peak (float, optional) – 2θ for the peak you want to analyse. The default is 0.

Returns:

fwhm – value of FWHM for the peak you specified.

Return type:

float

PyGamLab.Data_Analysis.XRD_ZnO(XRD, application)

Parameters:

• XRD (DataFrame) – Data containing XRD data.

• application (str) – Type of application ‘plot’,’FWHM’,’Scherrer’. plot:To draw the figure. FWHM:Width at Half Maximum. Scherrer:To calculate the crystallite size.

• Returns

• FWHM

• Scherrer

• -------

• None.

PyGamLab.Data_Analysis.Xrd_Analysis(data, operation)

XRD is a nondestructive technique that provides detailed information about the crystallographic structure, chemical ———————————————————– composition, and physical properties of a material this function return max intensity of xrd pattern and degree of difraction. also based on user requierment return specified plot. statistics analysis is presented too. ———————————————————- :type data: :param data:

data set include tow features:

1. degree (2* degree of difraction)

2. intensity

Parameters:

operation (str) –

determine an operation which apply on data possible values:

max intensity scatter plot line graph line graph fill between

Returns:

• max intensity and degree of max intensity

• or

• plot

PyGamLab.Data_Analysis.aerospace2(CSV, which)

this function has the ability to convert your datas into answers that you need your datas should be in Newton and M**2 format in this program we will be using presure as the output data if you want to make a sketch Use === Plot if you want to check the max_presure use === MaxPer

PyGamLab.Data_Analysis.aerospace_analysis(CSV, which)

this function has the ability to convert your datas into answers that you need your datas should be in Newton and M**2 format in this program we will be using presure as the output data if you want to make a sketch Use === Plot if you want to check the max_presure use === MaxPer

PyGamLab.Data_Analysis.fatigue(f_loc, which)

PyGamLab.Data_Analysis.polarization_control(Data, Application)

Parameters:

• Data (DataFrame : The results of the polymerization of a polymer control laboratory are given) –

  that included four columns: time, temperature, pressure,

  and reaction percentage of the polymer product.

  DESCRIPTION.

• Application (float) – Six applications are done in this function. 1) Application = ‘temp_time’ : Temperature is plotted according to time. 2) Application = ‘pressure_time’ : Pressure is plotted according to time. 3) Application = ‘Percent_time’ : The percentage of reaction is plotted over time. 4) Application = ‘100% reaction’: If the percentage of polymerization reaction proceed to 100, the temperature and pressure of polymerization is printed and returned. 5) Application = ‘Max_pressyre’: It returns maximum pressure of process. 6) Application = ‘Max_temp’: It returns maximum temperature of process.

Returns:

It returns temperature and pressure of process according to related application.

Return type:

float

PyGamLab.Data_Analysis.pressure_volume_ideal_gases(file, which)

By using this function, the relationship between pressure and volume of ideal gases in thermodynamic will be shown.

input_file.csv format

*the file must be inserted in csv.

whhch: str

what do you want this function to do?