DAIPProLi

Overview

DAIPProLi is a python script that aims to analyze the data generated by differential spectroscopy experiments.

Usage

This software is created in Google Colab. To access it, click on the Google Colab badge above or on this link.

Step 1: Check the format of the data it must be a csv file and have one of the two structures display in the examples below:

Example 1: set intercaladas=False in the function leeFichero():

Wavelength (nm)	Baseline	2	4	6	...
300	-0.0002	0.0004	0.0031	0.0034	...
300.5	-0.0001	0.0004	0.0029	0.0034	...
301	-0.0002	0.0002	0.0027	0.0032	...
...	...	...	...	...	...

Example 2: set intercaladas=True in the function leeFichero():

...	...	...	...	...	...	...	...	...	...	...	...
SAMPLES	...	...	...	...	...	...	...	...	...	...	...
Name	Baseline		0		2		4		6		...
...	...	...	...	...	...	...	...	...	...	...	...
...	Wavelength (nm)	Abs	Wavelength (nm)	Abs	Wavelength (nm)	Abs	Wavelength (nm)	Abs	Wavelength (nm)	Abs	...
	300	-0.015	300	-0.0002	300	0.0004	300	0.0031	300	0.0034	...
	300.5	-0.015	300.5	-0.0001	300.5	0.0004	300.5	0.0029	300.5	0.0034	...
	301	-0.015	301	-0.0002	301	0.0002	301	0.0027	301	0.0032	...
...	...	...	...	...	...	...	...	...	...	...	...

Step 2: Load the libraries, modules and functions (Environment). This step only needs to be performed once, regardless of the number of datasets processed.

Step 3: Run the next cell (Upload file) and do not change the parameters. A message will appear below it asking the user to select the file to be uploaded.

Step 4: Run diff_absorbance, in this cell the difference between minimum and maximum in each spectra will be performed. There is an option to choose the method to determine the minimum and maximum wavelengths. It can take the following three arguments: "Mean", "Median" and "Manual".

1. "Mean": it uses the mean of wavelengths at minimum and maximum absorbance values of all conditions evaluated.
2. "Median": it uses the median of the wavelengths at minimum and maximum absorbance values of all conditions evaluated. Default is Median.
3. "Manual": it uses min_chosen and max_chosen as the chosen wavelengths for the minimum and maximum absorbance, respectively.

Step 5: In this cell (Spectra plot) the user will be able to plot the spectra recorded for each condition in 2D and 3D. Moreover, it allows to set the names of the titles and leyend of the plots and adjust all spectra so that their absorbance is zero at a given target wavelength. To shift the spectra to zero at a given target wavelength the user has to check the box next to Shift_spectra and provide the target_wavelength.

Step 6: In this cell (Plot Δ Absorbance vs Volume (µL)) the data generated from diff_absorbance will be plotted. The title and the leyend names can be personalized.

Step 7: Here, in Model, the model that may explain the experimental data is written.

Step 8: The Parameters cell is very important. Here the user has to write the parameters needed by the model and select whether they are fixed or not. If the parameter is fixed, the procesa function (responsible for the fitting) will not optimize those values. Warning: if the values inputted for the parameters differ greatly from reality even if they are marked as not fixed the fitting process might have worse results or even fail. A good initial estimation, will provide a better fitting.

Step 9: Run the Procesa cell which will perform the fitting via the least squares method.

Step 10: Here (Plot Δ Absorbance vs Volume (µL) with model fitting) it plots the the data generated from diff_absorbance (experimental data) and the values obtained using the model and the optimized parameters from procesa.

Step 11: Lastly, this cell (Export results) saves and export all the data inputted and generated. The datasets are saved in csv format and the plots are saved in html and png. All of this items are downloaded in a zip which the user can name (but it will always have the date and hour of when the cells was run as suffix).

Troubleshooting

Case 1: CSV formatting

The program was created to handle csv whose numbers have points for decimal separators and commas for thousands separator. Other formats will not be read properly by the program. The most common alternative format is to have commas as decimal separators and points as thousands separators. In this particular case there are several solutions depending on the spreadsheet software used:

Excel

In the latest versions of this software you can use the solution depicted in the following YouTube video. Once you have opened the dataset:

1. Click on File.
2. Then, go to Options.
3. In the new window that appears, click on Advanced.
4. Once there look for the Use system separator and modify the decimal and thousands separator accordingly ("," and "." respectively).

Beware this can only be done in the Desktop version of Excel, the online version of Excel lacks this personalization and for the moment lacks a solution.

Google Spreadsheet

You only need a Google account to access it, which you also need to run the program, so everyone can have access to this software (and a relativey good Internet connection). Moreover, the solution is a bit more straightforward. Once you have opened the dataset:

1. Click on File.
2. Then, click on Settings.
3. In the new window set the Regional settings to English (EE.UU.). The drawback is that in this case all formats will change to those of the United States (e.g. dates, ...). However, it can be easily changed any time.

LibreOffice Calc

LibreOffice Calc is part of the LibreOffice environment and is free of charge. Once you have opened the dataset:

1. Click on Tools.
2. Then, click on Options.
3. In the new window that appears, click Languages and regions, and then on General.
4. Once there set Regional configuration to English (EE.UU.). This has the same drawback that Google Spreadsheet but can be personalized a little bit further.