- Table of Contents
- Overview
- Features
- Project Structure
- Modules
- Getting Started
- Roadmap
- Contributing
- License
- Acknowledgments
The Ionozor project provides tools for analyzing Very Low Frequency (VLF) data as well as an accessible platform for sharing the corresponding results. Leveraging the Python and Octave/MATLAB languages, this project helps deliver deep scientific data-based insight into ionospheric and space-based phenomena, including the analysis of radio signals from various sources like meteor and solar activity effects on the ionosphere. Equipped with algorithms, the project provides visualization and carefully considered processing of general ionospheric and radio-signal-based data, paving the way for detailed analysis to a level where plasma and electromagnetic interactions at different altitudes are available. This contributes to a deeper understanding of interactions between Earth's atmosphere and outer-space phenomena and could support wider scientific research in astronomical events, meteorology, and atmospheric physics, essential for scientists and researchers in relevant domains.
| Feature | Description |
|---|---|
| ** Architecture** | The project utilizes a highly language-diverse architecture, mainly consisting of Python and Octave; the former for digital signal processing and data handling and the latter for numerical computations involved in VLF data analysis. |
| ** Documentation** | Although detailed logging is provided in the code, understanding individual functions and their data-flow aren't outwardly unfolded. Explicit in-line code commenting is missing, decreasing rapid cognizance of distinct code sections. |
| ** Dependencies** | The codebase is dependent on external libraries. Python notebooks appear to use libraries such as os and urllib for data handling. Octave scripts necessitate specialty packages for numerical and signal processing. |
| ** Modularity** | The system modules are well-separated according to their functionality. E.g., Octave-based data extraction & processing in unique files, whereas plotting parameters are managed and grouped by separate Python codes. Data is transferred between these modules via intermediate storage. |
| ** Testing** | The repository, however, does not involve explicit testing codes. Thus, user testing, probable hardcoded debugging, and trial-run methodologies can be assumed but these won't vouch for systematic, rigorous validation. |
| ** Performance** | Considering the limited availability of function benchmarks; structured high-performance cannot be conclusively confirmed. Efficient computational operations have still been considered e.g., keeping intermediate files minimal/flushing almost certain outcomes. |
| ** Security** | Proper security measures are not explicitly showcased. Using urllib library for cloud-based computations can arguably raise concerns due to nonencrypted or authenticated channels of information request/transmission. |
| ** Version Control** | Github is utilized for versioning, but no outlines probably contradicts regular or hierarchic updates. Most scripts are standalone; version control seems redundant here. Keeping more utility functions could have maximized script-upgrade tracking. |
| ** Integrations** | Its integration being pulling data from AWS servers online. Saving processed stimuli in HDF5 (Hierarchical Data Format), evidently meeting requirements of efficient data exchange & archival storage. |
| ** Scalability** | Its manageable division across services ascertains better lateral scaling. The python requires linear scheme progression, though fits well with horizontally derived data considerations seen here networking or user-access scalability scopes remain questionable. |
Python
| File | Summary |
|---|---|
| [VLF data overview.ipynb](https://github.com/Ionozor/data-processing/blob/main/Python/VLF data overview.ipynb) | HTTPStatus Exception: 429 |
| [VLF data processor.ipynb](https://github.com/Ionozor/data-processing/blob/main/Python/VLF data processor.ipynb) | This script ingests data captured from a Very Low Frequency (VLF) measurements of space-based phenomena, particularly the ionospheric plasma data, then applies some basic plasma physics computations over it. It imports the values, corrects time difference, imports data as a range before downloading the fits images of particular date range and place. Further, it derives more values using many physics constants and worked data, and then simplifies data output for efficient plotting and visualization. After visually plotting data computations, it also takes care of deleting temporary files it worked on. |
| [Interactive VLF data processor.ipynb](https://github.com/Ionozor/data-processing/blob/main/Python/Interactive VLF data processor.ipynb) | HTTPStatus Exception: 400 |
| FITS_merge.ipynb | HTTPStatus Exception: 429 |
| writter.py | This code is a set of functionalities for processing and manipulating Very Low Frequency (VLF) radio wave image data. It downloads images from a specified source URL, filters the data based on specified time values and downloads the data in FITS format. Then, the user has options to make a mosaic of these images along specified dimensions and to divide them by color channel. Essentially, it automates and simplifies data collection and preprocessing for radio astronomy science analysis. |
| [VLF FITS collector.ipynb](https://github.com/Ionozor/data-processing/blob/main/Python/VLF FITS collector.ipynb) | This Jupyter notebook, locally called'Ionozor FITS collector', is essentially processing very low frequency (VLF) data. Written in Python, it loads requisite libraries; sets computation parameters for a specific source URL and time frames; and defines various functions to handle imagery data (such as downloading and concatenating varying sets of FITS images from a URL, splitting multiple color channels into respective singular channels, and creating mosaics of these images along different geometric axes). Overall, it manipulates downloaded radio astronomical data for analysis. |
Zpracovani_dat
| File | Summary |
|---|---|
| vyboje1.m | The code largely embraces data manipulation and graphical representation in mathematical computations. Its function is to load timestamps and vibration data sets, run calculations, generate a mesh plot ideal for 3D linear data, and save the output visual representation. It integrates operations like copying datasets, data transformation, and plot labeling. |
| model_SID1.m | The code visualizes and compares the radio signal intensity levels between model results and actual measurement results. First, it takes data from several text files containing data of time intervals and radio signal intensities. It normalizes model data by adding 10 for visual compatibility then it creates a 2D plot, visualizing model result ('m;Model;') in magenta and the measurements('b;Measurement;') in blue. Label details are added, the resulting plot image is saved in.jpg format, sandbox memory is cleared after use. |
| model_SID.m | The provided script loads data from files(t0.txt, L0.txt, t.txt, L.txt) required for the processing. It plots a model graph (t0,L0-log) represented in magenta, identified by "Model". After generating the model plot, it holds it. A measurement graph is drawn over the model plot displayed in blue, termed "Measurement". After finalizing the plots, the hold is deactivated. The axis labels are defined and the final graphical representation is printed as'SID_model_date.jpg'. The print command also dictates certain specifications: the landscape orientation, font, and size. Lastly, the script closes after the operation is completed. |
| distance.m | The code performs data analysis on the x and y values loaded from separate.txt files. It applies a complex mathematical function to transform the data into a measure'd'. This value is then scaled to'l' using an exponential function and converted to light years. Info about'l' is plotted on a log scale graph highlighted by time interval (x, the independent variable) and ray burst distance (y, dependent). Then, the graphical findings are thereafter saved as a.jpg file, and numerical results are serialized to'Distance.txt'. |
| teplota.m | The script calculates and plots the plasma temperature based on electron density data over a given timespan. The calculations involve physical constants and functions such as the Debeye length and frequency. The plots are labelled and saved as a.jpg file, and temperature data is saved in a.txt file for further analysis. |
| radioteleskop.m | The code, written in MATLAB, uses VLF data for analysis of radio signalsObservations from a radio telescope. It load time-related and signal-related data from'x.txt' and'y.txt' respectively. A scatterplot is created using'x' and'y' data with a label'Radio Telescope' on a red line. The X-axis label is set as'Time interval [t/24 hrs.]' and Y-axis label as'Radio signal intensity level [dB]'. A.jpg file named'Radiotelescope_date.jpg' is saved using a print statement. Size adjustment, font, and landscape orientation are modified for the image output. |
| ionizace.m | The script computes ionization degrees using the Saha and particle dispersion equations, taking into account parameters like electron temperature and density. The results are output by plotting ionization against time and saved as an image plus exporting data as a text file. |
| zarivy_tok.m | The code analyzes Very Low Frequency (VLF) data. It loads time, activation energy and electron density data, then calculates'F' factor by implementing derivative formula. Next, it converts energy to Flux and plots it against time, saving the graph and its data file. Once plot's saved, it's closed to clear memory. |
| ionogram.m | The script performs analysis of Ionospheric VLF data, calculating electron density gradient change associated with altitude (H) and electron density change (L). It computes several expressions with these measurements, alongside time as variables. It visualizes the computed measurements in 3D plots, classified into'Ionogram' and'Gradients', saved as jpg and an ASCII text file. |
| teplotni_zmena.m | The code serves primarily for solving derivations and performs VLF (Very Low Frequency) data analysis related to physics and electronics. Firstly, it loads data from.txt files. Adjustments occur in loaded data (L1) calculation through a multiplication of 0.1. The values associated with electric charge (e), permittivity of free space (epsilon), k_B (Boltzmann's constant) form scientific values required for the later utilization. Then the electron density (n) and kinetic energy (E_k) get calculated in preference to solving derivations. E_k variable takes negative scaling and conversion into electronvolt (E_k1), which helps in modeling the probable functions W_k applied by employing inversion/perlustration of energies (E_k, E_k1) and obtaining critical calculation derived (T) from ratios of respective energies (W_k) and Boltzmann Constant(k_B). The code is noted not to save the results or generate images. |
| zareni.m | This script calculates and visualizes the X-ray flux (energy per area per time) in the Debye Sphere as a function of time and electron density. The model employed uses time-varying components such as a negative reciprocal fifth power of time, and an exponential decay term, scaled by the electron density. The results are then graphed in a 3D plot with specified dimensions and labels, then saved as a.jpg image. |
| teplo.m | This code performs computations related to plasma physics. It reads files't.txt','L.txt', and'electron_density.txt', then calculates specific calorific capacity'c_eV' and heat'Q_eV' using provided mathematical formulas. Both calculated values are plotted with respect to time, saved as images titled'Specific_calorific_capacity_date.jpg' and'Heat_date.jpg', and as text files. Additionally, the code calculates the difference in heat'dQ' and saves it as a text file'dQ.txt'. |
| zrychleni_elektronu.m | This code facilitates data analysis of VLF(scroll speed) records. It initiates by loading previously styled data records ('zrychleni.txt') and time intervals ('t.txt'). It then plots a graph using this data, labeling axes with appropriate units before exporting the final graph as a PNG file labeled'Acceleration_date.jpg'. The code ends by saving the acceleration data as an ASCII file and terminating the process. |
| hustota.m | This code represents the analysis of Very Low Frequency (VLF) data mainly used to evaluate electron density in particle physics. After some initial constant definitions, it loads text data consisting of frequency observations, computes the electron density based on these values and performs a differential analysis. The program outputs results both graphically (as a.jpg file plotting time against electron density) and textually (saves data as.txt files). |
| kineticky_model.m | This script processes data related to radio astronomy, performing rudimentary analysis on VLF (Very Low Frequency) transmissions. The data presumably relates to some energy transmission in a cosmic physics context (electron kinetic energy), but lacks more explanation. The script reads time & signal data from two separate files (t.txt & L.txt). Then it scales the signal data, performs warping, and runs few complex calculations using constants related to physics such as motion formula and Boltzmann constant. The output differentiates the computed kinetic energy, and it's stored in a text file hybnost_el.txt. |
| entropie.m | The code loads data from't.txt' and'dQ.txt', which presumably pertain to time intervals and thermodynamic heat. It then calculates the thermodynamic entropy "S", plotting "S" against time intervals on a log scale. It labels the graph and saves it as'Entropy_date.jpg'. Lastly, the code saves entropy values'S' as an ASCII file. |
| solar.m | This code analyzes VLF data related to solar impacts with computational physiology. The script does:1. Data loads from various sources t.txt, lambda_S.txt, etc.2. It calculates the temperature T of the solar impacts and plots it versus the instance of time t.3. The electron density n is also determined and visualized.4. Hypothetical atomic numbers Z are computed, they express ionization levels at every time point with a plot generated.5. All the calculated values are then saved as ASCII txt files for future use. |
| plasma.m | The code calculates & visualizes spectroscopic parameters for atmospheric plasma reactions involving multiple gases like O2, N2, N2O, NO and CO2. It helps in analysing decay rates of reaction wavelengths and energy levels variations across time intervals, displaying the results in a graphical format and a *.txt file. |
| impakt.m | This code analyzes VLF data functionality related to plasma atmosphere parameters. It calculates and visualizes electron density, thermodynamic temperatures, and wavelength associated with the ejections from meteors and the sun. It is based on physical constants and data derived from separate txt files. Also, it saves the resulting data for its offline usage to'txt' files. |
| ionosphere.m | The code calculates and visualizes horizontal flows in the atmosphere. It reads time (t), intensities (L), and height data, performs mathematical manipulations to compute the horizontal flow using an exponential decay model. Plots are generated showing horizontal flow over time, its vertical and horizontal distribution. Results are exported as images and an ASCII-compliant text file. |
| kineticka.m | This script in MATLAB loads a temperature file't.txt', calculates kinetic and potential energy in electronvolts of previously defined plasma and electron parameters over time, saves results as ASCII files. It also computes and saves an electron momentum. Additionally, a graph for kinetic energy vs. time interval is generated, saved as a jpg file. |
| frekvence.m | The script essentially computes, plots, and saves electron plasma frequency data from specified input. It calculates frequency changes ('nu_Delta') using provided electron mobility ('hybnost_el') and light speed constants. It then adds a base frequency (23400 Hz), plots the result using time data ('t') for the X-axis, and final frequency for the Y-axis. This graph is saved as a'jpg', and associated frequency change data is saved as an'ASCII' file. |
| energie_radioteleskop.m | The script analyzes data from x.txt and y.txt regarding time intervals and power respectively. It calculates energy using nuclear radiation constants and the initial least power level, and arrives at a Berlinur's oscillator radiated power to assess more specifically gamma radiation (X-ray) energy changes throughout time. This requires an interconversion between energy using Planck's constant and various frequencies. The results are visually plotted, particularly as a function of time intervals, and stored as both a hi-res image and ASCII-coded text-file. |
| plazmovy_parametr.m | This script achieves data analysis for Very Low Frequency (VLF) recordings. It initially loads time vector data and calculates plasma's Debye length. Next, the data related to'electron_density' is loaded, then the Plasma Parameter(N_D) is calculated and plotted in correspondence to the time interval. It finally saves and exports this plot in.jpg format while also storing the plasma parameter data in a.txt file. |
| vyska_ionosfery.m | The script performs analysis on loaded VLF (Very-Low-Frequency) data regarding electron density, adjusting for magnetic flux and diffraction over time, then calculates the height with the altered electron density over the time period. The calculated height is plotted against time with part of it represented as a stem plot. They are saved as images and the calculated height array is saved as an ASCII file. |
| spectrum.m | This code comprehensively analyses VLF signals data related to different elements (O2, N2, N2O, NO, CO2). It calculates the respective energy levels, loads in parameters from external files, adjusts those parameters for changeable conditions like electron density and plasma parsing. This results in adjusted Lambert wavelengths that are then plotted as energy levels over defined time intervals. The generated plots visualize the energy spectrum of the processed elements as well as X-rays. The spectrums and diagrams are saved as.jpg and.txt files for further use. |
| rychlost.m | The code accomplishes four main tasks: it calculates electron velocity based on electron temperature and density along with Debye length, plots this velocity against time, saves the plot, and computes their deceleration. The results are stored in output file. |
| debeyova_delka.m | The script represents a part of a VLF data analysis that computes the Debye radius-a parameter showing the scale of an electron's influence in a plasma. The code imports a text file, calculates Debye's radius using the given electron number density (n) and temperature (T), plots it against time, saves the plot as a.jpg file, and also saves these radius values into a.txt file. |
| potencialni.m | The script loads data from three text files. It calculates the potential energy (W_p1) using the data from'kinetic_work.txt' and'plasma_parameter.txt'. Then, it plots the potential energy against an unit time interval, labeling the axes, saves the plot as a.jpg file, and also as a data file (.txt), containing potential energy. |
| vyboje.m | This code section is built to perform VLF (Very Low Frequency) data analysis. The program loads specific files with data for computation before creating variables X, Y, Z, X0, Y0, Z0 using the given formulas. A 3D mesh is generated to represent data graphically. Two meshes are put on and held in one figure using the command'hold', and labels are added for clarification. The final mesh is exported to a'Discharges_date.jpg' file before closing. The program is primarily based on manipulating and visually presenting loaded data. |
| vychyleni.m | The code imports and measures variable affect of Vostok Low Frequency data, loading temperature and electron density files. Debye length (plasma characteristic) and electron temperature are computed. A fluctuation scope output is established (plasma oscillation size), displayed graphically, then saved in txt and jpeg formats. |
| aktivacni.m | This script performs VLF data analysis for Ionozor group. It loads existing datasets related to time, electron density, and dn files before calculating the energy level of ionization and respective frequencies. It constantly manipulates the loaded data with physical constants to extract important measures such as activation energy and ionization frequency. Extracted measures are then visually represented in plots and saved as jpg & text files. |
| tderiv.m | This script analyses Very Low Frequency (VLF) data. It derives time gaps between observations in't.txt' file using the'diff()' function, which calculates differences between successive time points. The results of these calculations are then saved into'dt.txt' file and existing data visualizations are closed. |
| intenzita.m | The code performs data manipulations and analysis about Very Low Frequency (VLF) meteor and solar data with respect to time intervals. Firstly, it runs computations on prominent properties such as electron density, thermodynamic temperature; and it applies different textbook physics formulas on variables loaded from imported files. It plots graphs for various parameters like Intensity varying over time for both solar and meteor data and saves the result quantitatively and graphically. It also computes theory-based attributes-wavelength, temperature, electron density, plasma parameters, and atomic number of meteor coverage, graphically representing changes against time, and saves these calculations and plots to appropriate output files. |
| meteoric_spectra.m | This script, primarily for VLF data analysis, calculates the effective temperature from loaded waveform data, subsequently plotting and saving it. It determines emission wavelengths and hypothetical atomic numbers, plots these against time intervals, and saves plots and calculations. Lastly, the script calculates electron density and presents it in both plotted and saved textual formats. |
Bin
| File | Summary |
|---|---|
| speclab2octave.sh | This is a Bash script for managing data, primarily performing data extraction and time conversion. The script requires three command line arguments representing input_file, output_file1, and output_file2. It performs file-processing tasks: extract the first two column-values from input CSV file-convert the time value (given in second column of hh:mm:ss format) to its decimal representation and save it in output_file1, extract and save second column data into output_file2. |
| pathlocation.m | The code is retrieving data sets of the previous day's Very Low Frequency (VLF) observations from the Ionozor's web server. The first set of code gets yesterday's date and constructs file paths. There are hard extensions for the assumed-life paths, with statistic names like VLFOSTROV, HFKVARY, and RATIOS. Data is fetched using'urlread' function, put often on local folders depending on statistical names (which is changed/directed thrice) and their pathways are set. It also creates directories in the local system for each set. Variables'stept' and'stepnu' are set to 0.5 and 10 respectively (could be used, omitted in the given texts). Lastly, SID1-a not defined command, function or script is run. The exact purpose of not accounting for this therefore cannot be ascribed properly. |
| one_shot-old.sh | This bash script iterates through four different locations and all the days from 2015 and 2016. For each day in each location, it runs the shell script'process_data-old.sh'. The script path, location, year, month, and day are passed as arguments to the called script. |
| one_shot-location.sh | The script automates processing of data in specific location(s) using another bash script (process_data-location.sh). Currently, it runs the processing script for the HVEZDARNA location for some specific range of dates within the month of March, 2016, with results and errors stored in os.out and os.err files respectively. |
| speclab2octave2.sh | This Bash script encapsulates a functionality capable of reading data from an input file and refining the extracted data. Primarily, it prints the first two columns and then converts the time represtation. It uses AWS to manipulate data & mathematical computations, to calculate time in seconds, before saving to an output file. |
| process_data.sh | This bash script sets up an automated daily job to process weather data files. For each of four specified locations, it runs a script named'process_data-location.sh', passing location-specific and yesterday's date details as inputs. The data is stored in a Dropbox location. |
| one_shot-sid.sh | The script runs'process_data-sid.sh' script for multiple specific locations (HVEZDARNA, OSTROV, SOKOLOV), and for each day of the years'15 and'16. The input parameters for the'process_data-sid.sh' script are each location, year, month, and day; the standard output and error output are redirected to'os.out' and'os.err' files respectively. |
| SID1.m | The provided code is designed for very low frequency (VLF) data analysis, primarily analyzing ionized electrons in the atmosphere. It calculates and stores various attributes of the atmosphere such as electron density, temperature, plasma parameter, kinetic and potential energy, the scope of fluctuation, and more. Also, it evaluates specific attributes related to soundwaves, generated by the effect of particles resulting from the introduction of power into the earth's atmosphere due to different events occurring in space including meteors, the Sun, etc, and their impact on the ionized particles. |
| process_data-old.sh | The script first checks and prepares the directories and files. Then, it converts Spectrum Lab data files for Octave scripts, this depends on the location (HVEZDARNA, OSTROV or SOKOLOV). Subsequently, it executes different series of data processing Octave ".m" scripts based on the location and inserts zero values at required lines in input text files. After every Octave execution, it checks and cleans up empty stderr files too. |
| process_data-location.sh | This script primarily manages data manipulation for use by Octave.m scripts, generated by Spectrum Lab from different locations (HVEZDARNA, OSTROV, & SOKOLOV). Initially, the script checks, creates necessary directories, and clears destination before processing: it transforms.txt spectral data from these sources into Octave-friendly input, runs a set of Octave.m scripts (using a'nice' priority), specific to each source to process the data, with another set for common data flow. Scripts executed depend on the "location" value, along with an error checking functionality. It also deletes empty.err (stderr) outputs and prepares maintenance functions for files with warnings and generated meteroic spectra. |
| one_shot.sh | This Bash script automates data prep for Octave data analysis. It explores given directories corresponding to specific locations (namely, HVEZDARNA, OSTROV, SOKOLOV, and SUN) for txt files tagged by date. If these exist, they're processed by a'speclab2octave' script and outputted as separate data files into a created directory within Octave's data folder. The handling varies depending on whether the directory corresponds to'SUN'. |
| process_data-sid.sh | This script converts.txt data from Spectrum Lab into a format for Octave scripts, and then runs these scripts. It takes four parameters: source, year, month, and day, then locates the input file in a specific directory. If the input file, processing directory, and output directories exist, various Octave scripts are run. Finally, all results, including errors and output files, are moved to an archive directory. |
User data mining
| File | Summary |
|---|---|
| [VLF_spectrum.m](https://github.com/Ionozor/data-processing/blob/main/Octave/bin/User data mining/VLF_spectrum.m) | The code loads VLF (Very Low Frequency) radio spectrograph data and filters based on desired time and frequency range. It averages the intensity levels over the selected range and provides a two-dimensional spectrograph display. Simultaneously, it saves the modified data in an HDF5 file. |
| [drift.m](https://github.com/Ionozor/data-processing/blob/main/Octave/bin/User data mining/drift.m) | This MATLAB program is designed for analysis of very low frequency (VLF) data. It computes spectra using physical parameters such as time and Electromotive force function, calculates Debye radius and height data, computes concentration dependent on height, and draws a 3D mesh plot for visualizing horizontal flow against height. It saves the calculated data as hdf5 files. |
| [ionogram.m](https://github.com/Ionozor/data-processing/blob/main/Octave/bin/User data mining/ionogram.m) | The supplied code functions in analyzing Very Low Frequency (VLF) data by creating a time-labelled ionogram. It extracts a specific timeframe from the given dataset before computing a modified mean. Moreover, it calculates the Debye radius(Gaussian units), which is saved into an hdf5 file. It computes arrays of parameters based on the extracted data gleaning insights on energy, temperature, electro-density fluctuation, and changes in plasma frequency, employed in calculating altitude parameters used in estimating ionosphere's height through their data bundles. It then draws a 3D plot depicting densities of ions in response to altitude and time within the specified interval. |
| [spectra.m](https://github.com/Ionozor/data-processing/blob/main/Octave/bin/User data mining/spectra.m) | The code calculates and visualizes spectrographic data received from an analyser that studies electromagnetic transmissions such as cannot waves. It applies mathematical and physical calculations on the input data to obtain relevant electron properties. Some properties evaluated are wavelength, intensity, Debye Radius and temperature. |
| [introduction.m](https://github.com/Ionozor/data-processing/blob/main/Octave/bin/User data mining/introduction.m) | This code enables data browsing for SID monitors, representing several key functionalities such as: 1. VLF Spectrum-to generate the radio wave spectrum reflecting the behavior of the D ionospheric layer. 2. Ionogram-a time-related diagram describing the ionosphere's condition. 3. 3D Ionospheric model-graphic representation of D ionospheric layer focusing and defocusing facades. 4. High-energy impact spectra-approximation of high-energy impact parameters within ionospheric responses. |
| [continue.m](https://github.com/Ionozor/data-processing/blob/main/Octave/bin/User data mining/continue.m) | The core functionality of the code is to structure a specific HTTP request path and send that request online to obtain monitoring data regarding Very Low Frequency (VLF) electromagnetic waves. It outlines further steps to display that data, presenting the user with diagnostic methods like spectrum analysis data, ionograms, 3D ionospheric models, or high-energy impact spectra. |
| [SIDrequest.m](https://github.com/Ionozor/data-processing/blob/main/Octave/bin/User data mining/SIDrequest.m) | This script browses data for SID monitors and it involves four user specified parameters: observatory location, station, specific date and time range. Users input commands to display data from a chosen location, from a specific station on a particular date and within a desired timeframe. |
Contributions are always welcome! Please follow these steps:
- Fork the project repository. This creates a copy of the project on your account that you can modify without affecting the original project.
- Clone the forked repository to your local machine using a Git client like Git or GitHub Desktop.
- Create a new branch with a descriptive name (e.g.,
new-feature-branchorbugfix-issue-123).
git checkout -b new-feature-branch- Make changes to the project's codebase.
- Commit your changes to your local branch with a clear commit message that explains the changes you've made.
git commit -m 'Implemented new feature.'- Push your changes to your forked repository on GitHub using the following command
git push origin new-feature-branch- Create a new pull request to the original project repository. In the pull request, describe the changes you've made and why they're necessary. The project maintainers will review your changes and provide feedback or merge them into the main branch.
This project is licensed under the GPL 3 License.