prognoz

main is prognoz.py

ABOUT

A program for prediction new perspective mineral deposits areas.
You could use one or more unique areas. At least one should have deposits points. The program makes preprocessing of rasters, extracts rasters values at points, fits SVC (Support Vector Classification) and MLP (Multi-Layer Perceptron) classification models. Finally, the system applies models to selected areas. If there are multiple areas with points - the latter will be consolidated into one table.

The unique feature of program is the wavelet decomposition preprocessing method. The main idea is integral nature of geological fields: signals of different scales from most regional provinces to local orebodies are overlayed in geological fields. Therefore, wavelets are used as an attempt to separate these signals and find the most valuable for prediction.

The program also offers feature selection methods: multicollinearity exclusion by r-Pearson values, univariate F-scores, RFE with logistic regression.

Input:

• folder with subfolders. Each subfolder - unique area with files inside (rasters, shapefiles).
• rasters must of a *.tif extension:
  • Within each area they must have equal sizes (width x height);
  • They should be georeferenced;
  • They could contain NaN values, nodata values (substitute values for nan);
  • They could be multiband. In this case just add the same name file with *.txt extension. Inside each line equals name of a band. In case of an error, band names will be generated automatically (band 1, band 2, etc.)
  • rasters could be binary [0, 1].
• Deposits.shp - a file containing deposits points or multipoints
  • it must has a column named "Commodity" (string). There you assign classes that should be discriminated, e.g.: "Au epithermal", "SEDEX", "Cu-porphyry", "background", etc.
  • it is optional to have additional columns:
    • Label - str, names of points to show;
    • Train - str, only two values: Train, Test - specify which points will be in Train subset, which in Test. You could generate new split anytime;
  • should be the same CRS as rasters, or errors will occur;
  • If it has multipoints (assume several pits for one deposit): in case of binary feature a mode value will be calculated, in case of real number - a mean value;
• Boundaries.shp - lines to show on a plot. Just for picture.

Output:

geotifs with predictions for each class, or binary classifications. Plots.

HOW TO LAUNCH

The program is written in Spyder IDE on Python 3.9.10.
All requirements are listed in a file of the same name. But in short you need:

• pip libraries:

  • pandas
  • numpy
  • scikit-learn
  • scikit-image
  • PyWavelets
  • PyQt5
  • pyqt5-tools
  • spyder-kernels
  • matplotlib
  • seaborn
  • pyqtgraph
  • openpyxl

• wheel libraries lfd.uci.edu:

  • GDAL-3.4.3-cp39-cp39-win_amd64.whl
  • pyproj-3.3.1-cp39-cp39-win_amd64.whl
  • Shapely-1.8.2-cp39-cp39-win_amd64.whl
  • Fiona-1.8.21-cp39-cp39-win_amd64.whl

If while installing Fiona you get an error, try to clear hash:

 pipenv --clear
 pipenv lock
 pipenv install Fiona-wheel-file

launch main file - prognoz.py or download *.exe file from releases
Take a look at the folder "Screenshots" or watch a video on YouTube.