pyidw 0.1.22

IDW interpolation library for python

All in one IDW package for python

This is an example map created using pyidw library.

Features

1. Simple IDW
2. IDW with external raster (eg, elevation raster) covariable.
3. Accuracy Score.
4. Builtin raster visualisation with co-ordinate and colour bar.

Why pyidw ?

Inverse distance weighted interpolation is one of the simplest geospatial interpolations available in GIS. Although it is easy to produce an idw raster using conventional desktop GIS software (eg. ArcGIS, QGIS). It was never straightforward to create such a beautiful map image using python. This is why I have created the pyidw library where you can create beautiful idw maps of your desired location using your favourite programming language 🐍

pyidw also incorporates a clever technique to use additional raster data as a covariable using simple linear regression. For example, if you are working with temperature data, it is widely known that temperature is inversely proportional to elevation, the higher the elevation, the lower the temperature is. With pyidw, you can easily add elevation data with traditional idw calculation and improve your interpolation accuracy.

Installation

pyidw library can be installed using simple pip install pyidw. However, if you are facing trouble installing pyidw on your windows machine, please try the commands below on the windows command line.

pip install wheel
pip install pipwin
pipwin refresh
pipwin install numpy
pipwin install pandas
pipwin install shapely
pipwin install gdal
pipwin install fiona
pipwin install pyproj
pipwin install six
pipwin install rtree
pipwin install geopandas
pipwin install rasterio
pip install pyidw
pipwin refresh

Example

If you are convinced enough to give pyidw a try, here is a simple tutorial for you. You should first download the pyidw_example.zip file. This zip file contains four files,

• pyidw_tutorial.ipynb
• Bangladesh_Temperature.shp
• Bangladesh_Border.shp
• Bangladesh_Elevation.tif

The pyidw_tutorial.ipynb file is a jupyter notebook file which you could try to run and then modify with your data. Bangladesh_Temperature.shp file is an ESRI point shapefile which contains maximum and minimum temperture value for 34 weather stations all over Bangladesh. It's attribute table looks something like this.

Station_Name	Station_ID	Latitude	Longitude	Max_Temp	Min_Temp
BARISAL	BGM00041950	22.75	90.37	36.75	9.60
BHOLA	41951099999	22.68	90.65	35.62	10.19
BOGRA	BGM00041883	24.85	89.37	38.62	8.29
CHANDPUR	41941099999	23.27	90.70	35.87	11.28
CHITTAGONG	BGM00041978	22.25	91.81	36.92	11.24
CHUADANGA	41926099999	23.65	88.82	37.84	8.59
COMILLA	41933099999	23.43	91.18	35.41	10.35
COXS BAZAR	BGM00041992	21.45	91.96	37.11	11.51

For those who are not familiar wih shapefile, Every shapefile consists of seven different file with same name but seven different file extensions. Namely .cpg .dbf .prj .sbn .sbx .shp and .shx. If any of these file is missing then shapefile system won't work properly. Note that Max_Temp and Min_Temp column, we will use this value latter when creating IDW interpolated maps.

The Bangladesh_Border.shp is an ESRI polygon shapefile which covers all the area of country Bangladesh. We will use this shapefile to define the calculation extent for IDW interpolation. And finally the Bangladesh_Elevation.tif file which is a raster file containing elevation information in meter, We don't need this file for standard IDW interpolation but with regression_idw, we will use this file as an external covariable. All the files and their spatial dimension is shown below.

If you have any questions or problems, feel free to contact me at: [e-mail]