py

GridTiler in Python

Install latest version of pygridmap library with:

pip install git+https://github.com/eurostat/pygridmap.git

Tiling gridded raster data

To tile gridded data from a raster file such as GeoTiff, import gridtiler_raster in your code with from pygridmap import gridtiler_raster. gridtiler_raster gives access to a function tiling_raster.

See an example here. See also this repository.

NB: For aggregating raster data, use gdalwarp program.

Tiling gridded CSV data

To tile CSV gridded data, import gridtiler in your code with from pygridmap import gridtiler. gridtiler gives the three functions:

• gridtiler.grid_transformation to change the format of a CSV grid.
• gridtiler.grid_aggregation to aggregate a CSV grid into a lower resolution CSV grid.
• gridtiler.grid_tiling to tile a CSV grid.

Let's see an example on european population grid at 5000m resolution. This input CSV dataset includes total population for 2006, 2011, 2018 and 2021 (columns TOT_P_2006, TOT_P_2011, TOT_P_2018, TOT_P_2021), a columns on country code CNTR_ID and the grid cell identifier GRD_ID.

The first step is to transform the input data to extract the x and y from the GRD_ID and then remove the GRD_ID and CNTR_ID colmuns. It can be achieved with:

#define cell transformation function
def cell_transformation_fun(c):

    #extract x and y from grid cell code
    a = c['GRD_ID'].split("N")[1].split("E")
    c["x"] = int(a[1])
    c["y"] = int(a[0])

    #delete unecessary data
    del c['GRD_ID']
    del c['CNTR_ID']

print("Transformation")
gridtiler.grid_transformation("assets/pop_5000m.csv", cell_transformation_fun, "tmp/pop_5000.csv")

The output file tmp/pop_5000.csv is ready to be tiled, but aggregated version at 10000, 20000 and 50000m resolution can be produced first with:

print("Aggregation to 10 000m")
gridtiler.grid_aggregation("tmp/pop_5000.csv", 5000, "tmp/pop_10000.csv", 2, 0)

print("Aggregation to 20 000m")
gridtiler.grid_aggregation("tmp/pop_5000.csv", 5000, "tmp/pop_20000.csv", 4, 0)

print("Aggregation to 50 000m")
gridtiler.grid_aggregation("tmp/pop_5000.csv", 5000, "tmp/pop_50000.csv", 10, 0)

Each resolution file can be tiled with:

print("Tiling 5000m")
gridtiler.grid_tiling("tmp/pop_5000.csv", "tmp/5000", 5000)

print("Tiling 10 000m")
gridtiler.grid_tiling("tmp/pop_10000.csv", "tmp/10000", 10000)

print("Tiling 20 000m")
gridtiler.grid_tiling("tmp/pop_20000.csv", "tmp/20000", 20000)

print("Tiling 50 000m")
gridtiler.grid_tiling("tmp/pop_50000.csv", "tmp/50000", 50000)

See the entire script here.