pymt_soilgrids converts soilgrids into a reusable, plug-and-play data component for PyMT modeling framework. pymt_soilgrids allows the soil datasets to be easily coupled with other datasets or models that expose a Basic Model Interface.

Installation

Install the pymt in a new environment:

$ conda config --add channels conda-forge
$ conda create -n pymt -c conda-forge python=3 pymt
$ conda activate pymt

Install the pymt_soilgrids using pip:

$ pip install pymt_soilgrids

or conda:

$ conda install -c conda-forge pymt_soilgrids

Coding Example

You can learn more details from the tutorial notebook.

import matplotlib.pyplot as plt
import numpy as np

from pymt.models import SoilData

# initiate a data component
data_comp = SoilData()
data_comp.initialize('config.yaml')

# get variable info
var_name = data_comp.output_var_names[0]
var_unit = data_comp.var_units(var_name)
var_location = data_comp.var_location(var_name)
var_type = data_comp.var_type(var_name)
var_grid = data_comp.var_grid(var_name)

print('variable_name: {} \nvar_unit: {} \nvar_location: {} \nvar_type: {} \nvar_grid: {}'.format(
    var_name, var_unit, var_location, var_type, var_grid))

# get variable grid info
grid_type = data_comp.grid_type(var_grid)
grid_rank = data_comp.grid_ndim(var_grid)
grid_shape = data_comp.grid_shape(var_grid)
grid_spacing = data_comp.grid_spacing(var_grid)
grid_origin = data_comp.grid_origin(var_grid)

print('grid_type: {} \ngrid_rank: {} \ngrid_shape: {} \ngrid_spacing: {} \ngrid_origin: {}'.format(
    grid_type, grid_rank, grid_shape, grid_spacing, grid_origin))

# get variable data
data = data_comp.get_value(var_name)
data_2D = data.reshape(grid_shape)

print(data.shape, data_2D.shape)

# get X, Y extent for plot
min_y, min_x = grid_origin
max_y = min_y + grid_spacing[0]*(grid_shape[0]-1)
max_x = min_x + grid_spacing[1]*(grid_shape[1]-1)
dy = grid_spacing[0]/2
dx = grid_spacing[1]/2
extent = [min_x - dx, max_x + dx, min_y - dy, max_y + dy]

# plot data
fig, ax = plt.subplots(1,1, figsize=(9,5))
im = ax.imshow(data_2D, extent=extent)
fig.colorbar(im)
plt.xlabel('X')
plt.ylabel('Y')
plt.title('Mean pH between 0 and 5 cm soil depth in Senegal')

# complete the example by finalizing the component
data_comp.finalize()