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linder
Release 2020.6.3.2

linder is a machine-learning based land use/land cover (LULC) classifier using Sentinel imagery.

Homepage PyPI Python

Keywords: climate-model, land-surface-modeling, science-research, urban-climate-model
License: GPL-3.0
Install: pip install linder==2020.6.3.2

Documentation

SuPy

THIS PROJECT IS ARCHIVED AND NOW MAINTAINED HERE BY @UMEP-dev.

SUEWS that speaks Python

Installation

SuPy requires 64-bit python 3.6+ and can be installed with pip in command line prompt:

python3 -m pip install supy --upgrade

Quick Demo

Once installed, supy can be quickly started to get SUEWS simulations done:

import supy as sp
import matplotlib.pyplot as plt

#load sample data
df_state_init, df_forcing = sp.load_SampleData()
grid = df_state_init.index[0]

#run supy/SUEWS simulation
df_output, df_state_end = sp.run_supy(df_forcing, df_state_init)

#plot results and save figure
res_plot = df_output.SUEWS.loc[grid, ['QN', 'QF', 'QS', 'QE', 'QH']]
ax=res_plot.loc['2012 6 4':'2012 6 6'].resample('30T').mean().plot()
plt.show()
ax.figure.savefig('sample_plot.png')