dlong 0.1.0

Prototype framework for projected socio-economic climate damages

dlong

Prototype framework for projected socio-economic climate damages

This is a prototype. It is likely to change in breaking ways. It might delete all your data so don't use it in production.

Examples

import dlong
from dlong.types import ClimateData
import xarray as xr

# First, let's make some demo data.
# Say 3 years of annual temperature data across 3 regions:
region = [1, 2, 3]
year = [2019, 2020, 2021]
input_temperature = xr.DataArray(
    [[1.0, 2.0, 3.0], [2.0, 3.0, 4.0], [3.0, 4.0, 5.0]],
    coords=[region, year],
    dims=["region", "year"],
)
# And here are coefficients for a quadratic damage function. Different for 
# each region.
damage_coefficients = xr.Dataset(
    data_vars={
        "beta0": (["region"], [1, 1, 1]),
        "beta1": (["region"], [1, 2, 3]),
        "beta2": (["region"], [4, 5, 6]),
    },
    coords={"region": (["region"], region)},
)

# Put it all together to describe climate data, a damage function, and
# a strategy for discounting damages.
climate = dlong.types.ClimateData(temperature=input_temperature)
damage_model = dlong.QuadraticDamageModel(coefs=damage_coefficients)
discount_strategy = dlong.FractionalDiscount(rate=0.02, reference_year=2020)
# We could use these individually, or combine them into a "recipe" to output 
# discounted damages. The idea is that these components are compositable
# so components can be customized and run in large batches.
recipe = dlong.ExampleRecipe(
    climate=climate, damage_function=damage_model, discount=discount_strategy
)
damages = recipe.discounted_damages()
#<xarray.DataArray (region: 3, year: 3)>
#array([[  6.12      ,  19.        ,  39.21568627],
#       [ 25.5       ,  52.        ,  87.25490196],
#       [ 65.28      , 109.        , 162.74509804]])
#Coordinates:
#* region   (region) int64 1 2 3
#* year     (year) int64 2019 2020 2021

Installation

pip install dlong

dlong currently requires Python > 3.8 and the xarray package.

Install the unreleased bleeding-edge version of the package with:

pip install git+https://github.com/brews/dlong

Support

Source code is available online at https://github.com/brews/dlong/. This software is Open Source and available under the Apache License, Version 2.0.

Development

Please file bugs in the bug tracker.

Want to contribute? Great! Fork the main branch and file a pull request when you're ready. Please be sure to write unit tests and follow pep8. Fork away!