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jules_scripts

jupyter_scripts

jupyterlab

JupyterLab computational environment. This is a very early preview, and is not suitable for general usage yet.

kafka

Kascading Fast Kalman Assimilation

kalman-and-bayesian-filters-in-python

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.

kmeans_memory_submission

Code for paper submission

landsat_preprocess

IPython notebook documenting a workflow for preprocessing Landsat data

lavendar

The Land Variational Ensemble Data Assimilation fRamework (LaVEnDAR) implements the method of Four-Dimensional Ensemble Variational data assimilation for land surface models.

leaf13c

This is a global dataset of leaf 13C values

licornetics

Plot physiological parameters measured using the Li-COR photosystem

littlemcmc

A lightweight and performant implementation of HMC and NUTS in Python, spun out of the PyMC project.

logistic_risk

lomb_scargle

Lomb-Scargle periodogram method of estimating a frequency spectrum from unevenly spaced data based on a least squares fit of sinusoids to data samples.

longterm_rainfall_deficit

lotka_voltera

lpj-guess_nightmare

Scripts

lpj_photosynthesis

lpj_stuff

maat

MAAT v1.0

maestra

MAESTRA is a model of forest canopy radiation absorption and photosynthesis. See website, these are some minor changes I have made to the codebase.

markdown_paper_example

matplotlib

matplotlib: plotting with Python

mauna_loa

Some simple model fitting with Python

mauna_loa_co2_gp

Predict CO2 obs using Gaussian process regression

mcmc_pydata_london_2019

PyData London 2019 Tutorial on Markov chain Monte Carlo with PyMC3

mdekauwe.github.io

My work website

medfate

Functions to simulate Mediterranean forest functioning and dynamics using cohort-based description of vegetation

metropolis_hastings

Metropolis Hastings sampler

millennial

This is a repository for the newly developed Millennial model

ml-biomass

An example of linking TERN AusCover field and image data to predict biomass