Ales Kuchar kuchaale
kuchaale
/ Recover_data_with_known_colourmap.ipynb
Created
September 14, 2022 14:39
— forked from kwinkunks/Recover_data_with_known_colourmap.ipynb
Demo of recovering data from an image with a known colourmap. Thank you to David Johnstone (Manchester) for the data example.
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kuchaale
/ geoapps_vs_xcontour.ipynb
Created
April 13, 2022 14:27
Notebook documenting differences between GeoApps and xcontour calculation of effective diffusivity
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kuchaale
/ pyvortex_bug.ipynb
Created
November 25, 2021 20:46
Correction of functions to calculate the equivalent latitude and edge of a polar vortex using Nash criteria
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kuchaale
/ style.css
Created
October 13, 2021 23:19
— forked from rougier/style.css
Jupyter stylesheet
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| @import url('https://fonts.googleapis.com/css2?family=Roboto+Condensed:wght@300;400&family=Source+Code+Pro:wght@300;400&display=swap'); | |
| .rendered_html h1, | |
| .rendered_html h2, | |
| .rendered_html h3, | |
| .rendered_html h4 { | |
| color: #000099; | |
| font-weight: 400; | |
| } |
kuchaale
/ GW_activity_t_tide_analysis.ipynb
Created
August 12, 2021 17:05
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kuchaale
/ SSW_detection_ERA5.ipynb
Created
June 25, 2021 11:07
Split and discplament detection in ERA5
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kuchaale
/ sherman.py
Created
January 4, 2021 16:07
— forked from 0x0L/sherman.py
Fast moving window regressions
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| import numba | |
| import numpy as np | |
| @numba.jit(nopython=True, fastmath=True) | |
| def move_regress(X, Y, w, fit_intercept=True): | |
| """Moving window multi-regressions | |
| Solves the least-squares problems `Y[t-w+1:t+1] = X[t-w+1:t+1] @ B[t] + A[t]` | |
| for `B` and `A` for all `t` in `[w-1, len(Y)-1]`. | |
kuchaale
/ globaltemp.R
Created
December 11, 2020 14:23
— forked from jrnold/globaltemp.R
Kalman filter in Stan
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| library(KFAS) | |
| library(rstan) | |
| data(GlobalTemp) | |
| model_dlm1a <- stan_model("../stan/dlm1a.stan") | |
| y <- as.matrix(GlobalTemp) | |
| data <- | |
| within(list(), | |
| { |
kuchaale
/ bootstrap_threshold_parallel.ipynb
Created
October 15, 2020 14:38
— forked from aaronspring/bootstrap_threshold_parallel.ipynb
bootstrap threshold in parallel with dask
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kuchaale
/ wrf_python_extraction.py
Created
October 15, 2020 10:51
— forked from jthielen/wrf_python_extraction.py
Use wrf-python, xarray, and pyproj to post-process WRF output
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| from wrf import getvar | |
| from netCDF4 import Dataset | |
| import xarray as xr | |
| import pyproj | |
| # Extract the variables of interest at time index 17 | |
| ds = Dataset('../wrfout_d02_2015-07-12_1200.nc') | |
| variables = [getvar(ds, var, 17) for var in ('z', 'dbz', 'pressure', 'ter', 'ua', | |
| 'va', 'wa', 'temp', 'rh')] | |
| data = xr.merge(variables) |
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