bennyistanto

Custom xkcd-style map for Indonesia

Label setting for capital, country name and the ocean, and the red-dot is manually set, the value is calculate from top-left main map area.

You can paste the below code into an online Python compiler like https://python-fiddle.com/ and grab the result instantly.

bennyistanto

xkcd style for country map

This is example of Python script that could generate a xkcd-style for Country Map.

Example:

bennyistanto

xkcd style for LSEQM illustration

This is example of Python script that could generate a xkcd graph-style to illustrate concept of Linear Scaling and Empirical Quantile Mapping (LSEQM) method for daily precipitation bias correction.

version a

version b

bennyistanto

<?xml version="1.0" encoding="utf-8"?>
<!-- Modified by: Benny Istanto/KLI/G2501222008, bennyistanto@apps.ipb.ac.id -->
<!-- English version available on: https://gist.github.com/bennyistanto/ef6b1a2bb1ed303a7832f789ac7e7a70 -->
<style xmlns="http://purl.org/net/xbiblio/csl" class="in-text" version="1.0" demote-non-dropping-particle="sort-only" default-locale="en-US">
  <!-- changed default-locale to en-US -->
  <info>
    <title>Institut Pertanian Bogor: Pedoman Penulisan Karya Ilmiah Edisi ke-4 (English)</title>
    <!-- updated title -->
    <title-short>IPB PPKI 4</title-short>
    <id>http://www.zotero.org/styles/institut-pertanian-bogor</id>

bennyistanto

Skip PEARSON fitting on climate-indices python package

I have been using climate-indices python packages years ago, and the tool developed by James Adam is awesome, it help us to calculate various climate indices. There are two indices that I frequently produced using this tool: SPI and SPEI.

I also wrote a guideline on how to calculate these two indices using this package https://bennyistanto.github.io/spi/.

When I wrote this guideline, I never have any problem during the indices calculation. Then I noticed some people contacted me to ask about some error related to Pearson fitted also in the Github repository there are lot of [Issues](https://github.com/monocongo/climate_indices/issues?q=is%3A

bennyistanto

Install CUDA and cuDNN using Conda

Tested on:

Windows 11 Pro for Workstations and WSL2 Debian 12
Processor: Intel(R) Xeon(R) Gold 6138 CPU @ 2.00GHz 2.00 GHz (2 processors)
Installed RAM: 384 GB
VGA: NVIDIA Quadro P2000 5GB

---

bennyistanto

bennyistanto

# -*- coding: utf-8 -*-
"""
NAME
    13_mxd13q1_viproducts_annual.py
    Generate derivative product from Vegetation Indices
DESCRIPTION
    Input data for this script will use MXD13Q1 annual data generate by 06_mxd13q1_8day2annual.py 
    This script can do calculation for ratio, difference, standardize anomaly 
    and vegetation condition index.
    The calculation required timeseries VI and the long-term statistics (min, mean, max, std)

bennyistanto

# -*- coding: utf-8 -*-
"""
NAME
    12_mxd13q1_viproducts_quarter.py
    Generate derivative product from Vegetation Indices
DESCRIPTION
    Input data for this script will use MXD13Q1 quarterly data generate by 05_mxd13q1_8day2quarter.py 
    from NASA. This script can do calculation for ratio, difference, standardize anomaly 
    and vegetation condition index.
    The calculation required timeseries VI and the long-term statistics (min, mean, max, std)

bennyistanto

# -*- coding: utf-8 -*-
"""
NAME
    11_mxd13q1_viproducts_monthly.py
    Generate derivative product from Vegetation Indices
DESCRIPTION
    Input data for this script will use MXD13Q1 monthly data generate by 04_mxd13q1_8day2monthly.py 
    This script can do calculation for ratio, difference, standardize anomaly 
    and vegetation condition index.
    The calculation required timeseries VI and the long-term statistics (min, mean, max, std)