monocongo

monocongo

#!/usr/bin/env bash

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#

gordthompson

# Copyright 2023 Gordon D. Thompson, gord@gordthompson.com
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

bennyistanto

Calculate SPI using monthly rainfall data in GeoTIFF format

These last few months, I have tried a lot of difference formulation to calculate Standardized Precipitation Index (SPI) based on rainfall data in netCDF format, check below files as a background:

• SPI using IMERG netCDF (notebook)
• SPI using CHIRPS netCDF (how-to guideline)

The reason why I use rainfall in netCDF format in above files because the software to calculate SPI: climate-indices python package will only accept single netCDF as input, and the SPI script will read the netCDF input file based on time dimension.

Converting raster files into netCDF is easy using GDAL or other GIS software, but to make the time dimension enabled n

BryanCutler

#!/usr/bin/env bash

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#

mbaitelman

Automated Terraform Deployments

Requirements

• AWS Account
• AWS API User API Key/Secret
• Bitbucket Account

Setup

1. Create or update an existing Bitbucket repo
2. Open https://bitbucket.org/USERNAME/REPO/addon/pipelines/deployments

joshbode

import sys
import logging
from typing import Optional, Dict

from colorama import Fore, Back, Style


class ColoredFormatter(logging.Formatter):
    """Colored log formatter."""

keithweaver

'''
Using OpenCV takes a mp4 video and produces a number of images.

Requirements
----
You require OpenCV 3.2 to be installed.

Run
----
Open the main.py and edit the path to the video. Then run:

cameres

from pyspark.mllib.stat import Statistics
import pandas as pd

# result can be used w/ seaborn's heatmap
def compute_correlation_matrix(df, method='pearson'):
    # wrapper around
    # https://forums.databricks.com/questions/3092/how-to-calculate-correlation-matrix-with-all-colum.html
    df_rdd = df.rdd.map(lambda row: row[0:])
    corr_mat = Statistics.corr(df_rdd, method=method)
    corr_mat_df = pd.DataFrame(corr_mat,

bikz05

sudo apt-get update
sudo apt-get upgrade

# Added by me
sudo apt-get install freeglut3 freeglut3-dev libtbb-dev libqt4-dev
# Copied from pyimagesearch.com
sudo apt-get install build-essential cmake git pkg-config
sudo apt-get install libjpeg8-dev libtiff4-dev libjasper-dev libpng12-dev
sudo apt-get install libgtk2.0-dev
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev