All Projects → WFRT → verif

WFRT / verif

Licence: other
Software for verifying weather forecasts

Programming Languages

python
139335 projects - #7 most used programming language
r
7636 projects

Projects that are alternatives of or similar to verif

hydrotools
Suite of tools for retrieving USGS NWIS observations and evaluating National Water Model (NWM) data.
Stars: ✭ 36 (-48.57%)
Mutual labels:  evaluation, verification, forecasting
Neural prophet
NeuralProphet - A simple forecasting model based on Neural Networks in PyTorch
Stars: ✭ 1,125 (+1507.14%)
Mutual labels:  prediction, forecasting
Sales-Prediction
In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays and oil prices.
Stars: ✭ 56 (-20%)
Mutual labels:  prediction, forecasting
AIODrive
Official Python/PyTorch Implementation for "All-In-One Drive: A Large-Scale Comprehensive Perception Dataset with High-Density Long-Range Point Clouds"
Stars: ✭ 32 (-54.29%)
Mutual labels:  evaluation, forecasting
arima
ARIMA, SARIMA, SARIMAX and AutoARIMA models for time series analysis and forecasting in the browser and Node.js
Stars: ✭ 31 (-55.71%)
Mutual labels:  prediction, forecasting
Forecasting Mutual Funds
This Project gives you an overall idea for Forecasting Mutual Funds
Stars: ✭ 15 (-78.57%)
Mutual labels:  prediction, forecasting
Tcdf
Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series
Stars: ✭ 217 (+210%)
Mutual labels:  prediction, forecasting
Ergo
A Python library for integrating model-based and judgmental forecasting
Stars: ✭ 82 (+17.14%)
Mutual labels:  prediction, forecasting
Achoo
Achoo uses a Raspberry Pi to predict if my son will need his inhaler on any given day using weather, pollen, and air quality data. If the prediction for a given day is above a specified threshold, the Pi will email his school nurse, and myself, notifying her that he may need preemptive treatment. Community-sourced health monitoring!
Stars: ✭ 200 (+185.71%)
Mutual labels:  weather, prediction
forecastVeg
A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python
Stars: ✭ 44 (-37.14%)
Mutual labels:  prediction, forecasting
hagelslag
Hagelslag is an object-based severe storm hazard forecasting system.
Stars: ✭ 58 (-17.14%)
Mutual labels:  weather, verification
point-cloud-prediction
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks
Stars: ✭ 97 (+38.57%)
Mutual labels:  prediction, forecasting
Diebold-Mariano-Test
This Python function dm_test implements the Diebold-Mariano Test (1995) to statistically test forecast accuracy equivalence for 2 sets of predictions with modification suggested by Harvey et. al (1997).
Stars: ✭ 70 (+0%)
Mutual labels:  prediction, forecasting
foot
foot是一个集足球数据采集器,简单分析的项目.AI足球球探为程序全自动处理,全程无人为参与干预足球分析足球预测程序.程序根据各大指数多维度数据,结合作者多年足球分析经验,精雕细琢,集天地之灵气,汲日月之精华,历时七七四十九天,经Bug九九八十一个,编码而成.有兴趣的朋友,可以关注一下公众号AI球探(微信号ai00268).
Stars: ✭ 96 (+37.14%)
Mutual labels:  prediction, forecasting
python-awips
A framework for querying AWIPS meteorological datasets from an EDEX Data Server.
Stars: ✭ 31 (-55.71%)
Mutual labels:  weather, forecasting
gridpp
Software to post-process gridded weather forecasts
Stars: ✭ 33 (-52.86%)
Mutual labels:  weather, prediction
naacl2018-fever
Fact Extraction and VERification baseline published in NAACL2018
Stars: ✭ 109 (+55.71%)
Mutual labels:  evaluation, verification
speech-recognition-evaluation
Evaluate results from ASR/Speech-to-Text quickly
Stars: ✭ 25 (-64.29%)
Mutual labels:  evaluation
GA-BP
基于遗传算法的BP网络设计,应用背景为交通流量的预测
Stars: ✭ 102 (+45.71%)
Mutual labels:  prediction
docker-mkcert
Docker container for creating valid local ssl certificates
Stars: ✭ 87 (+24.29%)
Mutual labels:  verification

Forecast verification software

Verif is a command-line tool that lets you verify the quality of weather forecasts for point locations. It can also compare forecasts from different forecasting systems (that have different models, post-processing methods, etc).

The program reads files with observations and forecasts in a specific format (see "Input files" below). The input files contain information about dates, forecast lead times, and locations such that statistics can be aggregated across different dimensions. To ensure a fair comparison among files, Verif will discard data points where one or more forecast systems have missing forecasts. Since Verif is a command-line tool, it can be used in scripts to automatically create verification figures.

Verif version 1.2 has been released (see "Installation Instruction" below). We welcome suggestions for improvements. Verif is developed by Thomas Nipen ([email protected]), with contributions from many.

Documentation

For more information on how to use Verif, check out the wiki at https://github.com/WFRT/verif/wiki.

Features

  • Deterministic metrics such as MAE, bias, correlation, RMSE (e.g. -m mae)
  • Threshold-based metrics such as the false alarm rate, ETS, EDI, Yule's Q (e.g. -m ets)
  • Probabilistic metrics such as brier score, PIT-histogram, reliability diagrams (e.g. -m bs)
  • Special plots like Taylor diagrams (-m taylor), quantile-quantile plots (-m qq).
  • Plot scores as a function of date, lead time, station altitude/lat/longitude (e.g. -x date)
  • Show scores on maps (-type map)
  • Subset the data by specifying a date range and lat/lon range (-latrange 58,60)
  • Export to text (-type text)
  • Options to adjust font sizes, label positions, tick marks, legends, etc (-labfs 14)
  • Anomaly statistics relative to a baseline like climatology (-c climfile.txt)
  • Output to png, jpeg, eps, etc and specify dimensions and resolution (-f image.png -dpi 300)

Example plots

Installing on Ubuntu

Prerequisites

Verif requires a pip installation and Python 3. The python package "cartopy" is optional, but provides a background map when verification scores are plotted on a map. To install Cartopy, with its GEOS and PROJ4 dependencies, do the following:

sudo apt-get update
sudo apt-get install libgeos-dev libproj-dev
sudo pip3 install cartopy

Installing using pip

After this, the easiest is to install the lastest version of Verif using pip:

sudo pip install verif

Verif should then be accessible by typing verif on the command-line. If you do not have sudo-rights, then install verif as follows:

pip install verif --user

This will create the executable ~/.local/bin/verif. Add this to your PATH environment variable if necessary (i.e add export PATH=$PATH:~/.local/bin to ~/.bashrc).

To upgrade to a newer version of Verif, run the following:

pip install verif --upgrade

Installing from source

Alternatively, to install from source, download the source code of the latest version: https://github.com/WFRT/verif/releases/. Unzip the file and navigate into the extracted folder.

Then install Verif by executing the following inside the extracted folder:

sudo pip install -r requirements.txt
sudo python setup.py install

This will create the executable /usr/local/bin/verif. Add /usr/local/bin to your PATH environment variable if necessary. If you do not have sudo privileges do:

pip install -r requirements.txt --user
python setup.py install --user

This will create the executable ~/.local/bin/verif. Add ~/.local/bin to your PATH environment variable.

Installing on Mac OSX

Follow the proceedure as for Ubuntu (either installing with pip or from source). If installing from source, then look for the line "Installing verif script to <some directory>", as this will indicate what folder Verif is installed into. Add the folder to your PATH environment variable if necessary.

Example

A sample dataset for testing the program is found in ./examples/. There is one "raw" forecast file and one "calibrated" forecast file (where statistical methods have been applied). For more information about the dataset check out the wiki. Here are some example commands to test out:

# Shows mean absolute error as a function of lead-time
verif examples/raw.txt examples/kf.txt -m mae
# Shows average observed and forecasted values as a function on time
verif examples/raw.txt examples/kf.txt -m obsfcst -x time
# Shows equitable threat score as a function of threshold
verif examples/raw.txt examples/kf.txt -m ets
# Shows a reliability diagram for a threshold of 0 °C
verif examples/raw.txt examples/kf.txt -m reliability -r 0
# Shows Brier skill score as a function of threshold
verif examples/raw.txt examples/kf.txt -m bss -x threshold

Copyright and license

Copyright © 2013-2022 UBC Weather Forecast Research Team. Verif is licensed under the 3-clause BSD license. See LICENSE file.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].