New proposed function: getWeather

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評価

難易度
5/5
見積もり時間
1週間以上
初心者へのやさしさ
25/100
issue の種類
機能追加
明瞭さ
説明が足りない
活発さ
静か
領域
data-visualization

調査の方向性

The proposed function is linked from the issue as a standalone getWeather repository; begin by reviewing that repository and its current implementation. The issue describes weather data retrieval, anomaly detection, indicators, and visualization, but does not define a specific change or completion criteria.

索引モデルが issue の本文から書いたものです。

説明

Hi everybody,

Today I am showing a new utility function, getWeather, designed to bring robust statistical analysis and advanced visualization to meteorological data within the FSDA "mind".
Inspired by the workflow and the interactive design of getYahoo, this function provides an end-to-end pipeline: from data retrieval (via Open-Meteo API) to robust anomaly detection and visualization. Given the recent meteorological shifts and the growing need for climate data quality checks, this function is intended to be a reliable "first-look" tool for time-series meteorological assessment.

Image

Screenshot produced by: getWeather("Parma","lastperiod","1mo")

Key Features

  • Pipeline Design: One-step retrieval, cleaning, and structuring of surface weather variables (Temperature, Humidity, Pressure, Wind, Precipitation) into a timetable.

  • Robust Statistics: Implements multivariate anomaly detection using Robust Covariance (robustcov) and Mahalanobis distances, allowing users to spot outliers (e.g., sensor malfunctions or extreme micro-climatic events) without being misled by non-Gaussian noise.

  • Technical Indicators: Uses Exponential Moving Averages (EMA) to identify structural trends in temperature and provides linear regression fitting between Wind Speed and Gusts to assess correlation stability.

  • Advanced Visualization: A custom three-panel diagnostic layout featuring a dark-themed UI, interactive datatips (implemented via DataTipTemplate for optimal performance), and automatic figure exportation.

Next integrations:

I am actively planning to expand this function's capabilities to align with FSDA’s core philosophy:
like integrate MahalFS for a more granular identification of outliers and potential statistical depth also a spatial visualization: Implementing geoplotFS to visualize weather stations or event paths on maps.
Also, am actively exploring API sources or calculation methods to integrate CAPE (Convective Available Potential Energy) and SWT (Severe Weather Threat) indices to enhance forecasting diagnostic power. Also a lot things are now missing (like a proper documentation) but I am going to add on this type of things, as soon as I can.

I am open to every tipe of suggestion, also if you want to try the code or propose some changes, this is the standalone repository of this beta code:

getWeather

主要言語
MATLAB
スター
30
フォーク
1
30日以内にマージされた PR はありません

環境構築

このプロジェクトには開発コンテナ、Dockerfile、コントリビューションガイドがありません。まず README を読み、一般的な手順ははじめてのコントリビューションガイドを参照してください。

はじめの一歩

  1. issue を最後まで読み、次にプロジェクトのコントリビューションガイドを読みます。
  2. 着手することを issue にコメントします — 二人が同じ作業をするのを防げます。
  3. リポジトリをフォークし、ブランチを切って変更します。
  4. issue 番号を参照したプルリクエストを送ります。

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