air-monitor-algorithms

A package containing algorithms used in the processing of hourly time series data. Initial use cases include air quality monitoring time series.

This package is a dependency of the air-monitor package for working with air quality monitoring data archives hosted by the US Forest Service.

NOTE: A core assumption of the "air-monitor" data model is that all time series data are on a regular hourly axis with no gaps. When working with this javascript package, missing values should be indicated by null.

Important functions for data analysis include:

dailyStats() -- Converts time series data into local time daily statistics.
diurnalStats() -- Converts time series data into local time statistics by hour-of-day.
pm_nowcast() -- Applies the Nowcast algorithm to PM2.5 or PM10 time series data.
trimDate() -- Returns an object with time series data trimmed to local time full days.

Low level utility functions for sane array manipulation in javascript include:

arrayCount() -- Returns the count of non-missing values in an array.
arraySum() -- Returns the sum of non-missing values in an array.
arrayMin() -- Returns the minimum of non-missing values in an array.
arrayMean() -- Returns the mean of non-missing values in an array.
arrayMax() -- Returns the maximum of non-missing values in an array.

Usage

The package can be installed with npm:

npm install github:MazamaScience/air-monitor-algorithms

This package is provided as an ES Module intended for use in other modules or in Svelte and Vue applications. Here is an example of how to import functions from this module:

import {
  dailyStats,
  diurnalStats,
  pm_nowcast,
} from "air-monitor-algorithms";
...

This project is supported by the USFS AirFire group.