r-cran-spatstat.linnet

linear networks functionality of the 'spatstat' family of GNU R

Defines types of spatial data on a linear network and provides functionality for geometrical operations, data analysis and modelling of data on a linear network, in the 'spatstat' family of packages. Contains definitions and support for linear networks, including creation of networks, geometrical measurements, topological connectivity, geometrical operations such as inserting and deleting vertices, intersecting a network with another object, and interactive editing of networks. Data types defined on a network include point patterns, pixel images, functions, and tessellations. Exploratory methods include kernel estimation of intensity on a network, K- functions and pair correlation functions on a network, simulation envelopes, nearest neighbour distance and empty space distance, relative risk estimation with cross-validated bandwidth selection. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov- Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two- stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller- Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the function lppm() similar to glm(). Only Poisson models are implemented so far. Models may involve dependence on covariates and dependence on marks. Models are fitted by maximum likelihood. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots. Random point patterns on a network can be generated using a variety of models.

python3-gcal-sync

A python library for syncing Google Calendar to local storage

This package provides an asyncio Python library for the Google Calendar API (as per https://developers.google.com/calendar/api). This library provides a simplified Google Calendar API that is lighter weight and more streamlined compared to using aiogoogle, and increased reliability by supporting efficient sync and reading from local storage.

python3-aioautomower

Python module to talk to Husqvarna Automower API

This package provides an asynchronous library to communicate with the Husqvarna Automower Connect API. To use this library, you need to register on the Husqvarna Developers Portal at https://developer.husqvarnagroup.cloud/, and connect your account to the "Authentication API" and the "Automower Connect API".

rime-data-combo-pinyin

Rime Input Method Engine schema data - Combo Pinyin

RIME is the acronym of Rime Input Method Engine.

libdtkdeclarative5

Deepin DTK QtQuick/QtQml widget library (shared libraries)

Dtkdeclarative is the base library of Deepin Qt/QtQuick applications.

qml-module-qtquick-controls2-styles-chameleon

Deepin DTK QtQuick/QtQml widget library (Qt Quick Controls 2 QML module)

Dtkdeclarative is the base library of Deepin Qt/QtQuick applications.