ActiveInferenceInstitute

geo-infer-time

Time series analysis and temporal modeling for geospatial data. Use when analyzing temporal patterns, forecasting spatial time series, detecting change points, or working with spatio-temporal datasets.

ActiveInferenceInstitute 15 2 Updated 6mo ago

Resources

10
GitHub

Install

npx skillscat add activeinferenceinstitute/geo-infer/geo-infer-time

Install via the SkillsCat registry.

SKILL.md

GEO-INFER-TIME

Instructions

Core Capabilities

  • Time series analysis: Decomposition, trend detection, seasonality
  • Forecasting: ARIMA, exponential smoothing, temporal GP
  • Change detection: CUSUM, Bayesian change points, structural breaks
  • Temporal indexing: Time-aware spatial queries, temporal resolution management
  • Spatio-temporal: Joint analysis of spatial and temporal dimensions

Key Imports

from geo_infer_time.core.time_series import TimeSeriesAnalyzer
from geo_infer_time.core.forecasting import Forecaster
from geo_infer_time.core.change_detection import ChangePointDetector

Examples

from geo_infer_time.core.time_series import TimeSeriesAnalyzer

analyzer = TimeSeriesAnalyzer(frequency="daily")
decomposition = analyzer.decompose(series, method="stl")
trend = decomposition.trend
seasonal = decomposition.seasonal

Guidelines

Integrations

  • Integrates with SPACE for spatio-temporal analysis
  • ISO 8601 for all datetime handling
  • Test: uv run python -m pytest GEO-INFER-TIME/tests/ -v

Categories