geo-infer-time

name	geo-infer-time
description	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.
prerequisites	{"required":["geo-infer-math"],"recommended":["geo-infer-data"]}
difficulty	intermediate
estimated_time	45min
examples_dir	../GEO-INFER-EXAMPLES/examples/

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