Traccess
Transportation access and equity computations.
Traccess offers a set of fast and convenient functions to calculate multiple transport accessibility measures. Given a pre-computed travel cost matrix, and using data sets on land use supply, demand, and demographics, the package computes accessibility levels using multiple accessibility measures, such as: cumulative opportunities, minimum travel cost to closest n number of activities, gravity-based (with different decay functions) and different floating catchment area methods.
The package also contains a number of different methods for computing distributive and sufficientarian equity measures to compare the level of access provided across demographic groups.
Decay functions
traccess.decay provides weighting functions for
AccessComputer.cumulative_decay, mirroring IPEA's R
accessibility package:
binary, exponential, linear, logistic, power and stepped. A missing
(NaN) travel cost always gets weight 0.
Equity and inequality measures
EquityComputer computes, once per demographic group:
- Sufficientarian measures:
fgt_poverty,in_poverty,poverty_index - Distributive summaries:
weighted_average,weighted_quantile - Inequality indices (ported from R
accessibility):gini_index,theil_t,theil_t_decomposition(between/within a categorical grouping),palma_ratioandconcentration_index(both ranked by an income-per-capita or other socioeconomic column)
Pass population_columns to choose which demographic columns are population
counts, e.g. when the demographic data also holds an income column.
Metadata
Release files for traccess 0.0.4
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| File | Size | Uploaded | Provenance | Actions |
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| traccess-0.0.4-py3-none-any.whl | Python 3 | none | any | Details for traccess-0.0.4-py3-none-any.whl |
Total release size: 29.7 kB
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