netsy

Synthesizes aggregate supply and demand, and the capacity and need distributions of individual agents, from effects and thresholds files.

Install

pip install netsy

Requires Python 3.11 or newer.

Usage

Run each command in the directory holding its input files.

netsy synth supply       # supply_effects.csv + supply_thresholds.csv -> supply.csv
netsy synth demand       # demand_effects.csv + demand_thresholds.csv -> demand.csv
netsy synth capacities   # capacity_effects.csv + capacity_thresholds.csv -> capacities.csv
netsy synth needs        # need_effects.csv + need_thresholds.csv -> needs.csv

An existing output file is only replaced with --force. The output is a deterministic function of its two inputs.

Data files

*_effects.csv holds one additive effect per stratum value and resource. zone_id is always a stratum. An empty cell means the stratum value does not take part in that resource.

*_thresholds.csv holds the sorted cutpoints of each resource. The largest level has none.

supply.csv and demand.csv have one row per stratum combination and one column per resource.

capacities.csv and needs.csv have one row per stratum combination, resource and level.

Model

Each resource $r$ is an ordinal outcome under a cumulative-logit model, with $\sigma(x) = 1 / (1 + e^{-x})$. A stratum $s = (v_1, \dots, v_D)$ takes one value from each of the $D$ dimensions, and its linear predictor is the sum of the effects $\gamma$ of those values:

$$\beta_{r,s} = \sum_{d=1}^{D} \gamma_{r,d,v_d}$$

If any of these effects is empty the pair $(s, r)$ is omitted, which is not the same as an effect of zero. With levels $\ell_{r,1} < \dots < \ell_{r,K_r}$ and thresholds $\mu_{r,1} \le \dots \le \mu_{r,K_r-1}$, the cumulative probability of level $k$ is

$$F_{r,s}(k) = \sigma(\mu_{r,k} - \beta_{r,s})$$

with $F_{r,s}(0) = 0$ and $F_{r,s}(K_r) = 1$, and the probability of each level is the difference

$$p_{r,s}(\ell_{r,k}) = F_{r,s}(k) - F_{r,s}(k-1)$$

Capacities and needs are these probabilities. Supply and demand are the expected level rounded to a whole unit:

$$A_{r,s} = \operatorname{round}\left( \sum_{k=1}^{K_r} \ell_{r,k} p_{r,s}(\ell_{r,k}) \right)$$