---
url: >-
  https://jer-k.github.io/effect-prophet/benchmarks/linear/map-mixed-features-explicit-small.md
---

# Everything at once, small

 [← All linear growth benchmarks](/benchmarks/linear)

24 rows with a switchable weekly pattern, a three-day cycle, an event and a regressor.

## Input

[`benchmark/inputs/v1/map-mixed-features-explicit-small.json`](https://github.com/jer-k/effect-prophet/blob/main/benchmark/inputs/v1/map-mixed-features-explicit-small.json): 24 history rows and 3 forecast rows.

## Output

Largest difference: **1.0e-12** (< 0.0001% of the input's range).

Every forecast row from both libraries.

| Date | Effect Prophet | Python Prophet | Difference |
| --- | ---: | ---: | ---: |
| 2020-01-25 | 21.5149 | 21.5149 | 2.9e-13 |
| 2020-01-26 | 21.9165 | 21.9165 | 7.9e-13 |
| 2020-01-27 | 21.2025 | 21.2025 | 1.0e-12 |

## Timing

Median of all measured repetitions.

| Step | Effect Prophet | Python Prophet | Effect Prophet is |
| --- | ---: | ---: | --- |
| Convert input rows | 11 µs | 486 µs | 44× faster |
| Fit | 2.04 ms | 12.3 ms | 6.0× faster |
| Predict | 170 µs | 4.99 ms | 29× faster |
| Fit and predict | 1.79 ms | 16.0 ms | 8.9× faster |
| Convert, fit and predict | 1.59 ms | 19.7 ms | 12× faster |
| First forecast in a new process | 182 ms | 1.46 s | 8.1× faster |
| Save model to JSON | 27 µs | 585 µs | 22× faster |
| Load model from JSON | 141 µs | 3.74 ms | 27× faster |
| Load and predict in a new process | 174 ms | 1.47 s | 8.5× faster |

## Settings

The case declaration both libraries ran.

```json
{
  "kind": "linear-map",
  "comparison": {
    "kind": "equivalent-objective",
    "evidenceId": "linear-output-first-v4"
  },
  "configuration": {
    "effectMap": "explicit",
    "changepoints": {
      "mode": "explicit",
      "timestamps": [
        "2020-01-11T00:00:00.000Z"
      ]
    },
    "changepointPriorScale": 0.2,
    "seasonalities": [
      {
        "name": "weekly-on",
        "periodDays": 7,
        "fourierOrder": 1,
        "priorScale": 10,
        "conditionName": "onSeason"
      },
      {
        "name": "three-day",
        "periodDays": 3,
        "fourierOrder": 1,
        "priorScale": 5
      }
    ],
    "events": [
      {
        "name": "launch",
        "date": "2020-01-08",
        "lowerWindowDays": 0,
        "upperWindowDays": 0,
        "priorScale": 10
      }
    ],
    "regressors": [
      {
        "name": "promotion",
        "priorScale": 10,
        "standardization": "never"
      }
    ]
  },
  "effectOptimizer": {
    "algorithm": "auto",
    "maxIterations": 10000,
    "fallback": "newton",
    "lbfgs": {
      "historySize": 5,
      "initAlpha": 0.001,
      "tolObj": 1e-12,
      "tolRelObj": 10000,
      "tolGrad": 1e-8,
      "tolRelGrad": 10000000,
      "tolParam": 1e-8
    }
  },
  "pythonOptimizer": {
    "algorithm": "Auto",
    "maxIterations": 10000,
    "newtonFallback": true,
    "sigFigs": 12
  }
}
```