---
url: >-
  https://jer-k.github.io/effect-prophet/benchmarks/flat/flat-defaults-seasonal.md
---

# Defaults, weekly pattern

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

96 days around one level with a clear weekly rhythm.

## Input

[`benchmark/inputs/v1/flat-seasonal.json`](https://github.com/jer-k/effect-prophet/blob/main/benchmark/inputs/v1/flat-seasonal.json): 96 history rows and 24 forecast rows.

## Output

Largest difference: **1.1e-10** (< 0.0001% of the input's range).

Every forecast row from both libraries.

| Date | Effect Prophet | Python Prophet | Difference |
| --- | ---: | ---: | ---: |
| 2020-04-06 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-04-07 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-04-08 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-04-09 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-04-10 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-04-11 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-04-12 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-04-13 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-04-14 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-04-15 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-04-16 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-04-17 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-04-18 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-04-19 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-04-20 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-04-21 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-04-22 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-04-23 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-04-24 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-04-25 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-04-26 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-04-27 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-04-28 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-04-29 | 35.0025 | 35.0025 | 1.0e-12 |

## Timing

Median of all measured repetitions.

| Step | Effect Prophet | Python Prophet | Effect Prophet is |
| --- | ---: | ---: | --- |
| Convert input rows | 13 µs | 478 µs | 37× faster |
| Fit | 105 ms | 392 ms | 3.8× faster |
| Predict | 306 µs | 3.31 ms | 11× faster |
| Fit and predict | 105 ms | 398 ms | 3.8× faster |
| Convert, fit and predict | 104 ms | 398 ms | 3.8× faster |
| First forecast in a new process | 292 ms | 1.84 s | 6.3× faster |
| Save model to JSON | 25 µs | 481 µs | 19× faster |
| Load model from JSON | 126 µs | 2.14 ms | 17× faster |
| Load and predict in a new process | 161 ms | 1.44 s | 9.0× faster |

## Settings

The case declaration both libraries ran.

```json
{
  "kind": "map",
  "comparison": {
    "kind": "equivalent-objective",
    "evidenceId": "flat-growth-reduced-v1"
  },
  "fitRequest": "growth-only",
  "configuration": {
    "growth": "flat",
    "scaling": "absmax",
    "seasonalityMode": "additive",
    "holidaysMode": "additive",
    "changepoints": {
      "mode": "auto",
      "count": 25,
      "range": 0.8
    },
    "changepointPriorScale": 0.05,
    "seasonalities": [
      {
        "name": "weekly",
        "periodDays": 7,
        "fourierOrder": 3,
        "priorScale": 10
      }
    ],
    "events": [],
    "regressors": []
  },
  "pythonOptimizer": {
    "algorithm": "Auto",
    "maxIterations": 10000,
    "newtonFallback": true
  }
}
```