---
url: >-
  https://jer-k.github.io/effect-prophet/benchmarks/flat/uncertainty-flat-defaults-seasonal-intervals-1000.md
---

# Defaults, ranges with a weekly pattern

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

80% ranges from 1,000 simulated paths on every past and future date. A flat trend never changes, so the ranges come from noise alone.

## 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 |
| --- | ---: | ---: | ---: |
| 2020-01-01 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-01-02 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-01-03 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-01-04 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-01-05 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-01-06 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-01-07 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-01-08 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-01-09 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-01-10 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-01-11 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-01-12 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-01-13 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-01-14 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-01-15 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-01-16 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-01-17 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-01-18 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-01-19 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-01-20 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-01-21 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-01-22 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-01-23 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-01-24 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-01-25 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-01-26 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-01-27 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-01-28 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-01-29 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-01-30 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-01-31 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-02-01 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-02-02 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-02-03 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-02-04 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-02-05 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-02-06 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-02-07 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-02-08 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-02-09 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-02-10 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-02-11 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-02-12 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-02-13 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-02-14 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-02-15 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-02-16 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-02-17 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-02-18 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-02-19 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-02-20 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-02-21 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-02-22 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-02-23 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-02-24 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-02-25 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-02-26 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-02-27 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-02-28 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-02-29 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-03-01 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-03-02 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-03-03 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-03-04 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-03-05 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-03-06 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-03-07 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-03-08 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-03-09 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-03-10 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-03-11 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-03-12 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-03-13 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-03-14 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-03-15 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-03-16 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-03-17 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-03-18 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-03-19 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-03-20 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-03-21 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-03-22 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-03-23 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-03-24 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-03-25 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-03-26 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-03-27 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-03-28 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-03-29 | 34.3921 | 34.3921 | 4.7e-11 |
| 2020-03-30 | 33.6334 | 33.6334 | 1.0e-10 |
| 2020-03-31 | 33.9115 | 33.9115 | 8.2e-11 |
| 2020-04-01 | 35.0025 | 35.0025 | 1.0e-12 |
| 2020-04-02 | 36.0968 | 36.0968 | 8.4e-11 |
| 2020-04-03 | 36.3663 | 36.3663 | 1.1e-10 |
| 2020-04-04 | 35.6079 | 35.6079 | 4.8e-11 |
| 2020-04-05 | 34.3921 | 34.3921 | 4.7e-11 |
| 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 | 27 µs | 498 µs | 19× faster |
| Save model to JSON | 18 µs | 448 µs | 25× faster |
| Load model from JSON | 157 µs | 2.13 ms | 14× faster |
| Simulate uncertainty | 4.83 ms | 129 ms | Not compared: different work |
| First simulation in a new process | 298 ms | 1.96 s | Not compared: different work |
| Load and simulate in a new process | 172 ms | 1.57 s | Not compared: different work |

Some steps aren't compared, because the two libraries' public calls produce different outputs. Their times show what each call costs, not which library is faster.

* **Simulate uncertainty, First simulation in a new process, Load and simulate in a new process:** Python's `predict(vectorized=False)` also builds the point forecast and every component, while Effect Prophet's `predictUncertainty` returns only the ranges.

## 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
  },
  "uncertainty": {
    "seed": 19,
    "samples": 1000,
    "intervalWidth": 0.8,
    "output": "intervals",
    "algorithm": "scalar-continuous-time",
    "evidence": "docs/validation/uncertainty.md#evidence-classes",
    "samplerMemoryLimitBytes": 67108864
  }
}
```