analyze-convergence skillC
analyze-convergence is agent-read markdown (skill) from equinor/neqsim.
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What the file says
# Skill: Analyze Convergence
## Purpose
Interpret flash algorithm convergence metrics, identify patterns, and produce
publication-quality analysis for the Results section.
## When to Use
- After running benchmark experiments
- When comparing baseline vs candidate algorithms
- When investigating failure cases
## Analysis Procedure
### Step 1: Load and Parse Results
```python
import json
import pandas as pd
def load_results(results_dir, algorithm_name):
"""Load JSONL results into DataFrame."""
records = []
with open(f"{results_dir}/raw/{algorithm_name}_results.jsonl") as f:
for line in f:
records.append(json.loads(line))
return pd.DataFrame(records)
```
### Step 2: Convergence Rate by Family
```python
def convergence_by_family(df):
"""Calculate convergence rate per fluid family."""
return df.groupby("family").agg(
total=("converged", "count"),
converged=("converged", "sum"),
rate_pct=("converged", lambda x: round(100 * x.mean(), 2)),
median_time_ms=("cpu_time_ms", "median")
).reset_index()
```
### Step 3: Convergence Maps
Generate 2D convergence maps in (T, P) space:
```python
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How to install
mdr add equinor/neqsim/analyze-convergence@git:20260919.77c34a0mdr add equinor/neqsim/analyze-convergence@sha256:4a30f1f359908c86Pin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_7uu2rdodhqdzb6sw)
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Source
equinor/neqsim · 155 stars · license Apache-2.0 · pushed 2026-09-24 · branch master
API
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