File size: 8,250 Bytes
4c02fbe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 | """Build portable StrandMD analysis packages for browser downloads."""
from __future__ import annotations
import io
import json
import re
import zipfile
from dataclasses import asdict
from datetime import datetime, timezone
from pathlib import Path
from typing import Mapping
from casmd import __version__
from casmd.project import Project
from casmd.report.comparison import ComparisonData
from casmd.report.data import AnalysisResult, AnalysisSummary
from casmd.report.stats import StatTest
_README = """# StrandMD analysis package
This archive contains the numerical data, available figures, and provenance
shown in the StrandMD web dashboard.
## Interpretation limits
- Molecular dynamics frames are autocorrelated and are not independent
biological replicates.
- Descriptive differences between single trajectories do not establish
statistical significance.
- Structure prediction and simulation results prioritize hypotheses for
experimental testing; they do not prove binding affinity or activity.
- Inspect `manifest.json` and `summary.json` before reusing a figure.
"""
def _slug(value: str) -> str:
value = re.sub(r"[^A-Za-z0-9._-]+", "_", value.strip())
return value.strip("._") or "run"
def _json_bytes(value: object) -> bytes:
return json.dumps(value, indent=2, allow_nan=False).encode("utf-8")
def _summary_dict(summary: AnalysisSummary) -> dict:
data = asdict(summary)
# JSON has no portable NaN representation. Missing/non-finite values are
# exported as null instead of implementation-specific NaN tokens.
for key, value in list(data.items()):
if isinstance(value, float) and value != value:
data[key] = None
return data
def build_descriptive_comparison(
*,
summary_a: AnalysisSummary,
summary_b: AnalysisSummary,
label_a: str,
label_b: str,
figures_a: Mapping[str, Path] | None = None,
figures_b: Mapping[str, Path] | None = None,
) -> ComparisonData:
"""Build scalar, descriptive comparison data without frame-wise tests."""
scalar_fields = {
"rmsd": "protein_rmsd_equil_mean_A",
"rmsf": "protein_rmsf_mean_A",
"rg": "protein_rg_equil_mean_A",
}
stats = {}
for metric, field in scalar_fields.items():
value_a = getattr(summary_a, field)
value_b = getattr(summary_b, field)
if value_a is None or value_b is None:
continue
stats[metric] = StatTest(
metric=metric,
mean_a=float(value_a),
mean_b=float(value_b),
delta=float(value_b) - float(value_a),
test_name="descriptive difference",
pvalue=float("nan"),
significant=False,
)
def _result(summary: AnalysisSummary) -> AnalysisResult:
return AnalysisResult(
n_frames=summary.n_frames,
equil_skip=summary.equil_skip,
protein_rmsd_equil_mean_A=summary.protein_rmsd_equil_mean_A,
protein_rmsf_mean_A=summary.protein_rmsf_mean_A,
protein_rg_equil_mean_A=summary.protein_rg_equil_mean_A,
)
return ComparisonData(
label_a=label_a,
label_b=label_b,
analysis_a=_result(summary_a),
analysis_b=_result(summary_b),
figures_a=dict(figures_a or {}),
figures_b=dict(figures_b or {}),
stats=stats,
interpretation=(
"Descriptive trajectory differences only; independent replicates "
"are required for inferential analysis."
),
)
def _write_run_files(
zf: zipfile.ZipFile,
*,
root: str,
summary: AnalysisSummary,
dat_files: Mapping[str, Path],
fig_files: Mapping[str, Path],
) -> list[str]:
written = []
summary_name = f"{root}/summary.json"
zf.writestr(summary_name, _json_bytes(_summary_dict(summary)))
written.append(summary_name)
for key, path in sorted(dat_files.items()):
path = Path(path)
if path.exists():
name = f"{root}/data/{_slug(key)}{path.suffix or '.dat'}"
zf.writestr(name, path.read_bytes())
written.append(name)
for key, path in sorted(fig_files.items()):
path = Path(path)
if path.exists():
name = f"{root}/figures/{_slug(key)}{path.suffix or '.png'}"
zf.writestr(name, path.read_bytes())
written.append(name)
return written
def build_single_analysis_package(
*,
label: str,
summary: AnalysisSummary,
dat_files: Mapping[str, Path],
fig_files: Mapping[str, Path],
project: Project | None = None,
condition_id: str | None = None,
replicate_id: str | None = None,
) -> bytes:
"""Return a ZIP containing one run's dashboard data and provenance."""
output = io.BytesIO()
root = f"runs/{_slug(label)}"
with zipfile.ZipFile(output, "w", compression=zipfile.ZIP_DEFLATED) as zf:
written = _write_run_files(
zf, root=root, summary=summary,
dat_files=dat_files, fig_files=fig_files,
)
manifest = {
"schema_version": 1,
"application": "StrandMD",
"application_version": __version__,
"package_type": "single_analysis",
"created_utc": datetime.now(timezone.utc).isoformat(),
"label": label,
"project_id": project.project_id if project else None,
"condition_id": condition_id,
"replicate_id": replicate_id,
"files": written,
}
if project is not None:
zf.writestr("project.json", _json_bytes(project.to_manifest()))
written.append("project.json")
zf.writestr("manifest.json", _json_bytes(manifest))
zf.writestr("README.md", _README.encode("utf-8"))
return output.getvalue()
def build_comparison_analysis_package(
*,
comparison: ComparisonData,
summary_a: AnalysisSummary,
summary_b: AnalysisSummary,
dat_a: Mapping[str, Path],
dat_b: Mapping[str, Path],
fig_a: Mapping[str, Path],
fig_b: Mapping[str, Path],
project: Project | None = None,
) -> bytes:
"""Return a ZIP for a descriptive two-run comparison.
Inferential p-values are deliberately excluded: a pair of autocorrelated
trajectories does not provide independent replicate-level evidence.
"""
output = io.BytesIO()
with zipfile.ZipFile(output, "w", compression=zipfile.ZIP_DEFLATED) as zf:
written = []
written += _write_run_files(
zf, root=f"runs/{_slug(comparison.label_a)}", summary=summary_a,
dat_files=dat_a, fig_files=fig_a,
)
written += _write_run_files(
zf, root=f"runs/{_slug(comparison.label_b)}", summary=summary_b,
dat_files=dat_b, fig_files=fig_b,
)
descriptive = {
"label_a": comparison.label_a,
"label_b": comparison.label_b,
"note": (
"Descriptive trajectory differences only. Add independent "
"replicates before inferential analysis."
),
"metrics": {
key: {
"mean_a": stat.mean_a,
"mean_b": stat.mean_b,
"delta_b_minus_a": stat.delta,
}
for key, stat in comparison.stats.items()
},
}
zf.writestr("comparison_summary.json", _json_bytes(descriptive))
written.append("comparison_summary.json")
if project is not None:
zf.writestr("project.json", _json_bytes(project.to_manifest()))
written.append("project.json")
manifest = {
"schema_version": 1,
"application": "StrandMD",
"application_version": __version__,
"package_type": "descriptive_comparison",
"created_utc": datetime.now(timezone.utc).isoformat(),
"labels": [comparison.label_a, comparison.label_b],
"project_id": project.project_id if project else None,
"files": written,
}
zf.writestr("manifest.json", _json_bytes(manifest))
zf.writestr("README.md", _README.encode("utf-8"))
return output.getvalue()
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