Survival Analysis functionalities for Python. Compatible with Python 2 or 3.
Analysis output is compatible for visualizations with: https://github.com/oncojs/survivalplot
$ pip install SurvivalPy
A requirements.txt file is provided for use with pip and virtualenv
Sample Data:
| time | censored | Donor ID |
|---|---|---|
| 1 | 0 | D13 |
| 1 | 1 | D54 |
| 3 | 0 | D81 |
| 4 | 0 | D95 |
| 6 | 1 | D32 |
| 6 | 0 | D20 |
| 9 | 1 | D51 |
Encoded in python as objects and analyzed:
from survivalpy.survival import Analyzer
from survivalpy.survival import Datum
data = [Datum(1, False, {'id': 'D13'}),
Datum(1, True, {'id': 'D54'}),
Datum(3, False, {'id': 'D81'}),
Datum(4, False, {'id': 'D95'}),
Datum(6, True, {'id': 'D32'}),
Datum(6, False, {'id': 'D20'}),
Datum(9, True, {'id': 'D51'})]
analyzer = Analyzer(data)
results = analyzer.compute()The results will be a list of intervals. If you serialize to json using the to_json_dict method of the Intervals, it will look like:
>>> results = analyzer.compute()
>>> json_results = list(map(lambda interval: interval.to_json_dict(), results))
>>> print(json.dumps(json_results))
[{"start": 0, "donors": [{"time": 1, "censored": false, "meta": {"id": "D13"}}, {"time": 1, "censored": true, "meta": {"id": "D54"}}], "censored": 1, "died": 1, "cumulativeSurvival": 1, "end": 1}, {"start": 0, "donors": [{"time": 3, "censored": false, "meta": {"id": "D81"}}], "censored": 0, "died": 1, "cumulativeSurvival": 0.8333333333333334, "end": 3}, {"start": 0, "donors": [{"time": 4, "censored": false, "meta": {"id": "D95"}}], "censored": 0, "died": 1, "cumulativeSurvival": 0.8, "end": 4}, {"start": 0, "donors": [{"time": 6, "censored": true, "meta": {"id": "D32"}}, {"time": 6, "censored": false, "meta": {"id": "D20"}}], "censored": 1, "died": 1, "cumulativeSurvival": 0.75, "end": 6}, {"start": 0, "donors": [], "censored": 0, "died": 0, "cumulativeSurvival": 0, "end": 6}]To perform a log-rank test between two or more curves:
from survivalpy.logrank import LogRankTest
from survivalpy.survival import Analyzer
...
# Two curves expressed as intervals
curves = [analyzer_1.compute(), analyzer_2.compute()]
stats = LogRankTest(survival_results=curves).compute()
The ouput will be a json serializable dictionary of the form:
{"chiSquared": 15.232850289359583, "pValue": 9.503581328784705e-05, "degreesFreedom": 1}
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