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cached-contingency-0.0.4
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مشاهده بیشتر
تبلیغات ما
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مشاهده بیشترتوضیحات
Compute and cache Fisher's exact test and Boschloo's test more efficiently!
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | cached-contingency-0.0.4 |
| نام | cached-contingency |
| نسخه کتابخانه | 0.0.4 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Thomas Roder |
| ایمیل نویسنده | roder.thomas@gmail.com |
| آدرس صفحه اصلی | https://github.com/MrTomRod/cached-contingency |
| آدرس اینترنتی | https://pypi.org/project/cached-contingency/ |
| مجوز | MIT |
# CachedContingency
Python 3.9+ classes to compute and cache
[Fisher's exact test](https://en.wikipedia.org/wiki/Fisher%27s_exact_test) and
[Boschloo's test](https://en.wikipedia.org/wiki/Boschloo%27s_test) more efficiently.
## Installation
This package requires at least `Python 3.9`.
```bash
pip install cached_contingency
```
## Idea
I have to compute lots of these tests and want to accelerate the process. There are two optimizations that came to my mind:
1) My contingency tables often have identical column sums, so many tests can be recycled
2) Some contingency tables are equivalent and only have to be computed once
* Fisher's test: `abcd`, `acbd`, `badc`, `bdac`, `cadb`, `cdab`, `dbca` and `dcba` are equivalent (pvalue, _not_ odds ratio)
* Boschloo's test: `abcd`, `badc`, `cdab` and `dcba` are equivalent
Furthermore, sometimes, one has to re-run tools. In these cases, all previously computed results can be recycled.
As cache, an SQLite database is used.
### Execution
1) Replace equivalent contingency tables with the same contingency table
2) Find all tests that are not cached yet
3) Calculate them in parallel, using all CPU cores
4) Add them to the cache
5) Return results
## Usage
Set the location of the cache database:
```bash
export KEY_VALUE_STORE_DB=/custom/path.db # default: ~/.cache/keyvaluestore.db
```
Calculate single tests:
```python
from cached_contingency import CachedFisher, CachedBoschloo, odds_ratio
from scipy.stats import fisher_exact, boschloo_exact
from numpy import isclose
# Create class (automatically creates database if none exists yet)
cf = CachedFisher()
# Calculate Fisher's test
pval_cache = cf.get_or_create(74, 31, 43, 32)
odds_ratio_cache = odds_ratio(74, 31, 43, 32)
# This is equivalent to:
odds_ratio_calc, pval_calc = fisher_exact([[74, 31], [43, 32]])
assert isclose(pval_cache, pval_calc)
assert isclose(odds_ratio_cache, odds_ratio_calc)
# Create class (automatically creates database if none exists yet)
cb = CachedBoschloo()
# Calculate Fisher's test
pval_cache = cb.get_or_create(74, 31, 43, 32)
# This is almost* equivalent to:
pval_calc = boschloo_exact([[74, 31], [43, 32]]).pvalue
assert isclose(pval_cache, pval_calc)
```
* \*: Not exactly equivalent: My function never returns pvalues greater than 1 and never returns nan as pvalues.
(See [scipy issue](https://github.com/scipy/scipy/issues/15345).)
Calculate multiple tests:
```python
from cached_contingency import CachedFisher, CachedBoschloo
import pandas as pd
import numpy as np
# Create class (automatically creates database if none exists yet)
cb = CachedBoschloo()
# Create test DataFrame, column names are important!
np.random.seed(42)
test_df = pd.DataFrame(
[(np.random.randint(200) for _ in range(4)) for _ in range(5)],
columns=['c1r1', 'c2r1', 'c1r2', 'c2r2']
)
print(test_df)
# c1r1 c2r1 c1r2 c2r2
# 0 102 179 92 14
# 1 106 71 188 20
# 2 102 121 74 87
# 3 116 99 103 151
# 4 130 149 52 1
# Calculate multiple Boschloo's tests
result_df = cb.get_or_create_many(test_df)
print(result_df)
# c1r1 c2r1 c1r2 c2r2 pval
# 0 102 179 92 14 3.442564e-20
# 1 106 71 188 20 1.144156e-12
# 2 102 121 74 87 9.692791e-01
# 3 116 99 103 151 3.821222e-03
# 4 130 149 52 1 1.831830e-14
# If you run this again, the results will be loaded from cache:
result_df = cb.get_or_create_many(test_df)
print('Like a flash!')
```
**Advanced usage:**
Alternative way to specify the path to the database via Python and change number of CPUs:
```python
from cached_contingency import CachedFisher
cf = CachedFisher(db_path='/custom/path.db', n_cpus=1)
```
نحوه نصب
نصب پکیج whl cached-contingency-0.0.4:
pip install cached-contingency-0.0.4.whl
نصب پکیج tar.gz cached-contingency-0.0.4:
pip install cached-contingency-0.0.4.tar.gz