francois/HowBadIsMyBatch
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

refactoring

Browse Source
This commit is contained in:
frankknoll
2023-01-23 08:07:23 +01:00
parent 28e71af7af
commit b6eb929a7b
2 changed files with 18 additions and 18 deletions
Download Patch File Download Diff File Expand all files Collapse all files

170
src/SymptomByBatchcodeTableFactoryTest.py Normal file
View File

@@ -0,0 +1,170 @@
import unittest
from pandas.testing import assert_frame_equal
from TestHelper import TestHelper
from SymptomByBatchcodeTableFactory import SymptomByBatchcodeTableFactory
import pandas as pd
import numpy as np
# FIXME: brauchen Normalisierung analog zu DataFrameNormalizer.removeUnknownBatchCodes(dataFrame) und DataFrameNormalizer.convertVAX_LOTColumnToUpperCase(dataFrame)
class SymptomByBatchcodeTableFactoryTest(unittest.TestCase):
def test_createSymptomByBatchcodeTable(self):
# Given
VAERSVAX = TestHelper.createDataFrame(
columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],
data = [ ['COVID19', 'JANSSEN', 'EW0175', 'UNK'],
['COVID19', 'PFIZER\BIONTECH', '1808982', '1']],
index = pd.Index(
name = 'VAERS_ID',
data=[
2547730,
2547730]),
dtypes = {
'VAX_DOSE_SERIES': 'string',
'VAX_LOT': 'string'})
VAERSSYMPTOMS = TestHelper.createDataFrame(
columns = ['SYMPTOM1', 'SYMPTOM2', 'SYMPTOM3', 'SYMPTOM4', 'SYMPTOM5'],
data = [ ['Blood pressure orthostatic abnormal', 'COVID-19', 'Coma', 'Computerised tomogram', 'Exposure to SARS-CoV-2'],
['Head injury', 'Headache', 'Laboratory test', 'Magnetic resonance imaging', 'SARS-CoV-2 antibody test negative'],
['SARS-CoV-2 test positive', 'Unresponsive to stimuli', 'X-ray', np.nan, np.nan]],
index = pd.Index(
name = 'VAERS_ID',
data=[
2547730,
2547730,
2547730]))
# When
symptomByBatchcodeTable = SymptomByBatchcodeTableFactory.createSymptomByBatchcodeTable(VAERSVAX, VAERSSYMPTOMS)
# Then
assert_frame_equal(
symptomByBatchcodeTable,
TestHelper.createDataFrame(
columns = ['SYMPTOM'],
data = [ ['Blood pressure orthostatic abnormal'],
['Head injury'],
['SARS-CoV-2 test positive'],
['COVID-19'],
['Headache'],
['Unresponsive to stimuli'],
['Coma'],
['Laboratory test'],
['X-ray'],
['Computerised tomogram'],
['Magnetic resonance imaging'],
['Exposure to SARS-CoV-2'],
['SARS-CoV-2 antibody test negative']],
index = pd.MultiIndex.from_tuples(
names = ['VAX_LOT1', 'VAX_LOT2'],
tuples = [['1808982', 'EW0175']] * 13)))
def test_createSymptomByBatchcodeTable_two_patients_same_symptoms(self):
# Given
VAERSVAX = TestHelper.createDataFrame(
columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],
data = [ ['COVID19', 'JANSSEN', 'EW0175', '1'],
['COVID19', 'JANSSEN', 'EW0175', '1']],
index = pd.Index(
name = 'VAERS_ID',
data=[
2547730,
2547731]),
dtypes = {
'VAX_DOSE_SERIES': 'string',
'VAX_LOT': 'string'})
VAERSSYMPTOMS = TestHelper.createDataFrame(
columns = ['SYMPTOM1', 'SYMPTOM2', 'SYMPTOM3', 'SYMPTOM4', 'SYMPTOM5'],
data = [ ['Blood pressure orthostatic abnormal', np.nan, np.nan, np.nan, np.nan],
['Blood pressure orthostatic abnormal', np.nan, np.nan, np.nan, np.nan]],
index = pd.Index(
name = 'VAERS_ID',
data=[
2547730,
2547731]))
# When
symptomByBatchcodeTable = SymptomByBatchcodeTableFactory.createSymptomByBatchcodeTable(VAERSVAX, VAERSSYMPTOMS)
# Then
assert_frame_equal(
symptomByBatchcodeTable,
TestHelper.createDataFrame(
columns = ['SYMPTOM'],
data = [ ['Blood pressure orthostatic abnormal'],
['Blood pressure orthostatic abnormal']],
index = pd.Index(
name = 'VAX_LOT1',
data = ['EW0175',
'EW0175'])),
check_dtype = False)
def test_createSymptomByBatchcodeTable_two_patients_distinct_symptoms(self):
# Given
VAERSVAX = TestHelper.createDataFrame(
columns = ['VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],
data = [ ['COVID19', 'JANSSEN', '1808982', 'UNK'],
['COVID19', 'PFIZER\BIONTECH', 'EW0175', '1'],
['COVID19', 'PFIZER\BIONTECH', 'EW0175', '1'],
['COVID19', 'PFIZER\BIONTECH', 'EW0167', '2']],
index = pd.Index(
name = 'VAERS_ID',
data=[
2547730,
2547730,
2547744,
2547744]),
dtypes = {
'VAX_DOSE_SERIES': 'string',
'VAX_LOT': 'string'})
VAERSSYMPTOMS = TestHelper.createDataFrame(
columns = ['SYMPTOM1', 'SYMPTOM2', 'SYMPTOM3', 'SYMPTOM4', 'SYMPTOM5'],
data = [ ['Blood pressure orthostatic abnormal', 'COVID-19', 'Coma', 'Computerised tomogram', 'Exposure to SARS-CoV-2'],
['Head injury', 'Headache', 'Laboratory test', 'Magnetic resonance imaging', 'SARS-CoV-2 antibody test negative'],
['SARS-CoV-2 test positive', 'Unresponsive to stimuli', 'X-ray', np.nan, np.nan],
['Computerised tomogram head abnormal', 'Ear pain', 'Headache', 'Idiopathic intracranial hypertension', 'Intracranial pressure increased'],
['Lumbar puncture', 'Magnetic resonance imaging head', 'Pain', 'Swelling', 'Vision blurred']],
index = pd.Index(
name = 'VAERS_ID',
data=[
2547730,
2547730,
2547730,
2547744,
2547744]))
# When
symptomByBatchcodeTable = SymptomByBatchcodeTableFactory.createSymptomByBatchcodeTable(VAERSVAX, VAERSSYMPTOMS)
# Then
assert_frame_equal(
symptomByBatchcodeTable,
TestHelper.createDataFrame(
columns = ['SYMPTOM'],
data = [ ['Blood pressure orthostatic abnormal'],
['Head injury'],
['SARS-CoV-2 test positive'],
['COVID-19'],
['Headache'],
['Unresponsive to stimuli'],
['Coma'],
['Laboratory test'],
['X-ray'],
['Computerised tomogram'],
['Magnetic resonance imaging'],
['Exposure to SARS-CoV-2'],
['SARS-CoV-2 antibody test negative'],
['Computerised tomogram head abnormal'],
['Lumbar puncture'],
['Ear pain'],
['Magnetic resonance imaging head'],
['Headache'],
['Pain'],
['Idiopathic intracranial hypertension'],
['Swelling'],
['Intracranial pressure increased'],
['Vision blurred']],
index = pd.MultiIndex.from_tuples(
names = ['VAX_LOT1', 'VAX_LOT2'],
tuples = [['1808982', 'EW0175']] * 13 + [['EW0167', 'EW0175']] * 10)))