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refactoring

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frankknoll
2022-02-02 00:06:00 +01:00
parent 0317d25a90
commit 8e1713d3b6
1 changed files with 43 additions and 46 deletions
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89
HowBadIsMyBatch.ipynb
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@@ -546,57 +546,54 @@
"class DoseAnalysisTest(unittest.TestCase):\n",
"\n",
" def test_getFirstDoseTable(self):\n",
" # Given\n",
" dataFrame = self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['Y', np.NaN, np.NaN,\t 'COVID19', 'MODERNA', '016M20A', '2'],\n",
" ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '030L20A', '1'],\n",
" ['Y', 'Y', 'Y', 'COVID19', 'MODERNA', '030L20B', '1']],\n",
" index = [\n",
" \"1048786\",\n",
" \"1048786\",\n",
" \"4711\"],\n",
" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
" \n",
" # When\n",
" doseTable = DoseAnalysis.getNthDoseTable(dataFrame, dose = '1')\n",
" \n",
" # Then\n",
" doseTableExpected = pd.Series(\n",
" {\n",
" 'Total reports': 2,\n",
" 'Deaths': 2,\n",
" 'Disabilities': 1,\n",
" 'Life Threatening Illnesses': 1,\n",
" 'Severe reports': (2 + 1 + 1)/2 * 100\n",
" })\n",
" assert_series_equal(doseTable, doseTableExpected)\n",
" self._test_getNthDoseTable(\n",
" dataFrame = self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['Y', np.NaN, np.NaN,\t 'COVID19', 'MODERNA', '016M20A', '2'],\n",
" ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '030L20A', '1'],\n",
" ['Y', 'Y', 'Y', 'COVID19', 'MODERNA', '030L20B', '1']],\n",
" index = [\n",
" \"1048786\",\n",
" \"1048786\",\n",
" \"4711\"],\n",
" dtypes = {'VAX_DOSE_SERIES': \"string\"}),\n",
" dose = '1',\n",
" doseTableExpected = pd.Series(\n",
" {\n",
" 'Total reports': 2,\n",
" 'Deaths': 2,\n",
" 'Disabilities': 1,\n",
" 'Life Threatening Illnesses': 1,\n",
" 'Severe reports': (2 + 1 + 1)/2 * 100\n",
" }))\n",
"\n",
" def test_getSecondDoseTable(self):\n",
" # Given\n",
" dataFrame = self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['Y', np.NaN, np.NaN,\t 'COVID19', 'MODERNA', '016M20A', '2'],\n",
" ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '030L20A', '1'],\n",
" ['Y', 'Y', 'Y', 'COVID19', 'MODERNA', '030L20B', '1']],\n",
" index = [\n",
" \"1048786\",\n",
" \"1048786\",\n",
" \"4711\"],\n",
" dtypes = {'VAX_DOSE_SERIES': \"string\"})\n",
" \n",
" self._test_getNthDoseTable(\n",
" dataFrame = self.createDataFrame(\n",
" columns = ['DIED', 'L_THREAT', 'DISABLE', 'VAX_TYPE', 'VAX_MANU', 'VAX_LOT', 'VAX_DOSE_SERIES'],\n",
" data = [ ['Y', np.NaN, np.NaN,\t 'COVID19', 'MODERNA', '016M20A', '2'],\n",
" ['Y', np.NaN, np.NaN, 'COVID19', 'MODERNA', '030L20A', '1'],\n",
" ['Y', 'Y', 'Y', 'COVID19', 'MODERNA', '030L20B', '1']],\n",
" index = [\n",
" \"1048786\",\n",
" \"1048786\",\n",
" \"4711\"],\n",
" dtypes = {'VAX_DOSE_SERIES': \"string\"}),\n",
" dose = '2',\n",
" doseTableExpected = pd.Series(\n",
" {\n",
" 'Total reports': 1,\n",
" 'Deaths': 1,\n",
" 'Disabilities': 0,\n",
" 'Life Threatening Illnesses': 0,\n",
" 'Severe reports': (1 + 0 + 0)/1 * 100\n",
" }))\n",
"\n",
" def _test_getNthDoseTable(self, dataFrame, dose, doseTableExpected):\n",
" # When\n",
" doseTable = DoseAnalysis.getNthDoseTable(dataFrame, dose = '2')\n",
" doseTable = DoseAnalysis.getNthDoseTable(dataFrame, dose)\n",
" \n",
" # Then\n",
" doseTableExpected = pd.Series(\n",
" {\n",
" 'Total reports': 1,\n",
" 'Deaths': 1,\n",
" 'Disabilities': 0,\n",
" 'Life Threatening Illnesses': 0,\n",
" 'Severe reports': (1 + 0 + 0)/1 * 100\n",
" })\n",
" assert_series_equal(doseTable, doseTableExpected)\n",
"\n",
" def createDataFrame(self, index, columns, data, dtypes = {}):\n",