def test_query_single(self):
"""
This function test whether the "querySingle" function extract correct row and attributes.
"""
data_extract = query_single(DF, 'subject_id', 61, ["subject_id"],
["insurance", "age"], "subject_id")
incorrect_data_extract = query_single(DF, 'subject_id', 300, ["subject_id"],
["insurance"], "subject_id")
self.assertEqual(data_extract.shape, (1, 3))
self.assertEqual(incorrect_data_extract.shape, (0, 2))
self.assertTrue(len(data_extract['insurance'][0]) == len(data_extract['age'][0]))
def test_filter(self):
"""
This function test "filter" function, to see if it can successfully filter the data
from extracted data by "querySingle" function.
"""
data_extract = query_single(DF, 'subject_id', 61, ["subject_id"], \
["insurance", "age"], "subject_id")
filtered_data = f(data_extract, 'subject_id', 66, '>')
self.assertTrue(filtered_data.shape[0] == 0)
filtered_data = f(data_extract, 'subject_id', 66, '<')
self.assertTrue(filtered_data.shape[0] == data_extract.shape[0])
def get_report(self, subject_id, birth_year):
'''main report generator program'''
df1 = database_build.main()
# df1 = pd.read_csv('../Data/test_file.csv')
list_tolist = reversed([
'hadm_id', 'Code', 'Descriptor', 'icd9_code', 'long_title',
'admission_type', 'diagnosis', 'insurance', 'language', 'religion',
'marital_status', 'ethnicity', 'gender', 'expire_flag', 'age',
'age_death', 'age_group', 'admit_year', 'admit_new', 'disch_new',
'description', 'drug_type', 'drug', 'formulary_drug_cd'
])
table = qu.query_single(df1, 'subject_id', int(subject_id),
["subject_id"], list_tolist, ["subject_id"])
ages = table['age'].tolist()
patient_age = int(ages[0][0])
year = birth_year + patient_age
if patient_age <= 4:
age = '0-4'
elif patient_age <= 9:
age = '5-9'
elif patient_age <= 19:
age = '10-19'
elif patient_age <= 29:
age = '20-29'
elif patient_age <= 39:
age = '30-39'
elif patient_age <= 49:
age = '40-49'
elif patient_age <= 59:
age = '50-59'
elif patient_age <= 69:
age = '60-69'
elif patient_age <= 79:
age = '70-79'
elif patient_age >= 80:
age = '80+'
for column in list_tolist:
if column not in list(table.columns.values):
table[column] = 'Nah'
narms = qu.narms_query("../Data/narms_processed.csv", year, age)
data_row = table.iloc[0]
list_content = (data_row.tolist())
list_name = [
'subject_id', 'hadm_id', 'Code', 'Descriptor', 'icd9_code',
'long_title', 'admission_type', 'diagnosis', 'insurance',
'language', 'religion', 'marital_status', 'ethnicity', 'gender',
'expire_flag', 'age', 'age_death', 'age_group', 'admit_year',
'admit_new', 'disch_new', 'description', 'drug_type', 'drug',
'formulary_drug_cd'
]
list_narms = [
'Data_Year', 'Age_Group', 'Specimen_ID', 'Resistance_Pattern',
'AMI_Concl', 'AMP_Concl', 'ATM_Concl', 'AUG_Concl', 'AXO_Concl',
'AZM_Concl', 'CAZ_Concl', 'CCV_Concl', 'CEP_Concl', 'CEQ_Concl',
'CHL_Concl', 'CIP_Concl', 'CLI_Concl', 'COT_Concl', 'CTC_Concl',
'CTX_Concl', 'ERY_Concl', 'FEP_Concl', 'FFN_Concl', 'FIS_Concl',
'FOX_Concl', 'GEN_Concl', 'IMI_Concl', 'KAN_Concl', 'NAL_Concl',
'PTZ_Concl', 'SMX_Concl', 'STR_Concl', 'TEL_Concl', 'TET_Concl',
'TIO_Concl'
]
variable = {}
table_narms = OrderedDict()
for count in range(0, len(list_name)):
cell = list_content[count]
if isinstance(cell, list):
if len(cell) > 1 and list_name[count] != 'drug':
list_content[count] = list_content[count][:1]
elif list_name[count] == 'drug':
list_content[count] = list_content[count][:50]
list_content[count] = str(list_content[count])
variable[list_name[count]] = list_content[count]
for count in range(0, len(list_narms)):
table_narms[list_narms[count]] = str(narms.iloc[0][count])
for item in variable.keys():
values_tem = variable[item]
if (values_tem[0] == '[' and values_tem[1] == "'"
and values_tem[len(values_tem) - 2] == "'"
and values_tem[len(values_tem) - 1] == ']'):
variable[item] = values_tem[2:(len(variable[item]) - 2)]
elif (values_tem[0] == '['
and values_tem[len(values_tem) - 1] == ']'):
variable[item] = values_tem[1:(len(variable[item]) - 1)]
variable['drug'] = variable['drug'].replace("'", " ")
variable['age'] = int(float(variable['age']))
variable['age'] = str(variable['age'])
if variable['age_death'] != 'nan':
variable['age_death'] = int(float(variable['age_death']))
variable['age_death'] = str(variable['age_death'])
if variable['expire_flag'] == '1':
variable['expire_flag'] = 'Death'
else:
variable['expire_flag'] = 'Live'
return variable, table_narms
def test1(self):
'''
test1 is to test if the html is the same as we expect
'''
df1 = pd.read_csv('../Data/test_file.csv')
list_tolist = reversed([
'hadm_id', 'Code', 'Descriptor', 'icd9_code', 'long_title',
'admission_type', 'diagnosis', 'insurance', 'language', 'religion',
'marital_status', 'ethnicity', 'gender', 'expire_flag', 'age',
'age_death', 'age_group', 'admit_year', 'admit_new', 'disch_new',
'description', 'drug_type', 'drug', 'formulary_drug_cd'
])
table = qu.query_single(df1, 'subject_id', 61, ["subject_id"],
list_tolist, ["subject_id"])
for column in list_tolist:
if column not in list(table.columns.values):
table[column] = 'Nah'
table_narms = qu.narms_query("../Data/narms_processed.csv", 1996,
'0-4')
data_row = table.iloc[0]
list_tem = (data_row.tolist())
html = op.html_maker(list_tem, table_narms)
f = open('tem_out.csv', 'w')
f.write(html)
html_template = '''
<hr>
<h1 align="center">Patient Case Report Form</h1>
<hr>
<div class="bordered" style="float: left; width: 48%;">
<h3>Patient Information</h3>
<p>
<b>Subject ID:</b> 61<br>
<b>Hospital Visit ID:</b> 189535<br>
<b>Age:</b> 55<br>
<b>Deceased:</b> Death<br>
<b>Age at Death:</b> 55<br>
<b>Gender:</b> M<br>
<b>Ethnicity:</b> WHITE<br>
<b>Primary Language:</b> nan<br>
<b>Marital Status:</b> MARRIED<br>
<b>Religion:</b> CATHOLIC<br>
<b>Insurance:</b> Private<br>
</p>
</div>
<div class="bordered" style="float: right; width: 50%;">
<p>
<h3>Disease Information</h3>
<b>Condition Diagnosis Code:</b> 99591<br>
<b>Descriptor:</b> Salmonella sepsis<br>
<b>All Diagnoses:</b> Acidosis<br>
<b>Hospital Admission Type:</b>EMERGENCY <br>
<b>Admission Date:</b> 2002-01-04<br>
<b>Discharge Date:</b> 2002-02-03<br>
<h3>Prescription Information</h3>
<b>Medications:</b> Amino Acids 4.25% W/ Dextrose 5% , Calcium Gluconate , Digoxin , Potassium Chloride , Potassium Chloride , Multivitamin IV , Heparin Flush PICC (100 units/ml) , Digoxin , Digoxin , Insulin , Hydrocortisone Na Succ. , Syringe , Insulin , Insulin , NS , Hydrocortisone Na Succ. , Digoxin , Neutra-Phos , Vial , Vial , Sodium Phosphate , Potassium Chloride , Hydrocortisone Na Succ. , Potassium Chloride , Daptomycin , NS , Levofloxacin , Potassium Chloride , SW , Potassium Chloride , Potassium Chloride , NS , Hydrocortisone Na Succ. , Vial , Diltiazem , NS , Potassium Chloride , Potassium Chloride , Potassium Chloride , Potassium Phosphate , SW , SW , SW , Spironolactone , Vial , Filgrastim , Potassium Chloride , Potassium Chloride , Hydrocortisone Na Succ. , Caspofungin<br>
</div>
<br>
<div class="bordered2" style="float: left; width: 100%;">
<p>
<h3>NARMS Data</h3>
<br>
<b>List</b><br>
AMI Amikacin : 0<br>
AMP Ampicillin : 2<br>
ATM Aztreonam : 0<br>
AUG Amoxicillin-clavulanic acid: 0<br>
AXO Ceftriaxone: 0<br>
AZM Azithromycin: 0<br>
CAZ Ceftazidime: 0<br>
CCV Ceftazidime-clavulanic acid: 0<br>
CEP Cephalothin: 0<br>
CEQ Cefquinome: 0<br>
CHL Chloramphenicol: 2<br>
CIP Ciprofloxacin: 0<br>
CLI Clindamycin: 0<br>
COT Trimethoprim-sulfamethoxazole: 0<br>
CTC Cefotaxime-clavulanic acid: 0<br>
CTX Cefotaxime: 0<br>
ERY Erythromycin: 0<br>
FEP Cefepime: 0<br>
FFN Florfenicol: 0<br>
FIS Sulfisoxazole: 0<br>
FOX Cefoxitin: 0<br>
GEN Gentamicin: 0<br>
IMI Imipenem: 0<br>
KAN Kanamycin: 0<br>
NAL Naladixic acid: 0<br>
PTZ Piperacillin-tazobactam: 0<br>
SMX Sulfamethoxazole: 2<br>
STR Streptomycin: 2<br>
TEL Telithromycin: 0<br>
TIO Ceftiofur: 0<br>
TET Tetracycline: 3<br>
</p>
</div>
<img src="eCRx_logo_small.png" alt="eCRx Logo" style="float:left;width:10px;height:8.3px;">
'''
self.assertEqual(len(html), len(html_template))
''' update: stu_id is optional
# do login (need stu_id from args)
if args.stu_id:
stu_id = args.stu_id
load_from_cookies(stu_id)
else:
print ('You must provide a student ID for login!')
#exit(0)
'''
if args.mode == 'query':
if args.search and args.begin and args.end:
print('please do not provide them at the same time!')
exit(0)
if args.search or (args.begin and args.end):
import query
if args.search:
query.query_single(args.search)
else:
query.query_multiple(args.begin, args.end)
else:
print('please provide --search or (--begin AND --end)!')
exit(0)
if args.export:
from parse import parse
if args.export == 'csv':
parse('csv')
elif args.export == 'jpg':
parse()