Issue
I have a par.json
file were i stored the variable values. And fetched the values in .py
file successfully. I'm trying to run all function of .py
file in jupyter notebook (all is in same location) where .py
file already getting values from json
file but while running in jupyter notebook
it is throwing an error called as 'b_threshold' is not defined
json file I have
{
"mul": 200,
"b_threshold": 2,
"a_threshold": 5,
}
the multi.py file snippet is below
def h_b_acc(data, har={}):
trr = data.tt.unique()
# global b_threshold, a_threshold, mul
for tr in trr:
temp_dict = {}
temp_df = data.loc[data['tt']==tr].copy()
temp_df['b_event'] = temp_df['aci'].apply(lambda x: 1 if x < b_threshold else 0)
temp_df['a_event'] = temp_df['aci'].apply(lambda x: 1 if x > a_threshold else 0)
total_d_dis = temp_df['dd'].max() - temp_df['dd'].min()
temp_dict['b_s'] = (2015* mul)/ total_d_dis
temp_dict['a_s']= (2016 * mul)/ total_d_dis
har['tr_' + str(tr)] = temp_dict
# print(temp_dict)
return har
if __name__ =='__main__':
try:
with open(r'path\par.json', "r") as prm_mp:
pp = json.load(prm_mp)
b_threshold = pp.get('b_threshold', 2)
a_threshold = pp.get('a_threshold', 5)
mul = pp.get(['mul'],200)
except:
print("Parameter mapping file not parsed")
loaded json file in following way in jupyter notebook
with open(r'path\par.json', "r") as prm_mp:
pp = json.load(prm_mp)
b_threshold = pp.get('b_threshold', 2)
a_threshold = pp.get('a_threshold', 5)
mul = pp.get(['mul'],200)
har_1 = multi.h_b_acc(tm)
har_1
showing following error .. how can I import it ? or may I wrong in writing function.
Solution
Your imported module multi
and its function h_b_acc()
do not have access to your variables a_threshold
and b_threshold
. I recommend that you modify multi.h_b_acc()
to pass them as optional arguments, so you can use the function in the Jupyer Notebook, as well as use your global variables in multi.py
when needed. (It's also probably a good idea to ALL-CAPS your global variables)
def h_b_acc(data, a_threshold=A_THRESHOLD, b_threshold=B_THRESHOLD, mul=MUL, har={}):
trr = data.tt.unique()
for tr in trr:
temp_dict = {}
temp_df = data.loc[data['tt']==tr].copy()
temp_df['b_event'] = temp_df['aci'].apply(lambda x: 1 if x < b_threshold else 0)
temp_df['a_event'] = temp_df['aci'].apply(lambda x: 1 if x > a_threshold else 0)
total_d_dis = temp_df['dd'].max() - temp_df['dd'].min()
temp_dict['b_s'] = (2015* mul)/ total_d_dis
temp_dict['a_s']= (2016 * mul)/ total_d_dis
har['tr_' + str(tr)] = temp_dict
# print(temp_dict)
return har
This, way, in your Jupyter Notebook, you can do the following:
with open(r'path\par.json', "r") as prm_mp:
pp = json.load(prm_mp)
b_threshold = pp.get('b_threshold', 2)
a_threshold = pp.get('a_threshold', 5)
mul = pp.get(['mul'],200)
har_1 = multi.h_b_acc(tm, a_threshold, b_threshold, mul)
har_1
Answered By - Aatlantise
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