junos
/
rapids
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Get the name of the questionnaire from Snakefile.

labels
junos 2022-03-16 18:28:57 +01:00
parent 679f00dc19
commit 23f0aaba3a
2 changed files with 11 additions and 12 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
rules/features.smk
View File

@ -327,7 +327,7 @@ rule conversation_r_features:
rule preprocess_esm: rule preprocess_esm:
input: "data/raw/{pid}/phone_esm_with_datetime.csv" input: "data/raw/{pid}/phone_esm_with_datetime.csv"
params: params:
questionnaire_names = lambda wildcards: config["PHONE_ESM"]["PROVIDERS"][wildcards.feature]["FEATURES"] questionnaire_name = "{feature}"
output: "data/interim/{pid}/phone_esm_{feature}_clean.csv" output: "data/interim/{pid}/phone_esm_{feature}_clean.csv"
script: script:
"../src/features/phone_esm/straw/preprocess.py" "../src/features/phone_esm/straw/preprocess.py"

21
src/features/phone_esm/straw/preprocess.py
View File

@ -1,17 +1,16 @@
from esm_preprocess import * from esm_preprocess import *
questionnaire_names = snakemake.params["questionnaire_names"] questionnaire_name = snakemake.params["questionnaire_name"]
df_esm = pd.read_csv(snakemake.input[0]) df_esm = pd.read_csv(snakemake.input[0])
df_esm_preprocessed = preprocess_esm(df_esm) df_esm_preprocessed = preprocess_esm(df_esm)
for questionnaire_name in questionnaire_names: try:
try: questionnaire_id = QUESTIONNAIRE_IDS[questionnaire_name]
questionnaire_id = QUESTIONNAIRE_IDS[questionnaire_name] except ValueError:
except ValueError: print("The requested questionnaire name should be one of the following:")
print("The requested questionnaire name should be one of the following:") print(QUESTIONNAIRE_IDS.keys())
print(QUESTIONNAIRE_IDS.keys()) else:
else: df_esm_selected = df_esm_preprocessed[df_esm_preprocessed["questionnaire_id"] == questionnaire_id]
df_esm_selected = df_esm_preprocessed[df_esm_preprocessed["questionnaire_id"] == questionnaire_id] df_esm_clean = clean_up_esm(df_esm_selected)
df_esm_clean = clean_up_esm(df_esm_selected) df_esm_clean.to_csv(snakemake.output[0])
df_esm_clean.to_csv(snakemake.output[0])