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Commit adc7fe1e authored by Clara Betancourt's avatar Clara Betancourt
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data capture evaluations

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...@@ -5,7 +5,7 @@ ...@@ -5,7 +5,7 @@
# venv is created in this directory. # venv is created in this directory.
# check if we are really in the ozone-mapping directory # check if we are really in the ozone-mapping directory
S="ozone-mapping" S="aq-bench"
if [[ $(pwd) == *$S ]] if [[ $(pwd) == *$S ]]
then then
echo "Prepare..." echo "Prepare..."
......
...@@ -419,6 +419,43 @@ class MetricsRow(): ...@@ -419,6 +419,43 @@ class MetricsRow():
+ ' ' + print_metric + ': ' + str(self.row[print_metric])) + ' ' + print_metric + ': ' + str(self.row[print_metric]))
def data_capture():
"""
A simple function to look at the data capture of our metrics.
"""
import pdb
# df = pd.read_csv(resources_dir+'yearly_metrics.csv')
# df['hourly_samples'] = [0] * len(df)
# df['capture'] = [0] * len(df)
df = pd.read_csv(resources_dir+'intermediate_at_cap5500.csv')
for idx, row in df.iterrows():
if idx > 5500:
id_tuple = row['o3_series_id']
id_string_list = [str(id_) for id_ in eval(id_tuple)]
query = f"""
SELECT
datetime, value
FROM o3_hourly
WHERE id IN ({','.join(id_string_list)})
AND datetime between '2010-01-01 00:00:00'
AND '2014-12-31 23:59:59';
"""
result = query_db(query)
result.drop_duplicates(subset='datetime', inplace=True,
ignore_index=True)
count = len(result)
df.loc[idx, 'hourly_samples'] = count
df.loc[idx, 'capture'] = count / 43824
print(count, count/43824)
if (idx > 1) and (idx % 500 == 0):
df.to_csv(resources_dir+f'intermediate_at_cap{idx}.csv',
index=False)
df.to_csv(resources_dir+f'yearly_metrics_cap.csv',
index=False)
pdb.set_trace()
def full_aqbench(): def full_aqbench():
""" """
start one retrieval. start one retrieval.
...@@ -458,4 +495,5 @@ if __name__ == '__main__': ...@@ -458,4 +495,5 @@ if __name__ == '__main__':
logging.StreamHandler()]) logging.StreamHandler()])
# start retrieval # start retrieval
full_aqbench() # full_aqbench()
data_capture()
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