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

Small necessary changes in Location Doryab Features.

pull/95/head
nikunjgoel95 2020-08-05 13:39:37 -04:00
parent 81a4f23310
commit 2859a53202
1 changed files with 8 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
src/features/location_doryab/location_base.py
View File

@ -99,11 +99,11 @@ def base_location_features(location_data, day_segment, requested_features, dbsca
preComputedmaxminCluster = pd.DataFrame()
for localDate in newLocationData['local_date'].unique():
smax, smin, sstd,smean = len_stay_at_clusters_in_minutes(newLocationData[newLocationData['local_date']==localDate])
preComputedmaxminCluster.loc[localDate,"location_" + day_segment + "_maxlengthstayatclusters"] = smax * sampling_frequency
preComputedmaxminCluster.loc[localDate,"location_" + day_segment + "_minlengthstayatclusters"] = smin * sampling_frequency
preComputedmaxminCluster.loc[localDate,"location_" + day_segment + "_stdlengthstayatclusters"] = sstd * sampling_frequency
preComputedmaxminCluster.loc[localDate,"location_" + day_segment + "_meanlengthstayatclusters"] = smean * sampling_frequency
smax, smin, sstd,smean = len_stay_at_clusters_in_minutes(newLocationData[newLocationData['local_date']==localDate],sampling_frequency)
preComputedmaxminCluster.loc[localDate,"location_" + day_segment + "_maxlengthstayatclusters"] = smax
preComputedmaxminCluster.loc[localDate,"location_" + day_segment + "_minlengthstayatclusters"] = smin
preComputedmaxminCluster.loc[localDate,"location_" + day_segment + "_stdlengthstayatclusters"] = sstd
preComputedmaxminCluster.loc[localDate,"location_" + day_segment + "_meanlengthstayatclusters"] = smean
if "maxlengthstayatclusters" in features_to_compute:
for localDate in newLocationData['local_date'].unique():
@ -355,7 +355,7 @@ def time_at_topn_clusters_in_group(locationData,n,sampling_frequency): # releva
if len(sorted_valcounts) >= n:
topn = sorted_valcounts[n-1]
topn_time = topn[1]
topn_time = topn[1] * sampling_frequency
else:
topn_time = None
@ -380,7 +380,7 @@ def moving_time_percent(locationData):
# print(numtotal)
return (float(nummoving) / numtotal)
def len_stay_at_clusters_in_minutes(locationData):
def len_stay_at_clusters_in_minutes(locationData,sampling_frequency):
if locationData is None or len(locationData) == 0:
return (None, None, None,None)
@ -403,7 +403,7 @@ def len_stay_at_clusters_in_minutes(locationData):
count = 0 + 1
if count > 0: # in case of no transition
lenstays.append(count)
lenstays = np.array(lenstays)
lenstays = np.array(lenstays) * sampling_frequency
if len(lenstays) > 0:
smax = np.max(lenstays)