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Merge branch 'develop' into feature/embeddedvideo

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This commit is contained in:
Sander Roosendaal
2019-11-08 15:50:43 +01:00
parent d0ffdf94e7 c6c7f85bb3
commit f05f596866
4 changed files with 289 additions and 275 deletions
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8
rowers/dataprep.py
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@@ -2564,9 +2564,11 @@ def dataprep(rowdatadf, id=0, bands=True, barchart=True, otwpower=True,
if id != 0: if id != 0:
data['workoutid'] = id data['workoutid'] = id
data.fillna(0,inplace=True) data.fillna(0,inplace=True)
data = data.astype( for k, v in dtypes.items():
dtype=dtypes, try:
) data[k] = data[k].astype(v)
except KeyError:
pass
filename = 'media/strokedata_{id}.parquet.gz'.format(id=id) filename = 'media/strokedata_{id}.parquet.gz'.format(id=id)

8
rowers/dataprepnodjango.py
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@@ -1254,7 +1254,13 @@ def dataprep(rowdatadf,id=0,bands=True,barchart=True,otwpower=True,
# write data if id given # write data if id given
if id != 0: if id != 0:
data['workoutid'] = id data['workoutid'] = id
data = data.astype(dtype=dtypes) data.fillna(0,inplace=True)
for k, v in dtypes.items():
try:
data[k] = data[k].astype(v)
except KeyError:
pass
filename = 'media/strokedata_{id}.parquet.gz'.format(id=id) filename = 'media/strokedata_{id}.parquet.gz'.format(id=id)
df = dd.from_pandas(data,npartitions=1) df = dd.from_pandas(data,npartitions=1)
df.to_parquet(filename,engine='fastparquet',compression='GZIP') df.to_parquet(filename,engine='fastparquet',compression='GZIP')

521
rowers/views/analysisviews.py
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File diff suppressed because it is too large Load Diff

27
rowers/views/workoutviews.py
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@@ -2796,18 +2796,21 @@ def workout_stats_view(request,id=0,message="",successmessage=""):
pass pass
for field,verbosename in fielddict.items(): for field,verbosename in fielddict.items():
thedict = { try:
'mean':datadf[field].mean(), thedict = {
'wmean': wavg(datadf, field, 'deltat'), 'mean':datadf[field].mean(),
'min': datadf[field].min(), 'wmean': wavg(datadf, field, 'deltat'),
'std': datadf[field].std(), 'min': datadf[field].min(),
'max': datadf[field].max(), 'std': datadf[field].std(),
'median': datadf[field].median(), 'max': datadf[field].max(),
'firstq':datadf[field].quantile(q=0.25), 'median': datadf[field].median(),
'thirdq':datadf[field].quantile(q=0.75), 'firstq':datadf[field].quantile(q=0.25),
'verbosename':verbosename, 'thirdq':datadf[field].quantile(q=0.75),
} 'verbosename':verbosename,
stats[field] = thedict }
stats[field] = thedict
except KeyError:
pass
# Create a dict with correlation values # Create a dict with correlation values
cor = datadf.corr(method='spearman') cor = datadf.corr(method='spearman')