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alerts, analysis, api tested

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This commit is contained in:
Sander Roosendaal
2024-04-21 10:56:37 +02:00
parent 85bd89d3d2
commit 409f4aff63
8 changed files with 124 additions and 117 deletions
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4
rowers/views/analysisviews.py
View File

@@ -612,7 +612,7 @@ def histodata(workouts, options):
if savedata: # pragma: no cover
workstrokesonly = not includereststrokes
ids = [int(w.id) for w in workouts]
df = dataprep.getsmallrowdata_db([plotfield], ids=ids,
df = dataprep.read_data([plotfield], ids=ids,
workstrokesonly=workstrokesonly,
doclean=True,
)
@@ -885,7 +885,7 @@ def comparisondata(workouts, options):
'time', 'pace', 'workoutstate',
'workoutid']
df = dataprep.getsmallrowdata_db(columns, ids=ids,
df = dataprep.read_data(columns, ids=ids,
workstrokesonly=workstrokesonly,
doclean=True,
)

121
rowers/views/apiviews.py
View File

@@ -68,102 +68,102 @@ def strokedataform(request, id=0):
def api_get_dataframe(startdatetime, df):
try:
time = df['time']/1.e3
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
try:
time = df['t']/10.
except KeyError:
return 400, "Missing time", pd.DataFrame()
except (KeyError, ColumnNotFoundError):
return 400, "Missing time", pl.DataFrame()
try:
spm = df['spm']
except KeyError: # pragma: no cover
return 400, "Missing spm", pd.DataFrame()
except (KeyError, ColumnNotFoundError): # pragma: no cover
return 400, "Missing spm", pl.DataFrame()
try:
distance = df['distance']
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
try:
distance = df['d']/10.
except KeyError:
return 400, "Missing distance", pd.DataFrame()
except (KeyError, ColumnNotFoundError):
return 400, "Missing distance", pl.DataFrame()
try:
pace = df['pace']/1.e3
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
try:
pace = df['p']/10.
except KeyError:
return 400, "Missing pace", pd.DataFrame()
except (KeyError, ColumnNotFoundError):
return 400, "Missing pace", pl.DataFrame()
try:
power = df['power']
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
power = 0*time
try:
drivelength = df['drivelength']
except KeyError:
except (KeyError, ColumnNotFoundError):
drivelength = 0*time
try:
dragfactor = df['dragfactor']
except KeyError:
except (KeyError, ColumnNotFoundError):
dragfactor = 0*time
try:
drivetime = df['drivetime']
except KeyError:
except (KeyError, ColumnNotFoundError):
drivetime = 0*time
try:
strokerecoverytime = df['strokerecoverytime']
except KeyError:
except (KeyError, ColumnNotFoundError):
strokerecoverytime = 0*time
try:
averagedriveforce = df['averagedriveforce']
except KeyError:
except (KeyError, ColumnNotFoundError):
averagedriveforce = 0*time
try:
peakdriveforce = df['peakdriveforce']
except KeyError:
except (KeyError, ColumnNotFoundError):
peakdriveforce = 0*time
try:
wash = df['wash']
except KeyError:
except (KeyError, ColumnNotFoundError):
wash = 0*time
try:
catch = df['catch']
except KeyError:
except (KeyError, ColumnNotFoundError):
catch = 0*time
try:
finish = df['finish']
except KeyError:
except (KeyError, ColumnNotFoundError):
finish = 0*time
try:
peakforceangle = df['peakforceangle']
except KeyError:
except (KeyError, ColumnNotFoundError):
peakforceangle = 0*time
try:
driveenergy = df['driveenergy']
except KeyError:
except (KeyError, ColumnNotFoundError):
driveenergy = 60.*power/spm
try:
slip = df['slip']
except KeyError:
except (KeyError, ColumnNotFoundError):
slip = 0*time
try:
lapidx = df['lapidx']
except KeyError:
except (KeyError, ColumnNotFoundError):
lapidx = 0*time
try:
hr = df['hr']
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
hr = 0*df['time']
try:
latitude = df['latitude']
except KeyError:
except (KeyError, ColumnNotFoundError):
latitude = 0*df['time']
try:
longitude = df['longitude']
except KeyError:
except (KeyError, ColumnNotFoundError):
longitude = 0*df['time']
starttime = totimestamp(startdatetime)+time[0]
@@ -171,7 +171,7 @@ def api_get_dataframe(startdatetime, df):
dologging('apilog.log',"(strokedatajson_v2/3 POST - data parsed)")
data = pd.DataFrame({'TimeStamp (sec)': unixtime,
data = pl.DataFrame({'TimeStamp (sec)': unixtime,
' Horizontal (meters)': distance,
' Cadence (stokes/min)': spm,
' HRCur (bpm)': hr,
@@ -522,7 +522,7 @@ def strokedatajson_v3(request):
title = request.data.get('name','')
try:
elapsedTime = request.data['elapsedTime']
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
try:
duration = request.data['duration']
try:
@@ -534,7 +534,7 @@ def strokedatajson_v3(request):
return HttpResponse("Missing Elapsed Time", status=400)
try:
totalDistance = request.data['distance']
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
return HttpResponse("Missing Total Distance", status=400)
timeZone = request.data.get('timezone','UTC')
workouttype = request.data.get('workouttype','rower')
@@ -552,23 +552,21 @@ def strokedatajson_v3(request):
dologging('apilog.log',totalDistance)
dologging('apilog.log',elapsedTime)
df = pd.DataFrame()
df = pl.DataFrame()
try:
strokes = request.data['strokes']
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
return HttpResponse("No Stroke Data in JSON", status=400)
try:
df = pd.DataFrame(strokes['data'])
except KeyError: # pragma: no cover
df = pl.DataFrame(strokes['data'])
except (KeyError, ColumnNotFoundError): # pragma: no cover
try:
df = pd.DataFrame(request.data['strokedata'])
df = pl.DataFrame(request.data['strokedata'])
except:
return HttpResponse("No JSON Object could be decoded", status=400)
df.index = df.index.astype(int)
df.sort_index(inplace=True)
df = df.sort("time")
status, comment, data = api_get_dataframe(startdatetime, df)
if status != 200: # pragma: no cover
@@ -576,7 +574,8 @@ def strokedatajson_v3(request):
csvfilename = 'media/{code}.csv.gz'.format(code=uuid4().hex[:16])
_ = data.to_csv(csvfilename, index_label='index', compression='gzip')
with gzip.open(csvfilename, 'w') as f:
_ = data.write_csv(f)
duration = datetime.time(0,0,1)
w = Workout(
@@ -667,10 +666,11 @@ def strokedatajson_v2(request, id):
if request.method == 'GET':
columns = ['spm', 'time', 'hr', 'pace', 'power', 'distance']
datadf = dataprep.getsmallrowdata_db(columns, ids=[id])
datadf = dataprep.read_data(columns, ids=[id])
datadf = dataprep.remove_nulls_pl(datadf)
dologging('apilog.log',request.user.username+"(strokedatajson_v2 GET)")
data = datadf.to_json(orient='records')
data = datadf.write_json(row_oriented=True)
data2 = json.loads(data)
data2 = {"data": data2}
@@ -681,28 +681,27 @@ def strokedatajson_v2(request, id):
try:
for d in request.data['data']:
dologging('apilog.log',json.dumps(d))
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
try:
for d in request.data['strokedata']:
dologging('apilog.log',json.dumps(d))
except KeyError:
except (KeyError, ColumnNotFoundError):
dologging('apilog.log','No data in request.data')
checkdata, r = dataprep.getrowdata_db(id=row.id)
if not checkdata.empty: # pragma: no cover
return HttpResponse("Duplicate Error", status=409)
df = pd.DataFrame()
df = pl.DataFrame()
try:
df = pd.DataFrame(request.data['data'])
except KeyError: # pragma: no cover
df = pl.DataFrame(request.data['data'])
except (KeyError, ColumnNotFoundError): # pragma: no cover
try:
df = pd.DataFrame(request.data['strokedata'])
df = pl.DataFrame(request.data['strokedata'])
except:
return HttpResponse("No JSON object could be decoded", status=400)
df.index = df.index.astype(int)
df.sort_index(inplace=True)
df = df.sort("time")
status, comment, data = api_get_dataframe(row.startdatetime, df)
if status != 200: # pragma: no cover
@@ -724,7 +723,8 @@ def strokedatajson_v2(request, id):
row.duplicate = True
row.save()
_ = data.to_csv(csvfilename+'.gz', index_label='index', compression='gzip')
with gzip.open(csvfilename+'.gz', 'w') as f:
_ = data.write_csv(f)
row.csvfilename = csvfilename
row.save()
@@ -796,7 +796,11 @@ def strokedatajson(request, id=0):
if request.method == 'GET':
# currently only returns a subset.
columns = ['spm', 'time', 'hr', 'pace', 'power', 'distance']
datadf = dataprep.getsmallrowdata_db(columns, ids=[id])
datadf = dataprep.read_data(columns, ids=[id])
datadf = dataprep.remove_nulls_pl(datadf)
datadf = datadf.to_pandas()
dologging("apilog.log",request.user.username+"(strokedatajson GET) ")
return JSONResponse(datadf)
@@ -817,14 +821,13 @@ def strokedatajson(request, id=0):
return HttpResponse("No JSON object could be decoded", status=400)
try:
df = pd.DataFrame(strokedata)
df = pl.DataFrame(strokedata)
except ValueError: # pragma: no cover
return HttpResponse("Arrays must all be same length", status=400)
df.index = df.index.astype(int)
df.sort_index(inplace=True)
df = df.sort("time")
try:
time = df['time']/1.e3
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
return HttpResponse("There must be time values", status=400)
aantal = len(time)
pace = df['pace']/1.e3
@@ -863,7 +866,7 @@ def strokedatajson(request, id=0):
dologging("apilog.log",request.user.username+"(POST)")
data = pd.DataFrame({'TimeStamp (sec)': unixtime,
data = pl.DataFrame({'TimeStamp (sec)': unixtime,
' Horizontal (meters)': distance,
' Cadence (stokes/min)': spm,
' HRCur (bpm)': hr,
@@ -890,8 +893,8 @@ def strokedatajson(request, id=0):
timestr = row.startdatetime.strftime("%Y%m%d-%H%M%S")
csvfilename = 'media/Import_'+timestr+'.csv'
res = data.to_csv(csvfilename+'.gz', index_label='index',
compression='gzip')
with gzip.open(csvfilename+'.gz','w') as f:
res = data.write_csv(f)
row.csvfilename = csvfilename
row.save()

7
rowers/views/statements.py
View File

@@ -16,7 +16,7 @@ from rowers.utils import (
from rowers.celery import result as celery_result
from rowers.interactiveplots import *
from scipy.interpolate import griddata
from rowers.dataprep import getsmallrowdata_db, read_data
from rowers.dataprep import getsmallrowdata_pd, read_data
from rowers.dataprep import timedeltaconv
from scipy.special import lambertw
from io import BytesIO
@@ -35,6 +35,7 @@ import threading
import redis
import colorsys
import re
import gzip
import zipfile
import bleach
import arrow
@@ -1345,9 +1346,9 @@ def trydf(df, aantal, column): # pragma: no cover
s = df[column]
if len(s) != aantal:
return np.zeros(aantal)
if not np.issubdtype(s, np.number):
if not s.dtype in pl.NUMERIC_DTYPES:
return np.zeros(aantal)
except KeyError:
except (KeyError, ColumnNotFoundError):
s = np.zeros(aantal)
return s