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some warnings

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This commit is contained in:
Sander Roosendaal
2021-04-27 15:02:30 +02:00
parent b4ed7a0a6b
commit 6f55a975c1
11 changed files with 63 additions and 51 deletions
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9
rowers/c2stuff.py
View File

@@ -604,15 +604,18 @@ def createc2workoutdata(w):
try:
averagehr = int(row.df[' HRCur (bpm)'].mean())
maxhr = int(row.df[' HRCur (bpm)'].max())
except ValueError: # pragma: no cover
except (ValueError,KeyError): # pragma: no cover
averagehr = 0
maxhr = 0
# Calculate intervalstats
itime, idist, itype = row.intervalstats_values()
lapnames = row.df[' lapIdx'].unique()
try:
lapnames = row.df[' lapIdx'].unique()
except KeyError:
lapnames = range(len(itime))
nrintervals = len(itime)
if len(lapnames != nrintervals):
if len(lapnames) != nrintervals:
newlapnames = []
for name in lapnames:
newlapnames += [name,name]

36
rowers/dataprep.py
View File

@@ -265,7 +265,7 @@ def get_latlon(id):
rowdata = rdata(w.csvfilename)
if rowdata.df.empty: # pragma: no cover
return [pd.Series([]), pd.Series([])]
return [pd.Series([],dtype='float'), pd.Series([],dtype='float')]
try:
try:
@@ -276,9 +276,9 @@ def get_latlon(id):
longitude = 0 * rowdata.df.loc[:, 'TimeStamp (sec)']
return [latitude, longitude]
except AttributeError: # pragma: no cover
return [pd.Series([]), pd.Series([])]
return [pd.Series([],dtype='float'), pd.Series([],dtype='float')]
return [pd.Series([]), pd.Series([])] # pragma: no cover
return [pd.Series([],dtype='float'), pd.Series([],dtype='float')] # pragma: no cover
def get_latlon_time(id):
try:
@@ -290,7 +290,7 @@ def get_latlon_time(id):
rowdata = rdata(w.csvfilename)
if rowdata.df.empty: # pragma: no cover
return [pd.Series([]), pd.Series([])]
return [pd.Series([],dtype='float'), pd.Series([],dtype='float')]
try:
try:
@@ -1152,8 +1152,8 @@ def calculate_goldmedalstandard(rower,workout,recurrance=True):
job = myqueue(queuelow,handle_getagegrouprecords,
jsondf,distances,durations,age,rower.sex,rower.weightcategory)
wcpower = pd.Series(wcpower)
wcdurations = pd.Series(wcdurations)
wcpower = pd.Series(wcpower,dtype='float')
wcdurations = pd.Series(wcdurations,dtype='float')
fitfunc = lambda pars,x: pars[0]/(1+(x/pars[2])) + pars[1]/(1+(x/pars[3]))
errfunc = lambda pars,x,y: fitfunc(pars,x)-y
@@ -1203,14 +1203,14 @@ def fetchcp_new(rower,workouts):
if len(data) == 0:
return pd.Series(),pd.Series(),0,pd.Series(),pd.Series()
return pd.Series(dtype='float'),pd.Series(dtype='float'),0,pd.Series(dtype='float'),pd.Series(dtype='float')
if len(data)>1:
df = pd.concat(data,axis=0)
try:
df = df[df['cp'] == df.groupby(['delta'])['cp'].transform('max')]
except KeyError: # pragma: no cover
return pd.Series(),pd.Series(),0,pd.Series(),pd.Series()
return pd.Series(dtype='float'),pd.Series(dtype='float'),0,pd.Series(dtype='float'),pd.Series(dtype='float')
df = df.sort_values(['delta']).reset_index()
@@ -1224,13 +1224,13 @@ def setcp(workout,background=False,recurrance=True):
try:
if strokesdf['power'].std()==0:
return pd.DataFrame(),pd.Series(),pd.Series()
return pd.DataFrame(),pd.Series(dtype='float'),pd.Series(dtype='float')
except KeyError:
return pd.DataFrame(),pd.Series(),pd.Series()
return pd.DataFrame(),pd.Series(dtype='float'),pd.Series(dtype='float')
if background: # pragma: no cover
job = myqueue(queuelow,handle_setcp,strokesdf,filename,workout.id)
return pd.DataFrame({'delta':[],'cp':[]}),pd.Series(),pd.Series()
return pd.DataFrame({'delta':[],'cp':[]}),pd.Series(dtype='float'),pd.Series(dtype='float')
if not strokesdf.empty:
totaltime = strokesdf['time'].max()
@@ -1261,7 +1261,7 @@ def setcp(workout,background=False,recurrance=True):
workout.save()
return df,delta,cpvalues
return pd.DataFrame({'delta':[],'cp':[]}),pd.Series(),pd.Series()
return pd.DataFrame({'delta':[],'cp':[]}),pd.Series(dtype='float'),pd.Series(dtype='float')
def update_rolling_cp(r,types,mode='water'):
firstdate = datetime.date.today()-datetime.timedelta(days=r.cprange)
@@ -1315,20 +1315,20 @@ def fetchcp(rower,theworkouts,table='cpdata'): # pragma: no cover
avgpower2 = {}
for id in theids:
avgpower2[id] = 0
return pd.Series([]),pd.Series([]),avgpower2
return pd.Series([],dtype='float'),pd.Series([],dtype='float'),avgpower2
try:
dfgrouped = df.groupby(['workoutid'])
except KeyError:
avgpower2 = {}
return pd.Series([]),pd.Series([]),avgpower2
return pd.Series([],dtype='float'),pd.Series([],dtype='float'),avgpower2
try:
avgpower2 = dict(dfgrouped.mean()['power'].astype(int))
except KeyError:
avgpower2 = {}
for id in theids:
avgpower2[id] = 0
return pd.Series([]),pd.Series([]),avgpower2
return pd.Series([],dtype='float'),pd.Series([],dtype='float'),avgpower2
cpdf = getcpdata_sql(rower.id,table=table)
@@ -1341,10 +1341,10 @@ def fetchcp(rower,theworkouts,table='cpdata'): # pragma: no cover
theids,
table=table)
return pd.Series([]),pd.Series([]),avgpower2
return pd.Series([],dtype='float'),pd.Series([],dtype='float'),avgpower2
return pd.Series([]),pd.Series([]),avgpower2
return pd.Series([],dtype='float'),pd.Series([],dtype='float'),avgpower2
# create a new workout from manually entered data
@@ -1631,7 +1631,7 @@ def save_workout_database(f2, r, dosmooth=True, workouttype='rower',
else: # pragma: no cover
velo2 = velo
velo3 = pd.Series(velo2)
velo3 = pd.Series(velo2,dtype='float')
velo3 = velo3.replace([-np.inf, np.inf], np.nan)
velo3 = velo3.fillna(method='ffill')

2
rowers/dataprepnodjango.py
View File

@@ -676,7 +676,7 @@ def update_agegroup_db(age,sex,weightcategory,wcdurations,wcpower,
engine.dispose()
def updatecpdata_sql(rower_id,delta,cp,table='cpdata',distance=pd.Series([]),debug=False):
def updatecpdata_sql(rower_id,delta,cp,table='cpdata',distance=pd.Series([],dtype='float'),debug=False):
deletecpdata_sql(rower_id,table=table,debug=debug)
df = pd.DataFrame(
{

22
rowers/datautils.py
View File

@@ -136,7 +136,7 @@ def getlogarr(maxt):
v = 0
res.append(v)
logarr = pd.Series(res)
logarr = pd.Series(res,dtype='float')
logarr.drop_duplicates(keep='first',inplace=True)
logarr = logarr.values
@@ -197,11 +197,11 @@ def getcp_new(dfgrouped,logarr): # pragma: no cover
newt,method='linear',
rescale=True)
tt = pd.Series(newt)
ww = pd.Series(ww)
tt = pd.Series(newt,dtype='float')
ww = pd.Series(ww,dtype='float')
G = pd.Series(ww.cumsum())
G = pd.concat([pd.Series([0]),G])
G = pd.Series(ww.cumsum(),dtype='float')
G = pd.concat([pd.Series([0],dtype='float'),G])
h = np.mgrid[0:len(tt)+1:1,0:len(tt)+1:1]
@@ -321,8 +321,8 @@ def getcp(dfgrouped,logarr):
cpw.append(wmax)
dt = pd.Series(dt)
cpw = pd.Series(cpw)
dt = pd.Series(dt,dtype='float')
cpw = pd.Series(cpw,dtype='float')
if len(dt)>2:
cpvalues = griddata(dt.values,
cpw.values,
@@ -336,8 +336,8 @@ def getcp(dfgrouped,logarr):
delta = pd.Series(delta,name='Delta')
cpvalue = pd.Series(cpvalue,name='CP')
delta = pd.Series(delta,name='Delta',dtype='float')
cpvalue = pd.Series(cpvalue,name='CP',dtype='float')
cpdf = pd.DataFrame({
@@ -410,8 +410,8 @@ def getfastest(df,thevalue,mode='distance'):
dd = griddata(tt.values,
dd.values,newt,method='linear',rescale=True)
tt = pd.Series(newt)
dd = pd.Series(dd)
tt = pd.Series(newt,dtype='float')
dd = pd.Series(dd,dtype='float')
G = pd.concat([pd.Series([0]),dd])
T = pd.concat([pd.Series([0]),dd])

10
rowers/interactiveplots.py
View File

@@ -836,7 +836,7 @@ def interactive_activitychart2(workouts,startdate,enddate,stack='type',toolbar_l
callback = CustomJS(args={'links':df.link}, code="""
callback = CustomJS(args={'links':df['link']}, code="""
var index = cb_data.source.selected['1d'].indices[0];
console.log(links);
console.log(index);
@@ -3387,8 +3387,8 @@ def interactive_otwcpchart(powerdf,promember=0,rowername="",r=None,cpfit='data',
urls = powerdf['url']
# add world class
wcpower = pd.Series(wcpower)
wcdurations = pd.Series(wcdurations)
wcpower = pd.Series(wcpower,dtype='float')
wcdurations = pd.Series(wcdurations,dtype='float')
# fitting WC data to three parameter CP model
@@ -3683,8 +3683,8 @@ def interactive_cpchart(rower,thedistances,thesecs,theavpower,
errfunc = lambda pars,x,y: fitfunc(pars,x)-y
# p0 = [500,350,10,8000]
wcpower = pd.Series(wcpower)
wcdurations = pd.Series(wcdurations)
wcpower = pd.Series(wcpower,dtype='float')
wcdurations = pd.Series(wcdurations,dtype='float')
# fitting WC data to three parameter CP model
if len(wcdurations)>=4:

17
rowers/runkeeperstuff.py
View File

@@ -126,16 +126,23 @@ def createrunkeeperworkoutdata(w):
except: # pragma: no cover
return 0
averagehr = int(row.df[' HRCur (bpm)'].mean())
maxhr = int(row.df[' HRCur (bpm)'].max())
try:
averagehr = int(row.df[' HRCur (bpm)'].mean())
maxhr = int(row.df[' HRCur (bpm)'].max())
except KeyError:
averagehr = 0
maxhr = 0
duration = w.duration.hour*3600
duration += w.duration.minute*60
duration += w.duration.second
duration += +1.0e-6*w.duration.microsecond
# adding diff, trying to see if this is valid
#t = row.df.ix[:,'TimeStamp (sec)'].values-10*row.df.ix[0,'TimeStamp (sec)']
t = row.df.loc[:,'TimeStamp (sec)'].values-row.df.loc[:,'TimeStamp (sec)'].iloc[0]
try:
t = row.df.loc[:,'TimeStamp (sec)'].values-row.df.loc[:,'TimeStamp (sec)'].iloc[0]
except KeyError: # pragma: no cover
return pd.DataFrame()
t[0] = t[1]
d = row.df.loc[:,'cum_dist'].values

4
rowers/tests/statements.py
View File

@@ -16,7 +16,9 @@ except NameError:
import pytest
import warnings
#warnings.filterwarnings("error",category=UserWarning)
#warnings.filterwarnings("error",
# category=DeprecationWarning
# )
pytestmark = pytest.mark.django_db

2
rowers/tests/test_analysis.py
View File

@@ -176,7 +176,7 @@ class PlannedSessionTests(TestCase):
d1 = startdate.strftime("%Y%m%d"),
d2 = enddate.strftime("%Y%m%d"),
)
self.assertEquals(
self.assertEqual(
response.get('Content-Disposition'),
'attachment; filename="{name}"'.format(name=filename)
)

2
rowers/tests/test_api.py
View File

@@ -111,7 +111,7 @@ class OwnApi(TestCase):
login = self.c.login(username=self.u.username, password=self.password)
self.assertTrue(login)
w = self.user_workouts[0]
w = self.user_workouts[1]
url = reverse('strokedataform_v2',kwargs={'id':encoder.encode_hex(w.id)})
response = self.c.get(url)

4
rowers/views/analysisviews.py
View File

@@ -1101,7 +1101,7 @@ def performancemanager_view(request,userid=0,mode='rower',
showtests = True,
)
ids = pd.Series(ids).dropna().values
ids = pd.Series(ids,dtype='int').dropna().values
bestworkouts = Workout.objects.filter(id__in=ids).order_by('-date')
@@ -1411,7 +1411,7 @@ def rankings_view2(request,userid=0,
p1 = res[4]
message = res[5]
try:
testcalc = pd.Series(res[6])*3
testcalc = pd.Series(res[6],dtype='float')*3
except TypeError: # pragma: no cover
age = 0

6
rowsandall_app/settings.py
View File

@@ -60,8 +60,8 @@ INSTALLED_APPS = [
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'suit',
'suit_rq',
# 'suit',
# 'suit_rq',
'leaflet',
'django_rq',
# 'django_rq_dashboard',
@@ -98,7 +98,7 @@ MIDDLEWARE = [
'django.middleware.csrf.CsrfViewMiddleware',
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.locale.LocaleMiddleware',
# 'django.middleware.locale.LocaleMiddleware',
'corsheaders.middleware.CorsMiddleware',
'django.middleware.common.CommonMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',