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adding critical stroke rate chart

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This commit is contained in:
Sander Roosendaal
2025-02-04 20:00:44 +01:00
parent 8f7060ead8
commit 03f68aa72e
9 changed files with 364 additions and 76 deletions
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32
rowers/dataprep.py
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@@ -553,7 +553,10 @@ def setcp(workout, background=False, recurrance=True):
# check dts
tarr = datautils.getlogarr(4000)
if df['delta'][0] in tarr:
return(df, df['delta'], df['cp'])
try:
return(df, df['delta'], df['cp'], df['cr'])
except KeyError:
return(df, df['delta'], df['cp'], 0*df['cp'])
except Exception as e:
try:
os.remove(filename)
@@ -565,7 +568,7 @@ def setcp(workout, background=False, recurrance=True):
strokesdf = remove_nulls_pl(strokesdf)
if strokesdf.is_empty():
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
totaltime = strokesdf['time'].max()
maxt = totaltime/1000.
@@ -580,7 +583,7 @@ def setcp(workout, background=False, recurrance=True):
elif os.path.exists(csvfilename+'.gz'): # pragma: no cover
csvfile = csvfilename+'.gz'
else: # pragma: no cover
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
csvfile = os.path.abspath(csvfile)
with grpc.insecure_channel(
@@ -593,7 +596,7 @@ def setcp(workout, background=False, recurrance=True):
grpc.channel_ready_future(channel).result(timeout=10)
except grpc.FutureTimeoutError: # pragma: no cover
dologging('metrics.log','grpc channel time out in setcp')
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr':[]}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
stub = metrics_pb2_grpc.MetricsStub(channel)
req = metrics_pb2.CPRequest(filename = csvfile, filetype = "CSV", tarr = logarr)
@@ -602,16 +605,18 @@ def setcp(workout, background=False, recurrance=True):
response = stub.GetCP(req, timeout=60)
except Exception as e:
dologging('metrics.log', traceback.format_exc())
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
delta = pl.Series(np.array(response.delta))
cpvalues = pl.Series(np.array(response.power))
powermean = response.avgpower
spmvalues = pl.Series(np.array(response.spm))
try:
df = pl.DataFrame({
'delta': delta,
'cp': cpvalues,
'cr': spmvalues,
'id': workout.id,
})
@@ -620,7 +625,7 @@ def setcp(workout, background=False, recurrance=True):
except Exception as e:
dologging("metrics.log", "setcp: "+ str(e))
return pl.DataFrame({'delta': [], 'cp': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.DataFrame({'delta': [], 'cp': [], 'cr': []}), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
#df.to_parquet(filename, engine='fastparquet', compression='GZIP')
@@ -631,7 +636,7 @@ def setcp(workout, background=False, recurrance=True):
workout.goldmedalduration = goldmedalduration
workout.save()
return df, delta, cpvalues
return df, delta, cpvalues, spmvalues # pragma: no cover
@@ -772,7 +777,7 @@ def fetchcp_new(rower, workouts):
data = []
for workout in workouts:
df, delta, cpvalues = setcp(workout)
df, delta, cpvalues, cpvalues_spm = setcp(workout)
df = df.drop('id')
df = df.with_columns((pl.lit(str(workout))).alias("workout"))
df = df.with_columns((pl.lit(workout.url())).alias("url"))
@@ -780,7 +785,7 @@ def fetchcp_new(rower, workouts):
data.append(df)
if len(data) == 0:
return pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), 0, pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), 0, pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
if len(data) > 1:
df = pl.concat(data)
@@ -791,11 +796,16 @@ def fetchcp_new(rower, workouts):
pl.all().sort_by('cp').last(),
])
except (KeyError, ColumnNotFoundError): # pragma: no cover
return pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), 0, pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
return pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64), 0, pl.Series(dtype=pl.Float64), pl.Series(dtype=pl.Float64)
df = df.filter(pl.col("cp")>20)
return df['delta'], df['cp'], 0, df['workout'], df['url']
try:
testje = df['cr']
except KeyError:
return df['delta'], df['cp'], 0*df['cp'], 0, df['workout'], df['url']
return df['delta'], df['cp'], df['cr'], 0, df['workout'], df['url']