sander/rowsandall
Private
Public Access
1
0
Fork 0
Code Activity

first routines with polars

Browse Source
This commit is contained in:
Sander Roosendaal
2024-04-07 19:19:44 +02:00
parent c94da7bd6c
commit 12915ad6b7
3 changed files with 382 additions and 41 deletions
Download Patch File Download Diff File Expand all files Collapse all files

53
rowers/interactiveplots.py
View File

@@ -18,8 +18,10 @@ import rowers.metrics as metrics
import rowers.dataprep as dataprep
from rowers.dataprep import rdata
import rowers.utils as utils
import polars as pl
from rowers.rower_rules import ispromember
from polars.exceptions import ColumnNotFoundError
from scipy.interpolate import griddata
from scipy.signal import savgol_filter
@@ -2306,29 +2308,30 @@ def interactive_cum_flex_chart2(theworkouts, promember=0,
columns = [name for name, d in metrics.rowingmetrics]
columns_basic = [name for name, d in metrics.rowingmetrics if d['group'] == 'basic']
columns = columns + ['spm', 'driveenergy', 'distance']
columns_basic = columns_basic + ['spm', 'driveenergy', 'distance']
columns = columns + ['spm', 'driveenergy', 'distance' ,'workoutstate']
columns_basic = columns_basic + ['spm', 'driveenergy', 'distance', 'workoutstate']
datadf = pd.DataFrame()
if promember:
datadf = dataprep.getsmallrowdata_db(columns, ids=ids, doclean=True,
datadf = dataprep.getsmallrowdata_pl(columns, ids=ids, doclean=True,
workstrokesonly=workstrokesonly, for_chart=True)
else:
datadf = dataprep.getsmallrowdata_db(columns_basic, ids=ids, doclean=True,
datadf = dataprep.getsmallrowdata_pl(columns_basic, ids=ids, doclean=True,
workstrokesonly=workstrokesonly, for_chart=True)
try:
_ = datadf[yparam2]
except KeyError: # pragma: no cover
except (KeyError, ColumnNotFoundError): # pragma: no cover
yparam2 = 'None'
try:
_ = datadf[yparam1]
except KeyError:
except (KeyError, ColumnNotFoundError):
yparam1 = 'None'
datadf.dropna(axis=1, how='all', inplace=True)
datadf.dropna(axis=0, how='any', inplace=True)
datadf.drop_nulls()
#datadf.dropna(axis=1, how='all', inplace=True)
#datadf.dropna(axis=0, how='any', inplace=True)
# test if we have drive energy
try: # pragma: no cover
@@ -2347,42 +2350,43 @@ def interactive_cum_flex_chart2(theworkouts, promember=0,
yparamname2 = axlabels[yparam2]
# check if dataframe not empty
if datadf.empty: # pragma: no cover
if datadf.is_empty(): # pragma: no cover
return ['', '<p>No non-zero data in selection</p>', '', '']
try:
datadf['x1'] = datadf.loc[:, xparam]
datadf = datadf.with_columns(pl.col(xparam).alias("x1"))
except KeyError: # pragma: no cover
try:
datadf['x1'] = datadf['distance']
datadf = datadf.with_columns(pl.col("distance").alias("x1"))
except KeyError:
try:
datadf['x1'] = datadf['time']
datadf = datadf.with_columns(pl.col('time').alias("x1"))
except KeyError: # pragma: no cover
return ['', '<p>No non-zero data in selection</p>', '', '']
try:
datadf['y1'] = datadf.loc[:, yparam1]
datadf = datadf.with_columns(pl.col(yparam1).alias("y1"))
except KeyError:
try:
datadf['y1'] = datadf['pace']
datadf = datadf.with_columns(pl.col('pace').alias("y1"))
except KeyError: # pragma: no cover
return ['', '<p>No non-zero data in selection</p>', '', '']
if yparam2 != 'None':
try:
datadf['y2'] = datadf.loc[:, yparam2]
datadf = datadf.with_columns(pl.col(yparam2).alias("y2"))
except KeyError: # pragma: no cover
datadf['y2'] = datadf['y1']
datadf = datadf.with_columns(pl.col("y1").alias("y2"))
else: # pragma: no cover
datadf['y2'] = datadf['y1']
datadf = datadf.with_columns(pl.col("y1").alias("y2"))
datadf['xname'] = axlabels[xparam]
datadf['yname1'] = axlabels[yparam1]
datadf = datadf.with_columns(xname = pl.lit(axlabels[xparam]))
datadf = datadf.with_columns(yname1 = pl.lit(axlabels[yparam1]))
if yparam2 != 'None':
datadf['yname2'] = axlabels[yparam2]
datadf = datadf.with_columns(yname2 = pl.lit(axlabels[yparam2]))
else: # pragma: no cover
datadf['yname2'] = axlabels[yparam1]
datadf = datadf.with_columns(yname2 = pl.lit(axlabels[yparam1]))
def func(x, a, b):
return a*x+b
@@ -2392,11 +2396,12 @@ def interactive_cum_flex_chart2(theworkouts, promember=0,
try:
popt, pcov = optimize.curve_fit(func, x1, y1)
ytrend = func(x1, popt[0], popt[1])
datadf['ytrend'] = ytrend
datadf= datadf.with_columns(ytrend = ytrend)
except TypeError:
datadf['ytrend'] = y1
datadf = datadf.with_columns(ytrend = y1)
data_dict = datadf.to_dict("records")
data_dict = datadf.to_dicts()
metrics_list = [{'name': name, 'rowingmetrics':d } for name, d in metrics.rowingmetrics]