otw chart pandas to polars

rowers/datautils.py

@@ -81,8 +81,8 @@ def cpfit(powerdf, fraclimit=0.0001, nmax=1000):
 
     p1 = p0
 
-    thesecs = powerdf['Delta']
-    theavpower = powerdf['CP']
+    thesecs = powerdf['Delta'].to_numpy()
+    theavpower = powerdf['CP'].to_numpy()
 
     if len(thesecs) >= 4:
         try:
@@ -102,7 +102,7 @@ def cpfit(powerdf, fraclimit=0.0001, nmax=1000):
     fitpower = fitfunc(p1, fitt)
 
     fitpoints = fitfunc(p1, thesecs)
-    fitpoints0 = fitpoints.copy()
+    fitpoints0 = fitpoints
     dd = fitpoints-theavpower
 
     ddmin = dd.min()

rowers/interactiveplots.py

@@ -996,7 +996,8 @@ def interactive_otwcpchart(powerdf, promember=0, rowername="", r=None,
                            title='', type='water',
                            wcpower=[], wcdurations=[], cpoverlay=False):
 
-    powerdf2 = powerdf[~(powerdf == 0).any(axis=1)].copy()
+    powerdf2 = powerdf.filter(pl.col("Delta") > 0, pl.col("CP") > 0)
+
     # plot tools
     if (promember == 1):  # pragma: no cover
         TOOLS = 'save,pan,box_zoom,wheel_zoom,reset,tap,hover,crosshair'
@@ -1006,11 +1007,9 @@ def interactive_otwcpchart(powerdf, promember=0, rowername="", r=None,
     x_axis_type = 'log'
 
     deltas = powerdf2['Delta'].apply(lambda x: timedeltaconv(x))
-    powerdf2['ftime'] = deltas.apply(lambda x: strfdelta(x))
-    powerdf2['Deltaminutes'] = powerdf2['Delta']/60.
-
-    source = ColumnDataSource(
-        data=powerdf2
+    powerdf2 = powerdf2.with_columns(
+        ftime = deltas.apply(lambda x: strfdelta(x)),
+        Deltaminutes = pl.col("Delta")/60.
     )
 
     # there is no Paul's law for OTW
@@ -1071,7 +1070,7 @@ def interactive_otwcpchart(powerdf, promember=0, rowername="", r=None,
         fitpoweraverage = 0*fitpower
 
 
-    fit_data =  pd.DataFrame(dict(
+    fit_data =  pl.DataFrame(dict(
             CP=fitpower,
             CPmax=ratio*fitpower,
             duration=fitt/60.,
@@ -1085,13 +1084,12 @@ def interactive_otwcpchart(powerdf, promember=0, rowername="", r=None,
             #            url = urls,
         ))
 
-
     if not title:
         title = "Critical Power for "+rowername
     
     chart_dict = {
-        'data': powerdf2.to_dict("records"),
-        'fitdata': fit_data.to_dict("records"),
+        'data': powerdf2.to_dicts(),
+        'fitdata': fit_data.to_dicts(),
         'title': title,
     }
 

rowers/views/analysisviews.py

@@ -639,7 +639,7 @@ def cpdata(workouts, options):
     delta, cpvalue, avgpower, workoutnames, urls = dataprep.fetchcp_new(
         r, workouts)
 
-    powerdf = pd.DataFrame({
+    powerdf = pl.DataFrame({
         'Delta': delta,
         'CP': cpvalue,
         'workout': workoutnames,
@@ -648,16 +648,17 @@ def cpdata(workouts, options):
 
     savedata = options.get('savedata',False)
     if savedata: # pragma: no cover
-        return powerdf
+        return powerdf.to_pandas()
 
-    if powerdf.empty:  # pragma: no cover
+    if powerdf.is_empty():  # pragma: no cover
         return('', '<p>No valid data found</p>')
 
 
-    powerdf = powerdf[powerdf['CP'] > 0]
-    powerdf.dropna(axis=0, inplace=True)
-    powerdf.sort_values(['Delta', 'CP'], ascending=[1, 0], inplace=True)
-    powerdf.drop_duplicates(subset='Delta', keep='first', inplace=True)
+    powerdf = powerdf.lazy().filter(pl.col("CP")>0)
+    powerdf = powerdf.sort(["Delta", "CP"], descending=[False, True])
+    powerdf = powerdf.unique(subset="Delta", keep="first")
+    powerdf = powerdf.fill_nan(None).drop_nulls()
+    powerdf = powerdf.collect()
 
     rowername = r.user.first_name+" "+r.user.last_name