From 766cea9d737142b8b5c642b4d5e7e5db119ae696 Mon Sep 17 00:00:00 2001 From: Sander Roosendaal Date: Mon, 31 Oct 2022 21:00:35 +0100 Subject: [PATCH 1/2] quiske updates --- rowers/templates/instroke_interactive.html | 1 + 1 file changed, 1 insertion(+) diff --git a/rowers/templates/instroke_interactive.html b/rowers/templates/instroke_interactive.html index cad3bd0e..79f15834 100644 --- a/rowers/templates/instroke_interactive.html +++ b/rowers/templates/instroke_interactive.html @@ -62,6 +62,7 @@ $( function() { range: true, min: 0, max: 60, + step: 0.1, values: [ {{ spm_min }}, {{ spm_max }} ], slide: function( event, ui ) { $( "#amountspm" ).val(ui.values[ 0 ] + " - " + ui.values[ 1 ] ); From de5152fcfcd3280de5b860424fd96c7ccbd42c12 Mon Sep 17 00:00:00 2001 From: Sander Roosendaal Date: Mon, 31 Oct 2022 21:01:23 +0100 Subject: [PATCH 2/2] quiske changes --- rowers/forms.py | 4 ++-- rowers/interactiveplots.py | 3 +++ 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/rowers/forms.py b/rowers/forms.py index 805abc7b..d1e9d116 100644 --- a/rowers/forms.py +++ b/rowers/forms.py @@ -154,8 +154,8 @@ class InstrokeForm(forms.Form): metric = forms.ChoiceField(label='metric',choices=(('a','a'),('b','b'))) individual_curves = forms.BooleanField(label='individual curves',initial=False, required=False) - spm_min = forms.IntegerField(initial=15,label='SPM Min',widget=HiddenInput) - spm_max = forms.IntegerField(initial=45,label='SPM Max',widget=HiddenInput) + spm_min = forms.FloatField(initial=15,label='SPM Min',widget=HiddenInput) + spm_max = forms.FloatField(initial=45,label='SPM Max',widget=HiddenInput) activeminutesmin = forms.FloatField( required=False, initial=0, widget=forms.HiddenInput()) activeminutesmax = forms.FloatField( diff --git a/rowers/interactiveplots.py b/rowers/interactiveplots.py index a239928a..a3dc27bf 100644 --- a/rowers/interactiveplots.py +++ b/rowers/interactiveplots.py @@ -4318,6 +4318,9 @@ def instroke_interactive_chart(df,metric, workout, spm_min, spm_max, df_pos = (df+abs(df))/2. df_min = -(-df+abs(-df))/2. + if df.empty: + return "", "No data in selection" + mean_vals = df.median().replace(0, np.nan) q75 = df_pos.quantile(q=0.75).replace(0,np.nan) q25 = df_pos.quantile(q=0.25).replace(0,np.nan)