Question Types#

Question Implementation

Each question type is implemented as a class the class also specifies the HTML/js templates to use for that question type. The constructor documents the logging variables that can be passed.

Normal Curve Questions#

This question has two normal curves, one moves and one does not.

class ssbuilder.NormalCurveSlider(logging_vars={'location_var_name': 'loc', 'overlap_var_name': 'ov'})#
generate_figure(static_name='other group', static_color='#CE00D1', static_mean=80, static_curve_width=10, dynamic_name='your group', dynamic_color='#00CED1', dynamic_starting_mean=10, dynamic_curve_width=10, num_slider_locs=101, min_slider_value=None, max_slider_value=None, overlap_decimals=2, mean_decimals=None, xaxis_title='')#

Generate a normal curve question object on a default scale of

Parameters:

  • static_name (string) – legend text for static curve

  • static_color (hex including #) – hex code for the color to use for static curve, including a # sign as the first character

  • static_mean (number) – location of the static curve

  • static_curve_width (number) – width of curve, as the scipy.norm scale

  • dynamic_name (string) – legend text for dynamic curve

  • dynamic_color (hex including #) – hex code for the color to use for dynamic curve, including a # sign as the first character

  • dynamic_starting_mean (number) – the location where the slider starts

  • curve_width (number) – width of curves

  • num_slider_locs (integer) – number of slilder locations

  • min_slider_value (number) – the minimum value for the slider

  • max_slider_value (number) – the maximum value for the slider

  • overlap_decimals (integer) – number of place values to round the % overlap value to for both display and reporting, positive to the right of the decimal, negative for left of decimal (eg -2 rounds to nearest 100)

  • mean_decimals (integer) – number of place values to round the mean (position) value to for both display and reporting positive to the right of the decimal, negative for left of decimal (eg -2 rounds to nearest 100)

  • xaxis_title (string) – text label for the x axis

Returns:

fig – figure object based on parameters

Return type:

plotly figure object

Notes:#

curve is drawn with scipy.norm

Trade Off Questions#

this quesiton typ trades off between two two extremes over a number of models in the middle

class ssbuilder.TradeoffLine(logging_vars={'location_var_name': 'model_number'})#
generate_figure(pretty_data_file, slider_label='Model', trace_col='metric', x_col='model_number', trace_value1='accuracy', trace1_hover='accurate', trace_value2='false_positive_rate', trace2_hover='false positives', y_col='percent', y_min=None, y_max=None, num_digits=2, color_col='group', color_hover='people', anchor_name='selected model', disable_zoom=True, default_selection=10)#

make the lineplot

Parameters:

  • pretty_data_file (string) – file name of a tidy (tall) dataset with pretty content. that is any data transformations should occur on the data (eg scaling .7523943 to 75.23943 and expanding column names) column names can still rely on python conventions, before display the _ will be converted to space

  • slider_column (string) – name of column to use for the slider

  • slider_label (string) – name to display when labeling the slider postion values (and in hovertext)

  • x_col (string) – name of column to use for the xor y axis

  • y_col (string) – name of column to use for the xor y axis

  • trace_value1 (same as the values of x_col in the data file) – first,second value to filter (left, right metric)

  • trace_value2 (same as the values of x_col in the data file) – first,second value to filter (left, right metric)

  • trace1_hover (string) – noun versions to use in the hovertext

  • trace2_hover (string) – noun versions to use in the hovertext

  • y_min (numerical) – minimum and maximum values to fix the plot axies, if none, allow plotly to decide

  • y_max (numerical) – minimum and maximum values to fix the plot axies, if none, allow plotly to decide

  • num_digits (num digits to display)

  • color_col (string) – name of colum to use for the colring of the lines

  • color_hover (string) – noun to use for groups

  • disable_zoom (bool) – disable the zoom on the generated plot

  • anchor_name (string) – name for vertical bar

  • default_selection (int) – model that is selected when laoding

Returns:

  • fig (plotly figure object)

  • figure object based on parameters

class ssbuilder.TradeoffBar(logging_vars={'location_var_name': 'model_number'})#
generate_figure(pretty_data_file, slider_column='model_number', slider_label='Model', x_col='metric', x_value1='accuracy', x_value1_hover='accurate', x_value2='false_positive_rate', x_value2_hover='false positives', y_col='percent', y_min=None, y_max=None, num_digits=1, color_col='group', color_hover='people', disable_zoom=True, default_selection=10)#

make the barplot

Parameters:

  • pretty_data_file (string) – file name of a tidy (tall) dataset with pretty content. that is any data transformations should occur on the data (eg scaling .7523943 to 75.23943 and expanding column names) column names can still rely on python conventions, before display the _ will be converted to space

  • slider_column (string) – name of column to use for the slider

  • slider_label (string) – name to display when labeling the slider postion values (and in hovertext)

  • x_col (string) – name of column to use for the xor y axis

  • y_col (string) – name of column to use for the xor y axis

  • x_value1 (same as the values of x_col in the data file) – first,second value to filter (left, right metric)

  • x_value2 (same as the values of x_col in the data file) – first,second value to filter (left, right metric)

  • x_value1_hover (string) – noun versions to use in the hovertext

  • x_value2_hover (string) – noun versions to use in the hovertext

  • y_min (numerical) – minimum and maximum values to fix the plot axies, if none, allow plotly to decide

  • y_max (numerical) – minimum and maximum values to fix the plot axies, if none, allow plotly to decide

  • num_digits (num digits to display)

  • color_col (string) – name of colum to use for the colring of the bars

  • color_hover – hover text to use for groups created by color

  • disable_zoom (bool) – disable the zoom on the generated plot

  • default_selection (int) – model that is selected when laoding

Returns:

  • fig (plotly figure object)

  • figure object based on parameters

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