Source code for pandas_visual_analysis.widgets.parcoords
import numbers
import ipywidgets as widgets
import numpy as np
import pandas as pd
import plotly.graph_objs as go
from plotly.callbacks import Points
from pandas_visual_analysis import DataSource
from pandas_visual_analysis.data_source import SelectionType
from pandas_visual_analysis.utils.config import Config
from pandas_visual_analysis.widgets import BaseWidget, register_widget
from pandas_visual_analysis.widgets.helpers.multi_select import (
HasMultiSelect,
)
[docs]@register_widget
class ParallelCoordinatesWidget(BaseWidget, HasMultiSelect):
"""
The ParallelCoordinatesWidget shows a parallel coordinates plot for high dimensional data and supports brushing.
Only displays numerical columns, which can be reordered arbitrarily.
Displays a multi column selection if there are too many columns to display them all at once.
"""
def __init__(
self,
data_source: DataSource,
row: int,
index: int,
relative_size: float,
max_height: int,
):
"""
:param data_source: :class:`pandas_visual_analysis.data_source.DataSource` for the widget.
:param row: The row the widget is in.
:param index: Index of the row the widget is in.
:param relative_size: The space the widget has in a row which is then converted to the width. (e.g. 0.33 => 33%)
:param max_height: height in pixels the plot has to have
"""
super(ParallelCoordinatesWidget, self).__init__(
data_source, row, index, relative_size, max_height
)
super(BaseWidget, self).__init__(
self.data_source.numerical_columns, relative_size, max_height
)
if len(self.columns) < 1:
raise ValueError(
"The data contains too few numerical columns to display a parallel coordinates plot."
"Remove the widget from the layout!"
)
if self.use_multi_select:
self.multi_select_toggle: widgets.Button = widgets.Button(
description="Hide Selection"
)
# self.multi_select_toggle.on_click(callback=self._toggle_multi_select)
self.trace, self.figure_widget = self._get_figure_widget()
self.constraint_ranges = {}
self.change_initiated = False
def f(x, y):
pass
self.pass_func = f
self.set_observers()
# set root here because need to toggle the select and need widgets for that
self.root: widgets.Widget = widgets.HBox(
[self.figure_widget], layout=widgets.Layout(width="100%")
)
if self.multi_select:
self.root = widgets.HBox([self.figure_widget, self.multi_select_widget])
if self.data_source.few_num_cols:
pass # todo: implement behaviour for few numerical columns (HTML message)
[docs] def observe_brush_indices_change(self, sender):
if not self.change_initiated:
# shortly disable selection behaviour to reset constraint ranges
self.figure_widget.data[0].on_change(self.pass_func, "dimensions")
with self.figure_widget.batch_update(), self.figure_widget.hold_trait_notifications():
for dimension in self.figure_widget.data[0].dimensions:
dimension["constraintrange"] = None
self.figure_widget.data[0].on_change(
self._on_selection_helper, "dimensions"
)
self.constraint_ranges = {}
self.change_initiated = False
new_indices = list(self.data_source.brushed_indices)
new_color = np.zeros(self.data_source.len, dtype="uint8")
new_color[new_indices] = 1
with self.figure_widget.batch_update(), self.figure_widget.hold_trait_notifications():
self.figure_widget.data[0].line.color = new_color
[docs] def set_observers(self):
self.data_source.on_indices_changed.connect(self.observe_brush_indices_change)
if self.use_multi_select:
self.multi_select.on_selected_options_changed.connect(
self._on_selected_columns_changed
)
[docs] def on_selection(self, trace, points, state):
self.change_initiated = True
if self.data_source.selection_type in {
SelectionType.ADDITIVE,
SelectionType.SUBTRACTIVE,
}:
self.change_initiated = False # we want to remove constraint ranges in observe_brush_indices_change
new_color = np.zeros(self.data_source.len, dtype="uint8")
new_color[points.point_inds] = 1
with self.figure_widget.batch_update(), self.figure_widget.hold_trait_notifications():
self.figure_widget.data[0].line.color = new_color
self.data_source.brushed_indices = points.point_inds
def _on_selection_helper(self, obj, dimensions):
old_ranges = self.constraint_ranges
self.constraint_ranges = {
dim["label"]: dim["constraintrange"]
for dim in dimensions
if dim["constraintrange"]
}
if self.constraint_ranges == old_ranges:
return # this is the case when the user just reorders the dimensions
if len(list(self.constraint_ranges.keys())) == 0:
self.on_deselection(None, None)
return
mask = self._get_constraint_mask(self.constraint_ranges)
points = np.arange(self.data_source.len)[mask].tolist()
self.on_selection(None, Points(point_inds=points), None)
def _get_constraint_mask(self, constraint_ranges: dict) -> np.array:
cols = list(constraint_ranges.keys())
mask: np.array = np.full(self.data_source.len, fill_value=True, dtype=bool)
for col in cols:
range_tuple = constraint_ranges[col]
if all(isinstance(x, numbers.Number) for x in range_tuple):
range_tuple = (range_tuple,)
intermediate_mask: np.array = np.full(
self.data_source.len, fill_value=False, dtype=bool
) # for several constraints in one dimension
for ranges in range_tuple:
intermediate_mask |= (
self.data_source.data[col].between(ranges[0], ranges[1])
).values
mask &= intermediate_mask
return mask
def _get_par_coords(self) -> go.Parcoords:
config = Config()
self.trace: go.Parcoords = go.Parcoords(
line=dict(
color=config.color_scale[1][1],
colorscale=config.color_scale,
cmin=0,
cmax=1,
),
dimensions=[self._get_dimension_dict(col) for col in self.selected_columns],
)
return self.trace
def _get_figure_widget(self):
trace: go.Parcoords = self._get_par_coords()
figure_widget: go.FigureWidget = go.FigureWidget(
data=[self.trace],
layout=go.Layout(
margin=dict(l=50, r=50, b=30, t=50, pad=10),
autosize=True,
xaxis=dict(automargin=True),
showlegend=False,
),
)
figure_widget.data[0].on_change(self._on_selection_helper, "dimensions")
return trace, figure_widget
def _get_dimension_dict(self, col: str) -> dict:
series: pd.Series = self.data_source.data[col]
return dict(range=[series.min(), series.max()], label=col, values=series)
# def _toggle_multi_select(self, obj):
# if self.multi_select:
# self.show_multi_select = not self.show_multi_select
# button_description = "Hide" if self.show_multi_select else "Show"
# self.multi_select_toggle.description = button_description + " Selection"
#
# if self.show_multi_select:
# children = (self.figure_widget, self.multi_select_widget)
# else:
# children = (self.figure_widget,)
# self.root.children = (self.multi_select_toggle, widgets.HBox(children))
def _on_selected_columns_changed(self, sender):
self.selected_columns = sender.selected_options
self._redraw_plot()
def _redraw_plot(self):
# shortly disable selection behaviour to reset constraint ranges
self.figure_widget.data[0].on_change(self.pass_func, "dimensions")
old_constraint_ranges = {
dim["label"]: dim["constraintrange"]
for dim in self.figure_widget.data[0].dimensions
if dim["constraintrange"]
}
with self.figure_widget.batch_update(), self.figure_widget.hold_trait_notifications():
self.figure_widget.data[0].dimensions = [
self._get_dimension_dict(col) for col in self.selected_columns
]
# add old constraint ranges to plot
for dim in self.figure_widget.data[0].dimensions:
if dim["label"] in old_constraint_ranges.keys():
dim["constraintrange"] = old_constraint_ranges[dim["label"]]
# if constraint ranges were removed by deselecting a column with a constraint update selection
# only updates if constraint ranges actually change, else it returns without updating the selection
self._on_selection_helper(
None, dimensions=self.figure_widget.data[0].dimensions
)
self.figure_widget.data[0].on_change(self._on_selection_helper, "dimensions")
