Parallel Plot: draw all features on one Figure

Parallel plot or parallel coordinates plot allows to compare features of several individual observations (series) on a set of numeric variables.

Each vertical bar represents a variable or an objective value and has its own scale (units can even be different). Values are then plotted as series of lines connected across each axis.

Thanks to Parallel Plot, correlations between variables and objectives can be globally visually studied.

How to draw a Parallel Plot ?

1. Import the required packages

# Required packages
import random
import plot_data.core as pld
from plot_data.colors import BLUE, RED, GREEN, BLACK

2. Create Data

In order to draw a Parallel plot with random values, build a random vector of samples (stored as Python dict) with different attributes. Here 3 float attributes (mass, length and speed), 1 integer attribute (rank) and 1 discrete attribute (shape) are chosen to describe each sample.

# Vector construction
elements = []
SHAPES = ['round', 'square', 'triangle', 'ellipse']
for i in range(500):
    elements.append({"mass": random.uniform(0, 10),
                     "length": random.uniform(0, 100),
                     "speed": random.uniform(0, 3.6),
                     "shape": random.choice(SHAPES),
                     "rank": random.randint(1, 20)})

3. Build the Parallel Plot object and draw it in a web browser

parallel_plot = pld.ParallelPlot(
    elements=elements,
    axes=["mass", "length", "speed", "shape", "rank"],
    edge_style=edge_style
    )

Once done, the figure can be displayed with the following command line :

pld.plot_canvas(plot_data_object=parallel_plot, canvas_id='my_parallel_plot')

Parallel Plot Features

• Rubberbands can be drawn on axes by clicking and dragging on it with mouse. Rubberbands allow to select range of values on each axis,

• Axes layout can be changed from vertical to horizontal with the Change Disposition button,

• Values order on axes can be changed from ascending to descending by clicking on its title,

• Each axis can be scrolled and scaled with mouse click and wheel,

• Each axis can be moved by clicking on its title and dragging it with mouse,

• Values can be displayed in log scales by clicking on Log Scale button,

• One can select several lines with several mouse click by keeping pressed Ctrl key,

• One can reset the view by pressing Ctrl + Space,

• One can reset the whole figure by pressing Ctrl + Shift + Left Click.

How to write a method to draw a Parallel Plot in a DessiaObject ?

For the previously designed PendulumDOE ([section 2.2.2](https://www.notion.so/Using-data-display-with-PlotData-30f86e58db6240788cf4f3b543b0ae51?pvs=21)), an interesting plot may be to draw all pendulum variables and objective values (length, gravity, speed and period).

To do it, add a method to draw a Parallel Plot to the PendulumDOE class:

class PendulumDOE(Dataset):
    :
    :
    :
  @plot_data_view("parallelplot")
  def parallel_plot(self, reference_path: str = "#"):
    elements = [
      {"period": pendulum.period, "speed": pendulum.max_speed, "length": pendulum.length, "g": pendulum.g}
      for pendulum in self.dessia_objects]
    return pld.ParallelPlot(axes=["g", "length", "period", "speed"], elements=elements)

And draw the Parallel Plot with the function plot_canvas :

# Parameters sampling definition
planet_sampling = BoundedAttributeValue('g', 1, 11, 10)
length_sampling = BoundedAttributeValue('length', 0.1, 3, 10)

# DOE instantiation
pendulum_doe = PendulumDOE.from_boundaries(planet_sampling, length_sampling, 10, 0.01, method = 'fullfact')

# Parallel Plot construction
parallel_plot = pendulum_doe.parallel_plot()

# Draw the figure in a web browser
pld.plot_canvas(plot_data_object=parallel_plot, filepath="section2_4_2_parallel_plotod")