def generate_multiplot(self, values: Dict[str, Any] = None):
# TOCHECK Avoid circular imports
import plot_data
from plot_data.colors import BLACK, LIGHTBLUE, LIGHTGREY, BLUE
if values is None:
values = []
for i, line in enumerate(self.array):
value = {}
for variable in self.variables:
value[variable] = self.get_value_by_name(line, variable)
# for objective_name, ratings in objective_ratings.items():
# value[objective_name] = ratings[i]
values.append(value)
fontsize = 12
first_vars = self.variables[:2]
values2d = [{key: val[key]} for key in first_vars for val in values]
rgbs = [[192, 11, 11], [14, 192, 11], [11, 11, 192]]
tooltip = plot_data.Tooltip(to_disp_attribute_names=self.variables,
name='Tooltip')
scatterplot = plot_data.Scatter(axis=plot_data.Axis(),
tooltip=tooltip,
to_disp_attribute_names=first_vars,
elements=values2d,
name='Scatter Plot')
parallelplot = plot_data.ParallelPlot(
disposition='horizontal',
to_disp_attribute_names=self.variables,
rgbs=rgbs,
elements=values)
objects = [scatterplot, parallelplot]
sizes = [
plot_data.Window(width=560, height=300),
plot_data.Window(width=560, height=300)
]
coords = [(0, 0), (0, 300)]
multiplot = plot_data.MultiplePlots(plots=objects,
elements=values,
sizes=sizes,
coords=coords,
name='Results plot')
return multiplot
def plot_data(self):
cycle_time = [
i + 1 for i in range(len(self.wltp_cycle.cycle_speeds[:-1]))
]
points = []
for car_speed, wheel_torque, engine_speed, engine_torque, fuel_consumption, time, gear in zip(
self.wltp_cycle.cycle_speeds[:-1],
self.wltp_cycle.cycle_torques, self.engine_speeds,
self.engine_torques, self.fuel_consumptions, cycle_time,
self.gears_ratios[0]):
points.append({
'c_s': car_speed,
'whl_t': wheel_torque,
'w_e': engine_speed,
't_e': engine_torque,
'f_cons (g/kWh)': fuel_consumption * 3.6e9,
'time': time,
'gear': gear
})
color_fill = LIGHTBLUE
color_stroke = GREY
point_style = plot_data.PointStyle(color_fill=color_fill,
color_stroke=color_stroke)
axis = plot_data.Axis()
attributes = ['c_s', 'f_cons (g/kWh)']
tooltip = plot_data.Tooltip(attributes=attributes)
objects = [
plot_data.Scatter(tooltip=tooltip,
x_variable=attributes[0],
y_variable=attributes[1],
point_style=point_style,
elements=points,
axis=axis)
]
attributes = ['whl_t', 'f_cons (g/kWh)']
tooltip = plot_data.Tooltip(attributes=attributes)
objects.append(
plot_data.Scatter(tooltip=tooltip,
x_variable=attributes[0],
y_variable=attributes[1],
point_style=point_style,
elements=points,
axis=axis))
attributes = ['w_e', 't_e', 'f_cons (g/kWh)']
edge_style = plot_data.EdgeStyle()
rgbs = [[192, 11, 11], [14, 192, 11], [11, 11, 192]]
objects.append(
plot_data.ParallelPlot(elements=points,
edge_style=edge_style,
disposition='vertical',
axes=attributes,
rgbs=rgbs))
coords = [(0, 0), (500, 0), (1000, 0)]
sizes = [
plot_data.Window(width=500, height=500),
plot_data.Window(width=500, height=500),
plot_data.Window(width=500, height=500)
]
multiplot = plot_data.MultiplePlots(elements=points,
plots=objects,
sizes=sizes,
coords=coords)
list_colors = [BLUE, BROWN, GREEN, BLACK]
graphs2d = []
point_style = plot_data.PointStyle(color_fill=RED,
color_stroke=BLACK,
size=1)
tooltip = plot_data.Tooltip(attributes=['sec', 'gear'])
edge_style = plot_data.EdgeStyle(line_width=0.5,
color_stroke=list_colors[0])
elements = []
for i, gear in enumerate(self.gears_ratios[0]):
elements.append({'sec': cycle_time[i], 'gear': gear})
dataset = plot_data.Dataset(elements=elements,
edge_style=edge_style,
tooltip=tooltip,
point_style=point_style)
graphs2d.append(
plot_data.Graph2D(graphs=[dataset],
x_variable='sec',
y_variable='gear'))
tooltip = plot_data.Tooltip(attributes=['sec', 'f_cons (g/kWh)'])
edge_style = plot_data.EdgeStyle(line_width=0.5,
color_stroke=list_colors[0])
elements = []
for i, gear in enumerate(self.gears_ratios[0]):
point = {
'sec': cycle_time[i],
'f_cons (g/kWh)': self.fuel_consumptions[i] * 3.6e9
}
elements.append(point)
dataset = plot_data.Dataset(elements=elements,
edge_style=edge_style,
tooltip=tooltip,
point_style=point_style)
graphs2d.append(
plot_data.Graph2D(graphs=[dataset],
x_variable='sec',
y_variable='f_cons (g/kWh)'))
tooltip = plot_data.Tooltip(attributes=['sec', 'w_e'])
edge_style = plot_data.EdgeStyle(line_width=0.5,
color_stroke=list_colors[2])
elements = []
for i, torque in enumerate(self.wltp_cycle.cycle_torques):
elements.append({
'sec': cycle_time[i],
'w_e': self.engine_speeds[i]
})
dataset = plot_data.Dataset(elements=elements,
edge_style=edge_style,
tooltip=tooltip,
point_style=point_style)
graphs2d.append(
plot_data.Graph2D(graphs=[dataset],
x_variable='sec',
y_variable='w_e'))
tooltip = plot_data.Tooltip(attributes=['sec', 'w_t'])
edge_style = plot_data.EdgeStyle(line_width=0.5,
color_stroke=list_colors[3])
elements = []
for i, torque in enumerate(self.wltp_cycle.cycle_torques):
elements.append({
'sec': cycle_time[i],
'w_t': self.engine_torques[i]
})
dataset = plot_data.Dataset(elements=elements,
edge_style=edge_style,
tooltip=tooltip,
point_style=point_style)
graphs2d.append(
plot_data.Graph2D(graphs=[dataset],
x_variable='sec',
y_variable='w_t'))
coords = [(0, 0), (0, 187.5), (0, 375), (0, 562.5)]
sizes = [
plot_data.Window(width=1500, height=187.5),
plot_data.Window(width=1500, height=187.5),
plot_data.Window(width=1500, height=187.5),
plot_data.Window(width=1500, height=187.5)
]
multiplot2 = plot_data.MultiplePlots(elements=points,
plots=graphs2d,
sizes=sizes,
coords=coords)
return [multiplot, multiplot2]
def plot_data(self):
attributes = ['cx', 'cy']
# Contour
contour = self.standalone_subobject.contour().plot_data()
primitives_group = plot_data.PrimitiveGroup(primitives=[contour],
name='Contour')
# Scatter Plot
bounds = {'x': [0, 6], 'y': [100, 2000]}
catalog = Catalog.random_2d(bounds=bounds, threshold=8000)
points = [
plot_data.Point2D(cx=v[0], cy=v[1], name='Point' + str(i))
for i, v in enumerate(catalog.array)
]
axis = plot_data.Axis()
tooltip = plot_data.Tooltip(to_disp_attribute_names=attributes,
name='Tooltips')
scatter_plot = plot_data.Scatter(axis=axis,
tooltip=tooltip,
elements=points,
to_disp_attribute_names=attributes,
name='Scatter Plot')
# Parallel Plot
attributes = ['cx', 'cy', 'color_fill', 'color_stroke']
parallel_plot = plot_data.ParallelPlot(
elements=points,
to_disp_attribute_names=attributes,
name='Parallel Plot')
# Multi Plot
objects = [scatter_plot, parallel_plot]
sizes = [
plot_data.Window(width=560, height=300),
plot_data.Window(width=560, height=300)
]
coords = [(0, 0), (300, 0)]
multi_plot = plot_data.MultiplePlots(elements=points,
plots=objects,
sizes=sizes,
coords=coords,
name='Multiple Plot')
attribute_names = ['time', 'electric current']
tooltip = plot_data.Tooltip(to_disp_attribute_names=attribute_names)
time1 = linspace(0, 20, 20)
current1 = [t**2 for t in time1]
elements1 = []
for time, current in zip(time1, current1):
elements1.append({'time': time, 'electric current': current})
# The previous line instantiates a dataset with limited arguments but
# several customizations are available
point_style = plot_data.PointStyle(color_fill=RED, color_stroke=BLACK)
edge_style = plot_data.EdgeStyle(color_stroke=BLUE, dashline=[10, 5])
custom_dataset = plot_data.Dataset(elements=elements1,
name='I = f(t)',
tooltip=tooltip,
point_style=point_style,
edge_style=edge_style)
# Now let's create another dataset for the purpose of this exercice
time2 = linspace(0, 20, 100)
current2 = [100 * (1 + cos(t)) for t in time2]
elements2 = []
for time, current in zip(time2, current2):
elements2.append({'time': time, 'electric current': current})
dataset2 = plot_data.Dataset(elements=elements2, name='I2 = f(t)')
graph2d = plot_data.Graph2D(graphs=[custom_dataset, dataset2],
to_disp_attribute_names=attribute_names)
return [
primitives_group, scatter_plot, parallel_plot, multi_plot, graph2d
]
color_stroke=colors.VIOLET,
stroke_width=0.5,
size=2, # 1, 2, 3 or 4
shape='square') # 'circle', 'square' or 'crux'
# Finally, axis can be personalized too
graduation_style = plot_data.TextStyle(text_color=colors.BLUE,
font_size=10,
font_style='Arial')
axis_style = plot_data.EdgeStyle(line_width=0.5,
color_stroke=colors.ROSE,
dashline=[])
axis = plot_data.Axis(nb_points_x=7,
nb_points_y=5,
graduation_style=graduation_style,
axis_style=axis_style)
# a tooltip is drawn when clicking on a point. Users can choose what information
# they want to be displayed.
tooltip = plot_data.Tooltip(attributes=['mass', 'length', 'shape', 'color'])
# Now, here is the new scatterplot
customized_scatterplot = plot_data.Scatter(x_variable='mass',
y_variable='shape',
point_style=point_style,
elements=elements,
axis=axis,
tooltip=tooltip)
# if debug_mode is True, set it to False