/
plottools.py
131 lines (104 loc) · 3.98 KB
/
plottools.py
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from bokeh.plotting import figure, show
from bokeh.layouts import row
from bokeh.io import output_notebook
from bokeh.palettes import Viridis256
from bokeh.transform import linear_cmap
from bokeh.models import ColumnDataSource, ColorBar, Span
import numpy as np
from carfollow import U_I
def plot_single_trajectory(p, x, y, c, mapper,size=2):
""" Daraws a single trajectory"""
source = ColumnDataSource(dict(x=x, y=y, color=c))
p.circle(x="x", y="y", line_color=mapper, color=mapper, fill_alpha=1, size=size, source=source)
p.line(x, y, color="gainsboro")
return p
def get_mapper(data_mapper):
""" Color mapper"""
color_min, color_max = np.min(data_mapper), np.max(data_mapper)
revViridis256 = list(reversed(Viridis256))
mapper = linear_cmap(field_name="color", palette=revViridis256, low=color_min, high=color_max)
return mapper
def post_decoration(p, mapper, xlabel, ylabel):
""" add colorbar + labels """
color_bar = ColorBar(color_mapper=mapper["transform"], width=8, location=(0, 0))
p.add_layout(color_bar, "right")
p.xaxis.axis_label = xlabel
p.yaxis.axis_label = ylabel
return p
def plot_multiple_trajectories(
data_x,
data_y,
data_color,
title=None,
xlabel=None,
ylabel=None,
x_range=(0, 800),
y_range=(0, 20000),
):
""" Draw multiple trajectories"""
p = figure(
title=title, tools=[], plot_height=500, plot_width=500, x_range=x_range, y_range=y_range
)
mapper = get_mapper(data_color)
p.toolbar.logo = None
p.toolbar_location = None
for i, data in enumerate(zip(data_y.T, data_color.T)):
y, c = data
p = plot_single_trajectory(p, data_x, y, c, mapper)
p = post_decoration(p, mapper, xlabel, ylabel)
return p
def plot_single_trace(data_x, data_y, title=None, xlabel=None, ylabel=None, p_height=500, p_width=500):
""" Plots a single trace """
p = figure(title=title, plot_height=p_height, plot_width=p_width)
p.yaxis.axis_label_text_font_size='14pt'
p.yaxis.major_label_text_font_size='14pt'
p.xaxis.axis_label_text_font_size='14pt'
p.xaxis.major_label_text_font_size='14pt'
mapper = get_mapper(data_y)
p = plot_single_trajectory(p, data_x, data_y, data_y, mapper, 4)
p = post_decoration(p, mapper, xlabel, ylabel)
return p
def plot_xva(time, x, v, a, y_range, titles):
""" Plots all trajectories pos, speed acceleration"""
pos_zoom, spd_zoom, acc_zoom = y_range
pos_tit, spd_tit, acc_tit = titles
pos = plot_multiple_trajectories(
time, x, v, pos_tit, "Time [secs]", "Position [m]", y_range=pos_zoom
)
spd = plot_multiple_trajectories(
time, v, v, spd_tit, "Time [secs]", "Speed [m/s]", y_range=spd_zoom
)
acc = plot_multiple_trajectories(
time, a, a, acc_tit, "Time [secs]", "Acceleration [m/s²]", y_range=acc_zoom
)
return (pos, spd, acc)
def plot_histogram(data_x, var_name=None):
""" Plots histogram of data"""
hist, edges = np.histogram(data_x, density=True)
p = figure(title="Histogram", plot_height=500, plot_width=500, background_fill_color="#fafafa")
p.quad(
top=hist,
bottom=0,
left=edges[:-1],
right=edges[1:],
fill_color="navy",
line_color="white",
alpha=0.5,
)
p.yaxis.axis_label_text_font_size='13pt'
p.yaxis.major_label_text_font_size='13pt'
p.xaxis.axis_label_text_font_size='13pt'
p.xaxis.major_label_text_font_size='13pt'
mean = Span(location=np.mean(data_x), dimension="height", line_color="red", line_width=1)
p.add_layout(mean)
p.xaxis.axis_label = var_name
p.yaxis.axis_label = "Density"
p.grid.grid_line_color = "white"
return p
def plot_stairs(data_x, data_y, title=None, xlabel=None, ylabel=None):
""" Plot stairs plot"""
p = figure(title=title, plot_height=500, plot_width=500)
p.step(data_x, data_y, line_width=2, mode="before")
p.xaxis.axis_label = xlabel
p.yaxis.axis_label = ylabel
return p