在 Bokeh python 中创建雷达图的步骤是什么？
What are the steps to create a radar chart in Bokeh python?
Objective: 在 Bokeh 中创建雷达图 python
为了提供帮助，这是我想要的图表类型：
我从 Matplotlib 获得了 this chart example，这可能有助于缩小解决方案的差距，但我不知道如何到达那里。
下面是我能找到的最接近使用 Bokeh 的雷达图的示例：
from collections import OrderedDict
from math import log, sqrt
import numpy as np
import pandas as pd
from six.moves import cStringIO as StringIO
from bokeh.plotting import figure, show, output_file
antibiotics = """
bacteria, penicillin, streptomycin, neomycin, gram
Mycobacterium tuberculosis, 800, 5, 2, negative
Salmonella schottmuelleri, 10, 0.8, 0.09, negative
Proteus vulgaris, 3, 0.1, 0.1, negative
Klebsiella pneumoniae, 850, 1.2, 1, negative
Brucella abortus, 1, 2, 0.02, negative
Pseudomonas aeruginosa, 850, 2, 0.4, negative
Escherichia coli, 100, 0.4, 0.1, negative
Salmonella (Eberthella) typhosa, 1, 0.4, 0.008, negative
Aerobacter aerogenes, 870, 1, 1.6, negative
Brucella antracis, 0.001, 0.01, 0.007, positive
Streptococcus fecalis, 1, 1, 0.1, positive
Staphylococcus aureus, 0.03, 0.03, 0.001, positive
Staphylococcus albus, 0.007, 0.1, 0.001, positive
Streptococcus hemolyticus, 0.001, 14, 10, positive
Streptococcus viridans, 0.005, 10, 40, positive
Diplococcus pneumoniae, 0.005, 11, 10, positive
"""
drug_color = OrderedDict([
("Penicillin", "#0d3362"),
("Streptomycin", "#c64737"),
("Neomycin", "black" ),
])
gram_color = {
"positive" : "#aeaeb8",
"negative" : "#e69584",
}
df = pd.read_csv(StringIO(antibiotics),
skiprows=1,
skipinitialspace=True,
engine='python')
width = 800
height = 800
inner_radius = 90
outer_radius = 300 - 10
minr = sqrt(log(.001 * 1E4))
maxr = sqrt(log(1000 * 1E4))
a = (outer_radius - inner_radius) / (minr - maxr)
b = inner_radius - a * maxr
def rad(mic):
return a * np.sqrt(np.log(mic * 1E4)) + b
big_angle = 2.0 * np.pi / (len(df) + 1)
small_angle = big_angle / 7
p = figure(plot_width=width, plot_height=height, title="",
x_axis_type=None, y_axis_type=None,
x_range=(-420, 420), y_range=(-420, 420),
min_border=0, outline_line_color="black",
background_fill_color="#f0e1d2", border_fill_color="#f0e1d2",
toolbar_sticky=False)
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
# annular wedges
angles = np.pi/2 - big_angle/2 - df.index.to_series()*big_angle
colors = [gram_color[gram] for gram in df.gram]
p.annular_wedge(
0, 0, inner_radius, outer_radius, -big_angle+angles, angles, color=colors,
)
# small wedges
p.annular_wedge(0, 0, inner_radius, rad(df.penicillin),
-big_angle+angles+5*small_angle, -big_angle+angles+6*small_angle,
color=drug_color['Penicillin'])
p.annular_wedge(0, 0, inner_radius, rad(df.streptomycin),
-big_angle+angles+3*small_angle, -big_angle+angles+4*small_angle,
color=drug_color['Streptomycin'])
p.annular_wedge(0, 0, inner_radius, rad(df.neomycin),
-big_angle+angles+1*small_angle, -big_angle+angles+2*small_angle,
color=drug_color['Neomycin'])
# circular axes and lables
labels = np.power(10.0, np.arange(-3, 4))
radii = a * np.sqrt(np.log(labels * 1E4)) + b
p.circle(0, 0, radius=radii, fill_color=None, line_color="white")
p.text(0, radii[:-1], [str(r) for r in labels[:-1]],
text_font_size="8pt", text_align="center", text_baseline="middle")
# radial axes
p.annular_wedge(0, 0, inner_radius-10, outer_radius+10,
-big_angle+angles, -big_angle+angles, color="black")
# bacteria labels
xr = radii[0]*np.cos(np.array(-big_angle/2 + angles))
yr = radii[0]*np.sin(np.array(-big_angle/2 + angles))
label_angle=np.array(-big_angle/2+angles)
label_angle[label_angle < -np.pi/2] += np.pi # easier to read labels on the left side
p.text(xr, yr, df.bacteria, angle=label_angle,
text_font_size="9pt", text_align="center", text_baseline="middle")
# OK, these hand drawn legends are pretty clunky, will be improved in future release
p.circle([-40, -40], [-370, -390], color=list(gram_color.values()), radius=5)
p.text([-30, -30], [-370, -390], text=["Gram-" + gr for gr in gram_color.keys()],
text_font_size="7pt", text_align="left", text_baseline="middle")
p.rect([-40, -40, -40], [18, 0, -18], width=30, height=13,
color=list(drug_color.values()))
p.text([-15, -15, -15], [18, 0, -18], text=list(drug_color),
text_font_size="9pt", text_align="left", text_baseline="middle")
output_file("burtin.html", title="burtin.py example")
show(p)
如有任何帮助，我们将不胜感激。
这是一个基于上面链接的 matplotlib 示例的方法的类似示例。这让你非常接近你想要的东西，你需要修复所有格式以使其看起来更好，并添加轮廓线。
import numpy as np
from bokeh.plotting import figure, show, output_file
from bokeh.models import ColumnDataSource, LabelSet
num_vars = 9
centre = 0.5
theta = np.linspace(0, 2*np.pi, num_vars, endpoint=False)
# rotate theta such that the first axis is at the top
theta += np.pi/2
def unit_poly_verts(theta, centre ):
"""Return vertices of polygon for subplot axes.
This polygon is circumscribed by a unit circle centered at (0.5, 0.5)
"""
x0, y0, r = [centre ] * 3
verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta]
return verts
def radar_patch(r, theta, centre ):
""" Returns the x and y coordinates corresponding to the magnitudes of
each variable displayed in the radar plot
"""
# offset from centre of circle
offset = 0.01
yt = (r*centre + offset) * np.sin(theta) + centre
xt = (r*centre + offset) * np.cos(theta) + centre
return xt, yt
verts = unit_poly_verts(theta, centre)
x = [v[0] for v in verts]
y = [v[1] for v in verts]
p = figure(title="Baseline - Radar plot")
text = ['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP', 'CO', 'O3','']
source = ColumnDataSource({'x':x + [centre ],'y':y + [1],'text':text})
p.line(x="x", y="y", source=source)
labels = LabelSet(x="x",y="y",text="text",source=source)
p.add_layout(labels)
# example factor:
f1 = np.array([0.88, 0.01, 0.03, 0.03, 0.00, 0.06, 0.01, 0.00, 0.00])
f2 = np.array([0.07, 0.95, 0.04, 0.05, 0.00, 0.02, 0.01, 0.00, 0.00])
f3 = np.array([0.01, 0.02, 0.85, 0.19, 0.05, 0.10, 0.00, 0.00, 0.00])
f4 = np.array([0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 0.00, 0.00])
f5 = np.array([0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 0.00, 0.00])
#xt = np.array(x)
flist = [f1,f2,f3,f4,f5]
colors = ['blue','green','red', 'orange','purple']
for i in range(len(flist)):
xt, yt = radar_patch(flist[i], theta, centre)
p.patch(x=xt, y=yt, fill_alpha=0.15, fill_color=colors[i])
show(p)
Objective: 在 Bokeh 中创建雷达图 python
为了提供帮助，这是我想要的图表类型：
我从 Matplotlib 获得了 this chart example，这可能有助于缩小解决方案的差距，但我不知道如何到达那里。
下面是我能找到的最接近使用 Bokeh 的雷达图的示例：
from collections import OrderedDict
from math import log, sqrt
import numpy as np
import pandas as pd
from six.moves import cStringIO as StringIO
from bokeh.plotting import figure, show, output_file
antibiotics = """
bacteria, penicillin, streptomycin, neomycin, gram
Mycobacterium tuberculosis, 800, 5, 2, negative
Salmonella schottmuelleri, 10, 0.8, 0.09, negative
Proteus vulgaris, 3, 0.1, 0.1, negative
Klebsiella pneumoniae, 850, 1.2, 1, negative
Brucella abortus, 1, 2, 0.02, negative
Pseudomonas aeruginosa, 850, 2, 0.4, negative
Escherichia coli, 100, 0.4, 0.1, negative
Salmonella (Eberthella) typhosa, 1, 0.4, 0.008, negative
Aerobacter aerogenes, 870, 1, 1.6, negative
Brucella antracis, 0.001, 0.01, 0.007, positive
Streptococcus fecalis, 1, 1, 0.1, positive
Staphylococcus aureus, 0.03, 0.03, 0.001, positive
Staphylococcus albus, 0.007, 0.1, 0.001, positive
Streptococcus hemolyticus, 0.001, 14, 10, positive
Streptococcus viridans, 0.005, 10, 40, positive
Diplococcus pneumoniae, 0.005, 11, 10, positive
"""
drug_color = OrderedDict([
("Penicillin", "#0d3362"),
("Streptomycin", "#c64737"),
("Neomycin", "black" ),
])
gram_color = {
"positive" : "#aeaeb8",
"negative" : "#e69584",
}
df = pd.read_csv(StringIO(antibiotics),
skiprows=1,
skipinitialspace=True,
engine='python')
width = 800
height = 800
inner_radius = 90
outer_radius = 300 - 10
minr = sqrt(log(.001 * 1E4))
maxr = sqrt(log(1000 * 1E4))
a = (outer_radius - inner_radius) / (minr - maxr)
b = inner_radius - a * maxr
def rad(mic):
return a * np.sqrt(np.log(mic * 1E4)) + b
big_angle = 2.0 * np.pi / (len(df) + 1)
small_angle = big_angle / 7
p = figure(plot_width=width, plot_height=height, title="",
x_axis_type=None, y_axis_type=None,
x_range=(-420, 420), y_range=(-420, 420),
min_border=0, outline_line_color="black",
background_fill_color="#f0e1d2", border_fill_color="#f0e1d2",
toolbar_sticky=False)
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
# annular wedges
angles = np.pi/2 - big_angle/2 - df.index.to_series()*big_angle
colors = [gram_color[gram] for gram in df.gram]
p.annular_wedge(
0, 0, inner_radius, outer_radius, -big_angle+angles, angles, color=colors,
)
# small wedges
p.annular_wedge(0, 0, inner_radius, rad(df.penicillin),
-big_angle+angles+5*small_angle, -big_angle+angles+6*small_angle,
color=drug_color['Penicillin'])
p.annular_wedge(0, 0, inner_radius, rad(df.streptomycin),
-big_angle+angles+3*small_angle, -big_angle+angles+4*small_angle,
color=drug_color['Streptomycin'])
p.annular_wedge(0, 0, inner_radius, rad(df.neomycin),
-big_angle+angles+1*small_angle, -big_angle+angles+2*small_angle,
color=drug_color['Neomycin'])
# circular axes and lables
labels = np.power(10.0, np.arange(-3, 4))
radii = a * np.sqrt(np.log(labels * 1E4)) + b
p.circle(0, 0, radius=radii, fill_color=None, line_color="white")
p.text(0, radii[:-1], [str(r) for r in labels[:-1]],
text_font_size="8pt", text_align="center", text_baseline="middle")
# radial axes
p.annular_wedge(0, 0, inner_radius-10, outer_radius+10,
-big_angle+angles, -big_angle+angles, color="black")
# bacteria labels
xr = radii[0]*np.cos(np.array(-big_angle/2 + angles))
yr = radii[0]*np.sin(np.array(-big_angle/2 + angles))
label_angle=np.array(-big_angle/2+angles)
label_angle[label_angle < -np.pi/2] += np.pi # easier to read labels on the left side
p.text(xr, yr, df.bacteria, angle=label_angle,
text_font_size="9pt", text_align="center", text_baseline="middle")
# OK, these hand drawn legends are pretty clunky, will be improved in future release
p.circle([-40, -40], [-370, -390], color=list(gram_color.values()), radius=5)
p.text([-30, -30], [-370, -390], text=["Gram-" + gr for gr in gram_color.keys()],
text_font_size="7pt", text_align="left", text_baseline="middle")
p.rect([-40, -40, -40], [18, 0, -18], width=30, height=13,
color=list(drug_color.values()))
p.text([-15, -15, -15], [18, 0, -18], text=list(drug_color),
text_font_size="9pt", text_align="left", text_baseline="middle")
output_file("burtin.html", title="burtin.py example")
show(p)
如有任何帮助，我们将不胜感激。
这是一个基于上面链接的 matplotlib 示例的方法的类似示例。这让你非常接近你想要的东西，你需要修复所有格式以使其看起来更好，并添加轮廓线。
import numpy as np
from bokeh.plotting import figure, show, output_file
from bokeh.models import ColumnDataSource, LabelSet
num_vars = 9
centre = 0.5
theta = np.linspace(0, 2*np.pi, num_vars, endpoint=False)
# rotate theta such that the first axis is at the top
theta += np.pi/2
def unit_poly_verts(theta, centre ):
"""Return vertices of polygon for subplot axes.
This polygon is circumscribed by a unit circle centered at (0.5, 0.5)
"""
x0, y0, r = [centre ] * 3
verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta]
return verts
def radar_patch(r, theta, centre ):
""" Returns the x and y coordinates corresponding to the magnitudes of
each variable displayed in the radar plot
"""
# offset from centre of circle
offset = 0.01
yt = (r*centre + offset) * np.sin(theta) + centre
xt = (r*centre + offset) * np.cos(theta) + centre
return xt, yt
verts = unit_poly_verts(theta, centre)
x = [v[0] for v in verts]
y = [v[1] for v in verts]
p = figure(title="Baseline - Radar plot")
text = ['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP', 'CO', 'O3','']
source = ColumnDataSource({'x':x + [centre ],'y':y + [1],'text':text})
p.line(x="x", y="y", source=source)
labels = LabelSet(x="x",y="y",text="text",source=source)
p.add_layout(labels)
# example factor:
f1 = np.array([0.88, 0.01, 0.03, 0.03, 0.00, 0.06, 0.01, 0.00, 0.00])
f2 = np.array([0.07, 0.95, 0.04, 0.05, 0.00, 0.02, 0.01, 0.00, 0.00])
f3 = np.array([0.01, 0.02, 0.85, 0.19, 0.05, 0.10, 0.00, 0.00, 0.00])
f4 = np.array([0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 0.00, 0.00])
f5 = np.array([0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 0.00, 0.00])
#xt = np.array(x)
flist = [f1,f2,f3,f4,f5]
colors = ['blue','green','red', 'orange','purple']
for i in range(len(flist)):
xt, yt = radar_patch(flist[i], theta, centre)
p.patch(x=xt, y=yt, fill_alpha=0.15, fill_color=colors[i])
show(p)