在Bokeh python中创建雷达图表的步骤是什么？

Question

目的：创建散景蟒内的雷达图

是有帮助的，这是我后的图表类型：

我从Matplotlib获得this chart example这可能在闭合上的溶液中的间隙是有帮助，但是我看不到如何到达那里。

下面是我能找到使用背景虚化的雷达图最接近的例子：

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) 

任何帮助，将不胜感激。

Answer 1

下面是一个基于上面链接的matplotlib示例上的方法的示例。这会让你非常接近你想要的东西，你需要修正所有的格式以使它看起来更漂亮，并且加入轮廓线。

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)