Dear developers,
I wrote a code (using different examples), that is plotting together:
a 3d barplot with a smooth line that follows the "points" of bars.
I could not find something similar, therefore, i am sending you this
example.
You may edit some sections if you find something wrong.
Sorry for my english - not my primary language.
#The following plot presents a 3d barplot together
with a smooth line that follows the "points" of bars.
#needed modules
import csv
import pandas as pandas
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from scipy.interpolate import spline
#here, we are importing a simple datafile, csv type. data are comma
seperated
#Also, we are importing only 1st, 2nd and 4th columns. We can call
these data now by thie new name, 'io'.
#io = pandas.read_csv('test.csv', sep=",",usecols=(1,2,3,4)) #not available
#io = io[np.isfinite(io['alice'])] #not available
#We define a new name for the column that is named 'alice' inside 'io'
dataset.
result=([9,6,14,7,16,4,14,19,16,7,13,10,15,16,19,27,7,6])
#we need to make these data 'array type'
result = np.array(result)
#we now define the dimensions of our figure/plot, as well its dpi
fig=plt.figure(figsize=(14, 6), dpi=150)
#This line defines our first plot, afterwards, the '112' will define our
second plot.
ax1=fig.add_subplot(111, projection='3d')
#we define here labels
xlabels =np.array([9,6,14,7,16,4,14,19,16,7,13,10,15,16,19,27,7,6])
xpos = np.arange(xlabels.shape[0])
ylabels = np.array(['series A'])
ypos = np.arange(ylabels.shape[0])
xposM, yposM = np.meshgrid(xpos, ypos, copy=False)
zpos=result
zpos = zpos.ravel()
#this defines the dimensions of the actual boxes, you can play with
these values.
dx=0.7
dy=0.7
dz=zpos
#here, we define ticks, they are placed in the 'middle' of each bar
ax1.w_xaxis.set_ticks(xpos + dx/2.)
ax1.w_xaxis.set_ticklabels(xlabels)
ax1.w_yaxis.set_ticks(ypos + dy/2.)
ax1.w_yaxis.set_ticklabels(ylabels)
#here we define the colors of the bars, rainbow style, you can play with
these numbers
values = np.linspace(0.2, 1., xposM.ravel().shape[0])
colors = cm.rainbow(values)
#figure subtitle
fig.suptitle('test title', fontsize=20)
#here, we define in the x axis the size of its ticks, its numbers
ax1.tick_params(axis='x', which='major', pad=15,labelsize=6)
#Here, we define the limits of y axis,
#NOTE that this defines WHERE bars will be placed IN relation to the
rest figure, their offset point
plt.ylim((-2,5))
#this says if the grid will be printed
plt.grid(True)
#this defines the placement of the 3d plot in its placeholders, in the
surrounding white space
plt.subplots_adjust(left=0.0, right=1.0, bottom=0.0, top=1.0)
#this is the actual command to define the plot, all 6 parameters that we
previously defined, are placed here.
#colors is an extra parameter
ax1.bar3d(xposM.ravel(), yposM.ravel(), dz*0, dx, dy, dz, color=colors)
#here we define that we will place a second plot
ax1=fig.add_subplot(112, projection='3d')
#here we say to produce numbers from 0 according to how many data exist
in our 'result'
x=np.arange(0, len(result))
#here, i apply a math trick, in order to get the line a little higher,
out of the bars
x=x+0.4
y=result
#here, i try to center the linein relation to the top of bars.
y=y+5
#here, i try to produce more points in order to make the line to look
nicer.
x_smooth=np.linspace(x.min(),x.max(), 100)
y_smooth=spline(x,y, x_smooth)
#here, i try to produce a 'z' array of so many zeros as the length of
'x_smooth'
z=np.linspace(0, 0, len(x_smooth))
#here, we define the parameters of the second plot.
#note that 'ax1' symbol is duplicated, in order to plot the line in the
same plot with the barplot.
ax1.plot(x_smooth,z,y_smooth)
#here, finally, we will check our results, visually!
plt.show()
???..
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???
*estatisticseu at gmail.com*
???
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