def cont():
rw = RandomWalk()
rw.fill_walk()
plt.plot(rw.x ,rw.y, c = (0.3, 0.6, 0.6))
plt.show()
# CH15 Exercise 15-10
#
# random_pygal.py
#
# Use pygal to vizualize a random walk. Pygal is the visualization library that
# contains histograms and other plots
import pygal
from random_walk import RandomWalk
# Create new random walk with just 1000 points and run fill_walk() method
new_walk = RandomWalk(1000)
new_walk.fill_walk()
# Create list of tuples for xy_chart using a function and list comprehension
def merged(list1, list2):
merged_list = [(list1[i], list2[i]) for i in range(0, len(list1))]
return merged_list
# Merge x and y lists from new_walk instance
points = merged(new_walk.x_values, new_walk.y_values)
# Correctly color first and last points of the merged list. I can't believe how
# much work goes into this crap. This is why we use matplotlib...
formatted_points = []
for item in points:
if item == points[0]:
formatted_points.append({"value": item, "color": "green"})
elif item == points[-1]:
formatted_points.append({"value": item, "color": "blue"})
import matplotlib.pyplot as plt
from random_walk import RandomWalk
while True:
rw = RandomWalk()
rw.fill_walk() #num_points个点的数据全部载入
point_numbers = list(range(rw.num_points))
print(point_numbers)
print(rw.x_values)
print(rw.y_values)
plt.scatter(rw.x_values,
rw.y_values,
c=point_numbers,
cmap=plt.cm.Blues,
edgecolor='none',
s=15) #c颜色深浅，越大越深，cmap为色系,c和cmp联用
plt.scatter(rw.x_values[0],
rw.y_values[0],
c='green',
edgecolor='none',
s=100) #起点
plt.scatter(rw.x_values[-1],
rw.y_values[-1],
c='red',
edgecolor='none',
s=100) #终点
plt.show()
keep_running = input("make another walk?(y/n):")
import matplotlib.pyplot as plt from random_walk import RandomWalk #创建一个Randomalk实例，并将其包含的点描绘出来 rw = RandomWalk() #将Randomalk实例保存至rw rw.fill_walk() #调用fill_walk() plt.scatter(rw.x_values, rw.y_values, s=15) #将随机漫步包含的x与y值传递 plt.show()
from random_walk import RandomWalk
from matplotlib import pyplot as plt
# create an object
steps = RandomWalk()
steps.fill_walk()
# create a list representing point sequence
point_numbers = list(range(steps.num_points))
# plot random path
plt.scatter(steps.x_values,
steps.y_values,
s=1,
c=point_numbers,
cmap=plt.cm.Greens)
# plot origin
plt.scatter(0, 0, s=20)
plt.show()
import matplotlib.pyplot as plt from random_walk import RandomWalk # Keep making new walks, as long as the program is active. while True: # Make a random walk, and plot the points. # Adding plot points rw= RandomWalk(50000) # call RandomWalk class rw.fill_walk() # call fill_walk function # Set the size of the plotting window. plt.figure(dpi=128, figsize=(10,6)) # Plot and color the random walking point_numbers = list(range(rw.num_points)) plt.scatter(rw.x_values, rw.y_values, c=point_numbers, cmap=plt.cm.Blues , edgecolor='none', s=2) # Emphasize the first and last points. plt.scatter(0,0, c='green', edgecolor='none' , s=50) plt.scatter(rw.x_values[-1], rw.y_values[-1], c='red', edgecolor='none' ,s=50) # Remove the axes. plt.axes().get_xaxis().set_visible(False) plt.axes().get_yaxis().set_visible(False) plt.show() # ploting
import matplotlib.pyplot as plt
from random_walk import RandomWalk
while True:
# Make a random walk, and plot the points.
rw = RandomWalk()
rw.fill_walk()
# Set the size of tthe plotting window.
plt.figure(figsize=(10, 6))
point_numbers = list(range(rw.num_points))
plt.plot(rw.x_values, rw.y_values, linewidth=5)
# Emphasize the first and las points.
plt.scatter(0, 0, c="green", edgecolors="none", s=100)
plt.scatter(rw.x_values[-1], rw.y_values[-1], c="red", edgecolors="none",
s=100)
# Remove the axes.
plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
plt.show()
keep_running = input("Make anotther walk (y/n): ")
if keep_running == 'n':
break
import matplotlib.pyplot as plt
from random_walk import RandomWalk
while True:
a = RandomWalk(50000)
a.fill_walk()
point_numbers = list(range(a.num_point))
plt.scatter(a.x_points, a.y_points, s=1, c=point_numbers, cmap=plt.cm.Blues)
plt.scatter(0, 0, c='green', s=100)
plt.scatter(a.x_points[-1], a.y_points[-1], c='red', s=100)
plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
# plt.figure(figsize=(5, 3))
plt.show()
keep_running = input("Make another walk? (y/n): ")
if keep_running == 'n':
break
import matplotlib.pyplot as plt
from random_walk import RandomWalk
# Make a random walk and plot the points
while True:
walk = RandomWalk(50000)
walk.fill_walk()
point_numbers = list(range(walk.num_points))
# Set the size of the plot window
plt.figure(dpi=128, figsize=(10, 6))
plt.scatter(walk.x_values, walk.y_values, c=point_numbers, cmap=plt.cm.Blues, edgecolors='none', s=1)
plt.scatter(0, 0, c='green', edgecolors='none', s=100)
plt.scatter(walk.x_values[-1], walk.y_values[-1], c='red', edgecolors='none', s=100)
# Remove the axes
plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
plt.show()
keep_running = input('Make another walk? (y/n) ')
if keep_running.lower() == 'n':
break
import matplotlib.pyplot as plt from random_walk import RandomWalk #创建一个RandomWalk实例 rw = RandomWalk(); rw.fill_walk(); point_numbers = list(range(rw.num_points)) plt.scatter(rw.x_values,rw.y_values,c=point_numbers,cmap=plt.cm.Blues,edgecolors='none',s=10); plt.show();
# -*- coding: utf-8 -*-
"""
Created on Tue Mar 3 14:31:31 2020
@author: jwitherspoon
"""
import pygal
from random_walk import RandomWalk
rw1 = RandomWalk()
rw2 = RandomWalk()
rw3 = RandomWalk()
rw1.fill_walk()
rw2.fill_walk()
rw3.fill_walk()
xy1 = [i for i in zip(rw1.x_values, rw1.y_values)]
xy2 = [i for i in zip(rw2.x_values, rw2.y_values)]
xy3 = [i for i in zip(rw3.x_values, rw3.y_values)]
scatter_chart = pygal.XY(stroke=False)
scatter_chart.title = 'Random Walk'
scatter_chart.add('Step1', xy1)
scatter_chart.add('Step2', xy2)
scatter_chart.add('Step3', xy3)
scatter_chart.render_to_file('randomwalk_xy.svg')
#coding=utf-8
from random_walk import RandomWalk
import matplotlib.pyplot as plt
#while True:
rm = RandomWalk(50000)
rm.fill_walk()
point_numbers = list(range(rm.num_points))
plt.scatter(rm.x_values,
rm.y_values,
c=point_numbers,
cmap=plt.cm.Blues,
s=5,
edgecolor='none')
plt.scatter(0, 0, c='green', edgecolor='none', s=100)
plt.scatter(rm.x_values[-1], rm.y_values[-1], c='red', edgecolor='none', s=100)
# 隐藏坐标轴
plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
plt.show()
# keep_running = raw_input("Make another walk? (y/n): ")
# if keep_running == 'n':
# break
"""This module contains a logic that allows to build random walks visualizations"""
# import
import matplotlib.pyplot as plt
from random_walk import RandomWalk
# create and visualize random walk data set
while True:
random_walk = RandomWalk(
50000) # random walk data set will consist of 50000 points
random_walk.fill_walk()
points_numbers = list(range(random_walk.num_points))
# set plot size
plt.figure(figsize=(10, 6)) # in inches
# set plot title
plt.title('Random walk visualization: {} points'.format(
len(points_numbers)),
loc='center')
# plot random walk
plt.scatter(random_walk.x_values,
random_walk.y_values,
c=points_numbers,
cmap=plt.cm.Blues,
edgecolor='none',
s=1)
# highlight first and last points in the random walk
plt.scatter(0, 0, c='green', edgecolor='none', s=50, label='start point')
plt.scatter(random_walk.x_values[-1],
random_walk.y_values[-1],
# Use the RandomWalk class.
from random_walk import RandomWalk
# Keep making random walks as long as the program is active.
print("Enter 'q' to quit at any time.")
while True:
# Make a walk and plot the points
steps = input("How many steps would you like to take? ")
if steps == 'q':
break
my_walk = RandomWalk(int(steps))
my_walk.fill_walk()
my_walk.plot_walk()
from random_walk import RandomWalk
import pygal
# Generate a random walk dataset with 10,000 points
rw_dataset = RandomWalk(10000)
rw_dataset.fill_walk()
# Helper function for generating xy_pairs from random walk dataset
def get_xy_pairs(random_walk, start, end):
"""Generate a list comprehension from the xy-pairings in *random_walk* in _range(*start*, *end*)_"""
xy_pairs = [(random_walk.x_values[n], random_walk.y_values[n])
for n in range(start, end)]
return xy_pairs
# Display the dataset as a scatter plot and a line graph
line_chart = pygal.XY()
line_chart.title = "Data from a random walk of 10,000 steps"
#line_chart.x_labels
line_chart.add('Steps 0-999', get_xy_pairs(rw_dataset, 0, 1000))
line_chart.add('Steps 1,000-1,999', get_xy_pairs(rw_dataset, 1000, 2000))
line_chart.add('Steps 2,000-2,999', get_xy_pairs(rw_dataset, 2000, 3000))
line_chart.add('Steps 3,000-3,999', get_xy_pairs(rw_dataset, 3000, 4000))
line_chart.add('Steps 4,000-4,999', get_xy_pairs(rw_dataset, 4000, 5000))
line_chart.add('Steps 5,000-5,999', get_xy_pairs(rw_dataset, 5000, 6000))
line_chart.add('Steps 6,000-6,999', get_xy_pairs(rw_dataset, 6000, 7000))
line_chart.add('Steps 7,000-7,999', get_xy_pairs(rw_dataset, 7000, 8000))
line_chart.add('Steps 8,000-8,999', get_xy_pairs(rw_dataset, 8000, 9000))
line_chart.add('Steps 9,000-9,999', get_xy_pairs(rw_dataset, 9000, 10000))
line_chart.render_to_file('rw_walk_test.svg')
#multiple random walk and styling
import matplotlib.pyplot as plt
from random_walk import RandomWalk
while True:
mrw = RandomWalk(50000) #we create a random walk and store it in rw
mrw.fill_walk()
plt.figure(dpi=128,
figsize=(10,
6)) #it control width, height, background, resolution
point_number = list(range(mrw.num_points))
plt.scatter(mrw.x_values,
mrw.y_values,
c=point_number,
cmap=plt.cm.Reds,
edgecolor='none',
s=10)
#Emphasis the first and last points
plt.scatter(0, 0, c='green', edgecolor='none',
s=100) #starting point in Green
plt.scatter(mrw.x_values[-1],
mrw.y_values[-1],
c='red',
edgecolors='none',
s=100) #ending point in Red
plt.savefig('mrw.png', bbox_inches='tight')
plt.show()
keep_running = input("Make Another walk (Y/N): ")
if keep_running == 'n':
break
import matplotlib.pyplot as plt
from random_walk import RandomWalk
# Use RandomWalk class to generate this plot
mol = RandomWalk()
mol.fill_walk()
# Set the size of the plotting window.
plt.figure(figsize=(12, 6))
point_numbers = list(range(mol.num_points))
plt.plot(mol.x_values, mol.y_values, c='purple', linewidth=1.2)
# Emphasize the first and last points.
plt.scatter(0, 0, c='green', edgecolors='none', s=60)
plt.scatter(mol.x_values[-1],
mol.y_values[-1],
c='red',
edgecolors='none',
s=60)
# Remove the axes.
plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
plt.show()
import matplotlib.pyplot as plt
from statistics import median
from random_walk import RandomWalk
while True: #keep making new walks as long as the program is active
#make a random walk and plot the points
rw = RandomWalk(
10000
) #the input here is basically running the class with this number of points since it
#is feeding the 'point numbers' attribute for the class
rw.fill_walk(rw.get_step)
point_numbers = list(
range(rw.num_points)
) #make a list from 0-the number of points we set in the call to the class
plt.scatter(rw.x_values,
rw.y_values,
c=point_numbers,
cmap=plt.cm.Reds,
s=5) #we plot the scatter points and we use
#the 'point number' to gradually darken the scatter as the number of points plotted increases to show the path of the walk
#settings for the axes and title of graph
plt.title('Random Walk', fontsize=14)
plt.xlabel('X Values', fontsize=10)
plt.ylabel('Y Values', fontsize=10)
#this is to hide the axes to get a pure view of our scatter
#plt.axes().get_xaxis().set_visible(False)
#plt.axes().get_yaxis().set_visible(False)
import matplotlib.pyplot as plt
from random_walk import RandomWalk
#传进一个RandomWalk实例，并将其包含的点都绘制出来
rw = RandomWalk(5000)
rw.fill_walk([1], [1, 2, 3, 4, 5, 6, 7, 8], [1, -1])
point_numbers = list(range(rw.num_points))
plt.scatter(rw.x_values,
rw.y_values,
s=10,
edgecolors='none',
c=point_numbers,
cmap=plt.cm.Blues)
#plt.scatter(rw.x_values, rw.y_values, s=10, edgecolors='none', c='red')
plt.title("Random Walk")
#隐藏坐标轴
# plt.axes().get_xaxis().set_visible(False)
# plt.axes().get_yaxis().set_visible(False)
plt.show()
import matplotlib.pyplot as plt
from random_walk import RandomWalk
#只要程序活跃就不断的模拟随机漫步
while True:
# 创建一个RandomWalk实例, 并将其包含的点都绘制出来
rw = RandomWalk(50000)
rw.fill_walk() #生成随机漫步坐标列表
#设置绘图窗口的分辨率与尺寸
plt.figure( dpi=128, figsize=(10, 6))
#生成一个有num_points数目个数的列表
point_numbers = list(range(rw.num_points))
plt.scatter(rw.x_values, rw.y_values, c=point_numbers, cmap=plt.cm.Blues,
edgecolor='none', s=1) #绘制散点图,按顺序着色深浅,删除黑色轮廓,大小为10
#突出起点和终点
plt.scatter(0, 0, c='green', edgecolor='none', s=50)
plt.scatter(rw.x_values[-1], rw.y_values[-1], c='red', edgecolor='none',
s=50) #显示列表中的最后一个点
#隐藏坐标轴
plt.axes().get_xaxis().set_visible(False)
plt.axes().get_yaxis().set_visible(False)
plt.show()
#判断
keep_running = input("Make it running again? (y/n)") #输入语句
if keep_running == 'n': #如果是'n'就结束循环
import matplotlib.pyplot as plt
from random_walk import RandomWalk
while True:
rw = RandomWalk(50000)
rw.fill_walk()
plt.figure(figsize=(10, 6))
point_numbers = list(range(rw.num_points))
#Emphasize the first and last point
#plt.scatter(0, 0, c='green', edgecolors='none', s=100)
#plt.scatter(rw.x_values[-1], rw.y_values[-1], c='red', edgecolor='none', s=100)
#Remove the axes.
#plt.axes().get_xaxis().set_visible(False)
#plt.axes().get_yaxis().set_visible(False)
plt.scatter(rw.x_values, rw.y_values, c=point_numbers, cmap=plt.cm.Blues, edgecolor='none', s=15)
plt.scatter(rw.x_values, rw.y_values, s=15)
plt.show()
keep_running = raw_input("Make another walk? (y/n): ")
if keep_running == 'n':
break
import matplotlib.pyplot as plt
from random_walk import RandomWalk
grain_path = RandomWalk(5000)
grain_path.fill_walk()
point_numbers = range(grain_path.num_points)
plt.style.use('classic')
fig, ax = plt.subplots(figsize=(15, 9))
ax.plot(grain_path.x_values, grain_path.y_values, linewidth=1, c='blue')
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
plt.savefig('pollen_grain.png', bbox_inches='tight')
plt.show()
