Trazado de gráficos en Python | Serie 1
subtramas
Python
# importing required modules
import matplotlib.pyplot as plt
import numpy as np
# function to generate coordinates
def create_plot(ptype):
# setting the x-axis values
x = np.arange(-10, 10, 0.01)
# setting the y-axis values
if ptype == 'linear':
y = x
elif ptype == 'quadratic':
y = x**2
elif ptype == 'cubic':
y = x**3
elif ptype == 'quartic':
y = x**4
return(x, y)
# setting a style to use
plt.style.use('fivethirtyeight')
# create a figure
fig = plt.figure()
# define subplots and their positions in figure
plt1 = fig.add_subplot(221)
plt2 = fig.add_subplot(222)
plt3 = fig.add_subplot(223)
plt4 = fig.add_subplot(224)
# plotting points on each subplot
x, y = create_plot('linear')
plt1.plot(x, y, color ='r')
plt1.set_title('$y_1 = x$')
x, y = create_plot('quadratic')
plt2.plot(x, y, color ='b')
plt2.set_title('$y_2 = x^2$')
x, y = create_plot('cubic')
plt3.plot(x, y, color ='g')
plt3.set_title('$y_3 = x^3$')
x, y = create_plot('quartic')
plt4.plot(x, y, color ='k')
plt4.set_title('$y_4 = x^4$')
# adjusting space between subplots
fig.subplots_adjust(hspace=.5,wspace=0.5)
# function to show the plot
plt.show()
Python
# importing required modules
import matplotlib.pyplot as plt
import numpy as np
# function to generate coordinates
def create_plot(ptype):
# setting the x-axis values
x = np.arange(0, 5, 0.01)
# setting y-axis values
if ptype == 'sin':
# a sine wave
y = np.sin(2*np.pi*x)
elif ptype == 'exp':
# negative exponential function
y = np.exp(-x)
elif ptype == 'hybrid':
# a damped sine wave
y = (np.sin(2*np.pi*x))*(np.exp(-x))
return(x, y)
# setting a style to use
plt.style.use('ggplot')
# defining subplots and their positions
plt1 = plt.subplot2grid((11,1), (0,0), rowspan = 3, colspan = 1)
plt2 = plt.subplot2grid((11,1), (4,0), rowspan = 3, colspan = 1)
plt3 = plt.subplot2grid((11,1), (8,0), rowspan = 3, colspan = 1)
# plotting points on each subplot
x, y = create_plot('sin')
plt1.plot(x, y, label = 'sine wave', color ='b')
x, y = create_plot('exp')
plt2.plot(x, y, label = 'negative exponential', color = 'r')
x, y = create_plot('hybrid')
plt3.plot(x, y, label = 'damped sine wave', color = 'g')
# show legends of each subplot
plt1.legend()
plt2.legend()
plt3.legend()
# function to show plot
plt.show()
Python
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import style
import numpy as np
# setting a custom style to use
style.use('ggplot')
# create a new figure for plotting
fig = plt.figure()
# create a new subplot on our figure
# and set projection as 3d
ax1 = fig.add_subplot(111, projection='3d')
# defining x, y, z co-ordinates
x = np.random.randint(0, 10, size = 20)
y = np.random.randint(0, 10, size = 20)
z = np.random.randint(0, 10, size = 20)
# plotting the points on subplot
# setting labels for the axes
ax1.set_xlabel('x-axis')
ax1.set_ylabel('y-axis')
ax1.set_zlabel('z-axis')
# function to show the plot
plt.show()
Python
# importing required modules
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import style
import numpy as np
# setting a custom style to use
style.use('ggplot')
# create a new figure for plotting
fig = plt.figure()
# create a new subplot on our figure
ax1 = fig.add_subplot(111, projection='3d')
# defining x, y, z co-ordinates
x = np.random.randint(0, 10, size = 5)
y = np.random.randint(0, 10, size = 5)
z = np.random.randint(0, 10, size = 5)
# plotting the points on subplot
ax1.plot_wireframe(x,y,z)
# setting the labels
ax1.set_xlabel('x-axis')
ax1.set_ylabel('y-axis')
ax1.set_zlabel('z-axis')
plt.show()
Python
# importing required modules
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import style
import numpy as np
# setting a custom style to use
style.use('ggplot')
# create a new figure for plotting
fig = plt.figure()
# create a new subplot on our figure
ax1 = fig.add_subplot(111, projection='3d')
# defining x, y, z co-ordinates for bar position
x = [1,2,3,4,5,6,7,8,9,10]
y = [4,3,1,6,5,3,7,5,3,7]
z = np.zeros(10)
# size of bars
dx = np.ones(10) # length along x-axis
dy = np.ones(10) # length along y-axs
dz = [1,3,4,2,6,7,5,5,10,9] # height of bar
# setting color scheme
color = []
for h in dz:
if h > 5:
color.append('r')
else:
color.append('b')
# plotting the bars
ax1.bar3d(x, y, z, dx, dy, dz, color = color)
# setting axes labels
ax1.set_xlabel('x-axis')
ax1.set_ylabel('y-axis')
ax1.set_zlabel('z-axis')
plt.show()
Python
# importing required modules
from mpl_toolkits.mplot3d import axes3d
import matplotlib.pyplot as plt
from matplotlib import style
import numpy as np
# setting a custom style to use
style.use('ggplot')
# create a new figure for plotting
fig = plt.figure()
# create a new subplot on our figure
ax1 = fig.add_subplot(111, projection='3d')
# get points for a mesh grid
u, v = np.mgrid[0:2*np.pi:200j, 0:np.pi:100j]
# setting x, y, z co-ordinates
x=np.cos(u)*np.sin(v)
y=np.sin(u)*np.sin(v)
z=np.cos(v)
# plotting the curve
ax1.plot_wireframe(x, y, z, rstride = 5, cstride = 5, linewidth = 1)
plt.show()
Publicación traducida automáticamente
Artículo escrito por GeeksforGeeks-1 y traducido por Barcelona Geeks. The original can be accessed here. Licence: CCBY-SA