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x = [1, 2, 3]
>>> y = np.array([[1, 2], [3, 4], [5, 6]])
>>> plot(x, y)
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import matplotlib.pyplot as plt
fig = plt.figure(1) #identifies the figure
plt.title("Y vs X", fontsize='16') #title
plt.plot([1, 2, 3, 4], [6,2,8,4]) #plot the points (x_axis, y_axis)
plt.xlabel("X",fontsize='13') #adds a label in the x axis
plt.ylabel("Y",fontsize='13') #adds a label in the y axis
plt.legend(('YvsX'),loc='best') #creates a legend to identify the plot
plt.savefig('Y_X.png') #saves the figure in the present directory
plt.grid() #shows a grid under the plot
plt.show()
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import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4], [1, 4, 9, 16])
plt.show()
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import matplotlib.pyplot as plt
%matplotlib inline
plt.plot(data)
#this is not nessisary but makes your plot more readable
plt.ylabel('y axis means ...')
plt.xlabel('x axis means ...')
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import numpy as np
import matplotlib.pyplot as plt
x = np.arange(0, 5, 0.1);
y = np.sin(x)
plt.plot(x, y)
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import matplotlib.pyplot as plt
x=[0,10,20,30,60,90]
y=[-4.39,-4.69,-4.99,-5.30,-6.21,-7.13]
fig=plt.figure()
ax=fig.add_axes([0,0,1,1]) #grand
plt.plot(x,y)
plt.show()
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import matplotlib.pyplot as plt
import numpy as np
# Generate pseudo-random numbers:
np.random.seed(0)
# Sampling interval:
dt = 0.01
# Sampling Frequency:
Fs = 1 / dt # ex[;aom Fs]
# Generate noise:
t = np.arange(0, 10, dt)
res = np.random.randn(len(t))
r = np.exp(-t / 0.05)
# Convolve 2 signals (functions):
conv_res = np.convolve(res, r)*dt
conv_res = conv_res[:len(t)]
s = 0.5 * np.sin(1.5 * np.pi * t) + conv_res
# Create the plot:
fig, (ax) = plt.subplots()
ax.plot(t, s)
# Function plots phase spectrum:
ax.phase_spectrum(s, Fs = Fs)
plt.title(“Phase Spectrum Plot”)
plt.show()
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x = [1, 2, 3]
>>> y = np.array([[1, 2], [3, 4], [5, 6]])
>>> plot(x, y)
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plot([x], y, [fmt], *, data=None, **kwargs)
plot([x], y, [fmt], [x2], y2, [fmt2], , **kwargs)