import numpy as np
import matplotlib.pyplot as plt


def sweep(x, sweep_time, fs):

    plt.subplots_adjust(hspace=0.4)
    t = np.arange(0, sweep_time, 1 / fs)
    p = 20 * np.log10(abs(np.fft.rfft(x)))
    f = np.linspace(0, fs / 2, len(p))
    plt.figure(1)
    plt.subplot(211)
    plt.plot(t, x)
    plt.grid()
    plt.xlabel('t / s')
    plt.ylabel('x(t)')
    plt.title('time domain')
    plt.subplot(212)
    plt.plot(f, p)
    plt.xscale('log')
    plt.grid()
    plt.xlabel('f / Hz')
    plt.ylabel('A / dB')
    plt.title('frequency domain')
    plt.show()

import numpy as np
import scipy as sp
import matplotlib.pyplot as plt


def sweep(x, sweep_time, fs):

    t = np.arange(0, sweep_time, 1 / fs)
    p = 20 * np.log10(abs(sp.fft(x)))
    f = np.linspace(0, fs / 2, len(p))
    plt.figure(1)
    plt.subplot(211)
    plt.plot(t, x)
    plt.grid()
    plt.subplot(212)
    plt.plot(f, p)
    plt.xscale('log')
    plt.grid()
    plt.show()

--- 
+++ 
@@ -1,19 +1,25 @@
 import numpy as np
-import scipy as sp
 import matplotlib.pyplot as plt
 
 
 def sweep(x, sweep_time, fs):
 
+    plt.subplots_adjust(hspace=0.4)
     t = np.arange(0, sweep_time, 1 / fs)
-    p = 20 * np.log10(abs(sp.fft(x)))
+    p = 20 * np.log10(abs(np.fft.rfft(x)))
     f = np.linspace(0, fs / 2, len(p))
     plt.figure(1)
     plt.subplot(211)
     plt.plot(t, x)
     plt.grid()
+    plt.xlabel('t / s')
+    plt.ylabel('x(t)')
+    plt.title('time domain')
     plt.subplot(212)
     plt.plot(f, p)
     plt.xscale('log')
     plt.grid()
+    plt.xlabel('f / Hz')
+    plt.ylabel('A / dB')
+    plt.title('frequency domain')
     plt.show()
Add axis label and change import
