raspberry pi - Make Python FFT code faster -

can me make python code faster? @ moment reach 11 meassurements per second. hope faster don't know how it.

import matplotlib.pyplot plt import matplotlib.animation animation import numpy np import time pylab import * ################################################################### import accelneu accel import rpi.gpio gpio scipy.fftpack import fft gpio.setmode(gpio.bcm) high=true low=false ###variablendefinitionen: ##adda wandler: #pins: sclk        = 18    #taktuhr mosi        = 24    #master-out-slave-in miso        = 23    #master-in-slave-out cs1         = 25    #chip-select 1  (a/d) cs2         = 12    #chip-select 2  (d/a) cs3         = 4     #chip-select 2  (acceleration) #sonst infos: numbit1         = 12    # in anzahl bits ic 1  (a/d) numbit2         = 10    # out anzahl bits ic 2  (d/a) #variablendefinition voltagemaxin    = 5.000 voltagemaxout   = 4.0955 #maximalspannung voltage = 2.500 ##drucksensor: voltageoffset       = 0.014652014652014652  #v spannungsoffset typ:20mv pressuresensitivity = 0.0035                #v/kpa empfindlichkeit #accelerationsensitivity = 0.015625 ##gpios   gpio.setup(sclk, gpio.out) gpio.setup(mosi, gpio.out) gpio.setup(miso, gpio.in) gpio.setup(cs1, gpio.out) gpio.setup(cs2, gpio.out) gpio.setup(cs3, gpio.out)  ####################### xlimit=500 fig=figure(figsize=(8,7),dpi=100) x=[i+1 in range (xlimit)] y=[0 in range (xlimit)] ax1=fig.add_subplot(211) ax2=fig.add_subplot(212) line1, =ax1.plot(x,y,'r-') line2, =ax2.plot(x,y,'g-') ax1.set_ylim([-0.5, 2.5]) ax2.set_ylim([0, 0.4]) ############################################################ #fft:  n=xlimit    #512#1000         #number of samplepoints/sampling rate spacing=2048    #1024 t=1.0/spacing          #sample spacing/sampling interval xf=np.linspace(0.0, 1.0/(2.0*t), n/2) line2.set_xdata(xf[1:n/2-1]) ############################################################ def animate(i):     t0=time.time()     y[1:]=y[:-1]    ##zeitraum 1     t1=time.time()     y[0],z=accel.readaxisacceleration(1)    ##zeitraum 2     t2=time.time()     line1.set_ydata(y)    ##zeitraum 3     t3=time.time()     ffty=fft(y)    ##zeitraum 4     t4=time.time()     ffty=ffty[1:n/2-1]    ##zeitraum 5     t5=time.time()     line2.set_ydata(2.0/n*np.abs(ffty[0:n/2]))#ffty)    ##zeitraum 6     t6=time.time()     print(t1-t0,t2-t1,t3-t2,t4-t3,t5-t4,t6-t5)     return line1, line2 #lines t7=time.time() ani =animation.funcanimation(fig,animate,xrange(1,200),interval=0,blit=true) t8=time.time() print (t8-t7) plt.show() 

maybe can tell me how make faster. class accelneu function reads out data acceleration sensor (not source of slow behaviour, profiled this).