def callback():
if not os.path.isfile(e.get()):
textabc = tkinter.Text(top, height=1, font="font, 20", width=20)
textabc.insert(tkinter.INSERT, "File does not exist!")
textabc.config(state=tkinter.DISABLED, bg="#f0f0f0", bd=0)
textabc.pack()
else:
stsdatacheck = e.get()
if ".stsdata" not in stsdatacheck:
filemanager.wpitch(s.get() + 1)
filemanager.wlength(l.get())
filemanager.wpath(e.get())
top.withdraw()
import curve # next part in script, to keep it readable
if qdebug.get() == 1:
curve.write()
sys.exit()
else:
importdata.data(e.get(), l.get())
def plotPair(number):
dataset = data()
subplot = 210
plt.figure(figsize=(5, 8), dpi=160)
for key in dataset:
subplot += 1
plt.subplot(subplot)
plt.plot(dataset[key][number])
plt.ylim(0, 27)
plt.title('{} raw signal'.format(key))
plt.ylabel('acceleration')
plt.xlabel('samples')
plt.subplots_adjust(hspace=0.53)
plt.savefig('presentation/figures/rawplot.png')
#!python from numpy import cos, sin, pi, absolute, arange from scipy.signal import kaiserord, lfilter, firwin, freqz from pylab_test import figure, clf, plot, xlabel, ylabel, xlim, ylim, title, grid, axes, show from importdata import data #------------------------------------------------ # Create a signal for demonstration. #------------------------------------------------ dataset = data() sample_rate = 100.0 nsamples = len(dataset['walk'][1]) t = arange(nsamples) / sample_rate x = dataset['walk'][1] #------------------------------------------------ # Create a FIR filter and apply it to x. #------------------------------------------------ # The Nyquist rate of the signal. nyq_rate = sample_rate / 2.0 # The desired width of the transition from pass to stop, # relative to the Nyquist rate. We'll design the filter # with a 5 Hz transition width. width = 1.0 / nyq_rate # The desired attenuation in the stop band, in dB.
shape = 410
fir.plot_impulse_response(subplot=shape + count)
count += 1
fir.plot_step_responce(subplot=shape + count)
count += 1
# fir.plot_magnitude(shape + count)
# count += 1
fir.plot_frequesy_response(shape + count)
count += 1
fir.plot_phase_response(shape + count)
plt.subplots_adjust(hspace=0.3)
plt.savefig("presentation/figures/{}".format(savefig))
if __name__ == '__main__':
data = data()
plt.rc('text', usetex=True)
higpa_cutoff_hz = 2.0
# --------- Lopass filterd signals------------
fig = plt.figure(figsize=(8, 13), tight_layout=False)
fig.suptitle("LOW pass filterd signal")
plot_filter_results(data, savefig="plot_lti_lopasl.png")
# --------- Highpass filterd signals------------
fig = plt.figure(figsize=(8, 13), tight_layout=False)
fig.suptitle("HIGH pass filterd signal", fontsize=18)
plot_filter_results(data,
savefig='plot_lti_higpas.png',
cutoff_hz=higpa_cutoff_hz,
hp=True)
# # --------- Lopass filter plot ------------