FFT_tools: cleanup namespace by using _pyplot

diff --git a/FFT_tools.py b/FFT_tools.py
index 3383c0864f9fcc4d52c707fdd3805abe1cd2ee46..1c3455fda40502bc159e068de2455c5182bb5c52 100644 (file)
--- a/FFT_tools.py
+++ b/FFT_tools.py
@@ -207,15 +207,15 @@ def _test_unitary_rfft_rect(a=1.0, time_shift=5.0, samp_freq=25.6, samples=256)
         expected[i] = 1.0/_numpy.abs(a) * _numpy.sinc(f/a)
 
     if TEST_PLOTS :
         expected[i] = 1.0/_numpy.abs(a) * _numpy.sinc(f/a)
 
     if TEST_PLOTS :

-        pylab.figure()
-        pylab.subplot(211)
-        pylab.plot(_numpy.arange(0, dt*samples, dt), x)
-        pylab.title('time series')
-        pylab.subplot(212)
-        pylab.plot(freq_axis, X.real, 'r.')
-        pylab.plot(freq_axis, X.imag, 'g.')
-        pylab.plot(freq_axis, expected, 'b-')
-        pylab.title('freq series')
+        figure = _pyplot.figure()
+        time_axes = figure.add_subplot(2, 1, 1)
+        time_axes.plot(_numpy.arange(0, dt*samples, dt), x)
+        time_axes.set_title('time series')
+        freq_axes = figure.add_subplot(2, 1, 2)
+        freq_axes.plot(freq_axis, X.real, 'r.')
+        freq_axes.plot(freq_axis, X.imag, 'g.')
+        freq_axes.plot(freq_axis, expected, 'b-')
+        freq_axes.set_title('freq series')

 
 def _test_unitary_rfft_rect_suite() :
     print('Test unitary FFTs on variously shaped rectangular functions')
 
 def _test_unitary_rfft_rect_suite() :
     print('Test unitary FFTs on variously shaped rectangular functions')


@@ -255,15 +255,15 @@ def _test_unitary_rfft_gaussian(a=1.0, time_shift=5.0, samp_freq=25.6, samples=2
             1.0/a, _numpy.pi*f)
 
     if TEST_PLOTS :
             1.0/a, _numpy.pi*f)
 
     if TEST_PLOTS :

-        pylab.figure()
-        pylab.subplot(211)
-        pylab.plot(_numpy.arange(0, dt*samples, dt), x)
-        pylab.title('time series')
-        pylab.subplot(212)
-        pylab.plot(freq_axis, X.real, 'r.')
-        pylab.plot(freq_axis, X.imag, 'g.')
-        pylab.plot(freq_axis, expected, 'b-')
-        pylab.title('freq series')
+        figure = _pyplot.figure()
+        time_axes = figure.add_subplot(2, 1, 1)
+        time_axes.plot(_numpy.arange(0, dt*samples, dt), x)
+        time_axes.set_title('time series')
+        freq_axes = figure.add_subplot(2, 1, 2)
+        freq_axes.plot(freq_axis, X.real, 'r.')
+        freq_axes.plot(freq_axis, X.imag, 'g.')
+        freq_axes.plot(freq_axis, expected, 'b-')
+        freq_axes.set_title('freq series')

 
 def _test_unitary_rfft_gaussian_suite() :
     print("Test unitary FFTs on variously shaped gaussian functions")
 
 def _test_unitary_rfft_gaussian_suite() :
     print("Test unitary FFTs on variously shaped gaussian functions")


@@ -366,14 +366,16 @@ def _test_unitary_power_spectrum_sin(sin_freq=10, samp_freq=512, samples=1024) :
     print('The total power should be {} ({})'.format(Pexp, P))
 
     if TEST_PLOTS :
     print('The total power should be {} ({})'.format(Pexp, P))
 
     if TEST_PLOTS :

-        pylab.figure()
-        pylab.subplot(211)
-        pylab.plot(_numpy.arange(0, samples/samp_freq, 1.0/samp_freq), x, 'b-')
-        pylab.title('time series')
-        pylab.subplot(212)
-        pylab.plot(freq_axis, power, 'r.')
-        pylab.plot(freq_axis, expected, 'b-')
-        pylab.title('{} samples of sin at {} Hz'.format(samples, sin_freq))
+        figure = _pyplot.figure()
+        time_axes = figure.add_subplot(2, 1, 1)
+        time_axes.plot(
+            _numpy.arange(0, samples/samp_freq, 1.0/samp_freq), x, 'b-')
+        time_axes.set_title('time series')
+        freq_axes = figure.add_subplot(2, 1, 2)
+        freq_axes.plot(freq_axis, power, 'r.')
+        freq_axes.plot(freq_axis, expected, 'b-')
+        freq_axes.set_title(
+            '{} samples of sin at {} Hz'.format(samples, sin_freq))

 
 def _test_unitary_power_spectrum_sin_suite() :
     print('Test unitary power spectrums on variously shaped sin functions')
 
 def _test_unitary_power_spectrum_sin_suite() :
     print('Test unitary power spectrums on variously shaped sin functions')


@@ -412,14 +414,15 @@ def _test_unitary_power_spectrum_delta(amp=1, samp_freq=1, samples=256) :
         expected_amp, power[0]))
 
     if TEST_PLOTS :
         expected_amp, power[0]))
 
     if TEST_PLOTS :

-        pylab.figure()
-        pylab.subplot(211)
-        pylab.plot(_numpy.arange(0, samples/samp_freq, 1.0/samp_freq), x, 'b-')
-        pylab.title('time series')
-        pylab.subplot(212)
-        pylab.plot(freq_axis, power, 'r.')
-        pylab.plot(freq_axis, expected, 'b-')
-        pylab.title('{} samples of delta amp {}'.format(samples, amp))
+        figure = _pyplot.figure()
+        time_axes = figure.add_subplot(2, 1, 1)
+        time_axes.plot(
+            _numpy.arange(0, samples/samp_freq, 1.0/samp_freq), x, 'b-')
+        time_axes.set_title('time series')
+        freq_axes = figure.add_subplot(2, 1, 2)
+        freq_axes.plot(freq_axis, power, 'r.')
+        freq_axes.plot(freq_axis, expected, 'b-')
+        freq_axes.set_title('{} samples of delta amp {}'.format(samples, amp))

 
 def _test_unitary_power_spectrum_delta_suite() :
     print('Test unitary power spectrums on various delta functions')
 
 def _test_unitary_power_spectrum_delta_suite() :
     print('Test unitary power spectrums on various delta functions')


@@ -469,14 +472,15 @@ def _test_unitary_power_spectrum_gaussian(area=2.5, mean=5, std=1, samp_freq=10.
             expected[0], power[0]))
 
     if TEST_PLOTS :
             expected[0], power[0]))
 
     if TEST_PLOTS :

-        pylab.figure()
-        pylab.subplot(211)
-        pylab.plot(_numpy.arange(0, samples/samp_freq, 1.0/samp_freq), x, 'b-')
-        pylab.title('time series')
-        pylab.subplot(212)
-        pylab.plot(freq_axis, power, 'r.')
-        pylab.plot(freq_axis, expected, 'b-')
-        pylab.title('freq series')
+        figure = _pyplot.figure()
+        time_axes = figure.add_subplot(2, 1, 1)
+        time_axes.plot(
+            _numpy.arange(0, samples/samp_freq, 1.0/samp_freq), x, 'b-')
+        time_axes.set_title('time series')
+        freq_axes = figure.add_subplot(2, 1, 2)
+        freq_axes.plot(freq_axis, power, 'r.')
+        freq_axes.plot(freq_axis, expected, 'b-')
+        freq_axes.set_title('freq series')

 
 def _test_unitary_power_spectrum_gaussian_suite() :
     print('Test unitary power spectrums on various gaussian functions')
 
 def _test_unitary_power_spectrum_gaussian_suite() :
     print('Test unitary power spectrums on various gaussian functions')


@@ -585,14 +589,16 @@ def _test_unitary_avg_power_spectrum_sin(sin_freq=10, samp_freq=512, samples=102
     print('The total power should be {} ({})'.format(Pexp, P))
 
     if TEST_PLOTS :
     print('The total power should be {} ({})'.format(Pexp, P))
 
     if TEST_PLOTS :

-        pylab.figure()
-        pylab.subplot(211)
-        pylab.plot(_numpy.arange(0, samples/samp_freq, 1.0/samp_freq), x, 'b-')
-        pylab.title('time series')
-        pylab.subplot(212)
-        pylab.plot(freq_axis, power, 'r.')
-        pylab.plot(freq_axis, expected, 'b-')
-        pylab.title('{} samples of sin at {} Hz'.format(samples, sin_freq))
+        figure = _pyplot.figure()
+        time_axes = figure.add_subplot(2, 1, 1)
+        time_axes.plot(
+            _numpy.arange(0, samples/samp_freq, 1.0/samp_freq), x, 'b-')
+        time_axes.set_title('time series')
+        freq_axes = figure.add_subplot(2, 1, 2)
+        freq_axes.plot(freq_axis, power, 'r.')
+        freq_axes.plot(freq_axis, expected, 'b-')
+        freq_axes.set_title(
+            '{} samples of sin at {} Hz'.format(samples, sin_freq))

 
 def _test_unitary_avg_power_spectrum_sin_suite() :
     print('Test unitary avg power spectrums on variously shaped sin functions')
 
 def _test_unitary_avg_power_spectrum_sin_suite() :
     print('Test unitary avg power spectrums on variously shaped sin functions')


@@ -628,8 +634,8 @@ if __name__ == '__main__':
     options,args = p.parse_args()
 
     if options.plot:
     options,args = p.parse_args()
 
     if options.plot:

-        import pylab
+        import matplotlib.pyplot as _pyplot

         TEST_PLOTS = True
     test()
     if options.plot:
         TEST_PLOTS = True
     test()
     if options.plot:

-        pylab.show()
+        _pyplot.show()