def test_plotBinningError(self): """ Tests the plotting of a trace with a certain amount of sampling that had a binning problem. """ tr = Trace(data=np.sin(np.linspace(0, 200, 432000))) outfile = os.path.join(self.path, 'binning_error.png') tr.plot(outfile=outfile)
def test_plot_binning_error_2(self, image_path): """ Tests the plotting of a trace with a certain amount of sampling that had a binning problem. """ tr = Trace(data=np.sin(np.linspace(0, 200, 431979))) # create and compare image tr.plot(outfile=image_path)
def test_plot(self): """ Tests plot method if matplotlib is installed """ try: import matplotlib # @UnusedImport except ImportError: return tr = Trace(data=np.arange(25)) tr.plot(show=False)
def test_plot(self): """ Tests plot method if matplotlib is installed """ try: import matplotlib except ImportError: return tr = Trace(data=np.arange(25)) tr.plot(show=False)
def test_plotBinningError(self): """ Tests the plotting of a trace with a certain amount of sampling that had a binning problem. """ tr = Trace(data=np.sin(np.linspace(0, 200, 432000))) # create and compare image with ImageComparison(self.path, 'waveform_binning_error.png') as ic: tr.plot(outfile=ic.name) tr = Trace(data=np.sin(np.linspace(0, 200, 431979))) # create and compare image with ImageComparison(self.path, 'waveform_binning_error_2.png') as ic: tr.plot(outfile=ic.name)
def test_plot_binning_error(self): """ Tests the plotting of a trace with a certain amount of sampling that had a binning problem. """ tr = Trace(data=np.sin(np.linspace(0, 200, 432000))) # create and compare image with ImageComparison(self.path, 'waveform_binning_error.png') as ic: tr.plot(outfile=ic.name) tr = Trace(data=np.sin(np.linspace(0, 200, 431979))) # create and compare image with ImageComparison(self.path, 'waveform_binning_error_2.png') as ic: tr.plot(outfile=ic.name)
def pca_display(pca, original_trace, transformed_wiggle, reconstructed_wiggle): original_wiggle = original_trace.data IPython.display.display( IPython.display.Audio(data=original_wiggle, rate=playback_sampling_rate)) IPython.display.display( IPython.display.Audio(data=reconstructed_wiggle, rate=playback_sampling_rate)) plot_wiggle(transformed_wiggle) reduced_trace = Trace(data=reconstructed_wiggle, header=None) print("principal_component length: " + str(len(reduced_trace))) print("PCA Variance Ratio: ") print(pca.explained_variance_ratio_) original_trace.plot() reduced_trace.plot()
def test_plotBinningError(self): """ Tests the plotting of a trace with a certain amount of sampling that had a binning problem. """ tr = Trace(data=np.sin(np.linspace(0, 200, 432000))) # create and compare image with NamedTemporaryFile(suffix='.png') as tf: tr.plot(outfile=tf.name) # compare images expected_image = os.path.join(self.path, 'waveform_binning_error.png') compare_images(tf.name, expected_image, 0.001) tr = Trace(data=np.sin(np.linspace(0, 200, 431979))) # create and compare image with NamedTemporaryFile(suffix='.png') as tf: tr.plot(outfile=tf.name) # compare images expected_image = os.path.join(self.path, 'waveform_binning_error_2.png') compare_images(tf.name, expected_image, 0.001)
def plot_helicorder(tr: Trace, outfile: str = None, **kwargs) -> plt.Axes: """ Plot a helicorder style plot. 1 channel for a day of data. Defaults to showing 60 minutes of data per line in the helicorder. :param st: Obspy Trace object of data to plot :type st: Stream :param **kwargs: Valid Stream.plot(type='dayplot') parameters :return: ax containing plot :rtype: plt.Axes """ fig = tr.plot(type='dayplot', interval=60, show_y_UTC_label=False, outfile=outfile, **kwargs) return fig
plt.psd(y,NFFT=nfft, pad_to=nfft, Fs=fs,noverlap=nfft//2,detrend='mean') plt.title("demean") plt.show() #https://github.com/obspy/obspy/issues/1095 # write out a seed file to put into other code. tr=Trace() tr.stats.station='KAS' tr.stats.network='XX' tr.stats.channel='00' tr.stats.location='BHZ' tr.data=y tr.data = np.require(tr.data, dtype=np.int32) tr.stats.sampling_rate=40. tr.starttime=UTCDateTime('2017-09-19T00:00:00') tr.stats.encoding='STEIM1' tr.stats.reclen=512 print(tr.stats['starttime']) print(tr.stats['endtime']) tr.plot() st=Stream() st+=tr print(st[0].stats) print(st[0].data.dtype) st.write('XX_KAS.00_BHZ.seed', format='MSEED') #st.write('XX_KAS.00_BHZ.seed', format='MSEED', encoding='STEIM2') #shift_time_of_file(fileIn, fileOut, 10000) #