コード例 #1
0
def average_signals(directory, files, channels):
    avg_signals = np.zeros((3, 5119))
    for file in files:
        (times, signals) = labview.load_data(directory, file, channels=channels)
        avg_signals += signals
    avg_signals /= len(files)
    return (times, avg_signals)
コード例 #2
0
    mpl.rcParams['figure.subplot.top'] = 0.9
    mpl.rcParams['figure.subplot.bottom'] = 0.1
    mpl.rcParams['figure.subplot.wspace'] = 0.2
    mpl.rcParams['figure.subplot.hspace'] = 0.2


reset_plot_params()

lv_directory = "C:\\Users\\plane\\Desktop\\Data\\HPRF\\HPRF 20120605\sparks_29p5MV-M_15Hz\\"
#lv_file = "reduced_53_55.npz"
lv_file = "spark_53_55.npz"

#(times, signals) = labview.load_data(lv_directory, lv_file, t0=286.4e-3, t1=286.6e-3,
(times, signals) = labview.load_data(lv_directory,
                                     lv_file,
                                     t0=286.377e-3,
                                     t1=286.8e-3,
                                     channels=[0, 1, 2, 3, 4, 5, 6])
signal = signals[5] / np.max(signals[5])
damped_signal = [
    signal[x] * (math.exp(1 - times[x] / 2.0e-5)) for x in range(len(signal))
]
damped_signal = damped_signal / np.max(damped_signal)
fig = plt.figure(figsize=(12, 7))
fig.text(0.04,
         0.52,
         'Normalized Amplitude',
         ha='center',
         va='center',
         rotation='vertical')
plt.subplot(211)
コード例 #3
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    mpl.rcParams['figure.subplot.right'] = 0.98
    mpl.rcParams['figure.subplot.top'] = 0.9
    mpl.rcParams['figure.subplot.bottom'] = 0.1
    mpl.rcParams['figure.subplot.wspace'] = 0.2
    mpl.rcParams['figure.subplot.hspace'] = 0.2


reset_plot_params()

plt.figure(figsize=(12, 9))

lv_directory = "C:\\Users\\plane\\Desktop\\Data\\HPRF\\HPRF 20120605\sparks_29p5MV-M_15Hz\\"
lv_file = "spark_66_68.npz"
(times, raw_signals) = labview.load_data(lv_directory,
                                         lv_file,
                                         t0=221.524e-3,
                                         t1=222.324e-3,
                                         channels=[0, 1, 2])
dt = 1.0e-6
flip_time = 310.e-6
flip_offset = int(round(flip_time / dt))
raw_signals[2, flip_offset:] = -raw_signals[2, flip_offset:]
plt.subplot(311)
plt.ylim((-1.2, 1.2))
plot.plot_signals(times * 1e6, raw_signals, norm=True)  # 22us wavefront delay

data_dir = "C:\\Users\\plane\\Dropbox\\Research\\MTA\\Analysis\\HPRF\\"
if platform.system() == 'Linux':
    data_dir = "/home/lane/Dropbox/Research/MTA/Analysis/HPRF/"

comsol_file = "hpc_wall_shock.npy"
コード例 #4
0
comsol_file = "ring_under_disk_0.25ms_30.5cm_25ms_1.5e8_1.5e8_1.5e8.csv"
plot_all(tek_dir, tek_file, comsol_dir, comsol_file, -1)


# # High-Pressure Cavity

# ## HC Observed vs. Simulated RF Hammer Comparison

# In[ ]:

#get_ipython().magic(u'matplotlib qt')
lv_dir = "C:\\Users\\peter\\Development\\Dissertation\\data\\HC\\"
if platform.system() == 'Linux':
    lv_dir = "/home/lane/Data/HPRF/HPRF 20120614/sparks_36MV-M_15Hz/"
lv_file = "spark_66_68.npz"
(times, real_hammer_signals) = labview.load_data(lv_dir, lv_file, t0=0.029342, t1=0.039342, channels=(0,5,3,))  # channels=(0,5,3,6,))
(frequencies, magnitudes, phases) = psig.spectra(times, real_hammer_signals)
fig = plt.figure(figsize=(20.0, 8.0))
plt.subplot(221)
#plt.xlabel('Time (s)')
plt.ylabel('Normalized Voltage')
plot.plot_signals(times*1e6, real_hammer_signals, tlim=300, ylim=1.5, norm=True)
plt.subplot(222)
#plt.xlabel('Frequency (Hz)')
plt.ylabel('Normalized Magnitude')
plot.plot_signals(frequencies*1e-3, magnitudes, ylim=(0,1.2), tlim=30, norm=True)

comsol_dir = "C:\\Users\\peter\\Development\\Dissertation\\data\\HC\\"
if platform.system() == 'Linux':
    comsol_dir = "/home/lane/Data/COMSOL/HPRF/RF Hammer with Thin Elastic Layer/"
comsol_file = "\S0_TEL_r_1e9_z_21e6_S1_TEL_r_15e6_z_1e9_S5_TEL_r_1e9_z_37e6_10ms.npy"
コード例 #5
0
    upsampled_signals = np.zeros((np.shape(breakdown_signals)[0], np.shape(breakdown_signals)[1]*2))
    upsampled_times = np.linspace(0, times[-1], np.shape(upsampled_signals)[1])
    for i,signal in enumerate(breakdown_signals):
        upsampled_signals[i] = np.roll(sig.resample(signal, len(signal)*2), -i)
    plot.plot_signals(upsampled_times*1e6, upsampled_signals, tlim=50)
plt.show()

fig = plt.figure(figsize=(15,10))
location_predictions = np.zeros((len(lv_files), 2))
"""
for index, lv_file in enumerate(lv_files):
    #(times, breakdown_signals) = labview.load_data(lv_dir, lv_file, t0=40e-6, t1=90e-6, channels=[4,5,6,7])
    #(times, breakdown_signals) = labview.load_data(lv_dir, lv_file, t0=40e-6, t1=90e-6, channels=[4,5,6,7])
    (times, breakdown_signals) = labview.load_data(lv_dir,
                                                   lv_file,
                                                   t0=40e-6,
                                                   t1=130e-6,
                                                   channels=[4, 5, 6, 7])
    #(times, breakdown_signals) = labview.load_data(lv_dir, lv_file, t0=20e-6, t1=130e-6, channels=[0,1,2,3])
    #(times, breakdown_signals) = mc.condition_signals(times, breakdown_signals, window_width=200e-6)
    plt.subplot(231 + index)
    """
  dt = times[1] - times[0]
  signal = breakdown_signals[3]
  frequency_spectrum = np.fft.fft(signal)[:int(round(signal.size/2))]
  spectrum_magnitudes = np.sqrt(  np.real(frequency_spectrum)**2
                                + np.imag(frequency_spectrum)**2)
  frequencies = np.fft.fftfreq(frequency_spectrum.size*2, d=dt)\
                  [:int(round(signal.size/2))]
  #plt.plot(frequencies, spectrum_magnitudes)
  f_peak = frequencies[np.argmax(spectrum_magnitudes[1:])]
コード例 #6
0
  labview.load_data(lv_dir, lv_file, t0=229.386e-3, t1=229.686e-3, channels=[0,1,2,3,5])[1]))
avg_hammer = np.average(hammers, axis=0)
times,spark = labview.load_data(lv_dir, lv_file, t0=296.092e-3, t1=296.392e-3, channels=[0,1,2,3,5])
"""

lv_dir = "C:\\Users\\plane\\Desktop\\Data\\MC\\2016-01-13\\"
lv_files = [
    "raw_data_2016-01-13@20_47_30.401.npz",
    "raw_data_2016-01-13@21_02_29.931.npz",
    "raw_data_2016-01-13@21_17_29.865.npz",
    "raw_data_2016-01-13@21_32_29.923.npz",
    "raw_data_2016-01-13@21_47_29.931.npz"
]
hammers = np.array([
    labview.load_data(lv_dir, lv_file, t0=30e-6, t1=430e-6, channels=[
        6,
    ])[1] for lv_file in lv_files
])
avg_hammer = np.average(hammers, axis=0)
lv_file = "reduced_data_2016-01-13@18_43_18.362.npz"
times, spark = labview.load_data(lv_dir,
                                 lv_file,
                                 t0=30e-6,
                                 t1=430e-6,
                                 channels=[
                                     6,
                                 ])
times = times * 1e6

fig = plt.figure(figsize=(16.0, 8.0))
#fig.text(0.5, 0.05, r'Time ($ms$)', ha='center', va='center', size=26)