Script to plot an experiment sequence executed for a shot as extracted from the shot file.
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@ -71,7 +71,9 @@ def parse_NIST_data(path, min_J, max_J, max_wavenumber):
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def plot_level_structure_with_red_and_blue_transitions(*args, **kwargs):
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#start plotting
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f, ax = plt.subplots(figsize=(4, 8))
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f, ax = plt.subplots(figsize=(4.5, 7))
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#plt.subplots_adjust(top=0.973, bottom=0.121, left=0.244, right=0.959, hspace=0.2, wspace=0.2)
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named_colors = ['r', 'm']
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Red_Blue_colors = ['#ab162a', '#cf5246', '#eb9172', '#fac8af', '#faeae1', '#e6eff4', '#bbdaea', '#7bb6d6', '#3c8abe', '#1e61a5']
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@ -79,53 +81,55 @@ def plot_level_structure_with_red_and_blue_transitions(*args, **kwargs):
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plot_handle = sns.scatterplot(x='J', y='Wavenumber', data = dataframe, s=2000, hue = 'Parity', palette = sns.color_palette(named_colors), marker = '_', linewidth=1.5, legend=False)
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#write electronic configuration for GS
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ax.text(gs_J + 0.15, gs_wavenumber + 400, '$6s^2$')
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#ax.text(gs_J + 0.15, gs_wavenumber + 400, '$6s^2$')
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#draw guide line for GS
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#plt.axhline(y=gs_wavenumber, color='m', linestyle='--', linewidth=1, alpha=0.5)
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#write wavelength of red transition
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ax.text(red_J - 0.4, red_wavenumber * 0.5, '$626.082 ~ \mathrm{nm}$', color = '#db2929')
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ax.text(red_J - 0.4, red_wavenumber * 0.46, '$(\\Gamma = 2\\pi\\times 136 ~ \mathrm{kHz})$', fontsize = 8, color = '#db2929')
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ax.text(red_J - 0.4, red_wavenumber * 0.5, '626.082 nm', color = '#db2929', fontsize = 16, fontweight = 'bold')
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#ax.text(red_J - 0.49, red_wavenumber * 0.42, '$(\\Gamma = 2\\pi\\times 136 ~ \mathrm{kHz})$', fontsize = 12, color = '#db2929')
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#draw red transition arrow
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ax.annotate('',
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xy=(red_J, red_wavenumber),
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xytext=(gs_J, gs_wavenumber),
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arrowprops=dict(color='#db2929', alpha=0.8, width=1.5),
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arrowprops=dict(color='#db2929', width=1.5),
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horizontalalignment='right',
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verticalalignment='top')
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#write electronic configuration for triplet excited state
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ax.text(red_J + 0.35, red_wavenumber + 200, '$6s6p(^3P_1)$', fontsize = 10)
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#ax.text(red_J + 0.35, red_wavenumber + 200, '$6s6p(^3P_1)$', fontsize = 10)
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#draw guide line for triplet excited state
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plt.axhline(y=red_wavenumber, color='m', linestyle='--', linewidth=1, alpha=0.5)
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#write wavelength of red transition
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ax.text(blue_J - 1.5, blue_wavenumber * 0.55, '$421.291~ \mathrm{nm}$', color = '#2630ea')
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ax.text(blue_J - 1.55, blue_wavenumber * 0.52, '$(\\Gamma = 2\\pi\\times 32.2 ~ \mathrm{MHz})$', fontsize = 8, color = '#2630ea')
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ax.text(blue_J - 1.8, blue_wavenumber * 0.4, '421.291 nm', color = '#2630ea', fontsize = 16, fontweight = 'bold')
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#ax.text(blue_J - 1.85, blue_wavenumber * 0.4, '$(\\Gamma = 2\\pi\\times$', fontsize = 12, color = '#2630ea') #$(\\Gamma = 2\\pi\\times 32.2 ~ \mathrm{MHz})$
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#ax.text(blue_J - 1.5, blue_wavenumber * 0.35, '$32.2 ~ \mathrm{MHz})$', fontsize = 12, color = '#2630ea')
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#draw blue transition arrow
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ax.annotate('',
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xy=(blue_J, blue_wavenumber),
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xytext=(gs_J, gs_wavenumber),
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arrowprops=dict(color='#2630ea', alpha=0.8, width=3.5),
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arrowprops=dict(color='#2630ea', width=3.5),
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horizontalalignment='right',
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verticalalignment='top')
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#write electronic configuration for singlet excited state
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ax.text(blue_J + 0.35, blue_wavenumber + 200, '$6s6p(^1P_1)$', fontsize = 10)
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#ax.text(blue_J + 0.35, blue_wavenumber + 200, '$6s6p(^1P_1)$', fontsize = 10)
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#draw guide line for singlet excited state
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plt.axhline(y=blue_wavenumber, color='m', linestyle='--', linewidth=1, alpha=0.5)
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#figure options
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f.canvas.draw()
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plt.xlabel('J', fontsize=16)
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plt.xlabel('J', fontsize=20, fontweight = 'bold')
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#plt.ylabel('$\\tilde{v}~(cm^{-1})$', fontsize=16)
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plt.ylabel('Wavelength (nm)', fontsize=16)
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plt.ylabel('Wavelength (nm)', fontsize=20, fontweight = 'bold')
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plot_handle.set_xticks(range(min_J-1, max_J+2))
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ax.get_xticklabels()[0].set_visible(False)
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ax.get_xticklabels()[-1].set_visible(False)
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ax.get_xticklines()[0].set_visible(False)
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ax.get_xticklines()[-2].set_visible(False)
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ax.set_xticklabels(ax.get_xticks(), weight='bold')
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yticklabels = [item.get_text() for item in ax.get_yticklabels()]
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yticklabels = ['' if item.startswith('−') or item.startswith('0') else item for item in yticklabels]
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@ -133,14 +137,15 @@ def plot_level_structure_with_red_and_blue_transitions(*args, **kwargs):
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new_yticks = np.arange(min(yticks), max_wavenumber, 4000)
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plot_handle.set_yticks(new_yticks)
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new_yticklabels = [round(1e7/item) if item != 0 else item for item in new_yticks]
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ax.set_yticklabels(new_yticklabels)
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ax.set_yticklabels(new_yticklabels, weight='bold')
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ax.get_yticklabels()[0].set_visible(False)
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#ax.get_yticklabels()[-1].set_visible(False)
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ax.get_yticklines()[0].set_visible(False)
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#ax.get_yticklines()[-2].set_visible(False)
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plt.tick_params(axis='both', which='major', labelsize=14)
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plt.tick_params(axis='both', which='major', labelsize=16)
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#f.tight_layout()
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#plt.show()
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f.savefig(Path(home_path + os.sep + 'result.pdf'), format='pdf', bbox_inches = "tight")
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@ -149,7 +154,8 @@ if __name__ == '__main__':
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min_J = 8
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max_J = 9
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max_wavenumber = 24500.0
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#max_wavenumber = 24500.0
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max_wavenumber = 28500.0
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#Ground State: [Xe]4f^{10} 6s^2(^5I_8)
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gs_J = 8
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331
readAndPlotSequence.py
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331
readAndPlotSequence.py
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@ -0,0 +1,331 @@
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import numpy, imageio, os
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from scipy import interpolate
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import matplotlib.pyplot as plt
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from qtutils import *
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from labscript_utils.connections import ConnectionTable
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from labscript_utils import device_registry
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from labscript_c_extensions.runviewer.resample import resample as _resample
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import h5py
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def generate_ylabel(channel_name):
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if channel_name == 'AO_MOT_Grad_Coil_current':
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label = '$ \\nabla B_{AHH}$'
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elif channel_name == 'AO_MOT_CompZ_Coil_current':
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label = '$B_{HH}$'
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elif channel_name == 'AO_MOT_3D_freq':
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label = '$\Delta \\nu$'
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elif channel_name == 'AO_MOT_3D_amp':
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label = '$P_{3D}$'
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elif channel_name == 'AO_Red_Push_amp':
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label = '$P_{Push}$'
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elif channel_name == 'MOT_2D_Shutter':
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label = '$P_{2D}$'
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elif channel_name == 'AO_ODT1_Pow':
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label = '$P_{cODT1}$'
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elif channel_name == 'Imaging_RF_Switch':
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label = '$P_{img}$'
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elif channel_name == 'MOT_3D_Camera_Trigger':
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label = '$Cam$'
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return label
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def plotSequence(Channels, Switches, animate = False, idx = 0):
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axs = plt.subplots(len(Channels), figsize = (10, 6), constrained_layout=True, sharex=True)[1]
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for i, channel_name in enumerate(Channels):
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#markers_unscaled = sorted(list(shotObj.markers.keys()))
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#scalehandler = ScaleHandler(markers_unscaled, markers_unscaled, shotObj.stop_time)
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#unscaled_time = numpy.asarray(Traces[channel_name])[0]
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#scaled_time = scalehandler.get_scaled_time(unscaled_time)
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channel_time = numpy.asarray(Traces[channel_name])[0]
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channel_trace = numpy.asarray(Traces[channel_name])[1]
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xmin = 0
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xmax = shotObj.stop_time
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dx = 1e-9
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resampled_channel_trace = shotObj.resample(channel_time, channel_trace, xmin, xmax, shotObj.stop_time, dx)[1]
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time = numpy.arange(xmin, xmax, (xmax-xmin)/len(resampled_channel_trace))
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switch_time = numpy.asarray(Traces[Switches[i]])[0]
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switch_trace = numpy.asarray(Traces[Switches[i]])[1]
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xmin = 0
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xmax = shotObj.stop_time
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dx = 1e-9
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resampled_switch_trace = shotObj.resample(switch_time, switch_trace, xmin, xmax, shotObj.stop_time, dx)[1]
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trace = numpy.multiply(resampled_channel_trace, resampled_switch_trace)
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if not animate:
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axs[i].plot(time, trace, '-b') #'-ob'
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axs[i].fill_between(time, trace, alpha=0.4)
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else:
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axs[i].plot(time[0:idx], trace[0:idx], '-b') #'-ob'
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axs[i].fill_between(time[0:idx], trace[0:idx], alpha=0.4)
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axs[i].axvline(x=0, color = 'b', linestyle = '--')
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axs[i].axvline(x=4, color = 'b', linestyle = '--')
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axs[i].axvline(x=4.315, color = 'b', linestyle = '--')
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axs[i].axvline(x=shotObj.stop_time, color = 'b', linestyle = '--')
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axs[i].set_xlim(0, shotObj.stop_time)
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axs[i].set_ylim(0, max(resampled_channel_trace) + 0.2)
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if i == len(Channels)-1:
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axs[i].set_xlabel('Time (s)', fontsize = 16)
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axs[i].set_ylabel(generate_ylabel(channel_name), fontsize = 16)
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if not animate:
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plt.savefig(f'seq.png', format='png', bbox_inches = "tight")
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plt.show()
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else:
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plt.savefig(f'seq-{idx}.png')
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plt.close()
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def animateSequence(Channels, Switches):
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SIZE = 6000
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STEP = 58
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for i in range(2, SIZE, STEP):
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plotSequence(Channels, Switches, animate = True, idx = i)
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with imageio.get_writer('seq_animated.gif', mode='i', fps = 24, loop = 1) as writer:
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for i in range(2, SIZE, STEP):
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image = imageio.imread(f'seq-{i}.png')
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writer.append_data(image)
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os.remove(f'seq-{i}.png')
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class ScaleHandler():
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def __init__(self, input_times, target_positions, stop_time):
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# input_times is a list (may be unsorted) of times which should be scaled evenly with target_length
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# an input list of [1,2,4,6] and target_length of 1.0 will result in:
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# get_scaled_time(1) -> 1
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# get_scaled_time(1.5) -> 1.5
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# get_scaled_time(3) -> 2.5
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# get_scaled_time(4) -> 3
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# get_scaled_time(5) -> 3.5 ...
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self.org_stop_time = float(stop_time)
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if not all((x >= 0) and (x <= self.org_stop_time) for x in input_times):
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raise Exception('shot contains at least one marker before t=0 and/or after the stop time. Non-linear time currently does not support this.')
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unscaled_times = sorted(input_times)
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scaled_times = sorted(target_positions)
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# append values for linear scaling before t=0 and after stop time
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unscaled_times = [min(unscaled_times)-1e-9] + unscaled_times + [max(unscaled_times) + 1e-9]
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scaled_times = [min(scaled_times)-1e-9] + scaled_times + [max(scaled_times) + 1e-9]
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self.get_scaled_time = interpolate.interp1d(unscaled_times, scaled_times, assume_sorted=True, bounds_error=False, fill_value='extrapolate')
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self.get_unscaled_time = interpolate.interp1d(scaled_times, unscaled_times, assume_sorted=True, bounds_error=False, fill_value='extrapolate')
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self.scaled_stop_time = self.get_scaled_time(self.org_stop_time)
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class Shot(object):
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def __init__(self, path):
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self.path = path
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# Store list of traces
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self._traces = None
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# store list of channels
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self._channels = None
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# store list of markers
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self._markers = None
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# store list of shutter changes and callibrations
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self._shutter_times = None
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self._shutter_calibrations = {}
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# Load connection table
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self.connection_table = ConnectionTable(path)
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# open h5 file
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with h5py.File(path, 'r') as file:
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# Get master pseudoclock
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self.master_pseudoclock_name = file['connection table'].attrs['master_pseudoclock']
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if isinstance(self.master_pseudoclock_name, bytes):
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self.master_pseudoclock_name = self.master_pseudoclock_name.decode('utf8')
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else:
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self.master_pseudoclock_name = str(self.master_pseudoclock_name)
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# get stop time
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self.stop_time = file['devices'][self.master_pseudoclock_name].attrs['stop_time']
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self.device_names = list(file['devices'].keys())
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# Get Shutter Calibrations
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if 'calibrations' in file and 'Shutter' in file['calibrations']:
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for name, open_delay, close_delay in numpy.array(file['calibrations']['Shutter']):
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name = name.decode('utf8') if isinstance(name, bytes) else str(name)
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self._shutter_calibrations[name] = [open_delay, close_delay]
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def _load(self):
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if self._channels is None:
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self._channels = {}
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if self._traces is None:
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self._traces = {}
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if self._markers is None:
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self._markers = {}
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if self._shutter_times is None:
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self._shutter_times = {}
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self._load_markers()
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# Let's walk the connection table, starting with the master pseudoclock
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master_pseudoclock_device = self.connection_table.find_by_name(self.master_pseudoclock_name)
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self._load_device(master_pseudoclock_device)
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def _load_markers(self):
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with h5py.File(self.path, 'r') as file:
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if "time_markers" in file:
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for row in file["time_markers"]:
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self._markers[row['time']] = {'color': row['color'].tolist()[0], 'label': row['label']}
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elif "runviewer" in file:
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for time, val in file["runviewer"]["markers"].attrs.items():
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props = val.strip('{}}').rsplit(",", 1)
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color = list(map(int, props[0].split(":")[1].strip(" ()").split(",")))
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label = props[1].split(":")[1]
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self._markers[float(time)] = {'color': color, 'label': label}
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if 0 not in self._markers:
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self._markers[0] = {'color': [0,0,0], 'label': 'Start'}
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if self.stop_time not in self._markers:
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self._markers[self.stop_time] = {'color': [0,0,0], 'label' : 'End'}
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def add_trace(self, name, trace, parent_device_name, connection):
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name = str(name)
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self._channels[name] = {'device_name': parent_device_name, 'port': connection}
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self._traces[name] = trace
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# add shutter times
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con = self.connection_table.find_by_name(name)
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if con.device_class == "Shutter" and 'open_state' in con.properties:
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self.add_shutter_times([(name, con.properties['open_state'])])
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# Temporary solution to physical shutter times
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def add_shutter_times(self, shutters):
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for name, open_state in shutters:
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x_values, y_values = self._traces[name]
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if len(x_values) > 0:
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change_indices = numpy.where(y_values[:-1] != y_values[1:])[0]
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change_indices += 1 # use the index of the value that is changed to
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change_values = list(zip(x_values[change_indices], y_values[change_indices]))
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change_values.insert(0, (x_values[0], y_values[0])) # insert first value
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self._shutter_times[name] = {x_value + (self._shutter_calibrations[name][0] if y_value == open_state else self._shutter_calibrations[name][1]): 1 if y_value == open_state else 0 for x_value, y_value in change_values}
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def _load_device(self, device, clock=None):
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try:
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module = device.device_class
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device_class = device_registry.get_runviewer_parser(module)
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device_instance = device_class(self.path, device)
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clocklines_and_triggers = device_instance.get_traces(self.add_trace, clock)
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for name, trace in clocklines_and_triggers.items():
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child_device = self.connection_table.find_by_name(name)
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for grandchild_device_name, grandchild_device in child_device.child_list.items():
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self._load_device(grandchild_device, trace)
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except Exception:
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pass
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def resample(self, data_x, data_y, xmin, xmax, stop_time, num_pixels):
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"""This is a function for downsampling the data before plotting
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it. Unlike using nearest neighbour interpolation, this method
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preserves the features of the plot. It chooses what value to
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use based on what values within a region are most different
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from the values it's already chosen. This way, spikes of a short
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duration won't just be skipped over as they would with any sort
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of interpolation."""
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# TODO: Only finely sample the currently visible region. Coarsely sample the rest
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# x_out = numpy.float32(numpy.linspace(data_x[0], data_x[-1], 4000*(data_x[-1]-data_x[0])/(xmax-xmin)))
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x_out = numpy.float64(numpy.linspace(xmin, xmax, 3 * 2000 + 2))
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y_out = numpy.empty(len(x_out) - 1, dtype=numpy.float64)
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data_x = numpy.float64(data_x)
|
||||
data_y = numpy.float64(data_y)
|
||||
|
||||
# TODO: investigate only resampling when necessary.
|
||||
# Currently pyqtgraph sometimes has trouble rendering things
|
||||
# if you don't resample. If a point is far off the graph,
|
||||
# and this point is the first that should be drawn for stepMode,
|
||||
# because there is a long gap before the next point (which is
|
||||
# visible) then there is a problem.
|
||||
# Also need to explicitly handle cases where none of the data
|
||||
# is visible (which resampling does by setting NaNs)
|
||||
#
|
||||
# x_data_slice = data_x[(data_x>=xmin)&(data_x<=xmax)]
|
||||
# print len(data_x)
|
||||
# if len(x_data_slice) < 3*2000+2:
|
||||
# x_out = x_data_slice
|
||||
# y_out = data_y[(data_x>=xmin)&(data_x<=xmax)][:-1]
|
||||
# logger.info('skipping resampling')
|
||||
# else:
|
||||
resampling = True
|
||||
|
||||
if resampling:
|
||||
_resample(data_x, data_y, x_out, y_out, numpy.float64(stop_time))
|
||||
# self.__resample4(data_x, data_y, x_out, y_out, numpy.float32(stop_time))
|
||||
else:
|
||||
x_out, y_out = data_x, data_y
|
||||
|
||||
return x_out, y_out
|
||||
|
||||
@property
|
||||
def channels(self):
|
||||
if self._channels is None:
|
||||
self._load()
|
||||
|
||||
return self._channels.keys()
|
||||
|
||||
@property
|
||||
def markers(self):
|
||||
if self._markers is None:
|
||||
self._load()
|
||||
return self._markers
|
||||
|
||||
@property
|
||||
def traces(self):
|
||||
if self._traces is None:
|
||||
self._load()
|
||||
return self._traces
|
||||
|
||||
@property
|
||||
def shutter_times(self):
|
||||
if self._shutter_times is None:
|
||||
self._load()
|
||||
return self._shutter_times
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
filepath = 'C:/Users/Karthik/Desktop/PreTalk/Plot Sequence/2023-01-25_0069_ODT_Imaging_9.h5'
|
||||
|
||||
shotObj = Shot(filepath)
|
||||
shotObj._load()
|
||||
|
||||
Channels = list(shotObj.channels)
|
||||
Traces = shotObj.traces
|
||||
|
||||
"""
|
||||
'prawn_clock_line_0', 'prawn_clock_line_1', 'Dummy_1', 'Imaging_RF_Switch', 'Imaging_Shutter', 'MOT_2D_Shutter', 'MOT_3D_RF_Switch', 'MOT_3D_Shutter', 'Push_Beam_Blue_Shutter',
|
||||
'Push_Beam_Blue_Switch', 'Push_Beam_Red_Shutter', 'Push_Beam_Red_Switch', 'CDT1_Switch', 'CDT2_Switch', 'MOT_3D_Camera_Trigger', 'MOT_3D_Camera_trigger', 'MOT_CompX_Coil_Switch',
|
||||
'MOT_CompY_Coil_Switch', 'MOT_CompZ_Coil_Switch', 'MOT_Grad_Coil_Switch', 'ODT_Axis_Camera_Trigger', 'ODT_Axis_Camera_trigger', 'AO_Blue_Push_amp', 'AO_Blue_Push_freq', 'AO_Imaging_amp',
|
||||
'AO_Imaging_freq', 'AO_MOT_3D_amp', 'AO_MOT_3D_freq', 'AO_MOT_CompX_Coil_current', 'AO_MOT_CompX_Coil_voltage', 'AO_MOT_CompY_Coil_current', 'AO_MOT_CompY_Coil_voltage', 'AO_MOT_CompZ_Coil_current',
|
||||
'AO_MOT_CompZ_Coil_voltage', 'AO_MOT_Grad_Coil_current', 'AO_MOT_Grad_Coil_voltage', 'AO_Red_Push_amp', 'AO_Red_Push_freq', 'AO_Dummy', 'AO_ODT1_Mod', 'AO_ODT1_Pow', 'AO_ODT2_Pow'
|
||||
"""
|
||||
|
||||
""" Without Imaging """
|
||||
Channels = ['MOT_2D_Shutter', 'AO_Red_Push_amp', 'AO_MOT_3D_amp', 'AO_MOT_3D_freq', 'AO_MOT_Grad_Coil_current', 'AO_MOT_CompZ_Coil_current', 'AO_ODT1_Pow']
|
||||
Switches = ['MOT_2D_Shutter', 'Push_Beam_Red_Switch', 'MOT_3D_RF_Switch', 'MOT_3D_RF_Switch', 'MOT_Grad_Coil_Switch', 'MOT_CompZ_Coil_Switch', 'CDT1_Switch']
|
||||
|
||||
""" With Imaging """
|
||||
# Channels = ['MOT_2D_Shutter', 'AO_Red_Push_amp', 'AO_MOT_3D_amp', 'AO_MOT_3D_freq', 'AO_MOT_Grad_Coil_current', 'AO_MOT_CompZ_Coil_current', 'AO_ODT1_Pow', 'Imaging_RF_Switch', 'MOT_3D_Camera_Trigger']
|
||||
# Switches = ['MOT_2D_Shutter', 'Push_Beam_Red_Switch', 'MOT_3D_RF_Switch', 'MOT_3D_RF_Switch', 'MOT_Grad_Coil_Switch', 'MOT_CompZ_Coil_Switch', 'CDT1_Switch', 'Imaging_RF_Switch', 'MOT_3D_Camera_Trigger']
|
||||
|
||||
plotSequence(Channels, Switches)
|
||||
|
||||
# animateSequence(Channels, Switches)
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user