Luke
852f4cad1d
Added support to plot measurement results, as well as some updates to the default style.
94 lines
3 KiB
Python
Executable file
94 lines
3 KiB
Python
Executable file
#!/usr/bin/env python3
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import os
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import argparse
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import numpy as np
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import matplotlib
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################################################################################
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args_parser = argparse.ArgumentParser()
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args_parser.add_argument('-n', type=int, default=1,
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help='plot testing number')
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args_parser.add_argument('--save','-s', action='store_true',
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help='save to files')
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args_parser.add_argument('--raster','-r', action='store_true',
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help='save as raster')
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args_parser.add_argument('--debug','-d', action='store_true',
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help='hold for debugging')
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args_parser.add_argument('--headless','-q', action='store_true',
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help='Remain neadless even if we aren\'t saving files.')
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args = args_parser.parse_args()
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################################################################################
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if args.raster:
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args.save = True
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fig_ext = 'png'
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else:
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fig_ext = 'pdf'
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################################################################################
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HEADLESS = not 'DISPLAY' in os.environ.keys()
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if args.headless: HEADLESS = True # Override Manually if request
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if HEADLESS: matplotlib.use('Agg')
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from matplotlib import rcParams, pyplot as pp
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from collections import namedtuple
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import LPRDefaultPlotting
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################################################################################
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# Override the defaults for this script
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figScaleSize = 1.0 if args.save else 1.6
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rcParams['figure.figsize'] = [3.4*figScaleSize,3*figScaleSize]
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default_window_position=['+20+80', '+120+80']
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################################################################################
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search_curves = (
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['2018-05-15',3.13],
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['2018-05-16',3.18],
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['2018-05-21',3.19],
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['2018-05-25',3.13]
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)
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currentBiasTable = np.load('fromCadence/current_bias.npy')
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bias_t_mV = currentBiasTable[0,:]*1e3
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bias_t_mA = currentBiasTable[1,:]*1e3
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bufferPerformanceTable = np.load('fromCadence/buffer_arrays.npz')
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[buffer_bias,buffer_freq,buffer_gain,buffer_phase] = \
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[item[1] for item in bufferPerformanceTable.iteritems()]
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for curve in search_curves:
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ind = np.argmin(np.abs(bias_t_mA-curve[1]))
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curve.append(ind)
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curve.append(bias_t_mV[ind]*1e-3)
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h=[pp.figure() for x in range(2)]
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ax=[hT.subplots(1,1) for hT in h]
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ax.append(ax[1].twinx())
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ax[0].set_xlabel('Gate Bias (mV)')
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ax[0].set_ylabel('Current (mA)')
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ax[0].plot(bias_t_mV, bias_t_mA)
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ax[1].set_xlabel('Frequency (GHz)')
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ax[1].set_ylabel('Gain (dB)')
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ax[2].set_ylabel('Phase (deg)')
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inds = [curve[2] for curve in search_curves]
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bw = 28
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freq_synthetic = np.linspace(-bw/2,bw/2,201)+28
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print(search_curves)
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for ind in inds:
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GP=np.polyfit(buffer_freq, buffer_gain[:,ind], 2)
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PP=np.polyfit(buffer_freq, buffer_phase[:,ind], 2)
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#print(" %.2fe-3 x^2 + %.2fe-3 x + %.2fe-3 " % tuple(1e3*P))
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print(ind, bias_t_mA[ind])
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print(GP)
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print(PP)
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ax[1].plot(freq_synthetic, np.polyval(GP,freq_synthetic))
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ax[2].plot(freq_synthetic, np.polyval(PP,freq_synthetic))
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ax[1].plot(buffer_freq, buffer_gain[:,inds])
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ax[2].plot(buffer_freq, buffer_phase[:,inds])
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[aT.grid() for aT in ax]
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[hT.tight_layout() for hT in h]
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[hT.show() for hT in h]
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