180 lines
No EOL
4.5 KiB
Python
Executable file
180 lines
No EOL
4.5 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
import os
|
|
import argparse
|
|
import numpy as np
|
|
import matplotlib
|
|
################################################################################
|
|
args_parser = argparse.ArgumentParser()
|
|
args_parser.add_argument('--save','-s', action='store_true',
|
|
help='save to files')
|
|
args_parser.add_argument('--raster','-r', action='store_true',
|
|
help='save as raster')
|
|
args_parser.add_argument('--debug','-d', action='store_true',
|
|
help='hold for debugging')
|
|
args_parser.add_argument('--headless','-q', action='store_true',
|
|
help='Remain neadless even if we aren\'t saving files.')
|
|
args_parser.add_argument('-n', type=int, default=0,
|
|
help='plot testing number')
|
|
args = args_parser.parse_args()
|
|
|
|
################################################################################
|
|
if args.raster:
|
|
args.save = True
|
|
fig_ext = 'png'
|
|
else:
|
|
fig_ext = 'pdf'
|
|
|
|
################################################################################
|
|
HEADLESS = not 'DISPLAY' in os.environ.keys()
|
|
if args.headless: HEADLESS = True # Override Manually if request
|
|
if HEADLESS: matplotlib.use('Agg')
|
|
|
|
from matplotlib import rcParams, pyplot as pp
|
|
if not HEADLESS: pp.interactive(True)
|
|
import LPRDefaultPlotting
|
|
from tankComputers import *
|
|
import csv
|
|
|
|
file_list = [
|
|
['NF_vs_Freq',
|
|
'20190727_PS_NoiseFigure_Simulation_NoBuffer_Frequency'],
|
|
['NF_vs_Bias',
|
|
'20190727_PS_NoiseFigure_Simulation_NoBuffer'],
|
|
['stability',
|
|
'20190727_PS_KF_Simulation_NoBuffer_BiasDP_WorstCase_C9'],
|
|
['stability_corners',
|
|
'20190810_PS_KF_Simulation_NoBuffer_BiasDP_WorstCase_C9_Corners']
|
|
]
|
|
|
|
file_test = file_list[args.n]
|
|
|
|
fig_dir='figures-revised'
|
|
fn='revisedData/clean_%s.csv' % (file_test[1])
|
|
fo=file_test[0]
|
|
|
|
fh=open(fn,'r')
|
|
reader=csv.reader(fh)
|
|
h1 = None
|
|
|
|
if args.n in [0,1,2]: # X/Y data
|
|
x_dat=[]
|
|
y_dat=[]
|
|
reader.__next__() # toss the keys
|
|
|
|
for row in reader:
|
|
x_dat.append(float(row[0]))
|
|
y_dat.append(float(row[1]))
|
|
|
|
if args.n in [3]: # X/Y data
|
|
x_dat=[]
|
|
y_dat=[]
|
|
legend_strs = reader.__next__() # toss the keys
|
|
legend_strs = legend_strs[1:]
|
|
|
|
for row in reader:
|
|
x_dat.append(float(row[0]))
|
|
y_dat.append(np.array([float(x) for x in row[1:]]))
|
|
|
|
y_lims = None
|
|
|
|
if args.n == 0:
|
|
x = 1e-9 * np.array(x_dat)
|
|
lab_x = 'Frequency (GHz)'
|
|
lab_title = 'Noise Figure vs. Frequency'
|
|
h1=pp.figure(figsize=(3.4,1.8))
|
|
|
|
if args.n == 1:
|
|
x = np.array(x_dat)*1e3
|
|
lab_x = 'Bias (mV)'
|
|
lab_title = 'Noise Figure vs. Q-enhancement bias'
|
|
|
|
if args.n in [0, 1]:
|
|
y = np.array(y_dat)
|
|
lab_y = 'Noise Figure (dB)'
|
|
y_lims = [9.7, 10.7]
|
|
x_lims = [min(x),max(x)]
|
|
|
|
if args.n == 2:
|
|
x = np.array(x_dat) * 1e3
|
|
y = np.array(y_dat)
|
|
lab_x = 'Bias (mV)'
|
|
lab_y = '$K_f$ (-)'
|
|
lab_title = 'Stability vs. Bias'
|
|
y_lims = [-2, 50]
|
|
x_lims = [250,500]
|
|
h1=pp.figure(figsize=(3.4,2))
|
|
|
|
if args.n == 3:
|
|
x = np.array(x_dat) * 1e3
|
|
y = np.array(y_dat)
|
|
lab_x = 'Bias (mV)'
|
|
lab_y = '$K_f$ (-)'
|
|
lab_title = 'Stability vs. Bias'
|
|
y_lims = [-5, 50]
|
|
x_lims = [min(x),500]
|
|
h1=pp.figure(figsize=(3.4,2))
|
|
|
|
|
|
if h1 == None: h1 = pp.figure(figsize=(3.4,2))
|
|
ax = h1.add_subplot(1,1,1)
|
|
|
|
ax.plot(x,y)
|
|
ax.set_title(lab_title)
|
|
ax.set_xlabel(lab_x)
|
|
ax.set_ylabel(lab_y)
|
|
ax.set_xlim(x_lims)
|
|
|
|
if y_lims != None: ax.set_ylim(y_lims)
|
|
if args.n == 2:
|
|
nl_x = np.ones((2,1))*min(x[y <= 0])
|
|
nl_y = ax.get_ylim()
|
|
nl_1 = matplotlib.lines.Line2D(nl_x, nl_y)
|
|
nl_x = np.ones((2,1))*400
|
|
nl_2 = matplotlib.lines.Line2D(nl_x, nl_y)
|
|
for nl in [nl_1, nl_2]:
|
|
nl.set_color('C1')
|
|
ax.add_line(nl_1)
|
|
LPRDefaultPlotting.annotateArrow(ax, 5, [397, 381], direction='left')
|
|
LPRDefaultPlotting.annotateArrow(ax, 10, [481, 495])
|
|
|
|
LPRDefaultPlotting.annotateArrowStr(ax,
|
|
"Measurement\nBound", 5, 350)
|
|
LPRDefaultPlotting.annotateArrowStr(ax,
|
|
"Unstable\nRegion", 15, 475)
|
|
|
|
ax.add_line(nl_2)
|
|
|
|
if args.n == 3:
|
|
line = ax.get_lines()[0]
|
|
line.set_linewidth(line.get_linewidth()*2)
|
|
|
|
nl_x = ax.get_xlim()
|
|
nl_y = np.ones((2,1))*1
|
|
#nl_x = np.ones((2,1))*min(x[np.any(y <= 1,1)])
|
|
nl_1 = matplotlib.lines.Line2D(nl_x, nl_y)
|
|
nl_y = ax.get_ylim()
|
|
nl_x = np.ones((2,1))*400
|
|
nl_2 = matplotlib.lines.Line2D(nl_x, nl_y)
|
|
for nl in [nl_1, nl_2]:
|
|
nl.set_color('K')
|
|
ax.add_line(nl_1)
|
|
#legend_strs.append('Unstable')
|
|
leg=ax.legend(legend_strs, labelspacing=0)
|
|
#leg.set_frame_on(False)
|
|
LPRDefaultPlotting.annotateArrow(ax, 35.5, [395, 310], direction='left')
|
|
#LPRDefaultPlotting.annotateArrow(ax, 10, [481, 495])
|
|
|
|
LPRDefaultPlotting.annotateArrowStr(ax,
|
|
"Measurement\nBound", 35, 270)
|
|
#LPRDefaultPlotting.annotateArrowStr(ax,
|
|
# "Unstable\nRegion", 15, 475)
|
|
|
|
ax.add_line(nl_2)
|
|
|
|
ax.grid(True)
|
|
h1.tight_layout()
|
|
|
|
if args.save:
|
|
h1.savefig('%s/%s.%s' % (fig_dir, fo, fig_ext))
|
|
if HEADLESS:
|
|
pp.close() |