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# Python script for plotting curves for gm/Id method design | |
# MIT license. https://opensource.org/licenses/MIT | |
import sys | |
import os | |
sys.path.append(os.path.expanduser('~/src')) | |
import numpy as np | |
import rawread | |
import matplotlib as mpl | |
import matplotlib.pyplot as plt | |
arrs, plots = rawread.rawread(os.path.expanduser('~/ckt/gmid/gmid.raw')) | |
n = 0 | |
for mos in ['mn', 'mp']: | |
gm = np.asarray([elt['@%s[gm]' % mos] for elt in arrs]) | |
id = np.abs(np.asarray([elt['i(@%s[id])' % mos] for elt in arrs])) | |
gds = np.asarray([elt['@%s[gds]' % mos] for elt in arrs]) | |
cgs = np.asarray([elt['@%s[cgs]' % mos] for elt in arrs]) | |
cgg = np.asarray([elt['@%s[cgg]' % mos] for elt in arrs]) | |
w = np.asarray([elt['@%s[w]' % mos] for elt in arrs]) | |
l = np.asarray([elt['@%s[l]' % mos] for elt in arrs]) | |
gm_id = gm/id | |
gds_w = gds/w | |
gm_gds = gm/gds | |
gm_cgg = gm/cgg | |
fteff = gm_cgg*gm_id | |
gaineff = gm_gds*gm_id | |
id_w = id/w | |
label = ['%g' % elt for elt in l[:,0]] | |
curves = ( | |
(gds_w, 'gds/w %s' % mos, plt.semilogy), | |
(gm_gds, 'gm/gds %s' % mos, plt.plot), | |
(gm_cgg, '\omega_t = gm/cgg %s' % mos, plt.semilogy), | |
(fteff, '\omega_t*gm/id %s' % mos, plt.semilogy), | |
(gaineff, 'gm/gds*gm/id %s' % mos, plt.plot), | |
(id_w, 'id/w %s' % mos, plt.semilogy)) | |
for curve in curves: | |
fig = plt.figure(n) | |
ax = plt.subplot(111) | |
curve[2](gm_id.T, curve[0].T) | |
# Shrink current axis by 20% | |
box = ax.get_position() | |
ax.set_position([box.x0, box.y0, box.width * 0.8, box.height]) | |
# Put a legend to the right of the current axis | |
ax.legend(label, loc='center left', bbox_to_anchor=(1, 0.5)) | |
# ax.legend(label, loc='best', ncol=3, fancybox=True) # | |
plt.title(curve[1]) | |
fig.savefig(('%d_%s_%s.pdf' % (n, mos, curve[1])).replace('/','_'), format='pdf') | |
n = n+1 | |
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Yes. I used the same spice file that you provided as gmid.sp (with 'set filetype binary' option)... the raw file generated is in binary form