def touch_with_func():
plot_data = {}
read_data = CVMCv1Parser.from_file('cv1.txt')
for i in range(0, 1):
data = read_data.data[i]['data']
temp = read_data.data[i]['temp']
data.set_free_energy_00_from_logtxt('log.txt')
data.set_end_energy(0, 0)
err = make_err_func(func)
points = []
for j in range(15):
pylab.plot(data['comp1'], data['corrected_g'], '+')
pylab.axvline(x=1/16*(j+1), color='black')
try:
p = pylab.ginput(n=1, timeout=2)
while p == []:
p = pylab.ginput(n=1, timeout=2)
print(1/16*(j+1), p[0][1])
except KeyboardInterrupt:
print("座標習得を諦めました")
exit()
points.append(p[0])
pylab.close()
points = np.array(points)
param = optimize.leastsq(
err, [1, 1, 1, 1, 1], args=(points[:, 0],
points[:, 1]))[0]
judge = np.abs(err(param, data['comp1'], data['corrected_g'])) < 1
inliersx = data['comp1'][judge]
inliersy = data['corrected_g'][judge]
x = inliersx
y = inliersy
opt = optimize.leastsq(
err, [1, 1, 1, 1, 1], args=(x, y))[0]
fitx = np.linspace(0, 1, 100)
fity = func(opt, fitx)
plot_data.update({temp:[data['comp1'], data['corrected_g'], fitx, fity]})
i = 1
for temp in plot_data:
pd = plot_data[temp]
d = (33 // (len(plot_data) + 1))
pylab.plot(pd[0], pd[1], '+',
color=COLOR_PALETTE[d*i][1])
pylab.plot(pd[2], pd[3], color=COLOR_PALETTE[d*i][0], linewidth=2)
save_results(temp, pd)
i += 1
pylab.xlim(0, 1)
pylab.show()
def normal_fit(func_order, log_file):
func = {5: penta, 6: hex}[func_order]
data = CVMCv1Parser.from_file('cv1.txt').data[0]['data']
data.set_free_energy_00_from_logtxt(log_file)
data.set_end_energy(0, 0)
err = make_err_func(func)
param = optimize.leastsq(
err, [1, 1, 1, 1, 1], args=(data['comp1'], data['corrected_g']))[0]
fitx = np.linspace(0, 1, 100)
fity = func(param, fitx)
# plot
fig = pylab.figure()
plot1 = fig.add_subplot(111)
pylab.plot(fitx, fity)
pylab.plot(data['comp1'], data['corrected_g'], 'p')
plot1.set_ylabel("Free energy (kJ/mol)", fontsize=16)
plot1.set_xlabel("Fraction of atom A", fontsize=16)
pylab.xticks(fontsize=14)
pylab.yticks(fontsize=14)
fig.subplots_adjust(bottom=0.15)
# pylab.savefig("energy.eps")
pylab.show()
return
def ransac(func):
for i in range(1):
data = CVMCv1Parser.from_file('cv1.txt').data[i]['data']
data.set_free_energy_00_from_logtxt('log.txt')
data.set_end_energy(0, 0)
err = make_err_func(func)
iterations = 0
residuals = []
models = []
num = []
while len(num) < 1000:
idx = np.random.choice(len(data['comp1']), 10, False)
param = optimize.leastsq(
err, [1, 1, 1, 1, 1], args=(data['comp1'][idx],
data['corrected_g'][idx]))[0]
inliers = []
judge = np.abs(err(param, data['comp1'], data['corrected_g'])) < 1
# print(judge)
inliersx = data['comp1'][judge]
inliersy = data['corrected_g'][judge]
# for i in range(len(data['comp1'])):
# if err(param, data['comp1'][i], data['corrected_g'][i])**2 > 5:
# continue
# else:
# inliers.append([data['comp1'][i], data['corrected_g'][i]])
if len(inliersx) > len(data['comp1']) * 0.5:
# x = np.array(inliers)[:, 0]
# y = np.array(inliers)[:, 1]
x = inliersx
y = inliersy
candidate = optimize.leastsq(
err, [1, 1, 1, 1, 1], args=(x, y))[0]
res = (err(candidate, x, y) ** 2).sum() / len(inliersx)
res = (err(param, x, y) ** 2).sum() / len(inliersx)
# models.append(candidate)
models.append(param)
residuals.append(res)
num.append(len(inliersx))
iterations += 1
best_index = np.argmin(residuals)
# best_index = np.argmax(num)
print(num[best_index])
fitparam = models[best_index]
fitx = np.linspace(0, 1, 100)
fity = func(fitparam, fitx)
# fit = CVMPlt.fit_penta(data['comp1'][idx], data['corrected_g'][idx])
# print(fit[2])
# iterations += 1
# fit = CVMPlt.fit_octa(data['comp1'], data['corrected_g'])
#yp = None
#xi = pylab.linspace(0, 1, 100)
#y1 = pylab.stineman_interp(xi, data['comp1'], data['corrected_g'], yp)
d = (33//(i+1))
# c.set_end_energy(0, 348.725971609)
# c.set_end_energy(0, 0)
pylab.plot(data['comp1'], data['corrected_g'], '+', color=COLOR_PALETTE[d*i][1])
pylab.plot(fitx, fity, color=COLOR_PALETTE[d*i][0], linewidth=1)
pylab.xlim(0, 1)
#pylab.ylim(-1, 1)
#pylab.savefig('t{0}.eps'.format(tmp))
pylab.show()
def plot(save, log_file, with_cem, vac_corr, end, wo_zero_zero,
set_yrange, set_xrange):
def get_correction(x, vac_corr):
if Fraction(vac_corr):
return 1/(x+Fraction(vac_corr))
else:
return 1
def get_slope(x, end):
return end[0]*(1-x) + end[1]*(x)
data = CVMCv1Parser.from_file('cv1.txt')
seaborn.set_style('whitegrid')
fig = pylab.figure()
plot1 = fig.add_subplot(111)
plot1.set_ylabel("Free energy (kJ/mol)", fontsize=16)
plot1.set_xlabel("Fraction of atom A", fontsize=16)
pylab.xticks(fontsize=14)
pylab.ylabel("Free energy (kJ/mol)", fontsize=16)
pylab.xlabel("Fraction of atom A", fontsize=16)
pylab.yticks(fontsize=14)
fig.subplots_adjust(bottom=0.15)
# seaborn.set_palette("winter", len(data.data))
dict_data = {}
for data_tmp in data.data:
dict_data.update({data_tmp['temp']: data_tmp['data']})
for i, temp in enumerate(sorted(dict_data.keys())):
color = pylab.cm.cool(i/len(dict_data)) #pylint: disable=E1101
if wo_zero_zero:
dict_data[temp].set_free_energy_00(0, 0)
else:
dict_data[temp].set_free_energy_00_from_logtxt(log_file)
dict_data[temp].set_end_energy(end[0], end[1])
label = str(temp) + "K"
x = dict_data[temp]['comp1']
corr = get_correction(x, vac_corr)
pylab.plot(x*corr, dict_data[temp]['corrected_g']*corr,
'o', label=label, color=color)
pylab.legend(loc='lower left')
if with_cem:
cem = CVMLogEnth.from_file(log_file)
x = cem.stable['c_a']
corr = get_correction(x, vac_corr)
pylab.plot(x * corr,
(cem.stable['enth']*96.485/1000+get_slope(x, end))*corr, '*',
color='orange')
x = cem.meta['c_a']
corr = get_correction(x, vac_corr)
pylab.plot(x * corr,
(cem.meta['enth']*96.485/1000+get_slope(x, end))*corr, '*',
color='orange')
x = cem.unstable['c_a']
corr = get_correction(x, vac_corr)
pylab.plot(x * corr,
(cem.unstable['enth']*96.485/1000+get_slope(x, end))*corr,
'*', color='orange')
x = cem.exact['c_a']
corr = get_correction(x, vac_corr)
pylab.plot(x * corr,
(cem.exact['exact']*96.485/1000+get_slope(x, end))*corr,
'.', color='magenta')
if set_yrange != (0, 0):
pylab.ylim(*set_yrange)
if set_xrange != (0, 0):
pylab.xlim(*set_xrange)
if save:
pylab.savefig("plot.eps")
else:
pylab.show()
def touch():
read_data = CVMCv1Parser.from_file('cv1.txt')
d = read_data.data[0]['data']
datax = d['comp1']
dataz = d['F'] * 8.31 / 1000
max_x = datax.max()
min_x = datax.min()
yp = None
xi = pylab.linspace(min_x, max_x, 20)
z1 = pylab.stineman_interp(xi, datax, dataz, yp)
points = []
for i, x in enumerate(xi):
fig = pylab.figure()
ax = fig.add_subplot(111)
ax.plot(datax, dataz, '+')
ax.plot(xi, z1, color='red', linewidth=2)
ax.axvline(x, color='black', linewidth=1)
Cursor(ax, vertOn=False, useblit=True, color='black', linewidth=1)
try:
p = pylab.ginput(n=1, timeout=2)
while p == []:
p = pylab.ginput(n=1, timeout=2)
print(x, p[0][1])
except KeyboardInterrupt:
print("そのまま利用します")
print(x, z1[i])
p = [[x, z1[i]]]
points.append(p[0][1])
pylab.close()
z2 = pylab.stineman_interp(datax, xi, points)
delta = (z2 - dataz)**2
sl = 5
# pylab.plot(datax, delta[delta < sl])
# pylab.show()
### interp
# z3 = pylab.stineman_interp(
# xi, datax[delta < sl], dataz[delta < sl])
# pylab.plot(datax, dataz, '+')
# pylab.plot(xi, z3)
# pylab.show()
### interp
err = make_err_func(hex_free_end)
opt = optimize.leastsq(err, [1, 1, 1, 1, 1, 1, 1],
args=(datax[delta<sl], dataz[delta<sl]))[0]
xi2 = pylab.linspace(min_x, max_x, 200)
fity = hex_free_end(opt, xi2)
pylab.plot((datax/(datax+0.5))[::5], (dataz/(datax+0.5))[::5], '+')
pylab.plot(xi2/(xi2+0.5), fity/(xi2+0.5), linewidth=2)
print(xi2/(xi2+0.5))
print(fity/(xi2+0.5))
# pylab.plot(datax, dataz, '+')
# pylab.plot(xi, fity, linewidth=2)
pylab.show()
lines = ''
for x, z in zip(datax[::5], dataz[::5]):
lines += '{0}\t{1}\n'.format(str(x/(x+0.5)), str(z/(x+0.5)))
with open('data.txt', 'w') as wfile:
wfile.write(lines)
lines = ''
for x, z in zip(xi2, fity):
lines += '{0}\t{1}\n'.format(str(x/(x+0.5)), str(z/(x+0.5)))
with open('fit.txt', 'w') as wfile:
wfile.write(lines)
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
cv1parser
"""
from parse_cvm import CVMCv1Parser
import pylab
cv1s = CVMCv1Parser.from_file('cv1.txt')
cv1s.data[0]['data'].set_free_energy_00_from_logtxt('log.txt')
pylab.plot(cv1s.data[0]['data']['comp1'], cv1s.data[0]['data']['g00'])
pylab.show()
pylab.close()
def plot(seq_num, best, fix_zero, with_fit, select_label):
"""
cv1.txt を plot する
"""
seq_dirc = "seq{0}".format(seq_num)
exe = SequenceCVM.from_dirc(seq_dirc)
fig = pylab.figure(figsize=(8, 10))
if not best:
best = len(exe.results.data)
exe.results = exe.results.get_best_cv_scores(best)
if select_label:
exe.results = exe.results.get_data_selected_labels(select_label.split())
color = [pylab.cm.cool(i/len(exe.results['label'])) #pylint: disable=E1101
for i in range(len(exe.results['label']))]
plot2 = fig.add_subplot(212)
plot2.scatter(exe.results['MxCls'], exe.results['CV_score'], c=color, s=50)
plot2.text(exe.results.data[0]['MxCls'] + 0.5, exe.results.data[0]['CV_score'],
exe.results.data[0]['label'])
plot2.set_xlim(0, exe.results['MxCls'].max()+1)
plot2.set_ylim(0, None)
plot1 = fig.add_subplot(211)
for i, label in enumerate(exe.results['label'][::-1]):
print(label)
cv1txt = os.path.join(exe.seq_dirc, label, "cv1.txt")
logtxt = os.path.join(exe.seq_dirc, label, "log.txt_cem")
# cv1.txt が空ファイルの場合の error を除去
try:
data = CVMCv1Parser.from_file(cv1txt).data[0]['data']
except IndexError:
continue
label_txt = "{0}: {1:.4f}".format(
label, exe.results.data[::-1][i]['CV_score'])
# label_txt = label
if fix_zero:
data.set_free_energy_00_from_logtxt(logtxt)
data['g'] = data['g00']
else:
data['g'] = data['F'] * 1.380662 * 6.02 / 1000
color = pylab.cm.cool(1-i/len(exe.results['label'])) #pylint: disable=E1101
plot1.plot(data['comp1'], data['g'], '.', label=label_txt, color=color)
if with_fit:
fitx, fity = fitting_hex(data['comp1'], data['g'])
plot1.plot(fitx, fity, color=color)
# print(help(fig.subplots_adjust))
pylab.legend(bbox_to_anchor=(1.0, 1.0), loc='upper left', borderaxespad=0,
fontsize=12)
plot1.set_ylabel("Free energy (kJ/mol)", fontsize=16)
plot1.set_xlabel("Fraction of atom A", fontsize=16)
plot2.set_ylabel("Predictive Error", fontsize=16)
plot2.set_xlabel("Num of Max Clusters", fontsize=16)
pylab.subplot(211)
pylab.xticks(fontsize=14)
pylab.yticks(fontsize=14)
pylab.subplot(212)
pylab.xticks(fontsize=14)
pylab.yticks(fontsize=14)
pylab.tight_layout()
fig.subplots_adjust(right=0.75)
pylab.show()