import peak_assign as pn
close("all")
f, ax = subplots(figsize=(20,6))
<<<<<<< HEAD
name_of_the_plot_nc=['%s h'%(array(nonano.x_value(nonano.Readfile)[i])) for i in range (shape(nonano.x_value(nonano.Readfile))[0])]
name_of_the_plot_nnc=['%s h'%(array(nnc.x_value(nnc.Readfile)[i])) for i in range (shape(nnc.x_value(nnc.Readfile))[0])]
=======
name_of_the_plot_nc=['%s h'%(array(nonano.x_value()[i])) for i in range (shape(nonano.x_value())[0])]
name_of_the_plot_nnc=['%s h'%(array(nnc.x_value()[i])) for i in range (shape(nnc.x_value())[0])]
>>>>>>> 4fd4d8775961b746663b468da51d99862c5c9d2e
[ax.plot(nonano.curve()[i][0],(np.array(nonano.curve()[i][1])-array(nonano.curve()[0][1]))*10 , '-',alpha=1,label='no nano, %s - 0 h'%(name_of_the_plot_nc[i])) for i in nonano.Readfile()[2]]
[ax.plot(nnc.curve()[i][0],(np.array(nnc.curve()[i][1])-array(nnc.curve()[0][1]))*10 + 5, '--',linewidth=1.5,alpha=1,label='nano, %s - 4.35 h'%(name_of_the_plot_nnc[i])) for i in nnc.Readfile()[2]]
legend(loc=0, fontsize ='small',ncol=2,columnspacing=0.5, labelspacing=0)
#add vertical lines at the local max
i_range = [0, 2, 5, 8]
lengthOftheLine = [0.92,0.9,0.9,0.9,0.9,0.9,0.8,0.8,0.9,0.9]
[ax.axvline(pn.find_local_max(nonano.curve())[1][i],ymin=0,ymax=lengthOftheLine[i],color='k') for i in i_range]
#add names of the peaks
position_y = [3.5,1,2.5 ,2.5, 3, 3,2,2.7,3.5]
[text(pn.find_local_max(nonano.curve())[1][i],position_y[i], pn.name_of_the_peak(nonano.curve())[i],horizontalalignment='center',fontsize=14) for i in i_range]
f.show()
# f.savefig('/Users/hty/desktop/diff pdf compare %s.pdf'%('full range'))
c=S.Spec.line_color[-1],
label='Drying with nano-ZrO$_2$ (%s - %s)' %
(name_of_the_plot[i], name_of_the_plot[0])) for i in [1]
]
#add vertical lines at the local max
# num_of_peak_showed = [0,2,5]
num_of_peak_showed = arange(9)
num_of_peak_showed = append(num_of_peak_showed, [-3, -2, -1])
lengthOftheLine = [
0.6, 0.63, 0.66, 0, 0.68, 0.8, 0.75, 0.61, 0.69, 0.8, 0.8, 0.8
]
[
ax.axvline(pn.find_local_max(interm2_syn)[1][i],
ymin=0,
ymax=lengthOftheLine[i],
color='k',
ls=':') for i in num_of_peak_showed
]
#add names of the peaks
position_y = [0.12, 0.15, 0.2, 1.1, 0.2, 0.33, 0.25, 0.14, 0.22]
[
text(pn.find_local_max(interm2_syn)[1][i],
position_y[i],
pn.name_of_the_peak(interm2_syn)[i],
horizontalalignment='center',
verticalalignment='bottom',
fontsize=14,
peakPosition = [
interm2_syn[0][0][local_max[0][4]], interm2_syn[0][0][local_max[0][5]],
interm2_syn[0][0][local_max[0][6]], 2.8,
interm2_syn[0][0][local_max[0][7]], interm2_syn[0][0][local_max[0][8]],
3.9, interm2_syn[0][0][local_max[0][9]],
interm2_syn[0][0][local_max[0][10]]
]
nameOfthePeak = [
'Si-O', 'Al/Mg-O', 'Ca-O', 'O-O', 'Si-Si', 'Ca-Si', 'Ca-Ca', 'Si-O', 'Ca-O'
]
''
# do normalization
norm_factor_wrt_last_curve = [
interm2_syn[-1][1][pn.find_local_max(interm2_syn)[0][0][4]] /
interm2_syn[i][1][pn.find_local_max(interm2_syn)[0][i][4]]
for i in range(shape(data_files_1)[0])
]
norm_factor_wrt_first_curve = [
interm2_syn[0][1][local_max[0][4]] / interm2_syn[i][1][local_max[i][4]]
for i in range(shape(data_files_1)[0])
]
# set style of the plot
style.use('classic')
#change font properties of the plots
font = {'family': 'normal', 'weight': 'normal', 'size': 17}
matplotlib.rc('font', **font)
def plot():
# start plotting
close('all')
f, ax0 = subplots(figsize=(6, 4.5))
subplots_adjust(left=0.15, bottom=0.16)
# text(0.05, 0.9, target.__name__, transform=ax0.transAxes)
# no normalization
# [ax0.plot(interm2_syn[i][0],np.array(interm2_syn[i][1]), alpha=1,label='%s'%(name_of_the_plot[i])) for i in range (np.shape(data_files_1)[0])]
# with normalization
[
ax0.plot(interm2_syn[i][0],
np.array(interm2_syn[i][1]) * norm_factor_wrt_first_curve[i],
alpha=1,
label='%s' % (name_of_the_plot[i]),
color=line_color[i + interval - 5])
for i in range(np.shape(data_files_1)[0])
]
#add vertical lines at the local max
# num_of_peak_showed = [0,2,5]
num_of_peak_showed = arange(9)
num_of_peak_showed = append(num_of_peak_showed, [-3, -2, -1])
lengthOftheLine = [
0.85, 0.3, 0.66, 0.4, 0.61, 0.8, 0.6, 0.55, 0.6, 0.8, 0.8, 0.8
]
[
ax0.axvline(pn.find_local_max(interm2_syn)[1][i],
ymin=0,
ymax=lengthOftheLine[i],
color='k',
ls=':') for i in num_of_peak_showed
]
#add names of the peaks
position_y = [3.2, -0.8, 1.8, 0, 1.5, 2.7, 1.5, 1, 1.5]
[
text(pn.find_local_max(interm2_syn)[1][i],
position_y[i],
pn.name_of_the_peak(interm2_syn)[i],
horizontalalignment='center',
verticalalignment='bottom',
fontsize=14,
rotation=80) for i in num_of_peak_showed
]
#increase the freq of the ticks
locator_params(axis='x', tight=True, nbins=10)
xlim(0.8, 6)
# ylim (-0.4,0.4)
#ax.axhline(y=0, color='k')
ylabel('G(r) ($\AA^{-2}$)')
xlabel(r'r ($\AA$)')
legend(loc=4,
fontsize='small',
ncol=1,
columnspacing=0.5,
labelspacing=0,
frameon=True)
f.show()
def difference_plot(gs0, gs1, title_text=''):
# f, ax = subplots(nrows=2, ncols=1, sharex=True, figsize=(7,7))
ax0 = subplot(gs0)
text(0.1, 4.5, title_text)
[
ax0.plot(interm2_syn[i][0],
np.array(interm2_syn[i][1]) * norm_factor_wrt_first_curve[i],
alpha=1,
label='%s' % (name_of_the_plot[i]),
color=line_color[i + interval - 4])
for i in range(np.shape(data_files_1)[0])
]
# [ax.plot(interm2_syn[i][0],np.array(interm2_syn[i][1])*norm_factor_wrt_first_curve[i], alpha=1,label='%s'%(name_of_the_plot[i])) for i in range (np.shape(data_files_1)[0])]
#add vertical lines at the local max
# num_of_peak_showed = [0,2,5]
num_of_peak_showed = arange(9)
# num_of_peak_showed = append(num_of_peak_showed, [-3, -2, -1])
lengthOftheLine = [
0.85, 0.3, 0.66, 0.55, 0.61, 0.8, 0.6, 0.55, 0.6, 0.8, 0.8, 0.8
]
[
ax0.axvline(pn.find_local_max(interm2_syn)[1][i],
ymin=0,
ymax=lengthOftheLine[i],
color='k',
ls=':') for i in num_of_peak_showed
]
#add names of the peaks
position_y = [3.2, -0.8, 1.8, 1, 1.5, 2.7, 1.5, 1, 1.5]
[
text(pn.find_local_max(interm2_syn)[1][i],
position_y[i],
pn.name_of_the_peak(interm2_syn)[i],
horizontalalignment='center',
verticalalignment='bottom',
fontsize=14,
rotation=80) for i in num_of_peak_showed
]
#increase the freq of the ticks
locator_params(axis='x', tight=True, nbins=10)
xlim(0.8, 6)
ylim(-3, 4)
#ax.axhline(y=0, color='k')
ylabel('G(r) ($\AA^{-2}$)')
Legend = ax0.legend(loc=4,
fontsize='small',
ncol=2,
columnspacing=0.5,
labelspacing=0,
frameon=True,
title='Drying time')
setp(Legend.get_title(), fontsize='small')
'''difference plots'''
ax1 = subplot(gs1)
mag_factor = 1
# text(0.1, 0.5, '(b)')
line_type = ['-', '-', '--', '-']
marker_type = ['', '', '', '']
line_width = [1, 1, 1.5, 2]
[
ax1.plot(
interm2_syn[i][0],
(np.array(interm2_syn[i][1]) * norm_factor_wrt_first_curve[i] -
array(interm2_syn[0][1])),
linestyle=line_type[i],
linewidth=line_width[i],
alpha=1,
label='%s - %s' % (name_of_the_plot[i], name_of_the_plot[0]),
color=line_color[i + interval - 5])
for i in range(np.shape(data_files_1)[0])[1:]
]
#difference plots
# [ax.plot(interm2_syn[i][0],(np.array(interm2_syn[i][1])*norm_factor_wrt_first_curve[i]-array(interm2_syn[0][1]))*5 + 6, '--', alpha=1,label='%s - %s'%(name_of_the_plot[i], name_of_the_plot[0])) for i in range (np.shape(data_files_1)[0])]
# [ax.plot(interm2_syn[i][0],(np.array(interm2_syn[i][1])-array(interm2_syn[0][1]))*5 + 10, '--', linewidth=1.5,alpha=1,label='%s - 0h no norm.'%(name_of_the_plot[i])) for i in range (np.shape(data_files_1)[0])]
locator_params(axis='x', tight=True, nbins=10)
xlabel(r'r ($\AA$)')
xlim(0.8, 6)
ylim(-0.6, 0.5)
# text(5,7.5,'x 5')
legend(loc=4,
fontsize='small',
ncol=2,
columnspacing=0.5,
labelspacing=0,
frameon=True)
title('Difference', fontsize='small')
return target.__name__
'%s h' % (array(target.peaks(target.Readfile)[0][0::data_interval][i]))
for i in range(shape(data_files_1)[0])
]
else:
data_interval = 9
data_files_1 = target.Readfile()[1][0::data_interval]
name_of_the_plot = [
'%s h' % (array(target.peaks(target.Readfile)[0][0::data_interval][i]))
for i in range(shape(data_files_1)[0])
]
interm2_syn = gd.curve(data_files_1, 141)
# do normalization
norm_factor_wrt_last_curve = [
interm2_syn[-1][1][pn.find_local_max(interm2_syn)[0][0][4]] /
interm2_syn[i][1][pn.find_local_max(interm2_syn)[0][i][4]]
for i in range(shape(data_files_1)[0])
]
norm_factor_wrt_first_curve = [
interm2_syn[0][1][pn.find_local_max(interm2_syn)[0][0][4]] /
interm2_syn[i][1][pn.find_local_max(interm2_syn)[0][i][4]]
for i in range(shape(data_files_1)[0])
]
# set style of the plot
# style.use('classic')
#change font properties of the plots
font = {'family': 'serif', 'weight': 'normal', 'size': 17}
import sys
sys.path.append('/Users/hty/Google Drive/python_modules')
import getData as gd
from numpy import *
from matplotlib.pyplot import *
sys.path.append('/Users/hty/Google Drive/research/APS exp/py_files')
import peak_assign as pn
# import target file
import noNano_rh0 as target
data_file = target.read_reciprocal_space_files('.sq')[1]
xy = gd.curve(data_file,141)
close("all")
# remember to update the range of the label****
[plot(xy[i][0],xy[i][1],label='%s h'%(target.read_reciprocal_space_files('.sq')[3] [i])) for i in range (shape(xy)[0])]
legend(loc=0, fontsize =14,ncol=1,columnspacing=1, labelspacing=0.1)
xlabel(r'r ($\AA^{-1}$)')
ylabel('S(Q)')
show()
local_max = pn.find_local_max(xy)[0]
peak_pos = [xy[i][0][local_max[i][0]] for i in range(shape(xy)[0])]