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@@ -0,0 +1,6 @@
model_checkpoint_path: "model.ckpt-1200"
all_model_checkpoint_paths: "model.ckpt-800"
all_model_checkpoint_paths: "model.ckpt-900"
all_model_checkpoint_paths: "model.ckpt-1000"
all_model_checkpoint_paths: "model.ckpt-1100"
all_model_checkpoint_paths: "model.ckpt-1200"
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@@ -1,10 +1,11 @@
#!/usr/bin/env python
import numpy as np
import cv
#import cv
import cv2
from PIL import Image

import pyfits
#import pyfits
import astropy.io.fits as pyfits
import matplotlib.pyplot as plt

from array import array
@@ -13,7 +14,8 @@

from scipy import optimize
import math as math
import ROOT
#import ROOT # If you tuurn on this, it won't be running...why?

#from numpy import *

add = 1 #root no figure size wo bigger ni dekiru
@@ -27,15 +29,15 @@



print "fit width ", fit_max_x - fit_min_x
print "fit height ", fit_max_y - fit_min_y
print ("fit width ", fit_max_x - fit_min_x)
print ("fit height ", fit_max_y - fit_min_y)

hdulist=pyfits.open('2015.fits')
hdu=hdulist[0]
data=hdu.data
header=hdu.header
height, width = data.shape
print "width=",width,"height=",height
print ("width=",width,"height=",height)
#print data[height-1][width-1]


@@ -68,8 +70,8 @@
f1.write(str)
f1.close()

print "width + %d*2 = " % add, fit_max_x - fit_min_x + add*2
print "height + %d*2 = " % add, fit_max_y - fit_min_y + add*2
print ("width + %d*2 = " % add, fit_max_x - fit_min_x + add*2)
print ("height + %d*2 = " % add, fit_max_y - fit_min_y + add*2)
f_root = open('width_height_for_root.txt','w')
str_x = "%d " % (fit_max_x - fit_min_x + add*2)
str_y = "%d " % (fit_max_y - fit_min_y + add*2)
@@ -188,9 +190,9 @@ def gauss(y, q):
#fit area
fit_min = fit_min_x
fit_max = fit_max_x
print ""
print "fit min =",fit_min, "Hz, fit max =", fit_max, "Hz"
print "max X_stack_mean =", max(X_stack_mean)
print ("")
print ("fit min =",fit_min, "Hz, fit max =", fit_max, "Hz")
print ("max X_stack_mean =", max(X_stack_mean))

parameter_optimal = array('d')
paramater_0 = max(X_stack_mean)
@@ -277,9 +279,9 @@ def gauss(y, q):
fit_min = fit_min_y
#fit_max = max(Y_mean)
fit_max = fit_max_y
print ""
print "fit min =",fit_min, "Hz, fit max =", fit_max, "Hz"
print "max Y_stack_mean =", max(Y_stack_mean)
print ("")
print ("fit min =",fit_min, "Hz, fit max =", fit_max, "Hz")
print ("max Y_stack_mean =", max(Y_stack_mean))

parameter_optimal = array('d')
paramater_0 = max(Y_stack_mean)
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@@ -212,17 +212,18 @@ def func(y, q):
plt.rcParams['font.family'] = 'Arial'
plt.rcParams['pdf.fonttype'] = 42
params = {'backend': 'ps', #
'axes.labelsize': 15, #
'text.fontsize': 15, #
'legend.fontsize': 15, #
'xtick.labelsize': 15, #
'ytick.labelsize': 15,
'axes.labelsize': 20, #
'text.fontsize': 20, #
'legend.fontsize': 20, #
'xtick.labelsize': 20, #
'ytick.labelsize': 20,
'text.usetex': False} #
plt.rcParams.update(params)


#plt.xlabel("Depth distribution from the ground surface of $^{137}$Cs [cm]")
plt.xlabel(u'Buffer depth of $^{137}$Cs $\u03b2$ [cm]')
#plt.xlabel(u'Buffer depth of $^{137}$Cs $\u03b2$ [cm]')
plt.xlabel(u'Buffer depth $\u03b2$ [cm]')
plt.ylabel("$L_{air}$ [m]")
plt.xscale("log")
#plt.legend(['G4 Data', 'Mean','Fitting error', '', 'Observed Lair'],loc="upper left")
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@@ -65,42 +65,45 @@
'text.usetex': False} #
plt.rcParams.update(params)

#"""

# plot theory and observed
"""
ax1 = fig.add_subplot(1, 2, 1)
ax1.pcolormesh(X, Y, Z2, cmap='gist_ncar')
#plt.pcolor(X, Y, Z, cmap='hsv')
#ax1.set_xlabel('X', fontsize=24)
#ax1.pcolormesh(X, Y, Z2, cmap='gist_ncar')
mesh1 = ax1.pcolormesh(X, Y, Z2, cmap='gist_ncar')
ax1.set_ylabel('Height [m]', fontsize=18)
ax1.set_xlabel('Theory', fontsize=18)
ax1.tick_params(labelbottom="off",bottom="off")

mesh1.set_clim(0.1,5.3)
ax2 = fig.add_subplot(1, 2, 2)
ax2.pcolormesh(X, Y, Z1, cmap='gist_ncar')
#ax2.pcolormesh(X, Y, Z1, cmap='gist_ncar')
mesh2 = ax2.pcolormesh(X, Y, Z1, cmap='gist_ncar')
ax2.set_xlabel('Observed', fontsize=18)
ax2.tick_params(labelbottom="off",bottom="off")

mesh2.set_clim(0.1,5.3)
plt.subplots_adjust(wspace=0.5, hspace=0.3, bottom=0.2, left=0.2)
#"""
"""





## plot colorbar
##
##
"""
#"""
fig, ax = plt.subplots()
image = ax.pcolormesh(X, Y, Z1, cmap='gist_ncar')
#image = ax.pcolormesh(X, Y, Z1, cmap='gist_ncar')
image = ax.pcolormesh(X, Y, Z2, cmap='gist_ncar')
ax.axis("image")

divider = make_axes_locatable(ax)
ax_cb = divider.new_horizontal(size="10%", pad=1.0)
fig.add_axes(ax_cb)
image.set_clim(0.1,5.3)
plt.colorbar(image, cax=ax_cb, label=u'dose rate [\u03bcSv/h]')
"""
#"""
##
##

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