def convert_all_to_png(vis_path, out_dir="maps_png", size=None):
units = {
'gas_density': 'Gas Density [g/cm$^3$]',
'Tm': 'Temperature [K]',
'Tew': 'Temperature [K]',
'S': 'Entropy []',
'dm': 'DM Density [g/cm$^3$]',
'v': 'Velocity [km/s]'
}
log_list = ['gas_density']
for vis_file in os.listdir(vis_path):
if ".dat" not in vis_file:
continue
print "converting %s" % vis_file
map_type = re.search('sigma_(.*)_[xyz]', vis_file).group(1)
(image, pixel_size,
axis_values) = read_visualization_data(vis_path + "/" + vis_file,
size)
print "image width in Mpc/h: ", axis_values[-1] * 2.0
x, y = np.meshgrid(axis_values, axis_values)
cmap_max = image.max()
cmap_min = image.min()
''' plotting '''
plt.figure(figsize=(5, 4))
if map_type in log_list:
plt.pcolor(x, y, image, norm=LogNorm(vmax=cmap_max, vmin=cmap_min))
else:
plt.pcolor(x, y, image, vmax=cmap_max, vmin=cmap_min)
cbar = plt.colorbar()
if map_type in units.keys():
cbar.ax.set_ylabel(units[map_type])
plt.axis(
[axis_values[0], axis_values[-1], axis_values[0], axis_values[-1]])
del image
plt.xlabel(r"$Mpc/h$", fontsize=18)
plt.ylabel(r"$Mpc/h$", fontsize=18)
out_file = vis_file.replace("dat", "png")
plt.savefig(out_dir + "/" + out_file, dpi=150)
plt.close()
plt.clf()
def convert_all_to_png(vis_path, out_dir = "maps_png", size = None) :
units = { 'gas_density' : 'Gas Density [g/cm$^3$]',
'Tm' : 'Temperature [K]',
'Tew' : 'Temperature [K]',
'S' : 'Entropy []',
'dm' : 'DM Density [g/cm$^3$]',
'v' : 'Velocity [km/s]' }
log_list = ['gas_density']
for vis_file in os.listdir(vis_path) :
if ".dat" not in vis_file :
continue
print "converting %s" % vis_file
map_type = re.search('sigma_(.*)_[xyz]', vis_file).group(1)
(image, pixel_size, axis_values) = read_visualization_data(vis_path+"/"+vis_file, size)
print "image width in Mpc/h: ", axis_values[-1]*2.0
x, y = np.meshgrid( axis_values, axis_values )
cmap_max = image.max()
cmap_min = image.min()
''' plotting '''
plt.figure(figsize=(5,4))
if map_type in log_list:
plt.pcolor(x,y,image, norm=LogNorm(vmax=cmap_max, vmin=cmap_min))
else :
plt.pcolor(x,y,image, vmax=cmap_max, vmin=cmap_min)
cbar = plt.colorbar()
if map_type in units.keys() :
cbar.ax.set_ylabel(units[map_type])
plt.axis([axis_values[0], axis_values[-1],axis_values[0], axis_values[-1]])
del image
plt.xlabel(r"$Mpc/h$", fontsize=18)
plt.ylabel(r"$Mpc/h$", fontsize=18)
out_file = vis_file.replace("dat", "png")
plt.savefig(out_dir+"/"+out_file, dpi=150 )
plt.close()
plt.clf()
def _plot(self):
p = plt.pcolor(self.matrix, cmap=self.cmap, vmin=self.vmin, vmax=self.vmax)
plt.colorbar(p)
plt.xlim((0, self.matrix.shape[0]))
plt.ylim((0, self.matrix.shape[1]))
if self.labels is not None:
plt.xticks(numpy.arange(0.5, len(self.labels) + 0.5), self.labels, fontsize=self.fontsize, rotation=90)
plt.yticks(numpy.arange(0.5, len(self.labels) + 0.5), self.labels, fontsize=self.fontsize)
def _plot(self):
colormap = plt.pcolor(self.x, self.y, self.z, cmap=self.cmap)
cb = plt.colorbar(colormap)
cb.set_label('value')
def _plot(self):
colormap = plt.pcolor(self.x, self.y, self.z, cmap=self.cmap)
cb = plt.colorbar(colormap)
cb.set_label('value')
# initially the k-loop was here, and it didn't work for any plot except the first one
# for k in range(1,29): # so, this didn't work
print 'now function ', k
for i in range(h):
yc = ylim[1] - i * dy
for j in range(m):
xc = xlim[0] + j * dx
dat[j * n] = xc
dat[j * n + 1] = yc
#print "first DNA: ",dat[0],dat[1];
#print "2nd DNA: ",dat[2],dat[3];
#print "last DNA: ",dat[2*m-2],dat[2*m-1];
r1 = tf.test_func(dat, f, ct.c_int(n), ct.c_int(m), ct.c_int(k))
rarr[i, :] = [f[j] for j in range(m)]
plt.pcolor(x, y, flipud(rarr), vmin=np.min(rarr), vmax=np.max(rarr))
plt.colorbar()
plt.xlim(xlim)
plt.ylim(ylim)
plt.xlabel(r'$x_1$')
plt.ylabel(r'$x_2$')
plt.title('CEC-2013 test function suite:\nno. {0}: {1}'.format(k, fnames[k]))
plt.suptitle('evaluated using ctypes',
x=0.02,
y=0.02,
ha='left',
va='bottom',
fontsize=9)
#plt.show()
plt.savefig('./pics/test_func_' + str(k).zfill(2) +
'_using_ctypes_zoomlevel_2.png')
# initially the k-loop was here, and it didn't work for any plot except the first one
# for k in range(1,29): # so, this didn't work
print 'now function ',k
for i in range(h):
yc=ylim[1]-i*dy
for j in range(m):
xc=xlim[0]+j*dx;
dat[j*n]=xc;
dat[j*n+1]=yc;
#print "first DNA: ",dat[0],dat[1];
#print "2nd DNA: ",dat[2],dat[3];
#print "last DNA: ",dat[2*m-2],dat[2*m-1];
r1=tf.test_func(dat,f,ct.c_int(n),ct.c_int(m),ct.c_int(k))
rarr[i,:]=[f[j] for j in range(m)]
plt.pcolor(x,y,flipud(rarr),vmin=np.min(rarr),vmax=np.max(rarr))
plt.colorbar()
plt.xlim(xlim)
plt.ylim(ylim)
plt.xlabel(r'$x_1$')
plt.ylabel(r'$x_2$')
plt.title('CEC-2013 test function suite:\nno. {0}: {1}'.format(k,fnames[k]))
plt.suptitle('evaluated using ctypes',x=0.02,y=0.02,ha='left',va='bottom',fontsize=9)
#plt.show()
plt.savefig('./pics/test_func_'+str(k).zfill(2)+'_using_ctypes_zoomlevel_2.png')
plt.clf()
plt.close('all')