def plot_array(self, prefix='lasslab', filenumber=0, keyword='cnt', field='dens', refine=2, vrange=[0, 2.7], box_panning=[0.1, 0.1], box_scale=0.8, geom=[0.004, 0.008], figure_size=(4, 8), geom_factor=10000, ifdisplay=True):
'''
This function is used to visualize 2d FLASH output data.
Parameters:
prefix - FLASH output file prefix.
filenumber - FLASH output file number.
keyword - FLASH output file keyword.
field - physical field.
refine - refine level.
vrange - plot range.
box_scale - total box scale.
box_panning - box panning
geom - 2d geometry axis.
figure_size - figure size
geom_factor - 2d geometry axis factor.
Returns:
None.
Raises:
KeyError.
'''
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
import flash_class
fc = flash_class.flash_class()
constant = fc.get_constant(field)
length = len(filenumber)
for j in range(length):
data = fc.get_data(prefix=prefix, filenumber=filenumber[j], keyword=keyword)
field_data = data[field][:]
block = fc.get_block(data, refine=refine, geom=geom, box_scale=box_scale, box_panning=box_panning)
n = len(block)
# plot
fig = plt.figure(figsize=figure_size)
plt.axes([box_panning[0], box_panning[1], box_scale, box_scale], xlim=[0, geom[0]*geom_factor], ylim=[0, geom[1]*geom_factor])
plt.title(field + ' ' + r'$ time = ' + str(filenumber[j]/100.) + ' ns $', fontsize=20)
plt.xlabel(r'$ X/\mu m $', fontsize=16)
plt.ylabel(r'$ Y/\mu m $', fontsize=16)
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
color_map = cm.RdBu_r
for i in range(n):
ax = plt.axes(block[i][1:])
ax = plt.imshow(field_data[block[i][0], 0, :, :]/constant, origin='lower', cmap=color_map, vmin=vrange[0], vmax=vrange[1])
plt.xticks([])
plt.yticks([])
# add color bar
color_bar = fig.add_axes([0.2, 0.04, 0.6, 0.02])
norm = colors.Normalize(vmin=vrange[0], vmax=vrange[1])
cb = colorbar.ColorbarBase(color_bar, cmap=color_map, norm=norm, orientation="horizontal")
if (ifdisplay == True):
plt.show()
else:
s1 = 'figure/'
s2 = field + '_' + str(filenumber[j]).zfill(4) + '.png'
path = s1 + s2
plt.savefig(path, dpi=300)
plt.close()
def calcu_field(self, prefix='lasslab', filenumber=0, keyword='cnt', info='turb_bs', refine=0, field_data=[], \
box_panning=[0.1, 0.1, 0.1], box_scale=0.8, geom=[0., 1., 0., 1., 0., 1.], dimension=2, axis='z', coordinate=0., \
ngrid=[8,8,8], nblock=[12,12,1], geom_factor=10000, ifexist=True):
'''
This function is used to calculate fields inner informaion.
Parameters:
prefix - FLASH output file prefix.
filenumber - FLASH output file number.
keyword - FLASH output file keyword.
refine - refine level.
box_scale - total box scale.
box_panning - box panning
geom - 2d geometry axis.
geom_factor - 2d geometry axis factor.
ngrid - grids of block in each direction.
nblock - block in each direction.
ifexist - if read data file.
field_data - data external.
Returns:
line.
Raises:
KeyError.
'''
import numpy as np
import flash_class
fc = flash_class.flash_class()
if (ifexist == True):
data = fc.get_data(prefix=prefix,
filenumber=filenumber,
keyword=keyword)
block = fc.get_block(data=data,
box_scale=box_scale,
box_panning=box_panning,
geom=geom)
else:
pass
if (info == 'turb_bs'):
ibx = data['magx'][:]
nbx = fc.get_plane(field_data=ibx,
block=block,
dimension=dimension,
axis=axis,
ngrid=ngrid)
bx = fc.grid_UG(narray=nbx, ngrid=ngrid, nblock=nblock)
fftbx = np.fft.fft2(bx)
mbx = np.abs(fftbx)**2
iby = data['magy'][:]
nby = fc.get_plane(field_data=iby,
block=block,
dimension=dimension,
axis=axis,
ngrid=ngrid)
by = fc.grid_UG(narray=nby, ngrid=ngrid, nblock=nblock)
fftby = np.fft.fft2(by)
mby = np.abs(fftby)**2
modeb = mbx + mby
nx, ny = modeb.shape
nx = int(nx / 2)
ny = int(ny / 2)
spec = fc.turb_energy(array=modeb[:nx, :ny], ngrid=500)
elif (info == 'epoch_turb_bs'):
bx = field_data[0]
fftbx = np.fft.fft2(bx)
mbx = np.abs(fftbx)**2
by = field_data[1]
fftby = np.fft.fft2(by)
mby = np.abs(fftby)**2
modeb = mbx + mby
nx, ny = modeb.shape
nx = int(nx / 2)
ny = int(ny / 2)
spec = fc.turb_energy(array=modeb[:nx, :ny], ngrid=500)
else:
pass
return spec
def plot_array(self, array=[], info='PI', prefix='PItest', filenumber=[1], geom=[0,1,0,1], geom_factor=1., vrange=[0,1], shape=[512,512], figure_size=(8,8), \
fig_position=[0.15, 0.15, 0.70, 0.70], rotation='vertical', cb_label=r'$ KGs $', cb_ticks=[(-1e3,0,1e3), ('-1','0','1')], extent=[0,1,0,1], \
plottype='imshow', text=[1.5, 1.02, r'$ \times 10^2 $', False], postfix='cal', ifdisplay=True, ifcolorbar=False):
'''
This function is used to plot Proton Imaging data in FLASH.
Parameters:
array - data array.
info - case information.
prefix - FLASH output file prefix.
filenumber - FLASH output file number.
geom - 2d geometry axis.
geom_factor - 2d geometry axis factor.
vrange - plot range.
shape - shape of array to hold density.
figure_size - figure size.
fig_position - figure position.
rotation - colorbar direction.
cb_label - colorbar label.
cb_ticks - colorbar ticks.
ifdisplay - if display figure.
'''
import numpy as np
import copy
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
import flash_class
fc = flash_class.flash_class()
#from constants import turbMR as const
lens = len(filenumber)
for k in range(lens):
if (info == 'PI'):
color_map = cm.RdBu_r
extent = [
geom[0] * geom_factor, geom[1] * geom_factor,
geom[2] * geom_factor, geom[3] * geom_factor
]
coord = fc.get_PI(prefix=prefix, filenumber=filenumber[k])
array = fc.particle_to_grid(shape=shape, coord=coord)
elif (info == 'epoch_de'):
color_map = cm.RdBu_r
#array = array / (const.J0 * const.E0)
array = np.transpose(array)
extent = [0, 51.2, 0, 51.2]
elif (info == 'problem_image'):
if (plottype == 'imshow'):
#color_map = cm.OrRd
color_map = cm.RdBu_r
extent = [-1.5, 1.5, -1.5, 1.5]
xlabel = r'$ \rm X/mm $'
ylabel = r'$ \rm Y/mm $'
xticks = ([-1.5, -1.0, -0.5, 0, 0.5, 1.0, 1.5], [
'-1.5', '-1.0', '-0.5', '0.0', '0.5', '1.0', '1.5'
])
yticks = ([-1.5, -1.0, -0.5, 0, 0.5, 1.0, 1.5], [
'-1.5', '-1.0', '-0.5', '0.0', '0.5', '1.0', '1.5'
])
cb_label = r'$ \rm Path-Int-Mag \quad B(Gs \cdot cm) $'
cb_ticks = ([-1500, -1000, -500, 0, 500, 1000, 1500],
['-15', '-10', '-5', '0', '5', '10', '15'])
#cb_ticks = ([0, 500, 1000, 1500, 2000], ['0', '5', '10', '15', '20'])
#cb_ticks = ([-1500, -1000, -500, 0, 500, 1000, 1500], ['-15', '-10', '-5', '0', '5', '10', '15'])
elif (plottype == 'stream'):
color_map = cm.RdYlGn_r
xlabel = r'$ \rm X/mm $'
ylabel = r'$ \rm Y/mm $'
xticks = ([-1.5, -1.0, -0.5, 0, 0.5, 1.0, 1.5], [
'-1.5', '-1.0', '-0.5', '0.0', '0.5', '1.0', '1.5'
])
yticks = ([-1.0, -0.5, 0, 0.5,
1.0], ['-1.0', '-0.5', '0.0', '0.5', '1.0'])
cb_label = r'$ \rm Path-Int-Mag \quad B(Gs \cdot cm) $'
cb_ticks = ([-1500, -1000, -500, 0, 500, 1000, 1500],
['-15', '-10', '-5', '0', '5', '10', '15'])
elif (info == 'contrast'):
#color_map = cm.OrRd
color_map = cm.viridis
extent = [-1.5, 1.5, -1, 1]
xlabel = r'$ \rm X/mm $'
ylabel = r'$ \rm Y/mm $'
xticks = ([-1.5, -1.0, -0.5, 0, 0.5, 1.0, 1.5],
['-1.5', '-1.0', '-0.5', '0.0', '0.5', '1.0', '1.5'])
yticks = ([-1.0, -0.5, 0, 0.5,
1.0], ['-1.0', '-0.5', '0.0', '0.5', '1.0'])
cb_label = r'$ \rm contrast \quad \delta \Psi / \Psi_{0} $'
cb_ticks = ([-0.3, -0.2, -0.1, 0.0, 0.1, 0.2, 0.3], [
'-0.3', '-0.2', '-0.1', '0.0', '0.1', '0.2', '0.3'
])
elif (info == 'proton_radiography'):
if (plottype == 'imshow'):
color_map = cm.RdBu_r
extent = [-1, 1, -1, 1]
xlabel = r'$ \rm X $'
ylabel = r'$ \rm Y $'
xticks = ([-1, -0.5, 0, 0.5,
1], ['-1.0', '-0.5', '0.0', '0.5', '1.0'])
yticks = ([-1, -0.5, 0, 0.5,
1], ['-1.0', '-0.5', '0.0', '0.5', '1.0'])
cb_label = r'$ \rm contrast \quad (\psi - \psi_0) / \psi_0 $'
cb_ticks = ([-1, 0, 1], ['-1.0', '0', '1.0'])
elif (plottype == 'stream'):
color_map = cm.RdYlGn_r
xlabel = r'$ \rm X $'
ylabel = r'$ \rm Y $'
xticks = ([-1, -0.5, 0, 0.5,
1], ['-1.0', '-0.5', '0.0', '0.5', '1.0'])
yticks = ([-1, -0.5, 0, 0.5,
1], ['-1.0', '-0.5', '0.0', '0.5', '1.0'])
cb_label = r'$ \rm Path-Int-Mag \quad B(Gs \cdot cm) $'
cb_ticks = ([0, 500, 1000, 1500], ['0', '5', '10', '15'])
else:
pass
if (plottype == 'stream'):
# data
U = array[0]
V = array[1]
X = np.linspace(-1.5, 1.5, U.shape[1])
Y = np.linspace(-1, 1, U.shape[0])
carray = np.sqrt(U**2 + V**2)
font1 = 20
font2 = 16
fontdict1 = {
'family': 'serif',
'style': 'italic',
'weight': 'normal',
'color': 'black',
'size': font1
}
fontdict2 = {
'family': 'serif',
'style': 'italic',
'weight': 'normal',
'color': 'black',
'size': font2
}
fig = plt.figure(figsize=figure_size)
plt.axes(fig_position)
if (plottype == 'imshow'):
#plt.imshow(array, extent=extent, origin='lower', cmap=color_map, aspect='auto', vmin=vrange[0], vmax=vrange[1])
plt.imshow(array,
extent=extent,
cmap=color_map,
aspect='auto',
vmin=vrange[0],
vmax=vrange[1])
elif (plottype == 'stream'):
plt.streamplot(X,
Y,
U,
V,
color=carray,
cmap=color_map,
linewidth=2,
density=2)
plt.xlabel(xlabel, fontdict=fontdict1)
plt.ylabel(ylabel, fontdict=fontdict1)
plt.xticks(xticks[0], xticks[1], fontsize=font2)
plt.yticks(yticks[0], yticks[1], fontsize=font2)
# add color bar
cb_position = copy.deepcopy(fig_position)
cb_position[0] = fig_position[0] + +fig_position[2] + 0.02
cb_position[1] = fig_position[1]
cb_position[2] = 0.02
cb_position[3] = fig_position[3]
color_bar = fig.add_axes(cb_position)
norm = colors.Normalize(vmin=vrange[0], vmax=vrange[1])
cb = colorbar.ColorbarBase(color_bar,
cmap=color_map,
norm=norm,
orientation=rotation)
cb.set_label(cb_label, fontdict=fontdict1)
cb.set_ticks(cb_ticks[0])
cb.set_ticklabels(cb_ticks[1])
cb.ax.tick_params(labelsize=12)
if (text[3] == True):
plt.text(text[0], text[1], text[2], fontsize=font2)
if (ifdisplay == True):
plt.show()
else:
figname = info + '_' + postfix + '.png'
plt.savefig(figname, dpi=300)
plt.close()
def plot_line(self, prefix='lasslab', filenumber=[0], keyword='cnt', info='none', field='dens', refine=0, box_panning=[0.1, 0.1, 0.1], \
box_scale=0.8, geom=[0, 1, 0, 1, 0, 1], dimension=2, axis=['z', 'x'], coordinate=[0., 0.], ngrid=[8,8,8], \
figure_size=(8, 5), xlim=[0,1], ylim=[0,1], geom_factor=1,\
ifdirect=True, ifexist=True, ifrecontruct=True, ifdisplay=True):
'''
This function is used to visualize 2d FLASH output data.
Parameters:
prefix - FLASH output file prefix.
filenumber - FLASH output file number.
keyword - FLASH output file keyword.
info - information.
field - physical field.
refine - refine level.
box_scale - total box scale.
box_panning - box panning
geom - 2d geometry axis.
dimension - dimensions.
axis - coordinate axis.
coordinate - coordinate to be ploted.
ngrid - number of grid in each block.
figure_size - figure size
xlim - x axis range.
ylim - y axis range.
geom_factor - 2d geometry axis factor.
ifreconstruct - if reconstruct data, always True.
ifdisplay - if display figure.
Returns:
None.
Raises:
KeyError.
'''
import matplotlib.pyplot as plt
import flash_class
fc = flash_class.flash_class()
line_list = fc.line_set()
constant = fc.get_constant(field)
plot_lines = []
length = len(filenumber)
for j in range(length):
data = fc.get_data(prefix=prefix,
filenumber=filenumber[j],
keyword=keyword)
block = fc.get_block(data,
refine=refine,
geom=geom,
box_scale=box_scale,
box_panning=box_panning)
field_data = data[field][:]
n = len(block)
figinfo = fc.get_figinfo(box_scale=box_scale,
box_panning=box_panning,
geom=geom,
geom_factor=geom_factor,
axis=axis[0],
coordinate=coordinate[0],
ngrid=ngrid)
narray = fc.get_plane(field_data=field_data,
block=block,
dimension=dimension,
axis=axis[0],
coordinate=figinfo[4],
ngrid=ngrid,
ifexist=ifexist)
if (ifdirect == True):
nline = fc.get_line(narray=narray,
dimension=dimension,
box_scale=box_scale,
box_panning=box_panning,
geom=geom,
axis=axis,
coordinate=coordinate[1],
ngrid=ngrid)
lines = fc.reconstruct(nline=nline,
axis=axis,
ngrid=ngrid,
box_scale=box_scale,
box_panning=box_panning,
geom=geom,
geom_factor=geom_factor)
plot_lines.append(lines)
else:
# convert block to array
pass
return plot_lines
# plot
font1 = 20
font2 = 16
for axis_plot in 'xyz':
if (axis_plot not in axis):
break
fig = plt.figure(figsize=figure_size)
for j in range(length):
plt.plot(plot_lines[j][0],
plot_lines[j][1],
linewidth=2,
label='time = ' + str(filenumber[j]))
plt.xlabel(axis_plot, fontsize=font1)
plt.xlim(xlim)
plt.ylim(ylim)
plt.xticks(fontsize=font2)
plt.yticks(fontsize=font2)
plt.legend(fontsize=font1)
plt.show()
return plot_lines
def plot_block(self, prefix='lasslab', filenumber=[0], keyword='cnt', field='dens', refine=0, vrange=[0, 2.7], box_panning=[0.1, 0.1, 0.1], \
box_scale=0.8, geom=[0., 1., 0., 1., 0., 1.], dimension=2, axis='z', coordinate=0., ngrid=[8,8,8], \
figure_size=(4, 8), geom_factor=10000, cb_position=[0.20, 0.05, 0.70, 0.02], component='z', resistivity=1e-3, rotation='horizontal', \
cb_label=r'$ KGs $', cb_ticks=[(-1e3,0,1e3), ('-1','0','1')], text=[0.1, 0.1, 'Te', False], \
iflog=False, ifexist=True, ifdisplay=True, axisoff=False, dpi=300):
'''
This function is used to visualize 2d FLASH output data.
Parameters:
prefix - FLASH output file prefix.
filenumber - FLASH output file number.
keyword - FLASH output file keyword.
field - physical field.
refine - refine level.
vrange - plot range.
box_scale - total box scale.
box_panning - box panning
geom - 2d geometry axis.
figure_size - figure size.
geom_factor - 2d geometry axis factor.
cb_position - colorbar position.
component - vector component('x', 'y' or 'z').
resistivity - electric resistivity.
ifdisplay - if display figure.
ifexist - if the field exist or need to compute.
axisoff - if turn on axis.
dpi - figuredpi.
Returns:
None.
Raises:
KeyError.
'''
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
import flash_class
fc = flash_class.flash_class()
#constant = fc.get_constant(field)
constant = 1
length = len(filenumber)
for j in range(length):
data = fc.get_data(prefix=prefix,
filenumber=filenumber[j],
keyword=keyword)
block = fc.get_block(data,
refine=refine,
geom=geom,
box_scale=box_scale,
box_panning=box_panning)
# compute
if (ifexist == True):
field_data = data[field][:]
else:
if (field == 'electric_field'):
field_data = fc.compute_field(field_data=data,
block=block,
field=field,
component=component,
resistivity=resistivity)
elif (field == 'tension_force'):
field_data = fc.compute_field(field_data=data,
block=block,
field=field,
component=component,
resistivity=resistivity)
elif (field == 'magnetic_pressure_force'):
field_data = fc.compute_field(field_data=data,
block=block,
field=field,
component=component,
resistivity=resistivity)
elif (field == 'thermal_pressure_force'):
field_data = fc.compute_field(field_data=data,
block=block,
field=field,
component=component,
resistivity=resistivity)
elif (field == 'total_pressure_force'):
field_data = fc.compute_field(field_data=data,
block=block,
field=field,
component=component,
resistivity=resistivity)
else:
print('No match field data!')
# plot
font1 = 20
font2 = 12
fontdict1 = {
'family': 'serif',
'style': 'italic',
'weight': 'normal',
'color': 'black',
'size': font1
}
fontdict2 = {
'family': 'serif',
'style': 'italic',
'weight': 'normal',
'color': 'black',
'size': font2
}
n = len(block)
fig = plt.figure(figsize=figure_size)
figinfo = fc.get_figinfo(box_scale=box_scale,
box_panning=box_panning,
geom=geom,
geom_factor=geom_factor,
axis=axis,
coordinate=coordinate,
ngrid=ngrid)
#plt.axes([box_panning[0], box_panning[1], box_scale, box_scale], xlim=[geom[0]*geom_factor, geom[1]*geom_factor], ylim=[geom[2]*geom_factor, geom[3]*geom_factor])
plt.axes(figinfo[0], xlim=figinfo[1], ylim=figinfo[2])
#plt.title(field + ' ' + r'$ time = ' + str(filenumber[j]) + ' t_0 $', fontsize=20)
plt.xlabel(figinfo[3][0], fontsize=16)
plt.ylabel(figinfo[3][1], fontsize=16)
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
color_map = cm.RdBu_r
#color_map = cm.rainbow
#color_map = cm.Blues
narray = fc.get_plane(field_data=field_data,
block=block,
dimension=dimension,
axis=axis,
coordinate=figinfo[4],
ngrid=ngrid,
ifexist=ifexist)
for i in range(len(narray)):
ax = plt.axes(narray[i][0])
if (ifexist == True):
if (iflog == False):
ax = plt.imshow(narray[i][1] / constant,
origin='lower',
cmap=color_map,
aspect='auto',
vmin=vrange[0],
vmax=vrange[1])
else:
#sign = narray[i][1] / np.abs(narray[i][1])
#lognarray = np.abs(np.log10(np.abs(narray[i][1])))
#ax = plt.imshow(sign * lognarray/constant, origin='lower', cmap=color_map, aspect='auto', vmin=vrange[0], vmax=vrange[1])
ax = plt.imshow(np.log10(np.abs(narray[i][1])) /
constant,
origin='lower',
cmap=color_map,
aspect='auto',
vmin=vrange[0],
vmax=vrange[1])
else:
if (iflog == False):
ax = plt.imshow(field_data[i] / constant,
origin='lower',
cmap=color_map,
aspect='auto',
vmin=vrange[0],
vmax=vrange[1])
else:
ax = plt.imshow(np.log10(field_data[i] / constant),
origin='lower',
cmap=color_map,
aspect='auto',
vmin=vrange[0],
vmax=vrange[1])
setax = plt.gca()
setax.spines['top'].set_linewidth(0.1)
setax.spines['bottom'].set_linewidth(0.1)
setax.spines['left'].set_linewidth(0.1)
setax.spines['right'].set_linewidth(0.1)
plt.xticks([])
plt.yticks([])
if (axisoff == True):
plt.axis('off')
# add color bar
color_bar = fig.add_axes(cb_position)
norm = colors.Normalize(vmin=vrange[0], vmax=vrange[1])
cb = colorbar.ColorbarBase(color_bar,
cmap=color_map,
norm=norm,
orientation=rotation)
#cb.set_label(cb_label, fontdict=fontdict2)
cb.set_ticks(cb_ticks[0])
cb.set_ticklabels(cb_ticks[1])
cb.ax.tick_params(labelsize=12)
if (text[3] == True):
plt.text(text[0], text[1], text[2], fontsize=font2)
if (ifdisplay == True):
plt.show()
else:
s1 = 'figure/'
s2 = field + '_' + axis + '_ ' + str(
filenumber[j]).zfill(4) + '.png'
path = s1 + s2
plt.savefig(path, dpi=dpi)
plt.close()
return narray
prefix='Harris_mhd_2d',
filenumber=[0],
keyword='cnt',
case='energy',
refine=0,
geom=[-20, 20, -20, 20],
box_scale=0.8,
box_panning=[0.1, 0.1],
ngrid=16):
'''
'''
import numpy as np
import matplotlib.pyplot as plt
import flash_class
fc = flash_class.flash_class()
length = len(filenumber)
# calculation
array = np.zeros([10, length])
for i in range(length):
data = fc.get_data(prefix=prefix,
filenumber=filenumber[i],
keyword=keyword)
block = fc.get_block(data,
refine=refine,
geom=geom,
box_scale=box_scale,
box_panning=box_panning)
# select case
if (case == 'energy'):
def plot_line(self, prefix='lasslab', filenumber=0, keyword='cnt', field='dens', refine=0, vrange=[0, 2.7], box_panning=[0.1, 0.1], box_scale=0.8, geom=[0.004, 0.008], figure_size=(8, 4), geom_factor=10000, axis='x', coordinate=0.5, ngrid=16, ifrecontruct=True, ifdisplay=True):
'''
This function is used to visualize 2d FLASH output data.
Parameters:
prefix - FLASH output file prefix.
filenumber - FLASH output file number.
keyword - FLASH output file keyword.
field - physical field.
refine - refine level.
vrange - plot range.
box_scale - total box scale.
box_panning - box panning
geom - 2d geometry axis.
figure_size - figure size
geom_factor - 2d geometry axis factor.
axis - coordinate axis.
coordinate - coordinate.
ngrid - number of grid in each block.
ifdisplay - if display figure.
Returns:
None.
Raises:
d5 # plot
fig = plt.figure(figsize=figure_size)
plt.title(field + ' ' + r'$ time = ' + str(filenumber[j]/100.) + ' ns $', fontsize=20)
plt.xlabel(coord[2], fontsize=16)
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
KeyError.
'''
import matplotlib.pyplot as plt
import flash_class
fc = flash_class.flash_class()
constant = fc.get_constant(field)
line_list = fc.line_set()
coord = fc.get_coord(axis=axis, coordinate=coordinate, geom=geom, geom_factor=geom_factor, box_scale=box_scale, box_panning=box_panning)
length = len(filenumber)
# plot
fig = plt.figure(figsize=figure_size)
plt.title(field + ' ' + axis + ' = ' + str(coordinate), fontsize=20)
plt.xlabel(coord[2], fontsize=16)
plt.xticks(fontsize=12)
plt.yticks(fontsize=12)
for j in range(length):
data = fc.get_data(prefix=prefix, filenumber=filenumber[j], keyword=keyword)
field_data = data[field][:]
block = fc.get_block(data, refine=refine, geom=geom, box_scale=box_scale, box_panning=box_panning)
array = fc.get_line(field_data=field_data, block=block, axis=axis, coordinate=coord[0], ngrid=ngrid)
if (ifrecontruct == False):
n = len(array)
for i in range(n):
plt.plot(array[i][0], array[i][1]/constant, linewidth=2)
else:
array = fc.reconstruct(array=array, axis=axis, ngrid=ngrid, geom=geom, geom_factor=geom_factor, box_scale=box_scale, box_panning=box_panning, constant=constant)
legend = 'T = ' + str(filenumber[j]/100.) + ' ns'
plt.plot(array[0], array[1]/constant, line_list[j], linewidth=2, label=legend)
plt.legend()
if (ifdisplay == True):
plt.show()
else:
s1 = 'figure/'
s2 = 'line_' + field + '_'
s3 = axis + ' ' + str(coordinate) + '.png'
path = s1 + s2 + s3
plt.savefig(path, dpi=300)
plt.close()