def something(rundir, file_no):
my_path = os.getcwd()
#print(my_path)
working_dir = my_path + '/' + rundir
#print(working_dir)
efield_dir = working_dir + '/DIAG/Ex/'
phase_space_dir = working_dir + '/DIAG/Vx_x/'
ex_prefix = 'Ex-0_'
phase_prefix = 'vx_x_'
plt.figure(figsize=(10, 5))
filename1 = phase_space_dir + phase_prefix + repr(file_no).zfill(
6) + '.h5'
filename2 = efield_dir + ex_prefix + repr(file_no).zfill(6) + '.h5'
#print(filename1)
#print(filename2)
phase_space = np.abs(osh5io.read_h5(filename1))
# print(repr(phase_space))
ex = osh5io.read_h5(filename2)
phase_plot = plt.subplot(121)
#print(repr(phase_space.axes[0].min))
#print(repr(phase_space.axes[1].min))
title = phase_space.data_attrs['LONG_NAME']
time = phase_space.run_attrs['TIME'][0]
ext_stuff = [
phase_space.axes[1].min, phase_space.axes[1].max,
phase_space.axes[0].min, phase_space.axes[0].max
]
phase_contour = plt.contourf(
abs(phase_space) + 1e-11,
levels=[0.1, 1, 2, 3, 5, 10, 100, 1000, 100000],
extent=ext_stuff,
cmap='Spectral',
vmin=1e-1,
vmax=100000,
norm=matplotlib.colors.LogNorm(vmin=0.1, vmax=100000))
phase_plot.set_title('Phase Space' + ' , t=' + repr(time) +
' $\omega_{pe}^{-1}$')
phase_plot.set_xlabel('Position [$\Delta x$]')
phase_plot.set_ylabel('Velocity [$\omega_{pe} \Delta x$]')
#plt.colorbar()
#osh5vis.oscontour(phase_space,levels=[10**-5,10**-3,10**-1,1,10,100],colors='black',linestyles='dashed',vmin=1e-5,vmax=1000)
plt.contour(phase_space,
levels=[0.1, 1, 2, 3, 5, 10, 100, 1000, 100000],
extent=ext_stuff,
colors='black',
linestyles='dashed')
plt.colorbar(phase_contour)
ex_plot = plt.subplot(122)
plt.plot(ex[0, :])
plt.ylim([-2, 2])
ex_plot.set_xlabel('Position [$\Delta x$]')
ex_plot.set_ylabel('Electric Field')
plt.tight_layout()
plt.show()
def combine(dir_or_filelist,
prefix=None,
file_slice=slice(None, ),
preprocess=None,
axesdata=None,
save=None):
"""
stack a directory of grid data and optionally save the result to a file
:param dir_or_filelist: name of the directory
:param prefix: string, match file names with specific prefix
:param file_slice: a slice that applies to the file name list, useful for skipping every other files or start
in the middle of the list for example
:param preprocess: a list of callable (and their args and kwargs if any) that will act on the data before stacking
happens. It has to accept one H5Data objects as argument and return one H5Data objects.
Note that it has to be a list, not tuple or any other type, aka if isinstance(preprocess, list)
returns False then this parameter will be ignored entirely.
:param axesdata: user difined axes, see stack for more detail
:param save: name of the save file. user can also set it to true value and the output will use write_h5 defaults
:return: combined grid data, one dimension more than the preprocessed original data
Usage of preprocess:
The functino list should look like:
[(func1, arg11, arg21, ..., argn1, {'kwarg11': val11, 'kwarg21': val21, ..., 'kwargn1', valn1}),
(func2, arg12, arg22, ..., argn2, {'kwarg12': val12, 'kwarg22': val22, ..., 'kwargn2', valn2}),
...,
(func2, arg1n, arg2n, ..., argnn, {'kwarg1n': val1n, 'kwarg2n': val2n, ..., 'kwargnn', valnn})] where
any of the *args and/or **args can be omitted. see also __parse_func_param for limitations.
if preprocess=[(numpy.power, 2), (numpy.average, {axis=0}), numpy.sqrt], then the data to be stacked is
numpy.sqrt( numpy.average( numpy.power( read_h5(file_name), 2 ), axis=0 ) )
"""
prfx = str(prefix).strip() if prefix else ''
if isinstance(dir_or_filelist, str):
flist = sorted(glob.glob(dir_or_filelist + '/' + prfx +
'*.h5'))[file_slice]
else: # dir_or_filelist is a list of file names
flist = dir_or_filelist[file_slice]
if isinstance(preprocess, list) and preprocess:
func_list = [__parse_func_param(item) for item in preprocess]
tmp = [
reduce(lambda x, y: y[0](x, *y[1], **y[2]), func_list,
osh5io.read_h5(fn)) for fn in flist
]
else:
tmp = [osh5io.read_h5(f) for f in flist]
res = stack(tmp, axesdata=axesdata)
if save:
if not isinstance(save, str):
save = dir_or_filelist if isinstance(
dir_or_filelist, str) else './' + res.name + '.h5'
osh5io.write_h5(res, save)
return res
def __init__(self,
filefilter,
processing=Generic2DPlotCtrl._idle,
**extra_kwargs):
fp = filefilter + '/*.h5' if os.path.isdir(filefilter) else filefilter
self.filter, self.flist, self.processing = fp, sorted(
glob.glob(fp)), processing
try:
self.data = processing(osh5io.read_h5(self.flist[0]))
except IndexError:
raise IOError('No file found matching ' + fp)
items_layout = Layout(flex='1 1 auto', width='auto')
self.file_slider = widgets.SelectionSlider(options=self.flist,
description='filename:',
value=self.flist[0],
continuous_update=False,
layout=items_layout)
self.time_label = widgets.Label(value=osh5vis.time_format(
self.data.run_attrs['TIME'][0], self.data.run_attrs['TIME UNITS']),
layout=items_layout)
self.file_slider.observe(self.update_slice, 'value')
super(DirSlicer, self).__init__(self.data,
time_in_title=False,
**extra_kwargs)
def make_plot(rundir, file_no):
my_path = os.getcwd()
working_dir = my_path + '/' + rundir
efield_dir = working_dir + '/MS/FLD/e1/'
laser_dir = working_dir + '/MS/FLD/e2/'
eden_dir = working_dir + '/MS/DENSITY/electrons/charge/'
phase_space_dir = working_dir + '/MS/PHA/p1x1/electrons/'
p2x1_dir = working_dir + '/MS/PHA/p2x1/electrons/'
efield_prefix = 'e1-'
laser_prefix = 'e2-'
phase_prefix = 'p1x1-electrons-'
p2x1_prefix = 'p2x1-electrons-'
eden_prefix = 'charge-electrons-'
filename1 = phase_space_dir + phase_prefix + repr(file_no).zfill(
6) + '.h5'
fig = plt.figure(figsize=(12, 5))
phase_space = np.abs(osh5io.read_h5(filename1))
time = phase_space.run_attrs['TIME'][0]
fig.suptitle('Time = ' + repr(time) + '$\omega_p^{-1}$', fontsize=18)
filename2 = eden_dir + eden_prefix + repr(file_no).zfill(6) + '.h5'
filename3 = efield_dir + efield_prefix + repr(file_no).zfill(6) + '.h5'
eden = osh5io.read_h5(filename2)
ex = osh5io.read_h5(filename3)
psi = osh5io.read_h5(filename3)
den_plot = plt.subplot(121)
osh5vis.osplot(eden, title='Electron Density')
ex_plot = plt.subplot(122)
for i in range(psi.shape[0] - 2, -1, -1):
psi[i] = psi[i + 1] + psi.axes[0].increment * psi[i]
osh5vis.osplot(psi, title='Wake $\psi$ ', ylabel='$\psi [m_e c^2/e]$')
second_x = plt.twinx()
second_x.plot(ex.axes[0], ex, 'g', linestyle='-.')
second_x.set_ylabel('$E_{z}$', color='g')
second_x.tick_params(axis='y', labelcolor='g')
def plot_maxgamma_t(simdir):
maxg, time = [], []
for f in sorted(glob.glob(simdir + '/MS/PHA/p1x1/electrons/*.h5')):
data = read_h5(f)
ind = np.nonzero(data)
if len(ind[0] == 0):
maxg.append(np.sqrt(1 + (data.axes[0][max(ind[0])])**2))
time.append(data.run_attrs['TIME'])
print('max gamma = ', max(maxg))
def make_plot(rundir, file_no):
my_path = os.getcwd()
#print(my_path)
working_dir = my_path + '/' + rundir
#print(working_dir)
efield_dir = working_dir + '/MS/FLD/e1/'
laser_dir = working_dir + '/MS/FLD/e2/'
eden_dir = working_dir + '/MS/DENSITY/electrons/charge/'
phase_space_dir = working_dir + '/MS/PHA/p1x1/electrons/'
p2x1_dir = working_dir + '/MS/PHA/p2x1/electrons/'
efield_prefix = 'e1-'
laser_prefix = 'e2-'
phase_prefix = 'p1x1-electrons-'
p2x1_prefix = 'p2x1-electrons-'
eden_prefix = 'charge-electrons-'
filename1 = phase_space_dir + phase_prefix + repr(file_no).zfill(
6) + '.h5'
fig = plt.figure(figsize=(12, 5))
phase_space = np.abs(osh5io.read_h5(filename1))
time = phase_space.run_attrs['TIME'][0]
fig.suptitle('Time = ' + repr(time) + '$\omega_p^{-1}$', fontsize=18)
filename4 = laser_dir + laser_prefix + repr(file_no).zfill(6) + '.h5'
ey = osh5io.read_h5(filename4)
ey_plot = plt.subplot(121)
osh5vis.osplot(ey, title='Laser Electric Field')
ey_plot_k = plt.subplot(122)
osh5vis.osplot(np.abs(osh5utils.fft(ey)),
xlim=[0, 20],
linestyle='-',
title='k spectrum')
def make_plot(rundir, file_no):
my_path = os.getcwd()
working_dir = my_path + '/' + rundir
efield_dir = working_dir + '/MS/FLD/e1/'
laser_dir = working_dir + '/MS/FLD/e2/'
eden_dir = working_dir + '/MS/DENSITY/electrons/charge/'
phase_space_dir = working_dir + '/MS/PHA/p1x1/electrons/'
p2x1_dir = working_dir + '/MS/PHA/p2x1/electrons/'
efield_prefix = 'e1-'
laser_prefix = 'e2-'
phase_prefix = 'p1x1-electrons-'
p2x1_prefix = 'p2x1-electrons-'
eden_prefix = 'charge-electrons-'
filename1 = phase_space_dir + phase_prefix + repr(file_no).zfill(
6) + '.h5'
fig = plt.figure(figsize=(12, 5))
phase_space = np.abs(osh5io.read_h5(filename1))
time = phase_space.run_attrs['TIME'][0]
fig.suptitle('Time = ' + repr(time) + '$\omega_p^{-1}$', fontsize=18)
filename2 = eden_dir + eden_prefix + repr(file_no).zfill(6) + '.h5'
filename3 = efield_dir + efield_prefix + repr(file_no).zfill(6) + '.h5'
eden = osh5io.read_h5(filename2)
ex = osh5io.read_h5(filename3)
den_plot = plt.subplot(121)
osh5vis.osplot(eden, title='Electron Density')
for i in range(ex.shape[0] - 2, -1, -1):
ex[i] = ex[i + 1] + ex.axes[0].increment * ex[i]
ex_plot = plt.subplot(122)
osh5vis.osplot(ex, title='Wake $\psi$ ', ylabel='$\psi [m_e c^2/e]$')
b2 = sorted(glob.glob(dirName + '/FLD/b2' + dir_ext + '/*.h5'))
b3 = sorted(glob.glob(dirName + '/FLD/b3' + dir_ext + '/*.h5'))
total_time = len(e2)
my_share = total_time // size
i_begin = rank * my_share
if rank < (size - 1):
i_end = (rank + 1) * my_share
else:
i_end = total_time
part = total_time / size
#
# read the second file to get the time-step
#
h5_filename = e2[1]
h5_data = osh5io.read_h5(h5_filename)
array_dims = h5_data.shape
nx = array_dims[0]
# ny = array_dims[1]
time_step = h5_data.run_attrs['TIME'][0]
# h5_output = hdf_data()
# h5_output.shape = [total_time, nx]
print('nx=' + repr(nx))
# print('ny=' + repr(ny))
print('time_step=' + repr(time_step))
print('total_time=' + repr(total_time))
h5_output = np.zeros((total_time, nx))
total = np.zeros((total_time,nx))
#total = 0
# tmp = ndimage.filters.median_filter(r.values, size=3)
tmp = scipy.signal.medfilt2d(r.values)
mask = np.abs(r.values) > np.abs(tmp) * 2
np.copyto(r.values, tmp, where=mask)
else:
r.values = ndimage.filters.median_filter(r.values, size=3)
if kmax is not None:
r.values[r.values > kmax] = kmax
r.values[r.values < -kmax] = -kmax
r.data_attrs['UNITS'] = monogenic_local_phase.axes[axis].units**-1
return r
if __name__ == '__main__':
fn = 'n0-123456.h5'
d = osh5io.read_h5(fn)
# d = subrange(d, ((0, 35.5), (0, 166)))
# d = np.ones((7, 20))
# d = rebin(d, fac=[3, 3])
# d = d.subrange(bound=[None, (None, 23., -10.)])
d.set_value(bound=(None, (None, 140., 10.)),
val=2.,
inverse_select=True,
method=np.multiply)
print(repr(d.view(np.ndarray)))
c = hfft(d)
print('c = ', repr(c))
b = ihfft(c)
print('b is d? ', b is d)
diff = d - b
print('b - d = ', diff.view(np.ndarray))
total_time = len(e1)
my_share = total_time // size
i_begin = rank * my_share
if rank < (size - 1):
i_end = (rank + 1) * my_share
else:
i_end = total_time
part = total_time / size
#
# read the second file to get the time-step
#
h5_filename = e1[1]
h5_data = osh5io.read_h5(h5_filename)
array_dims = h5_data.shape
#
# the array is transposed due to Fortran array ordering
nx = array_dims[0]
ny = array_dims[1]
#
#
time_step = h5_data.run_attrs['TIME'][0]
# h5_output = hdf_data()
# h5_output.shape = [total_time, nx]
print('nx=' + repr(nx))
print('ny=' + repr(ny))
def something(rundir, file_no):
my_path = os.getcwd()
#print(my_path)
working_dir = my_path + '/' + rundir
#print(working_dir)
efield_dir = working_dir + '/MS/FLD/e1/'
laser_dir = working_dir + '/MS/FLD/e2/'
eden_dir = working_dir + '/MS/DENSITY/electrons/charge/'
iden_dir = working_dir + '/MS/DENSITY/ions/charge/'
phase_space_dir = working_dir + '/MS/PHA/p1x1/ions/'
p1x1_dir = working_dir + '/MS/PHA/p1x1/electrons/'
efield_prefix = 'e1-'
laser_prefix = 'e2-'
phase_prefix = 'p1x1-ions-'
p1x1_prefix = 'p1x1-electrons-'
eden_prefix = 'charge-electrons-'
iden_prefix = 'charge-ions-'
fig = plt.figure(figsize=(12, 16))
# filename1=phase_space_dir+phase_prefix+repr(file_no).zfill(6)+'.h5'
filename2 = eden_dir + eden_prefix + repr(file_no).zfill(6) + '.h5'
filename3 = efield_dir + efield_prefix + repr(file_no).zfill(6) + '.h5'
filename4 = laser_dir + laser_prefix + repr(file_no).zfill(6) + '.h5'
filename5 = p1x1_dir + p1x1_prefix + repr(file_no).zfill(6) + '.h5'
# filename6=iden_dir+iden_prefix+repr(file_no).zfill(6)+'.h5'
#print(filename1)
#print(filename2)
phase_space = np.abs(osh5io.read_h5(filename5))
# print(repr(phase_space))
eden = osh5io.read_h5(filename2)
ex = osh5io.read_h5(filename3)
ey = osh5io.read_h5(filename4)
# p1x1=np.abs(osh5io.read_h5(filename5))
# iden = osh5io.read_h5(filename6)
phase_plot = plt.subplot(224)
#print(repr(phase_space.axes[0].min))
#print(repr(phase_space.axes[1].min))
title = phase_space.data_attrs['LONG_NAME']
time = phase_space.run_attrs['TIME'][0]
fig.suptitle('Time = ' + repr(time) + '$\omega_p^{-1}$', fontsize=24)
ext_stuff = [
phase_space.axes[1].min, phase_space.axes[1].max,
phase_space.axes[0].min, phase_space.axes[0].max
]
data_max = max(np.abs(np.amax(phase_space)), 100)
#print(repr(data_max))
phase_contour = plt.contourf(
np.abs(phase_space + 0.000000001),
levels=[
0.000001 * data_max, 0.00001 * data_max, 0.0001 * data_max,
0.001 * data_max, 0.005 * data_max, 0.01 * data_max,
0.02 * data_max, 0.05 * data_max
],
extent=ext_stuff,
cmap='Spectral',
vmin=1e-6 * data_max,
vmax=1.5 * data_max,
norm=colors.LogNorm(vmin=0.000001 * data_max, vmax=1.5 * data_max))
phase_plot.set_title('Ion P1X1 Phase Space')
phase_plot.set_xlabel('Position [$c / \omega_{p}$]')
phase_plot.set_ylabel('Proper Velocity $\gamma v_1$ [ c ]')
# second_x = plt.twinx()
# second_x.plot(ex.axes[0],ex,'g',linestyle='-.')
#plt.colorbar()
#osh5vis.oscontour(phase_space,levels=[10**-5,10**-3,10**-1,1,10,100],colors='black',linestyles='dashed',vmin=1e-5,vmax=1000)
# plt.contour(np.abs(phase_space+0.000001),levels=[0.0001,0.001,0.01,0.05,0.1,0.2,0.5,1],extent=ext_stuff,colors='black',linestyles='dashed')
plt.colorbar(phase_contour)
den_plot = plt.subplot(223)
osh5vis.osplot(np.log(np.sum(np.abs(phase_space), axis=1) + 0.001),
title='f(v)')
ex_plot = plt.subplot(222)
osh5vis.osplot(ex, title='Wake E-field ', ylabel='$E_1 [m_e c^2/e]$')
ey_plot = plt.subplot(221)
osh5vis.osplot(ey, title='Laser Electric Field')
def update_slice(self, change):
self.data = self.processing(osh5io.read_h5(change['new']))
self.time_label.value = osh5vis.time_format(
self.data.run_attrs['TIME'][0], self.data.run_attrs['TIME UNITS'])
self.redraw(self.data)
def make_plot(rundir, file_no):
my_path = os.getcwd()
working_dir = my_path + '/' + rundir
efield_dir = working_dir + '/MS/FLD/e1/'
phase_space_dir = working_dir + '/MS/PHA/p1x1/electrons/'
p2x1_dir = working_dir + '/MS/PHA/p2x1/electrons/'
efield_prefix = 'e1-'
phase_prefix = 'p1x1-electrons-'
p2x1_prefix = 'p2x1-electrons-'
fig = plt.figure(figsize=(12, 5))
filename1 = phase_space_dir + phase_prefix + repr(file_no).zfill(
6) + '.h5'
filename3 = efield_dir + efield_prefix + repr(file_no).zfill(6) + '.h5'
filename5 = p2x1_dir + p2x1_prefix + repr(file_no).zfill(6) + '.h5'
phase_space = np.abs(osh5io.read_h5(filename1))
ex = osh5io.read_h5(filename3)
p2x1 = np.abs(osh5io.read_h5(filename5))
phase_plot = plt.subplot(121)
title = phase_space.data_attrs['LONG_NAME']
time = phase_space.run_attrs['TIME'][0]
fig.suptitle('Time = ' + repr(time) + '$\omega_p^{-1}$', fontsize=18)
ext_stuff = [
phase_space.axes[1].min, phase_space.axes[1].max,
phase_space.axes[0].min, phase_space.axes[0].max
]
data_max = max(np.abs(np.amax(phase_space)), 100)
phase_contour = plt.contourf(
np.abs(phase_space + 0.000000001),
levels=[
0.00001 * data_max, 0.0001 * data_max, 0.001 * data_max,
0.01 * data_max, 0.05 * data_max, 0.1 * data_max,
0.2 * data_max, 0.5 * data_max
],
extent=ext_stuff,
cmap='Spectral',
vmin=1e-5 * data_max,
vmax=1.5 * data_max,
norm=colors.LogNorm(vmin=0.00001 * data_max, vmax=1.5 * data_max))
phase_plot.set_title('P1X1 Phase Space')
phase_plot.set_xlabel('Position [$c / \omega_{p}$]')
phase_plot.set_ylabel('Proper Velocity $\gamma v_1$ [ c ]')
second_x = plt.twinx()
second_x.plot(ex.axes[0], ex, 'g', linestyle='-.')
plt.colorbar(phase_contour)
p2x1_plot = plt.subplot(122)
title = p2x1.data_attrs['LONG_NAME']
time = p2x1.run_attrs['TIME'][0]
ext_stuff = [
p2x1.axes[1].min, p2x1.axes[1].max, p2x1.axes[0].min,
p2x1.axes[0].max
]
p2x1_contour = plt.contourf(np.abs(p2x1 + 0.000000001),
levels=[
0.00001, 0.0001, 0.001, 0.01, 0.05,
0.1, 0.2, 0.5, 1, 10, 100, 500
],
extent=ext_stuff,
cmap='Spectral',
vmin=1e-5,
vmax=3000,
norm=colors.LogNorm(vmin=0.0001,
vmax=3000))
p2x1_plot.set_title('P2X1 Phase Space')
p2x1_plot.set_xlabel('Position [$c/ \omega_{p}$]')
p2x1_plot.set_ylabel('Proper Velocity $\gamma v_2$ [$c$]')
plt.colorbar(p2x1_contour)
total_time = len(e2)
i_end=i_begin+total_time*file_interval
my_share = total_time // size
i_begin = rank * my_share
if rank < (size - 1):
i_end = (rank + 1) * my_share
else:
i_end = total_time
part = total_time / size
avg_array=np.ones(n_avg)/n_avg
#
# read the second file to get the time-step
#
#
h5_filename = e2[1]
h5_data = osh5io.read_h5(h5_filename)
array_dims = h5_data.shape
nx = array_dims[0]
dx=h5_data.axes[0]
ny = array_dims[1]
time_step = h5_data.run_attrs['TIME'][0]
# h5_output = hdf_data()
# h5_output.shape = [total_time, nx]
print('nx=' + repr(nx))
print('ny=' + repr(ny))
print('time_step=' + repr(time_step))
print('total_time=' + repr(total_time))
print('i_begin =' + repr(i_begin))
print('i_end =' + repr(i_end))
print('file_interval =' + repr(file_interval))
def srs_quick_look(path,fileno):
path_e1=path_main+'/MS/FLD/e1/'
file_prefix_e1='e1-'
path_e2=path_main+'/MS/FLD/e2/'
file_prefix_e2='e2-'
path_e3=path_main+'/MS/FLD/e3/'
file_prefix_e3='e3-'
path_b1=path_main+'/MS/FLD/b1/'
file_prefix_b1='b1-'
path_b2=path_main+'/MS/FLD/b2/'
file_prefix_b2='b2-'
path_b3=path_main+'/MS/FLD/b3/'
file_prefix_b3='b3-'
path_p1x1_e = path_main+'/MS/PHA/p1x1/species_1/'
file_prefix_p1x1_e = 'p1x1-species_1-'
# fileno = 22500
interval = 30
nfiles=10
path_p1p2_e = path_main+'/MS/PHA/p1p2/species_1/'
file_prefix_p1p2_e = 'p1p2-species_1-'
from scipy import signal
filename_e1=path_e1+file_prefix_e1+repr(fileno).zfill(6)+'.h5'
filename_e2=path_e2+file_prefix_e2+repr(fileno).zfill(6)+'.h5'
filename_e3=path_e3+file_prefix_e3+repr(fileno).zfill(6)+'.h5'
filename_b1=path_b1+file_prefix_b1+repr(fileno).zfill(6)+'.h5'
filename_b2=path_b2+file_prefix_b2+repr(fileno).zfill(6)+'.h5'
filename_b3=path_b3+file_prefix_b3+repr(fileno).zfill(6)+'.h5'
filename_p1x1_e = path_p1x1_e+file_prefix_p1x1_e+repr(fileno).zfill(6)+'.h5'
filename_p1p2_e = path_p1p2_e+file_prefix_p1p2_e+repr(fileno).zfill(6)+'.h5'
# print(filename)
e1 = osh5io.read_h5(filename_e1)
e2 = osh5io.read_h5(filename_e2)
e3 = osh5io.read_h5(filename_e3)
b1 = osh5io.read_h5(filename_b1)
b2 = osh5io.read_h5(filename_b2)
b3 = osh5io.read_h5(filename_b3)
# print(e1.axes[0].attrs)
# Method 1: Just read files
# p1x1_e = osh5io.read_h5(filename_p1x1_e)
# p1p2_e = osh5io.read_h5(filename_p1p2_e)
# Method 2: Average over N steps
interval=30
nfiles = 20
p1x1_e = phase_space_average_new(path_p1x1_e,file_prefix_p1x1_e,fileno,interval,nfiles)
p1p2_e = phase_space_average_new(path_p1p2_e,file_prefix_p1p2_e,fileno,interval,nfiles)
SMALL_SIZE = 12
MEDIUM_SIZE = 14
BIGGER_SIZE = 18
plt.rc('font', size=SMALL_SIZE) # controls default text sizes
plt.rc('axes', titlesize=SMALL_SIZE) # fontsize of the axes title
plt.rc('axes', labelsize=MEDIUM_SIZE) # fontsize of the x and y labels
plt.rc('xtick', labelsize=SMALL_SIZE) # fontsize of the tick labels
plt.rc('ytick', labelsize=SMALL_SIZE) # fontsize of the tick labels
plt.rc('legend', fontsize=SMALL_SIZE) # legend fontsize
plt.rc('figure', titlesize=BIGGER_SIZE) # fontsize of the figure title
s1 = e2*b3 - e3 * b2
s1.data_attrs['NAME']='S1'
s1.data_attrs['LONG_NAME']='S_1'
n_smooth=200
smoothing=np.ones((1,n_smooth))/n_smooth
n_avg = 200
smooth_array=np.ones((1,n_avg))/n_avg
temp=signal.convolve2d(s1,smooth_array,mode='same',boundary='wrap')
s1[:,:]=temp[:,:]
s1 = np.average(s1,axis=0)
plt.figure(figsize=(10,7.0))
plt.subplot(222)
temp=signal.convolve2d(e1,smoothing,mode='same',boundary='wrap')
osh5vis.osplot(np.average(e1,axis=0))
plt.ylim(-0.02,0.02)
# plt.subplot(222)
# osh5vis.osplot(e2,cmap='seismic',vmin=-0.02,vmax=0.02)
# plt.subplot(223)
# osh5vis.osplot(s1,cmap='PuBu',vmin=0,vmax=0.000025)
plt.subplot(221)
p1x1_e = numpy.abs(p1x1_e)
data_max= numpy.amax(p1x1_e)
p1x1_e=p1x1_e/data_max
osh5vis.oscontourf(p1x1_e,levels=[10**-5,3.0*10**-3,5*10**-3,1*10**-2,10**-1,3*10**-1,5*10**1],norm=LogNorm(),cmap='terrain',vmin=1e-3,vmax=100)
osh5vis.oscontour(p1x1_e,levels=[10**-5,3.0*10**-3,5*10**-3,1*10**-2,10**-1,3*10**-1,5*10**1],norm=LogNorm(),colors='black',linestyles='dashed',vmin=1e-5,vmax=500,colorbar=False)
plt.subplot(223)
# osh5vis.osplot(np.log(np.abs(p1p2_e)+1e-5),cmap='hsv')
p1p2_e = numpy.abs(p1p2_e)
data_max= numpy.amax(p1p2_e)
p1p2_e=p1p2_e/data_max
osh5vis.oscontourf(p1p2_e,levels=[10**-6,3.0*10**-3,5*10**-3,1*10**-2,10**-1,3*10**-1,5*10**1],norm=LogNorm(),cmap='terrain',vmin=1e-3,vmax=100)
osh5vis.oscontour(p1p2_e,levels=[10**-6,3.0*10**-3,5*10**-3,1*10**-2,10**-1,3*10**-1,5*10**1],norm=LogNorm(),colors='black',linestyles='dashed',vmin=1e-5,vmax=500,colorbar=False)
# plt.xlim(-0.8,0.8)
plt.xlim(-0.35,0.35)
plt.subplot(224)
osh5vis.osplot(s1, title='Axial <Poynting Flux>')
plt.ylim(0,0.00009)
plt.tight_layout()
plt.show()
argc = len(sys.argv)
if (argc < 3):
print('Usage: python combine_2d.py DIRNAME OUTNAME')
sys.exit()
dirname = sys.argv[1]
outfilename = sys.argv[2]
filelist = sorted(glob.glob(dirname + '/*.h5'))
total_time = len(filelist)
my_share = total_time
i_begin = 0
i_end = total_time
h5_filename = filelist[1]
h5_data = osh5io.read_h5(h5_filename)
array_dims = h5_data.shape
nx = array_dims[0]
ny = array_dims[1]
time_step = h5_data.run_attrs['TIME'][0]
# h5_output=hdf_data()
# h5_output.shape=[total_time,ny]
print('nx=' + repr(nx))
print('time_step=' + repr(time_step))
print('total_time=' + repr(total_time))
#
xaxis = h5_data.axes[1]
taxis = osh5def.DataAxis(0,
time_step * (total_time - 1),
total_time,
attrs={
def q3d_to_3d(rundir, plasma_field, fileno, mode_max, x1_min, x1_max, nx1,
x2_min, x2_max, nx2, x3_min, x3_max, nx3):
from scipy import interpolate
dx1 = (x1_max - x1_min) / (nx1 - 1)
dx2 = (x2_max - x2_min) / (nx2 - 1)
dx3 = (x3_max - x3_min) / (nx3 - 1)
x1_axis = np.arange(x1_min, x1_max + dx1, dx1)
x2_axis = np.arange(x2_min, x2_max + dx2, dx2)
x3_axis = np.arange(x3_min, x3_max + dx3, dx3)
a = np.zeros((nx1, nx2, nx3), dtype=float)
filename_out = filename_3d(rundir, plasma_field, fileno)
x1 = osh5def.DataAxis(x1_min,
x1_max,
nx1,
attrs={
'NAME': 'x1',
'LONG_NAME': 'x_1',
'UNITS': 'c / \omega_0'
})
x2 = osh5def.DataAxis(x2_min,
x2_max,
nx2,
attrs={
'NAME': 'x2',
'LONG_NAME': 'x_2',
'UNITS': 'c / \omega_0'
})
x3 = osh5def.DataAxis(x3_min,
x3_max,
nx3,
attrs={
'NAME': 'x3',
'LONG_NAME': 'x_3',
'UNITS': 'c / \omega_0'
})
# More attributes associated with the data/simulation. Again no need to worry about the details.
data_attrs = {
'UNITS': osh5def.OSUnits('m_e c \omega_0 / e'),
'NAME': plasma_field,
'LONG_NAME': plasma_field
}
run_attrs = {
'NOTE': 'parameters about this simulation are stored here',
'TIME UNITS': '1/\omega_0',
'XMAX': np.array([1., 15.]),
'XMIN': np.array([0., 10.])
}
# Now "wrap" the numpy array into osh5def.H5Data. Note that the data and the axes are consistent and are in fortran ordering
b = osh5def.H5Data(a,
timestamp='123456',
data_attrs=data_attrs,
run_attrs=run_attrs,
axes=[x1, x2, x3])
# I am doing mode 0 outside of the loop
fname_re = filename_re(rundir, plasma_field, 0, fileno)
# DEBUG
print(fname_re)
# DEBUG
data_re = osh5io.read_h5(fname_re)
print(data_re.shape)
print(data_re.axes[1].ax.shape)
print(data_re.axes[0].ax.shape)
func_re = interpolate.interp2d(data_re.axes[1].ax,
data_re.axes[0].ax,
data_re,
kind='cubic')
for i1 in range(0, nx1):
for i2 in range(0, nx2):
for i3 in range(0, nx3):
z = x1_axis[i1]
x = x3_axis[i3]
y = x2_axis[i2]
r = np.sqrt(x * x + y * y)
# if r != 0:
# cos_th = x/r
# sin_th = y/r
# else:
# cos_th = 1
# sin_th = 0
a[i1, i2, i3] = a[i1, i2, i3] + func_re(z, r)
for i_mode in range(1, mode_max + 1):
fname_re = filename_re(rundir, plasma_field, i_mode, fileno)
fname_im = filename_im(rundir, plasma_field, i_mode, fileno)
# DEBUG
print(fname_re)
# DEBUG
if (plasma_field == 'e2' or plasma_field == 'e3'):
if (plasma_field == 'e2'):
field_comp = 'e3'
else:
field_comp = 'e2'
data_re_self = osh5io.read_h5(
filename_re(rundir, plasma_field, i_mode, fileno))
data_im_self = osh5io.read_h5(
filename_im(rundir, plasma_field, i_mode, fileno))
data_re_comp = osh5io.read_h5(
filename_re(rundir, field_comp, i_mode, fileno))
data_im_comp = osh5io.read_h5(
filename_im(rundir, field_comp, i_mode, fileno))
else:
data_re = osh5io.read_h5(
filename_re(rundir, plasma_field, i_mode, fileno))
data_im = osh5io.read_h5(
filename_im(rundir, plasma_field, i_mode, fileno))
func_re = interpolate.interp2d(data_re.axes[1].ax,
data_re.axes[0].ax,
data_re,
kind='cubic')
func_im = interpolate.interp2d(data_im.axes[1].ax,
data_im.axes[0].ax,
data_im,
kind='cubic')
for i1 in range(0, nx1):
for i2 in range(0, nx2):
for i3 in range(0, nx3):
z = x1_axis[i1]
x = x3_axis[i3]
y = x2_axis[i2]
r = np.sqrt(x * x + y * y)
if r > 0.000001:
cos_th = x / r
sin_th = y / r
else:
cos_th = 1
sin_th = 0
# start the recursion relation to evaluate cos(n*theta) and sin(n_theta)
sin_n = sin_th
cos_n = cos_th
for int_mode in range(2, i_mode + 1):
temp_s = sin_n
temp_c = cos_n
cos_n = temp_c * cos_th - temp_s * sin_th
sin_n = temp_s * cos_th + temp_c * sin_th
#
# here we perform the addition of the N-th mode
# to the data in 3D
#
a[i1, i2,
i3] = a[i1, i2, i3] + func_re(z, r) * cos_n - func_im(
z, r) * sin_n
osh5io.write_h5(b, filename=filename_out)
def something_2(rundir, file_no):
my_path = os.getcwd()
#print(my_path)
working_dir = my_path + '/' + rundir
#print(working_dir)
dir_0 = rundir + '/Vx_x/'
dir_1 = rundir + '/Ex/'
output_dir = rundir + '/movies/'
try:
os.mkdir(output_dir)
except OSError as exc:
if exc.errno != errno.EEXIST:
raise
pass
quan_0_prefix = 'vx_x_'
quan_1_prefix = 'Ex-0_'
output_prefix = 'frame_'
fig = plt.figure(figsize=(10, 8))
phase_space_filename = dir_0 + quan_0_prefix + repr(file_no).zfill(
6) + '.h5'
e1_filename = dir_1 + quan_1_prefix + repr(file_no).zfill(6) + '.h5'
output_filename = output_dir + '/' + output_prefix + repr(file_no).zfill(
6) + '.png'
phase_space_data = osh5io.read_h5(phase_space_filename)
e1_data = np.average(osh5io.read_h5(e1_filename), axis=0)
p1_x1_plot = plt.subplot(221)
osh5vis.osplot(np.log(np.abs(phase_space_data) + 1e-10),
title='Phase Space',
vmax=10,
vmin=-2,
cmap='Blues')
e1_plot = plt.subplot(222)
osh5vis.osplot(e1_data, title='Electric Field')
e1_plot.set_ylim([-0.1, 0.1])
plt.tight_layout()
fv_plot = plt.subplot(223)
# print(hdf5_data)
xmin = phase_space_data.axes[0].min
xmax = phase_space_data.axes[0].max
ymin = phase_space_data.axes[1].min
ymax = phase_space_data.axes[1].max
# dx=(xmax-xmin)/float(nx[0]-1)
# dy=(ymax-ymin)/float(nx[1]-1)
# print(dx)
# print(dy)
# xmax=xmax-dx
# ymax=ymax-dy
# xmin=xmin+10.0*dx
# ymin=ymin-10.0*dy
# print(repr(xmin)+' '+repr(xmax)+' '+repr(ymin)+' '+repr(ymax))
nx = phase_space_data.shape
xaxis = np.linspace(xmin, xmax, num=nx[0])
yaxis = np.linspace(ymin, ymax, num=nx[1])
plt.plot(xaxis, np.average(phase_space_data, axis=1))
plt.xlabel('$v/v_{th}$')
plt.ylabel('f(v) [a.u]')
fv_plot.set_ylim([0, 1500])
fv_slices = plt.subplot(224)
# print(hdf5_data)
xmin = phase_space_data.axes[0].min
xmax = phase_space_data.axes[0].max
ymin = phase_space_data.axes[1].min
ymax = phase_space_data.axes[1].max
# dx=(xmax-xmin)/float(nx[0]-1)
# dy=(ymax-ymin)/float(nx[1]-1)
# print(dx)
# print(dy)
# xmax=xmax-dx
# ymax=ymax-dy
# xmin=xmin+10.0*dx
# ymin=ymin-10.0*dy
# print(repr(xmin)+' '+repr(xmax)+' '+repr(ymin)+' '+repr(ymax))
nx = phase_space_data.shape
xaxis = np.linspace(xmin, xmax, num=nx[0])
yaxis = np.linspace(ymin, ymax, num=nx[1])
plt.plot(xaxis, np.average(phase_space_data[:, 492:532], axis=1))
plt.plot(xaxis, np.average(phase_space_data[:, 352:372], axis=1), 'r')
plt.plot(xaxis, np.average(phase_space_data[:, 652:672], axis=1), 'g')
plt.xlabel('$v/v_{th}$')
plt.ylabel('f(v) [a.u]')
fv_slices.set_ylim([0, 1500])
plt.savefig(output_filename)
def phase_space_average_new(path,prefix,fileno,interval,nfiles):
file_begin=fileno
file_end=fileno+((nfiles)*interval)
filename=path+prefix+repr(file_begin).zfill(6)+'.h5'
# print(filename)
hdf5_data=osh5io.read_h5(filename)
# print(hdf5_data)
xmin=hdf5_data.axes[0].min
xmax=hdf5_data.axes[0].max
ymin=hdf5_data.axes[1].min
ymax=hdf5_data.axes[1].max
# dx=(xmax-xmin)/float(nx[0]-1)
# dy=(ymax-ymin)/float(nx[1]-1)
# print(dx)
# print(dy)
# xmax=xmax-dx
# ymax=ymax-dy
# xmin=xmin+10.0*dx
# ymin=ymin-10.0*dy
# print(repr(xmin)+' '+repr(xmax)+' '+repr(ymin)+' '+repr(ymax))
nx=hdf5_data.shape
xaxis=numpy.linspace(xmin,xmax,num=nx[0])
yaxis=numpy.linspace(ymin,ymax,num=nx[1])
total_files=1
# print(repr(file_begin)+' '+repr(file_end)+' '+repr(nfiles))
for i_file in range(file_begin+interval,file_end,interval):
# print(repr(i_file))
filename=path+prefix+repr(i_file).zfill(6)+'.h5'
# print(filename)
try:
hdf5_data_temp=osh5io.read_h5(filename)
total_files=total_files+1
xmin_temp=hdf5_data_temp.axes[0].min
xmax_temp=hdf5_data_temp.axes[0].max
ymin_temp=hdf5_data_temp.axes[1].min
ymax_temp=hdf5_data_temp.axes[1].max
nx_temp=hdf5_data_temp.shape
if((xmin==xmin_temp) and (xmax==xmax_temp) and (ymin==ymin_temp) and (ymax==ymax_temp)):
# print('passed')
hdf5_data=numpy.abs(hdf5_data)+numpy.abs(hdf5_data_temp)
else:
# print('no pass')
xaxis_temp=numpy.linspace(xmin_temp,xmax_temp,nx_temp[0])
yaxis_temp=numpy.linspace(ymin_temp,ymax_temp,nx_temp[1])
interp_func=interpolate.interp2d(xaxis_temp,yaxis_temp,hdf5_data_temp,kind='cubic')
temp_data=numpy.zeros((nx[0],nx[1]))
for ix in range(0,nx[0]):
for iy in range(0,nx[1]):
temp_data[iy,ix]=interp_func(xaxis[ix],yaxis[iy])
hdf5_data=numpy.abs(hdf5_data)+numpy.abs(temp_data)
except:
print('error')
continue
# print(repr(total_files))
hdf5_data=hdf5_data/float(total_files)
return hdf5_data
def something_2(rundir,file_no):
v_phase = 1/.3
v_group = 3/v_phase
my_path=os.getcwd()
#print(my_path)
working_dir=my_path+'/'+rundir
#print(working_dir)
dir_0=rundir+'/Vx_x/'
dir_1=rundir+'/Ex/'
quan_0_prefix='vx_x_'
quan_1_prefix='Ex-0_'
fig = plt.figure(figsize=(10,8) )
phase_space_filename=dir_0+quan_0_prefix+repr(file_no).zfill(6)+'.h5'
e1_filename=dir_1+quan_1_prefix+repr(file_no).zfill(6)+'.h5'
phase_space_data = osh5io.read_h5(phase_space_filename)
e1_data = np.average(osh5io.read_h5(e1_filename),axis=0)
fig.suptitle('Landau Boundary Problem, time = '+repr(phase_space_data.run_attrs['TIME'][0])+' $\omega_p^{-1}$ \n \n')
p1_x1_plot = plt.subplot(221)
osh5vis.osplot(np.log(np.abs(phase_space_data)+1e-10),title='Phase Space',vmax=10,vmin=-2,cmap='Blues')
# =====================================================================
# =====================================================================
# the following lines draw vertical axis indicating the group velocity
# p1_x1_plot.axvline(x=512-v_group*phase_space_data.run_attrs['TIME'][0])
# p1_x1_plot.axvline(x=512+v_group*phase_space_data.run_attrs['TIME'][0])
# =====================================================================
# =====================================================================
e1_plot = plt.subplot(222)
osh5vis.osplot(e1_data,title='Electric Field')
# plt.tight_layout()
fig.subplots_adjust(top=0.82)
fv_plot = plt.subplot(223)
# print(hdf5_data)
xmin=phase_space_data.axes[0].min
xmax=phase_space_data.axes[0].max
ymin=phase_space_data.axes[1].min
ymax=phase_space_data.axes[1].max
# dx=(xmax-xmin)/float(nx[0]-1)
# dy=(ymax-ymin)/float(nx[1]-1)
# print(dx)
# print(dy)
# xmax=xmax-dx
# ymax=ymax-dy
# xmin=xmin+10.0*dx
# ymin=ymin-10.0*dy
# print(repr(xmin)+' '+repr(xmax)+' '+repr(ymin)+' '+repr(ymax))
nx=phase_space_data.shape
xaxis=np.linspace(xmin,xmax,num=nx[0])
yaxis=np.linspace(ymin,ymax,num=nx[1])
plt.plot(xaxis,np.average(phase_space_data,axis=1))
plt.xlabel('$v/v_{th}$')
plt.ylabel('f(v) [a.u]')
fv_plot.set_ylim([0, 1500])
fig.subplots_adjust(top=0.82)
fv_slices = plt.subplot(224)
# print(hdf5_data)
xmin=phase_space_data.axes[0].min
xmax=phase_space_data.axes[0].max
ymin=phase_space_data.axes[1].min
ymax=phase_space_data.axes[1].max
# dx=(xmax-xmin)/float(nx[0]-1)
# dy=(ymax-ymin)/float(nx[1]-1)
# print(dx)
# print(dy)
# xmax=xmax-dx
# ymax=ymax-dy
# xmin=xmin+10.0*dx
# ymin=ymin-10.0*dy
# print(repr(xmin)+' '+repr(xmax)+' '+repr(ymin)+' '+repr(ymax))
nx=phase_space_data.shape
xaxis=np.linspace(xmin,xmax,num=nx[0])
yaxis=np.linspace(ymin,ymax,num=nx[1])
plt.plot(xaxis,np.average(phase_space_data[:,492:532],axis=1))
plt.plot(xaxis,np.average(phase_space_data[:,352:372],axis=1),'r')
plt.plot(xaxis,np.average(phase_space_data[:,652:672],axis=1),'g')
plt.xlabel('$v/v_{th}$')
plt.ylabel('f(v) [a.u]')
fv_slices.set_ylim([0, 1500])
plt.tight_layout()
plt.show()
