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#! /usr/bin/env python
# Copyright 2017-2020 Luca Fedeli, Maxence Thevenet
#
# This file is part of WarpX.
#
# License: BSD-3-Clause-LBNL
'''
This script loops over 3D plotfiles plt*****, generates a 3D rendering
of the data with fields and particles, and saves one image per plotfile to
plt_****_img.png. It was written for a laser-wakefield acceleration
simulation, and contains a lot of custom values (for transparency,
color intensity etc.), so feel free to modify it to meet your needs.
Execute the file with
> python video_yt.py
or
> mpirun -np 4 python video_yt.py
to generate the images. It can be quite slow for even moderately large
plotfiles.
'''
# Import statements
import yt, glob
yt.enable_parallelism()
import numpy as np
field = 'Ez'
my_max = int(5.e9) # Field maximum amplitude
do_particles = True
species0 = 'beam'
species1 = 'electrons'
do_patch = False # if want to plot an MR patch
resolution = (512, 512)
camera_position = np.array([15., 20., -5.])*yt.units.micrometer
file_list = glob.glob('./diags/plotfiles/plt?????')
clight = 299792458.0 # must be the same value as in WarpX
def plot_species(species, ad, radii, transparency, abs_xmax):
# Color for each of these particles
colors_vect = [1., 1., 1., .05] # the last value is overwritten later
x = ad[species,'particle_position_x'].v
y = ad[species,'particle_position_y'].v
z = ad[species,'particle_position_z'].v
selector = np.abs(x) < abs_xmax
x = x[selector] ; y = y[selector] ; z = z[selector]
vertices = np.column_stack((x,y,z))
colors = np.tile(colors_vect,(vertices.shape[0], 1))
colors[:,3] = transparency
point = yt.visualization.volume_rendering.render_source.PointSource(vertices, colors=colors, radii=radii)
return point
# Create the 3d image for 1 timestep
# filename is the name of the folder (e.g. plt00000)
def img_onestep(filename):
# Load the data
ds = yt.load( filename )
ad = ds.all_data()
# Calculate the z position of the box.
# You can use ds.domain_right_edge[2] instead. However, if a moving window
# was used in the simulation, the rendering shows some jitter.
# This is because a cell is added in z at some iterations but not all.
# These lines calculate this jitter z_shift and remove it from the camera position and focus
iteration=int(filename[-5:])
dt = 1./clight * 1./np.sqrt((1./ad['dx'][-1]**2 + 1./ad['dy'][-1]**2 + 1./ad['dz'][-1]**2))
z_front = dt * float(iteration) * clight
z_shift = z_front-ds.domain_right_edge[2]
# Create a yt source object for the level1 patch
if do_patch:
box_patch = yt.visualization.volume_rendering.render_source.BoxSource(
left_edge=ds.index.grids[1].LeftEdge+np.array([0., 0., z_shift])*yt.units.meter,
right_edge=ds.index.grids[1].RightEdge+np.array([0., 0., z_shift])*yt.units.meter,
color=[1.,0.1,0.1,.01])
# Handle 2 populations of particles: beam and plasma electrons
if do_particles:
point0 = plot_species(species0, ad, 2, .01, 1.)
point1 = plot_species(species1, ad, 1, .002, 20.e-6)
sc = yt.create_scene(ds, field=field)
# Set camera properties
cam = sc.camera
dom_length = ds.domain_width[2].v
cam.set_width(ds.quan(dom_length, yt.units.meter))
cam.position = ds.domain_center + camera_position + np.array([0., 0., z_shift])*yt.units.meter
cam.focus = ds.domain_center + np.array([0., 0., z_shift])*yt.units.meter
cam.resolution = resolution
# Field rendering properties
source = sc[0]
source.set_field(field)
source.set_log(False)
source.use_ghost_zones = True
bounds = (-my_max, my_max)
tf = yt.ColorTransferFunction(bounds)
w = (.01*my_max)**2
# Define the transfer function for 3d rendering
# 3 isocontours for negative field values
# The sharpness of the contour is controlled by argument width
tf.add_gaussian(-.04 *my_max, width=8*w, height=[0.1, 0.1, 1.0, 0.02])
tf.add_gaussian(-.2 *my_max, width=5*w, height=[0.1, 0.1, 1.0, 0.05])
tf.add_gaussian(-.6 *my_max, width=w, height=[0.0, 0.0, 1.0, 0.3])
# 3 isocontours for positive field values
tf.add_gaussian(.04 *my_max, width=8*w, height=[1.0, 1.0, 0.2, 0.02])
tf.add_gaussian(.2 *my_max, width=5*w, height=[1.0, 1.0, 0.2, 0.05])
tf.add_gaussian(.6 *my_max, width=w, height=[1.0, 1.0, 0.0, 0.3])
source.tfh.tf = tf
source.tfh.bounds = bounds
source.tfh.set_log(False)
source.tfh.tf.grey_opacity = True
if do_particles:
sc.add_source(point0)
sc.add_source(point1)
if do_patch:
sc.add_source(box_patch)
sc.save('./img_' + filename[-8:] + '.png', sigma_clip=1.)
# Get plt folders in current folder and loop over them.
file_list.sort()
for filename in file_list[5:]:
# disabled test: do not plot image if already exists
# if os.path.isfile(filename + '.png') is False:
print(filename)
img_onestep(filename)
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