Write examples¶

In [1]:

# Useful for debugging
%load_ext autoreload
%autoreload 2

# Useful for debugging %load_ext autoreload %autoreload 2

In [2]:

from beamphysics import ParticleGroup, pmd_init
from h5py import File
import os
import tempfile
import numpy as np
import matplotlib.pyplot as plt

from beamphysics import ParticleGroup, pmd_init from h5py import File import os import tempfile import numpy as np import matplotlib.pyplot as plt

In [3]:

# Pick one:

# H5File = 'data/bmad_particles2.h5'
H5FILE = "data/distgen_particles.h5"
# H5FILE = 'data/astra_particles.h5'

P = ParticleGroup(H5FILE)

# Pick one: # H5File = 'data/bmad_particles2.h5' H5FILE = "data/distgen_particles.h5" # H5FILE = 'data/astra_particles.h5' P = ParticleGroup(H5FILE)

openPMD¶

The regular write routine writes in a proper openPMD format

In [4]:

P.write("openpmd_particles.h5")

P.write("openpmd_particles.h5")

An open h5 hande can also be used, but it needs to be properly initialized

In [5]:

with File("openpmd_particles.h5", "w") as h5:
    pmd_init(h5, basePath="/", particlesPath="/")
    P.write(h5)

with File("openpmd_particles.h5", "w") as h5: pmd_init(h5, basePath="/", particlesPath="/") P.write(h5)

This can be read in by another ParticleGroup

In [6]:

P2 = ParticleGroup("openpmd_particles.h5")

P2 = ParticleGroup("openpmd_particles.h5")

Check that they are the same:

In [7]:

P2 == P

P2 == P

Out[7]:

True

Some codes read in the particle's absolute time from the particle group. This can cause numerical issues when the time offset is much larger than the relative offset of each particle in the bunch. OpenPMD-beamphysics allows writing the additional attribute timeOffset to the HDF5 file to avoid this. We demonstrate its use with the (extreme) example of a femtosecond long beam offset by one second in a machine, showing the difference between adding the time offset to the ParticleGroup attribute versus writing in the file.

In [8]:

# Control the reference time
ref_time = 1
bunch_len = 1e-15

# Control the reference time ref_time = 1 bunch_len = 1e-15

In [9]:

# Generate a short bunch to demonstrate writing
P_short = P.copy()
P_short.t = np.random.normal(scale=bunch_len, size=len(P))

# Create a beam with naive offset
P_offset = P_short.copy()
P_offset.t = P_offset.t + ref_time


def write_read(pg, t_offset=0):
    with tempfile.NamedTemporaryFile() as f:
        pg.write(f.name, t_offset=t_offset)
        return ParticleGroup.from_hdf5(f.name, include_time_offset=False)


# Write the beams, read back without offsets (ie what a simulation code separating timeOffset will see)
P_offset_loaded = write_read(P_offset)
P_short_loaded = write_read(P_short, t_offset=ref_time)

# Generate a short bunch to demonstrate writing P_short = P.copy() P_short.t = np.random.normal(scale=bunch_len, size=len(P)) # Create a beam with naive offset P_offset = P_short.copy() P_offset.t = P_offset.t + ref_time def write_read(pg, t_offset=0): with tempfile.NamedTemporaryFile() as f: pg.write(f.name, t_offset=t_offset) return ParticleGroup.from_hdf5(f.name, include_time_offset=False) # Write the beams, read back without offsets (ie what a simulation code separating timeOffset will see) P_offset_loaded = write_read(P_offset) P_short_loaded = write_read(P_short, t_offset=ref_time)

In [10]:

# Plot the longitudinal phase spaces against each other
# Note the numerical roundoff error in the t coordinate
plt.scatter(1e15 * P_short_loaded["delta_t"], P_short["pz"], s=1, label="With t_offset")
plt.scatter(
    1e15 * P_offset_loaded["delta_t"], P_offset_loaded["pz"], s=1, label="Naive Write"
)
plt.xlabel(r"$\Delta t$ (fs)")
plt.ylabel(r"$p_z$ (eV/c)")
plt.legend()

# Plot the longitudinal phase spaces against each other # Note the numerical roundoff error in the t coordinate plt.scatter(1e15 * P_short_loaded["delta_t"], P_short["pz"], s=1, label="With t_offset") plt.scatter( 1e15 * P_offset_loaded["delta_t"], P_offset_loaded["pz"], s=1, label="Naive Write" ) plt.xlabel(r"$\Delta t$ (fs)") plt.ylabel(r"$p_z$ (eV/c)") plt.legend()

Out[10]:

<matplotlib.legend.Legend at 0x34ef9098710>

Astra¶

In [11]:

P.write_astra("astra_particles.txt")

P.write_astra("astra_particles.txt")

In [12]:

!head astra_particles.txt

!head astra_particles.txt

 -1.289814080985e-05   1.712192978919e-05   0.000000000000e+00  -9.245284702413e-01  -3.316650265292e+00   2.210558337183e+02   1.819664001274e-05   0.000000000000e+00    1    5
 -1.184861337727e-03  -2.101371437059e-03   0.000000000000e+00  -3.047044656318e+02  -3.039342419008e+02  -1.005645891013e+02  -9.745607002167e-04   1.000000000000e-06    1    5
 -5.181307340245e-04  -2.178353405029e-03   0.000000000000e+00   5.525456229648e+02   2.416723877028e+02  -6.554342847563e+01   1.280843753434e-03   1.000000000000e-06    1    5
 -1.773501610902e-03   2.864979597813e-03   0.000000000000e+00  -2.226004747820e+02   9.450238076106e+00  -1.055085411491e+02   3.835366744569e-04   1.000000000000e-06    1    5
  1.686555815999e-03  -2.401048305081e-04   0.000000000000e+00  -1.891692499417e+02   4.859547751754e+01   3.339263495319e+02   1.902998338336e-03   1.000000000000e-06    1    5
 -7.779454935491e-04  -6.800063114796e-04   0.000000000000e+00   6.716138938638e+01  -2.064173000222e+02  -1.405963302134e+02   1.779005092730e-04   1.000000000000e-06    1    5
 -2.593702199590e-03  -2.301030494125e-03   0.000000000000e+00  -1.455653402031e+01   2.074634953296e+02  -1.397453142110e+02   1.368567098305e-03   1.000000000000e-06    1    5
  1.997801509161e-03   2.648416193086e-03   0.000000000000e+00  -2.124047726665e+00  -6.792723569247e+01   6.931081537770e+01   2.616497721112e-04   1.000000000000e-06    1    5
  1.999741847023e-03  -6.945690451493e-04   0.000000000000e+00  -9.991142908925e+01  -9.189412445573e+01   2.259539675809e+02  -8.681109991004e-04   1.000000000000e-06    1    5
 -7.033822974359e-04  -5.677746866954e-04   0.000000000000e+00   7.520962264129e+02   3.125940718167e+02  -1.451032665210e+02   4.315191990002e-04   1.000000000000e-06    1    5

Check the readback:

In [13]:

from beamphysics.interfaces.astra import parse_astra_phase_file
import numpy as np

P1 = ParticleGroup(data=parse_astra_phase_file("astra_particles.txt"))
for k in ["x", "px", "y", "py", "z", "pz"]:
    assert np.allclose(P[k], P1[k])

from beamphysics.interfaces.astra import parse_astra_phase_file import numpy as np P1 = ParticleGroup(data=parse_astra_phase_file("astra_particles.txt")) for k in ["x", "px", "y", "py", "z", "pz"]: assert np.allclose(P[k], P1[k])

Bmad ASCII¶

In [14]:

P.write_bmad("bmad_particles.txt")

P.write_bmad("bmad_particles.txt")

In [15]:

!head bmad_particles.txt

!head bmad_particles.txt

!ASCII::3
0 ! ix_ele, not used
1 ! n_bunch
10000 ! n_particle
BEGIN_BUNCH
electron
1.0000000000000003e-11  ! bunch_charge
0 ! z_center
0 ! t_center
 -1.184861337727e-03  -3.047044656318e+02  -2.101371437059e-03  -3.039342419008e+02  -9.563640602039e-13   1.204912446170e+02   1.000000000000e-15  1

Bmad dict¶

In [16]:

P.to_bmad()

P.to_bmad()

Out[16]:

{'x': array([-0.00118486, -0.00051813, -0.0017735 , ..., -0.00052658,
         0.00252813,  0.00113815], shape=(10000,)),
 'y': array([-0.00210137, -0.00217835,  0.00286498, ..., -0.00161154,
         0.00160049, -0.0010351 ], shape=(10000,)),
 'px': array([-0.69011879,  1.25144906, -0.50416317, ...,  0.60249121,
         0.505233  ,  0.74928061], shape=(10000,)),
 'py': array([-0.68837433,  0.54735875,  0.02140365, ..., -0.07882388,
         0.29433475, -0.25918357], shape=(10000,)),
 'z': array([ 2.55529374e-07, -4.68009161e-07, -5.64739755e-08, ...,
        -9.69805225e-09,  4.20165276e-07,  2.70278112e-07], shape=(10000,)),
 'pz': array([ 0.01222356,  0.41059669, -0.4315584 , ..., -0.3093279 ,
         0.02463904,  0.08781142], shape=(10000,)),
 'charge': array([1.e-15, 1.e-15, 1.e-15, ..., 1.e-15, 1.e-15, 1.e-15],
       shape=(10000,)),
 'species': 'electron',
 'p0c': np.float64(441.5246616725094),
 'tref': np.float64(1.8196640012738958e-14),
 'state': array([1, 1, 1, ..., 1, 1, 1], shape=(10000,))}

Check that the conversion preserves information. Note that == uses np.allclose, because there is roundoff error in the conversion.

In [17]:

assert P == P.from_bmad(P.to_bmad())

assert P == P.from_bmad(P.to_bmad())

elegant¶

In [18]:

P.write_elegant("elegant_particles.txt", verbose=True)

P.write_elegant("elegant_particles.txt", verbose=True)

writing 10000 particles to elegant_particles.txt

In [19]:

!head -n 20 elegant_particles.txt

!head -n 20 elegant_particles.txt

SDDS1
!
! Created using the openPMD-beamphysics Python package
! https://github.com/ChristopherMayes/openPMD-beamphysics
! species: electron
!
&parameter name=Charge, type=double, units=C, description="total charge in Coulombs" &end
&column name=t,  type=double, units=s, description="time in seconds" &end
&column name=x,  type=double, units=m, description="x in meters" &end
&column name=xp, type=double, description="px/pz" &end
&column name=y,  type=double, units=m, description="y in meters" &end
&column name=yp, type=double, description="py/pz" &end
&column name=p,  type=double, units="m$be$nc", description="relativistic gamma*beta" &end
&data mode=ascii &end
1.0000000000000003e-11
10000
 -9.563640602039e-13  -1.184861337727e-03  -2.528851507845e+00  -2.101371437059e-03  -2.522459145201e+00   8.746038804465e-04
  1.299040393447e-12  -5.181307340245e-04   3.553064606663e+00  -2.178353405029e-03   1.554039289185e+00   1.218815081472e-03
  4.017333144697e-13  -1.773501610902e-03  -1.926488019169e+00   2.864979597813e-03   8.178675472159e-02   4.911575363923e-04
  1.921194978349e-12   1.686555815999e-03  -3.408564376497e-01  -2.401048305081e-04   8.756222989528e-02   1.151365619480e-03

Genesis 1.3 v2¶

In [20]:

P.write_genesis2_beam_file("genesis2.beam", n_slice=50, verbose=True)

P.write_genesis2_beam_file("genesis2.beam", n_slice=50, verbose=True)

Beam written: genesis2.beam

In [21]:

!head genesis2.beam

!head genesis2.beam

? VERSION=1.0
? SIZE=50
? COLUMNS TPOS CURPEAK GAMMA0 DELGAM EMITX EMITY RXBEAM RYBEAM XBEAM YBEAM PXBEAM PYBEAM ALPHAX ALPHAY
-1.96236040e-12 2.75359318e+00 1.00000042e+00 3.87022120e-07 1.19639887e-06 9.26536585e-07 2.04948080e-03 1.83621527e-03 -2.06231144e-04 5.85738124e-05 1.38209180e-05 4.17553933e-05 -1.01973407e-02 7.54079832e-04
-1.88646733e-12 2.46723994e+00 1.00000043e+00 3.39783123e-07 1.04698472e-06 1.03470799e-06 2.05064183e-03 1.92139881e-03 -2.53107201e-05 -1.13678787e-04 -2.85190907e-05 -2.90105674e-05 -2.32400675e-02 -2.55583997e-03
-1.80734757e-12 2.61898031e+00 1.00000043e+00 3.65257966e-07 9.78086021e-07 1.03038032e-06 1.97065976e-03 1.88550433e-03 -7.56576638e-05 1.77044304e-04 -4.48907172e-05 6.98821768e-05 5.38708456e-03 4.70844009e-03
-1.72583745e-12 2.30361285e+00 1.00000043e+00 3.43343192e-07 9.42099456e-07 1.07137205e-06 1.90156644e-03 1.92054974e-03 4.82559113e-05 -6.43105052e-05 1.66595205e-05 1.33986604e-05 9.16890850e-02 8.20635086e-03
-1.64047654e-12 2.48779835e+00 1.00000043e+00 3.76740496e-07 1.12901501e-06 1.01496463e-06 2.07085748e-03 1.84284581e-03 -2.63780641e-04 2.16425678e-05 9.07228823e-06 -2.65046022e-05 1.91567484e-03 3.63234933e-03
-1.55820367e-12 2.33273410e+00 1.00000041e+00 3.38657590e-07 9.79796546e-07 1.04648254e-06 1.84685458e-03 1.99189484e-03 3.36520774e-05 1.02123362e-04 3.01402301e-06 6.13937003e-05 -7.84493116e-02 2.84788841e-02
-1.47800120e-12 2.62363489e+00 1.00000044e+00 3.34570581e-07 1.12580877e-06 1.08628803e-06 1.97095399e-03 2.02149469e-03 -1.94415715e-04 -1.05666747e-04 -1.70675102e-05 -5.61809635e-06 -1.81522208e-01 -5.08353286e-03

Genesis 1.3 v4¶

beam file (slice statistics)¶

In [22]:

input_str = P.write_genesis4_beam(
    "genesis4_beam.h5", n_slice=123, verbose=True, return_input_str=True
)

input_str = P.write_genesis4_beam( "genesis4_beam.h5", n_slice=123, verbose=True, return_input_str=True )

Genesis4 beam file written: genesis4_beam.h5

This string is optionally returned for use in the main Genesis4 input file:

In [23]:

print(input_str)

print(input_str)

&profile_file
  label = current
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/current
  isTime = T
  reverse = T
&end
&profile_file
  label = gamma
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/gamma
  isTime = T
  reverse = T
&end
&profile_file
  label = delgam
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/delgam
  isTime = T
  reverse = T
&end
&profile_file
  label = ex
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/ex
  isTime = T
  reverse = T
&end
&profile_file
  label = ey
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/ey
  isTime = T
  reverse = T
&end
&profile_file
  label = xcenter
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/xcenter
  isTime = T
  reverse = T
&end
&profile_file
  label = ycenter
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/ycenter
  isTime = T
  reverse = T
&end
&profile_file
  label = pxcenter
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/pxcenter
  isTime = T
  reverse = T
&end
&profile_file
  label = pycenter
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/pycenter
  isTime = T
  reverse = T
&end
&profile_file
  label = alphax
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/alphax
  isTime = T
  reverse = T
&end
&profile_file
  label = alphay
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/alphay
  isTime = T
  reverse = T
&end
&profile_file
  label = betax
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/betax
  isTime = T
  reverse = T
&end
&profile_file
  label = betay
  xdata = genesis4_beam.h5/t
  ydata = genesis4_beam.h5/betay
  isTime = T
  reverse = T
&end
&beam
  current = @current
  gamma = @gamma
  delgam = @delgam
  ex = @ex
  ey = @ey
  xcenter = @xcenter
  ycenter = @ycenter
  pxcenter = @pxcenter
  pycenter = @pycenter
  alphax = @alphax
  alphay = @alphay
  betax = @betax
  betay = @betay
&end

These are the datasets written:

In [24]:

with File("genesis4_beam.h5", "r") as h5:
    for g in h5:
        print(g, len(h5[g]), h5[g].attrs["unitSymbol"])

with File("genesis4_beam.h5", "r") as h5: for g in h5: print(g, len(h5[g]), h5[g].attrs["unitSymbol"])

alphax 123 1
alphay 123 1
betax 123 m
betay 123 m
current 123 A
delgam 123 1
ex 123 m
ey 123 m
gamma 123 1
pxcenter 123 1
pycenter 123 1
t 123 s
xcenter 123 m
ycenter 123 m

Distribution file (particles)¶

In [25]:

P.write_genesis4_distribution("genesis4_distribution.h5", verbose=True)

P.write_genesis4_distribution("genesis4_distribution.h5", verbose=True)

Datasets x, xp, y, yp, t, p written to: genesis4_distribution.h5

This is what is written:

In [26]:

with File("genesis4_distribution.h5", "r") as h5:
    for g in h5:
        print(g, len(h5[g]))

with File("genesis4_distribution.h5", "r") as h5: for g in h5: print(g, len(h5[g]))

p 10000
t 10000
x 10000
xp 10000
y 10000
yp 10000

GPT ASCII¶

In [27]:

P.write_gpt("gpt_particles.txt", verbose=True)

P.write_gpt("gpt_particles.txt", verbose=True)

writing 10000 particles to gpt_particles.txt
ASCII particles written. Convert to GDF using: asci2gdf -o particles.gdf gpt_particles.txt

In [28]:

if os.path.exists(os.path.expandvars("$ASCI2GDF_BIN")):
    P.write_gpt("gpt_particles.gdf", verbose=True, asci2gdf_bin="$ASCI2GDF_BIN")

if os.path.exists(os.path.expandvars("$ASCI2GDF_BIN")): P.write_gpt("gpt_particles.gdf", verbose=True, asci2gdf_bin="$ASCI2GDF_BIN")

In [29]:

#!head gpt_particles.txt

#!head gpt_particles.txt

Impact-T¶

Impact-T particles must all be a the same time:

In [30]:

P.drift_to_t(P["mean_t"])

P.drift_to_t(P["mean_t"])

This will return settings for Impact-T to use:

In [31]:

P.write_impact("impact_particles.txt")

P.write_impact("impact_particles.txt")

Out[31]:

{'input_particle_file': 'impact_particles.txt',
 'Np': 10000,
 'Tini': np.float64(1.8196640012738958e-14),
 'Flagimg': 0}

In [32]:

!head impact_particles.txt

!head impact_particles.txt

10000
-1.185035553808536871e-03 -5.962917638487320827e-04 -2.101545212762017441e-03 -5.947844736087322046e-04 6.889138455579563163e-08 2.357954834433780911e-04
-5.185459410272206951e-04 1.081304809371362412e-03 -2.178535008255477572e-03 4.729410645099751584e-04 -1.168588384170137180e-07 3.043301850869014344e-04
-1.773451522909380617e-03 -4.356182619973316826e-04 2.864977471386672206e-03 1.849365456297997709e-05 -2.599963878411861387e-08 2.261204106451414635e-04
1.686767013783681485e-03 -3.701949870666343878e-04 -2.401590848711824449e-04 9.509897711516471621e-05 -6.196091990039513892e-07 1.086073038899323766e-03
-7.779525032181033037e-04 1.314315602716767861e-04 -6.799847675989087112e-04 -4.039485790400071342e-04 -8.397600106119063685e-09 1.574553203998415077e-04
-2.593690512006365748e-03 -2.848642644110359828e-05 -2.301197068593970833e-03 4.059959321822741662e-04 -6.528501134283619379e-08 1.591207171707416379e-04
1.997801835211931304e-03 -4.156657707019708285e-06 2.648426620219629726e-03 -1.329302841047836064e-04 -4.457257395121590637e-08 5.682333568473067146e-04
1.999690961886658146e-03 -1.955217891432792742e-04 -6.946158470527301386e-04 -1.798323153729413260e-04 2.276631904252130206e-07 8.747763585337833521e-04
-7.035727003849858666e-04 1.471815598441655838e-03 -5.678538239534577621e-04 6.117313379892479327e-04 -1.922838099347932618e-08 1.486354660704120706e-04

LiTrack¶

LiTrack particles must be at the same z:

In [33]:

P.drift_to_z()

P.drift_to_z()

In [34]:

P.write_litrack("litrack.zd", verbose=True)

P.write_litrack("litrack.zd", verbose=True)

Using mean_p as the reference momentum: 441.5246616725094 eV/c
writing 10000 LiTrack particles to litrack.zd

Out[34]:

'litrack.zd'

In [35]:

!head -n 20 litrack.zd

!head -n 20 litrack.zd

% LiTrack particles
%
% Created using the openPMD-beamphysics Python package
% https://github.com/ChristopherMayes/openPMD-beamphysics
%
% species: electron
% n_particle: 10000
% total charge: 1.0000000000000003e-11 (C)
% reference momentum p0: 441.5246616725094 (eV/c)
%
% Columns: ct, delta = p/p0 -1
% Units: mm, percent
 -2.910140500388e-01   1.222356070583e+00
  3.861082943987e-01   4.105966931910e+01
  1.159491741202e-01  -4.315583986424e+01
  5.750254785583e-01   3.325339997689e+01
  5.234406211768e-02  -4.756793241308e+01
  4.093643740668e-01  -4.942448528425e+01
  8.211012905157e-02  -3.245820052454e+01
 -2.559578717432e-01   5.807578013130e+00

Lucretia¶

In [36]:

P.write_lucretia(
    "lucretia.mat", ele_name="BEGINNING", t_ref=0, stop_ix=None, verbose=True
)

P.write_lucretia( "lucretia.mat", ele_name="BEGINNING", t_ref=0, stop_ix=None, verbose=True )

writing 10000 particles in the Lucretia format to lucretia.mat

Read back:

In [37]:

from beamphysics.interfaces.lucretia import lucretia_to_data, list_element_names

ParticleGroup(data=lucretia_to_data("lucretia.mat", verbose=True))

from beamphysics.interfaces.lucretia import lucretia_to_data, list_element_names ParticleGroup(data=lucretia_to_data("lucretia.mat", verbose=True))

1 elements found in the file!
10000 particles detected, 0 found dead!

Out[37]:

<ParticleGroup with 10000 particles at 0x34ef97827d0>

Helper function to list the available elements:

In [38]:

list_element_names("lucretia.mat")

list_element_names("lucretia.mat")

Out[38]:

['BEGINNING']

OPAL¶

Injected particled must be at the same time:

In [39]:

P.drift_to_t()

P.write_opal("opal_injected.txt", dist_type="injected")

P.drift_to_t() P.write_opal("opal_injected.txt", dist_type="injected")

In [40]:

!head opal_injected.txt

!head opal_injected.txt

10000
 -1.185024568260e-03  -5.962917638487e-04  -2.101534254983e-03  -5.947844736087e-04   6.454729855195e-08   2.357954834434e-04
 -5.185658620169e-04   1.081304809371e-03  -2.178543721297e-03   4.729410645100e-04  -1.224655447117e-07   3.043301850869e-04
 -1.773443497464e-03  -4.356182619973e-04   2.864977130676e-03   1.849365456298e-05  -3.016548095350e-08   2.261204106451e-04
  1.686773833925e-03  -3.701949870666e-04  -2.401608368896e-04   9.509897711516e-05  -6.396180358817e-07   1.086073038899e-03
 -7.779549245968e-04   1.314315602717e-04  -6.799773256079e-04  -4.039485790400e-04  -1.129841752215e-08   1.574553203998e-04
 -2.593689987198e-03  -2.848642644110e-05  -2.301204548304e-03   4.059959321823e-04  -6.821651057540e-08   1.591207171707e-04
  1.997801911791e-03  -4.156657707020e-06   2.648429069209e-03  -1.329302841048e-04  -5.504120150974e-08   5.682333568473e-04
  1.999694564006e-03  -1.955217891433e-04  -6.946125339824e-04  -1.798323153729e-04   2.115470903819e-07   8.747763585338e-04
 -7.035998157805e-04   1.471815598442e-03  -5.678650939367e-04   6.117313379892e-04  -2.196670599469e-08   1.486354660704e-04

Emitted particles must be at the same z:

In [41]:

P.drift_to_z(P["mean_z"])
P.write_opal("opal_emitted.txt", dist_type="emitted")

P.drift_to_z(P["mean_z"]) P.write_opal("opal_emitted.txt", dist_type="emitted")

In [42]:

!head opal_emitted.txt

!head opal_emitted.txt

10000
 -1.184838617375e-03  -5.962917638487e-04  -2.101348774139e-03  -5.947844736087e-04  -1.083461177889e-12   2.357954834434e-04
 -5.181626563723e-04   1.081304809371e-03  -2.178367367225e-03   4.729410645100e-04   1.200565320731e-12   3.043301850869e-04
 -1.773484302458e-03  -4.356182619973e-04   2.864978863003e-03   1.849365456298e-05   2.691980940714e-13   2.261204106451e-04
  1.686558878409e-03  -3.701949870666e-04  -2.401056172069e-04   9.509897711516e-05   1.893601130019e-12   1.086073038899e-03
 -7.779529930790e-04   1.314315602717e-04  -6.799832620349e-04  -4.039485790400e-04   5.764311716726e-15   1.574553203998e-04
 -2.593700591157e-03  -2.848642644110e-05  -2.301053417928e-03   4.059959321823e-04   1.198422972634e-12   1.591207171707e-04
  1.997801574883e-03  -4.156657707020e-06   2.648418294874e-03  -1.329302841048e-04   2.271058970013e-13   5.682333568473e-04
  1.999743855144e-03  -1.955217891433e-04  -6.945671981683e-04  -1.798323153729e-04  -8.841733180528e-13   8.747763585338e-04
 -7.034712631507e-04   1.471815598442e-03  -5.678116635530e-04   6.117313379892e-04   2.480886363183e-13   1.486354660704e-04

SIMION¶

Write SIMION input files (*.ion)

In [43]:

P.write_simion("simion_particles.ion")

P.write_simion("simion_particles.ion")

Cleanup¶

In [44]:

for file in [
    "astra_particles.txt",
    "bmad_particles.txt",
    "elegant_particles.txt",
    "gpt_particles.txt",
    "impact_particles.txt",
    "opal_injected.txt",
    "opal_emitted.txt",
    "openpmd_particles.h5",
    "genesis4_beam.h5",
    "genesis4_distribution.h5",
    "genesis2.beam",
    "litrack.zd",
    "gpt_particles.gdf",
    "lucretia.mat",
    "simion_particles.ion",
]:
    if os.path.exists(file):
        os.remove(file)

for file in [ "astra_particles.txt", "bmad_particles.txt", "elegant_particles.txt", "gpt_particles.txt", "impact_particles.txt", "opal_injected.txt", "opal_emitted.txt", "openpmd_particles.h5", "genesis4_beam.h5", "genesis4_distribution.h5", "genesis2.beam", "litrack.zd", "gpt_particles.gdf", "lucretia.mat", "simion_particles.ion", ]: if os.path.exists(file): os.remove(file)