Step class¶

Metadata¶

All the major classes are children of the MetaData class that is used to set metadata to the classes attributes.

twissed.utils.metadata.MetaData.__setattr__(self, name: str, value: Type[Any | Tuple[Any, Dict]]) → None¶

Set attribute for the MetaData object

Example

a = MetaData()

a.x = 12 # x is known in the database
a.y = 12 # y is known in the database
a.tmp = 12 # tmp is not known in the database
a.pos = (
        14,
        {
        'name_latex': '$x$',
        'units': 'm',
        'info': 'Positions x of the macro-particle of the beam.',
        'type': 'np.ndarray'
        }
        ) # Create an attribute pos = 14, with metadata defined by the dictionnary.

a.x = (13, {'units': 'mm', 'new': 'temporary'}) # Update the metadata of x

print(a._data) # print metadata

Parameters:

name (str) – Name of the attribute
value (Type[Any | Tuple[Any | Dict]]) – The value of the attribute. This argument can be a tuple with the wanted value and metadata for the attribute

Raises:

KeyError – Some attributes are reserved.

Introduction ot Step¶

The main class is the skypiea.Step class.

twissed.Step(*args, **kwargs)[source]¶

Main Class for simulation parameters. Include beam, laser and plasma parameters at a given timestep.

Examples

#Creation of the step class
step = twissed.Step()

# Read data
step = steps.read_beam(step,timestep,species='electrons',g=[10.,None])

# Examples
print(f"N particle: {step.N}")
print(f"Positions {step.x} [m]")
step.print('emit_norm_rms_y')
step.print('charge')
step.print('dt')
print(f"Convert dt: {step.convert('dt','ps')} [ps]")

step = twissed.read_dst("treacewin.dst")

Main keys¶

x (float) - Array of position in x, in m

y (float) - Array of position in y, in m

z (float) - Array of position in z, in m

ux (float) - Normalised momenta x \(u_x = \gamma v_x /c = \gamma beta_x\) of the macro-particle of the beam

uy (float) - Normalised momenta y \(u_y = \gamma v_y /c = \gamma beta_y\) of the macro-particle of the beam

uy (float) - Normalised momenta z \(u_z = \gamma v_z /c = \gamma beta_z\) of the macro-particle of the beam

w (float) - Weighs of the macro-particles in term of particles, in number of particles per macro-particles’

g (float) - Lorentz factor of every single macro-particles

Ek (float) - Relativistic kinetic energy of macro-particles

Note

Keys are only available if defined from read or set functions.

Functions¶

twissed.Step.copy(self) → Step¶

Create copy of Step class

Returns:: copy of Step class
Return type:: Step

Beam functions¶

twissed.Step.set_new_6D_beam(self, x: ndarray, y: ndarray, z: ndarray, ux: ndarray, uy: ndarray, uz: ndarray, w: ndarray) → None¶

Set position and momenta of the beam

Parameters:

x (np.ndarray) – Positions x of the macro-particle of the beam in m
y (np.ndarray) – Positions y of the macro-particle of the beam in m
z (np.ndarray) – Positions z of the macro-particle of the beam in m
ux (np.ndarray) – Normalised momenta x \(u_x = \gamma v_x /c = \gamma beta_x\) of the macro-particle of the beam
uy (np.ndarray) – Normalised momenta y \(u_y = \gamma v_y /c = \gamma beta_y\) of the macro-particle of the beam
uz (np.ndarray) – Normalised momenta z \(u_z = \gamma v_z /c = \gamma beta_z\) of the macro-particle of the beam
w (np.ndarray) – Weighs of the macro-particles in term of number of particles

twissed.Step.get_beam(self, **kwargs) → None¶

Generate all the beam data.

step.get_beam(x=[-12*1e-6,12*1e-6], g=[200,None],Ek_avg=[-50,50])

Range arguments accepted for selection¶

x (float) - Array of position in x, in m

y (float) - Array of position in y, in m

z (float) - Array of position in z, in m

ux (float) - Normalised momenta x \(u_x = \gamma v_x /c = \gamma beta_x\) of the macro-particle of the beam

uy (float) - Normalised momenta y \(u_y = \gamma v_y /c = \gamma beta_y\) of the macro-particle of the beam

uy (float) - Normalised momenta z \(u_z = \gamma v_z /c = \gamma beta_z\) of the macro-particle of the beam

w (float) - Weighs of the macro-particles in term of particles, in number of particles per macro-particles

g (float) - Lorentz factor of every single macro-particles

Ek (float) - Relativistic kinetic energy of macro-particles

Note

All the above arguments can be added with the ‘_avg’ suffix to force the selection to be performed around the mean value.
Variables self.w, self.ux, self.uy, self.uz, self.x, self.y and self.z must have be defined.

twissed.Step.rotationXY(self, angle: float) → Step¶

Counterclockwise rotate the x-y plan to a given angle

Example

# 90 degree rotation of the beam
step_new = step.rotationXY(90*np.pi/180)

Parameters:: angle (float) – Angle of the counterclockwise rotation, in rad
Returns:: New step class
Return type:: step