pencil.read.pvarfile

Classes

ParticleData

ParticleData -- holds Pencil Code PVAR file data.

Functions

pvar(*args, **kwargs)

pvar(pvarfile='', datadir='data', proc=-1, ipvar=-1, quiet=True,

Module Contents

pencil.read.pvarfile.pvar(*args, **kwargs)
pvar(pvarfile=’’, datadir=’data’, proc=-1, ipvar=-1, quiet=True,

ID=False, pflist=None, sim=None, precision=’f’, dtype=np.float64)

Read PVAR files from Pencil Code. If proc < 0, then load all data and assemble, otherwise load VAR file from specified processor.

The file format written by output() (and used, e.g. in pvar.dat) consists of the followinig Fortran records: 1. [npar] 2. indices(npar) 3. pdata(npvar, npar) Here npvar denotes the number of slots, i.e. 1 for one scalar field, 3 for one vector field, 6 for pvar.dat in the case of npar particles with 3 coordinates and 3 velocity components.

Parameters:

  • pvarfile (string) – Name of the VAR file. If not specified, use var.dat (which is the latest snapshot of the fields)

  • datadir (string) – Directory where the data is stored.

  • proc (int) – Processor to be read. If -1 read all and assemble to one array.

  • ipvar (int) – Index of the VAR file, if var_file is not specified.

  • quiet (bool) – Flag for switching off output.

  • ID (bool) – Flag for including the particle IDs in the object.

  • pflist (bool) – If present list of exclusive basic pfarrays to include

  • sim (pencil code simulation object) – Contains information about the local simulation.

  • precision (string) – Float ‘f’, double ‘d’ or half ‘half’.

  • lpersist (bool) – Read the persistent variables if they exist

Returns:

Instance of the pencil.read.var.DataCube class. All of the computed fields are imported as class members.

Return type:

DataCube

Examples

Read the latest var.dat file and print the shape of the uu array: >>> pvar = pc.read.pvar() >>> print(pvar.px.shape)

Read the PVAR2 file, and include only the x coordinates and velocity e.g., for instance to reduce memory load for large arrays. >>> pvar = pc.read.pvar(pvar_file=’PVAR2’, pflist=[‘px’,’pvx’]) >>> print(pvar.pvx.shape)

class pencil.read.pvarfile.ParticleData

Bases: object

ParticleData – holds Pencil Code PVAR file data.

Fill members with default values.

keys()
read(pvarfile='', datadir='data', proc=-1, proclist=None, ipvar=-1, quiet=True, pflist=None, ID=False, sim=None, precision='f', dtype=np.float64)
pvar(pvar_file=’’, datadir=’data’, proc=-1, ipvar=-1, quiet=True,

pflist=None, sim=None, precision=’f’, dtype=np.float64)

Read PVAR files from Pencil Code. If proc < 0, then load all data and assemble, otherwise load VAR file from specified processor.

The file format written by output() (and used, e.g. in pvar.dat) consists of the followinig Fortran records: 1. [npar] 2. indices(npar) 3. pdata(npvar, npar) Here npvar denotes the number of slots, i.e. 1 for one scalar field, 3 for one vector field, 6 for pvar.dat in the case of npar particles with 3 coordinates and 3 velocity components.

Parameters:

  • pvarfile (string) – Name of the VAR file. If not specified, use var.dat (which is the latest snapshot of the fields)

  • datadir (string) – Directory where the data is stored.

  • proc (int) – Processor to be read. If -1 read all and assemble to one array.

  • ipvar (int) – Index of the VAR file, if var_file is not specified.

  • quiet (bool) – Flag for switching off output.

  • ID (bool) – Flag for including the particle IDs in the object.

  • pflist (bool) – If present list of exclusive basic pfarrays to include

  • sim (pencil code simulation object) – Contains information about the local simulation.

  • precision (string) – Float ‘f’, double ‘d’ or half ‘half’.

  • lpersist (bool) – Read the persistent variables if they exist

Returns:

Instance of the pencil.read.var.DataCube class. All of the computed fields are imported as class members.

Return type:

DataCube

Examples

Read the latest var.dat file and print the shape of the uu array: >>> pvar = pc.read.pvar() >>> print(pvar.px.shape)

Read the PVAR2 file, and include only the x coordinates and velocity e.g., for instance to reduce memory load for large arrays. >>> pvar = pc.read.pvar(pvar_file=’PVAR2’, pflist=[‘px’,’pvx’]) >>> print(pvar.pvx.shape)