OnTheFly

class pyR2D2.OnTheFly(data)

Bases: _BaseReader

Class for on-the-fly analysis data Mean, RMS, and correlation are done in longitudinal or z directions.

pyR2D2.Data class can access this class as pyR2D2.Data.vc

Variables:

• data (numpy.ndarray, float) – pyR2D2.Data instance

• su (numpy.ndarray, float) – number of grid points of upflows

• sd (numpy.ndarray, float) – number of grid points of downflows

• rom (numpy.ndarray, float) – mean density

• vxm (numpy.ndarray, float) – mean vx

• vym (numpy.ndarray, float) – mean vy

• vzm (numpy.ndarray, float) – mean vz

• rxm (numpy.ndarray, float) – mean ro*vx

• rym (numpy.ndarray, float) – mean ro*vy

• rzm (numpy.ndarray, float) – mean ro*vz

• bxm (numpy.ndarray, float) – mean bx

• bym (numpy.ndarray, float) – mean by

• bzm (numpy.ndarray, float) – mean bz

• sem (numpy.ndarray, float) – mean entropy / unit mass

• tem (numpy.ndarray, float) – mean temperature

• prm (numpy.ndarray, float) – mean pressure

• enm (numpy.ndarray, float) – mean internal energy / unit mass

• opm (numpy.ndarray, float) – mean opacity

• tum (numpy.ndarray, float) – mean optical depth

• wxm (numpy.ndarray, float) – mean x vorticity

• wym (numpy.ndarray, float) – mean y vorticity

• wzm (numpy.ndarray, float) – mean z vorticity

• cxm (numpy.ndarray, float) – mean x current

• cym (numpy.ndarray, float) – mean y current

• czm (numpy.ndarray, float) – mean z current

• hkm (numpy.ndarray, float) – mean kinetic helicity

• hcm (numpy.ndarray, float) – mean current helicity

• wdm (numpy.ndarray, float) – mean work done by magnetic pressure

• wcm (numpy.ndarray, float) – mean work done by compression

• ekm (numpy.ndarray, float) – mean kinetic energy

• emm (numpy.ndarray, float) – mean magnetic energy

• rorms (numpy.ndarray, float) – rms density

• vxrms (numpy.ndarray, float) – rms vx

• vyrms (numpy.ndarray, float) – rms vy

• vzrms (numpy.ndarray, float) – rms vz

• bxrms (numpy.ndarray, float) – rms bx

• byrms (numpy.ndarray, float) – rms by

• bzrms (numpy.ndarray, float) – rms bz

• serms (numpy.ndarray, float) – rms entropy / unit mass

• terms (numpy.ndarray, float) – rms temperature

• prrms (numpy.ndarray, float) – rms pressure

• enrms (numpy.ndarray, float) – rms internal energy / unit mass

• rormsu (numpy.ndarray, float) – rms density of upflows

• vxrmsu (numpy.ndarray, float) – rms vx of upflows

• vyrmsu (numpy.ndarray, float) – rms vy of upflows

• vzrmsu (numpy.ndarray, float) – rms vz of upflows

• bxrmsu (numpy.ndarray, float) – rms bx of upflows

• byrmsu (numpy.ndarray, float) – rms by of upflows

• bzrmsu (numpy.ndarray, float) – rms bz of upflows

• sermsu (numpy.ndarray, float) – rms entropy / unit mass of upflows

• termsu (numpy.ndarray, float) – rms temperature of upflows

• prrmsu (numpy.ndarray, float) – rms pressure of upflows

• enrmsu (numpy.ndarray, float) – rms internal energy / unit mass of upflows

• rormsd (numpy.ndarray, float) – rms density of downflows

• vxrmsd (numpy.ndarray, float) – rms vx of downflows

• vyrmsd (numpy.ndarray, float) – rms vy of downflows

• vzrmsd (numpy.ndarray, float) – rms vz of downflows

• bxrmsd (numpy.ndarray, float) – rms bx of downflows

• byrmsd (numpy.ndarray, float) – rms by of downflows

• bzrmsd (numpy.ndarray, float) – rms bz of downflows

• sermsd (numpy.ndarray, float) – rms entropy / unit mass of downflows

• termsd (numpy.ndarray, float) – rms temperature of downflows

• prrmsd (numpy.ndarray, float) – rms pressure of downflows

• enrmsd (numpy.ndarray, float) – rms internal energy / unit mass of downflows

• vxyco (numpy.ndarray, float) – vx*vy correlation

• vxzco (numpy.ndarray, float) – vx*vz correlation

• vyzco (numpy.ndarray, float) – vy*vz correlation

• bxyco (numpy.ndarray, float) – bx*by correlation

• bxzco (numpy.ndarray, float) – bx*bz correlation

• byzco (numpy.ndarray, float) – by*bz correlation

• vxbxco (numpy.ndarray, float) – vx*bx correlation

• vxbyco (numpy.ndarray, float) – vx*by correlation

• vxbzco (numpy.ndarray, float) – vx*bz correlation

• vybxco (numpy.ndarray, float) – vy*bx correlation

• vybyco (numpy.ndarray, float) – vy*by correlation

• vybzco (numpy.ndarray, float) – vy*bz correlation

• vzbxco (numpy.ndarray, float) – vz*bx correlation

• vzbyco (numpy.ndarray, float) – vz*by correlation

• vzbzco (numpy.ndarray, float) – vz*bz correlation

• vxwxco (numpy.ndarray, float) – vx*wx correlation (w mean vorticity)

• vxwyco (numpy.ndarray, float) – vx*wy correlation

• vxwzco (numpy.ndarray, float) – vx*wz correlation

• vywxco (numpy.ndarray, float) – vy*wx correlation

• vywyco (numpy.ndarray, float) – vy*wy correlation

• vywzco (numpy.ndarray, float) – vy*wz correlation

• vzwxco (numpy.ndarray, float) – vz*wx correlation

• vzwyco (numpy.ndarray, float) – vz*wy correlation

• vzwzco (numpy.ndarray, float) – vz*wz correlation

• ro_xy (numpy.ndarray, float) – xy slice of density at kc

• vx_xy (numpy.ndarray, float) – xy slice of vx at kc

• vy_xy (numpy.ndarray, float) – xy slice of vy at kc

• vz_xy (numpy.ndarray, float) – xy slice of vz at kc

• bx_xy (numpy.ndarray, float) – xy slice of bx at kc

• by_xy (numpy.ndarray, float) – xy slice of by at kc

• bz_xy (numpy.ndarray, float) – xy slice of bz at kc

• se_xy (numpy.ndarray, float) – xy slice of entropy at kc

• pr_xy (numpy.ndarray, float) – xy slice of pressure at kc

• te_xy (numpy.ndarray, float) – xy slice of temperature at kc

• tu_xy (numpy.ndarray, float) – xy slice of optical depth at kc

• en_xy (numpy.ndarray, float) – xy slice of internal energy at kc

• op_xy (numpy.ndarray, float) – xy slice of opacity at kc

• ro_xz (numpy.ndarray, float) – xz slice of density at jc

• vx_xz (numpy.ndarray, float) – xz slice of vx at jc

• vy_xz (numpy.ndarray, float) – xz slice of vy at jc

• vz_xz (numpy.ndarray, float) – xz slice of vz at jc

• bx_xz (numpy.ndarray, float) – xz slice of bx at jc

• by_xz (numpy.ndarray, float) – xz slice of by at jc

• bz_xz (numpy.ndarray, float) – xz slice of bz at jc

• se_xz (numpy.ndarray, float) – xz slice of entropy at jc

• pr_xz (numpy.ndarray, float) – xz slice of pressure at jc

• te_xz (numpy.ndarray, float) – xz slice of temperature at jc

• tu_xz (numpy.ndarray, float) – xz slice of optical depth at jc

• en_xz (numpy.ndarray, float) – xz slice of internal energy at jc

• op_xz (numpy.ndarray, float) – xz slice of opacity at jc

• fe (numpy.ndarray, float) – mean enthalpy flux

• fd (numpy.ndarray, float) – mean conductive flux

• fk (numpy.ndarray, float) – mean kinetic flux

• fm (numpy.ndarray, float) – mean Poynting flux

• fr (numpy.ndarray, float) – mean radiative flux

• fvxl (numpy.ndarray, float) – SH expansion of vx

• fvyl (numpy.ndarray, float) – SH expansion of vy

• fvzl (numpy.ndarray, float) – SH expansion of vz

• fbxl (numpy.ndarray, float) – SH expansion of bx

• fbyl (numpy.ndarray, float) – SH expansion of by

• fbzl (numpy.ndarray, float) – SH expansion of bz

• fsel (numpy.ndarray, float) – SH expansion of entropy

• fvxm (numpy.ndarray, float) – SH expansion of vx with m = 0

• fvym (numpy.ndarray, float) – SH expansion of vy with m = 0

• fvzm (numpy.ndarray, float) – SH expansion of vz with m = 0

• fbxm (numpy.ndarray, float) – SH expansion of bx with m = 0

• fbym (numpy.ndarray, float) – SH expansion of by with m = 0

• fbzm (numpy.ndarray, float) – SH expansion of bz with m = 0

• fsem (numpy.ndarray, float) – SH expansion of entropy with m = 0

Methods Summary

read(n)

Reads on the fly analysis data from fortran.

Methods Documentation

read(n)

Reads on the fly analysis data from fortran. The data is stored in self.vc dictionary

Parameters:

• n (int) – A selected time step for data

• verbose (bool) – False suppresses a message of store

__init__(data)