Python NDG.comment方法代码示例

# 需要导入模块: from starutil import NDG [as 别名]
# 或者: from starutil.NDG import comment [as 别名]
def run_calcqu(input_data,config,harmonic):
    #  The following call to SMURF:CALCQU creates two HDS container files -
    #  one holding a set of Q NDFs and the other holding a set of U NDFs. Create
    #  these container files in the NDG temporary directory.
    qcont = NDG(1)
    qcont.comment = "qcont"
    ucont = NDG(1)
    ucont.comment = "ucont"

    msg_out( "Calculating Q and U values for each bolometer...")
    invoke("$SMURF_DIR/calcqu in={0} config=\"{1}\" lsqfit=no outq={2} outu={3} "
           "harmonic={4} fix".format(input_data,starutil.shell_quote(config),
                                     qcont,ucont,harmonic) )
    return (qcont,ucont)

# 需要导入模块: from starutil import NDG [as 别名]
# 或者: from starutil.NDG import comment [as 别名]
def get_filtered_skydip_data(qarray,uarray,clip,a):
    """

    This function takes q and u array data (output from calcqu), applies ffclean to remove spikes
    and puts in numpy array variable
    It borrows (copies) heavily from pol2cat.py (2015A)

    Invocation:
        ( qdata_total,qvar_total,udata_total,uvar_total,elevation,opacity_term,bad_pixel_ref ) = ...
            get_filtered_skydip_data(qarray,uarray,clip,a)

    Arguments:
        qarray = An NDF of Q array data (output from calcqu).
        uarray = An NDF of U array data (output form calcqu).
        clip = The sigma cut for ffclean.
           a = A string indicating the array (eg. 'S8A').

    Returned Value:
        qdata_total = A numpy array with the cleaned qarray data.
        qvar_total = A numpy array with the qarray variance data.
        udata_total = A numpy array with the cleaned uarray data.
        uvar_total = A numpy array with the uarray variance data.
        elevation = A numpy array with the elevation data
        opacity_term = A numpy array with the opacity brightness term (1-exp(-tau*air_mass))
            Here tau is calculated using the WVM data as input.

    """

    #  Remove spikes from the Q images for the current subarray. The cleaned NDFs
    #  are written to temporary NDFs specified by the new NDG object "qff", which
    #  inherit its size from the existing group "qarray"".
    msg_out( "Removing spikes from {0} bolometer Q values...".format(a))
    qff = NDG(qarray)
    qff.comment = "qff"
    invoke( "$KAPPA_DIR/ffclean in={0} out={1} genvar=yes box=3 clip=\[{2}\]".format(qarray,qff,clip) )

    #  Remove spikes from the U images for the current subarray. The cleaned NDFs
    #  are written to temporary NDFs specified by the new NDG object "uff", which
    #  inherit its size from the existing group "uarray"".
    msg_out( "Removing spikes from {0} bolometer U values...".format(a))
    uff = NDG(uarray)
    uff.comment = "uff"
    invoke( "$KAPPA_DIR/ffclean in={0} out={1} genvar=yes box=3 clip=\[{2}\]"
            .format(uarray,uff,clip) )

    elevation = []
    opacity_term = []
    for stare in range(len(qff[:])):
    # Stack Q data in numpy array
        # Get elevation information
        elevation.append(numpy.array( float( invoke( "$KAPPA_DIR/fitsmod ndf={0} edit=print keyword=ELSTART".format( qff[ stare ] ) ) ) ) )
        # Get Tau (Opacity) information
        tau_temp = numpy.array( float( invoke( "$KAPPA_DIR/fitsmod ndf={0} edit=print keyword=WVMTAUST".format( qff[ stare ] ) ) ) )
        # Convert to obs band.
        if '4' in a:
             tau_temp = 19.04*(tau_temp-0.018) # Eq from Dempsey et al
        elif '8' in a:
             tau_temp = 5.36*(tau_temp-0.006) # Eq from Dempsey et al.
        opacity_term.append(1-numpy.exp(-1*tau_temp/numpy.sin(numpy.radians(elevation[-1]))))
        invoke( "$KAPPA_DIR/ndftrace {0} quiet".format(qff[ stare ]))
        nx = get_task_par( "dims(1)", "ndftrace" )
        ny = get_task_par( "dims(2)", "ndftrace" )
        qdata_temp = numpy.reshape( Ndf( qff[ stare ] ).data, (ny,nx))
        qdata_temp[numpy.abs(qdata_temp)>1e300] = numpy.nan;
        if stare == 0:
            qdata_total = qdata_temp
        else:
            qdata_total = numpy.dstack((qdata_total,qdata_temp))
        qvar_temp = numpy.reshape( Ndf( qff[ stare ] ).var, (ny,nx))
        qdata_temp[numpy.abs(qvar_temp)>1e300] = numpy.nan;
        if stare == 0:
            qvar_total = qvar_temp
        else:
            qvar_total = numpy.dstack((qvar_total,qvar_temp))
        # Stack U data in numpy array
        invoke( "$KAPPA_DIR/ndftrace {0} quiet".format(uff[ stare ]))
        nx = get_task_par( "dims(1)", "ndftrace" )
        ny = get_task_par( "dims(2)", "ndftrace" )
        udata_temp = numpy.reshape( Ndf( uff[ stare ] ).data, (ny,nx))
        udata_temp[numpy.abs(udata_temp)>1e300] = numpy.nan;
        if stare == 0:
            udata_total = udata_temp
        else:
            udata_total = numpy.dstack((udata_total,udata_temp))
        uvar_temp = numpy.reshape( Ndf( uff[ stare ] ).var, (ny,nx))
        udata_temp[numpy.abs(uvar_temp)>1e300] = numpy.nan;
        if stare == 0:
            uvar_total = uvar_temp
        else:
            uvar_total = numpy.dstack((uvar_total,uvar_temp))

    # Create bad pixel reference.
    bad_pixel_ref = NDG(1)
    invoke( "$KAPPA_DIR/copybad in={0} ref={1} out={2}".format(qff,uff,bad_pixel_ref))
    return( qdata_total,qvar_total,udata_total,uvar_total,elevation,opacity_term,bad_pixel_ref )

# 需要导入模块: from starutil import NDG [as 别名]
# 或者: from starutil.NDG import comment [as 别名]
   plot = parsys["PLOT"].value

#  If any vectors are to be plotted, get the SNR limit for the plotted
#  vectors.
   if plot != None:
      snr = parsys["SNR"].value
      maxlen = parsys["MAXLEN"].value

#  See if temp files are to be retained.
   retain = parsys["RETAIN"].value

#  The following call to SMURF:CALCQU creates two HDS container files -
#  one holding a set of Q NDFs and the other holding a set of U NDFs. Create
#  these container files in the NDG temporary directory.
   qcont = NDG(1)
   qcont.comment = "qcont"
   ucont = NDG(1)
   ucont.comment = "ucont"

#  Create a set of Q images and a set of U images. These are put into the HDS
#  container files "q_TMP.sdf" and "u_TMP.sdf". Each image contains Q or U
#  values derived from a short section of raw data during which each bolometer
#  moves less than half a pixel.
   msg_out( "Calculating Q and U values for each bolometer...")
   invoke("$SMURF_DIR/calcqu in={0} config={1} outq={2} outu={3} fix".
          format(indata,config,qcont,ucont) )

#  Remove spikes from the Q and U images. The cleaned NDFs are written to
#  temporary NDFs specified by two new NDG objects "qff" and "uff", which
#  inherit their size from the existing groups "qcont" and "ucont".
   msg_out( "Removing spikes from bolometer Q and U values...")