Removed RMS noise estimate for being badly defined. Removed _chan 1D …

…outputs for being low-value and confusing.

RMtools_1D/do_RMclean_1D.py

@@ -186,7 +186,6 @@ def run_rmclean(mDict, aDict, cutoff,
         log('QU Noise = %.4g %s' % (mDict["dQU"],mDict["units"]))
         log('FDF Noise (theory)   = %.4g %s' % (mDict["dFDFth"],mDict["units"]))
         log('FDF Noise (Corrected MAD) = %.4g %s' % (mDict_cl["dFDFcorMAD"],mDict["units"]))
-        log('FDF Noise (rms)   = %.4g %s' % (mDict_cl["dFDFrms"],mDict["units"]))
 
         log('FDF SNR = %.4g ' % (mDict_cl["snrPIfit"]))
         log()

RMtools_1D/do_RMsynth_1D.py

@@ -216,11 +216,11 @@ def run_rmsynth(data, polyOrd=2, phiMax_radm2=None, dPhi_radm2=None,
         rmsFig = plt.figure(facecolor='w',figsize=(12.0, 8))
         ax = rmsFig.add_subplot(111)
         ax.plot(freqArr_Hz/1e9, dQUArr, marker='o', color='k', lw=0.5,
-                label='rms <QU>')
+                label='noise <QU>')
         ax.plot(freqArr_Hz/1e9, dQArr, marker='o', color='b', lw=0.5,
-                label='rms Q')
+                label='noise Q')
         ax.plot(freqArr_Hz/1e9, dUArr, marker='o', color='r', lw=0.5,
-                label='rms U')
+                label='noise U')
         xRange = (np.nanmax(freqArr_Hz)-np.nanmin(freqArr_Hz))/1e9
         ax.set_xlim( np.min(freqArr_Hz)/1e9 - xRange*0.05,
                      np.max(freqArr_Hz)/1e9 + xRange*0.05)
@@ -431,7 +431,6 @@ def run_rmsynth(data, polyOrd=2, phiMax_radm2=None, dPhi_radm2=None,
        log('QU Noise = %.4g %s' % (mDict["dQU"],units))
        log('FDF Noise (theory)   = %.4g %s' % (mDict["dFDFth"],units))
        log('FDF Noise (Corrected MAD) = %.4g %s' % (mDict["dFDFcorMAD"],units))
-       log('FDF Noise (rms)   = %.4g %s' % (mDict["dFDFrms"],units))
        log('FDF SNR = %.4g ' % (mDict["snrPIfit"]))
        log('sigma_add(q) = %.4g (+%.4g, -%.4g)' % (mDict["sigmaAddQ"],
                                             mDict["dSigmaAddPlusQ"],

RMtools_1D/rmtools_bwdepol.py

@@ -616,7 +616,6 @@ def bwdepol_measure_FDF_parms(FDF, phiArr, fwhmRMSF, adjoint_sens, adjoint_noise
     rm_fdf = absFDF / adjoint_noise # RM spectrum in S:N units (normalized by RM-dependent noise)
     amp_fdf = absFDF/ adjoint_sens # RM spectrum normalized by (RM-dependent) sensitivity
     indxPeakPIchan = np.nanargmax(rm_fdf[1:-1])+1  # Masks out the edge channels
-    ampPeakPIchan = amp_fdf[indxPeakPIchan]  # since they can't be fit to.
 
     # new theoretical dFDF correction for adjoint method
     #This is noise in the adjoint-spectrum.
@@ -638,42 +637,17 @@ def bwdepol_measure_FDF_parms(FDF, phiArr, fwhmRMSF, adjoint_sens, adjoint_noise
     absFDFmsked = absFDFmsked[np.where(absFDFmsked==absFDFmsked)]
     if float(len(absFDFmsked))/len(absFDF)<0.3:
         dFDFcorMAD = MAD(rm_fdf)
-        dFDFrms = np.sqrt( np.mean(rm_fdf**2) )
     else:
         dFDFcorMAD = MAD(absFDFmsked)
-        dFDFrms = np.sqrt( np.mean(absFDFmsked**2) )
 
     #The noise is re-normalized by the predicted noise at the peak RM.
     dFDFcorMAD = dFDFcorMAD * adjoint_noise[indxPeakPIchan]
-    dFDFrms  = dFDFrms  * adjoint_noise[indxPeakPIchan]
-
-    # Measure the RM of the peak channel
-    phiPeakPIchan = phiArr[indxPeakPIchan]
-    snrPIchan = ampPeakPIchan * adjoint_sens[indxPeakPIchan] / dFDF
-    dPhiPeakPIchan = fwhmRMSF / (2.0 * snrPIchan)
-
-    # Correct the peak for polarisation bias (POSSUM report 11)
-    ampPeakPIchanEff = ampPeakPIchan
-    if snrPIchan >= snrDoBiasCorrect:
-        ampPeakPIchanEff = np.sqrt(ampPeakPIchan**2.0 - 2.3 * dampPeakPI**2.0)
-
-    # Calculate the polarisation angle from the channel; normalize by sensitivity
-    peakFDFimagChan = FDF.imag[indxPeakPIchan] / adjoint_sens[indxPeakPIchan]
-    peakFDFrealChan = FDF.real[indxPeakPIchan] / adjoint_sens[indxPeakPIchan]
-    polAngleChan_deg = 0.5 * np.degrees(np.arctan2(peakFDFimagChan,
-                                         peakFDFrealChan)) % 180
-    dPolAngleChan_deg = np.degrees(0.5 / snrPIchan)
-
-    # Calculate the derotated polarisation angle and uncertainty
-    polAngle0Chan_deg = np.degrees(np.radians(polAngleChan_deg) -
-                                  phiPeakPIchan * lam0Sq) % 180
+
+
+
     nChansGood = np.sum(np.where(lamSqArr_m2==lamSqArr_m2, 1.0, 0.0))
     varLamSqArr_m2 = (np.sum(lamSqArr_m2**2.0) -
                       np.sum(lamSqArr_m2)**2.0/nChansGood) / (nChansGood-1)
-    dPolAngle0Chan_rad = \
-        np.sqrt( dampPeakPI**2.0*nChansGood / (4.0*(nChansGood-2.0)*ampPeakPIchan**2.0) *
-                 ((nChansGood-1)/nChansGood + lam0Sq**2.0/varLamSqArr_m2) )
-    dPolAngle0Chan_deg = np.degrees(dPolAngle0Chan_rad)
 
     # Determine the peak in the FDF, its amplitude and Phi using a
     # 3-point parabolic interpolation
@@ -733,20 +707,6 @@ def bwdepol_measure_FDF_parms(FDF, phiArr, fwhmRMSF, adjoint_sens, adjoint_noise
 
     # Store the measurements in a dictionary and return
     mDict = {'dFDFcorMAD':       toscalar(dFDFcorMAD),
-             'dFDFrms':          toscalar(dFDFrms),
-             'phiPeakPIchan_rm2':     toscalar(phiPeakPIchan),
-             'dPhiPeakPIchan_rm2':    toscalar(dPhiPeakPIchan),
-             'ampPeakPIchan':    toscalar(ampPeakPIchan),
-             'ampPeakPIchanEff': toscalar(ampPeakPIchanEff),
-             'dAmpPeakPIchan':   toscalar(dampPeakPI),
-             'snrPIchan':             toscalar(snrPIchan),
-             'indxPeakPIchan':        toscalar(indxPeakPIchan),
-             'peakFDFimagChan':       toscalar(peakFDFimagChan),
-             'peakFDFrealChan':       toscalar(peakFDFrealChan),
-             'polAngleChan_deg':      toscalar(polAngleChan_deg),
-             'dPolAngleChan_deg':     toscalar(dPolAngleChan_deg),
-             'polAngle0Chan_deg':     toscalar(polAngle0Chan_deg),
-             'dPolAngle0Chan_deg':    toscalar(dPolAngle0Chan_deg),
              'phiPeakPIfit_rm2':      toscalar(phiPeakPIfit),
              'dPhiPeakPIfit_rm2':     toscalar(dPhiPeakPIfit),
              'ampPeakPIfit':     toscalar(ampPeakPIfit),
@@ -1224,7 +1184,6 @@ def run_adjoint_rmsynth(data, polyOrd=3, phiMax_radm2=None, dPhi_radm2=None,
        log('QU Noise = %.4g %s' % (mDict["dQU"],units))
        log('FDF Noise (theory)   = %.4g %s' % (mDict["dFDFth"],units))
        log('FDF Noise (Corrected MAD) = %.4g %s' % (mDict["dFDFcorMAD"],units))
-       log('FDF Noise (rms)   = %.4g %s' % (mDict["dFDFrms"],units))
        log('FDF SNR = %.4g ' % (mDict["snrPIfit"]))
        log('sigma_add(q) = %.4g (+%.4g, -%.4g)' % (mDict["sigmaAddQ"],
                                             mDict["dSigmaAddPlusQ"],

RMtools_3D/RMpeakfit_3D.py

@@ -173,15 +173,7 @@ def save_maps(map_dict, prefix_path,FDFheader):
 
 
     #Dictionary of units for peak fitting output parameters (for FITS headers)
-    unit_dict={"dFDFcorMAD": flux_unit, "dFDFrms": flux_unit,
-           "phiPeakPIchan_rm2": 'rad/m^2', "dPhiPeakPIchan_rm2": 'rad/m^2',
-           "ampPeakPIchan": flux_unit, "ampPeakPIchanEff": flux_unit,
-           "dAmpPeakPIchan": flux_unit,
-           "snrPIchan": '',
-           "indxPeakPIchan": '',
-           "peakFDFimagChan": flux_unit, "peakFDFrealChan": flux_unit,
-           "polAngleChan_deg": 'deg', "dPolAngleChan_deg": 'deg',
-           "polAngle0Chan_deg": 'deg', "dPolAngle0Chan_deg": 'deg',
+    unit_dict={"dFDFcorMAD": flux_unit, 
            "phiPeakPIfit_rm2": 'rad/m^2', "dPhiPeakPIfit_rm2": 'rad/m^2',
            "ampPeakPIfit": flux_unit, "ampPeakPIfitEff": flux_unit,
            "dAmpPeakPIfit": flux_unit,
@@ -344,12 +336,7 @@ def main():
                       "ampPeakPIfitEff","dAmpPeakPIfit","snrPIfit",
                       "polAngle0Fit_deg","dPolAngle0Fit_deg"]
     elif args.all_products:
-        product_list=['dFDFcorMAD', 'dFDFrms', 'phiPeakPIchan_rm2',
-                      'dPhiPeakPIchan_rm2', 'ampPeakPIchan', 'ampPeakPIchanEff',
-                      'dAmpPeakPIchan', 'snrPIchan', 'indxPeakPIchan',
-                      'peakFDFimagChan', 'peakFDFrealChan', 'polAngleChan_deg',
-                      'dPolAngleChan_deg', 'polAngle0Chan_deg',
-                      'dPolAngle0Chan_deg', 'phiPeakPIfit_rm2',
+        product_list=['dFDFcorMAD', 'phiPeakPIfit_rm2',
                       'dPhiPeakPIfit_rm2', 'ampPeakPIfit', 'ampPeakPIfitEff',
                       'dAmpPeakPIfit', 'snrPIfit', 'indxPeakPIfit',
                       'peakFDFimagFit', 'peakFDFrealFit', 'polAngleFit_deg',

RMtools_3D/do_RMsynth_3D.py

@@ -69,12 +69,12 @@ def run_rmsynth(dataQ, dataU, freqArr_Hz, dataI=None, rmsArr=None,
 
     Kwargs:
         dataI (array_like): Model cube of Stokes I spectra (see do_fitIcube).
-        rmsArr (array_like): Cube of RMS spectra.
+        rmsArr (array_like): Cube of uncertainty spectra.
         phiMax_radm2 (float): Maximum absolute Faraday depth (rad/m^2).
         dPhi_radm2 (float): Faraday depth channel size (rad/m^2).
         nSamples (float): Number of samples across the RMSF.
            weightType (str): Can be "variance" or "uniform"
-            "variance" -- Weight by RMS.
+            "variance" -- Weight by inverse variance.
             "uniform" -- Weight uniformly (i.e. with 1s)
         fitRMSF (bool): Fit a Gaussian to the RMSF?
         nBits (int): Precision of floating point numbers.

RMutils/util_RM.py

@@ -832,7 +832,6 @@ def measure_FDF_parms(FDF, phiArr, fwhmRMSF, dFDF=None, lamSqArr_m2=None,
     # Determine the peak channel in the FDF, its amplitude and index
     absFDF = np.abs(FDF)
     indxPeakPIchan = np.nanargmax(absFDF[1:-1])+1  #Masks out the edge channels, since they can't be fit to.
-    ampPeakPIchan = absFDF[indxPeakPIchan]
 
     # Measure the RMS noise in the spectrum after masking the peak
     dPhi = np.nanmin(np.diff(phiArr))
@@ -844,42 +843,17 @@ def measure_FDF_parms(FDF, phiArr, fwhmRMSF, dFDF=None, lamSqArr_m2=None,
     absFDFmsked = absFDFmsked[np.where(absFDFmsked==absFDFmsked)]
     if float(len(absFDFmsked))/len(absFDF)<0.3:
         dFDFcorMAD = MAD(absFDF)
-        dFDFrms = np.sqrt( np.mean(absFDF**2) )
     else:
         dFDFcorMAD = MAD(absFDFmsked)
-        dFDFrms = np.sqrt( np.mean(absFDFmsked**2) )
 
     # Default to using the measured FDF if a noise value has not been provided
     if dFDF is None:
         dFDF = dFDFcorMAD
 
-    # Measure the RM of the peak channel
-    phiPeakPIchan = phiArr[indxPeakPIchan]
-    dPhiPeakPIchan = fwhmRMSF * dFDF / (2.0 * ampPeakPIchan)
-    snrPIchan = ampPeakPIchan / dFDF
-
-    # Correct the peak for polarisation bias (POSSUM report 11)
-    ampPeakPIchanEff = ampPeakPIchan
-    if snrPIchan >= snrDoBiasCorrect:
-        ampPeakPIchanEff = np.sqrt(ampPeakPIchan**2.0 - 2.3 * dFDF**2.0)
-
-    # Calculate the polarisation angle from the channel
-    peakFDFimagChan = FDF.imag[indxPeakPIchan]
-    peakFDFrealChan = FDF.real[indxPeakPIchan]
-    polAngleChan_deg = 0.5 * np.degrees(np.arctan2(peakFDFimagChan,
-                                         peakFDFrealChan)) % 180
-    dPolAngleChan_deg = np.degrees(dFDF / (2.0 * ampPeakPIchan))
-
-    # Calculate the derotated polarisation angle and uncertainty
-    polAngle0Chan_deg = np.degrees(np.radians(polAngleChan_deg) -
-                                  phiPeakPIchan * lam0Sq) % 180
+
     nChansGood = np.sum(np.where(lamSqArr_m2==lamSqArr_m2, 1.0, 0.0))
     varLamSqArr_m2 = (np.sum(lamSqArr_m2**2.0) -
                       np.sum(lamSqArr_m2)**2.0/nChansGood) / (nChansGood-1)
-    dPolAngle0Chan_rad = \
-        np.sqrt( dFDF**2.0*nChansGood / (4.0*(nChansGood-2.0)*ampPeakPIchan**2.0) *
-                 ((nChansGood-1)/nChansGood + lam0Sq**2.0/varLamSqArr_m2) )
-    dPolAngle0Chan_deg = np.degrees(dPolAngle0Chan_rad)
 
     # Determine the peak in the FDF, its amplitude and Phi using a
     # 3-point parabolic interpolation
@@ -946,20 +920,6 @@ def measure_FDF_parms(FDF, phiArr, fwhmRMSF, dFDF=None, lamSqArr_m2=None,
 
     # Store the measurements in a dictionary and return
     mDict = {'dFDFcorMAD':       toscalar(dFDFcorMAD),
-             'dFDFrms':          toscalar(dFDFrms),
-             'phiPeakPIchan_rm2':     toscalar(phiPeakPIchan),
-             'dPhiPeakPIchan_rm2':    toscalar(dPhiPeakPIchan),
-             'ampPeakPIchan':    toscalar(ampPeakPIchan),
-             'ampPeakPIchanEff': toscalar(ampPeakPIchanEff),
-             'dAmpPeakPIchan':   toscalar(dFDF),
-             'snrPIchan':             toscalar(snrPIchan),
-             'indxPeakPIchan':        toscalar(indxPeakPIchan),
-             'peakFDFimagChan':       toscalar(peakFDFimagChan),
-             'peakFDFrealChan':       toscalar(peakFDFrealChan),
-             'polAngleChan_deg':      toscalar(polAngleChan_deg),
-             'dPolAngleChan_deg':     toscalar(dPolAngleChan_deg),
-             'polAngle0Chan_deg':     toscalar(polAngle0Chan_deg),
-             'dPolAngle0Chan_deg':    toscalar(dPolAngle0Chan_deg),
              'phiPeakPIfit_rm2':      toscalar(phiPeakPIfit),
              'dPhiPeakPIfit_rm2':     toscalar(dPhiPeakPIfit),
              'ampPeakPIfit':     toscalar(ampPeakPIfit),

RMutils/util_misc.py

@@ -68,28 +68,32 @@
 #                                                                             #
 #=============================================================================#
 
-import os
 import sys
-import copy
 import re
-import time
 import traceback
 import math as m
 import numpy as np
 import numpy.ma as ma
 import scipy.ndimage as ndi
 from scipy.stats import norm
 #import ConfigParser
-import sqlite3
-import csv
-import json
 
 from RMutils.mpfit import mpfit
 
+from . import __version__
+from deprecation import deprecated
+
+
 C = 2.99792458e8
 
 
 #-----------------------------------------------------------------------------#
+@deprecated(
+    deprecated_in="1.3.1",
+    removed_in="1.4",
+    current_version=__version__,
+    details="This function is not used anywhere in current RM-Tools.",
+)
 def config_read(filename, delim='=', doValueSplit=True):
     """
     Read a configuration file and output a 'KEY=VALUE' dictionary.
@@ -179,6 +183,12 @@ def csv_read_to_list(fileName, delim=",", doFloat=False):
 
 
 #-----------------------------------------------------------------------------#
+@deprecated(
+    deprecated_in="1.3.1",
+    removed_in="1.4",
+    current_version=__version__,
+    details="This function is not used anywhere in RM-Tools.",
+)
 def cleanup_str_input(textBlock):
 
     # Compile a few useful regular expressions
@@ -209,6 +219,12 @@ def split_repeat_lst(inLst, nPre, nRepeat):
 
 
 #-----------------------------------------------------------------------------#
+@deprecated(
+    deprecated_in="1.3.1",
+    removed_in="1.4",
+    current_version=__version__,
+    details="This function is not used anywhere in RM-Tools.",
+)
 def deg2dms(deg, delim=':', doSign=False, nPlaces=2):
     """
     Convert a float in degrees to 'dd mm ss' format.
@@ -408,7 +424,12 @@ def calculate_StokesI_model(fitDict,freqArr_Hz):
 
 
 
-
+@deprecated(
+    deprecated_in="1.3",
+    removed_in="2.0",
+    current_version=__version__,
+    details="This function cannot current propagate errors. It may be reactivated if someone works through how to do that.",
+)
 def renormalize_StokesI_model(fitDict,new_reference_frequency):
     """This functions adjusts the reference frequency for the Stokes I model
     and fixes the fit parameters such that the the model is the same. This is
@@ -785,6 +806,12 @@ def calc_stats(a, maskzero=False):
 
 
 #-----------------------------------------------------------------------------#
+@deprecated(
+    deprecated_in="1.3.1",
+    removed_in="1.4",
+    current_version=__version__,
+    details="This function is not used anywhere in current RM-Tools.",
+)
 def sort_nicely(l):
     """
     Sort a list in the order a human would.

tests/RMclean1D_referencevalues.json

@@ -1 +1 @@
-{"dFDFcorMAD": 0.004604571498930454, "dFDFrms": 0.010632162913680077, "phiPeakPIchan_rm2": 201.0, "dPhiPeakPIchan_rm2": 0.248169183058158, "ampPeakPIchan": 0.6993770003318787, "ampPeakPIchanEff": 0.6993199035324889, "dAmpPeakPIchan": 0.005892556709695188, "snrPIchan": 118.68820866520879, "indxPeakPIchan": 267, "peakFDFimagChan": -0.5605486035346985, "peakFDFrealChan": 0.41822659969329834, "polAngleChan_deg": 153.36335372924805, "dPolAngleChan_deg": 0.2413709843523719, "polAngle0Chan_deg": 44.00355316060791, "dPolAngle0Chan_deg": 1.3733003278171074, "phiPeakPIfit_rm2": 200.32874264404734, "dPhiPeakPIfit_rm2": 0.24808332381938963, "ampPeakPIfit": 0.6996190479469143, "ampPeakPIfitEff": 0.6995619709029499, "dAmpPeakPIfit": 0.005892556709695188, "snrPIfit": 118.72928550620676, "indxPeakPIfit": 266.77624754801576, "peakFDFimagFit": -0.5592812449927833, "peakFDFrealFit": 0.4189165597767205, "polAngleFit_deg": 153.41709453229126, "dPolAngleFit_deg": 0.24128747709042306, "polAngle0Fit_deg": 48.02926667512406, "dPolAngle0Fit_deg": 1.3728252062919697, "cleanCutoff": 0.017677670129085565, "nIter": 11, "mom2CCFDF": 0.9521095156669617, "dPhiObserved_rm2": 0.19385768495688968, "dAmpObserved": 0.004604571498930454, "dPolAngleFitObserved_deg": 0.1885472630634841, "dPolAngleFit0Observed_deg": 1.0727553639839833}
+{"dFDFcorMAD": 0.004604571498930454, "phiPeakPIfit_rm2": 200.32874264404734, "dPhiPeakPIfit_rm2": 0.24808332381938963, "ampPeakPIfit": 0.6996190479469143, "ampPeakPIfitEff": 0.6995619709029499, "dAmpPeakPIfit": 0.005892556709695188, "snrPIfit": 118.72928550620676, "indxPeakPIfit": 266.77624754801576, "peakFDFimagFit": -0.5592812449927833, "peakFDFrealFit": 0.4189165597767205, "polAngleFit_deg": 153.41709453229126, "dPolAngleFit_deg": 0.24128747709042306, "polAngle0Fit_deg": 48.02926667512406, "dPolAngle0Fit_deg": 1.3728252062919697, "cleanCutoff": 0.017677670129085565, "nIter": 11, "mom2CCFDF": 0.9521095156669617, "dPhiObserved_rm2": 0.19385768495688968, "dAmpObserved": 0.004604571498930454, "dPolAngleFitObserved_deg": 0.1885472630634841, "dPolAngleFit0Observed_deg": 1.0727553639839833}