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'''Return to [[Analysis Utilities]]''' | '''Return to [[Analysis Utilities]]''' | ||
This page documents the '''spectralindex''' function of Python module [[Analysis Utilities|analysisUtils]]. | This page documents the '''spectralindex''' function of the linfit class in the Python module [[Analysis Utilities|analysisUtils]]. | ||
This function is designed to fit a power-law spectral index to the results output from casa's fluxscale task. Currently, it also requires the | This function is designed to fit a power-law spectral index to the results output from casa's [[fluxscale]] task (using scipy.optimize.leastsq). Currently, it also requires a [[listobs]]-generated ascii file as the first argument in order to determine the center frequencies of each spectral window. (To avoid the need for this file in the future, we have submitted an [https://bugs.nrao.edu/browse/CAS-3770 improvement request] for [[fluxscale]] to also print these frequencies.) By default, it estimates the uncertainties | ||
of the fitted slope and amplitude from the square root of the diagonals of the covariance matrix. Alternatively, there is an option to run a Monte-Carlo series of fits to empirically determine the uncertainties. Finally, it produces a plot summarizing the results. By default, it will use all spectral windows, but it will exclude those with an "INSUFFICIENT DATA" status from fluxscale (which can arise in high-frequency EVLA data if you have not split off the pointing spws). | |||
Usage: | '''Usage:''' | ||
<tt>au.spectralindex(filename, yfilename="", source="", verbose=False, maxpoints=0, trials=0, spw="", plotdir="", labelspw=False, referenceFrame='TOPO', plaintext=False, lineNumbers=None, columns=None, yscale=1.0, plotunits='linear') </tt> | |||
filename: contains a listobs output file | filename: contains a listobs output file | ||
yfilename: contains a fluxscale output file | yfilename: contains a fluxscale output file | ||
source: sourcename to choose from the (possibly) multi-source fluxscale file | source: sourcename to choose from the (possibly) multi-source fluxscale file | ||
maxpoints: the maximum number of spws to select for the fit (0=no max) | maxpoints: the maximum number of spws to select for the fit starting from the first one (0=no max) | ||
trials: | trials: if > 0, use a Monte-Carlo technique estimate the fit uncertainties, | ||
spw: the spws to use, e.g. | otherwise, use the sqrt(covarMatrix) from scipy.optimize.leastsq (default). | ||
(There is a minimum number of 100 trials, and ~1000 is recommended.) | |||
spw: the spws to use, e.g. ""=all, "1~3,5,6~8"=[1,2,3,5,6,7,8] | |||
plotdir: the directory in which to write the plotfile (in case you don't have permission in the pwd) | |||
labelspw: draw spw numeric labels adjacent to each point | |||
referenceFrame: the frequency reference frame in the listobs file, if not 'TOPO' | |||
plaintext: if True, then read the freqs, flux densities and uncertainties from a single plain text file, | |||
specified by filename, with one measurement per line with a format of | |||
"frequency_in_GHz flux_density uncertainty" | |||
lineNumbers: which lines to read, where 1 is the first line in the file (default=all) | |||
columns: which columns to read for freq, flux, error (starting at 1) (default=[1,2,3]) | |||
yscale: factor by which to scale the y values after reading them from the file | |||
plotunits: 'linear' or 'log' (only used if trials==0) | |||
==Examples== | ==Examples== | ||
<source lang="Python"> | |||
# In CASA | |||
CASA <6>: au.spectralindex('13A-287.sb24170282.eb24176850.56505.0217034838.ms.listobs','fluxdensities.log',labelspw=T) | |||
</source> | |||
<pre> | |||
Skipping spw 0 due to INSUFFICIENT DATA result from fluxscale. | |||
Skipping spw 1 due to INSUFFICIENT DATA result from fluxscale. | |||
Read 64 x values for J1215-1731 (avg=44700.000) | |||
Read 64 y values for J1215-1731 (avg=0.998) | |||
Error-weighted fit: Slope: -0.564+-0.086 Flux D. @ 47.240GHz: 0.966+-0.002 | |||
Un-weighted fit: Slope: -0.584 Flux D. @ 47.240GHz: 0.965 | |||
Plot saved in /tmp/fluxdensities.log.J1215-1731.png | |||
</pre> | |||
[[File:fluxdensities.log.J1215-1731.png]] | |||
==File formats== | |||
The listobs file should be a file generated by the listfile option of {{listobs}} (or at least the excerpt containing the spw information). It is keying off the referenceFrame string (default = "TOPO"), so there can be any number of leading or trailing comment characters on each line, and any number of unrelated lines of text at the top or bottom. It also works if the spw name is present, or not present (casa < 4.1). Here is an example of the old-style listobs format (which still works): | |||
<pre> | |||
SpwID #Chans Frame Ch1(MHz) ChanWid(kHz) TotBW(kHz) Corrs | |||
0 128 TOPO 39926 1000 128000 RR LL | |||
1 128 TOPO 40054 1000 128000 RR LL | |||
2 128 TOPO 40182 1000 128000 RR LL | |||
3 128 TOPO 40310 1000 128000 RR LL | |||
4 128 TOPO 40438 1000 128000 RR LL | |||
5 128 TOPO 40566 1000 128000 RR LL | |||
6 128 TOPO 40694 1000 128000 RR LL | |||
7 128 TOPO 40822 1000 128000 RR LL | |||
8 128 TOPO 42248 1000 128000 RR LL | |||
9 128 TOPO 42376 1000 128000 RR LL | |||
10 128 TOPO 42504 1000 128000 RR LL | |||
11 128 TOPO 42632 1000 128000 RR LL | |||
12 128 TOPO 42760 1000 128000 RR LL | |||
13 128 TOPO 42888 1000 128000 RR LL | |||
14 128 TOPO 43016 1000 128000 RR LL | |||
15 128 TOPO 43144 1000 128000 RR LL | |||
</pre> | |||
Similarly, the fluxscale file should look like this. It can contain the results for multiple sources. It is keying off of the string 'SpW', so there can be any number of leading comment characters on each line, and any number of unrelated lines of text at the top. | |||
<pre> | |||
# Found reference field(s): J1331+3030 | |||
# Found transfer field(s): J1717-3342 J1924-2914 | |||
# Flux density for J1717-3342 in SpW=0 is: 1.81919 +/- 0.0271038 (SNR = 67.1192, N= 40) | |||
# Flux density for J1717-3342 in SpW=1 is: 1.79095 +/- 0.0272306 (SNR = 65.7698, N= 40) | |||
# Flux density for J1717-3342 in SpW=2 is: 1.7854 +/- 0.0267479 (SNR = 66.7493, N= 40) | |||
# Flux density for J1717-3342 in SpW=3 is: 1.77486 +/- 0.0272127 (SNR = 65.222, N= 40) | |||
# Flux density for J1717-3342 in SpW=4 is: 1.77261 +/- 0.0278025 (SNR = 63.7573, N= 40) | |||
# Flux density for J1717-3342 in SpW=5 is: 1.77175 +/- 0.0280525 (SNR = 63.1585, N= 40) | |||
# Flux density for J1717-3342 in SpW=6 is: 1.76183 +/- 0.0287407 (SNR = 61.3007, N= 40) | |||
# Flux density for J1717-3342 in SpW=7 is: 1.76226 +/- 0.0288519 (SNR = 61.0795, N= 40) | |||
# Flux density for J1717-3342 in SpW=8 is: 1.7605 +/- 0.0303092 (SNR = 58.0849, N= 40) | |||
# Flux density for J1717-3342 in SpW=9 is: 1.76177 +/- 0.0301251 (SNR = 58.4819, N= 40) | |||
# Flux density for J1717-3342 in SpW=10 is: 1.75611 +/- 0.0296369 (SNR = 59.2543, N= 40) | |||
# Flux density for J1717-3342 in SpW=11 is: 1.74256 +/- 0.0300252 (SNR = 58.0368, N= 40) | |||
# Flux density for J1717-3342 in SpW=12 is: 1.7471 +/- 0.0304127 (SNR = 57.4463, N= 40) | |||
# Flux density for J1717-3342 in SpW=13 is: 1.75201 +/- 0.0304666 (SNR = 57.5059, N= 40) | |||
# Flux density for J1717-3342 in SpW=14 is: 1.74798 +/- 0.0303736 (SNR = 57.5495, N= 40) | |||
# Flux density for J1717-3342 in SpW=15 is: 1.74099 +/- 0.0306128 (SNR = 56.8714, N= 40) | |||
# Flux density for J1924-2914 in SpW=0 is: 13.5637 +/- 0.0392228 (SNR = 345.812, N= 40) | |||
# Flux density for J1924-2914 in SpW=1 is: 13.393 +/- 0.0400481 (SNR = 334.424, N= 40) | |||
# Flux density for J1924-2914 in SpW=2 is: 13.3472 +/- 0.0388534 (SNR = 343.528, N= 40) | |||
# Flux density for J1924-2914 in SpW=3 is: 13.3187 +/- 0.0386627 (SNR = 344.483, N= 40) | |||
# Flux density for J1924-2914 in SpW=4 is: 13.3088 +/- 0.0386251 (SNR = 344.564, N= 40) | |||
# Flux density for J1924-2914 in SpW=5 is: 13.2596 +/- 0.0392739 (SNR = 337.62, N= 40) | |||
# Flux density for J1924-2914 in SpW=6 is: 13.2172 +/- 0.0413275 (SNR = 319.816, N= 40) | |||
# Flux density for J1924-2914 in SpW=7 is: 13.2503 +/- 0.0422232 (SNR = 313.815, N= 40) | |||
# Flux density for J1924-2914 in SpW=8 is: 13.1581 +/- 0.0434202 (SNR = 303.042, N= 40) | |||
# Flux density for J1924-2914 in SpW=9 is: 13.1242 +/- 0.0443572 (SNR = 295.875, N= 40) | |||
# Flux density for J1924-2914 in SpW=10 is: 13.0839 +/- 0.0432023 (SNR = 302.853, N= 40) | |||
# Flux density for J1924-2914 in SpW=11 is: 13.0526 +/- 0.0424958 (SNR = 307.15, N= 40) | |||
# Flux density for J1924-2914 in SpW=12 is: 13.0662 +/- 0.0436696 (SNR = 299.206, N= 40) | |||
# Flux density for J1924-2914 in SpW=13 is: 13.057 +/- 0.0440618 (SNR = 296.335, N= 40) | |||
# Flux density for J1924-2914 in SpW=14 is: 13.0354 +/- 0.0437052 (SNR = 298.257, N= 40) | |||
# Flux density for J1924-2914 in SpW=15 is: 13.0241 +/- 0.0444637 (SNR = 292.915, N= 40) | |||
</pre> | |||
Latest revision as of 12:56, 8 August 2013
Return to Analysis Utilities
This page documents the spectralindex function of the linfit class in the Python module analysisUtils.
This function is designed to fit a power-law spectral index to the results output from casa's fluxscale task (using scipy.optimize.leastsq). Currently, it also requires a listobs-generated ascii file as the first argument in order to determine the center frequencies of each spectral window. (To avoid the need for this file in the future, we have submitted an improvement request for fluxscale to also print these frequencies.) By default, it estimates the uncertainties of the fitted slope and amplitude from the square root of the diagonals of the covariance matrix. Alternatively, there is an option to run a Monte-Carlo series of fits to empirically determine the uncertainties. Finally, it produces a plot summarizing the results. By default, it will use all spectral windows, but it will exclude those with an "INSUFFICIENT DATA" status from fluxscale (which can arise in high-frequency EVLA data if you have not split off the pointing spws).
Usage:
au.spectralindex(filename, yfilename="", source="", verbose=False, maxpoints=0, trials=0, spw="", plotdir="", labelspw=False, referenceFrame='TOPO', plaintext=False, lineNumbers=None, columns=None, yscale=1.0, plotunits='linear')
filename: contains a listobs output file
yfilename: contains a fluxscale output file
source: sourcename to choose from the (possibly) multi-source fluxscale file
maxpoints: the maximum number of spws to select for the fit starting from the first one (0=no max)
trials: if > 0, use a Monte-Carlo technique estimate the fit uncertainties,
otherwise, use the sqrt(covarMatrix) from scipy.optimize.leastsq (default).
(There is a minimum number of 100 trials, and ~1000 is recommended.)
spw: the spws to use, e.g. ""=all, "1~3,5,6~8"=[1,2,3,5,6,7,8]
plotdir: the directory in which to write the plotfile (in case you don't have permission in the pwd)
labelspw: draw spw numeric labels adjacent to each point
referenceFrame: the frequency reference frame in the listobs file, if not 'TOPO'
plaintext: if True, then read the freqs, flux densities and uncertainties from a single plain text file,
specified by filename, with one measurement per line with a format of
"frequency_in_GHz flux_density uncertainty"
lineNumbers: which lines to read, where 1 is the first line in the file (default=all)
columns: which columns to read for freq, flux, error (starting at 1) (default=[1,2,3])
yscale: factor by which to scale the y values after reading them from the file
plotunits: 'linear' or 'log' (only used if trials==0)
Examples
# In CASA
CASA <6>: au.spectralindex('13A-287.sb24170282.eb24176850.56505.0217034838.ms.listobs','fluxdensities.log',labelspw=T)
Skipping spw 0 due to INSUFFICIENT DATA result from fluxscale. Skipping spw 1 due to INSUFFICIENT DATA result from fluxscale. Read 64 x values for J1215-1731 (avg=44700.000) Read 64 y values for J1215-1731 (avg=0.998) Error-weighted fit: Slope: -0.564+-0.086 Flux D. @ 47.240GHz: 0.966+-0.002 Un-weighted fit: Slope: -0.584 Flux D. @ 47.240GHz: 0.965 Plot saved in /tmp/fluxdensities.log.J1215-1731.png
File formats
The listobs file should be a file generated by the listfile option of listobs (or at least the excerpt containing the spw information). It is keying off the referenceFrame string (default = "TOPO"), so there can be any number of leading or trailing comment characters on each line, and any number of unrelated lines of text at the top or bottom. It also works if the spw name is present, or not present (casa < 4.1). Here is an example of the old-style listobs format (which still works):
SpwID #Chans Frame Ch1(MHz) ChanWid(kHz) TotBW(kHz) Corrs 0 128 TOPO 39926 1000 128000 RR LL 1 128 TOPO 40054 1000 128000 RR LL 2 128 TOPO 40182 1000 128000 RR LL 3 128 TOPO 40310 1000 128000 RR LL 4 128 TOPO 40438 1000 128000 RR LL 5 128 TOPO 40566 1000 128000 RR LL 6 128 TOPO 40694 1000 128000 RR LL 7 128 TOPO 40822 1000 128000 RR LL 8 128 TOPO 42248 1000 128000 RR LL 9 128 TOPO 42376 1000 128000 RR LL 10 128 TOPO 42504 1000 128000 RR LL 11 128 TOPO 42632 1000 128000 RR LL 12 128 TOPO 42760 1000 128000 RR LL 13 128 TOPO 42888 1000 128000 RR LL 14 128 TOPO 43016 1000 128000 RR LL 15 128 TOPO 43144 1000 128000 RR LL
Similarly, the fluxscale file should look like this. It can contain the results for multiple sources. It is keying off of the string 'SpW', so there can be any number of leading comment characters on each line, and any number of unrelated lines of text at the top.
# Found reference field(s): J1331+3030 # Found transfer field(s): J1717-3342 J1924-2914 # Flux density for J1717-3342 in SpW=0 is: 1.81919 +/- 0.0271038 (SNR = 67.1192, N= 40) # Flux density for J1717-3342 in SpW=1 is: 1.79095 +/- 0.0272306 (SNR = 65.7698, N= 40) # Flux density for J1717-3342 in SpW=2 is: 1.7854 +/- 0.0267479 (SNR = 66.7493, N= 40) # Flux density for J1717-3342 in SpW=3 is: 1.77486 +/- 0.0272127 (SNR = 65.222, N= 40) # Flux density for J1717-3342 in SpW=4 is: 1.77261 +/- 0.0278025 (SNR = 63.7573, N= 40) # Flux density for J1717-3342 in SpW=5 is: 1.77175 +/- 0.0280525 (SNR = 63.1585, N= 40) # Flux density for J1717-3342 in SpW=6 is: 1.76183 +/- 0.0287407 (SNR = 61.3007, N= 40) # Flux density for J1717-3342 in SpW=7 is: 1.76226 +/- 0.0288519 (SNR = 61.0795, N= 40) # Flux density for J1717-3342 in SpW=8 is: 1.7605 +/- 0.0303092 (SNR = 58.0849, N= 40) # Flux density for J1717-3342 in SpW=9 is: 1.76177 +/- 0.0301251 (SNR = 58.4819, N= 40) # Flux density for J1717-3342 in SpW=10 is: 1.75611 +/- 0.0296369 (SNR = 59.2543, N= 40) # Flux density for J1717-3342 in SpW=11 is: 1.74256 +/- 0.0300252 (SNR = 58.0368, N= 40) # Flux density for J1717-3342 in SpW=12 is: 1.7471 +/- 0.0304127 (SNR = 57.4463, N= 40) # Flux density for J1717-3342 in SpW=13 is: 1.75201 +/- 0.0304666 (SNR = 57.5059, N= 40) # Flux density for J1717-3342 in SpW=14 is: 1.74798 +/- 0.0303736 (SNR = 57.5495, N= 40) # Flux density for J1717-3342 in SpW=15 is: 1.74099 +/- 0.0306128 (SNR = 56.8714, N= 40) # Flux density for J1924-2914 in SpW=0 is: 13.5637 +/- 0.0392228 (SNR = 345.812, N= 40) # Flux density for J1924-2914 in SpW=1 is: 13.393 +/- 0.0400481 (SNR = 334.424, N= 40) # Flux density for J1924-2914 in SpW=2 is: 13.3472 +/- 0.0388534 (SNR = 343.528, N= 40) # Flux density for J1924-2914 in SpW=3 is: 13.3187 +/- 0.0386627 (SNR = 344.483, N= 40) # Flux density for J1924-2914 in SpW=4 is: 13.3088 +/- 0.0386251 (SNR = 344.564, N= 40) # Flux density for J1924-2914 in SpW=5 is: 13.2596 +/- 0.0392739 (SNR = 337.62, N= 40) # Flux density for J1924-2914 in SpW=6 is: 13.2172 +/- 0.0413275 (SNR = 319.816, N= 40) # Flux density for J1924-2914 in SpW=7 is: 13.2503 +/- 0.0422232 (SNR = 313.815, N= 40) # Flux density for J1924-2914 in SpW=8 is: 13.1581 +/- 0.0434202 (SNR = 303.042, N= 40) # Flux density for J1924-2914 in SpW=9 is: 13.1242 +/- 0.0443572 (SNR = 295.875, N= 40) # Flux density for J1924-2914 in SpW=10 is: 13.0839 +/- 0.0432023 (SNR = 302.853, N= 40) # Flux density for J1924-2914 in SpW=11 is: 13.0526 +/- 0.0424958 (SNR = 307.15, N= 40) # Flux density for J1924-2914 in SpW=12 is: 13.0662 +/- 0.0436696 (SNR = 299.206, N= 40) # Flux density for J1924-2914 in SpW=13 is: 13.057 +/- 0.0440618 (SNR = 296.335, N= 40) # Flux density for J1924-2914 in SpW=14 is: 13.0354 +/- 0.0437052 (SNR = 298.257, N= 40) # Flux density for J1924-2914 in SpW=15 is: 13.0241 +/- 0.0444637 (SNR = 292.915, N= 40)
