# Source code for casatasks.analysis.imfit

```
#
# stub function definition file for docstring parsing
#
[docs]def imfit(imagename, box='', region='', chans='', stokes='', mask='', includepix='', excludepix='', residual='', model='', estimates='', logfile='', append=True, newestimates='', complist='', overwrite=False, dooff=False, offset=0.0, fixoffset=False, stretch=False, rms='-1', noisefwhm='', summary=''):
r"""
Fit one or more elliptical Gaussian components on an image region(s)
[`Description`_] [`Examples`_] [`Development`_] [`Details`_]
Parameters
- imagename_ (path) - Name of the input image
- box_ (string='') - Rectangular region(s) to select in direction plane. Default is to use the entire direction plane.
- region_ (variant='') - Region selection. Default is to use the full image.
- chans_ (variant='') - Channels to use. Default is to use all channels.
- stokes_ (string='') - Stokes planes to use. Default is to use first Stokes plane.
- mask_ (string='') - Mask to use. Default is none.
.. raw:: html
<details><summary><i> mask != '' </i></summary>
- stretch_ (bool=False) - Stretch the mask if necessary and possible?
.. raw:: html
</details>
- includepix_ (doubleVec='') - Range of pixel values to include for fitting.
- excludepix_ (doubleVec='') - Range of pixel values to exclude for fitting.
- residual_ (string='') - Name of output residual image.
- model_ (string='') - Name of output model image.
- estimates_ (string='') - Name of file containing initial estimates of component parameters.
- logfile_ (string='') - Name of file to write fit results.
.. raw:: html
<details><summary><i> logfile != '' </i></summary>
- append_ (bool=True) - If logfile exists, append to it if True or overwrite it if False
.. raw:: html
</details>
- newestimates_ (string='') - File to write fit results which can be used as initial estimates for next run.
- complist_ (string='') - Name of output component list table.
.. raw:: html
<details><summary><i> complist != '' </i></summary>
- overwrite_ (bool=False) - Overwrite component list table if it exists?
.. raw:: html
</details>
- dooff_ (bool=False) - Also fit a zero level offset? Default is False
.. raw:: html
<details><summary><i> dooff != False </i></summary>
- offset_ (double=0.0) - Initial estimate of zero-level offset. Only used if doff is True. Default is 0.0
- fixoffset_ (bool=False) - Keep the zero level offset fixed during fit? Default is False
.. raw:: html
</details>
- rms_ ({int, double, record, string}='-1') - RMS to use in calculation of uncertainties. Numeric or valid quantity (record or string). If numeric, it is given units of the input image. If quantity, units must conform to image units. If not positive, the rms of the residual image, in the region of the fit, is used.
- noisefwhm_ ({int, double, record, string}='') - Noise correlation beam FWHM. If numeric value, interpreted as pixel widths. If quantity (dictionary, string), it must have angular units.
- summary_ (string='') - File name to which to write table of fit parameters.
.. _Returns:
Returns
out (dict) - fitting information including list of fitted
components, per-channel convergence, and direction coordinate pixel
increments
.. _Description:
Description
This task is used to fit one or more two dimensional
Gaussians to sources in an image as well as an optional zero-level
offset. Fitting is limited to a single polarization but can be
performed over several contiguous spectral channels. If the image
has a clean beam, the report and returned dictionary will contain
both the convolved and the deconvolved fit results. For examples
and explanation of the dictionary, see the `Image Plane
Analysis <../../notebooks/image_analysis.ipynb#Image-Plane-Analysis>`__
pages.
When dooff is False, the method returns a dictionary with keys
named 'converged', 'pixelsperarcsec', 'results', and
'deconvolved'. The value of 'converged' is a boolean array which
indicates if the fit converged on a channel by channel basis. The
value of 'pixelsperarcsec' is a two element double array with the
absolute values of the direction coordinate pixel increments
(longitude-like and latitude-like coordinate, respectively) in
arcsec. The value of 'results' is a dictionary representing a
component list reflecting the fit results. In the case of an image
containing beam information, the sizes and position angles in the
'results' dictionary are those of the source(s) convolved with the
restoring beam, while the same parameters in the 'deconvolved'
dictionary represent the source sizes deconvolved from the beam.
In the case where the image does not contain a beam, 'deconvolved'
will be absent. Both the 'results' and 'deconvolved' dictionaries
can be read into a component list tool (default tool is named cl)
using the fromrecord() method for easier inspection using tool
methods, eg
::
cl.fromrecord(res['results'])
although this only works if the flux density units are conformant
with Jy.
There are also values in each component subdictionary not used by
**cl.fromrecord()** but meant to supply additional information.
There is a 'peak' subdictionary for each component that provides
the peak intensity of the component. It is present for both
'results' and 'deconvolved' components. There is also a 'sum'
subdictionary for each component indicating the simple sum of
pixel values in the the original image enclosed by the fitted
ellipse. There is a 'channel' entry in the 'spectrum'
subdictionary which provides the zero-based channel number in the
input image for which the solution applies. In addtion, if the
image has a beam(s), then there will be a 'beam' subdictionary
associated with each component in both the 'results' and
'deconvolved' dictionaries. This subdictionary will have three
keys: '*beamarcsec*' will be a subdictionary giving the beam
dimensions in arcsec, '*beampixels*' will have the value of the
beam area expressed in pixels, and '*beamster*' will have the
value of the beam area expressed in steradians. Also, if the image
has a beam(s), in the component level dictionaries will be an
'ispoint' entry with an associated boolean value describing if the
component is consistent with a point source. Each component level
dictionary will have a 'pixelcoords' entry which has the value of
a two element numeric array which provides the direction pixel
coordinates of the fitted position.
If *dooff* is True, in addition to the specified number of
Gaussians, a zero level offset will also be fit. The initial
estimate for this offset is specified using the *offset*
parameter. Units are assumed to be the same as the image
brightness units. The zero level offset can be held constant
during the fit by specifying *fixoffset=True*. In the case of
*dooff=True*, the returned dictionary contains two additional
keys, '*zerooff*' and '*zeroofferr*', which are both dictionaries
containing '*unit*' and '*value*' keys. The values associated with
the '*value*' keys are arrays containing the fitted zero level
offset value and its error, respectively, for each channel. In
cases where the fit did not converge, these values are set to NaN.
The value associated with '*unit*' is just the image brightness
unit.
The region can either be specified by a *box(es)* or a *region*.
Ranges of pixel values can be included or excluded from the fit.
If specified using the *box* parameter, multiple boxes can be
given using the format *box* ="blcx1, blcy1, trcx1, trcy1, blcx2,
blcy2, trcx2, trcy2, ... , blcxN, blcyN, trcxN, trcyN" where N is
the number of boxes. In this case, the union of the specified
boxes will be used.
The default behavior of imfit is to fit a single Gaussian
component. If a multiple-Gaussian fit is desired, the user must
specify initial estimates via a text file (see below for details).
If no estimate file is specified, imfit will attempt to guess the
initial parameters and fit a single Gaussian to the union of
specified boxes/regions. Users who wish to perform individual fits
to separate regions should run imfit multiple times, specifying a
single input box/region each time.
If specified, the *residual* and/or *model* images for successful
fits will be written.
The user has the option of writing the result of the fit to a log
file, and has the option of either appending to or overwriting an
existing file.
The user has the option of writing the (convolved) parameters of a
successful fit to a file which can be fed back to **imfit** as the
new estimates file for a subsequent run.
The user has the option of writing the fit results in tabular
format to a file whose name is specified using the *summary*
parameter.
If specified and positive, the value of *rms* is used to calculate
the parameter uncertainties, otherwise, the rms in the selected
region in the relevant channel is used for these calculations.
The *noisefwhm* parameter represents the noise-correlation beam
FWHM. If specified as a quantity, it should have angular units. If
specified as a numerical value, it is set equal to that number of
pixels. If specified and greater than or equal to the pixel size,
it is used to calculate parameter uncertainties using the
correlated noise equations (see below). If it is specified but
less than a pixel width, the uncorrelated noise equations (see
below) are used to compute the parameter uncertainties. If it is
not specified and the image has a restoring beam(s), the
correlated noise equations are used to compute parameter
uncertainties using the geometric mean of the relevant beam major
and minor axes as the noise-correlation beam FWHM. If *noisefwhm*
is not specified and the image does not have a restoring beam,
then the uncorrelated noise equations are used to compute the
parameter uncertainties.
.. rubric:: SUPPORTED UNITS
Currently only images with brightness units conformant with
Jy/beam, Jy/beam km/s, and K are fully supported for fitting. If
your image has some other base brightness unit, that unit will be
assumed to be equivalent to Jy/pixel and results will be
calculated accordingly. In particular, the flux density (reported
as Integrated Flux in the logger and associated with the "flux"
key in the returned component subdictionary(ies)) for such a case
represents the sum of pixel values.
Note also that converting the returned results subdictionary to a
component list via **cl.fromrecord()** currently only works
properly if the flux density units in the results dictionary are
conformant with Jy. If you need to be able to run
**cl.fromrecord()** on the resulting dictionary you can first
modify the flux density units by hand to be (some prefix)Jy and
then run cl.fromrecord() on that dictionary, bearing in mind your
unit conversion.
If the input image has units of K, the flux density of components
will be reported in units of [prefix]K*rad*rad, where prefix is an
SI prefix used so that the numerical value is between 1 and 1000.
To convert to units of K*beam, determine the area of the
appropriate beam, which is given by
.. math:: \begin{equation} \frac{\pi}{4 \rm{ln} 2} \, b_{\rm maj} \,b_{\rm min} \end{equation}
where :math: `b_{\rm maj}` and :math:`b_{\rm min}` are the major
and minor axes of the beam, and convert to steradians (=rad*rad).
This value is included in the beam portion of the component
subdictionary (key '*beamster*'). Then divide the numerical value
of the logged flux density by the beam area in steradians. So, for
example
::
# run on an image with K brightness units
res = imfit(...)
# get the I flux density in K*beam of component 0
comp = res['results']['component0']
flux_density_kbeam = comp['flux']['value'][0]/comp['beam']['beamster']
.. rubric:: FITTING OVER MULTIPLE CHANNELS
For fitting over multiple channels, the result of the previous
successful fit is used as the estimate for the next channel. The
number of Gaussians fit cannot be varied on a channel by channel
basis. Thus the variation of source structure should be reasonably
smooth in frequency to produce reliable fit results.
.. rubric:: MASK SPECIFICATION
`Mask <../../notebooks/image_analysis.ipynb#Image-Masks>`__
specification can be done using an `LEL
expression <../../notebooks/image_analysis.ipynb#Lattice-Expression-Language>`__.
For example
::
mask = "myimage>5"
will use only pixels with values greater than 5.
.. rubric:: INCLUDING AND EXCLUDING PIXELS
Pixels can be included or excluded from the fit based on their
values using these parameters. Note that specifying both is not
permitted and will cause an error. If specified, both take an
array of two numeric values.
.. rubric:: ESTIMATES
Initial estimates of fit parameters (peak intensity, peak x pixel
coordinate, peak y pixel coordinate, major axis, minor axis,
position angle) may be specified via an estimates text file. Each
line of this file should contain a set of parameters for a single
Gaussian. Optionally, some of these parameters can be fixed during
the fit. The format of each line is: peak intensity, peak x-pixel
value, peak y-pixel value, major axis, minor axis, position angle,
fixed.
The fixed parameter is optional. The peak intensity is assumed
to be in the same units as the image pixel values (eg Jy/beam).
The peak coordinates are specified in pixel coordinates. The
major and minor axes and the position angle are the convolved
parameters if the image has been convolved with a clean beam and
are specified as quantities. The fixed parameter is optional and
is a string. It may contain any combination of the following
characters 'f' (peak intensity), 'x' (peak x position), 'y'
(peak y position), 'a' (major axis), 'b' (axial ratio, R =
(major axis FWHM)/(minor axis FWHM)), 'p' (position angle).
**NOTE: One cannot hold the minor axis fixed without holding the
major axis fixed.** If the major axis is not fixed, specifying
'b' in the fixed string will hold the axial ratio fixed during
the fit.
In addition, lines in the file starting with a # are considered
comments.
An example of such a file is:
::
# peak intensity must be in map units
120, 150, 110, 23.5arcsec, 18.9arcsec, 120deg
90, 60, 200, 46arcsec, 23arcsec, 140deg, fxp
This is a file which specifies that two Gaussians are to be
simultaneously fit, and for the second Gaussian the specified peak
intensity, x position, and position angle are to be held fixed
during the fit.
.. rubric:: ERROR ESTIMATES
Error estimates are based on the work of Condon (1997) [1]_
Key assumptions made are:
- The given model (elliptical Gaussian, or elliptical Gaussian
plus constant offset) is an adequate representation of the data
- An accurate estimate of the pixel noise is provided or can be
derived (see above). For the case of correlated noise (e.g., a
CLEAN map), the fit region should contain many "beams" or an
independent value of rms should be provided.
- The signal-to-noise ratio (SNR) of the Gaussian component is
large. This is necessary because a Taylor series is used to
linearize the problem. Condon (1997) states that the fractional
bias in the fitted amplitude due to this assumption is of order
1/S :sup:`2`, where S is the overall SNR of the Gaussian with
respect to the given data set (defined more precisely below).
For a 5 sigma "detection" of the Gaussian, this is a 4% effect.
- All (or practically all) of the flux in the component being fit
falls within the selected region.
If a constant offset term is simultaneously fit and not fixed, the
region of interest should be even larger. The derivations of the
expressions summarized in this note assume an effectively infinite
region.
Two sets of equations are used to calculate the parameter
uncertainties, based on if the noise is correlated or
uncorrelated. The rules governing which set of equations are used
have been described above in the description of the *noisefwhm*
parameter.
In the case of uncorrelated noise, the equations used are
.. math:: \begin{equation} \frac{\sigma(A)}{A} = \frac{\sigma(I)}{I} = \frac{\sigma(\theta_M)}{\theta_M} = \frac{\sigma(\theta_m)}{\theta_m} = \sqrt{8ln2} \frac{\sigma(x_0)}{\theta_M} = \sqrt{8ln2}\frac{\sigma(y_0)}{\theta_m} = \frac{\sigma(\phi)}{\sqrt{2}}(\frac{\theta_M^2-\theta_m^2}{\theta_M\theta_m}) = \frac{\sqrt{2}}{\rho}\end{equation}
where :math:`\sigma(z)` is the uncertainty associated with
parameter :math:`z`, :math:`A` is the peak intensity, :math:`I` is
the flux density, :math:`\theta_M` and :math:`\theta_m` are the
FWHM major and minor axes, :math:`\phi` is the position angle of
the component, :math:`x_0` and :math:`y_0` are the direction
uncertainties of the component measured along the major and minor
axes; the resulting uncertainties measured along the principle
axes of the image direction coordinate are calculated by
propagation of errors using the 2D rotation matrix which enacts
the rotation through the position angle plus 90 degrees.
:math:`\rho` is the overall signal to noise ratio of the
component, which, for the uncorrelated noise case, is given by
.. math:: \begin{equation} \rho = \frac{A}{h\mu}\sqrt{\frac{\pi\theta_M\theta_m}{8ln2}} \end{equation}
where :math:`h` is the pixel width of the direction coordinate and
:math:`\mu` is the rms noise (see the discussion above for the
rules governing how the value of :math:`\mu` is determined).
For the correlated noise case, the same equations are used to
determine the uncertainties as in the uncorrelated noise case,
except for the uncertainty in :math:`I` (see below). However,
:math:`\rho` is given by
.. math:: \begin{equation} \rho = \frac{A}{\mu}\frac{\sqrt{\theta_M\theta_m}}{2\theta_N}\left(1 + \left(\frac{\theta_N}{\theta_M}\right)^2\right)^{\alpha_M/2}\left(1 + \left(\frac{\theta_N}{\theta_m}\right)^2\right)^{\alpha_m/2} \end{equation}
where :math:`\theta_N` is the noise-correlation beam FWHM (see
discussion of the *noisefwhm* parameter for rules governing how
this value is determined). Variables :math:`\alpha_M` and
:math:`\alpha_m` depend on which uncertainty is being calculated.
For :math:`\sigma(A)`, :math:`\alpha_M` = :math:`\alpha_m` = 3/2.
For :math:`\sigma_M` and :math:`x_0`, :math:`\alpha_M` = 5/2 and
:math:`\alpha_m` = 1/2. For :math:`\theta_m`, :math:`y_0`, and
:math:`\phi`, :math:`\alpha_M` = 1/2 and :math:`\alpha_m` = 5/2.
:math:`\sigma(I)` is calculated in the correlated noise case
according to
.. math:: \begin{equation} \frac{\sigma(I)}{I} = \sqrt{ \left(\frac{\sigma(A)}{A}\right)^2 + \left(\frac{\theta_N^2}{\theta_M\theta_m}\right)\left[\left(\frac{\sigma(\theta_M)}{\theta_M}\right)^2 + \left(\frac{\sigma(\theta_m)}{\theta_m}\right)^2 \right] } \end{equation}
Note well the following caveats:
- Fixing Gaussian component parameters will tend to cause the
parameter uncertainties reported for free parameters to be
overestimated.
- Fitting a zero level offset that is not fixed will tend to
cause the reported parameter uncertainties to be slightly
underestimated.
- The parameter uncertainties will be inaccurate at low SNR (a
~10% for SNR = 3).
- If the fitted region is not considerably larger than the
largest component that is fit, parameter uncertainties may be
mis-estimated.
- An accurate rms noise measurement, :math:`\mu`, for the region
in question must be supplied. Alternatively, a sufficiently
large signal-free region must be present in the selected region
(at least about 25 noise beams in area) to auto-derive such an
estimate.
- If the image noise is not statistically independent from pixel
to pixel, a reasonably accurate noise correlation scale,
:math:`\theta` :math:`_N`, must be provided. If the noise
correlation function is not approximately Gaussian, the
correlation length can be estimated using
.. math:: \begin{equation} \theta_N = \sqrt{ \frac{2 \ln (2)}{\pi} } \, \frac{ \iint C(x,y) \mathrm{d}x \mathrm{d}y} { \sqrt{ \iint C(x,y)^2 \mathrm{d}x \mathrm{d}y} } \end{equation}
where C(x,y) is the associated noise-smoothing function.
- If fitted model components have significant spatial overlap,
the parameter uncertainties are likely to be mis-estimated
(i.e., correlations between the parameters of separate
components are not accounted for).
- If the image being analyzed is an interferometric image with
poor uv sampling, the parameter uncertainties may be
significantly underestimated.
The deconvolved size and position angle errors are computed by
taking the maximum of the absolute values of the differences of
the best fit deconvolved value of the given parameter and the
deconvolved size of the eight possible combinations of (FWHM major
axis +/- major axis error), (FWHM minor axis +/- minor axis
error), and (position angle +/- position angle error). If the
source cannot be deconvolved from the beam (if the best fit
convolved source size cannot be deconvolved from the beam), upper
limits on the deconvolved source size are reported, if possible.
These limits simply come from the maximum major and minor axes of
the deconvolved Gaussians taken from trying all eight of the
aforementioned combinations. In the case none of these
combinations produces a deconvolved size, no upper limit is
reported.
.. rubric:: Task-specific Parameter Descriptions
*includepix*
Two element array giving the range of pixel values to include in
the fit. Only one range of pixel values may be specified in
includepix or excludepix.
*excludepix*
Two element array giving the range of pixel values to exclude in
the fit. Only one range of pixel values may be specified in
includepix or excludepix.
*residual*
Name of output residual image. Empty string indicates that the
residual image should not be written.
*model*
Name of output model image. Empty string indicates that the model
image should not be written.
*estimates*
Name of the text file that contains the initial parameter
estimates. See the above description describing the format for
such a file. An empty string indicates that the application should
automatically determine initial parameter estimates. If it is
desired that more than one Gaussian be fit simultaneously, an
estimates file must be specified.
*logfile*
Name of output file to which to write results. If set to the empty
string, no logfile is written, although the results can still be
obtained from the logger output.
*append*
If True, append results to the specified logfile if it already
exists. If False, overwrite an existing logfile if it already
exists.
*newestimates*
Name of file to which to write the results of the fit in an
estimates file format, so that the written file can be used as the
estimates file on subsequent runs. The empty string means do not
write such a file.
*complist*
Name of the component list table to which to write the fitted
model. The empty string indicates that a component list table
should not be written.
*overwrite*
Indicates if an existing component list table should be
overwritten. If False and a component list table of the name
specified by the complist parameter already exists, an exception
will be thrown.
*dooff*
Indicates if a constant zero-level offset should also be
simultaneously fit.
*offset*
Initial estimate for the zero level offset, in the same units as
the values in the image.
*fixoffset*
Indicates if the specified zero-level offset should be held fixed
during the fit.
*rms*
RMS to use in calculation of uncertainties. Numeric or valid
quantity (record or string). If numeric, it is given units of the
input image. If quantity, units must conform to image units. If
not positive, the rms of the residual image, in the region of the
fit, is used. See the above discussion for more details.
*noisefwhm*
Noise correlation beam FWHM. If numeric value, interpreted as
pixel widths. If quantity (dictionary, string), it must have
angular units. See the above discussion for more details.
*summary*
Name of file to which to write a plain text table summary of the
fit parameters. The empty string indicates that such a file should
not be written.
.. rubric:: Bibliography
.. [1] Condon (1997) `http://adsabs.harvard.edu/abs/1997PASP..109..166C <http://adsabs.harvard.edu/abs/1997PASP..109..166C>`__
.. _Examples:
Examples
Here is how one might fit two Gaussians to multiple channels of a
cube using the fit from the previous channel as the initial
estimate for the next. It also illustrates how one can specify a
region in the associated continuum image as the region to use as
the fit for the channel.
::
default imfit
imagename = "co_cube.im"
# specify box around source
box = "50,50,100,100"
chans = "2~20"
# only use pixels with positive values in the fit
excludepix = [-1e10,0]
# estimates file contains initial parameters for two
Gaussians in channel 2
estimates = "initial_estimates.txt"
# append results to the log file for all the channels
append = "True"
imfit()
.. _Development:
Development
No additional development details
.. _Details:
Parameter Details
Detailed descriptions of each function parameter
.. _imagename:
| ``imagename (path)`` - Name of the input image
.. _box:
| ``box (string='')`` - Rectangular region(s) to select in direction plane. Default is to use the entire direction plane.
.. _region:
| ``region (variant='')`` - Region selection. Default is to use the full image.
.. _chans:
| ``chans (variant='')`` - Channels to use. Default is to use all channels.
.. _stokes:
| ``stokes (string='')`` - Stokes planes to use. Default is to use first Stokes plane.
.. _mask:
| ``mask (string='')`` - Mask to use. Default is none.
.. _includepix:
| ``includepix (doubleVec='')`` - Range of pixel values to include for fitting.
.. _excludepix:
| ``excludepix (doubleVec='')`` - Range of pixel values to exclude for fitting.
.. _residual:
| ``residual (string='')`` - Name of output residual image.
.. _model:
| ``model (string='')`` - Name of output model image.
.. _estimates:
| ``estimates (string='')`` - Name of file containing initial estimates of component parameters.
.. _logfile:
| ``logfile (string='')`` - Name of file to write fit results.
.. _append:
| ``append (bool=True)`` - If logfile exists, append to it if True or overwrite it if False
.. _newestimates:
| ``newestimates (string='')`` - File to write fit results which can be used as initial estimates for next run.
.. _complist:
| ``complist (string='')`` - Name of output component list table.
.. _overwrite:
| ``overwrite (bool=False)`` - Overwrite component list table if it exists?
.. _dooff:
| ``dooff (bool=False)`` - Also fit a zero level offset? Default is False
.. _offset:
| ``offset (double=0.0)`` - Initial estimate of zero-level offset. Only used if doff is True. Default is 0.0
.. _fixoffset:
| ``fixoffset (bool=False)`` - Keep the zero level offset fixed during fit? Default is False
.. _stretch:
| ``stretch (bool=False)`` - Stretch the mask if necessary and possible?
.. _rms:
| ``rms ({int, double, record, string}='-1')`` - RMS to use in calculation of uncertainties. Numeric or valid quantity (record or string). If numeric, it is given units of the input image. If quantity, units must conform to image units. If not positive, the rms of the residual image, in the region of the fit, is used.
.. _noisefwhm:
| ``noisefwhm ({int, double, record, string}='')`` - Noise correlation beam FWHM. If numeric value, interpreted as pixel widths. If quantity (dictionary, string), it must have angular units.
.. _summary:
| ``summary (string='')`` - File name to which to write table of fit parameters.
"""
pass
```