From 55dd6acf4e090d5abef41c267933c545a7496413 Mon Sep 17 00:00:00 2001 From: sowmyakth Date: Mon, 1 Apr 2019 18:18:45 -0700 Subject: [PATCH 01/13] minor formatting --- btk/__init__.py | 1 + 1 file changed, 1 insertion(+) diff --git a/btk/__init__.py b/btk/__init__.py index fba02c8d9..23fc9fd44 100644 --- a/btk/__init__.py +++ b/btk/__init__.py @@ -1,5 +1,6 @@ """Toolkit for fast simulation and analysis of overlapping objects for the LSST Dark Energy Science Collaboration. + The code generates on the fly images of overlapping parametric galaxies while providing framework to test user defined detection/deblending/measurement algorithms. From af9138fe45fd5b90f9b7d99b2d34b41e4ee28b3b Mon Sep 17 00:00:00 2001 From: Sowmya Kamath Date: Fri, 5 Apr 2019 13:39:23 -0700 Subject: [PATCH 02/13] link fixed --- docs/source/tutorials.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/tutorials.rst b/docs/source/tutorials.rst index 75ef4c3a1..56bea319e 100644 --- a/docs/source/tutorials.rst +++ b/docs/source/tutorials.rst @@ -10,7 +10,7 @@ This `notebook `_ , `lsst science pipeline ` +* detection with `SEP `_ , `lsst science pipeline `_ * deblending with `scarlet `_ * segmentation with SEP. From 90cf5a4f2ddf271257630333bce71d4502affcf6 Mon Sep 17 00:00:00 2001 From: Pat Burchat Date: Thu, 11 Apr 2019 17:37:13 -0700 Subject: [PATCH 03/13] Fix typos. --- docs/source/index.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/index.rst b/docs/source/index.rst index 2855667de..9d6d467e6 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -20,7 +20,7 @@ Key features of the framework are: * It can generate training/validation/test sets for developing and testing detection, deblending and measurement algorithms. * It includes data augmentation and independent (but reproducible) noise realizations. -* It is easily customizable with options to include user defined functions for blend generation, observing conditions, etc,. produces images on the fly. +* It is easily customizable with options to include user defined functions for blend generation, observing conditions, etc., and produce images on the fly. Getting Started ================== From fb3cbba1ed20178200315f0381d5545a16aedc45 Mon Sep 17 00:00:00 2001 From: Pat Burchat Date: Sun, 14 Apr 2019 16:33:20 -0700 Subject: [PATCH 04/13] Edits for clarity, typos, etc. --- docs/source/user_guide.rst | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/docs/source/user_guide.rst b/docs/source/user_guide.rst index 042298eec..e14310090 100644 --- a/docs/source/user_guide.rst +++ b/docs/source/user_guide.rst @@ -1,24 +1,24 @@ User Guide ============== -This document gives a detailed look into the work-flow of *BlendingToolKit* (btk). For a quick tutorial on how to run btk, see the JuPyter notebook tutorials :doc:`here `. This page is especially useful if you plan on using btk with your own detection/deblending/measurement algorithm. +This document gives a detailed look into the work-flow of *BlendingToolKit* (btk). For a quick tutorial on how to run btk, see the JuPyter notebook tutorials :doc:`here `. This page is especially useful if you plan to use btk with your own detection/deblending/measurement algorithm. -The workflow of btk is shown below +The workflow of btk is shown here: .. image:: images/flow_chart.png :align: center -1. Set parameters (*config*): define parameters to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch, i.e yielded at once by btk. The observing survey name (e.g. LSST. DES) is set here along with name of the input catalog and names of observing bands. +1. Set parameters (*config*): define parameters to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog, and the names of the observing bands are also specified here. 2. Load Catalog (*load_catalog*): Reads the input catalog file. This step includes an option to input a selection criteria. -3. Make blend catalog (*create_blend_generator*): Samples objects from the input catalog based on a user defined sampling function to create a catalog with parameters of each blend. This step output a generator that yields a new set of catalogs each time run with *next()*. This `notebook `_ shows different examples of user input sampling functions to create different blend catalogs. -4. Make observing conditions (*create_observing_generator*): Creates a class that contains information about the observing conditions like PSF, noise level, etc. The default is to use the full depth values corresponding to the survey named in config. However a user can define a function to generate this. This `notebook `_ shows an example of a user input function to generate observing conditions. -5. Draw blends (*create_blend_generator*): Simulates scene of overlapping objects, convolved by PSF and with pixel noise (option set in *config*). Scene image is generated in each observing band. Isolated image of each object is also drawn without pixel contributions from other objects, in each band. -6. Detection/Deblending/Measure (*measure*): A user defined class to perform detection/deblending/measurement goes here. *btk* does not include any algorithm as default but only provides a a framework for the user to run their algorithm for the images generated in *create_blend_generator*. This `notebook `_ contains examples of running btk with `SEP `_ (SExtractor with python) , `lsst science pipeline `_ and `scarlet `_. -7. Compute metrics (*metrics*): compares the true centroids, shapes, flux values to those predicted by the user algorithm. At present this only assesses detection performance by returning the number of objects correctly detected, number undetected and number of spurious detections. This `notebook `_ shows how this can be done. +3. Make blend catalog (*create_blend_generator*): Samples objects from the input catalog based on a user defined sampling function to create a catalog with parameters of each blend. This step outputs a generator that yields a new set of catalogs each time it is run with *next()*. This `notebook `_ shows several examples of user input sampling functions to create different blend catalogs. +4. Make observing conditions (*create_observing_generator*): Creates a class that contains information about the observing conditions such as PSF definition, noise level, etc. The default is to use the full-depth values corresponding to the survey named in config. However, a user can define a function to generate this. This `notebook `_ shows an example of a user input function to generate custom observing conditions. +5. Draw blends (*create_blend_generator*): Simulates scene of overlapping objects, convolved by the PSF and with pixel noise (option set in *config*). Scene image is generated in each observing band. An "isolated" image of each object is also drawn without pixel contributions from other objects, in each band. +6. Detection/Deblending/Measure (*measure*): A user defined class to perform detection/deblending/measurement goes here. *btk* does not include any default algorithm; rather, it provides a framework for the user to run their choice of algorithm for the images generated in *create_blend_generator*. This `notebook `_ contains examples of running btk with `SEP `_ (SExtractor with python) , `LSST science pipeline `_ and `SCARLET `_. +7. Compute metrics (*metrics*): compares the true centroids, shapes, and flux values to those predicted by the user-provided *measure* algorithm. Currently, *metrics* assesses only detection performance by returning the number of objects correctly detected, the number that are undetected and the number of spurious detections. This `notebook `_ shows how this can be done. Utils ------- -*btk/utils.py* contains functions that the user may find useful in creating functions to perform detection/deblending/measurement in *measure*. It shows how a class derived from *measure.Measurement_params* can be defined by the user for use with SEP, lsst science pipeline or stand-alone scarlet. +*btk/utils.py* contains functions that the user may find useful in creating functions to perform detection/deblending/measurement in *measure*. It shows how a class derived from *measure.Measurement_params* can be defined by the user for use with SEP, the LSST science pipeline or stand-alone SCARLET; see point 6 above. From 4d4d35734baad1cea7182d356bcbfb2c667becfe Mon Sep 17 00:00:00 2001 From: Pat Burchat Date: Sun, 14 Apr 2019 16:57:59 -0700 Subject: [PATCH 05/13] Minor editorial changes for clarity. --- docs/source/index.rst | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/docs/source/index.rst b/docs/source/index.rst index 9d6d467e6..f24e8db4b 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -14,13 +14,13 @@ *BlendingToolKit* (btk) is a framework to generate images of blended objects and evaluate performance metrics for different algorithms. -Detecting and separating overlapping sources, or "deblending", is primarily a research problem with several potential algorithmic solutions, including machine learning approaches. Computation of performance metrics on identical datasets will enable comparison between different algorithms. BTK provides a framework to easily and quickly generate datasets of blended objects for testing different algorithms, along with training samples for machine learning algorithms. +Detecting and separating overlapping sources, or "deblending", is primarily a research problem with several potential algorithmic solutions, including machine learning approaches. Computation of performance metrics on identical datasets will enable comparison between different algorithms. The goals of the btk framework are to allow the user to easily and quickly generate datasets of blended objects for testing different algorithms, as well as training samples for machine learning algorithms. -Key features of the framework are: +Key features or functionalities of the framework include: -* It can generate training/validation/test sets for developing and testing detection, deblending and measurement algorithms. -* It includes data augmentation and independent (but reproducible) noise realizations. -* It is easily customizable with options to include user defined functions for blend generation, observing conditions, etc., and produce images on the fly. +* generation of training/validation/test sets for developing and testing detection, deblending and measurement algorithms. +* data augmentation and independent (but reproducible) noise realizations. +* customization options for including user-defined functions for blend generation, observing conditions, etc., and for producing images on the fly. Getting Started ================== From 19ce0e8a295a7b4ceed01cb1a10ad25084865161 Mon Sep 17 00:00:00 2001 From: Pat Burchat Date: Sun, 14 Apr 2019 17:04:28 -0700 Subject: [PATCH 06/13] Fixed typos; edited for clarity. --- docs/source/install.rst | 25 ++++++++++++------------- 1 file changed, 12 insertions(+), 13 deletions(-) diff --git a/docs/source/install.rst b/docs/source/install.rst index 44277be54..e68393463 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -2,9 +2,9 @@ Installation =============== *BlendingToolKit* (btk) is essentially a wrapper around the -`WealLensingDeblending `_ -which uses `GalSim `_ to simulate -the galaxy images. So these packages along with +`WeakLensingDeblending `_ +package, which uses `GalSim `_ to simulate galaxy images. +These packages along with their dependencies need to be installed first. The following dependencies are pip installable: @@ -15,7 +15,7 @@ The following dependencies are pip installable: * scipy * lmfit -Install Galsim +Install GalSim ------------------------------- GalSim is a python module that has much of its implementation in C++ for @@ -23,9 +23,9 @@ improved computational efficiency. It can be installed with :: pip install galsim -However you may have to install FFTW and Eigen manually. Refer +However you may have to install FFTW and Eigen manually. Refer to `this `_ -for mre details. +for more details. Install WeakLensingDeblending package --------------------------------------- @@ -47,7 +47,7 @@ First download the repo: :: git clone https://github.com/LSSTDESC/BlendingToolKit.git -then install using +Then install using :: cd BlendingToolKit python setup.py install @@ -56,15 +56,14 @@ Optional Packages ------------------------------- *BlendingToolKit* is meant to perform detection/deblending/measurement with any -user input algorithm. Thus, as such no algorithm is hard coded into the basic -framework. However, the tutorial notebooks do include examples of how these can -be performed with btk. - -The tutorial notebooks require: +user input algorithm; therefore, no algorithm is hard-coded into the basic +framework. However, the tutorial notebooks include several examples of detection/deblending/measurement +algoritms that can be performed with btk. +These tutorial notebooks require: #. scarlet_ (multi-band deblender) #. sep_ (Python library for Source Extraction and Photometry) -#. lsst_ science pipeline +#. lsst_ (LSST science pipeline) .. _scarlet: https://scarlet.readthedocs.io/en/latest/index.html From 05794f3ddb6ebdc6ce4fc29625e5c94f11da8305 Mon Sep 17 00:00:00 2001 From: Pat Burchat Date: Sun, 14 Apr 2019 17:09:00 -0700 Subject: [PATCH 07/13] Minor edits for clarity. --- README.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/README.md b/README.md index 347075eac..2ce3cfdb4 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ [![Documentation Status](https://readthedocs.org/projects/blendingtoolkit/badge/?version=latest)](https://blendingtoolkit.readthedocs.io/en/latest/?badge=latest) # BlendingToolKit -Tools to create blend catalogs, produce training samples and implement blending metrics +Tools to create blend catalogs, produce training samples and implement blending metrics. Documentation can be found at https://blendingtoolkit.readthedocs.io/en/latest/ @@ -12,8 +12,8 @@ Documentation can be found at https://blendingtoolkit.readthedocs.io/en/latest/ ## Running BlendingToolKit - BlendingToolKit (btk) requires an input catalog that contains information required to simulate galaxies and blends. -This repository includes sample input catalogs with small number of galaxies that can be used to draw blend images with btk. See [tutorials](https://github.com/LSSTDESC/BlendingToolKit/tree/master/notebooks) to learn how to run btk with these catalogs. -- Catalog corresponding to one square degree sky and pre-processed WeakLensingDeblending catalogs can be downloaded from [here](https://stanford.app.box.com/s/s1nzjlinejpqandudjyykjejyxtgylbk). +This repository includes sample input catalogs with a small number of galaxies that can be used to draw blend images with btk. See [tutorials](https://github.com/LSSTDESC/BlendingToolKit/tree/master/notebooks) to learn how to run btk with these catalogs. +- Catalog corresponding to one square degree of sky and pre-processed WeakLensingDeblending catalogs can be downloaded from [here](https://stanford.app.box.com/s/s1nzjlinejpqandudjyykjejyxtgylbk). ## Requirements The code is intended to run in python >=3.6. @@ -26,10 +26,10 @@ To run btk you need to install - scipy - lmfit -More detailed installation instructions can be found [here](https://blendingtoolkit.readthedocs.io/en/latest/install.html) +More detailed installation instructions can be found [here](https://blendingtoolkit.readthedocs.io/en/latest/install.html). ### Optional -The tutorials include examples of using btk with some packages like +The tutorials include examples of using btk with some detection, deblending or measurement packages including - [scarlet](https://github.com/fred3m/scarlet/) (multi-band deblender) -- [sep](https://sep.readthedocs.io/en/v1.0.x/index.html)(Source Extraction and Photometry) -- [lsst](https://pipelines.lsst.io) science pipeline +- [sep](https://sep.readthedocs.io/en/v1.0.x/index.html) (Source Extraction and Photometry) +- [lsst](https://pipelines.lsst.io) (LSST science pipeline) From 975be9adda92216dff3773c7a2a3d513ce4145e6 Mon Sep 17 00:00:00 2001 From: Pat Burchat Date: Sun, 14 Apr 2019 17:18:01 -0700 Subject: [PATCH 08/13] Minor edits for clarity. --- docs/source/tutorials.rst | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/docs/source/tutorials.rst b/docs/source/tutorials.rst index 56bea319e..f54678dec 100644 --- a/docs/source/tutorials.rst +++ b/docs/source/tutorials.rst @@ -3,31 +3,31 @@ Tutorials The following jupyter notebooks are included in the `notebooks/` directory: -Run basic btk (*run_basic.ipynb*) +Run basic btk (*run_basic.ipynb*). ----------------------------------- -This `notebook `_ shows the how btk can generate multi-band blend image scenes along with isolated object images. PSF convolved object images are drawn in isolation and in the blend for each band. +This `notebook `_ shows how btk can be used to generate images of multi-band blend scenes, along with isolated object images -- i.e., PSF-convolved object images are drawn both in isolation and in the blend scene for each band. The notebook shows examples of performing: -* detection with `SEP `_ , `lsst science pipeline `_ -* deblending with `scarlet `_ +* detection with `SEP `_ , `lsst science pipeline `_, +* deblending with `scarlet `_, * segmentation with SEP. The notebook also includes functions helpful for plotting multi-band images. -Run with user input custom functions (*custom_sampling_function.ipynb*) +Run with user-input custom functions (*custom_sampling_function.ipynb*). -------------------------------------------------------------------------- This `notebook `_ demonstrates how users can define their own sampling functions to draw blend image scenes. -Also shown is how a user defined custom function can generate different observing conditions. This would enable on the fly generation of blend scene images with different noise levels and observing PSFs. +Also shown is an example of how a user-defined custom function can be used to generate different observing conditions. This enables on-the-fly generation of blend scene images with different noise levels and observing PSFs. -Evaluate Metrics with btk (*evaluate_metrics.ipynb*) +Evaluate metrics with btk (*evaluate_metrics.ipynb*). ---------------------------------------------------- -This `notebook `_ shows how to test performance of different detection/deblending/measurement algorithms. At present this only assesses detection performance by returning the number of objects correctly detected, number undetected and number of spurious detections. +This `notebook `_ shows how to test the performance of different detection/deblending/measurement algorithms. At present this only assesses detection performance by returning the number of objects correctly detected, the number of undetected objects and the number of spurious detections. -Draw blends (*create_blend_generator*): Simulates scene of overlapping objects, convolved by PSF and with pixel noise (option set in *config*). Scene image is generated in each observing band. Isolated image of each object is also drawn without pixel contributions from other objects, in each band. +Draw blends (*create_blend_generator*): Simulates a scene of overlapping objects, convolved by a PSF, with pixel noise (option set in *config*). The scene image is generated in each observing band. An isolated image of each object is also drawn in each band, with no pixel contributions from other objects. From 2df59573c58b0080559ee08b4b9b8d890ed173b0 Mon Sep 17 00:00:00 2001 From: sowmyakth Date: Mon, 15 Apr 2019 09:37:37 -0700 Subject: [PATCH 09/13] minor formatting in docs --- docs/source/tutorials.rst | 4 ++-- docs/source/user_guide.rst | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/source/tutorials.rst b/docs/source/tutorials.rst index f54678dec..2c2aaeefd 100644 --- a/docs/source/tutorials.rst +++ b/docs/source/tutorials.rst @@ -10,7 +10,7 @@ This `notebook `_ , `lsst science pipeline `_, +* detection with `SEP `_, `lsst science pipeline `_, * deblending with `scarlet `_, * segmentation with SEP. @@ -25,7 +25,7 @@ Also shown is an example of how a user-defined custom function can be used to ge Evaluate metrics with btk (*evaluate_metrics.ipynb*). ----------------------------------------------------- +------------------------------------------------------ This `notebook `_ shows how to test the performance of different detection/deblending/measurement algorithms. At present this only assesses detection performance by returning the number of objects correctly detected, the number of undetected objects and the number of spurious detections. Draw blends (*create_blend_generator*): Simulates a scene of overlapping objects, convolved by a PSF, with pixel noise (option set in *config*). The scene image is generated in each observing band. An isolated image of each object is also drawn in each band, with no pixel contributions from other objects. diff --git a/docs/source/user_guide.rst b/docs/source/user_guide.rst index e14310090..f415dd73b 100644 --- a/docs/source/user_guide.rst +++ b/docs/source/user_guide.rst @@ -1,7 +1,7 @@ User Guide ============== -This document gives a detailed look into the work-flow of *BlendingToolKit* (btk). For a quick tutorial on how to run btk, see the JuPyter notebook tutorials :doc:`here `. This page is especially useful if you plan to use btk with your own detection/deblending/measurement algorithm. +This document gives a detailed look into the work-flow of *BlendingToolKit* (btk). For a quick tutorial on how to run btk, see the JuPyter notebook tutorials `here `_. This page is especially useful if you plan to use btk with your own detection/deblending/measurement algorithm. The workflow of btk is shown here: @@ -21,4 +21,4 @@ The workflow of btk is shown here: Utils ------- -*btk/utils.py* contains functions that the user may find useful in creating functions to perform detection/deblending/measurement in *measure*. It shows how a class derived from *measure.Measurement_params* can be defined by the user for use with SEP, the LSST science pipeline or stand-alone SCARLET; see point 6 above. +*btk/utils.py* contains functions that the user may find useful in creating functions to perform detection/deblending/measurement in *measure*. It shows how a class derived from *measure.Measurement_params* can be defined by the user for use with SEP, the LSST science pipeline or stand-alone SCARLET; see point 6 above. From 52efeee3c585c0b48c2a9386482f39b74e28c4a9 Mon Sep 17 00:00:00 2001 From: sowmyakth Date: Mon, 15 Apr 2019 18:47:01 -0700 Subject: [PATCH 10/13] minor formatting of the documentation --- btk/config.py | 8 ++++---- docs/source/user_guide.rst | 8 ++++---- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/btk/config.py b/btk/config.py index 030a4f294..7088e1a38 100644 --- a/btk/config.py +++ b/btk/config.py @@ -1,5 +1,5 @@ class Simulation_params(object): - """Parameters to create blends. + """Parameter values to create blends. Attributes: catalog_name: Name of input catalog from which to draw objects. @@ -14,7 +14,7 @@ class Simulation_params(object): S/N threshold, where the signal N is calculated for the full exposure time and the noise N is set by the expected fluctuations in the sky background during a full exposure. - verbose: If true prints returns description at multiple steps. + verbose: If true, prints description at multiple steps. """ def __init__(self, catalog_name, max_number=2, batch_size=8, stamp_size=24, @@ -22,8 +22,8 @@ def __init__(self, catalog_name, max_number=2, seed=0, add_noise=True, bands=('u', 'g', 'r', 'i', 'z', 'y'), min_snr=0.05, verbose=False): - """Inits Simulation_params with input observing conditions and image - parametrs.""" + """Initializes Simulation_params with input observing conditions and image + parameters.""" self.catalog_name = catalog_name self.max_number = max_number self.batch_size = batch_size diff --git a/docs/source/user_guide.rst b/docs/source/user_guide.rst index f415dd73b..6002b9586 100644 --- a/docs/source/user_guide.rst +++ b/docs/source/user_guide.rst @@ -10,10 +10,10 @@ The workflow of btk is shown here: :align: center -1. Set parameters (*config*): define parameters to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog, and the names of the observing bands are also specified here. -2. Load Catalog (*load_catalog*): Reads the input catalog file. This step includes an option to input a selection criteria. -3. Make blend catalog (*create_blend_generator*): Samples objects from the input catalog based on a user defined sampling function to create a catalog with parameters of each blend. This step outputs a generator that yields a new set of catalogs each time it is run with *next()*. This `notebook `_ shows several examples of user input sampling functions to create different blend catalogs. -4. Make observing conditions (*create_observing_generator*): Creates a class that contains information about the observing conditions such as PSF definition, noise level, etc. The default is to use the full-depth values corresponding to the survey named in config. However, a user can define a function to generate this. This `notebook `_ shows an example of a user input function to generate custom observing conditions. +1. Set parameter values (*config*): define parameter values to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog to draw objects from, and the names of the observing bands are also specified here. +2. Load Catalog (*load_catalog*): Reads the input catalog file. This step includes an option to input user-defined selection criteria. +3. Make blend catalog (*create_blend_generator*): Samples objects from the input catalog based on a user defined sampling function to create a catalog with parameters of each blend. This step outputs a generator that yields a new set of catalogs each time it is run with *next()*. This `notebook `_ shows several examples of user input sampling functions to create different blend catalogs. +4. Make observing conditions (*create_observing_generator*): Creates a class that contains information about the observing conditions such as PSF definition, noise level, etc. The default is to use the full-depth values corresponding to the survey named in *config*. However, a user can define a function to generate class with observing conditions of their choice. The user function can be such that it varies the observing conditions every time it's called. This `notebook `_ shows an example of a such a user input function that generates different observing conditions. Note that all blends drawn in a batch will be generated with the same observing conditions. 5. Draw blends (*create_blend_generator*): Simulates scene of overlapping objects, convolved by the PSF and with pixel noise (option set in *config*). Scene image is generated in each observing band. An "isolated" image of each object is also drawn without pixel contributions from other objects, in each band. 6. Detection/Deblending/Measure (*measure*): A user defined class to perform detection/deblending/measurement goes here. *btk* does not include any default algorithm; rather, it provides a framework for the user to run their choice of algorithm for the images generated in *create_blend_generator*. This `notebook `_ contains examples of running btk with `SEP `_ (SExtractor with python) , `LSST science pipeline `_ and `SCARLET `_. 7. Compute metrics (*metrics*): compares the true centroids, shapes, and flux values to those predicted by the user-provided *measure* algorithm. Currently, *metrics* assesses only detection performance by returning the number of objects correctly detected, the number that are undetected and the number of spurious detections. This `notebook `_ shows how this can be done. From a7b77c7bdf1b294a4c948bdc173d1e2cc34a252a Mon Sep 17 00:00:00 2001 From: sowmyakth Date: Mon, 15 Apr 2019 18:52:42 -0700 Subject: [PATCH 11/13] added link to config module page --- docs/source/user_guide.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/user_guide.rst b/docs/source/user_guide.rst index 6002b9586..00efcd89a 100644 --- a/docs/source/user_guide.rst +++ b/docs/source/user_guide.rst @@ -10,7 +10,7 @@ The workflow of btk is shown here: :align: center -1. Set parameter values (*config*): define parameter values to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog to draw objects from, and the names of the observing bands are also specified here. +1. Set parameter values (*config*): define parameter values to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog to draw objects from, and the names of the observing bands are also specified here. See `here `_ for more details. 2. Load Catalog (*load_catalog*): Reads the input catalog file. This step includes an option to input user-defined selection criteria. 3. Make blend catalog (*create_blend_generator*): Samples objects from the input catalog based on a user defined sampling function to create a catalog with parameters of each blend. This step outputs a generator that yields a new set of catalogs each time it is run with *next()*. This `notebook `_ shows several examples of user input sampling functions to create different blend catalogs. 4. Make observing conditions (*create_observing_generator*): Creates a class that contains information about the observing conditions such as PSF definition, noise level, etc. The default is to use the full-depth values corresponding to the survey named in *config*. However, a user can define a function to generate class with observing conditions of their choice. The user function can be such that it varies the observing conditions every time it's called. This `notebook `_ shows an example of a such a user input function that generates different observing conditions. Note that all blends drawn in a batch will be generated with the same observing conditions. From fa9b762f95b94f99ff7de08c40b588ecec101d8b Mon Sep 17 00:00:00 2001 From: sowmyakth Date: Mon, 15 Apr 2019 18:54:54 -0700 Subject: [PATCH 12/13] added link to config module page --- docs/source/user_guide.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/user_guide.rst b/docs/source/user_guide.rst index 00efcd89a..35d12d3a3 100644 --- a/docs/source/user_guide.rst +++ b/docs/source/user_guide.rst @@ -10,7 +10,7 @@ The workflow of btk is shown here: :align: center -1. Set parameter values (*config*): define parameter values to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog to draw objects from, and the names of the observing bands are also specified here. See `here `_ for more details. +1. Set parameter values (*config*): define parameter values to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog to draw objects from, and the names of the observing bands are also specified here. See `here `_ for more details. 2. Load Catalog (*load_catalog*): Reads the input catalog file. This step includes an option to input user-defined selection criteria. 3. Make blend catalog (*create_blend_generator*): Samples objects from the input catalog based on a user defined sampling function to create a catalog with parameters of each blend. This step outputs a generator that yields a new set of catalogs each time it is run with *next()*. This `notebook `_ shows several examples of user input sampling functions to create different blend catalogs. 4. Make observing conditions (*create_observing_generator*): Creates a class that contains information about the observing conditions such as PSF definition, noise level, etc. The default is to use the full-depth values corresponding to the survey named in *config*. However, a user can define a function to generate class with observing conditions of their choice. The user function can be such that it varies the observing conditions every time it's called. This `notebook `_ shows an example of a such a user input function that generates different observing conditions. Note that all blends drawn in a batch will be generated with the same observing conditions. From f1f91e92ed9512b8d893af6607f8fefeafbf2dbe Mon Sep 17 00:00:00 2001 From: sowmyakth Date: Mon, 15 Apr 2019 18:58:03 -0700 Subject: [PATCH 13/13] added link to config module page --- docs/source/user_guide.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/user_guide.rst b/docs/source/user_guide.rst index 35d12d3a3..fccc00587 100644 --- a/docs/source/user_guide.rst +++ b/docs/source/user_guide.rst @@ -10,7 +10,7 @@ The workflow of btk is shown here: :align: center -1. Set parameter values (*config*): define parameter values to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog to draw objects from, and the names of the observing bands are also specified here. See `here `_ for more details. +1. Set parameter values (*config*): define parameter values to create postage stamps, including size of stamp, number of objects per blend, and how many stamps are to be drawn in one batch -- i.e., the number of stamps btk will produce together in a singe batch. The observing survey name (e.g., LSST, DES), the name of the input catalog to draw objects from, and the names of the observing bands are also specified here. See `here `_ for more details. 2. Load Catalog (*load_catalog*): Reads the input catalog file. This step includes an option to input user-defined selection criteria. 3. Make blend catalog (*create_blend_generator*): Samples objects from the input catalog based on a user defined sampling function to create a catalog with parameters of each blend. This step outputs a generator that yields a new set of catalogs each time it is run with *next()*. This `notebook `_ shows several examples of user input sampling functions to create different blend catalogs. 4. Make observing conditions (*create_observing_generator*): Creates a class that contains information about the observing conditions such as PSF definition, noise level, etc. The default is to use the full-depth values corresponding to the survey named in *config*. However, a user can define a function to generate class with observing conditions of their choice. The user function can be such that it varies the observing conditions every time it's called. This `notebook `_ shows an example of a such a user input function that generates different observing conditions. Note that all blends drawn in a batch will be generated with the same observing conditions.