diff --git a/Mosaic.ipynb b/Mosaic.ipynb index ae3b834..3c9dc99 100644 --- a/Mosaic.ipynb +++ b/Mosaic.ipynb @@ -10,7 +10,7 @@ "\n", "Montage is a general toolkit for reprojecting and mosaicking astronomical images and generally you have to marshall the specific data you want to use carefully. But there are a few large-scale uniform surveys that cover a large enough portion of the sky to allow a simple location-based approach.\n", "\n", - "

In this notebook we will choose a region of the sky and dataset to mosaic, retrieve the archive data, reproject and background-correct the images, and finally build an output mosaic. You are free to modify any of the mosaic parameters but beware that as you go larger all of the steps will take longer (possibly much longer). If you do this for three different wavelenths, you can put them together in a full-color composite using our Sky Visualization notebook, which produced the image on the right.

\n", + "

In this notebook we will choose a region of the sky and dataset to mosaic, retrieve the archive data, reproject and background-correct the images, and finally build an output mosaic. You are free to modify any of the mosaic parameters but beware that as you go larger all of the steps will take longer (possibly much longer). If you do this for three different wavelenths, you can put them together in a full-color composite using our Sky Visualization notebook, which produced the image on the right.

\n", "\n", "As with many notebooks, this was derived from a longer script by breaking the processing up into sequential steps.\n", "These steps (cells) have to be run one in sequence. Wait for each cell to finish (watch for the step number in the brackets on the left to stop showing an asterisk) before starting the execution of next cell or run them all as a set.\n", @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -66,14 +66,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Startup folder: /Users/jcg/MontageDocs\n", + "Startup folder: /Users/jcg/FormalTest/MontageNotebooks\n", " Can't delete work tree; probably doesn't exist yet\n", "Work directory: Messier017\n" ] @@ -129,7 +129,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -181,7 +181,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -217,14 +217,14 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "mAdd: {'status': '0', 'time': 2.0}\n" + "mAdd: {'status': '0', 'time': 1.0}\n" ] } ], @@ -253,7 +253,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -270,7 +270,7 @@ "" ] }, - "execution_count": 8, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -304,7 +304,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -352,7 +352,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -395,7 +395,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "metadata": { "scrolled": true }, @@ -419,7 +419,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -429,7 +429,7 @@ "" ] }, - "execution_count": 12, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -442,9 +442,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Full Color and Interactive Display\n", + "## Full Color and Overlays\n", "\n", - "The above can be packaged up in a Python script with whatever minimum input and defaults you desired. Repeat the processing for three different wavelengths and you can combine them (and optionally overlays of various sorts) into a full-color image. Again, see our mViewer sky visualization notebook for details.\n" + "The above can be packaged up in a Python script with whatever minimum input and defaults you desired. Repeat the processing for three different wavelengths and you can combine them (and optionally overlays of various sorts) into a full-color image. See our mViewer sky visualization notebook for details.\n" ] }, { diff --git a/html/Mosaic.html b/html/Mosaic.html index 08f8b1f..eafa2b7 100644 --- a/html/Mosaic.html +++ b/html/Mosaic.html @@ -11777,7 +11777,7 @@

Building a Mosaic with Montage

Montage is a general toolkit for reprojecting and mosaicking astronomical images and generally you have to marshall the specific data you want to use carefully. But there are a few large-scale uniform surveys that cover a large enough portion of the sky to allow a simple location-based approach.

-

In this notebook we will choose a region of the sky and dataset to mosaic, retrieve the archive data, reproject and background-correct the images, and finally build an output mosaic. You are free to modify any of the mosaic parameters but beware that as you go larger all of the steps will take longer (possibly much longer). If you do this for three different wavelenths, you can put them together in a full-color composite using our Sky Visualization notebook, which produced the image on the right.

As with many notebooks, this was derived from a longer script by breaking the processing up into sequential steps. +

In this notebook we will choose a region of the sky and dataset to mosaic, retrieve the archive data, reproject and background-correct the images, and finally build an output mosaic. You are free to modify any of the mosaic parameters but beware that as you go larger all of the steps will take longer (possibly much longer). If you do this for three different wavelenths, you can put them together in a full-color composite using our Sky Visualization notebook, which produced the image on the right.

As with many notebooks, this was derived from a longer script by breaking the processing up into sequential steps. These steps (cells) have to be run one in sequence. Wait for each cell to finish (watch for the step number in the brackets on the left to stop showing an asterisk) before starting the execution of next cell or run them all as a set.

If you want to just see the code without all the explanation, check out this example.

Setup

The Montage Python package is a mixture of pure Python and Python binary extension code. It can be downloaded using pip install MontagePy

@@ -11788,7 +11788,7 @@

Setup

The M

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Working Environment
 

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# We create and move into subdirectories in this notebook 
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Working Environment
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Startup folder: /Users/jcg/MontageDocs
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Startup folder: /Users/jcg/FormalTest/MontageNotebooks
                 Can't delete work tree; probably doesn't exist yet
 Work directory: Messier017
 

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Retrieving Data from an Archive
 

 

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# Create the FITS header for the mosaic.
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Reprojecting the Images
 

 

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# Reproject the original images to the  frame of the 
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Coadding for a Mosaic
 

 

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# Coadd the projected images without backgound correction.
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Coadding for a Mosaic
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mAdd:    {'status': '0', 'time': 2.0}
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mAdd:    {'status': '0', 'time': 1.0}
 

 

 

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View the Image
 

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View the Image
 
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Background Matching
 

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# Determine the overlaps between images (for background modeling).
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Background Correcting and Re-Mo
 

 

 

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# Background correct the projected images.
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Final Image

 

 

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Final Image

 

 

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Image(filename='mosaic.png')
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Final Image

 
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Final Image

 

 

-
Full Color and Interactive Display
The above can be packaged up in a Python script with whatever minimum input and defaults you desired.  Repeat the processing for three different wavelengths and you can combine them (and optionally overlays of various sorts) into a full-color image.  Again, see our  mViewer sky visualization notebook for details.

+
Full Color and Overlays
The above can be packaged up in a Python script with whatever minimum input and defaults you desired.  Repeat the processing for three different wavelengths and you can combine them (and optionally overlays of various sorts) into a full-color image. See our  mViewer sky visualization notebook for details.