From d1f18373919946cd10beaa8b2db284d80b1ec3c8 Mon Sep 17 00:00:00 2001 From: Kyle Conroy Date: Tue, 29 Mar 2022 13:47:18 -0400 Subject: [PATCH] update sandbox notebook to call KosmosTrace on subtracted image --- .../jwst_boxcar/boxcar_extraction.ipynb | 92 +++---------------- 1 file changed, 15 insertions(+), 77 deletions(-) diff --git a/notebook_sandbox/jwst_boxcar/boxcar_extraction.ipynb b/notebook_sandbox/jwst_boxcar/boxcar_extraction.ipynb index 8f631913..b1de3ff9 100644 --- a/notebook_sandbox/jwst_boxcar/boxcar_extraction.ipynb +++ b/notebook_sandbox/jwst_boxcar/boxcar_extraction.ipynb @@ -44,7 +44,7 @@ "from jwst import datamodels\n", "\n", "from specreduce.extract import BoxcarExtract\n", - "from specreduce.tracing import FlatTrace\n", + "from specreduce.tracing import FlatTrace, KosmosTrace\n", "from specreduce.background import Background\n", "\n", "import os\n", @@ -379,67 +379,6 @@ "cell_type": "code", "execution_count": 12, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(34, 435)" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "bg.bkg_image(image).shape" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(34, 435)" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "bg.sub_image(image).shape" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(34, 435)" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# identical to calling bg.sub_image(image)\n", - "(image - bg).shape" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, "outputs": [ { "data": { @@ -447,7 +386,7 @@ "Text(0.5, 1.0, 'slit[0] slice')" ] }, - "execution_count": 15, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, @@ -472,7 +411,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -481,7 +420,7 @@ "Text(0.5, 1.0, 'slit[0] slice')" ] }, - "execution_count": 16, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, @@ -513,7 +452,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -522,7 +461,7 @@ "Text(0.5, 1.0, 'slit[0] slice')" ] }, - "execution_count": 17, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, @@ -550,17 +489,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Trace" + "## Trace\n", + "\n", + "Optional: we could now refine the initial flat trace by running an automated `KosmosTrace` on the subtracted image. This process could be iterated as necessary (recreating the subtracted image with the refined trace, etc)." ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ - "# optional: refine the trace on the background subtracted image (once PR#85 is merged)\n", - "#auto_trace = KosmosTrace(image-bg, ...)" + "auto_trace = KosmosTrace(image-bg, guess=ext_center)" ] }, { @@ -572,23 +512,22 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ - "# extract\n", "boxcar = BoxcarExtract()\n", - "spectrum = boxcar(image-bg, trace, width=ext_width)" + "spectrum = boxcar(image-bg, auto_trace, width=ext_width)" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 17, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -600,7 +539,6 @@ } ], "source": [ - "# plot \n", "f, ax = plt.subplots(figsize=(10, 6))\n", "ax.plot(spectrum.flux.value, 'k-')\n", "ax.set_title(\"Boxcar 1D extracted spectrum\")\n",