From af741aff3ccd3b23a458e7998778aec4c0694685 Mon Sep 17 00:00:00 2001 From: Jenna Ryon Date: Mon, 1 Jul 2019 20:42:18 -0400 Subject: [PATCH] Update zeropoints notebook links to Jahia and HDox versions, also remove output cells --- acs_zeropoints/acs_zeropoints.ipynb | 245 ++++------------------------ 1 file changed, 30 insertions(+), 215 deletions(-) diff --git a/acs_zeropoints/acs_zeropoints.ipynb b/acs_zeropoints/acs_zeropoints.ipynb index 22389a5..a94be18 100644 --- a/acs_zeropoints/acs_zeropoints.ipynb +++ b/acs_zeropoints/acs_zeropoints.ipynb @@ -21,7 +21,7 @@ "\n", "While we can use [PySynphot](http://pysynphot.readthedocs.io/en/latest/) to estimate the aperture corrections, it is best to measure these values from a selection of isolated point sources in your data. In the example below, we have used the PySynphot method. These examples give the same results as the [Zeropoint Calculator](https://acszeropoints.stsci.edu).\n", "\n", - "Aperture corrections from 0.5 and 1.0 arcseconds to \"infinity\" can be found on the [Aperture Corrections](http://www.stsci.edu/hst/acs/analysis/apcorr) webpage. These tables are a collection of information from several publications and include information for all ACS cameras (WFC, SBC, and HRC). For ACS, the \"infinite\" aperture corresponds to a radius of 5.5 arcseconds.\n", + "Aperture corrections from 0.5 and 1.0 arcseconds to \"infinity\" can be found on the [Aperture Corrections](http://www.stsci.edu/hst/instrumentation/acs/data-analysis/aperture-corrections) webpage. These tables are a collection of information from several publications and include information for all ACS cameras (WFC, SBC, and HRC). For ACS, the \"infinite\" aperture corresponds to a radius of 5.5 arcseconds.\n", "\n", "Recall that the appropriate `PHOTFLAM` and `PHOTPLAM` values for a given observation can be found in the SCI extention headers of every ACS image.\n", "\n", @@ -83,7 +83,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -108,20 +108,9 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "0" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "cmd_input = 'curl -O ftp://archive.stsci.edu/pub/hst/pysynphot/synphot1.tar.gz'\n", "os.system(cmd_input)" @@ -138,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -156,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -221,46 +210,9 @@ }, { "cell_type": "code", - "execution_count": 57, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "spec_bb = pyS.BlackBody(10000)\n", "plt.plot(spec_bb.wave, spec_bb.flux)\n", @@ -277,46 +229,9 @@ }, { "cell_type": "code", - "execution_count": 58, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "from synphot import SourceSpectrum\n", "from synphot.models import BlackBodyNorm1D\n", @@ -346,32 +261,9 @@ }, { "cell_type": "code", - "execution_count": 53, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 53, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", 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a32w4SDAU9rscEZkkFO68OZZ7srrhnJl09YV5aKMOrIpIhMIdaOtJjhEhR7NqVgkLqwr52Uv7/S5FRCYJhTvJ3S0DYGb81eqZbKrvYPNBDSYmIgp3QuFBekIDSd0tA/Des2aQm52h1ruIAAp32r0LmKYWJG/LHSLn6L97xWn89rWDdPX2+12OiPgspnA3syvNbIeZ1ZnZzaNs8xdmttXMtpjZz+NbZuK0eUMPJHvLHeCGc2cRDA3wwIaDfpciIj4bN9zNLBO4HbgKWApcb2ZLh22zAPgKcL5zbhnw+QTUmhDJOvTASM6YMYUzaqZy13P7GBzUFasi6SyWlvtqoM45t8c5FwJ+AVw7bJtPArc759oAnHNJMw7tsW6ZFGi5mxkfP382e5p7+NPOJr/LEREfxRLu04Hoyx/rvXXRFgILzew5M3vRzK6MV4GJ1paEI0KO5arl1VQV53Dnc3v9LkVEfBRLuI804Mrw//mzgAXAGuB64A4zm/qWFzK7yczWm9n6pqbJ0bJ8s1sm+VvuAIGsDD5y3mye3dXMziNdfpcjIj6JJdzrgZqoxzOA4ZdC1gO/dc71O+f2AjuIhP1xnHNrnXO1zrnaioqKk605rtqD/QSyMsjLzvS7lLi5fvVMcrIy+O/n9vldioj4JJZwfxlYYGZzzCwAXAc8OGyb3wAXA5hZOZFumj3xLDRR2noiQw+YJd+IkKMpLQjw3pXT+fWr9bT1hPwuR0R8MG64O+fCwGeBx4BtwH3OuS1m9g0zu8bb7DGgxcy2Ak8DX3bOtSSq6HiKjAiZGv3t0T52/hz6woPc/eIbfpciIj7IimUj59zDwMPD1t0SteyAL3i3pNJxNJQSZ8oMt2haEZcsruS/n9vLJy6YQ34gpm+1iKSItL9CNVVb7gCfXjOPtmA/v1insd5F0k3ah3uyDxo2ltrZpayeU8qPnt1DKDzodzkiMoHSOtydc7Qn8SxMsfj0mnk0dPTyGw1JIJJW0jrcu/rChAddynbLAFy0sIJlpxXzgz/tZkBDEoikjbQO9/aeoatTU7flbmZ8es189jT38Ojmw36XIyITJK3DPZUGDRvLlcunMa+igO/+Yada7yJpQuEOlBSkbssdIDPD+MLli9jV2M2DG9X3LpIO0jrc21Ns0LCxXLV8Gkuqi/nuH3bRP6AzZ0RSXVqHe7p0ywBkZBhfesdC3mgJcv8r9X6XIyIJlubh3o9ZZIq6dHDJ4kpWzpzKbU/uord/wO9yRCSB0jrc24MhinOzycxInUHDxmJmfOkdi2jo6OWedZpIWySVpXW4t6X4BUwjOX9+OefNLeN7T9XRqYm0RVJWWod7Kg89MJavvnMJrcEQtz9V53cpIpIgaR3ubcFQ2rXcAZZPn8IHV83gzuf2sq+5x+9yRCQB0jvce1J3RMjxfOkdi8jOzOBfHtnmdykikgBpHe7p2i0DUFmcy2cuns9jW47wwu6kmFdFRE5A2oZ7KDxIT2ggLbtlhtz49jlMn5rHN3+3VcMSiKSYtA33du8CpqkF6dlyB8jNzuTmqxaztaGTn7+k6fhEUknahnubN/RAOrfcAd61opoLFpRz66M7ONLZ63c5IhInaRzu6TP0wFjMjG+9ZzmhgUG+/tAWv8sRkThJ23A/1i2T5i13gFllBXzu0gU8/Pphntx2xO9yRCQO0jbch7plStO4zz3aJy+Yy8KqQm757RZ6+sJ+lyMipyimcDezK81sh5nVmdnNY2z3ATNzZlYbvxITo7VH3TLRAlkZ/PN7T+dg+1H+44mdfpcjIqdo3HA3s0zgduAqYClwvZktHWG7IuBzwEvxLjIR2oMhcrMzyM3O9LuUSaN2dik3nDOTO5/by7q9rX6XIyKnIJaW+2qgzjm3xzkXAn4BXDvCdt8EbgWS4pSL1p5+StVqf4v/ffUSakry+dIvN6p7RiSJxRLu04EDUY/rvXXHmNlKoMY597s41pZQ6Xx16lgKcrL4zgfP4EBbkH96WEMTiCSrWMJ9pMHOj13OaGYZwH8CXxz3hcxuMrP1Zra+qakp9ioToC0YSvm5U0/W6jmlfPKCufz8pf08vaPR73JE5CTEEu71QE3U4xnAoajHRcBy4I9mtg84F3hwpIOqzrm1zrla51xtRUXFyVcdB5Gx3NVyH80XLl/I4mlFfOm+jTTq4iaRpBNLuL8MLDCzOWYWAK4DHhx60jnX4Zwrd87Nds7NBl4ErnHOrU9IxXESGe5X4T6a3OxM/t/1KwmGBvj8va9p7BmRJDNuuDvnwsBngceAbcB9zrktZvYNM7sm0QUmwsCgo+NoPyU6x31MC6qK+Pq1y3h+dwu3P62JPUSSSVYsGznnHgYeHrbullG2XXPqZSVWx9F+nNO4MrH44KoZPF/XzHf/sJOzZ5dy3rwyv0sSkRik5RWqGlcmdmbGt957OnPKC/jMz1/lYPtRv0sSkRikZ7gPXZ2qbpmYFOZksfYjtfSHB/mbu9fT2z/gd0kiMo70DHcN93vC5lUU8t3rzmTLoU6+8uvXcU4HWEUmszQNd3XLnIxLl1TxhcsW8sCGg3z/T7v9LkdExhDTAdVUo26Zk/eZi+ezs7GbWx/dQU1JPu8+4zS/SxKREaRnuAf7yc40CgIaNOxEZWQY3/ngCo509PLF+zYybUouZ88u9bssERkmLbtlhsaVMRtpZAUZT05WJj/88CpmlOTxyZ+up66x2++SRGSYtAz31p6QRoQ8RSUFAe762GqyMowP//glDrQG/S5JRKKkZbi3B/s1vV4czCzL5+4bz6GnL8wNd7ykCbZFJpG0DPfWYEjT68XJkupifvLx1TR39/GhO146NsOViPgrLcNdY7nH18qZJdzx0VreaA3yVz96kebuPr9LEkl7aRfuzjlvuF91y8TT2+aV8+OP1rKvpYfr1r6oYYJFfJZ24d7ZG2Zg0KlbJgEuWFDBXR9bzaH2o/zFD1/gkMahEfFN2oV7i9dlUFaocE+Ec+eWcfeNq2npDvHBH7xAXWOX3yWJpKW0C/fm7sgBv/LCHJ8rSV2rZpVyz03n0hce5P3ff4GX97X6XZJI2km7cD/Wci9QuCfS8ulTeODTb6OsIMANd7zEo5sb/C5JJK2kXbg39wy13NUtk2g1pfnc/6m3sey0Yj71s1e5/ek6jSYpMkHSLtyHWu4aNGxilBYE+PknzuVdK07j24/t4G/v2cDRkMaDF0m0tBs4rKU7REl+NtmZafd3zTd5gUxuu+5MllYXc+tj29nb3OONTZPvd2kiKSvtEq65u48yHUydcGbGp9bM486Pns3+liDvvO3PPL7lsN9liaSstAv3lu4QZeqS8c3Fiyv53efezszSfG66+xW+/tAW+sLqphGJt7QL9+aePp0G6bNZZQXc/6nz+Ou3zea/n9vHB76v8+FF4i3twr2lO6QzZSaBnKxMvnbNMn744VXUtwW5+rY/c8ezexgY1Nk0IvEQU7ib2ZVmtsPM6szs5hGe/4KZbTWzTWb2pJnNin+ppy4UHqTjaL/63CeRK5ZN47G/u5ALF1Twrd9v4/q1L/JGS4/fZYkkvXHD3cwygduBq4ClwPVmtnTYZhuAWufcCuB+4NZ4FxoPQ8PRauiByaWyKJcffWQV3/ngGWxr6OQd//kMtz9dRyg86HdpIkkrlpb7aqDOObfHORcCfgFcG72Bc+5p59zQVDwvAjPiW2Z8NOvq1EnLzPjAqhk8/oULuWRxJd9+bAfvvO1Z1u3V0AUiJyOWcJ8OHIh6XO+tG82NwCOnUlSitHgt94oitdwnq+opeXz/Q6u4869rOdo/wF/88AX+7t7XNMKkyAmK5SKmkWaRHvGol5l9CKgFLhrl+ZuAmwBmzpwZY4nx09SllnuyuGRxFefNLed7T+/iR8/u5ZHNDdx0wVz+5qJ5FOSk3bV3IicslpZ7PVAT9XgGcGj4RmZ2GfBV4Brn3IhT8Tjn1jrnap1ztRUVFSdT7ykZmuNz2pTcCd+3nLi8QCZfvmIxT33xIt6xdBq3PVXHmu/8kbtffEP98SLjiCXcXwYWmNkcMwsA1wEPRm9gZiuBHxIJ9sb4lxkfRzp7mZKXTW52pt+lyAmYUZLPbdev5NeffhuzSvP5h99s5pJ//yP3vXyA8IBCXmQk44a7cy4MfBZ4DNgG3Oec22Jm3zCza7zNvg0UAr80s9fM7MFRXs5Xhzt6qSpWl0yyOmtmCb/8H+dx18fOprQgwN//ahOX/cefuO/lA2rJiwxjfg3BWltb69avXz+h+7z29ucozs3i7hvPmdD9Svw55/jDtkb+84mdbG3opKo4hxvfPofrV8+kKFfz40rqMrNXnHO1422XVleoHunoZVqx+ttTgZlx+dIqfv+5t/OTj69mbnkh//zwdt72r0/xLw9vY39LcPwXEUlhaXPawcCgo6m7jyqFe0oxMy5aWMFFCyvYeKCdtc/s4Y4/72Xts3tYs7CCD583i4sWVpKZMdJJXyKpK23Cvbm7j4FBR5XOlElZZ9RM5fYbzuJwRy8/X7efe9bt5+N3raemNI8bzpnF+86aTmWRvv+SHtIm3I+dBqmWe8qbNiWXL1y+kL+9ZD6PbznC3S/u418f2c6tj27n7QsqeN/K6bxjWRX5gbT58Zc0lDY/3Yc7FO7pJjszg3euqOadK6qpa+zmgQ31/GbDIT5/72sUBDK5Yvk03rdyBufOLSVLM3NJikmfcPda7lVTdCpkOppfWciXr1jMFy9fxLp9rTzw6kEefr2BX796kNKCAJcvqeKK5VWcP7+cnCxdByHJL23C/UBrkJysDCo03G9ay8gwzp1bxrlzy/j6tct4ansjj24+zMOvN3Dv+gMU5mSxZlEFVy6fxkULK3RapSStNAr3o8woycNMZ01IRG52JlefXs3Vp1fTFx7g+d0tPL7lMI9vOcLvNjWQlWGcNbOECxeWc+HCCpafNoUMnXUjSSJ9wr0tSE1pvt9lyCSVk5XJxYsquXhRJd96j+OVN9r4445GntnVxHce38l3Ht9JaUGACxaUc8GCCs6ZU6qfJ5nU0ifcW4OcNbPE7zIkCWRmGKvnlLJ6Til/f+Vimrv7+POuZp7Z2cQzu5r57WuRcfOmT807tt3qOaXMLS/Qf4YyaaRFuHcc7aezN0xNaZ7fpUgSKi/M4T0rp/OeldMZHHTsbOxi3d5WXtrbyrO7mnlgw0FvuwCrZpVwZk0JZ9RM4fTpU9RnL75Ji3A/0Bq5FL2mRP9Gy6nJyDAWTytm8bRiPnLebJxz7G3uORb2r+5v47EtRwAwg/kVhZxZM5UzaqayYsYUFlYVaVRSmRBpEe57myMTLs8qK/C5Ekk1ZsbcikLmVhRy3erIBDRtPSE21rez8UAHG+vbeWp7I798pR6IdPnMKS9gSXUxS6qLWFJdzNLqYiqLctSlI3GVFuG+q7GbDIO5FQp3SbySggBrFlWyZlElEBnBsr7tKJsPdrCtoZOtDV28+kYbD218c86b0oIA8ysLmVdRyLyKAuZVFjK/opDpU/N0ho6clLQI97rGLmaVFejfYfGFmVFTmk9NaT5XnV59bH3H0X62N3SytaGT7Q1d7G7q5pHNDbQH+49tk5OVwdyhwK8oZG5FATO91yorCKi1L6NKi3DfdaSb+ZWFfpchcpwpedmcM7eMc+aWHbe+tSfE7qZudjd2s7upm7rGbjbVd/D71xuInn4hP5BJTUkk6COBn3cs+GtK8skLqDGTzlI+3EPhQfY293DZ0iq/SxGJSWlBgNKCUs6eXXrc+t7+Afa3BjnQGmS/dzvQepQDrUGeq2vmaP/AcdtPzc9mWnEu1VNyqZ6aR3VxLtOm5FI9Jc+7z9Vk4yks5b+z2xo6CQ86Tp8+xe9SRE5JbnYmC6uKWFhV9JbnnHO09ISOhX9921EaOo5yuKOXho5eNtV30NITesvXFedmUVWcS3lhDhVFOVH3AcqLcqjwHpcVBDS4WpJJ+XB/7UA7AGfWTPW5EpHEMTPKCyPhPNrFer39AxzpjIT9UOg3dBylsbOP5u4+Nta309zVR09o4C1fawYl+QHKCwNMzQ9Qkp9NSX6AkoLIcmRd9HLkXpOk+Cflw33D/jaqinOo1iQdkuZyszOZVVYw7inBwVCY5q4QTd29NHVTc2lTAAAImklEQVSFaOruo7mrj6buPlq6+2gL9rOnqYe2YDvtwRDhwZHnYTaD4tzsY0FfnJdNcW4WRbnZFOdlUZybTVFu1H3e8Y8LAlk6U+gUpHS4O+d4YU8LtbNKdVaBSIzyA1nMLMtiZtn4F/055+juC9Me7KctGKK1J3RsuS3YT3vUuo5giAOtQbp6++k8GiY0MDjma5tBUU7kj0FRbhb5gUwKcrz7QBb5Od59IIuCnMxj99HPHVvvrctOo66llA73LYc6OdLZx8WLK/0uRSQlmZkXvtknPJBab/8AXb3hSNh79129YTqP9h+3vrO3n56+MMHQAD19YZq6+ugJhenpizzuC4/9RyJaIDOD3OwMcrMzyQtkkpuVeexx5OY95z3Oyc44tpyb9ebX5XhfN/RcICuDnKwM7z7ydYHMyDq/GpYxhbuZXQn8XyATuMM596/Dns8BfgqsAlqAv3TO7YtvqSfuNxsOkpVhXLyowu9SRGSYoUCtKDq1ORbCA4ME+wcI9g3QEwq/ee/9AQhG/SHoDoXp6x/kaGiA3vAAvf0D9PYPcrR/gPZg6Nhy79AtPEjoBP54jGQo5KP/ANxwziw+eeHcU3rd8Ywb7maWCdwOXA7UAy+b2YPOua1Rm90ItDnn5pvZdcC/AX+ZiIJj1R4Mcd/6A1yxbBplmqBDJGVlZWZQnJlBcYIGaRsYdPSFB94a/P2Dx5ZD4UH6vD8EfeEB+o57HFkXvU1lceIzKZaW+2qgzjm3B8DMfgFcC0SH+7XA17zl+4HvmZk550Y+0pJg7cEQn7/3NXpCA3zu0gV+lCAiKSIzw8gPZJEf8LuSExNLuE8HDkQ9rgfOGW0b51zYzDqAMqA5HkVG++OORr75u60Mushf1GM35xgcdIQHIwd4nHN86z2ns2jaW88JFhFJdbGE+0hHA4a3yGPZBjO7CbgJYObMmTHs+q2KcrNZPK2YjAwjK8PIMCMzAzIzMiL3ZkzJy+aq06tZUl18UvsQEUl2sYR7PVAT9XgGcGiUberNLAuYArQOfyHn3FpgLUBtbe1JddmsmlXCqlmaUUlEZCyxnPT5MrDAzOaYWQC4Dnhw2DYPAh/1lj8APOVXf7uIiMTQcvf60D8LPEbkVMg7nXNbzOwbwHrn3IPAj4G7zayOSIv9ukQWLSIiY4vpPHfn3MPAw8PW3RK13At8ML6liYjIyUqfa3FFRNKIwl1EJAUp3EVEUpDCXUQkBSncRURSkPl1OrqZNQFvnOSXl5OAoQ0mkOr3VzLXn8y1g+qPh1nOuXGHuvUt3E+Fma13ztX6XcfJUv3+Sub6k7l2UP0TSd0yIiIpSOEuIpKCkjXc1/pdwClS/f5K5vqTuXZQ/RMmKfvcRURkbMnachcRkTEkXbib2ZVmtsPM6szsZr/rGWJm+8zsdTN7zczWe+tKzewJM9vl3Zd4683MbvPewyYzOyvqdT7qbb/LzD462v7iUO+dZtZoZpuj1sWtXjNb5X0edd7XxnUK+FHq/5qZHfS+B6+Z2dVRz33Fq2WHmV0RtX7EnydviOuXvPd1rzfcdbxqrzGzp81sm5ltMbP/6a1Pis9/jPqT5fPPNbN1ZrbRq//rY+3TzHK8x3Xe87NP9n1NKOdc0tyIDDm8G5gLBICNwFK/6/Jq2weUD1t3K3Czt3wz8G/e8tXAI0RmsDoXeMlbXwrs8e5LvOWSBNV7IXAWsDkR9QLrgPO8r3kEuGoC6v8a8KURtl3q/azkAHO8n6HMsX6egPuA67zlHwCfimPt1cBZ3nIRsNOrMSk+/zHqT5bP34BCbzkbeMn7XEfcJ/Bp4Afe8nXAvSf7vibylmwt92OTdTvnQsDQZN2T1bXAT7zlnwDviVr/UxfxIjDVzKqBK4AnnHOtzrk24AngykQU5px7hrfOlhWXer3nip1zL7jIb8FPo14rkfWP5lrgF865PufcXqCOyM/SiD9PXiv3EiKTvcPxn0U8am9wzr3qLXcB24jMQ5wUn/8Y9Y9msn3+zjnX7T3M9m5ujH1Gf1/uBy71ajyh9xWv+mOVbOE+0mTdY/1QTSQHPG5mr1hkrliAKudcA0R+IYBKb/1o78Pv9xeveqd7y8PXT4TPel0Xdw51a3Di9ZcB7c658LD1cef9i7+SSOsx6T7/YfVDknz+ZpZpZq8BjUT+KO4eY5/H6vSe7/BqnKy/x0DyhXtME3H75Hzn3FnAVcBnzOzCMbYd7X1M1vd3ovX69T6+D8wDzgQagH/31k/K+s2sEPgV8HnnXOdYm45Sz2SrP2k+f+fcgHPuTCJzQq8Gloyxz0lXfyySLdxjmazbF865Q959I/AAkR+YI96/yHj3jd7mo70Pv99fvOqt95aHr08o59wR75d2EPgRke8B49Q50vpmIl0fWcPWx42ZZRMJxp85537trU6az3+k+pPp8x/inGsH/kikz320fR6r03t+CpEuwcn6exwx0Z38p3IjMi3gHiIHL4YOVCybBHUVAEVRy88T6Sv/NscfILvVW34nxx8gW+etLwX2Ejk4VuItlyaw7tkcf0AybvUSmVj9XN48oHf1BNRfHbX8d0T6QwGWcfyBrz1EDnqN+vME/JLjD659Oo51G5F+8O8OW58Un/8Y9SfL518BTPWW84BngXeNtk/gMxx/QPW+k31fE3mb0J3F6RtzNZGj87uBr/pdj1fTXO8buBHYMlQXkX65J4Fd3v3QL54Bt3vv4XWgNuq1Pk7kwEwd8LEE1nwPkX+d+4m0NG6MZ71ALbDZ+5rv4V0wl+D67/bq2wQ8OCxsvurVsoOoM0dG+3nyvqfrvPf1SyAnjrW/nci/6ZuA17zb1cny+Y9Rf7J8/iuADV6dm4FbxtonkOs9rvOen3uy72sib7pCVUQkBSVbn7uIiMRA4S4ikoIU7iIiKUjhLiKSghTuIiIpSOEuIpKCFO4iIilI4S4ikoL+PzMH12iMfaMzAAAAAElFTkSuQmCC\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "\n", "\n", @@ -421,63 +290,9 @@ }, { "cell_type": "code", - "execution_count": 51, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Help on method renorm in module pysynphot.spectrum:\n", - "\n", - "renorm(RNval, RNUnits, band, force=False) method of pysynphot.spectrum.BlackBody instance\n", - " :ref:`Renormalize ` the spectrum to the\n", - " specified value, unit, and bandpass.\n", - " \n", - " This wraps :func:`~pysynphot.renorm.StdRenorm` for convenience.\n", - " Basically, the spectrum is multiplied by a numeric factor so that\n", - " the total integrated flux will be the given value in the given\n", - " unit in the given bandpass.\n", - " \n", - " When ``force=False``, if spectrum is not fully defined within the\n", - " given bandpass, but the overlap is at least 99%, a warning is\n", - " printed to screen and ``self.warnings['PartialRenorm']`` is set\n", - " to `True`.\n", - " \n", - " Parameters\n", - " ----------\n", - " RNval : number\n", - " Flux value for renormalization.\n", - " \n", - " RNUnits : str\n", - " Unit name, as accepted by `~pysynphot.units.Units`, for ``RNval``.\n", - " \n", - " band : `SpectralElement`\n", - " Bandpass that ``RNval`` is based on.\n", - " \n", - " force : bool\n", - " Force renormalization regardless of overlap status with given\n", - " bandpass. If `True`, overlap check is skipped. Default is `False`.\n", - " \n", - " Returns\n", - " -------\n", - " newsp : `~pysynphot.spectrum.CompositeSourceSpectrum`\n", - " Renormalized spectrum.\n", - " \n", - " Raises\n", - " ------\n", - " ValueError\n", - " Integrated flux is zero, negative, NaN, or infinite.\n", - " \n", - " pysynphot.exceptions.DisjointError\n", - " Spectrum and bandpass are disjoint.\n", - " \n", - " pysynphot.exceptions.OverlapError\n", - " Spectrum and bandpass do not fully overlap.\n", - "\n" - ] - } - ], + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "help(spec_bb.renorm)" ] @@ -700,7 +515,7 @@ "source": [ "For more help...\n", "\n", - "See the [ACS Data Handbook](http://www.stsci.edu/hst/acs/documents/handbooks/currentDHB/acs_cover.html) section [5.1.3](http://www.stsci.edu/hst/acs/documents/handbooks/currentDHB/acs_Ch52.html#94716) for more information." + "See the Section 5.1.3 of the [ACS Data Handbook](http://www.stsci.edu/files/live/sites/www/files/home/hst/instrumentation/acs/documentation/other-documents/_documents/acs_dhb.pdf) for more information." ] }, { @@ -711,13 +526,13 @@ "\n", "***\n", "\n", - "* [Avila, R. J., Chiaberge, M. 2016, ACS ISR 2016-05](http://www.stsci.edu/hst/acs/documents/isrs/isr1605.pdf)\n", - "* [Bohlin, R. C. 2011, ACS ISR 2011-02](http://www.stsci.edu/hst/acs/documents/isrs/isr1102.pdf)\n", - "* [Bohlin, R. C. 2012, ACS ISR 2012-01](http://www.stsci.edu/hst/acs/documents/isrs/isr1201.pdf)\n", - "* [Bohlin, R. C. 2016, ACS ISR 2016-03](http://www.stsci.edu/hst/acs/analysis/zeropoints/hst/acs/documents/isrs/1603.html)\n", + "* [Avila, R. J., Chiaberge, M. 2016, ACS ISR 2016-05](http://www.stsci.edu/files/live/sites/www/files/home/hst/instrumentation/acs/documentation/instrument-science-reports-isrs/_documents/isr1605.pdf)\n", + "* [Bohlin, R. C. 2011, ACS ISR 2011-02](http://www.stsci.edu/files/live/sites/www/files/home/hst/instrumentation/acs/documentation/instrument-science-reports-isrs/_documents/isr1102.pdf)\n", + "* [Bohlin, R. C. 2012, ACS ISR 2012-01](http://www.stsci.edu/files/live/sites/www/files/home/hst/instrumentation/acs/documentation/instrument-science-reports-isrs/_documents/isr1201.pdf)\n", + "* [Bohlin, R. C. 2016, AJ, 152, 60](https://ui.adsabs.harvard.edu/abs/2016AJ....152...60B/abstract)\n", "* [Bohlin, R. C., Mack, J., & Ubeda L. 2011, ACS ISR 2011-03](http://www.stsci.edu/hst/acs/documents/isrs/isr1103.pdf)\n", - "* [Tran, D. et al. 2002, \"2002 HST Calibration Workshop\"](http://www.stsci.edu/hst/HST_overview/documents/calworkshop/workshop2002/CW2002_Papers/tran.pdf)\n", - "* [Sirianni, M. et al. 2005, PASP, 117, 1049S](http://adsabs.harvard.edu/abs/2005PASP..117.1049S)" + "* [Tran, D. et al. 2002, \"2002 HST Calibration Workshop\"](http://www.stsci.edu/files/live/sites/www/files/home/hst/instrumentation/acs/data-analysis/zeropoints/_documents/tran.pdf)\n", + "* [Sirianni, M. et al. 2005, PASP, 117, 1049S](https://ui.adsabs.harvard.edu/abs/2005PASP..117.1049S/abstract)" ] } ], @@ -737,7 +552,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.6" + "version": "3.6.7" } }, "nbformat": 4,