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@saimn
Last active May 5, 2018 03:10
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Hacking on fitting models in 3D\n",
"\n",
"PyAstro 2018"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Numpy 1.14.3\n",
"Astropy 3.1.dev21816\n",
"MPDAF 3.0.dev2675\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/simon/.pyenv/versions/3.6.3/lib/python3.6/site-packages/matplotlib/cbook/deprecation.py:107: MatplotlibDeprecationWarning: The mpl_toolkits.axes_grid module was deprecated in version 2.1. Use mpl_toolkits.axes_grid1 and mpl_toolkits.axisartist provies the same functionality instead.\n",
" warnings.warn(message, mplDeprecation, stacklevel=1)\n"
]
}
],
"source": [
"%matplotlib inline\n",
"%mpdaf\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from astropy.modeling import models, fitting\n",
"from muse_analysis.plotutils import show_images_grid\n",
"\n",
"import warnings\n",
"warnings.simplefilter('ignore', UserWarning)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Using a small cube with a star in the middle. This cube is already rebinned, but I rebin again to have fewer slices and fit faster (this is really for the experiment)."
]
},
{
"cell_type": "code",
"execution_count": 116,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<Cube(shape=(87, 50, 50), unit='', dtype='None')>\n"
]
},
{
"data": {
"text/plain": [
"<Cube(shape=(17, 50, 50), unit='', dtype='float64')>"
]
},
"execution_count": 116,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"c = Cube('star_rebin.fits')\n",
"print(c)\n",
"c = c.rebin((5, 1, 1))\n",
"c"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Have a quicklook at the white-light image, and the star profile."
]
},
{
"cell_type": "code",
"execution_count": 117,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1080x288 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"im = c.mean(axis=0)\n",
"\n",
"fig, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(15, 4))\n",
"im.plot(ax=ax1, colorbar='v')\n",
"im.plot(ax=ax2, colorbar='v', zscale=True)\n",
"ax3.plot(im.data[im.shape[0]//2]);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fit just one image"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<CompoundModel0(amplitude_0=0., amplitude_1=1659.26047148, x_0_1=25., y_0_1=25., gamma_1=3., alpha_1=2.5)>"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"yy, xx = np.mgrid[:im.shape[0], :im.shape[1]]\n",
"x_0, y_0 = np.array(im.shape) / 2\n",
"\n",
"data = im.data.filled(0)\n",
"\n",
"model = models.Const2D(amplitude=0) + models.Moffat2D(amplitude=data.max(), x_0=x_0, y_0=y_0, gamma=3, alpha=2.5)\n",
"model"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<CompoundModel0(amplitude_0=0.97230683, amplitude_1=1701.52724239, x_0_1=24.83433759, y_0_1=24.7628894, gamma_1=2.76389006, alpha_1=2.26009349)>"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fitter = fitting.LevMarLSQFitter()\n",
"fit = fitter(model, xx, yy, data, maxiter=500)\n",
"fit"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 864x288 with 6 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"show_images_grid([data, fit(xx, yy), data - fit(xx, yy)], figsize=(4, 4), titles=('data', 'fit', 'diff'));"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fit all slices"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"shape = c.shape[1:]\n",
"yy, xx = np.mgrid[:shape[0], :shape[1]]\n",
"x_0, y_0 = np.array(shape) / 2\n",
"\n",
"fitter = fitting.LevMarLSQFitter()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"fitres = []\n",
"for im in c:\n",
" data = im.data.filled(0)\n",
" model = models.Const2D(amplitude=0) + models.Moffat2D(amplitude=data.max(), x_0=x_0, y_0=y_0, gamma=3, alpha=2.5)\n",
" #model = models.Moffat2D(amplitude=data.max(), x_0=x_0, y_0=y_0, gamma=3, alpha=2.5)\n",
" fit = fitter(model, xx, yy, data, maxiter=500)\n",
" fitres.append(fit)"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<CompoundModel1(amplitude_0=0.93096377, amplitude_1=1753.54048669, x_0_1=24.86784414, y_0_1=24.69442081, gamma_1=3.37249207, alpha_1=2.44346401)>,\n",
" <CompoundModel2(amplitude_0=0.94088614, amplitude_1=2381.21067331, x_0_1=24.8605224, y_0_1=24.71052276, gamma_1=3.14197958, alpha_1=2.34593096)>,\n",
" <CompoundModel3(amplitude_0=0.99910091, amplitude_1=2405.97682473, x_0_1=24.85101529, y_0_1=24.72605836, gamma_1=3.00064027, alpha_1=2.29750943)>,\n",
" <CompoundModel4(amplitude_0=0.9985743, amplitude_1=2296.42235581, x_0_1=24.83033584, y_0_1=24.73900801, gamma_1=2.9577778, alpha_1=2.31246834)>,\n",
" <CompoundModel5(amplitude_0=1.05923325, amplitude_1=2276.12150493, x_0_1=24.82712772, y_0_1=24.75604221, gamma_1=2.87166054, alpha_1=2.3065077)>,\n",
" <CompoundModel6(amplitude_0=1.19331164, amplitude_1=2237.22968792, x_0_1=24.83295207, y_0_1=24.76532322, gamma_1=2.83668768, alpha_1=2.31649026)>,\n",
" <CompoundModel7(amplitude_0=1.1491433, amplitude_1=1960.35679928, x_0_1=24.84135268, y_0_1=24.7717288, gamma_1=2.77586169, alpha_1=2.30561706)>,\n",
" <CompoundModel8(amplitude_0=1.3025374, amplitude_1=2186.66462704, x_0_1=24.85141033, y_0_1=24.77830428, gamma_1=2.7161867, alpha_1=2.29392399)>,\n",
" <CompoundModel9(amplitude_0=1.12391398, amplitude_1=2130.82205439, x_0_1=24.84952093, y_0_1=24.78244555, gamma_1=2.67434147, alpha_1=2.29515519)>,\n",
" <CompoundModel10(amplitude_0=1.24113171, amplitude_1=1918.21556396, x_0_1=24.83525528, y_0_1=24.78756503, gamma_1=2.65920029, alpha_1=2.31376351)>,\n",
" <CompoundModel11(amplitude_0=1.01276245, amplitude_1=1499.84481538, x_0_1=24.81346945, y_0_1=24.79050741, gamma_1=2.62284605, alpha_1=2.3119009)>,\n",
" <CompoundModel12(amplitude_0=1.24795129, amplitude_1=1459.15469042, x_0_1=24.79411726, y_0_1=24.79102458, gamma_1=2.53773987, alpha_1=2.26778444)>,\n",
" <CompoundModel13(amplitude_0=0.70841535, amplitude_1=1236.96752934, x_0_1=24.81438909, y_0_1=24.79636028, gamma_1=2.48940807, alpha_1=2.2543994)>,\n",
" <CompoundModel14(amplitude_0=1.15668833, amplitude_1=1040.16038579, x_0_1=24.82262197, y_0_1=24.80572148, gamma_1=2.57327767, alpha_1=2.34711145)>,\n",
" <CompoundModel15(amplitude_0=0.84315658, amplitude_1=887.56855862, x_0_1=24.79926474, y_0_1=24.80294276, gamma_1=2.55455571, alpha_1=2.33834988)>,\n",
" <CompoundModel16(amplitude_0=1.05909101, amplitude_1=746.18653567, x_0_1=24.79276317, y_0_1=24.80592023, gamma_1=2.44411773, alpha_1=2.25607786)>,\n",
" <CompoundModel17(amplitude_0=0.48960819, amplitude_1=567.7169361, x_0_1=24.80550165, y_0_1=24.80729538, gamma_1=2.45507796, alpha_1=2.2690726)>]"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fitres"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fit all slices - with Nadia's branch"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"n_models = c.shape[0]\n",
"\n",
"shape = c.shape[1:]\n",
"yy, xx = np.mgrid[:shape[0], :shape[1]]\n",
"x_0, y_0 = np.array(shape) / 2\n",
"\n",
"fitter = fitting.LevMarLSQFitter()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"data = c.data.filled(0)\n",
"amplitude = [d.max() for d in data]"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(17, 50, 50)"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.shape"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(25.0, 25.0)"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x_0, y_0"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/simon/dev/astropy/astropy/modeling/functional_models.py:2340: RuntimeWarning: overflow encountered in multiply\n",
" return amplitude * (1 + rr_gg) ** (-alpha)\n"
]
}
],
"source": [
"#model = (models.Const2D(amplitude=[0]*n_models, n_models=n_models) + \n",
"# models.Moffat2D(amplitude=amplitude, x_0=[x_0]*n_models, y_0=[y_0]*n_models, gamma=[3]*n_models, alpha=[2.5]*n_models, n_models=n_models))\n",
"\n",
"model = models.Moffat2D(amplitude=amplitude, \n",
" x_0=[x_0]*n_models, \n",
" y_0=[y_0]*n_models, \n",
" gamma=[3]*n_models, \n",
" alpha=[2.5]*n_models, \n",
" n_models=n_models)\n",
"\n",
"fit = fitter(model, xx, yy, data, maxiter=500, estimate_jacobian=True)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Moffat2D(amplitude=[3717.79241318, 1671.36913366, 2414.52069863, 1224.94367863, 3091.7904829 , 1732.25959284, 1291.0823918 , 1185.27552187, 2267.95675725, 1085.53751763, 675.25733686, 203.25266295, 565.3968797 , 378.82329221, 467.61150088, 275.2585092 , 187.70317083], x_0=[24.83343602, 24.83870348, 24.82822186, 24.8101219 , 24.79718616, 24.7982329 , 24.8009886 , 24.80804346, 24.80557622, 24.79588313, 24.78119714, 24.76646373, 24.77871079, 24.78272335, 24.76224003, 24.76123149, 24.77289239], y_0=[ 3.84954187, 3.689346 , 4.95934945, 5.28841435, 7.14601465, 7.64120329, 8.45861851, 9.25155733, 10.87734963, 11.36665531, 12.09647781, 12.3893995 , 14.08571711, 14.87540279, 11.67100771, 16.85036549, 17.80077081], gamma=[2.77111357, 1.9110698 , 2.09361343, 1.55171744, 2.256866 , 1.81538784, 1.63702508, 1.45504309, 2.05380951, 1.64471887, 1.42786186, 1.75609696, 1.40686767, 1.2228266 , 1.60724291, 1.12867373, 1.18058757], alpha=[2.99029352, 1.92150425, 2.27872339, 1.61070762, 2.65152441, 2.03263498, 1.83876834, 1.6366475 , 2.48043002, 1.85423209, 1.59204193, 1.37238598, 1.62519056, 1.36088985, 1.83507534, 1.29427221, 1.32381693], n_models=17)>"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fit"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1440x216 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axes = plt.subplots(1, 5, figsize=(5*4, 3))\n",
"for ax, attr in zip(axes.flat, ('amplitude', 'x_0', 'y_0', 'alpha', 'gamma')):\n",
" ax.plot(getattr(fit, attr), label=\"nden's branch\")\n",
" ax.plot([getattr(f[1], attr) for f in fitres], label='individual fits')\n",
" ax.set_title(attr)\n",
"\n",
"axes.flat[0].legend();\n",
"#axes.flat[-1].axis('off');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Fit all slices - remove background as Compound model does not work"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"c.mask_ellipse((c.shape[1]/2, c.shape[1]/2), 4, 0, unit_center=None)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7fde0ff88ef0>"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"c[0].plot(zscale=True)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [],
"source": [
"bkg = np.array([im.background()[0] for im in c])\n",
"c.unmask()\n",
"\n",
"c_bkgsub = c - bkg[:, None, None]"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [],
"source": [
"n_models = c.shape[0]\n",
"shape = c.shape[1:]\n",
"yy, xx = np.mgrid[:shape[0], :shape[1]]\n",
"x_0, y_0 = np.array(shape) / 2\n",
"\n",
"fitter = fitting.LevMarLSQFitter()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"data = c_bkgsub.data.filled(0)\n",
"amplitude = [d.max() for d in data]"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(17, 50, 50)"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.shape"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(25.0, 25.0)"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"x_0, y_0"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/simon/dev/astropy/astropy/modeling/functional_models.py:2340: RuntimeWarning: overflow encountered in multiply\n",
" return amplitude * (1 + rr_gg) ** (-alpha)\n"
]
}
],
"source": [
"#model = (models.Const2D(amplitude=[0]*n_models, n_models=n_models) + \n",
"# models.Moffat2D(amplitude=amplitude, x_0=[x_0]*n_models, y_0=[y_0]*n_models, gamma=[3]*n_models, alpha=[2.5]*n_models, n_models=n_models))\n",
"\n",
"model = models.Moffat2D(amplitude=amplitude, x_0=[x_0]*n_models, y_0=[y_0]*n_models, gamma=[3]*n_models, alpha=[2.5]*n_models, n_models=n_models)\n",
"\n",
"fit = fitter(model, xx, yy, data, maxiter=500, estimate_jacobian=True)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Moffat2D(amplitude=[ 3820.48982817, 1511.56632015, 2611.83737438, 1308.5733207 , 3066.38266505, 2762.47521204, 2118.61695753, 44457.70819716, 2420.47148787, 1683.84690849, 721.13992839, 790.02658898, 830.19695328, 510.12561374, 926.18989327, 328.69381368, 242.70026524], x_0=[24.83381391, 24.83938231, 24.82848117, 24.81013738, 24.7974371 , 24.79785479, 24.80042775, 42.14663418, 24.80590784, 24.79573389, 24.78144488, 24.76533693, 24.77703435, 24.78210668, 24.76191661, 24.76104204, 24.77222358], y_0=[ 3.82319018, 3.55276196, 4.99264011, 5.34990747, 7.11122462, 8.04352526, 8.87567007, -207.11895477, 10.90507897, 11.66504228, 12.16444255, 13.20752294, 14.44816817, 15.17872614, 11.15896396, 17.08496893, 18.01877236], gamma=[ 2.78021017, 1.81438422, 2.13271461, 1.60865249, 2.2339572 , 2.2226557 , 2.0186312 , 17.67850764, 2.1006252 , 1.86293117, 1.52845365, 1.47975001, 1.7270391 , 1.53499674, 2.09314359, 1.45750404, 1.34616175], alpha=[3.04635254, 1.82129858, 2.36633372, 1.69632627, 2.6498674 , 2.63283974, 2.40985023, 1.58645008, 2.58298188, 2.25940467, 1.72908802, 1.75961617, 2.09780075, 1.78142181, 2.64719891, 1.69660967, 1.57952722], n_models=17)>"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"fit"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1440x216 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axes = plt.subplots(1, 5, figsize=(5*4, 3))\n",
"for ax, attr in zip(axes.flat, ('amplitude', 'x_0', 'y_0', 'alpha', 'gamma')):\n",
" ax.plot(getattr(fit, attr), label=\"nden's branch\")\n",
" ax.plot([getattr(f[1], attr) for f in fitres], label='individual fits')\n",
" ax.set_title(attr)\n",
"\n",
"axes.flat[0].legend();\n",
"#axes.flat[-1].axis('off');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 3D model, now with `scipy.optimize`\n",
"\n",
"From https://gist.github.com/tspriggs/989b57a495ab2831a021fb376e18fabc for another attempt."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Starts simple, 2D case"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"from scipy.optimize import least_squares"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"def moffat(x, y, bkg, amplitude, x_0, y_0, gamma, alpha):\n",
" rr_gg = ((x - x_0) ** 2 + (y - y_0) ** 2) / gamma ** 2\n",
" return bkg + amplitude * (1 + rr_gg) ** (-alpha)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [],
"source": [
"def func(params, x, y, data):\n",
" # params: \n",
" model = moffat(x, y, *params)\n",
" return np.ravel(model - data)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"im = c.mean(axis=0)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {},
"outputs": [],
"source": [
"data = im.data.filled(0)\n",
"res = least_squares(func, (0, data.max(), shape[0]/2, shape[1]/2, 2.5, 3), args=(xx, yy, data))"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([9.72322450e-01, 1.70152561e+03, 2.48342990e+01, 2.47629226e+01,\n",
" 2.76390040e+00, 2.26010337e+00])"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res.x"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 648x216 with 6 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"resim = moffat(xx, yy, *res.x)\n",
"show_images_grid([data, resim, data - resim]);"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### And now 3D, with broadcasting"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [],
"source": [
"def moffat(x, y, x_0, y_0, bkg, amplitude, gamma, alpha):\n",
" rr_gg = ((x - x_0) ** 2 + (y - y_0) ** 2) / gamma ** 2\n",
" return bkg + amplitude * (1 + rr_gg) ** (-alpha)"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {},
"outputs": [],
"source": [
"yy, xx = np.mgrid[:c.shape[1], :c.shape[2]]\n",
"\n",
"data = c.data.filled(0)\n",
"\n",
"bkg = np.zeros(n_models)\n",
"amplitude = np.array([d.max() for d in data])\n",
"gamma = np.zeros(n_models) + 3\n",
"alpha = np.zeros(n_models) + 2.5\n",
"\n",
"p0 = np.concatenate([[x_0]*n_models, [y_0]*n_models, bkg, amplitude, gamma, alpha]).tolist()"
]
},
{
"cell_type": "code",
"execution_count": 120,
"metadata": {},
"outputs": [],
"source": [
"def func(params, x, y, data):\n",
" x_0, y_0, bkg, amplitude, gamma, alpha = np.array(params).reshape(6, -1)\n",
" model = moffat(xx, yy, x_0[:, None, None], y_0[:, None, None], bkg[:, None, None], \n",
" amplitude[:, None, None], gamma[:, None, None], alpha[:, None, None])\n",
" return np.ravel(model - data)"
]
},
{
"cell_type": "code",
"execution_count": 109,
"metadata": {},
"outputs": [],
"source": [
"res = least_squares(func, p0, args=(xx, yy, data))"
]
},
{
"cell_type": "code",
"execution_count": 121,
"metadata": {},
"outputs": [],
"source": [
"x_0, y_0, bkg, amplitude, gamma, alpha = np.array(res.x).reshape(6, -1)"
]
},
{
"cell_type": "code",
"execution_count": 113,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 1440x216 with 5 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axes = plt.subplots(1, 5, figsize=(5*4, 3))\n",
"for ax, attr in zip(axes.flat, ('amplitude', 'alpha', 'gamma', 'x_0', 'y_0')):\n",
" ax.plot([getattr(f[1], attr) for f in fitres], label='individual fits')\n",
" ax.set_title(attr)\n",
"for ax, attr in zip(axes.flat, (amplitude, alpha, gamma, x_0, y_0)):\n",
" ax.plot(attr, label='3D fit')\n",
"#axes[3].hlines(x_0, 0, 17)\n",
"#axes[4].hlines(y_0, 0, 17)\n",
"\n",
"axes.flat[0].legend();\n",
"#axes.flat[-1].axis('off');"
]
},
{
"cell_type": "code",
"execution_count": 119,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
" active_mask: array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
" 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])\n",
" cost: 323435.16341175715\n",
" fun: array([0.30988161, 0.26214352, 0.41188866, ..., 0.42218857, 0.31748722,\n",
" 0.34453365])\n",
" grad: array([-6.47960657e-02, -4.84077285e-02, -2.80831293e-02, -1.37173779e-02,\n",
" -3.15968962e-03, -7.44750929e-03, -4.05704037e-02, -1.48264358e-01,\n",
" -1.76831108e-01, -4.15386009e-02, 5.36898079e-02, 1.01356821e-01,\n",
" 4.96981585e-02, -4.44686671e-02, 1.48662809e-01, 2.51650472e-01,\n",
" 1.17496002e-01, -5.64704951e-02, -5.01200355e-02, -3.00616669e-02,\n",
" 6.12141782e-04, 1.99024028e-02, 3.24702770e-03, -4.61456711e-02,\n",
" -1.99334968e-01, -4.47523242e-01, -5.11125266e-01, -3.47336656e-01,\n",
" -3.43636279e-01, -5.81193343e-01, -1.04704949e+00, -4.88050184e-01,\n",
" -2.78206499e-01, -3.43727567e-01, 2.88094398e-06, 6.69572557e-08,\n",
" 7.63990471e-09, 1.25122028e-08, 1.95384143e-04, -9.67044083e-04,\n",
" -3.25934859e-04, 5.97222330e-04, -3.02281099e-04, -7.36164019e-05,\n",
" -4.84512685e-05, -8.97602045e-04, -9.52900763e-08, 2.44749111e-06,\n",
" 5.47017152e-07, -1.01214850e-04, 2.44826026e-06, 2.47642902e-07,\n",
" -3.31903617e-07, -6.96452071e-07, -5.53544070e-07, 5.26512858e-07,\n",
" 5.69500166e-07, -8.14932299e-07, 2.67675944e-08, 6.14672544e-07,\n",
" 6.30990940e-07, -3.28174471e-07, -6.98469650e-07, 4.48608136e-07,\n",
" -8.73866020e-08, -3.56384057e-07, -3.19141291e-08, 2.55619421e-07,\n",
" 1.14514942e-01, 3.19017470e-02, 1.82997191e-02, 2.15349945e-02,\n",
" 2.07980208e-02, 9.91025991e-03, -1.22470803e-02, -5.51694827e-02,\n",
" -1.31652816e-01, -1.53312300e-01, -8.28608527e-02, -6.93785849e-02,\n",
" -1.71014627e-01, -3.21853210e-01, -1.02661570e-01, -9.57572557e-02,\n",
" -8.26541965e-02, -1.29480709e-01, -3.40450069e-02, -1.78803114e-02,\n",
" -2.27199738e-02, -1.91528248e-02, -9.54058007e-03, 6.62968789e-03,\n",
" 4.11791127e-02, 9.29961522e-02, 9.81937986e-02, 4.37577517e-02,\n",
" 2.80135465e-02, 9.56586194e-02, 1.88708950e-01, 4.76956761e-02,\n",
" 4.61082360e-02, 3.20899150e-02])\n",
" jac: array([[-0.00180717, 0. , 0. , ..., 0. ,\n",
" 0. , 0. ],\n",
" [-0.00199139, 0. , 0. , ..., 0. ,\n",
" 0. , 0. ],\n",
" [-0.00218999, 0. , 0. , ..., 0. ,\n",
" 0. , 0. ],\n",
" ...,\n",
" [ 0. , 0. , 0. , ..., 0. ,\n",
" 0. , -0.02253619],\n",
" [ 0. , 0. , 0. , ..., 0. ,\n",
" 0. , -0.0206953 ],\n",
" [ 0. , 0. , 0. , ..., 0. ,\n",
" 0. , -0.01900028]])\n",
" message: '`ftol` termination condition is satisfied.'\n",
" nfev: 6\n",
" njev: 6\n",
" optimality: 1.0470494887335562\n",
" status: 2\n",
" success: True\n",
" x: array([2.48678294e+01, 2.48605209e+01, 2.48510148e+01, 2.48303317e+01,\n",
" 2.48271053e+01, 2.48329202e+01, 2.48413129e+01, 2.48513648e+01,\n",
" 2.48494670e+01, 2.48351933e+01, 2.48134009e+01, 2.47940471e+01,\n",
" 2.48143105e+01, 2.48225237e+01, 2.47991536e+01, 2.47926469e+01,\n",
" 2.48053747e+01, 2.46944351e+01, 2.47105223e+01, 2.47260567e+01,\n",
" 2.47390087e+01, 2.47560602e+01, 2.47653495e+01, 2.47717623e+01,\n",
" 2.47783418e+01, 2.47824889e+01, 2.47876140e+01, 2.47905618e+01,\n",
" 2.47910816e+01, 2.47964202e+01, 2.48057839e+01, 2.48030166e+01,\n",
" 2.48059989e+01, 2.48073704e+01, 9.31054763e-01, 9.40904352e-01,\n",
" 9.99120289e-01, 9.98602102e-01, 1.05925987e+00, 1.19334021e+00,\n",
" 1.14917941e+00, 1.30257852e+00, 1.12395134e+00, 1.24116535e+00,\n",
" 1.01278732e+00, 1.24797381e+00, 7.08449464e-01, 1.15673012e+00,\n",
" 8.43192599e-01, 1.05913383e+00, 4.89670331e-01, 1.75353778e+03,\n",
" 2.38120929e+03, 2.40597528e+03, 2.29642010e+03, 2.27611912e+03,\n",
" 2.23722685e+03, 1.96035330e+03, 2.18666152e+03, 2.13082079e+03,\n",
" 1.91821558e+03, 1.49984525e+03, 1.45915498e+03, 1.23696903e+03,\n",
" 1.04016730e+03, 8.87570454e+02, 7.46185084e+02, 5.67718123e+02,\n",
" 3.37252987e+00, 3.14198741e+00, 3.00064837e+00, 2.95779025e+00,\n",
" 2.87167319e+00, 2.83670243e+00, 2.77588232e+00, 2.71620481e+00,\n",
" 2.67435368e+00, 2.65920896e+00, 2.62285265e+00, 2.53774632e+00,\n",
" 2.48941468e+00, 2.57325935e+00, 2.55456521e+00, 2.44415845e+00,\n",
" 2.45512504e+00, 2.44350230e+00, 2.34593810e+00, 2.29751691e+00,\n",
" 2.31248015e+00, 2.30651994e+00, 2.31650466e+00, 2.30563763e+00,\n",
" 2.29394300e+00, 2.29516965e+00, 2.31377557e+00, 2.31191125e+00,\n",
" 2.26779429e+00, 2.25441336e+00, 2.34711050e+00, 2.33837199e+00,\n",
" 2.25613023e+00, 2.26914960e+00])"
]
},
"execution_count": 119,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"res"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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