First working 2d fit

This commit is contained in:
Joschka 2023-07-26 09:41:51 +02:00
parent ade2304ccf
commit cd6cb974c7
4 changed files with 1142 additions and 247 deletions

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@ -2,7 +2,7 @@
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"import xarray as xr\n", "import xarray as xr\n",
@ -55,8 +55,8 @@
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@ -71,7 +71,7 @@
}, },
{ {
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"# get center of thresholded image\n", "# get center of thresholded image\n",
@ -110,26 +110,33 @@
"def gaussian(x, x0, sigma, A):\n", "def gaussian(x, x0, sigma, A):\n",
" return A * np.exp(-0.5 * (x-x0)**2 / sigma**2)\n", " return A * np.exp(-0.5 * (x-x0)**2 / sigma**2)\n",
"\n", "\n",
"def polylog(power, numerator, order = 15):\n", "# def polylog(power, numerator, order = 15):\n",
"#\n",
"# dataShape = numerator.shape\n",
"# numerator = np.tile(numerator, (order, 1))\n",
"# numerator = np.power(numerator.T, np.arange(1, order+1)).T\n",
"#\n",
"# denominator = np.arange(1, order+1)\n",
"# denominator = np.tile(denominator, (dataShape[0], 1))\n",
"# denominator = denominator.T\n",
"#\n",
"# data = numerator/ np.power(denominator, power)\n",
"#\n",
"# return np.sum(data, axis=0)\n",
"\n", "\n",
" dataShape = numerator.shape\n", "def polylog(pow, x):\n",
" numerator = np.tile(numerator, (order, 1))\n", " order = 15\n",
" numerator = np.power(numerator.T, np.arange(1, order+1)).T\n", " sum = 0\n",
"\n", " for k in range(1,order):\n",
" denominator = np.arange(1, order+1)\n", " sum += x ** k /k **pow\n",
" denominator = np.tile(denominator, (dataShape[0], 1))\n", " return sum\n",
" denominator = denominator.T\n",
"\n",
" data = numerator/ np.power(denominator, power)\n",
"\n",
" return np.sum(data, axis=0)\n",
"\n", "\n",
"def thermal(x, x0, amp, sigma, order = 15):\n", "def thermal(x, x0, amp, sigma, order = 15):\n",
" res = np.exp(-0.5 * (x-x0)**2 / sigma**2)\n", " res = np.exp(-0.5 * (x-x0)**2 / sigma**2)\n",
" return amp * polylog(2, res, order)\n", " return amp/1.643 * polylog(2, res, order)\n",
"\n", "\n",
"def Thomas_Fermi_1d(x, x0, amp, sigma):\n", "def Thomas_Fermi_1d(x, x0, amp, sigma):\n",
" res = (1-(( x - x0 ) / sigma) **2) **3/2\n", " res = (1-(( x - x0 ) / sigma) **2) **(3/2)\n",
" return amp * np.where(res > 0, res, 0)\n", " return amp * np.where(res > 0, res, 0)\n",
"\n", "\n",
"def density_1d(x, x0_bec, x0_th, amp_bec, amp_th, sigma_bec, sigma_th):\n", "def density_1d(x, x0_bec, x0_th, amp_bec, amp_th, sigma_bec, sigma_th):\n",
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@ -796,13 +803,13 @@
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{ {
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"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"fitting time: 112.2138500213623 ms\n" "fitting time: 106.31179809570312 ms\n"
] ]
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@ -843,14 +850,14 @@
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"# Fitting x without math constr\n", "# Fitting x without math constr\n",
@ -878,14 +885,14 @@
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"# Fitting x with math constraint on width\n", "# Fitting x with math constraint on width\n",
@ -915,8 +922,8 @@
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@ -1053,7 +1060,7 @@
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@ -1061,47 +1068,38 @@
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"[75.41570333 77.33388115 2.56706786 0.32435386 9.02534473 21.78913789]\n", "[75.41570333 77.33388115 2.56706786 0.32435386 9.02534473 21.78913789]\n",
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"19.0\n", "19.0\n",
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"18.0\n", "18.0\n",
"\n", "\n",
"[74.88995354 73.93092826 0.90810872 0.09114657 9.42569183 7.98461584]\n", "[74.88995354 73.93092826 0.90810872 0.09114657 9.42569183 7.98461584]\n",
"{'x0_bec': 74.84814609706852, 'x0_th': 74.34947866579368, 'amp_bec': 0.7917518736101876, 'amp_th': 0.12935441772036824, 'sigma_bec': 8.30427046215347, 'sigma_th': 8.304270463041027}\n", "{'x0_bec': 74.84814609706852, 'x0_th': 74.34947866579368, 'amp_bec': 0.7917518736101876, 'amp_th': 0.12935441772036824, 'sigma_bec': 8.30427046215347, 'sigma_th': 8.304270463041027}\n",
"{'x0_bec': 84.74015748031496, 'x0_th': 84.74015748031496, 'amp_bec': 0.79175187364107, 'amp_th': 0.0788407156338335, 'sigma_bec': 27.943373217645885, 'sigma_th': 8.304270463041027}\n",
"20.0\n", "20.0\n",
"\n" "\n"
] ]
@ -1113,7 +1111,7 @@
" for j in range(0, shape[1]):\n", " for j in range(0, shape[1]):\n",
" print(popt[i,j])\n", " print(popt[i,j])\n",
" print(result_x[i][j].best_values)\n", " print(result_x[i][j].best_values)\n",
" print(result_y[i][j].best_values)\n", " #print(result_y[i][j].best_values)\n",
" print(BEC_width_guess[i,j,1])\n", " print(BEC_width_guess[i,j,1])\n",
" print(\"\")\n", " print(\"\")\n",
"\n" "\n"
@ -1121,14 +1119,14 @@
"metadata": { "metadata": {
"collapsed": false, "collapsed": false,
"ExecuteTime": { "ExecuteTime": {
"end_time": "2023-07-20T13:34:58.548593Z", "end_time": "2023-07-25T10:29:51.620810400Z",
"start_time": "2023-07-20T13:34:58.484422900Z" "start_time": "2023-07-25T10:29:51.571566300Z"
} }
} }
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 205, "execution_count": 22,
"outputs": [ "outputs": [
{ {
"data": { "data": {
@ -1156,18 +1154,34 @@
"metadata": { "metadata": {
"collapsed": false, "collapsed": false,
"ExecuteTime": { "ExecuteTime": {
"end_time": "2023-07-20T13:23:24.146431Z", "end_time": "2023-07-25T10:29:32.565187100Z",
"start_time": "2023-07-20T13:23:22.681336600Z" "start_time": "2023-07-25T10:29:31.085329400Z"
} }
} }
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 28,
"outputs": [], "outputs": [
"source": [], {
"name": "stdout",
"output_type": "stream",
"text": [
"22.774\n",
"22.814\n"
]
}
],
"source": [
"print(11.8*1.93)\n",
"print(18.7*1.22)"
],
"metadata": { "metadata": {
"collapsed": false "collapsed": false,
"ExecuteTime": {
"end_time": "2023-07-25T13:42:22.372434400Z",
"start_time": "2023-07-25T13:42:22.299475700Z"
}
} }
}, },
{ {

View File

@ -906,7 +906,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 18, "execution_count": 1,
"outputs": [], "outputs": [],
"source": [ "source": [
"def find_fwhm(f_x, x):\n", "def find_fwhm(f_x, x):\n",
@ -924,8 +924,8 @@
"metadata": { "metadata": {
"collapsed": false, "collapsed": false,
"ExecuteTime": { "ExecuteTime": {
"end_time": "2023-07-11T15:19:35.219252800Z", "end_time": "2023-07-25T12:33:47.822058700Z",
"start_time": "2023-07-11T15:19:35.187552700Z" "start_time": "2023-07-25T12:33:47.814126200Z"
} }
} }
}, },