WIP
This commit is contained in:
Erik Fröjdh committed
1 parent
489b1dad8c
commit
d11cd36335
1 file changed
+41
-59
@@ -10,9 +10,15 @@
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},
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{
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"cell_type": "code",
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"execution_count": 65,
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"execution_count": 1,
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"id": "a7bafd1c-9c36-40c2-bf8d-3bba7fbc09f8",
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"metadata": {},
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"metadata": {
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"editable": true,
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"slideshow": {
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"slide_type": ""
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},
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"tags": []
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},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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@@ -52,7 +58,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 66,
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"execution_count": 2,
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"id": "8ae6ce69-313f-41d4-8019-64e93a5610a0",
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"metadata": {},
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"outputs": [
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@@ -102,13 +108,13 @@
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},
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{
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"cell_type": "code",
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"execution_count": 67,
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"execution_count": 3,
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"id": "6390e1ef-2216-47ed-a8ce-106b9a7766ed",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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truncated
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"image/png": "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 truncated
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"text/plain": [
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"<Figure size 1000x500 with 2 Axes>"
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]
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@@ -151,28 +157,19 @@
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},
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{
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"cell_type": "code",
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"execution_count": 68,
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"execution_count": 4,
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"id": "168d967c-94a3-4b32-aa14-4a248035e5c6",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"99\n",
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"Duration: 12.617s, FPS: 7.93, hits/s: 7.9e+03s\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"# Cluster file has the format\n",
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"# int32_t frame_number\n",
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"# uint32_t number_of_clusters\n",
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"# int16_t x, int16_t y, int32_t data[9] * number_of_clusters\n",
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"\n",
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||||
"generate_hits = True\n",
|
||||
"generate_hits = False\n",
|
||||
"n_hits = 1000\n",
|
||||
"n_frames = 100\n",
|
||||
"n_frames = 1000\n",
|
||||
"\n",
|
||||
"if generate_hits:\n",
|
||||
" t0 = time.perf_counter()\n",
|
||||
@@ -184,7 +181,6 @@
|
||||
" for i in range(n_frames):\n",
|
||||
" print(f'{i}',end = '\\r')\n",
|
||||
" #Generate a new set of n_hits hits\n",
|
||||
" # mx,my, pixels = generate.generate_uniform_hits(sigma = sigma_um, pixel_size = pixel_size, grid_size = grid_size, resolution=resolution, N=n_hits)\n",
|
||||
" mx, my, pixels = g.uniform_hits(n_hits)\n",
|
||||
" #Convert clusters to a numpy array\n",
|
||||
" clusters = np.zeros(n_hits, dtype = [('row', np.int16), ('col', np.int16), ('data', np.int32, (grid_size,grid_size))])\n",
|
||||
@@ -206,13 +202,13 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 69,
|
||||
"execution_count": 5,
|
||||
"id": "0b3fef19-144b-4421-8d21-66b67b838813",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"image/png": "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 truncated
|
||||
"image/png": "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 truncated
|
||||
"text/plain": [
|
||||
"<Figure size 640x480 with 2 Axes>"
|
||||
]
|
||||
@@ -241,8 +237,9 @@
|
||||
"with aare.ClusterFile(f'.data/test_{grid_size}x{grid_size}.clust', cluster_size = (grid_size,grid_size)) as f:\n",
|
||||
" for clusters in f:\n",
|
||||
" eta2 = aare.calculate_eta2(clusters)\n",
|
||||
" energy = clusters.sum_2x2()\n",
|
||||
" eta_hist.fill(eta2[:,0], eta2[:,1], energy['sum'])\n",
|
||||
" # energy = clusters.sum_2x2()\n",
|
||||
" eta_hist.fill(eta2['x'], eta2['y'], eta2['sum'])\n",
|
||||
" # eta_hist.fill(eta2[:,0], eta2[:,1], energy['sum'])\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"energy_index = 0\n",
|
||||
@@ -260,37 +257,13 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 70,
|
||||
"id": "fd896d4d-2d60-4328-ad8d-18cd80de09f6",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"eta = eta_hist.view().copy()\n",
|
||||
"etabinsx = np.array(eta_hist.axes.edges.T[0].flat)\n",
|
||||
"etabinsy = np.array(eta_hist.axes.edges.T[1].flat)\n",
|
||||
"ebins = np.array(eta_hist.axes.edges.T[2].flat)\n",
|
||||
"p = aare.Interpolator(eta_hist, etabinsx[0:-1], etabinsy[0:-1], ebins[0:-1])"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 71,
|
||||
"execution_count": 9,
|
||||
"id": "cada1860-6b7b-416a-a39b-295586121531",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"(20.0, 55.0)"
|
||||
]
|
||||
},
|
||||
"execution_count": 71,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
},
|
||||
{
|
||||
"data": {
|
||||
"image/png": 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truncated
|
||||
"image/png": 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truncated
|
||||
"text/plain": [
|
||||
"<Figure size 1000x1000 with 1 Axes>"
|
||||
]
|
||||
@@ -300,10 +273,12 @@
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"\n",
|
||||
"etabinsx = np.array(eta_hist.axes.edges.T[0].flat)\n",
|
||||
"etabinsy = np.array(eta_hist.axes.edges.T[1].flat)\n",
|
||||
"ebins = np.array(eta_hist.axes.edges.T[2].flat)\n",
|
||||
"p = aare.Interpolator(eta_hist, etabinsx, etabinsy, ebins)\n",
|
||||
"v = aare.ClusterVector((grid_size,grid_size))\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"show_arrows = True\n",
|
||||
"a = np.linspace(25,50,20)\n",
|
||||
"hit_position = np.zeros((a.size**2,2))\n",
|
||||
@@ -313,16 +288,15 @@
|
||||
" hit_position[i*a.size+j] = (a[i], a[j])\n",
|
||||
"\n",
|
||||
"for i, hit in enumerate(hit_position):\n",
|
||||
" # t = gaussian_2d(mx=hit[0], my = hit[1], sigma = sigma_um, res = resolution)\n",
|
||||
" t = gaussian_2d(mx=hit[0], my = hit[1], sigma = sigma_um, res = resolution, grid_size = grid_size, pixel_size = pixel_size)\n",
|
||||
" pixels = generate.sum_pixels(t, grid_size)\n",
|
||||
" charge, pixels = g.hit(*hit)\n",
|
||||
" pixels = (pixels*1000).astype(np.int32)\n",
|
||||
" pixels = np.array(pixels).reshape(1,9)[0]\n",
|
||||
" c = aare._aare.Cluster3x3i(1,1,pixels)\n",
|
||||
" v.push_back(c)\n",
|
||||
"\n",
|
||||
"tmp = p.interpolate(v)\n",
|
||||
"offset = 25/2\n",
|
||||
"# offset = 25/2\n",
|
||||
"offset = 0\n",
|
||||
"interpolated_position[:, 0] = tmp['x']*25+offset\n",
|
||||
"interpolated_position[:, 1] = tmp['y']*25+offset\n",
|
||||
"\n",
|
||||
@@ -337,17 +311,25 @@
|
||||
"\n",
|
||||
"\n",
|
||||
"ax.set_title('Interpolation from C++')\n",
|
||||
"\n",
|
||||
"ax.xaxis.set_minor_locator(MultipleLocator(5))\n",
|
||||
"ax.yaxis.set_minor_locator(MultipleLocator(5))\n",
|
||||
"ticks = [tick for tick in range(0,pixel_size*grid_size+1, pixel_size)]\n",
|
||||
"ax.set_xticks(ticks)\n",
|
||||
"ax.set_yticks(ticks)\n",
|
||||
"# ax.grid(which = 'both')\n",
|
||||
"ax.grid(visible=True, which='minor', color='silver', linestyle='--')\n",
|
||||
"ax.grid(visible=True, which='major', color='black', linestyle='-')\n",
|
||||
"ax.set_xlim(20,55)\n",
|
||||
"ax.set_ylim(20,55)"
|
||||
"# ax.set_xlim(15,60)\n",
|
||||
"# ax.set_ylim(15,60)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "b0398535-b646-4b3c-9029-0a8b8aa764f1",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"tmp"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
||||
Reference in new issue
Block a user