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rskoupy
2023-12-14 11:37:50 +01:00
parent e69d281399
commit 886d2bb59e
5 changed files with 12 additions and 14 deletions
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13
.ipynb_checkpoints/ptychoScopy-checkpoint.ipynb
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@ -28,7 +28,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 15,
"id": "7425242d-3c91-4c1e-a424-08625a38ee7a",
"metadata": {},
"outputs": [],
@ -301,7 +301,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 22,
"id": "8055b802-cf83-4250-aea9-54e3e6b73db0",
"metadata": {},
"outputs": [
@ -338,7 +338,7 @@
"cl = ToggleButtons(options=opt.cameralengths(), value=12, description='Nominal camera length (cm)', layout=Layout(width='auto', grid_area='cl_set1'), **ali)\n",
"camera = ToggleButtons(options=opt.detectors(), description='Detector', layout=Layout(width='auto', grid_area='camera_set1'), style = {'description_width': '60px','button_width': str(100/len(opt.detectors())-len(opt.detectors()))+'%', 'font_weight': 'bold'})\n",
"restriction = ToggleButtons(options=[('.',False), ('..',True)], value = False, description='PAAR',icons = ['times','check'], layout=Layout(width='auto', grid_area='camera_set2'),style = {'description_width': '80px','button_width': '48%', 'font_weight': 'bold'})\n",
"binning = ToggleButtons(options=[('.',1), ('2×2',2), ('4×4',4), ('6×6',6), ('8×8',8)], value=1, description='Binning', icons = ['times','',''], layout=Layout(width='auto', grid_area='camera_set3'), **ali)\n",
"binning = ToggleButtons(options=[('.',1), ('2×2',2), ('4×4',4), ('3×3',3), ('6×6',6), ('8×8',8), ('12×12',12), ('16×16',16), ('24×24',24), ('32×32',32), ('48×48',48)], value=1, description='Binning', icons = ['times','',''], layout=Layout(width='auto', grid_area='camera_set3'), **ali)\n",
"\n",
"beam_res = Label(value = f'λ (pm) '+ str(\"{:.1f}\".format(pty.get_wavelength(beam.value)*1e12)),layout=Layout(width='auto', grid_area='sidebar1'),)\n",
"beam.observe(inte.show_wavelength, names='value') \n",
@ -458,7 +458,6 @@
" \n",
"\n",
" ### SAMPLE PLANE ##########################################\n",
" points = 5\n",
" yyy = np.append(np.linspace(0,overlap,100), 200)\n",
" wid = np.array([-2, -1, 0, 1, 2]) * step_size_corr\n",
" fig5 = make_subplots(specs=[[{\"secondary_y\": True}]])\n",
@ -811,7 +810,7 @@
"id": "1e474cb7-5fd4-4113-a3fa-ddf5ca152ce5",
"metadata": {},
"source": [
"![title](./ptychoscopy_logo.png)\n",
"![title](./logo2.png)\n",
"\n",
"Jupyter based interactive data acquisition tool designed for appropriate ptychographic data collection. It computes nessesary characteristics which play crutial role in final data reconstruction. \n",
"You can chose of **Direct methods** (mainly Single Side Band ptychography) or **Iterative reconstruction** which takes probe defocus into account. With this tool, you can check for probe CTF, scanning step size, probe overlap, detector camera length a proper angular range collection, reconstructed probe size and many more.\n",
@ -836,14 +835,14 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 23,
"id": "7937f054-fcd0-4e67-a20f-7696f5903a94",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "c62795511dd9485eba200c05200bbee1",
"model_id": "0a48e2bb85fd41a5931e183508ad4aa4",
"version_major": 2,
"version_minor": 0
},

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calibrations.xlsx
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logo2.png Normal file
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13
ptychoScopy.ipynb
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@ -28,7 +28,7 @@
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": 15,
"id": "7425242d-3c91-4c1e-a424-08625a38ee7a",
"metadata": {},
"outputs": [],
@ -301,7 +301,7 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": 22,
"id": "8055b802-cf83-4250-aea9-54e3e6b73db0",
"metadata": {},
"outputs": [
@ -338,7 +338,7 @@
"cl = ToggleButtons(options=opt.cameralengths(), value=12, description='Nominal camera length (cm)', layout=Layout(width='auto', grid_area='cl_set1'), **ali)\n",
"camera = ToggleButtons(options=opt.detectors(), description='Detector', layout=Layout(width='auto', grid_area='camera_set1'), style = {'description_width': '60px','button_width': str(100/len(opt.detectors())-len(opt.detectors()))+'%', 'font_weight': 'bold'})\n",
"restriction = ToggleButtons(options=[('.',False), ('..',True)], value = False, description='PAAR',icons = ['times','check'], layout=Layout(width='auto', grid_area='camera_set2'),style = {'description_width': '80px','button_width': '48%', 'font_weight': 'bold'})\n",
"binning = ToggleButtons(options=[('.',1), ('2×2',2), ('4×4',4), ('6×6',6), ('8×8',8)], value=1, description='Binning', icons = ['times','',''], layout=Layout(width='auto', grid_area='camera_set3'), **ali)\n",
"binning = ToggleButtons(options=[('.',1), ('2×2',2), ('4×4',4), ('3×3',3), ('6×6',6), ('8×8',8), ('12×12',12), ('16×16',16), ('24×24',24), ('32×32',32), ('48×48',48)], value=1, description='Binning', icons = ['times','',''], layout=Layout(width='auto', grid_area='camera_set3'), **ali)\n",
"\n",
"beam_res = Label(value = f'λ (pm) '+ str(\"{:.1f}\".format(pty.get_wavelength(beam.value)*1e12)),layout=Layout(width='auto', grid_area='sidebar1'),)\n",
"beam.observe(inte.show_wavelength, names='value') \n",
@ -458,7 +458,6 @@
" \n",
"\n",
" ### SAMPLE PLANE ##########################################\n",
" points = 5\n",
" yyy = np.append(np.linspace(0,overlap,100), 200)\n",
" wid = np.array([-2, -1, 0, 1, 2]) * step_size_corr\n",
" fig5 = make_subplots(specs=[[{\"secondary_y\": True}]])\n",
@ -811,7 +810,7 @@
"id": "1e474cb7-5fd4-4113-a3fa-ddf5ca152ce5",
"metadata": {},
"source": [
"![title](./ptychoscopy_logo.png)\n",
"![title](./logo2.png)\n",
"\n",
"Jupyter based interactive data acquisition tool designed for appropriate ptychographic data collection. It computes nessesary characteristics which play crutial role in final data reconstruction. \n",
"You can chose of **Direct methods** (mainly Single Side Band ptychography) or **Iterative reconstruction** which takes probe defocus into account. With this tool, you can check for probe CTF, scanning step size, probe overlap, detector camera length a proper angular range collection, reconstructed probe size and many more.\n",
@ -836,14 +835,14 @@
},
{
"cell_type": "code",
"execution_count": 8,
"execution_count": 23,
"id": "7937f054-fcd0-4e67-a20f-7696f5903a94",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "c62795511dd9485eba200c05200bbee1",
"model_id": "0a48e2bb85fd41a5931e183508ad4aa4",
"version_major": 2,
"version_minor": 0
},

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ptychoscopy_logo.png
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