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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", "cell_type": "code",
"execution_count": 4, "execution_count": 15,
"id": "7425242d-3c91-4c1e-a424-08625a38ee7a", "id": "7425242d-3c91-4c1e-a424-08625a38ee7a",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -301,7 +301,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 22,
"id": "8055b802-cf83-4250-aea9-54e3e6b73db0", "id": "8055b802-cf83-4250-aea9-54e3e6b73db0",
"metadata": {}, "metadata": {},
"outputs": [ "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", "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", "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", "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", "\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_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", "beam.observe(inte.show_wavelength, names='value') \n",
@ -458,7 +458,6 @@
" \n", " \n",
"\n", "\n",
" ### SAMPLE PLANE ##########################################\n", " ### SAMPLE PLANE ##########################################\n",
" points = 5\n",
" yyy = np.append(np.linspace(0,overlap,100), 200)\n", " yyy = np.append(np.linspace(0,overlap,100), 200)\n",
" wid = np.array([-2, -1, 0, 1, 2]) * step_size_corr\n", " wid = np.array([-2, -1, 0, 1, 2]) * step_size_corr\n",
" fig5 = make_subplots(specs=[[{\"secondary_y\": True}]])\n", " fig5 = make_subplots(specs=[[{\"secondary_y\": True}]])\n",
@ -811,7 +810,7 @@
"id": "1e474cb7-5fd4-4113-a3fa-ddf5ca152ce5", "id": "1e474cb7-5fd4-4113-a3fa-ddf5ca152ce5",
"metadata": {}, "metadata": {},
"source": [ "source": [
"![title](./ptychoscopy_logo.png)\n", "![title](./logo2.png)\n",
"\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", "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", "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", "cell_type": "code",
"execution_count": 8, "execution_count": 23,
"id": "7937f054-fcd0-4e67-a20f-7696f5903a94", "id": "7937f054-fcd0-4e67-a20f-7696f5903a94",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"application/vnd.jupyter.widget-view+json": { "application/vnd.jupyter.widget-view+json": {
"model_id": "c62795511dd9485eba200c05200bbee1", "model_id": "0a48e2bb85fd41a5931e183508ad4aa4",
"version_major": 2, "version_major": 2,
"version_minor": 0 "version_minor": 0
}, },

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13
ptychoScopy.ipynb
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@ -28,7 +28,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 15,
"id": "7425242d-3c91-4c1e-a424-08625a38ee7a", "id": "7425242d-3c91-4c1e-a424-08625a38ee7a",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -301,7 +301,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 22,
"id": "8055b802-cf83-4250-aea9-54e3e6b73db0", "id": "8055b802-cf83-4250-aea9-54e3e6b73db0",
"metadata": {}, "metadata": {},
"outputs": [ "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", "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", "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", "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", "\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_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", "beam.observe(inte.show_wavelength, names='value') \n",
@ -458,7 +458,6 @@
" \n", " \n",
"\n", "\n",
" ### SAMPLE PLANE ##########################################\n", " ### SAMPLE PLANE ##########################################\n",
" points = 5\n",
" yyy = np.append(np.linspace(0,overlap,100), 200)\n", " yyy = np.append(np.linspace(0,overlap,100), 200)\n",
" wid = np.array([-2, -1, 0, 1, 2]) * step_size_corr\n", " wid = np.array([-2, -1, 0, 1, 2]) * step_size_corr\n",
" fig5 = make_subplots(specs=[[{\"secondary_y\": True}]])\n", " fig5 = make_subplots(specs=[[{\"secondary_y\": True}]])\n",
@ -811,7 +810,7 @@
"id": "1e474cb7-5fd4-4113-a3fa-ddf5ca152ce5", "id": "1e474cb7-5fd4-4113-a3fa-ddf5ca152ce5",
"metadata": {}, "metadata": {},
"source": [ "source": [
"![title](./ptychoscopy_logo.png)\n", "![title](./logo2.png)\n",
"\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", "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", "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", "cell_type": "code",
"execution_count": 8, "execution_count": 23,
"id": "7937f054-fcd0-4e67-a20f-7696f5903a94", "id": "7937f054-fcd0-4e67-a20f-7696f5903a94",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"application/vnd.jupyter.widget-view+json": { "application/vnd.jupyter.widget-view+json": {
"model_id": "c62795511dd9485eba200c05200bbee1", "model_id": "0a48e2bb85fd41a5931e183508ad4aa4",
"version_major": 2, "version_major": 2,
"version_minor": 0 "version_minor": 0
}, },

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ptychoscopy_logo.png
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