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indranilsinharoy/OpticStudio_GetTextFile_GetMetaFile_Text.json

Created March 21, 2014 23:27
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Quick test of GetTextFile and GetMetaFile data items used by Zeamx extensions show that there OpticStudio doesn't output the expected analysis windows.
Raw
OpticStudio_GetTextFile_GetMetaFile_Text.json
{
"metadata": {
"name": "OpticStudio_Tests"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": "Test of data items GetTextFile and GetMetaFile in Zemax OpticStudio14"
},
{
"cell_type": "code",
"collapsed": false,
"input": "import pyzdde.zdde as pyz\nimport matplotlib.pyplot as plt",
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "code",
"collapsed": false,
"input": "%matplotlib inline",
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": "A lens was already loaded into the ZOS LDE."
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln = pyz.PyZDDE()",
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 3
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zDDEInit()",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": "0"
}
],
"prompt_number": 4
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zGetVersion() ",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": "140317"
}
],
"prompt_number": 5
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zGetFile()",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": "'C:\\\\Users\\\\Indranil\\\\Documents\\\\ZEMAX\\\\Samples\\\\Sequential\\\\Objectives\\\\Cooke 40 degree field.zmx'"
}
],
"prompt_number": 6
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zGetRefresh()",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 7,
"text": "0"
}
],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": "pyz.zb.showZButtonList()",
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": "Listing all ZEMAX Button codes:\n"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>ABg</font></b><font color='blue'>]</font> ABg Data Catalog",
"metadata": {},
"output_type": "display_data",
"text": "[ABg] ABg Data Catalog"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Agm</font></b><font color='blue'>]</font> Athermal Glass Map",
"metadata": {},
"output_type": "display_data",
"text": "[Agm] Athermal Glass Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Bac</font></b><font color='blue'>]</font> Backup To Archive File",
"metadata": {},
"output_type": "display_data",
"text": "[Bac] Backup To Archive File"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Bfv</font></b><font color='blue'>]</font> Beam File Viewer",
"metadata": {},
"output_type": "display_data",
"text": "[Bfv] Beam File Viewer"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Caa</font></b><font color='blue'>]</font> Coating, Abs. vs. Angle",
"metadata": {},
"output_type": "display_data",
"text": "[Caa] Coating, Abs. vs. Angle"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Car</font></b><font color='blue'>]</font> Cardinal Points",
"metadata": {},
"output_type": "display_data",
"text": "[Car] Cardinal Points"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cas</font></b><font color='blue'>]</font> Coat All Surfaces",
"metadata": {},
"output_type": "display_data",
"text": "[Cas] Coat All Surfaces"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Caw</font></b><font color='blue'>]</font> Coating, Abs. vs. Wavelength",
"metadata": {},
"output_type": "display_data",
"text": "[Caw] Coating, Abs. vs. Wavelength"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cca</font></b><font color='blue'>]</font> Convert to Circular Apertures",
"metadata": {},
"output_type": "display_data",
"text": "[Cca] Convert to Circular Apertures"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cda</font></b><font color='blue'>]</font> Coating, Dia. vs. Angle",
"metadata": {},
"output_type": "display_data",
"text": "[Cda] Coating, Dia. vs. Angle"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cdw</font></b><font color='blue'>]</font> Coating, DIa. vs. Angle",
"metadata": {},
"output_type": "display_data",
"text": "[Cdw] Coating, DIa. vs. Angle"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cfa</font></b><font color='blue'>]</font> Convert to Floating Apertures",
"metadata": {},
"output_type": "display_data",
"text": "[Cfa] Convert to Floating Apertures"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cfm</font></b><font color='blue'>]</font> Convert to Maximum Apertures",
"metadata": {},
"output_type": "display_data",
"text": "[Cfm] Convert to Maximum Apertures"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cfo</font></b><font color='blue'>]</font> Convert Format",
"metadata": {},
"output_type": "display_data",
"text": "[Cfo] Convert Format"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cfs</font></b><font color='blue'>]</font> Chromatic Focal Shift",
"metadata": {},
"output_type": "display_data",
"text": "[Cfs] Chromatic Focal Shift"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cgl</font></b><font color='blue'>]</font> Convert Global To Local",
"metadata": {},
"output_type": "display_data",
"text": "[Cgl] Convert Global To Local"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Chk</font></b><font color='blue'>]</font> System Check",
"metadata": {},
"output_type": "display_data",
"text": "[Chk] System Check"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Clg</font></b><font color='blue'>]</font> Convert Local to Global",
"metadata": {},
"output_type": "display_data",
"text": "[Clg] Convert Local to Global"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cls</font></b><font color='blue'>]</font> Coating List",
"metadata": {},
"output_type": "display_data",
"text": "[Cls] Coating List"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cna</font></b><font color='blue'>]</font> Coating, Ret. vs. Angle",
"metadata": {},
"output_type": "display_data",
"text": "[Cna] Coating, Ret. vs. Angle"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cng</font></b><font color='blue'>]</font> Convert to NSC Group",
"metadata": {},
"output_type": "display_data",
"text": "[Cng] Convert to NSC Group"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cnw</font></b><font color='blue'>]</font> Coating, Ret. vs. Wavelength",
"metadata": {},
"output_type": "display_data",
"text": "[Cnw] Coating, Ret. vs. Wavelength"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Coa</font></b><font color='blue'>]</font> Convert Asphere Type",
"metadata": {},
"output_type": "display_data",
"text": "[Coa] Convert Asphere Type"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Con</font></b><font color='blue'>]</font> Conjugate Surface Analysis",
"metadata": {},
"output_type": "display_data",
"text": "[Con] Conjugate Surface Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cpa</font></b><font color='blue'>]</font> Coating, Phase vs. Angle",
"metadata": {},
"output_type": "display_data",
"text": "[Cpa] Coating, Phase vs. Angle"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cpw</font></b><font color='blue'>]</font> Coating, Phase vs. Wavelength",
"metadata": {},
"output_type": "display_data",
"text": "[Cpw] Coating, Phase vs. Wavelength"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cra</font></b><font color='blue'>]</font> Coating, Refl vs. Angle",
"metadata": {},
"output_type": "display_data",
"text": "[Cra] Coating, Refl vs. Angle"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Crw</font></b><font color='blue'>]</font> Coating, Refl. vs. Wavelength",
"metadata": {},
"output_type": "display_data",
"text": "[Crw] Coating, Refl. vs. Wavelength"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Cta</font></b><font color='blue'>]</font> Coating, Tran. vs. Angle",
"metadata": {},
"output_type": "display_data",
"text": "[Cta] Coating, Tran. vs. Angle"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ctw</font></b><font color='blue'>]</font> Coating, Tran. vs. Wavelength",
"metadata": {},
"output_type": "display_data",
"text": "[Ctw] Coating, Tran. vs. Wavelength"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Dbl</font></b><font color='blue'>]</font> Make Double Pass",
"metadata": {},
"output_type": "display_data",
"text": "[Dbl] Make Double Pass"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Dim</font></b><font color='blue'>]</font> Partially Coherent Image Analysis",
"metadata": {},
"output_type": "display_data",
"text": "[Dim] Partially Coherent Image Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Dip</font></b><font color='blue'>]</font> Biocular Dipvergence/Convergence",
"metadata": {},
"output_type": "display_data",
"text": "[Dip] Biocular Dipvergence/Convergence"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Dis</font></b><font color='blue'>]</font> Dispersion Plot",
"metadata": {},
"output_type": "display_data",
"text": "[Dis] Dispersion Plot"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Dvl</font></b><font color='blue'>]</font> Dispersion vs. Wavelength Plot",
"metadata": {},
"output_type": "display_data",
"text": "[Dvl] Dispersion vs. Wavelength Plot"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Dvr</font></b><font color='blue'>]</font> Detector Viewer",
"metadata": {},
"output_type": "display_data",
"text": "[Dvr] Detector Viewer"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>EDE</font></b><font color='blue'>]</font> Extra Data Editor",
"metadata": {},
"output_type": "display_data",
"text": "[EDE] Extra Data Editor"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ect</font></b><font color='blue'>]</font> Edit Coating",
"metadata": {},
"output_type": "display_data",
"text": "[Ect] Edit Coating"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Eec</font></b><font color='blue'>]</font> Export Encrypted Coating",
"metadata": {},
"output_type": "display_data",
"text": "[Eec] Export Encrypted Coating"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ele</font></b><font color='blue'>]</font> ZEMAX Element Drawing",
"metadata": {},
"output_type": "display_data",
"text": "[Ele] ZEMAX Element Drawing"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Enc</font></b><font color='blue'>]</font> Diff Encircled Energy",
"metadata": {},
"output_type": "display_data",
"text": "[Enc] Diff Encircled Energy"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ext</font></b><font color='blue'>]</font> Exit",
"metadata": {},
"output_type": "display_data",
"text": "[Ext] Exit"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fba</font></b><font color='blue'>]</font> Find Best Asphere",
"metadata": {},
"output_type": "display_data",
"text": "[Fba] Find Best Asphere"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fcd</font></b><font color='blue'>]</font> Field Curv/Distorion",
"metadata": {},
"output_type": "display_data",
"text": "[Fcd] Field Curv/Distorion"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fcl</font></b><font color='blue'>]</font> Fiber Coupling",
"metadata": {},
"output_type": "display_data",
"text": "[Fcl] Fiber Coupling"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fie</font></b><font color='blue'>]</font> Field Data",
"metadata": {},
"output_type": "display_data",
"text": "[Fie] Field Data"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fld</font></b><font color='blue'>]</font> Add Fold Mirror",
"metadata": {},
"output_type": "display_data",
"text": "[Fld] Add Fold Mirror"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Flx</font></b><font color='blue'>]</font> Delete Fold Mirror",
"metadata": {},
"output_type": "display_data",
"text": "[Flx] Delete Fold Mirror"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fmm</font></b><font color='blue'>]</font> FFT MTF Map",
"metadata": {},
"output_type": "display_data",
"text": "[Fmm] FFT MTF Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Foa</font></b><font color='blue'>]</font> Foucault Analysis",
"metadata": {},
"output_type": "display_data",
"text": "[Foa] Foucault Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Foo</font></b><font color='blue'>]</font> Footprint Analysis",
"metadata": {},
"output_type": "display_data",
"text": "[Foo] Footprint Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fov</font></b><font color='blue'>]</font> Biocular Field of View Analysis",
"metadata": {},
"output_type": "display_data",
"text": "[Fov] Biocular Field of View Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fps</font></b><font color='blue'>]</font> FFT PSF",
"metadata": {},
"output_type": "display_data",
"text": "[Fps] FFT PSF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Fvw</font></b><font color='blue'>]</font> Flux vs. Wavelength",
"metadata": {},
"output_type": "display_data",
"text": "[Fvw] Flux vs. Wavelength"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gbp</font></b><font color='blue'>]</font> Parax Gaussian Beam",
"metadata": {},
"output_type": "display_data",
"text": "[Gbp] Parax Gaussian Beam"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gbs</font></b><font color='blue'>]</font> Skew Gaussian Beam",
"metadata": {},
"output_type": "display_data",
"text": "[Gbs] Skew Gaussian Beam"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gcp</font></b><font color='blue'>]</font> Glass Compare",
"metadata": {},
"output_type": "display_data",
"text": "[Gcp] Glass Compare"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gee</font></b><font color='blue'>]</font> Geometric Encircled Energy",
"metadata": {},
"output_type": "display_data",
"text": "[Gee] Geometric Encircled Energy"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gen</font></b><font color='blue'>]</font> General Lens Data",
"metadata": {},
"output_type": "display_data",
"text": "[Gen] General Lens Data"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gft</font></b><font color='blue'>]</font> Glass Fit",
"metadata": {},
"output_type": "display_data",
"text": "[Gft] Glass Fit"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gho</font></b><font color='blue'>]</font> Ghost Focus",
"metadata": {},
"output_type": "display_data",
"text": "[Gho] Ghost Focus"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gip</font></b><font color='blue'>]</font> Grin Profile",
"metadata": {},
"output_type": "display_data",
"text": "[Gip] Grin Profile"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gla</font></b><font color='blue'>]</font> Glass Catalog",
"metadata": {},
"output_type": "display_data",
"text": "[Gla] Glass Catalog"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Glb</font></b><font color='blue'>]</font> Global Optimization",
"metadata": {},
"output_type": "display_data",
"text": "[Glb] Global Optimization"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gmm</font></b><font color='blue'>]</font> Geometric MTF Map",
"metadata": {},
"output_type": "display_data",
"text": "[Gmm] Geometric MTF Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gmp</font></b><font color='blue'>]</font> Glass Map",
"metadata": {},
"output_type": "display_data",
"text": "[Gmp] Glass Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gpr</font></b><font color='blue'>]</font> Gradium Profile",
"metadata": {},
"output_type": "display_data",
"text": "[Gpr] Gradium Profile"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Grd</font></b><font color='blue'>]</font> Grid Distortion",
"metadata": {},
"output_type": "display_data",
"text": "[Grd] Grid Distortion"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gst</font></b><font color='blue'>]</font> Glass Substitution Template",
"metadata": {},
"output_type": "display_data",
"text": "[Gst] Glass Substitution Template"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gtf</font></b><font color='blue'>]</font> Geometric MTF",
"metadata": {},
"output_type": "display_data",
"text": "[Gtf] Geometric MTF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Gvf</font></b><font color='blue'>]</font> Geometric MTF vs. Field",
"metadata": {},
"output_type": "display_data",
"text": "[Gvf] Geometric MTF vs. Field"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ham</font></b><font color='blue'>]</font> Hammer Optimization",
"metadata": {},
"output_type": "display_data",
"text": "[Ham] Hammer Optimization"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Hcs</font></b><font color='blue'>]</font> Huygens PSF Cross Section",
"metadata": {},
"output_type": "display_data",
"text": "[Hcs] Huygens PSF Cross Section"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Hlp</font></b><font color='blue'>]</font> Help",
"metadata": {},
"output_type": "display_data",
"text": "[Hlp] Help"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Hmf</font></b><font color='blue'>]</font> Huygens MTF",
"metadata": {},
"output_type": "display_data",
"text": "[Hmf] Huygens MTF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Hmh</font></b><font color='blue'>]</font> Huygens MTF vs Field",
"metadata": {},
"output_type": "display_data",
"text": "[Hmh] Huygens MTF vs Field"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Hps</font></b><font color='blue'>]</font> Huygens PSF",
"metadata": {},
"output_type": "display_data",
"text": "[Hps] Huygens PSF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Hsm</font></b><font color='blue'>]</font> Huygens Surface MTF",
"metadata": {},
"output_type": "display_data",
"text": "[Hsm] Huygens Surface MTF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Htf</font></b><font color='blue'>]</font> Huygens Through Focus MTF",
"metadata": {},
"output_type": "display_data",
"text": "[Htf] Huygens Through Focus MTF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>ISO</font></b><font color='blue'>]</font> ISO Element Drawing",
"metadata": {},
"output_type": "display_data",
"text": "[ISO] ISO Element Drawing"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ibm</font></b><font color='blue'>]</font> Geometric Bitmap Image Analysis",
"metadata": {},
"output_type": "display_data",
"text": "[Ibm] Geometric Bitmap Image Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Igs</font></b><font color='blue'>]</font> Export IGES File",
"metadata": {},
"output_type": "display_data",
"text": "[Igs] Export IGES File"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Iht</font></b><font color='blue'>]</font> Incident Angle vs. Image Height",
"metadata": {},
"output_type": "display_data",
"text": "[Iht] Incident Angle vs. Image Height"
},
{
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"output_type": "display_data",
"text": "[Ilf] Illumination Surface"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ils</font></b><font color='blue'>]</font> Illumination Scan",
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"output_type": "display_data",
"text": "[Ils] Illumination Scan"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ima</font></b><font color='blue'>]</font> Geometric Image Analysis",
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"output_type": "display_data",
"text": "[Ima] Geometric Image Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Imv</font></b><font color='blue'>]</font> IMA/BIM File Viewer",
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"output_type": "display_data",
"text": "[Imv] IMA/BIM File Viewer"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ins</font></b><font color='blue'>]</font> Insert Lens",
"metadata": {},
"output_type": "display_data",
"text": "[Ins] Insert Lens"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Int</font></b><font color='blue'>]</font> Interferogram",
"metadata": {},
"output_type": "display_data",
"text": "[Int] Interferogram"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Jbv</font></b><font color='blue'>]</font> Bitmap File Viewer",
"metadata": {},
"output_type": "display_data",
"text": "[Jbv] Bitmap File Viewer"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>L3d</font></b><font color='blue'>]</font> 3D Layout",
"metadata": {},
"output_type": "display_data",
"text": "[L3d] 3D Layout"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>L3n</font></b><font color='blue'>]</font> NSC 3D Layout",
"metadata": {},
"output_type": "display_data",
"text": "[L3n] NSC 3D Layout"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>LDE</font></b><font color='blue'>]</font> Lens Data Editor",
"metadata": {},
"output_type": "display_data",
"text": "[LDE] Lens Data Editor"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>LSn</font></b><font color='blue'>]</font> NSC Shaded Model Layout",
"metadata": {},
"output_type": "display_data",
"text": "[LSn] NSC Shaded Model Layout"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lac</font></b><font color='blue'>]</font> Last Configuration",
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"output_type": "display_data",
"text": "[Lac] Last Configuration"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lat</font></b><font color='blue'>]</font> Lateral Color",
"metadata": {},
"output_type": "display_data",
"text": "[Lat] Lateral Color"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lay</font></b><font color='blue'>]</font> 2D Layout",
"metadata": {},
"output_type": "display_data",
"text": "[Lay] 2D Layout"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Len</font></b><font color='blue'>]</font> Lens Search",
"metadata": {},
"output_type": "display_data",
"text": "[Len] Lens Search"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lin</font></b><font color='blue'>]</font> Line/Edge Response",
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"output_type": "display_data",
"text": "[Lin] Line/Edge Response"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lok</font></b><font color='blue'>]</font> Lock All Windows",
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"output_type": "display_data",
"text": "[Lok] Lock All Windows"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lon</font></b><font color='blue'>]</font> Longitudinal Aberration",
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"output_type": "display_data",
"text": "[Lon] Longitudinal Aberration"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lsa</font></b><font color='blue'>]</font> Light Source Analysis",
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"output_type": "display_data",
"text": "[Lsa] Light Source Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lsf</font></b><font color='blue'>]</font> FFT Line/Edge Spread",
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"output_type": "display_data",
"text": "[Lsf] FFT Line/Edge Spread"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lsh</font></b><font color='blue'>]</font> Shaded Model Layout",
"metadata": {},
"output_type": "display_data",
"text": "[Lsh] Shaded Model Layout"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lsm</font></b><font color='blue'>]</font> Solid Model Layout",
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"output_type": "display_data",
"text": "[Lsm] Solid Model Layout"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Lwf</font></b><font color='blue'>]</font> Wireframe Layout",
"metadata": {},
"output_type": "display_data",
"text": "[Lwf] Wireframe Layout"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>MCE</font></b><font color='blue'>]</font> Multi-Config Editor",
"metadata": {},
"output_type": "display_data",
"text": "[MCE] Multi-Config Editor"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>MFE</font></b><font color='blue'>]</font> Merit Function Editor",
"metadata": {},
"output_type": "display_data",
"text": "[MFE] Merit Function Editor"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Mfl</font></b><font color='blue'>]</font> Merit Function List",
"metadata": {},
"output_type": "display_data",
"text": "[Mfl] Merit Function List"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Mfo</font></b><font color='blue'>]</font> Make Focal",
"metadata": {},
"output_type": "display_data",
"text": "[Mfo] Make Focal"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Mgm</font></b><font color='blue'>]</font> Geometric MTF Map",
"metadata": {},
"output_type": "display_data",
"text": "[Mgm] Geometric MTF Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Mtf</font></b><font color='blue'>]</font> Modulation TF",
"metadata": {},
"output_type": "display_data",
"text": "[Mtf] Modulation TF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Mth</font></b><font color='blue'>]</font> MTF vs. Field",
"metadata": {},
"output_type": "display_data",
"text": "[Mth] MTF vs. Field"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>NCE</font></b><font color='blue'>]</font> Non-Sequential Editor",
"metadata": {},
"output_type": "display_data",
"text": "[NCE] Non-Sequential Editor"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>New</font></b><font color='blue'>]</font> New File",
"metadata": {},
"output_type": "display_data",
"text": "[New] New File"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Nxc</font></b><font color='blue'>]</font> Next Configuration",
"metadata": {},
"output_type": "display_data",
"text": "[Nxc] Next Configuration"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Obv</font></b><font color='blue'>]</font> NSC Object Viewer",
"metadata": {},
"output_type": "display_data",
"text": "[Obv] NSC Object Viewer"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Off</font></b><font color='blue'>]</font> None",
"metadata": {},
"output_type": "display_data",
"text": "[Off] None"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Opd</font></b><font color='blue'>]</font> Opd Fan",
"metadata": {},
"output_type": "display_data",
"text": "[Opd] Opd Fan"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ope</font></b><font color='blue'>]</font> Open File",
"metadata": {},
"output_type": "display_data",
"text": "[Ope] Open File"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Opt</font></b><font color='blue'>]</font> Optimization",
"metadata": {},
"output_type": "display_data",
"text": "[Opt] Optimization"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pab</font></b><font color='blue'>]</font> Pupil Aberration Fan",
"metadata": {},
"output_type": "display_data",
"text": "[Pab] Pupil Aberration Fan"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pal</font></b><font color='blue'>]</font> Power Field Map",
"metadata": {},
"output_type": "display_data",
"text": "[Pal] Power Field Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pat</font></b><font color='blue'>]</font> ZRD Path Analysis",
"metadata": {},
"output_type": "display_data",
"text": "[Pat] ZRD Path Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pci</font></b><font color='blue'>]</font> Partially Coherent Image Analysis",
"metadata": {},
"output_type": "display_data",
"text": "[Pci] Partially Coherent Image Analysis"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pcs</font></b><font color='blue'>]</font> PSF Cross Section",
"metadata": {},
"output_type": "display_data",
"text": "[Pcs] PSF Cross Section"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Per</font></b><font color='blue'>]</font> Performance Test",
"metadata": {},
"output_type": "display_data",
"text": "[Per] Performance Test"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pha</font></b><font color='blue'>]</font> Pol. Phase Aberration",
"metadata": {},
"output_type": "display_data",
"text": "[Pha] Pol. Phase Aberration"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pmp</font></b><font color='blue'>]</font> Pol. Pupil Map",
"metadata": {},
"output_type": "display_data",
"text": "[Pmp] Pol. Pupil Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pol</font></b><font color='blue'>]</font> Pol. Ray Trace",
"metadata": {},
"output_type": "display_data",
"text": "[Pol] Pol. Ray Trace"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pop</font></b><font color='blue'>]</font> Physical Optics Propagation",
"metadata": {},
"output_type": "display_data",
"text": "[Pop] Physical Optics Propagation"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ppm</font></b><font color='blue'>]</font> Power Pupil Map",
"metadata": {},
"output_type": "display_data",
"text": "[Ppm] Power Pupil Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pre</font></b><font color='blue'>]</font> Prescription Data",
"metadata": {},
"output_type": "display_data",
"text": "[Pre] Prescription Data"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Prf</font></b><font color='blue'>]</font> Preferences",
"metadata": {},
"output_type": "display_data",
"text": "[Prf] Preferences"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ptf</font></b><font color='blue'>]</font> Pol. Transmission Fan",
"metadata": {},
"output_type": "display_data",
"text": "[Ptf] Pol. Transmission Fan"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Pzd</font></b><font color='blue'>]</font> Playback ZRD on Detectors",
"metadata": {},
"output_type": "display_data",
"text": "[Pzd] Playback ZRD on Detectors"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Qad</font></b><font color='blue'>]</font> Quick Adjust",
"metadata": {},
"output_type": "display_data",
"text": "[Qad] Quick Adjust"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Qfo</font></b><font color='blue'>]</font> Quick Focus",
"metadata": {},
"output_type": "display_data",
"text": "[Qfo] Quick Focus"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Raa</font></b><font color='blue'>]</font> Remove All Apertures",
"metadata": {},
"output_type": "display_data",
"text": "[Raa] Remove All Apertures"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ray</font></b><font color='blue'>]</font> Ray Fan",
"metadata": {},
"output_type": "display_data",
"text": "[Ray] Ray Fan"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rcf</font></b><font color='blue'>]</font> Reload Coating File",
"metadata": {},
"output_type": "display_data",
"text": "[Rcf] Reload Coating File"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rdb</font></b><font color='blue'>]</font> Ray Database",
"metadata": {},
"output_type": "display_data",
"text": "[Rdb] Ray Database"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Red</font></b><font color='blue'>]</font> Redo",
"metadata": {},
"output_type": "display_data",
"text": "[Red] Redo"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rel</font></b><font color='blue'>]</font> Relative Illumination",
"metadata": {},
"output_type": "display_data",
"text": "[Rel] Relative Illumination"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Res</font></b><font color='blue'>]</font> Restore From Archive File",
"metadata": {},
"output_type": "display_data",
"text": "[Res] Restore From Archive File"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rev</font></b><font color='blue'>]</font> Reverse Elements",
"metadata": {},
"output_type": "display_data",
"text": "[Rev] Reverse Elements"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rfm</font></b><font color='blue'>]</font> RMS Field Map",
"metadata": {},
"output_type": "display_data",
"text": "[Rfm] RMS Field Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rg4</font></b><font color='blue'>]</font> New Report Graphic 4",
"metadata": {},
"output_type": "display_data",
"text": "[Rg4] New Report Graphic 4"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rg6</font></b><font color='blue'>]</font> New Report Graphic 6",
"metadata": {},
"output_type": "display_data",
"text": "[Rg6] New Report Graphic 6"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rmf</font></b><font color='blue'>]</font> RMS vs. Focus",
"metadata": {},
"output_type": "display_data",
"text": "[Rmf] RMS vs. Focus"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rml</font></b><font color='blue'>]</font> Refresh Macro List",
"metadata": {},
"output_type": "display_data",
"text": "[Rml] Refresh Macro List"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rms</font></b><font color='blue'>]</font> RMS vs. Field",
"metadata": {},
"output_type": "display_data",
"text": "[Rms] RMS vs. Field"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rmw</font></b><font color='blue'>]</font> RMS vs. Wavelength",
"metadata": {},
"output_type": "display_data",
"text": "[Rmw] RMS vs. Wavelength"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rtc</font></b><font color='blue'>]</font> Ray Trace Control",
"metadata": {},
"output_type": "display_data",
"text": "[Rtc] Ray Trace Control"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rtr</font></b><font color='blue'>]</font> Ray Trace",
"metadata": {},
"output_type": "display_data",
"text": "[Rtr] Ray Trace"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rva</font></b><font color='blue'>]</font> Remove Variables",
"metadata": {},
"output_type": "display_data",
"text": "[Rva] Remove Variables"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Rxl</font></b><font color='blue'>]</font> Refresh Extensions List",
"metadata": {},
"output_type": "display_data",
"text": "[Rxl] Refresh Extensions List"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sag</font></b><font color='blue'>]</font> Sag Table",
"metadata": {},
"output_type": "display_data",
"text": "[Sag] Sag Table"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sas</font></b><font color='blue'>]</font> Save As",
"metadata": {},
"output_type": "display_data",
"text": "[Sas] Save As"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sav</font></b><font color='blue'>]</font> Save File",
"metadata": {},
"output_type": "display_data",
"text": "[Sav] Save File"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sca</font></b><font color='blue'>]</font> Scale Lens",
"metadata": {},
"output_type": "display_data",
"text": "[Sca] Scale Lens"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Scc</font></b><font color='blue'>]</font> Surface Curvature Cross Section",
"metadata": {},
"output_type": "display_data",
"text": "[Scc] Surface Curvature Cross Section"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Scv</font></b><font color='blue'>]</font> Surface Curvature",
"metadata": {},
"output_type": "display_data",
"text": "[Scv] Surface Curvature"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sdi</font></b><font color='blue'>]</font> Seidel Diagram",
"metadata": {},
"output_type": "display_data",
"text": "[Sdi] Seidel Diagram"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sei</font></b><font color='blue'>]</font> Seidel Coefficients",
"metadata": {},
"output_type": "display_data",
"text": "[Sei] Seidel Coefficients"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sff</font></b><font color='blue'>]</font> Full Field Spot",
"metadata": {},
"output_type": "display_data",
"text": "[Sff] Full Field Spot"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sfv</font></b><font color='blue'>]</font> Scatter Function Viewer",
"metadata": {},
"output_type": "display_data",
"text": "[Sfv] Scatter Function Viewer"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sim</font></b><font color='blue'>]</font> Image Simulation",
"metadata": {},
"output_type": "display_data",
"text": "[Sim] Image Simulation"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sld</font></b><font color='blue'>]</font> Slider",
"metadata": {},
"output_type": "display_data",
"text": "[Sld] Slider"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sma</font></b><font color='blue'>]</font> Spot Matrix",
"metadata": {},
"output_type": "display_data",
"text": "[Sma] Spot Matrix"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Smc</font></b><font color='blue'>]</font> Spot Matrix Config",
"metadata": {},
"output_type": "display_data",
"text": "[Smc] Spot Matrix Config"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Smf</font></b><font color='blue'>]</font> Surface MTF",
"metadata": {},
"output_type": "display_data",
"text": "[Smf] Surface MTF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Spc</font></b><font color='blue'>]</font> Surface Phase Cross Section",
"metadata": {},
"output_type": "display_data",
"text": "[Spc] Surface Phase Cross Section"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Spt</font></b><font color='blue'>]</font> Spot Diagram",
"metadata": {},
"output_type": "display_data",
"text": "[Spt] Spot Diagram"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Spv</font></b><font color='blue'>]</font> Scatter Polar Plot",
"metadata": {},
"output_type": "display_data",
"text": "[Spv] Scatter Polar Plot"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Srp</font></b><font color='blue'>]</font> Surface Phase",
"metadata": {},
"output_type": "display_data",
"text": "[Srp] Surface Phase"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Srs</font></b><font color='blue'>]</font> Surface Sag",
"metadata": {},
"output_type": "display_data",
"text": "[Srs] Surface Sag"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ssc</font></b><font color='blue'>]</font> Surface Sag Cross Section",
"metadata": {},
"output_type": "display_data",
"text": "[Ssc] Surface Sag Cross Section"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Ssg</font></b><font color='blue'>]</font> System Summary Graphic",
"metadata": {},
"output_type": "display_data",
"text": "[Ssg] System Summary Graphic"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Stf</font></b><font color='blue'>]</font> Though Focus Spot",
"metadata": {},
"output_type": "display_data",
"text": "[Stf] Though Focus Spot"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sur</font></b><font color='blue'>]</font> Surface Data",
"metadata": {},
"output_type": "display_data",
"text": "[Sur] Surface Data"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Sys</font></b><font color='blue'>]</font> System Data",
"metadata": {},
"output_type": "display_data",
"text": "[Sys] System Data"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>TDE</font></b><font color='blue'>]</font> Tolerance Data Editor",
"metadata": {},
"output_type": "display_data",
"text": "[TDE] Tolerance Data Editor"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tde</font></b><font color='blue'>]</font> Tilt/Decenter Elements",
"metadata": {},
"output_type": "display_data",
"text": "[Tde] Tilt/Decenter Elements"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tfg</font></b><font color='blue'>]</font> Through Focus GTF",
"metadata": {},
"output_type": "display_data",
"text": "[Tfg] Through Focus GTF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tfm</font></b><font color='blue'>]</font> Through Focus MTF",
"metadata": {},
"output_type": "display_data",
"text": "[Tfm] Through Focus MTF"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tls</font></b><font color='blue'>]</font> Tolerance List",
"metadata": {},
"output_type": "display_data",
"text": "[Tls] Tolerance List"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tol</font></b><font color='blue'>]</font> Tolerancing",
"metadata": {},
"output_type": "display_data",
"text": "[Tol] Tolerancing"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tpf</font></b><font color='blue'>]</font> Test Plate Fit",
"metadata": {},
"output_type": "display_data",
"text": "[Tpf] Test Plate Fit"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tpl</font></b><font color='blue'>]</font> Test Plate Lists",
"metadata": {},
"output_type": "display_data",
"text": "[Tpl] Test Plate Lists"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tra</font></b><font color='blue'>]</font> Pol. Transmission",
"metadata": {},
"output_type": "display_data",
"text": "[Tra] Pol. Transmission"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Trw</font></b><font color='blue'>]</font> Transmission vs. Wavelength",
"metadata": {},
"output_type": "display_data",
"text": "[Trw] Transmission vs. Wavelength"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Tsm</font></b><font color='blue'>]</font> Tolerance Summary",
"metadata": {},
"output_type": "display_data",
"text": "[Tsm] Tolerance Summary"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Un2</font></b><font color='blue'>]</font> Universal Plot 2D",
"metadata": {},
"output_type": "display_data",
"text": "[Un2] Universal Plot 2D"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Und</font></b><font color='blue'>]</font> Undo",
"metadata": {},
"output_type": "display_data",
"text": "[Und] Undo"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Uni</font></b><font color='blue'>]</font> Universal Plot",
"metadata": {},
"output_type": "display_data",
"text": "[Uni] Universal Plot"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Unl</font></b><font color='blue'>]</font> Unlock All Windows",
"metadata": {},
"output_type": "display_data",
"text": "[Unl] Unlock All Windows"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Upa</font></b><font color='blue'>]</font> Update All",
"metadata": {},
"output_type": "display_data",
"text": "[Upa] Update All"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Upd</font></b><font color='blue'>]</font> Update",
"metadata": {},
"output_type": "display_data",
"text": "[Upd] Update"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Vig</font></b><font color='blue'>]</font> Vignetting Plot",
"metadata": {},
"output_type": "display_data",
"text": "[Vig] Vignetting Plot"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Vop</font></b><font color='blue'>]</font> Visual Optimization",
"metadata": {},
"output_type": "display_data",
"text": "[Vop] Visual Optimization"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Vra</font></b><font color='blue'>]</font> Make All Radii Variable",
"metadata": {},
"output_type": "display_data",
"text": "[Vra] Make All Radii Variable"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Vth</font></b><font color='blue'>]</font> Make All Thickness Variable",
"metadata": {},
"output_type": "display_data",
"text": "[Vth] Make All Thickness Variable"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Wav</font></b><font color='blue'>]</font> Wavelength Data",
"metadata": {},
"output_type": "display_data",
"text": "[Wav] Wavelength Data"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Wfm</font></b><font color='blue'>]</font> Wavefront Map",
"metadata": {},
"output_type": "display_data",
"text": "[Wfm] Wavefront Map"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Xdi</font></b><font color='blue'>]</font> Extended Diffraction Image Ana",
"metadata": {},
"output_type": "display_data",
"text": "[Xdi] Extended Diffraction Image Ana"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Xis</font></b><font color='blue'>]</font> Export IGES/STEP/SAT FIle",
"metadata": {},
"output_type": "display_data",
"text": "[Xis] Export IGES/STEP/SAT FIle"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Xse</font></b><font color='blue'>]</font> Extended Source Encircled",
"metadata": {},
"output_type": "display_data",
"text": "[Xse] Extended Source Encircled"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Yni</font></b><font color='blue'>]</font> YNI Contributions",
"metadata": {},
"output_type": "display_data",
"text": "[Yni] YNI Contributions"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Yyb</font></b><font color='blue'>]</font> Y-Ybar",
"metadata": {},
"output_type": "display_data",
"text": "[Yyb] Y-Ybar"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Zat</font></b><font color='blue'>]</font> Zernike Annular Terms",
"metadata": {},
"output_type": "display_data",
"text": "[Zat] Zernike Annular Terms"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Zbb</font></b><font color='blue'>]</font> Export Zemax Black Box Data",
"metadata": {},
"output_type": "display_data",
"text": "[Zbb] Export Zemax Black Box Data"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Zex</font></b><font color='blue'>]</font> ZEMAX Extensions",
"metadata": {},
"output_type": "display_data",
"text": "[Zex] ZEMAX Extensions"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Zfr</font></b><font color='blue'>]</font> Zernike Fringe Terms",
"metadata": {},
"output_type": "display_data",
"text": "[Zfr] Zernike Fringe Terms"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Zpd</font></b><font color='blue'>]</font> Zemax Part Designer",
"metadata": {},
"output_type": "display_data",
"text": "[Zpd] Zemax Part Designer"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Zpl</font></b><font color='blue'>]</font> Edit/Run ZPL Macros",
"metadata": {},
"output_type": "display_data",
"text": "[Zpl] Edit/Run ZPL Macros"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Zst</font></b><font color='blue'>]</font> Zernike Standard Terms",
"metadata": {},
"output_type": "display_data",
"text": "[Zst] Zernike Standard Terms"
},
{
"html": "<font color='blue'>[</font><b><font color='magenta'>Zvf</font></b><font color='blue'>]</font> Zernike Coefficients vs. Field",
"metadata": {},
"output_type": "display_data",
"text": "[Zvf] Zernike Coefficients vs. Field"
},
{
"html": "<font color='red'><b>Total number of buttons = </font></b><font color='green'><b>218</font></b><font color='red'><b></font></b>",
"metadata": {},
"output_type": "display_data",
"text": "Total number of buttons = 218"
}
],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": "Test of GetTextFile:\n-------------------\n\nTest of text file dump through ipz [ipzGetTextWindow() internally uses the data item `GetTextFile`]\n\nSummary:\n\n\n| Code | Result | Comment |\n|----------|---------------|-----------------------|\n| 'Pre' | Fail | Output ray trace data |\n| 'Ray' | Fail | Ouput ray trace data |\n| 'LDE' | Fail | Output ray trace data |\n| 'Gen' | Fail | Output ray trace data |\n| 'Sys' | Fail | Output ray trace data |\n| 'Rtr' | Pass | |"
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.ipzGetTextWindow('Pre')",
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": "Ray Trace Data\n\nFile : C:\\Users\\Indranil\\Documents\\ZEMAX\\Samples\\Sequential\\Objectives\\Cooke 40 degree field.zmx\nTitle: A SIMPLE COOKE TRIPLET.\nDate : 3/21/2014\n\n\nUnits :\t Millimeters\t\nWavelength :\t 0.550000\t \ufffdm\t\nCoordinates :\t Local\nDirection cosines are after refraction or reflection from the surface or object.\nAngles are in degrees.\n\nNormalized X Field Coord (Hx) :\t 0.0000000000\t\nNormalized Y Field Coord (Hy) :\t 0.0000000000\t\nNormalized X Pupil Coord (Px) :\t 0.0000000000\t\nNormalized Y Pupil Coord (Py) :\t 1.0000000000\t\n\nReal Ray Trace Data:\n\nSurf\t X-coordinate\t Y-coordinate\t Z-coordinate\t X-cosine\t Y-cosine\t Z-cosine\t X-normal\t Y-normal\t Z-normal\t Angle in\t Path length\t Comment\t\nOBJ\t Infinity\t Infinity\t Infinity\t 0.0000000000\t 0.0000000000\t 1.0000000000\t - - - - - \n 1\t 0.0000000000E+000\t 5.0000000000E+000\t 5.7534969034E-001\t 0.0000000000\t -0.0885747997\t 0.9960695281\t 0.0000000000\t 0.2271323955\t -0.9738638893\t 13.128302445\t 5.7534969034E-001\t \n 2\t 0.0000000000E+000\t 4.7636776412E+000\t -2.6038736886E-002\t 0.0000000000\t -0.1505837631\t 0.9885972538\t -0.0000000000\t -0.0109318728\t -0.9999402453\t 5.707984312\t 2.6680541144E+000\t \n 3\t 0.0000000000E+000\t 3.8971161977E+000\t -3.4452850939E-001\t 0.0000000000\t -0.0230902110\t 0.9997333855\t -0.0000000000\t -0.1754408485\t -0.9844899739\t 18.765071772\t 5.7546804884E+000\t \n 4\t 0.0000000000E+000\t 3.8575166425E+000\t 3.7003289831E-001\t 0.0000000000\t 0.0838674405\t 0.9964769202\t 0.0000000000\t 0.1901010776\t -0.9817645239\t 9.635593801\t 1.7149932167E+000\t \n 5\t 0.0000000000E+000\t 4.2356679447E+000\t 1.1265538705E-001\t 0.0000000000\t 0.0311718209\t 0.9995140407\t 0.0000000000\t 0.0531560799\t -0.9985862162\t 7.857956564\t 4.5089166922E+000\t \n 6\t 0.0000000000E+000\t 4.3082649428E+000\t -5.1162172527E-001\t 0.0000000000\t -0.1004375125\t 0.9949433683\t -0.0000000000\t -0.2342042428\t -0.9721874164\t 11.758417117\t 2.3289302930E+000\t \n 7\t 0.0000000000E+000\t -4.1719166457E-003\t 0.0000000000E+000\t 0.0000000000\t -0.1004375125\t 0.9949433683\t 0.0000000000\t 0.0000000000\t -1.0000000000\t 5.764364940\t 4.2936515974E+001\t \n\nParaxial Ray Trace Data:\n\nSurf\t X-coordinate\t Y-coordinate\t Z-coordinate\t X-cosine\t Y-cosine\t Z-cosine\t X-normal\t Y-normal\t Z-normal\t Angle in\t Path length\t Comment\t\nOBJ\t Infinity\t Infinity\t Infinity\t 0.0000000000\t 0.0000000000\t 1.0000000000\t \n 1\t 0.0000000000E+000\t 5.0000000000E+000\t 0.0000000000E+000\t 0.0000000000\t -0.0868234237\t 0.9962237164\t \n 2\t 0.0000000000E+000\t 4.7159737333E+000\t 0.0000000000E+000\t 0.0000000000\t -0.1465528591\t 0.9892028404\t \n 3\t 0.0000000000E+000\t 3.8259401086E+000\t 0.0000000000E+000\t 0.0000000000\t -0.0250813180\t 0.9996854143\t \n 4\t 0.0000000000E+000\t 3.8008515360E+000\t 0.0000000000E+000\t 0.0000000000\t 0.0758605031\t 0.9971184403\t \n 5\t 0.0000000000E+000\t 4.1622613712E+000\t 0.0000000000E+000\t 0.0000000000\t 0.0268347204\t 0.9996398840\t \n 6\t 0.0000000000E+000\t 4.2415080334E+000\t 0.0000000000E+000\t 0.0000000000\t -0.0995037200\t 0.9950371901\t \n 7\t 0.0000000000E+000\t 2.0729981239E-002\t 0.0000000000E+000\t 0.0000000000\t -0.0995037200\t 0.9950371901\t \n"
}
],
"prompt_number": 9
},
{
"cell_type": "markdown",
"metadata": {},
"source": "Test of GetMetaFile:\n-------------------\n\nNote that ipzCaptureWindow2() internally uses `GetMetaFile`"
},
{
"cell_type": "markdown",
"metadata": {},
"source": "Status:\n\n\n| Code | Result | Comment |\n|----------|---------------|-----------------------|\n| 'Lay' | Pass | |\n| 'L3d' | Fail | Outputs layout (Lay) |\n| 'Spt' | Fail | Outputs layout (Lay) |\n| 'Ray' | Fail | Outputs layout (Lay) |\n| 'Hps' | Fail | Outputs layout (Lay) |"
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.ipzCaptureWindow2('Spt') # Spot diagram",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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9G7T4AT9+xhgb2grE0zRpssMO22yjo5MixSMeMc64tJ4Sp7q2n5BCoUAgECA8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\nu+++O/LfeosJTBPyeQ+O48HjUdOE7uGBzSZ8/32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"text": "<IPython.core.display.Image at 0x84e8f28>"
}
],
"prompt_number": 10
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zDDEClose()",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 11,
"text": "0"
}
],
"prompt_number": 11
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": "Validate the same operations against ZEMAX 13"
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zDDEInit()",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 12,
"text": "0"
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zGetRefresh()",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 13,
"text": "0"
}
],
"prompt_number": 13
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zGetVersion() ",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 14,
"text": "140124"
}
],
"prompt_number": 14
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zGetFile()",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 15,
"text": "'C:\\\\Users\\\\Indranil\\\\Documents\\\\ZEMAX\\\\Samples\\\\Sequential\\\\Objectives\\\\Cooke 40 degree field.zmx'"
}
],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.ipzGetTextWindow('Pre')",
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": "System/Prescription Data\n\nFile : C:\\Users\\Indranil\\Documents\\ZEMAX\\Samples\\Sequential\\Objectives\\Cooke 40 degree field.zmx\nTitle: A SIMPLE COOKE TRIPLET.\nDate : 3/21/2014\n\n\nLENS NOTES:\n\nNotes...\n \n \nGENERAL LENS DATA:\n\nSurfaces : 7\nStop : 4\nSystem Aperture : Entrance Pupil Diameter = 10\nGlass Catalogs : SCHOTT\nRay Aiming : Off\nApodization : Uniform, factor = 0.00000E+000\nTemperature (C) : 2.00000E+001\nPressure (ATM) : 1.00000E+000\nAdjust Index Data To Environment : Off\nEffective Focal Length : 50 (in air at system temperature and pressure)\nEffective Focal Length : 50 (in image space)\nBack Focal Length : 42.41508\nTotal Track : 60.17675\nImage Space F/# : 5\nParaxial Working F/# : 5\nWorking F/# : 4.97822\nImage Space NA : 0.09950372\nObject Space NA : 5e-010\nStop Radius : 3.800852\nParaxial Image Height : 18.19851\nParaxial Magnification : 0\nEntrance Pupil Diameter : 10\nEntrance Pupil Position : 11.51216\nExit Pupil Diameter : 10.23373\nExit Pupil Position : -50.96134\nField Type : Angle in degrees\nMaximum Radial Field : 20\nPrimary Wavelength : 0.55 \ufffdm\nLens Units : Millimeters\nAngular Magnification : 0.977161\n\nFields : 3\nField Type : Angle in degrees\n # X-Value Y-Value Weight\n 1 0.000000 0.000000 1.000000\n 2 0.000000 14.000000 1.000000\n 3 0.000000 20.000000 1.000000\n\nVignetting Factors\n # VDX VDY VCX VCY VAN\n 1 0.000000 0.000000 0.000000 0.000000 0.000000\n 2 0.000000 0.000000 0.000000 0.000000 0.000000\n 3 0.000000 0.000000 0.000000 0.000000 0.000000\n\nWavelengths : 3\nUnits: \ufffdm\n # Value Weight\n 1 0.480000 0.800000\n 2 0.550000 1.000000\n 3 0.650000 0.800000\n\nSURFACE DATA SUMMARY:\n\nSurf Type Radius Thickness Glass Diameter Conic Comment\n OBJ STANDARD Infinity Infinity 0 0 \n 1 STANDARD 22.01359 3.258956 SK16 19 0 \n 2 STANDARD -435.7604 6.007551 19 0 \n 3 STANDARD -22.21328 0.9999746 F2 10 0 \n STO STANDARD 20.29192 4.750409 10 0 \n 5 STANDARD 79.6836 2.952076 SK16 15 0 \n 6 STANDARD -18.39533 42.20778 15 0 \n IMA STANDARD Infinity 36.34532 0 \n\nSURFACE DATA DETAIL:\n\nSurface OBJ STANDARD \n\nSurface 1 STANDARD \nCoating : AR\nAperture : Floating Aperture\nMaximum Radius : 9.5\n\nSurface 2 STANDARD \nCoating : AR\nAperture : Floating Aperture\nMaximum Radius : 9.5\n\nSurface 3 STANDARD \nCoating : AR\nAperture : Floating Aperture\nMaximum Radius : 5\n\nSurface STO STANDARD \nCoating : AR\nAperture : Floating Aperture\nMaximum Radius : 5\n\nSurface 5 STANDARD \nCoating : AR\nAperture : Floating Aperture\nMaximum Radius : 7.5\n\nSurface 6 STANDARD \nCoating : AR\nAperture : Floating Aperture\nMaximum Radius : 7.5\n\nSurface IMA STANDARD \n\nEDGE THICKNESS DATA:\n\nSurf Edge\n 1 1.000000\n 2 5.541077\n 3 2.195669\n STO 4.478499\n 5 0.999971\n 6 43.806141\n IMA 0.000000\n\nSOLVE AND VARIABLE DATA:\n\n Curvature of 1 : Variable\n Thickness of 1 : Variable\n Semi Diameter 1 : Fixed\n Curvature of 2 : Variable\n Thickness of 2 : Variable\n Semi Diameter 2 : Fixed\n Curvature of 3 : Variable\n Thickness of 3 : Variable\n Semi Diameter 3 : Fixed\n Curvature of 4 : Variable\n Thickness of 4 : Variable\n Semi Diameter 4 : Fixed\n Curvature of 5 : Variable\n Thickness of 5 : Variable\n Semi Diameter 5 : Fixed\n Curvature of 6 : Solve, Marginal ray exit angle = -0.1\n Thickness of 6 : Variable\n Semi Diameter 6 : Fixed\n\nINDEX OF REFRACTION DATA:\n\nSystem Temperature: 20.0000 Celsius\nSystem Pressure : 1.0000 Atmospheres\nAbsolute air index: 1.000273 at wavelength 0.550000 \ufffdm\nIndex data is relative to air at the system temperature and pressure.\nWavelengths are measured in air at the system temperature and pressure.\n\nSurf Glass Temp Pres 0.480000 0.550000 0.650000\n 0 20.00 1.00 1.00000000 1.00000000 1.00000000\n 1 SK16 20.00 1.00 1.62813927 1.62260769 1.61752112 \n 2 20.00 1.00 1.00000000 1.00000000 1.00000000\n 3 F2 20.00 1.00 1.63309920 1.62365512 1.61542246 lead containing glass type \n 4 20.00 1.00 1.00000000 1.00000000 1.00000000\n 5 SK16 20.00 1.00 1.62813927 1.62260769 1.61752112 \n 6 20.00 1.00 1.00000000 1.00000000 1.00000000\n 7 20.00 1.00 1.00000000 1.00000000 1.00000000\n\nTHERMAL COEFFICIENT OF EXPANSION DATA:\n\nSurf Glass TCE *10E-6\n 0 0.00000000\n 1 SK16 6.30000000 \n 2 0.00000000\n 3 F2 8.20000000 lead containing glass type \n 4 0.00000000\n 5 SK16 6.30000000 \n 6 0.00000000\n 7 0.00000000\n\nGLOBAL VERTEX COORDINATES, ORIENTATIONS, AND ROTATION/OFFSET MATRICES:\n\nReference Surface: 1\n\nSurf R11 R12 R13 X\n R21 R22 R23 Y\n R31 R32 R33 Z\n\n 1 1.0000000000 0.0000000000 0.0000000000 0.000000000E+000 \n 0.0000000000 1.0000000000 0.0000000000 0.000000000E+000\n 0.0000000000 0.0000000000 1.0000000000 0.000000000E+000\n\n 2 1.0000000000 0.0000000000 0.0000000000 0.000000000E+000 \n 0.0000000000 1.0000000000 0.0000000000 0.000000000E+000\n 0.0000000000 0.0000000000 1.0000000000 3.258955830E+000\n\n 3 1.0000000000 0.0000000000 0.0000000000 0.000000000E+000 \n 0.0000000000 1.0000000000 0.0000000000 0.000000000E+000\n 0.0000000000 0.0000000000 1.0000000000 9.266506930E+000\n\n 4 1.0000000000 0.0000000000 0.0000000000 0.000000000E+000 \n 0.0000000000 1.0000000000 0.0000000000 0.000000000E+000\n 0.0000000000 0.0000000000 1.0000000000 1.026648150E+001\n\n 5 1.0000000000 0.0000000000 0.0000000000 0.000000000E+000 \n 0.0000000000 1.0000000000 0.0000000000 0.000000000E+000\n 0.0000000000 0.0000000000 1.0000000000 1.501689043E+001\n\n 6 1.0000000000 0.0000000000 0.0000000000 0.000000000E+000 \n 0.0000000000 1.0000000000 0.0000000000 0.000000000E+000\n 0.0000000000 0.0000000000 1.0000000000 1.796896607E+001\n\n 7 1.0000000000 0.0000000000 0.0000000000 0.000000000E+000 \n 0.0000000000 1.0000000000 0.0000000000 0.000000000E+000\n 0.0000000000 0.0000000000 1.0000000000 6.017674617E+001\n\n\nGLOBAL Surface CENTER OF CURVATURE POINTS:\n\nReference Surface: 1\n\nSurf X Y Z\n 1 0.0000000000 0.0000000000 22.0135925084 \n 2 0.0000000000 0.0000000000 -432.5014803383 \n 3 0.0000000000 0.0000000000 -12.9467702523 \n 4 0.0000000000 0.0000000000 30.5584056223 \n 5 0.0000000000 0.0000000000 94.7004929775 \n 6 0.0000000000 0.0000000000 -0.4263665360 \n 7 - - - \n\nELEMENT VOLUME DATA:\n\nFor centered elements with plane or spherical circular faces, exact\nvolumes are computed by assuming edges are squared up to the larger\nof the front and back radial aperture.\n\nFor all other elements, approximate volumes are numerically integrated\nto 0.1% accuracy. Zero volume means the volume cannot be accurately computed.\n\nSingle elements that are duplicated in the Lens Data Editor\nfor ray tracing purposes may be listed more than once yielding\nincorrect total mass estimates.\n\n Volume cc Density g/cc Mass g\nElement surf 1 to 2 0.609012 3.580000 2.180262\nElement surf 3 to 4 0.125267 3.599000 0.450837\nElement surf 5 to 6 0.351353 3.580000 1.257845\nTotal Mass: 3.888945\n\nF/# DATA:\n\nF/# calculations consider vignetting factors and ignore surface apertures.\n\n Wavelength: 0.480000 0.550000 0.650000 \n# Field Tan Sag Tan Sag Tan Sag\n1 0.00 (deg): 4.9801 4.9801 4.9782 4.9782 4.9825 4.9825\n2 14.00 (deg): 5.3344 5.1149 5.3350 5.1130 5.3419 5.1174\n3 20.00 (deg): 5.6915 5.2853 5.7012 5.2837 5.7162 5.2885\n\nCARDINAL POINTS:\n\nObject space positions are measured with respect to surface 1.\nImage space positions are measured with respect to the image surface.\nThe index in both the object space and image space is considered.\n\n Object Space Image Space\nW = 0.480000\nFocal Length : -49.988055 49.988055\nFocal Planes : -37.301925 0.196773\nPrincipal Planes : 12.686131 -49.791282\nAnti-Principal Planes : -87.289980 50.184828\nNodal Planes : 12.686131 -49.791282\nAnti-Nodal Planes : -87.289980 50.184828\n\nW = 0.550000(Primary)\nFocal Length : -50.000000 50.000000\nFocal Planes : -37.345894 0.207300\nPrincipal Planes : 12.654105 -49.792700\nAnti-Principal Planes : -87.345894 50.207299\nNodal Planes : 12.654105 -49.792700\nAnti-Nodal Planes : -87.345894 50.207299\n\nW = 0.650000\nFocal Length : -50.066098 50.066098\nFocal Planes : -37.439691 0.273983\nPrincipal Planes : 12.626407 -49.792116\nAnti-Principal Planes : -87.505790 50.340081\nNodal Planes : 12.626407 -49.792116\nAnti-Nodal Planes : -87.505790 50.340081\n\nPHYSICAL OPTICS PROPAGATION SETTINGS SUMMARY:\n\n OBJ STANDARD \nUse Rays To Propagate To Next Surface : Off\nRecompute Pilot Beam : Off\nDo Not Rescale Beam Size Using Ray Data: Off\nUse Angular Spectrum Propagator : Off\nUse X-Axis ReferenceOff\nOutput Pilot Radius : Best Fit\n 1 STANDARD \nUse Rays To Propagate To Next Surface : Off\nRecompute Pilot Beam : Off\nDo Not Rescale Beam Size Using Ray Data: Off\nUse Angular Spectrum Propagator : Off\nUse X-Axis ReferenceOff\nOutput Pilot Radius : Best Fit\n 2 STANDARD \nUse Rays To Propagate To Next Surface : Off\nRecompute Pilot Beam : Off\nDo Not Rescale Beam Size Using Ray Data: Off\nUse Angular Spectrum Propagator : Off\nUse X-Axis ReferenceOff\nOutput Pilot Radius : Best Fit\n 3 STANDARD \nUse Rays To Propagate To Next Surface : Off\nRecompute Pilot Beam : Off\nDo Not Rescale Beam Size Using Ray Data: Off\nUse Angular Spectrum Propagator : Off\nUse X-Axis ReferenceOff\nOutput Pilot Radius : Best Fit\n STO STANDARD \nUse Rays To Propagate To Next Surface : Off\nRecompute Pilot Beam : Off\nDo Not Rescale Beam Size Using Ray Data: Off\nUse Angular Spectrum Propagator : Off\nUse X-Axis ReferenceOff\nOutput Pilot Radius : Best Fit\n 5 STANDARD \nUse Rays To Propagate To Next Surface : Off\nRecompute Pilot Beam : Off\nDo Not Rescale Beam Size Using Ray Data: Off\nUse Angular Spectrum Propagator : Off\nUse X-Axis ReferenceOff\nOutput Pilot Radius : Best Fit\n 6 STANDARD \nUse Rays To Propagate To Next Surface : Off\nRecompute Pilot Beam : Off\nDo Not Rescale Beam Size Using Ray Data: Off\nUse Angular Spectrum Propagator : Off\nUse X-Axis ReferenceOff\nOutput Pilot Radius : Best Fit\n IMA STANDARD \nUse Rays To Propagate To Next Surface : Off\nRecompute Pilot Beam : Off\nDo Not Rescale Beam Size Using Ray Data: Off\nUse Angular Spectrum Propagator : Off\nUse X-Axis ReferenceOff\nOutput Pilot Radius : Best Fit\n\nFILES USED:\n\nZemax File\n C:\\Users\\Indranil\\Documents\\ZEMAX\\Samples\\Sequential\\Objectives\\Cooke 40 degree field.zmx\nSession File\n C:\\Users\\Indranil\\Documents\\ZEMAX\\Samples\\Sequential\\Objectives\\Cooke 40 degree field.SES\nLens Configuration File\n C:\\Users\\Indranil\\Documents\\ZEMAX\\Samples\\Sequential\\Objectives\\Cooke 40 degree field.CFG\nGlass Catalogs\n C:\\Users\\Indranil\\Documents\\ZEMAX\\GLASSCAT\\SCHOTT.AGF\nCoating Data\n C:\\Users\\Indranil\\Documents\\ZEMAX\\COATINGS\\COATING.DAT\nABg Data\n C:\\Users\\Indranil\\Documents\\Zemax\\ABG_DATA\\ABG_DATA.DAT\n"
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"text": "Listing of Ray Fan Data\n\nFile : C:\\Users\\Indranil\\Documents\\ZEMAX\\Samples\\Sequential\\Objectives\\Cooke 40 degree field.zmx\nTitle: A SIMPLE COOKE TRIPLET.\nDate : 3/21/2014\n\n\nSurface: Image\nUnits are \ufffdm.\nAberration data is measured in image plane local coordinates.\nTangential data is y aberration as a function of Py.\nSagittal data is x aberration as a function of Px.\n\nTangential fan, field number 3 = 20.00 (deg)\n\n Pupil 0.480000 0.550000 0.650000\n -1.000 -4.840175 -17.078945 -34.048543\n -0.950 1.343535 -10.237055 -26.281209\n -0.900 6.402248 -4.520706 -19.644505\n -0.850 10.457366 0.190561 -14.018577\n -0.800 13.617425 4.004479 -9.296174\n -0.750 15.979718 7.017653 -5.381076\n -0.700 17.631675 9.316926 -2.186745\n -0.650 18.652071 10.980560 0.364847\n -0.600 19.112070 12.079279 2.344239\n -0.550 19.076155 12.677174 3.815382\n -0.500 18.602949 12.832517 4.836442\n -0.450 17.745950 12.598495 5.460522\n -0.400 16.554205 12.023865 5.736318\n -0.350 15.072917 11.153563 5.708717\n -0.300 13.344019 10.029265 5.419356\n -0.250 11.406697 8.689913 4.907142\n -0.200 9.297896 7.172209 4.208745\n -0.150 7.052798 5.511097 3.359075\n -0.100 4.705291 3.740221 2.391740\n -0.050 2.288424 1.892384 1.339498\n 0.000 -0.165131 -0.000000 0.234712\n 0.050 -2.622630 -1.904451 -0.890198\n 0.100 -5.050775 -3.787951 -2.002288\n 0.150 -7.415239 -5.616467 -3.067609\n 0.200 -9.680154 -7.354441 -4.050703\n 0.250 -11.807577 -8.964257 -4.914069\n 0.300 -13.756917 -10.405675 -5.617597\n 0.350 -15.484321 -11.635209 -6.117954\n 0.400 -16.942006 -12.605470 -6.367915\n 0.450 -18.077525 -13.264425 -6.315634\n 0.500 -18.832964 -13.554600 -5.903843\n 0.550 -19.144050 -13.412183 -5.068954\n 0.600 -18.939155 -12.766029 -3.740069\n 0.650 -18.138185 -11.536550 -1.837856\n 0.700 -16.651328 -9.634455 0.726696\n 0.750 -14.377642 -6.959333 4.053711\n 0.800 -11.203453 -3.398048 8.256031\n 0.850 -7.000538 1.177093 13.461055\n 0.900 -1.624051 6.910433 19.812844\n 0.950 5.089855 13.965360 27.474533\n 1.000 13.326748 22.527060 36.631100\n\nSagittal fan, field number 3 = 20.00 (deg)\n\n Pupil 0.480000 0.550000 0.650000\n -1.000 15.323466 16.911482 12.061917\n -0.950 16.517248 17.707398 12.857919\n -0.900 17.104827 17.955807 13.151449\n -0.850 17.212396 17.776894 13.057990\n -0.800 16.944834 17.270161 12.672842\n -0.750 16.388941 16.517567 12.074197\n -0.700 15.616147 15.586171 11.325721\n -0.650 14.684790 14.530344 10.478716\n -0.600 13.642044 13.393640 9.573946\n -0.550 12.525549 12.210387 8.643192\n -0.500 11.364818 11.007046 7.710576\n -0.450 10.182428 9.803370 6.793695\n -0.400 8.995064 8.613416 5.904604\n -0.350 7.814419 7.446413 5.050665\n -0.300 6.647982 6.307535 4.235296\n -0.250 5.499742 5.198572 3.458629\n -0.200 4.370810 4.118536 2.718095\n -0.150 3.259982 3.064206 2.008960\n -0.100 2.164260 2.030629 1.324803\n -0.050 1.079326 1.011579 0.657970\n 0.000 -0.000000 -0.000000 -0.000000\n 0.050 -1.079326 -1.011579 -0.657970\n 0.100 -2.164260 -2.030629 -1.324803\n 0.150 -3.259982 -3.064206 -2.008960\n 0.200 -4.370810 -4.118536 -2.718095\n 0.250 -5.499742 -5.198572 -3.458629\n 0.300 -6.647982 -6.307535 -4.235296\n 0.350 -7.814419 -7.446413 -5.050665\n 0.400 -8.995064 -8.613416 -5.904604\n 0.450 -10.182428 -9.803370 -6.793695\n 0.500 -11.364818 -11.007046 -7.710576\n 0.550 -12.525549 -12.210387 -8.643192\n 0.600 -13.642044 -13.393640 -9.573946\n 0.650 -14.684790 -14.530344 -10.478716\n 0.700 -15.616147 -15.586171 -11.325721\n 0.750 -16.388941 -16.517567 -12.074197\n 0.800 -16.944834 -17.270161 -12.672842\n 0.850 -17.212396 -17.776894 -13.057990\n 0.900 -17.104827 -17.955807 -13.151449\n 0.950 -16.517248 -17.707398 -12.857919\n 1.000 -15.323466 -16.911482 -12.061917\n"
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/WRi5uXDx2ghM1q5qNUFivd5MUn/79sWk8IugqmKbxaI4jkBANBPfvn2+abDz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\n9ulP62zS9eOy0dO89ZR0wXetp1z83PAaCG2Ipm0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qv1kWi/sdEU04D0RRFLxeL5oclT0H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\nSLBuAAAAAElFTkSuQmCC\n",
"text": "<IPython.core.display.Image at 0x850c198>"
}
],
"prompt_number": 18
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.ipzCaptureWindow2('Ray')",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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0k0jiqHy8pumndCsq9Po2c+aABy0PiiRrhIVp5EbK5ObEoalxtHf72VjfyMqq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\n",
"text": "<IPython.core.display.Image at 0x84e8fd0>"
}
],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.ipzCaptureWindow2('Spt')",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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mSOsOihXq6sykGhNj3k+zWlFcbvNMMTXVrFqi65CRjqJacAwfA126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\nMTg6MjI6MjItMDU6MDAhL60QAAAAAElFTkSuQmCC\n",
"text": "<IPython.core.display.Image at 0x84e8cf8>"
}
],
"prompt_number": 20
},
{
"cell_type": "code",
"collapsed": false,
"input": "ln.zDDEClose()",
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 21,
"text": "0"
}
],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": "",
"language": "python",
"metadata": {},
"outputs": []
}
],
"metadata": {}
}
]
}
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