Utilities ....

72a0dcd9-bda2-47a8-b4c4-b910e88c0cd8 34 4 5 decimal

&[DATE] &[TIME] - &[FILENAME]

Utilities ....

Mesh U, V  within the bounds L, H L H N xd U 0 : dx H L - N / : i 1 N 1 + (range U i el L dx i * dx - (+ : for U 41 line :

Generate the symmetric square matrix x y f U V Sym r 1 : i 1 U rows range c 1 : j 1 V rows range M r c el U i el V j el f eval : c c 1 + : 21 line for r r 1 + : 31 line for M 31 line :

You need that one for scaling grayscale image M lo hi Scale hi lo - (M M Min - M Max M Min - 106 -^+ / (* lo + :

M scale M M Min - M Max m Min - / 255 * vectorize :

A B r c replace U A : i 1 B rows range j 1 B cols range U r i + c j + el B i j el : for for U 31 line :

M γ scale_γ M M Min - M Max m Min - / γ * vectorize :

M γ0 γ1 Gamma M M Min - M Max m Min - / γ0 * vectorize (γ1 - :

Implicit 'zoom fractional' Up/Down M a b zoomfract a b ≡ (a b | (1 ≠ (& (implicit conditions ≡ i 1 M rows a * (range j 1 M cols b * (range N i j el M i a / Ceil j b / Ceil el : a 1 ≥ N i j el M i a / Floor j b / Floor el : cases for for N 31 line :

M Center Cyclic permutation: center/recenter a spectral 2D rowctr M rows 2 / Floor : colctr M cols 2 / Floor : 12 mat p 1 M rows range q 1 M cols range J p rowctr + M rows mod 0 + q colctr + M cols mod 0 + el M p q el : for for J 41 line :

Discrete compactor L 1 - : H 1 : 12 mat N 9 : U L H N xd : V U : 41 sys

x y f 255 x 2^y 2^+ (- 0.875 / exp * : Pic x y f U V Sym : 21 sys

Kernel convolution is infinite wrt infinite "Kernel design". To make things simpler, we convolve zoomed 10 'Pic' over 'Ks' which is adjustable ... observe the quality of !N!

Ks 0.1 0.1 0.1 0.1 k 0.1 0.1 0.1 0.1 33 mat :

ortho Ks 22 zoomfract 0255 Scale :

k 0.25 :

iVBORw0KGgoAAAANSUhEUgAAAAYAAAAGCAIAAABvrngfAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAAWSURBVBhXYyAF/AMDKAcCsAjhBQwMAKc4C+n7n2k6AAAAAElFTkSuQmCC ortho iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAIAAAACUFjqAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAABwSURBVChThdA5FUMhEAVQbIwDLFBR0qbFBQYiBQ8xgYzoSPvvGQHhNbyNYSkRUWttrY0xXgmEZIqKpfc+51xrvRMIyRQVRYK79/4kEJIpKkaps8453wRCMkXFYbo2CX4JhGSKbvFl+OVql4f9+5aIB7LIiI16ziX7AAAAAElFTkSuQmCC Pic

Z Pic 42 zoomfract : m Z rows : n Z cols : 12 mat r m 2 / Floor 2 - : c n 2 / Floor 2 - : 12 mat A m n matrix : K A ortho r c replace : 51 line

ω K 0255 Scale :

ortho 0000000000000025525500002552550000000000000066 mat

iVBORw0KGgoAAAANSUhEUgAAABQAAAAoCAIAAABxU02MAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAAkSURBVEhLYxgFo2AUjILhC/6BAZRDKqBI8ygYBaNgFBAEDAwA0EML6eTwsykAAAAASUVORK5CYII= ω iVBORw0KGgoAAAANSUhEUgAAABQAAAAoCAIAAABxU02MAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAC0SURBVEhL7dUxEYNgEERhbPwOsJAqJS0tLmIAKfEQE8iIDlpm9ktxDjI3w+tyu685DjKNMIdHWMJaMJFqsrrKfjzDFl5hL5hINVldZWsQqL7Dp2Ai1WR1lR2AlSgd4VswkWqyuspO3zKsh3AWTKSarFsOqj8vmEg1WX+UPW6P3hk4CQJMpJqsrrLX2ituGUrWAxOpJqur7PPtUy6wElWYSDVZXWV/035YgwNw+jCRarJaymNcFCFEnQTUQIoAAAAASUVORK5CYII= Z iVBORw0KGgoAAAANSUhEUgAAABQAAAAoCAIAAABxU02MAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAAkSURBVEhLYxgFo2AUjILhC/6BAZRDKqBI8ygYBaNgFBAEDAwA0EML6eTwsykAAAAASUVORK5CYII= K

Optimiz => symbolic x y convol x mwfft2 y mwfft2 * vectorize mwifft2 :

KZ ω Z convol : Convol KZ mwabs eval : Convol Convol 0255 Scale : Convol Convol mwround : 41 line

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 Convol

t0 1 time :

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1 time t0 - 0.5 s *

if stuff disappears ... 1. Open blank sheet 2. Do NOTHING, go back => resued.

t0 1 time :

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1 time t0 - min 5.4

Convol isolated

Convol 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N Convol Center :

1 time t0 - min 4.6

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r8RSxY8EEOrFSHUUwK6JbcSzLU3JCSh9WvdRUyv7QkoRMTFKENPQmmuuaeZOWI0aNSp90NyUgqV+a3njgeVda1K2nJWeSE+Ci2b67WIvO9o3vCof2cZCdibEWM5+XvCFR/ziXVHjdcAFRfBFOt6LWEdEpnNUQSfL7WIk2wWwayL5baYKuKswKyegBLwepLIm+3pIafCSRfNSZRJWBnF9LTmoGKW6mz/dDE455ZQFy2tHHE+NtzKZ6FwaElx00ky/XXp4JR9ZxbakJGvZzHL284IvPOIX74oar/mOAA5oBEsQdbxdIiyJc4RoAXIFpLpLIeeFcaLJlmqBewsTsznQdCPsdSL1VdWQCyGVUuWmNwmohak1gkKRFiByyvRk4Ex1N1IZ2XtgOeJ4aryV1jvLuTTQQxudSUa7pHiFFxtYwh5WsY2F7GQtm1nO/kQZj/jFOz7ytMAhgEOANHSOOKIjFIlFESeAHTrAU5Q4kvAuiMwXzIkmG4twRpibTYPCXufWj1RZtSMxFVKmR20+CaiRqTgJK91NZilGqe6mhMCaZJJJwPJvYDmeGm+l9c5KcNFDW5KRfruEV+KLDSxhD6vYxkJ2spbNLE+U8YVH/OJdYo2/vA47HIIvglLH2xFLCdLEmahTAT91iSNp77LIfyHtKikHtk+FYpDLKPj1b11JrU32FSkzpGYvcTSyVKuElR4nv1KwND5T6BRTTFGwvHbE8ZQtK62v4KKHNjpppr94JR/ZwBL2sIptQcZaNrOc/bzgC4/4lVjjKX95zXcEgiJYgqjj7Yil4UIgdz72BShxJPldHFVAYLtWikJhqoCSCHqTiquOyI4iZZLkm/TRziqskoMpWGp5X1iOp2wlEyu46KGNTpqLlx3ta3c2JCUTYoWMzSxnPy/4wqPEWoHjNd8RCIpgCaKOFRGRSZwTNMDT4goUoMSREuASqQUqqCBXGly9YDJJmw8lgl6uQ6m7qokcCamUKuljsNTUElZ6nLEgBQsUg9Xkk09esLx2xPGULSutT3DRQA9tKV7hZS872tfubGAJe1gVZOxkLZtZzn5e8CWxVuD4y2u+Bx8JliDqWBEcESFKggZ+ulyHApQ42nzzzRNK6qhQTzQVpgSUjq5Pqb5qSrKvSEkiTS3VSrAkBxUmjc+sANDEE08Mln+9dsRx7yYTrU/looGe4pV8tJcd7Wv3hFghS5Sxls0JNF4k1gocT/nL6+ALioZLF2XHohLnEIFKgsZFoNHVKECJozBy0VQHAa9MtDEloPR13UoN7ktKQqlBCStZpjCp5dC4JSxYXjviuHetSXA5K8k4Li972dG+CbE2Mhayk7UJNPYn1gocH3nK3+ALhABp6Iwe3bEo4oSIk4mIDRqXInQ23HDDAEoctRmprIJfyXBVgykBJUH0LJVYfSlSBvEkoAanEgmZ5KDypP31wHIkZcsaK613VpKRnuJFv13sZceEWJCxh1VsY2GbWmIt4PgVdjwNPr4HQkOki5J0rGuLMwOFaChB44KEjpAOIE1HXQijhJL6KgUUDtc2mMyNCSidSz1WZRJTIZUENBMkrOSa8qSiG68KlteOOO7dBJf1ScbwSnzRTL9dEmL2DTKWsIdVbEughRrL2R9wPAo7PgYfr+N+UDRcutKxLuKciPMDhWgrQeOyhI7ALkCJo2KkyibpEk2FycXXv1TlZF+RklapVgmrFCyA3vOe94DlX69TthJcqVzOKl7JR5rpt0shS5QlMVlV1BJrBY4vYce74ONvHA+EhkiXJulY2hYnh0ighItIDhqXKHQEue1FO1MSR2Hkwi6yyCKSYlxMAkFtVnHkUZGSXKlWwkfGQaMJFqw0RMe9m8qVZAwvemijMyHWg4wNLGFPqCXWWMtmlrM/7HgUfHwMQRL3g6Lh0pWO1T1CRYgESnFxfRI+dk0ECfgAShylMIVRkq4wVUCp0OqObCpSUixhJeMUqR5Yjjie4EoyhhcN9NBWIVbIkpihlnKWWAs4Nifiwi5OFUESxwOhITIkHSdEnFxCF3E1EjLFpdC4aKHjGgbQAgsswETXlq1KL7vd9/Ih0RRMFVCqj5xqk0pYpWAVrJStBFebl3NpqBALskSZHe1r95R/9rCKbQGXiGM5+wsfCUESl+N+w6IrQdRxTgkVJTQGR4gESnFx3RI+oeN6FqCkm6sdRkk6UVCYElBqkMxqk0pY9cBKcLV5Ocu5CbFCRn8SM9TsnvQscIm4sIvxRZDEwTgbxxsKXWnojBzZyZkldJVQHbFNiBSU4kISPm06CaIASsaFUaKJqwkolahNShAF1kQTTQSWfwPL8TYvZyXEgozOomavAseGHnZJVRKCJBBJHGy87QItabh0pZPz20JpiT0i9guOSKCES6Fp0xkXUBglmgqTetRDSkAVrAqu4mV9GxltoUZ6wJFiR4KPxOxAjMS1xs8u05KGyJB0aBlXskGJLSO2j8QaZoVIoIRLD5rQKUBtRm1MRaoHFgkvUshIUSMBR7JdGx+JYTEyBsf4xpMu0Ejj7ZA0LFrSica+ki1LGNGWWEZiKGF0JD5wJsKxNp0AajOKBA1GBYvkYLOiRY1EVdRmi2a/FsRIY98QTdL4MCSNh0PS+D+OjP1Q8NtKDBpXYm5b4kZb4l6k8bgroVASNBGkIs3PXWnWDUmjpSuN9q40u7aksawljfXjSOPtW0tj1kDekTTQxisN+XGkuVItaa5mS5or3pUmErrSRMiQNPHTlcayd2FkNenYT5oMHpImv4ekyf7/qprVFPo3S9MPhqTpFoNu2IwQLWlmjK40s8dgzurKYIIfK3Gw8XY8E3xz29OV5l6oK7lFyu1Sbp1yG/VffW+Y+2nS3F93JbfduQXP7fjgtw5k8PussfJOf5/V/BJwSPLrwfyqML82HPymtGTwO/gJ+R188x8XQ5L/0sh/bwz+d4c0XLoy+H/DCfl/w+Y/W7uS/4DNf8YO/keaBEhDZ/TowWcdJuSzDvl8CMnHRfLRkcGnaPp/iiafPCL5IFI+lDT4fFb/z2flM20kH3HLx90Gn/zr/8m/wWdKJ+Azpc0HcbuSD+cOPq38lp9Wzie8ST7wPfgc/Pg+B998eaArg29YhMtbfsPi9MF3d975d3cG3woLowLEa773/1bY4PuGE/B9w+ZLml0ZfJOVv7x+y2+y5tu/ZPAdaZ7yN3T6f0c63ysn+Zr54Nv3odP/2/fNIwu6cvPguQ7jf65D8zCMrgyeGBJGfO//xJA8ZYXkoSuDZ9HwOoD6PItm8JQjfhWmYoRAn6cc5clQJA+KGjw/i9cBhEPv87Oah451ZfBkNv4Woz5PZsvT7MijXRk884/XfEegzzP/8pxEMniaZKIpmAKo92mSg+eU8uudPqc0z3Ylgyfg8rSNKYDe9ATcPDWYDJ6tHFKFKYze9GzlwVO7+RVSPA0pviMQRm96avfgefD8qphKQPE9mNAIliAa/KWBCflLA/nrDGTwNyx42iYVTJj879+wGPx1lEpAnvaQCqbAGfvXUfIXZUio9fCSt+pckrEdXD2ZaMzTa9ply71ranxG0zRE97qBZUTKXMp5dzAFa/i7/O/uvNaV/NGiICteMlaFaweXidYdgPYhhjNDGO0ycCkK2rNbCnf2hmbm5r5He2rDyqiVuTRDfMEa8e7/i06DvxXGr1SrCiu+t0kFzti/FTb4K3SVg6lWCasUqZAKnLF/hS6wSMGC01Jok4lV5ilN2bKNpls1nhHutq76b/j7hoO/nNlTsNo52Cb1xhtv/AcEq1B7Y0lboAAAAABJRU5ErkJggg== Convol 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 N

t0 1 time :

S Convol mwifftshift :

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ZH+2br3pU2ustN5VrrWDfexmzw1eznU6H3hSMvKNh4mrMYL/ohCLiOqJlS3xVuMRwAGNS4NluNA1tYPGUTXPgFvBqg8a6hRIM4vmUrVKVp45TNIloF6uQ6m7qsmSlKKToFJTmAL0rne9693vfvd73vOeP18373jfp4EbyOyQxOy55OVE5zqdDyUjr/iWuKpcPOe/KMRST6xsiVS8jaYI4IDGdlgeggysS1haQ9X9lFNOqWDVB412yqTJpSaoIixlNRJQn1J91ZQlqTe/+c2kIa3kV5iwAOW9733vxRdf/BeT/eXKeul9n1pjZchcawf72G3Jy1lOdO5IxqW4+Flb5Dn/RVFPrGyJsRov6iUsTJBZg3X88ccHyyRmxGhu0BqMalX3UbDqgwY8xdL8YurTbka10olM1W5sCahb1fjkyyCVoJaYAvS+973v/e9//1+tm3e8H7glsiQ2eNm/FunEkpEPPOHPqFz85C2fec7/euIoW9V48Ypa7AjggEaw8NmEZboPVnODZ0sNwsCm/plHRsGqDxrzykGzX01wyMps7faWgHqWSqy+yJoNUgNTjD7wgQ9ccsklf71u3vF+1AayDV52tr9TnFUyOp0PQ1y1RX6WiTyvJ46yJToxilS8om56CBYma7COO+44Lzwx+sDYah6ztLmhVmhsUwVNJaNg1QdHDpoAzznnnFGt3FgTdrLS43Uu9ViVkTuRUokiRTVAxOiDH/zg30z2tyvrpfejZqX18bJDvOxpZ/s7xVmJy+mJq8rFNx6OTKwnjrIlLtGJsYbY9IAADmhgggw+KG2H5WHSBfroSSedVCs0vKmFZhOprvVWsJY5qJTSvDZUtUpWIwH1L1VZrRmaSlBUEyZo/m6yv5/sQx/6UP/Rmz4NmfVJbOjLnna2/0jGIS6e8IdXfFtmYmVLFGIRkbhEV0MUr6jFjsARYHlu9LHh1dKGLN305JNPrhUa4VREE4qE14Alv8m4Pjhy8Pzzz9eMVA1PcENWIwHV5pF9gxTtxAigf5jsH1fWy8BZY+XgNfLRniMZh7iczgee8GdkYj2RzzznvyjEIiJx1RBFKt5GLQRwQAOTTVgnnHBCsDwQWWSEdUFDlp7qabNWaJBTF3seXBYsHccQuMxBjalqNWRVAqrQZd+SVJjQ+fCHP/xP6+adqFmz5FU+2q1kHOKqcjl9mYl84+GybPFfFGIRUQ1RjCJt1BI7AjigESx8tsPqWaeJtCFLZ/XMWSs0zlXdDcSeUStYOo7SoPsYCMvBiy66SEZo6lWrpawkkeqzQSpM/zzZv6yslyHb4GWHkYyJq8rlROc6vUzkD6/4xsPKFp95Xo0XSw1RdGJs1Gou7YnnsLBOPPHEAcu874Im0oYs23nyrBU2jlbdPakuC5YeZCzcyMENWUki1VoN2iAVoH9dt97c4OVaO5SMS3FtZCJP+LMsW7ytxjea1hDFFSyRNpeKHYEBC5ktsPr5TLAa35tIG7KWsDSUnnIcb0T2lO/xQquuYOlHRsQmBtmhYXleMYUvZaVmq0RLUtD822T/vrJehmzwcpVrl+Kys/2d4qxmCKc3cPGHV3zjIT9523MP/5ewGrWaSxviByxMDgurHzkEq/F9TKRGEg/rzQ0aiiNrhcEa1X0UrPrgMgfN4lWrISv1aEkqRv+xsl4ueVk/xFXlsucyE+uJo2yNGh+sGiLP+d/0ICJxjbm0IX7AQuMIsPqRwwasJtIlrOaG0QrPPffcUd3H0FDB6snGZDRysGqVrCpSkYrRf66sl/GyxsrE5Vo7jEy0s/2dUtkaA8So8XwbDXFMD0tYotsLC4d9wfLYHayedcb4bopbDlnLuSFYF1xwgaezYFXdNfXGqwrWKO3lILFAMGS1JJUNWNZU7MvEUebtWdlyirNGjecDT/izAYvPy1FLRMESo0jFGywEPiJYje/BOuOMM5aw9OatsJqwBqyNgrXMwSWp/1pZL+O1zMSNsrWE5cStsHi4hMX/AUtcHz1YyyFr/7A2CtZRwXLtUcEao9bHHtZOWbuatW9Yu2643264m7OCdeQ5azfB73eC3z0b7vfZcPdTh6P4qcOAtft51hF+nrX7SelR/KQ0WLufwR/Fz+AHrN2/7hz2X3d2/24ouv3+u+GAtfsX6X39i/Tudx2aSMUr6iP8roMXu9+iaSIV9RLWpf3K0e73s0Qt9n39ftbuN/9ELXYELu03/3a/UyrS5oaedXBAY8vvlO5+W7nqLt7mBgRw2PLbypfZ/R78/n8PfsDa/YVF1V3sCOCAxpa/sNj97Y4YRVp1FzsCOKCByfY/dDpx91dh+/yrsN3fGzaOVt0RwAENTDb/3nD3l6xiFGkFq+rekBWsQ3/JuvsbadGJUaTirWAhgAMamCCDz+YflBtVmx7UNklrMCsT9YjKvJsgw7WPklHrjZdCMHipDqqp7lNKusmmZ08bIXP/JYsaHLW0JnhdjAERwayXfWRNOoqRHexjtzDZ3ykJyrlO5wNPBikeRorPJaAoxJKsRCfGclDUYkeguQGTTVi773UQo0jLQbEjgAMamCCz/UswFH9VrbJl1qgnHtx9Y8gS1u67aMQoUvGWgwhU3TFBZvOLewypBopqvGHMlEGNMCt4kMtnzaJk9MBZ8YoXVasCqqYuQ+qmGFOfKdlThXrB9VQmNdQRN19BoYIBTvqIXB4xFPZaH1lj5QBkB/vYzZ52Tk3OcqJznc4HnvCHV3zjIT8jVakSRQkoLtGJUaTiFbXYEai6Y4LMIVi7788SnRiTlajFjkDVHZNgHfqyseOO230z276/mS1YKlllq0wc4tIgSNSOZrbBi4blvBqpp5SSSWwgUybcW4mgarjVykdaG+BoQbREIewIBnFpvdkCK6131QCUjuxsf6c4y4nOHZiGoHjIT97ymeeDlIjEJToxDlmVgxUsTDZhHbv7Nsl9fpvk7ntKRSdGkVatxF4OooEJMvgc+lJXDz7eUsmkKO0lLnlbMu7lpSLqIDpuElsiUxQIXnVIaPxOawOcOy82EgifrGHCjuNe66OWhca1drDPAJSOYuRcp/OBJ0tMCYrPPOf/VlLiFXWywgENTJDBZw2Wgl/Zoj1QZax2UDIaZwcvua0W6h0EnMRC5o4pBESudi6ppbXAnfJ/47uVDRFqmOSkusSla5aM8UpfsloV1DWSmCkuZO6VEkDeqmZCi5oaofUETjrEzm0Pn/YkziDG8XDWgha7KjT2iY6dA+QsJ8YoKfGHV3zjYZj4nKBEIRYRpalIlYBiT1ZoYIIMPjOs3ffBi26QEnXVKllVsPA59OX5NUR6A7LKVTLGizJlssqXxDaQEbMndbcrammNizTPXeKPnZscPnkRwSDGMZSHsxa0uAvtYJ/Q2Dk6znKic52ejmLENx7ycy8mEYlLdGIcpMRetUIDE2TwWYMlLektcZWM8aJJOazmDYkNZCVm1CpnaS1wBJ/iYucms0EwiHEM5aVby7qky+PSttFJQc4NUDqqMMWopBuYhqBEJ0aRDlIIJCtMkFmDVdlKXEte1Ch7h8RClsqc5GnTqZV/94orB/4//N9RvEhcS150KG+T2EDmDpSYUXNnSs8BLsXFzs1kg2AQ4xjKaA4T8F6bP5usS7q8rdo2Lh036PBkACrdeBujkk4sA1OCEq+ol6SS1SFYu/+jU5gSlKiXpDAJ1qH//dUQ1+AlV5fI8I7aXnBLdgNfBAfEjOvRzMQzrAgvxeZ1k83Xf6z+X2FeDF5LZEtqA1zsNvBFMIhxXKLMOJ0VwzBR7cfm1Sub9/ro/1/olryylromcEt24cs6yZFZHrAcYpxbWh4PK4yjsvnKlc37rmw+dcWCzZ4toGQFUlAFWLAFPlNYkGL/A2vwyvp42HzRZG2UtfXSOnJpubLXcvQjtHmvPTafvbDZv4XNMUw2xzbZHPPKZiKTHXPMMf8N49xQexjIA6IAAAAASUVORK5CYII= S

1 time t0 - 0.9 s *