GIF89a=( õ' 7IAXKgNgYvYx\%wh…hŽth%ˆs%—x¨}9®Œ©€&©‰%¶†(¹–.¹5·œD¹&Çš)ÇŸ5ǘ;Í£*È¡&Õ²)ׯ7×µ<Ñ»4ï°3ø‘HÖ§KͯT÷¨Yÿšqÿ»qÿÔFØ !ù ' !ÿ NETSCAPE2.0 , =( þÀ“pH,È¤rÉl:ŸÐ¨tJ­Z¯Ø¬vËíz¿à°xL.›Ïè´zÍn»ßð¸|N¯Ûïø¼~Ïïûÿ€‚ƒ„…†‡ˆ‰Š‹ŒŽ‘’“”•–—˜™š›œžŸ ¡¢£¤¥¦§gª«ªE¯°¨¬ª±²Œ¹º¹E¾­”´ÂB¶¯ §Åȸ»ÑD¾¿Á•ÄÅ®° ÝH¾ÒLÀÆDÙ«D¶BÝïðÀ¾DÑÑÔTÌÍíH òGö¨A RÎڐ |¥ ٭&ºìE8œ¹kGÔAÞpx­a¶­ã R2XB®åE8I€Õ6Xî:vT)äžþÀq¦è³¥ì仕F~%xñ  4#ZÔ‰O|-4Bs‘X:= QÉ œš lºÒyXJŠGȦ|s hÏíK–3l7·B|¥$'7Jީܪ‰‡àá”Dæn=Pƒ ¤Òëí‰`䌨ljóá¯Éüv>á–Á¼5 ½.69ûϸd«­ºÀûnlv©‹ªîf{¬ÜãPbŸ  l5‘Ž¯pß ´ ˜3aÅùäI«O’ý·‘áÞ‡˜¾Æ‚ÙÏiÇÿ‹Àƒ #öó)pâš Þ½ ‘Ý{ó)vmÞü%D~ 6f s}ŃƒDØW Eþ`‡þ À…L8xá†ç˜{)x`X/> Ì}mø‚–RØ‘*|`D=‚Ø_ ^ð5 !_…'aä“OÚ—7âcð`D”Cx`ÝÂ¥ä‹éY¹—F¼¤¥Š?¡Õ™ n@`} lď’ÄÉ@4>ñd œ à‘vÒxNÃ×™@žd=ˆgsžG±æ ´²æud &p8Qñ)ˆ«lXD©øÜéAžHìySun jª×k*D¤LH] †¦§C™Jä–´Xb~ʪwStŽ6K,°£qÁœ:9ت:¨þªl¨@¡`‚ûÚ ».Û¬¯t‹ÆSÉ[:°=Š‹„‘Nåû”Ìî{¿ÂA ‡Rà›ÀÙ6úë°Ÿð0Ä_ ½;ÃϱîÉì^ÇÛÇ#Ëë¼ôº!±Ä˜íUîÅÇ;0L1óÁµö«p% AÀºU̬ݵ¼á%霼€‡¯Á~`ÏG¯»À× ­²± =4ªnpð3¾¤³¯­ü¾¦îuÙuµÙ®|%2ÊIÿür¦#0·ÔJ``8È@S@5ê¢ ö×Þ^`8EÜ]ý.뜃Âç 7 ú ȉÞj œ½Dç zý¸iþœÑÙûÄë!ˆÞÀl§Ïw‹*DçI€nEX¯¬¼ &A¬Go¼QföõFç°¯;é¦÷îŽêJ°îúôF5¡ÌQ|îúöXªæ»TÁÏyñêï]ê² o óÎC=öõ›ÒÓPB@ D×½œä(>èCÂxŽ`±«Ÿ–JЀ»Û á¤±p+eE0`ëŽ`A Ú/NE€Ø†À9‚@¤à H½7”à‡%B‰`Àl*ƒó‘–‡8 2ñ%¸ —€:Ù1Á‰E¸àux%nP1ð!‘ðC)¾P81lÑɸF#ˆ€{´âé°ÈB„0>±û °b¡Š´±O‚3È–Ù()yRpbµ¨E.Z‘D8ÊH@% òŒx+%Ù˜Æcü »¸˜fõ¬b·d`Fê™8èXH"ÉÈ-±|1Ô6iI, 2““¬$+](A*jÐ QTÂo‰.ÛU슬Œã„Ž`¯SN¡–¶Äåyše¯ª’­¬‚´b¦Éož œ)åyâ@Ì®3 ÎtT̉°&Ø+žLÀf"Ø-|žçÔ>‡Ðv¦Ðžì\‚ Q1)Ž@Žh#aP72”ˆ™¨$‚ !ù " , =( …7IAXG]KgNgYvYxR"k\%w]'}hŽth%ˆg+ˆs%—r.—m3šx3˜x¨}9®€&©€+¨‡7§‰%¶†(¹–.¹œD¹&ǘ;Í•&ײ)×»4ïÌ6ò§KÍ þ@‘pH,È¤rÉl:ŸÐ¨tJ­Z¯Ø¬vËíz¿à°xL.›Ïè´zÍn»ßð¸|N¯Ûïø¼~Ïïûÿ€‚ƒ„…†‡ˆ‰Š‹ŒŽ‘’“”•–—˜™š›œžŸ ¡¢£¤¥¦§g «¬ E ±± ¨­¶°ººE Á´”·®C¬²§Ç¶Œ»ÓDÃÕƷ¯Ê±H½ºM×ÁGÚ¬D¶BËÁ½î½DÓôTÏÛßîG»ôõC×CÌ l&âž:'òtU³6ɹ#·Ø)€'Ü.6±&ëÍÈ» K(8p0N?!æ2"ÛˆNIJX>R¼ÐO‚M '¡¨2¸*Ÿþ>#n↠å@‚<[:¡Iïf’ ¤TÚ˘CdbÜÙ“[«ŽEú5MBo¤×@€`@„€Êt W-3 ¶Ÿ¡BíêäjIÝ…Eò9[T…$íêﯧ„…•s»Óȳ¹€ÅÚdc®UUρ#±Ùïldj?´í¼²`\ŽÁðÞu|3'ÖŒ]ë6 ¶S#²‡˜FKLÈ *N E´‘áäŠ$˜›eÄYD„ºq«.è촁ƒs \-ÔjA 9²õ÷å- üúM[Âx(ís÷ì®x€|í¡Ù’p¦‚ ŽkÛTÇDpE@WÜ ²Ç]kŠ1¨ þ€·Yb ÓÁ‰l°*n0 ç™—žzBdОu¾7ĉBl€â‰-ºx~|UåU‰  h*Hœ|e"#"?vpÄiŠe6^ˆ„+qâŠm8 #VÇá ‘å–ÄV„œ|Šè•m"сœn|@›U¶ÆΞ—Špb¥G¨ED”€±Úê2FÌIç? >Éxå Œ± ¡¤„%‘žjŸ‘ꄯ<Ìaà9ijÐ2˜D¦È&›†Z`‚å]wþ¼Â:ç6àB¤7eFJ|õÒ§Õ,¨äàFÇ®cS·Ê¶+B°,‘Þ˜ºNûãØ>PADÌHD¹æž«ÄÀnÌ¥}­#Ë’ë QÀÉSÌÂÇ2ÌXÀ{æk²lQÁ2«ÊðÀ¯w|2Í h‹ÄÂG€,m¾¶ë3ÐÙ6-´ÅE¬L°ÆIij*K½ÀÇqï`DwVÍQXœÚÔpeœ±¬Ñ q˜§Tœ½µƒ°Œìu Â<¶aØ*At¯lmEØ ü ôÛN[P1ÔÛ¦­±$ÜÆ@`ùåDpy¶yXvCAyåB`ŽD¶ 0QwG#¯ æš[^Äþ $ÀÓÝǦ{„L™[±úKÄgÌ;ï£S~¹ìGX.ôgoT.»åˆ°ùŸûù¡?1zö¦Ÿž:ÅgÁ|ìL¹ „®£œŠ‚à0œ]PÁ^p F<"•ç?!,ñ‡N4—…PÄ Á„ö¨Û:Tè@hÀ‹%táÿ:ø-žI<`þ‹p I….)^ 40D#p@ƒj4–؀:²‰1Øâr˜¼F2oW¼#Z†;$Q q” ‘ ÂK¦ñNl#29 !’F@¥Bh·ᏀL!—XFóLH‘Kh¤.«hE&JòG¨¥<™WN!€ÑÙÚˆY„@†>Œž19J" 2,/ &.GXB%ÌRÈ9B6¹W]’î×ÔW¥’IÎ$ ñ‹ÓŒE8YÆ ¼³™ñA5“à®Q.aŸB€&Ø©³ JÁ—! ¦t)K%tœ-¦JF bòNMxLôþ)ÐR¸Ð™‘ èÝ6‘O!THÌ„HÛ ‰ !ù ) , =( …AXKgNgYvYxR"k\%wh…hŽh%ˆg+ˆs%—r.—x3˜x¨}9®€&©€+¨Œ,©‡7§‰%¶†(¹–.¹5·&Çš)ǘ;Í•&×£*Ȳ)ׯ7×»4ï°3øÌ6ò‘HÖ§KÍ»Hó¯T÷¨Yÿ»qÿÇhÿ þÀ”pH,È¤rÉl:ŸÐ¨tJ­Z¯Ø¬vËíz¿à°xL.›Ïè´zÍn»ßð¸|N¯Ûïø¼~Ïïûÿ€‚ƒ„…†‡ˆ‰Š‹ŒŽ‘’“”•–—˜™š›œžŸ ¡¢£¤¥¦§g ª« E$±²¨ª­ · °²½$E$ÂÕ««D· Í ¿¦Ç¶¸ÌŒ¾³CÃÅÆ E ééH½MÛÂGâªD­ çBêêϾD²ÒaÀà€Š1r­ðÓ¤ ÔožzU!L˜C'¾yW½UGtäÇïÙllê0×àÂuGþ)AÀs[þ·xì ÁxO%ƒûX2ó—  P£n›R/¡ÑšHše+êDm?# —‘Ç£6¡8íJ¡ŸâDiäªM¥Ö„ôj“¬¹£5oQ7°- <‡ *´lãÓŒ2r/a!l)dÈ A™ÈE¢ôÔ͆…ð ;Ö˜c ¡%ß‚’Ùˆâ¸b½—pe~C"BíëÚHïeF2§æŠ8qb t_`urŠeü wÅu3êæPv§h•"ß`íÍxçLĹÜÖ3á  ~Öº“®›¸ÏMDfJÙ °„ÛµáWõ%§œ‚à©–‚X Ó؁)@®Ñ›Eþ´wëuÅSxb8y\mÖzœ¥§ZbºE—ÂLªÌw!y(>¡™wú=Ç|ÅÝs¢d €CÁW)HÜcC$€L Ä7„r.á\{)@ð` @ äXÈ$PD” `šaG:§æˆOˆ72EÐamn]ù"ŒcÊxÑŒ° &dR8`g«iÙŸLR!¦P …d’ä¡“¦ðÎTƒ¦ià|À _ ¥ Qi#¦Šg›Æ ›noMµ ›V ã£)p ç£ÎW…š=Âeªk§†j„ ´®1ß²sÉxéW«jšl|0¯B0Û, \jÛ´›6±¬¶C ÛíWþï|ëÙ‹¸ñzĸV {ì;Ýñn¼òVˆm³I¼³.Ðã¤PN¥ ²µ¼„µCã+¹ÍByî£Ñ¾HŸ›ëê 7ìYÆFTk¨SaoaY$Dµœìï¿Ã29RÈkt Çïfñ ÇÒ:ÀÐSp¹3ÇI¨â¥DZÄ ü9Ïýögñ½­uÔ*3)O‘˜Ö[_hv ,àî×Et Ÿé¶BH€ Õ[ü±64M@ÔSÌM7dÐl5-ÄÙU܍´©zߌ3Ô€3ž„ „ ¶ÛPô½5×g› êÚ˜kN„Ý…0Îj4€Ìë°“#{þÕ3S2çKÜ'ợlø¼Ú2K{° {Û¶?žm𸧠ËI¼nEò='êüóºè^üæÃ_Û=°óž‚ì#Oý¿Í'¡½áo..ÏYìnüñCœO±Áa¿¢Kô½o,üÄËbö²çºíï{ËC Ú— "”Ï{ËK ÍÒw„õ±Oz dÕ¨à:$ ƒô—«v»] A#ð «€¿šéz)Rx׿ˆ¥‚d``èw-îyÏf×K!ð€þ­Ð|ìPľ„=Ì`ý(f” 'Pa ¥ÐBJa%Ðâf§„%Š¡}FàáÝ×6>ÉäŠG"éŽè=ø!oŠ°^FP¼Ø©Q„ÀCÙÁ`(Ž\ÄÝ® ©Â$<n@dÄ E#ììUÒI! ‚#lù‹`k¦ÐÇ'Rró’ZýNBÈMF Í[¤+‹ðɈ-áwj¨¥þ8¾rá ,VÂh„"|½œ=×G_¦Ñ™EØ 0i*%̲˜Æda0mV‚k¾)›;„&6 p>ÓjK “¦Ç# âDÂ:ûc?:R Ó¬fÞéI-Ì“•Ã<ä=™Ï7˜3œ¨˜c2ŒW ,ˆ”8(T™P‰F¡Jhç"‚ ; 403WebShell
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Current File : /opt/cloudlinux/venv/lib64/python3.11/site-packages/numpy/typing/tests/data/pass/arithmetic.py
from __future__ import annotations

from typing import Any
import numpy as np
import pytest

c16 = np.complex128(1)
f8 = np.float64(1)
i8 = np.int64(1)
u8 = np.uint64(1)

c8 = np.complex64(1)
f4 = np.float32(1)
i4 = np.int32(1)
u4 = np.uint32(1)

dt = np.datetime64(1, "D")
td = np.timedelta64(1, "D")

b_ = np.bool_(1)

b = bool(1)
c = complex(1)
f = float(1)
i = int(1)


class Object:
    def __array__(self) -> np.ndarray[Any, np.dtype[np.object_]]:
        ret = np.empty((), dtype=object)
        ret[()] = self
        return ret

    def __sub__(self, value: Any) -> Object:
        return self

    def __rsub__(self, value: Any) -> Object:
        return self

    def __floordiv__(self, value: Any) -> Object:
        return self

    def __rfloordiv__(self, value: Any) -> Object:
        return self

    def __mul__(self, value: Any) -> Object:
        return self

    def __rmul__(self, value: Any) -> Object:
        return self

    def __pow__(self, value: Any) -> Object:
        return self

    def __rpow__(self, value: Any) -> Object:
        return self


AR_b: np.ndarray[Any, np.dtype[np.bool_]] = np.array([True])
AR_u: np.ndarray[Any, np.dtype[np.uint32]] = np.array([1], dtype=np.uint32)
AR_i: np.ndarray[Any, np.dtype[np.int64]] = np.array([1])
AR_f: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.0])
AR_c: np.ndarray[Any, np.dtype[np.complex128]] = np.array([1j])
AR_m: np.ndarray[Any, np.dtype[np.timedelta64]] = np.array([np.timedelta64(1, "D")])
AR_M: np.ndarray[Any, np.dtype[np.datetime64]] = np.array([np.datetime64(1, "D")])
AR_O: np.ndarray[Any, np.dtype[np.object_]] = np.array([Object()])

AR_LIKE_b = [True]
AR_LIKE_u = [np.uint32(1)]
AR_LIKE_i = [1]
AR_LIKE_f = [1.0]
AR_LIKE_c = [1j]
AR_LIKE_m = [np.timedelta64(1, "D")]
AR_LIKE_M = [np.datetime64(1, "D")]
AR_LIKE_O = [Object()]

# Array subtractions

AR_b - AR_LIKE_u
AR_b - AR_LIKE_i
AR_b - AR_LIKE_f
AR_b - AR_LIKE_c
AR_b - AR_LIKE_m
AR_b - AR_LIKE_O

AR_LIKE_u - AR_b
AR_LIKE_i - AR_b
AR_LIKE_f - AR_b
AR_LIKE_c - AR_b
AR_LIKE_m - AR_b
AR_LIKE_M - AR_b
AR_LIKE_O - AR_b

AR_u - AR_LIKE_b
AR_u - AR_LIKE_u
AR_u - AR_LIKE_i
AR_u - AR_LIKE_f
AR_u - AR_LIKE_c
AR_u - AR_LIKE_m
AR_u - AR_LIKE_O

AR_LIKE_b - AR_u
AR_LIKE_u - AR_u
AR_LIKE_i - AR_u
AR_LIKE_f - AR_u
AR_LIKE_c - AR_u
AR_LIKE_m - AR_u
AR_LIKE_M - AR_u
AR_LIKE_O - AR_u

AR_i - AR_LIKE_b
AR_i - AR_LIKE_u
AR_i - AR_LIKE_i
AR_i - AR_LIKE_f
AR_i - AR_LIKE_c
AR_i - AR_LIKE_m
AR_i - AR_LIKE_O

AR_LIKE_b - AR_i
AR_LIKE_u - AR_i
AR_LIKE_i - AR_i
AR_LIKE_f - AR_i
AR_LIKE_c - AR_i
AR_LIKE_m - AR_i
AR_LIKE_M - AR_i
AR_LIKE_O - AR_i

AR_f - AR_LIKE_b
AR_f - AR_LIKE_u
AR_f - AR_LIKE_i
AR_f - AR_LIKE_f
AR_f - AR_LIKE_c
AR_f - AR_LIKE_O

AR_LIKE_b - AR_f
AR_LIKE_u - AR_f
AR_LIKE_i - AR_f
AR_LIKE_f - AR_f
AR_LIKE_c - AR_f
AR_LIKE_O - AR_f

AR_c - AR_LIKE_b
AR_c - AR_LIKE_u
AR_c - AR_LIKE_i
AR_c - AR_LIKE_f
AR_c - AR_LIKE_c
AR_c - AR_LIKE_O

AR_LIKE_b - AR_c
AR_LIKE_u - AR_c
AR_LIKE_i - AR_c
AR_LIKE_f - AR_c
AR_LIKE_c - AR_c
AR_LIKE_O - AR_c

AR_m - AR_LIKE_b
AR_m - AR_LIKE_u
AR_m - AR_LIKE_i
AR_m - AR_LIKE_m

AR_LIKE_b - AR_m
AR_LIKE_u - AR_m
AR_LIKE_i - AR_m
AR_LIKE_m - AR_m
AR_LIKE_M - AR_m

AR_M - AR_LIKE_b
AR_M - AR_LIKE_u
AR_M - AR_LIKE_i
AR_M - AR_LIKE_m
AR_M - AR_LIKE_M

AR_LIKE_M - AR_M

AR_O - AR_LIKE_b
AR_O - AR_LIKE_u
AR_O - AR_LIKE_i
AR_O - AR_LIKE_f
AR_O - AR_LIKE_c
AR_O - AR_LIKE_O

AR_LIKE_b - AR_O
AR_LIKE_u - AR_O
AR_LIKE_i - AR_O
AR_LIKE_f - AR_O
AR_LIKE_c - AR_O
AR_LIKE_O - AR_O

AR_u += AR_b
AR_u += AR_u
AR_u += 1  # Allowed during runtime as long as the object is 0D and >=0

# Array floor division

AR_b // AR_LIKE_b
AR_b // AR_LIKE_u
AR_b // AR_LIKE_i
AR_b // AR_LIKE_f
AR_b // AR_LIKE_O

AR_LIKE_b // AR_b
AR_LIKE_u // AR_b
AR_LIKE_i // AR_b
AR_LIKE_f // AR_b
AR_LIKE_O // AR_b

AR_u // AR_LIKE_b
AR_u // AR_LIKE_u
AR_u // AR_LIKE_i
AR_u // AR_LIKE_f
AR_u // AR_LIKE_O

AR_LIKE_b // AR_u
AR_LIKE_u // AR_u
AR_LIKE_i // AR_u
AR_LIKE_f // AR_u
AR_LIKE_m // AR_u
AR_LIKE_O // AR_u

AR_i // AR_LIKE_b
AR_i // AR_LIKE_u
AR_i // AR_LIKE_i
AR_i // AR_LIKE_f
AR_i // AR_LIKE_O

AR_LIKE_b // AR_i
AR_LIKE_u // AR_i
AR_LIKE_i // AR_i
AR_LIKE_f // AR_i
AR_LIKE_m // AR_i
AR_LIKE_O // AR_i

AR_f // AR_LIKE_b
AR_f // AR_LIKE_u
AR_f // AR_LIKE_i
AR_f // AR_LIKE_f
AR_f // AR_LIKE_O

AR_LIKE_b // AR_f
AR_LIKE_u // AR_f
AR_LIKE_i // AR_f
AR_LIKE_f // AR_f
AR_LIKE_m // AR_f
AR_LIKE_O // AR_f

AR_m // AR_LIKE_u
AR_m // AR_LIKE_i
AR_m // AR_LIKE_f
AR_m // AR_LIKE_m

AR_LIKE_m // AR_m

AR_O // AR_LIKE_b
AR_O // AR_LIKE_u
AR_O // AR_LIKE_i
AR_O // AR_LIKE_f
AR_O // AR_LIKE_O

AR_LIKE_b // AR_O
AR_LIKE_u // AR_O
AR_LIKE_i // AR_O
AR_LIKE_f // AR_O
AR_LIKE_O // AR_O

# Inplace multiplication

AR_b *= AR_LIKE_b

AR_u *= AR_LIKE_b
AR_u *= AR_LIKE_u

AR_i *= AR_LIKE_b
AR_i *= AR_LIKE_u
AR_i *= AR_LIKE_i

AR_f *= AR_LIKE_b
AR_f *= AR_LIKE_u
AR_f *= AR_LIKE_i
AR_f *= AR_LIKE_f

AR_c *= AR_LIKE_b
AR_c *= AR_LIKE_u
AR_c *= AR_LIKE_i
AR_c *= AR_LIKE_f
AR_c *= AR_LIKE_c

AR_m *= AR_LIKE_b
AR_m *= AR_LIKE_u
AR_m *= AR_LIKE_i
AR_m *= AR_LIKE_f

AR_O *= AR_LIKE_b
AR_O *= AR_LIKE_u
AR_O *= AR_LIKE_i
AR_O *= AR_LIKE_f
AR_O *= AR_LIKE_c
AR_O *= AR_LIKE_O

# Inplace power

AR_u **= AR_LIKE_b
AR_u **= AR_LIKE_u

AR_i **= AR_LIKE_b
AR_i **= AR_LIKE_u
AR_i **= AR_LIKE_i

AR_f **= AR_LIKE_b
AR_f **= AR_LIKE_u
AR_f **= AR_LIKE_i
AR_f **= AR_LIKE_f

AR_c **= AR_LIKE_b
AR_c **= AR_LIKE_u
AR_c **= AR_LIKE_i
AR_c **= AR_LIKE_f
AR_c **= AR_LIKE_c

AR_O **= AR_LIKE_b
AR_O **= AR_LIKE_u
AR_O **= AR_LIKE_i
AR_O **= AR_LIKE_f
AR_O **= AR_LIKE_c
AR_O **= AR_LIKE_O

# unary ops

-c16
-c8
-f8
-f4
-i8
-i4
with pytest.warns(RuntimeWarning):
    -u8
    -u4
-td
-AR_f

+c16
+c8
+f8
+f4
+i8
+i4
+u8
+u4
+td
+AR_f

abs(c16)
abs(c8)
abs(f8)
abs(f4)
abs(i8)
abs(i4)
abs(u8)
abs(u4)
abs(td)
abs(b_)
abs(AR_f)

# Time structures

dt + td
dt + i
dt + i4
dt + i8
dt - dt
dt - i
dt - i4
dt - i8

td + td
td + i
td + i4
td + i8
td - td
td - i
td - i4
td - i8
td / f
td / f4
td / f8
td / td
td // td
td % td


# boolean

b_ / b
b_ / b_
b_ / i
b_ / i8
b_ / i4
b_ / u8
b_ / u4
b_ / f
b_ / f8
b_ / f4
b_ / c
b_ / c16
b_ / c8

b / b_
b_ / b_
i / b_
i8 / b_
i4 / b_
u8 / b_
u4 / b_
f / b_
f8 / b_
f4 / b_
c / b_
c16 / b_
c8 / b_

# Complex

c16 + c16
c16 + f8
c16 + i8
c16 + c8
c16 + f4
c16 + i4
c16 + b_
c16 + b
c16 + c
c16 + f
c16 + i
c16 + AR_f

c16 + c16
f8 + c16
i8 + c16
c8 + c16
f4 + c16
i4 + c16
b_ + c16
b + c16
c + c16
f + c16
i + c16
AR_f + c16

c8 + c16
c8 + f8
c8 + i8
c8 + c8
c8 + f4
c8 + i4
c8 + b_
c8 + b
c8 + c
c8 + f
c8 + i
c8 + AR_f

c16 + c8
f8 + c8
i8 + c8
c8 + c8
f4 + c8
i4 + c8
b_ + c8
b + c8
c + c8
f + c8
i + c8
AR_f + c8

# Float

f8 + f8
f8 + i8
f8 + f4
f8 + i4
f8 + b_
f8 + b
f8 + c
f8 + f
f8 + i
f8 + AR_f

f8 + f8
i8 + f8
f4 + f8
i4 + f8
b_ + f8
b + f8
c + f8
f + f8
i + f8
AR_f + f8

f4 + f8
f4 + i8
f4 + f4
f4 + i4
f4 + b_
f4 + b
f4 + c
f4 + f
f4 + i
f4 + AR_f

f8 + f4
i8 + f4
f4 + f4
i4 + f4
b_ + f4
b + f4
c + f4
f + f4
i + f4
AR_f + f4

# Int

i8 + i8
i8 + u8
i8 + i4
i8 + u4
i8 + b_
i8 + b
i8 + c
i8 + f
i8 + i
i8 + AR_f

u8 + u8
u8 + i4
u8 + u4
u8 + b_
u8 + b
u8 + c
u8 + f
u8 + i
u8 + AR_f

i8 + i8
u8 + i8
i4 + i8
u4 + i8
b_ + i8
b + i8
c + i8
f + i8
i + i8
AR_f + i8

u8 + u8
i4 + u8
u4 + u8
b_ + u8
b + u8
c + u8
f + u8
i + u8
AR_f + u8

i4 + i8
i4 + i4
i4 + i
i4 + b_
i4 + b
i4 + AR_f

u4 + i8
u4 + i4
u4 + u8
u4 + u4
u4 + i
u4 + b_
u4 + b
u4 + AR_f

i8 + i4
i4 + i4
i + i4
b_ + i4
b + i4
AR_f + i4

i8 + u4
i4 + u4
u8 + u4
u4 + u4
b_ + u4
b + u4
i + u4
AR_f + u4

Youez - 2016 - github.com/yon3zu
LinuXploit