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4e125a4c01c8df887efbbe5d44a6aeddf0ed626c | 8,630 | py | Python | Batch_TextStopWord.py | yuhonghai123/Flok_muitimodal_operators | d938f158d609f76cd81b5a7516faa7babbe81457 | [
"MIT"
] | 1 | 2021-05-29T08:24:28.000Z | 2021-05-29T08:24:28.000Z | Batch_TextStopWord.py | yuhonghai123/Flok_muitimodal_operators | d938f158d609f76cd81b5a7516faa7babbe81457 | [
"MIT"
] | null | null | null | Batch_TextStopWord.py | yuhonghai123/Flok_muitimodal_operators | d938f158d609f76cd81b5a7516faa7babbe81457 | [
"MIT"
] | null | null | null | # encoding=utf-8
import sys, os
from FlokAlgorithmLocal import FlokDataFrame, FlokAlgorithmLocal
import json
import jieba
import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize
import pandas as pd
class Batch_TextStopWord(FlokAlgorithmLocal):
def run(self, inputDataSets, params):
text_dict = inputDataSets.get(0)
if params["type"] == "CHN":
stop_words_str = ',\n?\n、\n。\n“\n”\n《\n》\n！\n，\n：\n；\n？\n人民\n末##末\n啊\n阿\n哎\n哎呀\n哎哟\n唉\n俺\n俺们\n按\n按照\n吧\n吧哒\n把\n罢了\n被\n本\n本着\n比\n比方\n比如\n鄙人\n彼\n彼此\n边\n别\n别的\n别说\n并\n并且\n不比\n不成\n不单\n不但\n不独\n不管\n不光\n不过\n不仅\n不拘\n不论\n不怕\n不然\n不如\n不特\n不惟\n不问\n不 只\n朝\n朝着\n趁\n趁着\n乘\n冲\n除\n除此之外\n除非\n除了\n此\n此间\n此外\n从\n从而\n打\n待\n但\n但是\n当\n当着\n到\n得\n的\n的话\n等\n等等\n地\n第\n叮咚\n对\n对于\n多\n多少\n而\n而况\n而且\n而是\n而外\n而言\n而已\n尔后\n反过来\n反过来说\n反之\n非但\n非徒\n否则\n嘎\n嘎登\n该\n赶\n个\n各\n各个\n各位\n各种\n各自\n给\n根据\n跟\n故\n故此\n固然\n关于\n管\n归\n果然\n果真\n过\n哈\n哈哈\n呵\n和\n何\n何处\n何况\n何时\n嘿\n哼\n哼唷\n呼哧\n乎\n哗\n还是\n还有\n换句话说\n换言之\n 或\n或是\n或者\n极了\n及\n及其\n及至\n即\n即便\n即或\n即令\n即若\n即使\n几\n几时\n己\n既\n既然\n既是\n继而\n加之\n假如\n假若\n假使\n鉴于\n将\n较\n较之\n叫\n 接着\n结果\n借\n紧接着\n进而\n尽\n尽管\n经\n经过\n就\n就是\n就是说\n据\n具体地说\n具体说来\n开始\n开外\n靠\n咳\n可\n可见\n可是\n可以\n况且\n啦\n来\n来着\n离\n例如\n哩\n连\n连同\n两者\n了\n临\n另\n另外\n另一方面\n论\n嘛\n吗\n慢说\n漫说\n冒\n么\n每\n每当\n们\n莫若\n某\n某个\n某些\n拿\n哪\n哪边\n哪儿\n哪个\n哪里\n哪年\n哪怕\n哪天\n哪些\n哪样\n那\n那边\n那儿\n那个\n那会儿\n那里\n那么\n那么些\n那么样\n那时\n那些\n那样\n乃\n乃至\n呢\n能\n你\n你们\n您\n宁\n宁可\n宁肯\n宁愿\n哦\n呕\n啪达\n旁人\n呸\n凭\n凭借\n其\n其次\n其二\n其他\n其它\n其一\n其余\n其中\n起\n起见\n岂但\n恰恰相反\n前后\n前者\n且\n然而\n然后\n然则\n让\n人家\n任\n任何\n任凭\n如\n如此\n如果\n如何\n如其\n如若\n如上所述\n若\n若非\n若是\n啥\n上下\n尚且\n设若\n设使\n甚而\n甚么\n甚至\n省得\n时候\n什么\n什么样\n使得\n是\n是的\n首先\n谁\n谁知\n顺\n顺着\n似的\n虽\n虽然\n虽说\n虽则\n随\n随着\n所\n所以\n他\n他们\n他人\n它\n它们\n她\n她们\n倘\n倘或\n倘然\n倘若\n倘使\n腾\n替\n通过\n同\n同时\n哇\n万一\n往\n望\n为\n为何\n为了\n为什么\n为着\n喂\n嗡嗡\n我\n我们\n呜\n呜呼\n乌乎\n无论\n无宁\n毋宁\n嘻\n吓\n相对而言\n像\n向\n向着\n嘘\n呀\n焉\n沿\n 沿着\n要\n要不\n要不然\n要不是\n要么\n要是\n也\n也罢\n也好\n一\n一般\n一旦\n一方面\n一来\n一切\n一样\n一则\n依\n依照\n矣\n以\n以便\n以及\n以免\n以至\n以至于\n以致\n抑或\n因\n因此\n因而\n因为\n哟\n用\n由\n由此可见\n由于\n有\n有的\n有关\n有些\n又\n于\n于是\n于是乎\n与\n与此同时\n与否\n与其\n越是\n云云\n哉\n再说\n再者\n在\n在下\n咱\n咱们\n则\n怎\n怎么\n怎么办\n怎么样\n怎样\n咋\n照\n照着\n者\n这\n这边\n这儿\n这个\n这会儿\n这就是说\n这里\n这么\n这么点儿\n这么些\n这么样\n 这时\n这些\n这样\n正如\n吱\n之\n之类\n之所以\n之一\n只是\n只限\n只要\n只有\n至\n至于\n诸位\n着\n着呢\n自\n自从\n自个儿\n自各儿\n自己\n自家\n自身\n综上所述\n 总的来看\n总的来说\n总的说来\n总而言之\n总之\n纵\n纵令\n纵然\n纵使\n遵照\n作为\n兮\n呃\n呗\n咚\n咦\n喏\n啐\n喔唷\n嗬\n嗯\n嗳\n~\n!\n.\n:\n"\n\'\n(\n)\n*\nA\n白\n社会主义\n--\n..\n>>\n [\n ]\n\n<\n>\n/\n\\\n|\n-\n_\n+\n=\n&\n^\n%\n#\n@\n`\n;\n$\n（\n）\n——\n—\n￥\n·\n...\n‘\n’\n〉\n〈\n…\n\u3000\n0\n1\n2\n3\n4\n5\n6\n7\n8\n9\n０\n１\n２\n３\n４\n５\n６\n７\n８\n９\n二\n三\n四\n五\n六\n七\n八\n九\n零\n＞\n＜\n＠\n＃\n＄\n％\n︿\n＆\n＊\n＋\n～\n｜\n［\n］\n｛\n ｝\n啊哈\n啊呀\n啊哟\n挨次\n挨个\n挨家挨户\n挨门挨户\n挨门逐户\n挨着\n按理\n按期\n按时\n按说\n暗地里\n暗中\n暗自\n昂然\n八成\n白白\n半\n梆\n保管\n保险\n饱\n 背地里\n背靠背\n倍感\n倍加\n本人\n本身\n甭\n比起\n比如说\n比照\n毕竟\n必\n必定\n必将\n必须\n便\n别人\n并非\n并肩\n并没\n并没有\n并排\n并无\n勃然\n不\n不必\n 不常\n不大\n不但...而且\n不得\n不得不\n不得了\n不得已\n不迭\n不定\n不对\n不妨\n不管怎样\n不会\n不仅...而且\n不仅仅\n不仅仅是\n不经意\n不可开交\n不可抗拒\n不 力\n不了\n不料\n不满\n不免\n不能不\n不起\n不巧\n不然的话\n不日\n不少\n不胜\n不时\n不是\n不同\n不能\n不要\n不外\n不外乎\n不下\n不限\n不消\n不已\n不亦乐乎\n不 由得\n不再\n不择手段\n不怎么\n不曾\n不知不觉\n不止\n不止一次\n不至于\n才\n才能\n策略地\n差不多\n差一点\n常\n常常\n常言道\n常言说\n常言说得好\n长此下去\n长话 短说\n长期以来\n长线\n敞开儿\n彻夜\n陈年\n趁便\n趁机\n趁热\n趁势\n趁早\n成年\n成年累月\n成心\n乘机\n乘胜\n乘势\n乘隙\n乘虚\n诚然\n迟早\n充分\n充其极\n充其量\n抽冷子\n臭\n初\n出\n出来\n出去\n除此\n除此而外\n除此以外\n除开\n除去\n除却\n除外\n处处\n川流不息\n传\n传说\n传闻\n串行\n纯\n纯粹\n此后\n此中\n次第\n匆匆\n从不\n从此\n从此以后\n从古到今\n从古至今\n从今以后\n从宽\n从来\n从轻\n从速\n从头\n从未\n从无到有\n从小\n从新\n从严\n从优\n从早到晚\n从中\n从重\n凑巧\n粗\n存心\n达旦\n打从\n打开天窗说亮话\n大\n大不了\n大大\n大抵\n大都\n大多\n大凡\n大概\n大家\n大举\n大略\n大面儿上\n大事\n大体\n大体上\n大约\n大张旗鼓\n大致\n呆呆地\n带\n殆\n待到\n单\n单纯\n单单\n但愿\n弹指之间\n当场\n当儿\n当即\n当口儿\n当然\n当庭\n当头\n当下\n当真\n当中\n倒不如\n倒不如说\n倒是\n到处\n到底\n到了儿\n到目前 为止\n到头\n到头来\n得起\n得天独厚\n的确\n等到\n叮当\n顶多\n定\n动不动\n动辄\n陡然\n都\n独\n独自\n断然\n顿时\n多次\n多多\n多多少少\n多多益善\n多亏\n多年来\n 多年前\n而后\n而论\n而又\n尔等\n二话不说\n二话没说\n反倒\n反倒是\n反而\n反手\n反之亦然\n反之则\n方\n方才\n方能\n放量\n非常\n非得\n分期\n分期分批\n分头\n奋勇\n愤然\n风雨无阻\n逢\n弗\n甫\n嘎嘎\n该当\n概\n赶快\n赶早不赶晚\n敢\n敢情\n敢于\n刚\n刚才\n刚好\n刚巧\n高低\n格外\n隔日\n隔夜\n个人\n各式\n更\n更加\n更进一步\n更为\n公然\n共\n共总\n够瞧的\n姑且\n古来\n故而\n故意\n固\n怪\n怪不得\n惯常\n光\n光是\n归根到底\n归根结底\n过于\n毫不\n毫无\n毫无保留地\n毫无例外\n好在\n何必\n何尝\n何妨\n何苦\n何乐而不为\n何须\n何止\n很\n很多\n很少\n轰然\n后来\n呼啦\n忽地\n忽然\n互\n互相\n哗啦\n话说\n还\n恍然\n会\n豁然\n活\n伙同\n或多或少\n或许\n基本\n基本上\n基于\n极\n极大\n极度\n极端\n极力\n极其\n极为\n急匆匆\n即将\n即刻\n即是说\n几度\n几番\n几乎\n几经\n既...又\n继之\n加上\n加以\n间或\n简而言之\n简言之\n简直\n见\n将才\n将近\n将要\n交口\n较比\n较为\n接连不断\n接下来\n皆可\n截然\n截至\n藉以\n借此\n借以\n届时\n仅\n仅仅\n谨\n进来\n进去\n近\n近几年来\n近来\n近年来\n尽管如此\n尽可能\n尽快\n尽量\n尽然\n尽如人意\n尽心竭力\n尽心尽力\n尽早\n精光\n经常\n竟\n竟然\n究竟\n就此\n就地\n就算\n居然\n局外\n举凡\n据称\n据此\n据实\n据说\n据我所知\n据悉\n具体来说\n决不\n决非\n绝\n绝不\n绝顶\n绝对\n绝非\n均\n喀\n看\n看来\n看起来\n看上去\n看样子\n可好\n可能\n恐怕\n快\n快要\n来不及\n 来得及\n来讲\n来看\n拦腰\n牢牢\n老\n老大\n老老实实\n老是\n累次\n累年\n理当\n理该\n理应\n历\n立\n立地\n立刻\n立马\n立时\n联袂\n连连\n连日\n连日来\n连声\n连袂\n临到\n另方面\n另行\n另一个\n路经\n屡\n屡次\n屡次三番\n屡屡\n缕缕\n率尔\n率然\n略\n略加\n略微\n略为\n论说\n马上\n蛮\n满\n没\n没有\n每逢\n每每\n每时每刻\n猛然\n猛然间\n莫\n莫不\n莫非\n莫如\n默默地\n默然\n呐\n那末\n奈\n难道\n难得\n难怪\n难说\n内\n年复一年\n凝神\n偶而\n偶尔\n怕\n砰\n碰巧\n譬如\n偏偏\n乒\n平素\n颇\n 迫于\n扑通\n其后\n其实\n奇\n齐\n起初\n起来\n起首\n起头\n起先\n岂\n岂非\n岂止\n迄\n恰逢\n恰好\n恰恰\n恰巧\n恰如\n恰似\n千\n千万\n千万千万\n切\n切不可\n切莫\n 切切\n切勿\n窃\n亲口\n亲身\n亲手\n亲眼\n亲自\n顷\n顷刻\n顷刻间\n顷刻之间\n请勿\n穷年累月\n取道\n去\n权时\n全都\n全力\n全年\n全然\n全身心\n然\n人人\n仍\n仍旧\n仍然\n日复一日\n日见\n日渐\n日益\n日臻\n如常\n如此等等\n如次\n如今\n如期\n如前所述\n如上\n如下\n汝\n三番两次\n三番五次\n三天两头\n瑟瑟\n沙沙\n上\n上来\n上去'
stopwords = [line.rstrip() for line in stop_words_str.split('\n')]
for text_name, text in text_dict.items():
seg_list = jieba.cut(text)
text_dict[text_name] = " ".join([d for d in seg_list if d not in stopwords])
elif params["type"] == "ENG":
stopwords = ['very', 'ourselves', 'am', 'doesn', 'through', 'me', 'against', 'up', 'just', 'her', 'ours',
'couldn', 'because', 'is', 'isn', 'it', 'only', 'in', 'such', 'too', 'mustn', 'under', 'their',
'if', 'to', 'my', 'himself', 'after', 'why', 'while', 'can', 'each', 'itself', 'his', 'all',
'once',
'herself', 'more', 'our', 'they', 'hasn', 'on', 'ma', 'them', 'its', 'where', 'did', 'll',
'you',
'didn', 'nor', 'as', 'now', 'before', 'those', 'yours', 'from', 'who', 'was', 'm', 'been',
'will',
'into', 'same', 'how', 'some', 'of', 'out', 'with', 's', 'being', 't', 'mightn', 'she',
'again', 'be',
'by', 'shan', 'have', 'yourselves', 'needn', 'and', 'are', 'o', 'these', 'further', 'most',
'yourself',
'having', 'aren', 'here', 'he', 'were', 'but', 'this', 'myself', 'own', 'we', 'so', 'i',
'does', 'both',
'when', 'between', 'd', 'had', 'the', 'y', 'has', 'down', 'off', 'than', 'haven', 'whom',
'wouldn',
'should', 've', 'over', 'themselves', 'few', 'then', 'hadn', 'what', 'until', 'won', 'no',
'about',
'any', 'that', 'for', 'shouldn', 'don', 'do', 'there', 'doing', 'an', 'or', 'ain', 'hers',
'wasn',
'weren', 'above', 'a', 'at', 'your', 'theirs', 'below', 'other', 'not', 're', 'him', 'during',
'which']
for text_name, text in text_dict.items():
word_tokens = word_tokenize(text)
text_dict[text_name] = " ".join([w for w in word_tokens if w not in stopwords])
result = FlokDataFrame()
result.addDF(text_dict)
return result
if __name__ == "__main__":
all_info = json.loads(sys.argv[1])
# f = open("test.json", encoding='utf-8')
# all_info = json.load(f)
# all_info = {
# "input": ["data/chinese.txt"],
# "inputFormat":["txt"],
# "inputLocation": ["local_fs"],
# "output": ["data/chinese_stopword.txt"],
# "outputFormat": ["txt"],
# "outputLocation":["local_fs"],
# "parameters": {"language":"CHN"}#CHN/ENG
# }
params = all_info["parameters"]
inputPaths = all_info["input"]
inputTypes = all_info["inputFormat"]
inputLocation = all_info["inputLocation"]
outputPaths = all_info["output"]
outputTypes = all_info["outputFormat"]
outputLocation = all_info["outputLocation"]
algorithm = Batch_TextStopWord()
dataSet = algorithm.read(inputPaths, inputTypes, inputLocation, outputPaths, outputTypes)
result = algorithm.run(dataSet, params)
algorithm.write(outputPaths, result, outputTypes, outputLocation)
| 110.641026 | 4,815 | 0.620278 | 1,622 | 8,630 | 3.279901 | 0.84402 | 0.022932 | 0.031015 | 0.036842 | 0.039662 | 0.039662 | 0.030639 | 0.029323 | 0.018045 | 0.014662 | 0 | 0.0038 | 0.146118 | 8,630 | 77 | 4,816 | 112.077922 | 0.716651 | 0.039745 | 0 | 0.033898 | 0 | 0.016949 | 0.318892 | 0.234318 | 0 | 0 | 0 | 0 | 0 | 1 | 0.016949 | false | 0 | 0.135593 | 0 | 0.186441 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4e170045be47044a2dda4db6df3ae4aa5f117272 | 574 | py | Python | week_07/tests/test_my_math.py | vlasenckov/MIPT_py_3_term | ffe30371221017d61a22e18300f059d9f7086740 | [
"MIT"
] | 5 | 2020-10-05T15:21:11.000Z | 2020-12-17T19:19:32.000Z | week_07/tests/test_my_math.py | vlasenckov/MIPT_py_3_term | ffe30371221017d61a22e18300f059d9f7086740 | [
"MIT"
] | 8 | 2020-09-24T10:36:15.000Z | 2020-11-30T10:54:56.000Z | week_07/tests/test_my_math.py | vlasenckov/MIPT_py_3_term | ffe30371221017d61a22e18300f059d9f7086740 | [
"MIT"
] | 2 | 2020-10-11T13:08:35.000Z | 2020-12-04T19:54:21.000Z | from my_mathematics.simple_math import MyMath
import math
import pytest
@pytest.mark.parametrize('x', [0, 1, 2, 3, 4, 5, 0.01, 3e-7, 232, 213123, 392, 921])
def test_check_sine(x):
assert math.sin(x) == MyMath.sin(x)
def test_check_pi():
assert round(math.pi, 2) == MyMath.pi
@pytest.mark.parametrize('x', [0, 1, 2, 3, 4, 5, 0.01, 3e-7, 232, 213123, 392, 921])
def test_check_sqrt(x):
assert math.sqrt(x) == MyMath.sqrt(x)
@pytest.mark.xfail
@pytest.mark.parametrize('x', [-1, -4, -5, -2])
def test_neg_sqrt(x):
assert math.sqrt(x) == MyMath.sqrt(x)
| 23.916667 | 84 | 0.65331 | 105 | 574 | 3.47619 | 0.333333 | 0.082192 | 0.172603 | 0.180822 | 0.50411 | 0.50411 | 0.50411 | 0.50411 | 0.50411 | 0.334247 | 0 | 0.117526 | 0.155052 | 574 | 23 | 85 | 24.956522 | 0.635052 | 0 | 0 | 0.266667 | 0 | 0 | 0.005226 | 0 | 0 | 0 | 0 | 0 | 0.266667 | 1 | 0.266667 | false | 0 | 0.2 | 0 | 0.466667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4e271d262a5491b9974966194def88d93a6961c5 | 373 | py | Python | src/drkns/generation/GenerationTemplate.py | frantzmiccoli/drkns | 75d1259d7430cff2f62a557d9ae8e0826effc1bd | [
"X11"
] | 13 | 2021-05-18T21:30:30.000Z | 2022-03-17T18:16:13.000Z | src/drkns/generation/GenerationTemplate.py | frantzmiccoli/drkns | 75d1259d7430cff2f62a557d9ae8e0826effc1bd | [
"X11"
] | null | null | null | src/drkns/generation/GenerationTemplate.py | frantzmiccoli/drkns | 75d1259d7430cff2f62a557d9ae8e0826effc1bd | [
"X11"
] | null | null | null |
class GenerationTemplate:
def __init__(
self,
source_path: str,
template: str,
group_template: str,
unit_template: str
):
self.source_path: str = source_path
self.template: str = template
self.group_template: str = group_template
self.unit_template: str = unit_template
| 23.3125 | 49 | 0.579088 | 38 | 373 | 5.342105 | 0.289474 | 0.325123 | 0.137931 | 0.167488 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.356568 | 373 | 15 | 50 | 24.866667 | 0.845833 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.083333 | false | 0 | 0 | 0 | 0.166667 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4e2cd87278c919f5add5d70e390d11b28fdd9806 | 132 | py | Python | OOP_Python/4_Jueves/calculos/__init__.py | aMurryFly/Old_Courses | d5d105cbdcd3c4a35bf38fc60acfe76ce403bed3 | [
"MIT"
] | null | null | null | OOP_Python/4_Jueves/calculos/__init__.py | aMurryFly/Old_Courses | d5d105cbdcd3c4a35bf38fc60acfe76ce403bed3 | [
"MIT"
] | null | null | null | OOP_Python/4_Jueves/calculos/__init__.py | aMurryFly/Old_Courses | d5d105cbdcd3c4a35bf38fc60acfe76ce403bed3 | [
"MIT"
] | null | null | null | #Son directorios donde se almacenan módulos
'''
1) Crear una carpeta con un archivo __init__.py <- constructor
'''
| 12 | 63 | 0.651515 | 16 | 132 | 5.125 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010309 | 0.265152 | 132 | 10 | 64 | 13.2 | 0.835052 | 0.795455 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4e383540c73e930de3781f6952a9d448a067f6a4 | 230 | py | Python | tictac/tictac/setup.py | SteveDMurphy/tic_tac_go | 7e80dc1ec6fbeceb3c9879cee7fb32b7ecfe37a7 | [
"MIT"
] | null | null | null | tictac/tictac/setup.py | SteveDMurphy/tic_tac_go | 7e80dc1ec6fbeceb3c9879cee7fb32b7ecfe37a7 | [
"MIT"
] | null | null | null | tictac/tictac/setup.py | SteveDMurphy/tic_tac_go | 7e80dc1ec6fbeceb3c9879cee7fb32b7ecfe37a7 | [
"MIT"
] | null | null | null | from setuptools import setup
setup(
name="tictac",
version="0.1",
py_modules=["cli"],
install_requires=[
"Click",
],
entry_points="""
[console_scripts]
tictac=cli:tictac
""",
)
| 15.333333 | 28 | 0.543478 | 23 | 230 | 5.26087 | 0.826087 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012422 | 0.3 | 230 | 14 | 29 | 16.428571 | 0.73913 | 0 | 0 | 0 | 0 | 0 | 0.321739 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.076923 | 0 | 0.076923 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
9d68b8f97af4b31c3ebc01950b3c1de8d16cff3c | 3,504 | py | Python | tests/ml_utils/test_plot_cv_indices.py | jameshtwose/jmspack | b226519c1b8a0007f3d59eb8117234e63194d745 | [
"BSD-3-Clause"
] | null | null | null | tests/ml_utils/test_plot_cv_indices.py | jameshtwose/jmspack | b226519c1b8a0007f3d59eb8117234e63194d745 | [
"BSD-3-Clause"
] | 4 | 2021-03-21T14:46:19.000Z | 2021-12-21T09:33:56.000Z | tests/ml_utils/test_plot_cv_indices.py | jameshtwose/jmspack | b226519c1b8a0007f3d59eb8117234e63194d745 | [
"BSD-3-Clause"
] | null | null | null | # import matplotlib
# import matplotlib.pyplot as plt
# import pytest
# import seaborn as sns
#
# from jmspack.ml_utils import plot_cv_indices
#
#
# @pytest.fixture
# def df_test():
# """test dataset from seaborn"""
# return sns.load_dataset("iris")
#
#
# class TestPlotCvIndices:
# """Testing class to test the plot_decision_boundary function."""
#
# def test_if_dataframe_not_affected(self, df_test):
# """Check if the function leaves the data frame the same."""
# feature_list = df_test.columns.tolist()[0:2]
# target = "species"
# X = df_test[feature_list]
# y = df_test[target]
# X_original = X.copy()
# y_original = y.copy()
# _, _ = plot_decision_boundary(X=X, y=y)
# assert X_original.equals(X)
# assert y_original.equals(y)
#
# def test_returns_expected_objects(self, df_test):
# """Check if the function returns the expected output objects."""
# feature_list = df_test.columns.tolist()[0:2]
# target = "species"
# X = df_test[feature_list]
# y = df_test[target]
# fig, ax = plot_decision_boundary(X=X, y=y)
#
# assert isinstance(fig, matplotlib.figure.Figure)
# assert isinstance(ax, matplotlib.axes.Axes)
#
# def test_ax_attributes(self, df_test):
# """Check if the function outputs the expected axis object."""
# feature_list = df_test.columns.tolist()[0:2]
# target = "species"
# X = df_test[feature_list]
# y = df_test[target]
# fig, ax = plot_decision_boundary(X=X, y=y,
# clf = LogisticRegression(),
# title = 'Decision Boundary Logistic Regression',
# legend_title = 'Legend',
# h = 0.05,
# figsize = (11.7, 8.27))
# _ = plt.show(block=False)
#
# test_y_ticklabels = ["Text(0, 1.0, '1.0')", "Text(0, 1.5, '1.5')", "Text(0, 2.0, '2.0')"]
# test_x_ticklabels = ["Text(3.0, 0, '3')", "Text(4.0, 0, '4')", "Text(5.0, 0, '5')"]
# ax_y_ticklabels = [str(x) for x in list(ax.get_yticklabels()[:3])]
# ax_x_ticklabels = [str(x) for x in list(ax.get_xticklabels()[:3])]
#
# assert ax_x_ticklabels == test_x_ticklabels
# assert ax_y_ticklabels == test_y_ticklabels
#
# _ = plt.pause(1)
# _ = plt.close(fig=fig)
#
# # for this test to run you will need to make sure that
# # pytest-mpl is installed and that you have the baseline images
# # by running `pytest --mpl-generate-path=baseline` in the same
# # directory as the test files
# @pytest.mark.mpl_image_compare
# def test_plot_decision_boundary(self, df_test):
# """Check if the function returns the expected figure (compared to a baseline plot)."""
# feature_list = df_test.columns.tolist()[0:2]
# target = "species"
# X = df_test[feature_list]
# y = df_test[target]
# fig, ax = plot_decision_boundary(X=X, y=y,
# clf=LogisticRegression(),
# title='Decision Boundary Logistic Regression',
# legend_title='Legend',
# h=0.05,
# figsize=(11.7, 8.27))
# return fig
#
| 41.223529 | 99 | 0.543094 | 430 | 3,504 | 4.234884 | 0.288372 | 0.056013 | 0.065898 | 0.032949 | 0.450851 | 0.450851 | 0.450851 | 0.420099 | 0.400329 | 0.368479 | 0 | 0.02384 | 0.329623 | 3,504 | 84 | 100 | 41.714286 | 0.751384 | 0.950628 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
9d69659f81d75e4acb554702a6e9d3090d940e3d | 4,350 | py | Python | spirit.py | electric-blue-green/micro-spirit | 8d61250d710c9f4f28e6e215593d34d6facf5b4e | [
"MIT"
] | 1 | 2021-06-05T03:12:53.000Z | 2021-06-05T03:12:53.000Z | spirit.py | aejb/micro-spirit | 8d61250d710c9f4f28e6e215593d34d6facf5b4e | [
"MIT"
] | 1 | 2017-09-28T08:27:41.000Z | 2017-09-28T08:27:41.000Z | spirit.py | aejb/micro-spirit | 8d61250d710c9f4f28e6e215593d34d6facf5b4e | [
"MIT"
] | 2 | 2017-09-28T08:09:19.000Z | 2017-09-29T08:43:32.000Z | from microbit import *
# Images
# /
r_roll = Image("00009:" "00090:" "00900:" "09000:" "90000")
# -
c_roll = Image("00000:" "00000:" "99999:" "00000:" "00000")
# \
l_roll = Image("90000:" "09000:" "00900:" "00090:" "00009")
# \-\
l_h_roll = Image("00000:" "90000:" "09990:" "00009:" "00000")
# /-/
r_h_roll = Image("00000:" "00009:" "09990:" "90000:" "00000")
# |
h_roll = Image("00900:" "00900:" "00900:" "00900:" "00900")
# +
d_roll = Image("00000:" "00500:" "99999:" "00500:" "00000")
# /|/
r_n_roll = Image("00090:" "00900:" "00900:" "00900:" "09000")
# \|\
l_n_roll = Image("09000:" "00900:" "00900:" "00900:" "00090")
# <->
startim = Image("00000:" "09090:" "99999:" "09090:" "00000")
# Main
compass.calibrate()
while True:
button = 2
display.show(startim)
if button_a.is_pressed() == True:
button = 0
elif button_b.is_pressed() == True:
button = 1
else:
button = button
if button == 0:
display.show(" ")
while True:
roll = accelerometer.get_x()
pitch = accelerometer.get_y()
if -1024 <= roll <= -900: # horizontal
display.show(h_roll)
elif -900 <= roll <= -700: # near horizontal left
display.show(l_n_roll)
elif -700 <= roll <= -500: # left
display.show(l_roll)
elif -500 <= roll <= -100: # near vertical left
display.show(l_h_roll)
elif -100 <= roll <= -40: # vertical
display.show(c_roll)
elif -40 <= roll <= 40: # dead centre
display.show(d_roll)
elif 40 <= roll <= 100: # vertical
display.show(c_roll)
elif 100 <= roll <= 500: # near vertical right
display.show(r_h_roll)
elif 500 <= roll <= 700: # right
display.show(r_roll)
elif 700 <= roll <= 900: # near horizontal right
display.show(r_n_roll)
elif 900 <= roll <= 1024: # horizontal
display.show(h_roll)
elif button_b.is_pressed() == True:
button = 1
elif button == 1:
display.show(" ")
while True:
pitch = accelerometer.get_y()
if -1024 <= pitch <= -500:
display.set_pixel(2, 0, 9)
display.set_pixel(2, 1, 0)
display.set_pixel(2, 2, 0)
display.set_pixel(2, 3, 0)
display.set_pixel(2, 4, 0)
elif -500 <= pitch <= -100:
display.set_pixel(2, 0, 0)
display.set_pixel(2, 1, 9)
display.set_pixel(2, 2, 0)
display.set_pixel(2, 3, 0)
display.set_pixel(2, 4, 0)
elif -100 <= pitch <= 100:
display.set_pixel(2, 0, 0)
display.set_pixel(2, 1, 0)
display.set_pixel(2, 2, 9)
display.set_pixel(2, 3, 0)
display.set_pixel(2, 4, 0)
elif 100 <= pitch <= 500:
display.set_pixel(2, 0, 0)
display.set_pixel(2, 1, 0)
display.set_pixel(2, 2, 0)
display.set_pixel(2, 3, 9)
display.set_pixel(2, 4, 0)
elif 500 <= pitch <= 1024:
display.set_pixel(2, 0, 0)
display.set_pixel(2, 1, 0)
display.set_pixel(2, 2, 0)
display.set_pixel(2, 3, 0)
display.set_pixel(2, 4, 9)
else:
display.show(" ")
yaw = accelerometer.get_z()
if -1200 <= yaw <= -1024:
display.set_pixel(0, 2, 0)
display.set_pixel(1, 2, 0)
display.set_pixel(2, 2, 9)
display.set_pixel(3, 2, 0)
display.set_pixel(4, 2, 0)
elif -1024 <= yaw <= -500:
display.set_pixel(0, 2, 0)
display.set_pixel(1, 2, 9)
display.set_pixel(3, 2, 9)
display.set_pixel(4, 2, 0)
elif -500 <= yaw <= 1024:
display.set_pixel(0, 2, 9)
display.set_pixel(1, 2, 0)
display.set_pixel(3, 2, 0)
display.set_pixel(4, 2, 9)
else:
display.show(" ")
| 36.864407 | 62 | 0.470575 | 532 | 4,350 | 3.704887 | 0.12594 | 0.192796 | 0.289193 | 0.21106 | 0.506849 | 0.504313 | 0.419077 | 0.366312 | 0.334855 | 0.30898 | 0 | 0.182294 | 0.384598 | 4,350 | 117 | 63 | 37.179487 | 0.553978 | 0.042759 | 0 | 0.47619 | 0 | 0 | 0.071014 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.009524 | 0.009524 | 0 | 0.009524 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
9d79eea16be8de87daee1bd2d2619d3525130748 | 154 | py | Python | Flask API/post_test.py | exodustw/NYCU-E3-CAPTCHA-Autowrite | 73d8e155911e5f36d9a9c5e736e8cb57c8651fc3 | [
"CC-BY-3.0"
] | null | null | null | Flask API/post_test.py | exodustw/NYCU-E3-CAPTCHA-Autowrite | 73d8e155911e5f36d9a9c5e736e8cb57c8651fc3 | [
"CC-BY-3.0"
] | null | null | null | Flask API/post_test.py | exodustw/NYCU-E3-CAPTCHA-Autowrite | 73d8e155911e5f36d9a9c5e736e8cb57c8651fc3 | [
"CC-BY-3.0"
] | null | null | null | import requests
url = 'http://127.0.0.1:5000/e3autologin'
files = {'file': open('0009.png', 'rb')}
rq = requests.post(url, files=files)
print(rq.text)
| 17.111111 | 41 | 0.662338 | 25 | 154 | 4.08 | 0.76 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.110294 | 0.116883 | 154 | 8 | 42 | 19.25 | 0.639706 | 0 | 0 | 0 | 0 | 0 | 0.305195 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.2 | 0 | 0.2 | 0.2 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
9d9498fb7571470bbc851bf623ae21ecda187300 | 46,595 | py | Python | __WXFB_BLR_LMGR.py | daakru/BLReLM | ad1001c101821356abff711c1ed4d3178a77baa7 | [
"MIT"
] | null | null | null | __WXFB_BLR_LMGR.py | daakru/BLReLM | ad1001c101821356abff711c1ed4d3178a77baa7 | [
"MIT"
] | null | null | null | __WXFB_BLR_LMGR.py | daakru/BLReLM | ad1001c101821356abff711c1ed4d3178a77baa7 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
###########################################################################
## Python code generated with wxFormBuilder (version 3.10.0-35-gd79d7781)
## http://www.wxformbuilder.org/
##
## PLEASE DO *NOT* EDIT THIS FILE!
###########################################################################
from bitmap_panel import BitmapPanel
from part_select_panel import PartSelectPanel
import wx
import wx.xrc
import wx.stc
###########################################################################
## Class BLR_LMGR_FRAME
###########################################################################
class BLR_LMGR_FRAME ( wx.Frame ):
def __init__( self, parent ):
wx.Frame.__init__ ( self, parent, id = wx.ID_ANY, title = u"BLRevive Loadout Manager", pos = wx.DefaultPosition, size = wx.Size( 1280,720 ), style = wx.DEFAULT_FRAME_STYLE|wx.TAB_TRAVERSAL )
self.SetSizeHints( wx.DefaultSize, wx.DefaultSize )
self.SetBackgroundColour( wx.Colour( 0, 0, 64 ) )
bSizer_blrlm_main = wx.BoxSizer( wx.HORIZONTAL )
bSizer3 = wx.BoxSizer( wx.VERTICAL )
self.m_panel_blrlm_preview = BitmapPanel( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_STATIC|wx.TAB_TRAVERSAL )
self.m_panel_blrlm_preview.SetBackgroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_SCROLLBAR ) )
bSizer_blrlm_preview = wx.BoxSizer( wx.VERTICAL )
bSizer_blrlm_preview.SetMinSize( wx.Size( 420,-1 ) )
self.m_bitmap_blrlm_preview = wx.StaticBitmap( self.m_panel_blrlm_preview, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 260,132 ), wx.BORDER_SIMPLE )
bSizer_blrlm_preview.Add( self.m_bitmap_blrlm_preview, 0, wx.ALIGN_CENTER|wx.ALL|wx.FIXED_MINSIZE, 4 )
self.m_panel_blrlm_preview.SetSizer( bSizer_blrlm_preview )
self.m_panel_blrlm_preview.Layout()
bSizer_blrlm_preview.Fit( self.m_panel_blrlm_preview )
bSizer3.Add( self.m_panel_blrlm_preview, 0, wx.FIXED_MINSIZE|wx.LEFT|wx.RIGHT|wx.TOP, 8 )
self.m_panel_partselect = BitmapPanel( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_STATIC|wx.TAB_TRAVERSAL )
self.m_panel_partselect.SetBackgroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_SCROLLBAR ) )
bSizer19 = wx.BoxSizer( wx.VERTICAL )
bSizerPartSelect = wx.BoxSizer( wx.VERTICAL )
self.m_panel_partselect_re1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_re1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSRE1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_receiver = wx.BitmapToggleButton( self.m_panel_partselect_re1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_receiver.SetValue( True )
self.m_bmToggleBtn_blrlm_receiver.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_receiver.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSRE1.Add( self.m_bmToggleBtn_blrlm_receiver, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_receiver = wx.StaticBitmap( self.m_panel_partselect_re1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_receiver.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_receiver.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSRE1.Add( self.m_bitmap_blrlm_receiver, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_receiver = wx.StaticText( self.m_panel_partselect_re1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_receiver.Wrap( -1 )
self.m_staticText_blrlm_receiver.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSRE1.Add( self.m_staticText_blrlm_receiver, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_receiver_reset = wx.BitmapButton( self.m_panel_partselect_re1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_receiver_reset.SetBitmapPosition( wx.BOTTOM )
self.m_bpButton_blrlm_receiver_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSRE1.Add( self.m_bpButton_blrlm_receiver_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_re1.SetSizer( bSizerPSRE1 )
self.m_panel_partselect_re1.Layout()
bSizerPSRE1.Fit( self.m_panel_partselect_re1 )
bSizerPartSelect.Add( self.m_panel_partselect_re1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel_partselect_mz1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_mz1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSMZ1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_muzzle = wx.BitmapToggleButton( self.m_panel_partselect_mz1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_muzzle.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_muzzle.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSMZ1.Add( self.m_bmToggleBtn_blrlm_muzzle, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_muzzle = wx.StaticBitmap( self.m_panel_partselect_mz1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_muzzle.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_muzzle.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSMZ1.Add( self.m_bitmap_blrlm_muzzle, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_muzzle = wx.StaticText( self.m_panel_partselect_mz1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_muzzle.Wrap( -1 )
self.m_staticText_blrlm_muzzle.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSMZ1.Add( self.m_staticText_blrlm_muzzle, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_muzzle_reset = wx.BitmapButton( self.m_panel_partselect_mz1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_muzzle_reset.SetBitmapPosition( wx.BOTTOM )
self.m_bpButton_blrlm_muzzle_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSMZ1.Add( self.m_bpButton_blrlm_muzzle_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_mz1.SetSizer( bSizerPSMZ1 )
self.m_panel_partselect_mz1.Layout()
bSizerPSMZ1.Fit( self.m_panel_partselect_mz1 )
bSizerPartSelect.Add( self.m_panel_partselect_mz1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel_partselect_gp1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_gp1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSGP1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_grip = wx.BitmapToggleButton( self.m_panel_partselect_gp1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_grip.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_grip.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSGP1.Add( self.m_bmToggleBtn_blrlm_grip, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_grip = wx.StaticBitmap( self.m_panel_partselect_gp1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_grip.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_grip.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSGP1.Add( self.m_bitmap_blrlm_grip, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_grip = wx.StaticText( self.m_panel_partselect_gp1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_grip.Wrap( -1 )
self.m_staticText_blrlm_grip.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSGP1.Add( self.m_staticText_blrlm_grip, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_grip_reset = wx.BitmapButton( self.m_panel_partselect_gp1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_grip_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSGP1.Add( self.m_bpButton_blrlm_grip_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_gp1.SetSizer( bSizerPSGP1 )
self.m_panel_partselect_gp1.Layout()
bSizerPSGP1.Fit( self.m_panel_partselect_gp1 )
bSizerPartSelect.Add( self.m_panel_partselect_gp1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel_partselect_ba1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_ba1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSBA1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_barrel = wx.BitmapToggleButton( self.m_panel_partselect_ba1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_barrel.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_barrel.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSBA1.Add( self.m_bmToggleBtn_blrlm_barrel, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_barrel = wx.StaticBitmap( self.m_panel_partselect_ba1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_barrel.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_barrel.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSBA1.Add( self.m_bitmap_blrlm_barrel, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_barrel = wx.StaticText( self.m_panel_partselect_ba1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_barrel.Wrap( -1 )
self.m_staticText_blrlm_barrel.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSBA1.Add( self.m_staticText_blrlm_barrel, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_barrel_reset = wx.BitmapButton( self.m_panel_partselect_ba1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_barrel_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSBA1.Add( self.m_bpButton_blrlm_barrel_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_ba1.SetSizer( bSizerPSBA1 )
self.m_panel_partselect_ba1.Layout()
bSizerPSBA1.Fit( self.m_panel_partselect_ba1 )
bSizerPartSelect.Add( self.m_panel_partselect_ba1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel_partselect_mg1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_mg1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSMG1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_magazine = wx.BitmapToggleButton( self.m_panel_partselect_mg1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_magazine.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_magazine.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSMG1.Add( self.m_bmToggleBtn_blrlm_magazine, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_magazine = wx.StaticBitmap( self.m_panel_partselect_mg1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_magazine.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_magazine.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSMG1.Add( self.m_bitmap_blrlm_magazine, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_magazine = wx.StaticText( self.m_panel_partselect_mg1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_magazine.Wrap( -1 )
self.m_staticText_blrlm_magazine.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSMG1.Add( self.m_staticText_blrlm_magazine, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_magazine_reset = wx.BitmapButton( self.m_panel_partselect_mg1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_magazine_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSMG1.Add( self.m_bpButton_blrlm_magazine_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_mg1.SetSizer( bSizerPSMG1 )
self.m_panel_partselect_mg1.Layout()
bSizerPSMG1.Fit( self.m_panel_partselect_mg1 )
bSizerPartSelect.Add( self.m_panel_partselect_mg1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel_partselect_sc1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_sc1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSSC1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_scope = wx.BitmapToggleButton( self.m_panel_partselect_sc1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_scope.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_scope.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSSC1.Add( self.m_bmToggleBtn_blrlm_scope, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_scope = wx.StaticBitmap( self.m_panel_partselect_sc1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_scope.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_scope.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSSC1.Add( self.m_bitmap_blrlm_scope, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_scope = wx.StaticText( self.m_panel_partselect_sc1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_scope.Wrap( -1 )
self.m_staticText_blrlm_scope.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSSC1.Add( self.m_staticText_blrlm_scope, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_scope_reset = wx.BitmapButton( self.m_panel_partselect_sc1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_scope_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSSC1.Add( self.m_bpButton_blrlm_scope_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_sc1.SetSizer( bSizerPSSC1 )
self.m_panel_partselect_sc1.Layout()
bSizerPSSC1.Fit( self.m_panel_partselect_sc1 )
bSizerPartSelect.Add( self.m_panel_partselect_sc1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel_partselect_st1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_st1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSST1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_stock = wx.BitmapToggleButton( self.m_panel_partselect_st1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_stock.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_stock.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSST1.Add( self.m_bmToggleBtn_blrlm_stock, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_stock = wx.StaticBitmap( self.m_panel_partselect_st1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_stock.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_stock.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSST1.Add( self.m_bitmap_blrlm_stock, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_stock = wx.StaticText( self.m_panel_partselect_st1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_stock.Wrap( -1 )
self.m_staticText_blrlm_stock.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSST1.Add( self.m_staticText_blrlm_stock, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_stock_reset = wx.BitmapButton( self.m_panel_partselect_st1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_stock_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSST1.Add( self.m_bpButton_blrlm_stock_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_st1.SetSizer( bSizerPSST1 )
self.m_panel_partselect_st1.Layout()
bSizerPSST1.Fit( self.m_panel_partselect_st1 )
bSizerPartSelect.Add( self.m_panel_partselect_st1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel_partselect_tg1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_tg1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSTG1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_tag = wx.BitmapToggleButton( self.m_panel_partselect_tg1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_tag.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_tag.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSTG1.Add( self.m_bmToggleBtn_blrlm_tag, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_tag = wx.StaticBitmap( self.m_panel_partselect_tg1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_tag.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_tag.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSTG1.Add( self.m_bitmap_blrlm_tag, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_tag = wx.StaticText( self.m_panel_partselect_tg1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_tag.Wrap( -1 )
self.m_staticText_blrlm_tag.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSTG1.Add( self.m_staticText_blrlm_tag, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_tag_reset = wx.BitmapButton( self.m_panel_partselect_tg1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_tag_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSTG1.Add( self.m_bpButton_blrlm_tag_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_tg1.SetSizer( bSizerPSTG1 )
self.m_panel_partselect_tg1.Layout()
bSizerPSTG1.Fit( self.m_panel_partselect_tg1 )
bSizerPartSelect.Add( self.m_panel_partselect_tg1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel_partselect_cm1 = wx.Panel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
self.m_panel_partselect_cm1.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSCM1 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtn_blrlm_camo = wx.BitmapToggleButton( self.m_panel_partselect_cm1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BORDER_NONE )
self.m_bmToggleBtn_blrlm_camo.SetBitmap( wx.NullBitmap )
self.m_bmToggleBtn_blrlm_camo.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
bSizerPSCM1.Add( self.m_bmToggleBtn_blrlm_camo, 0, wx.ALL, 0 )
self.m_bitmap_blrlm_camo = wx.StaticBitmap( self.m_panel_partselect_cm1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_bitmap_blrlm_camo.SetMinSize( wx.Size( 64,32 ) )
self.m_bitmap_blrlm_camo.SetMaxSize( wx.Size( 64,32 ) )
bSizerPSCM1.Add( self.m_bitmap_blrlm_camo, 0, wx.LEFT|wx.RIGHT, 8 )
self.m_staticText_blrlm_camo = wx.StaticText( self.m_panel_partselect_cm1, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText_blrlm_camo.Wrap( -1 )
self.m_staticText_blrlm_camo.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizerPSCM1.Add( self.m_staticText_blrlm_camo, 1, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 0 )
self.m_bpButton_blrlm_camo_reset = wx.BitmapButton( self.m_panel_partselect_cm1, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.Size( 32,32 ), wx.BU_AUTODRAW|0|wx.BORDER_NONE )
self.m_bpButton_blrlm_camo_reset.SetBackgroundColour( wx.Colour( 0, 64, 128 ) )
bSizerPSCM1.Add( self.m_bpButton_blrlm_camo_reset, 0, wx.ALL, 0 )
self.m_panel_partselect_cm1.SetSizer( bSizerPSCM1 )
self.m_panel_partselect_cm1.Layout()
bSizerPSCM1.Fit( self.m_panel_partselect_cm1 )
bSizerPartSelect.Add( self.m_panel_partselect_cm1, 0, wx.EXPAND |wx.ALL, 4 )
self.m_panel14 = PartSelectPanel( self.m_panel_partselect, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_SIMPLE )
bSizerPartSelect.Add( self.m_panel14, 0, wx.EXPAND |wx.ALL, 4 )
bSizer19.Add( bSizerPartSelect, 0, wx.EXPAND, 0 )
bSizer22 = wx.BoxSizer( wx.VERTICAL )
bSizer24 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtnLoadout1 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnLoadout1.SetValue( True )
self.m_bmToggleBtnLoadout1.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnLoadout1.Enable( False )
self.m_bmToggleBtnLoadout1.SetMinSize( wx.Size( 130,24 ) )
bSizer24.Add( self.m_bmToggleBtnLoadout1, 0, wx.LEFT|wx.RIGHT, 2 )
bSizer24.Add( ( 0, 0), 1, wx.EXPAND, 5 )
self.m_bmToggleBtnLoadout2 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnLoadout2.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnLoadout2.Enable( False )
self.m_bmToggleBtnLoadout2.SetMinSize( wx.Size( 130,24 ) )
bSizer24.Add( self.m_bmToggleBtnLoadout2, 0, wx.LEFT|wx.RIGHT, 2 )
bSizer24.Add( ( 0, 0), 1, wx.EXPAND, 5 )
self.m_bmToggleBtnLoadout3 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnLoadout3.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnLoadout3.Enable( False )
self.m_bmToggleBtnLoadout3.SetMinSize( wx.Size( 130,24 ) )
bSizer24.Add( self.m_bmToggleBtnLoadout3, 0, wx.LEFT|wx.RIGHT, 2 )
bSizer22.Add( bSizer24, 0, wx.EXPAND, 0 )
bSizer21 = wx.BoxSizer( wx.HORIZONTAL )
bSizer221 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtnPrimary1 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnPrimary1.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnPrimary1.SetMinSize( wx.Size( 64,64 ) )
bSizer221.Add( self.m_bmToggleBtnPrimary1, 0, wx.LEFT|wx.RIGHT|wx.TOP, 2 )
self.m_bmToggleBtnSecondary1 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnSecondary1.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnSecondary1.SetMinSize( wx.Size( 64,64 ) )
bSizer221.Add( self.m_bmToggleBtnSecondary1, 0, wx.BOTTOM|wx.RIGHT|wx.TOP, 2 )
bSizer21.Add( bSizer221, 0, wx.EXPAND, 5 )
bSizer21.Add( ( 0, 0), 1, wx.EXPAND, 5 )
bSizer211 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtnPrimary2 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnPrimary2.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnPrimary2.SetMinSize( wx.Size( 64,64 ) )
bSizer211.Add( self.m_bmToggleBtnPrimary2, 0, wx.LEFT|wx.RIGHT|wx.TOP, 2 )
self.m_bmToggleBtnSecondary2 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnSecondary2.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnSecondary2.SetMinSize( wx.Size( 64,64 ) )
bSizer211.Add( self.m_bmToggleBtnSecondary2, 0, wx.BOTTOM|wx.RIGHT|wx.TOP, 2 )
bSizer21.Add( bSizer211, 0, wx.EXPAND, 5 )
bSizer21.Add( ( 0, 0), 1, wx.EXPAND, 5 )
bSizer2111 = wx.BoxSizer( wx.HORIZONTAL )
self.m_bmToggleBtnPrimary3 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnPrimary3.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnPrimary3.SetMinSize( wx.Size( 64,64 ) )
bSizer2111.Add( self.m_bmToggleBtnPrimary3, 0, wx.LEFT|wx.RIGHT|wx.TOP, 2 )
self.m_bmToggleBtnSecondary3 = wx.BitmapToggleButton( self.m_panel_partselect, wx.ID_ANY, wx.NullBitmap, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_NONE )
self.m_bmToggleBtnSecondary3.SetBackgroundColour( wx.Colour( 48, 48, 48 ) )
self.m_bmToggleBtnSecondary3.SetMinSize( wx.Size( 64,64 ) )
bSizer2111.Add( self.m_bmToggleBtnSecondary3, 0, wx.BOTTOM|wx.RIGHT|wx.TOP, 2 )
bSizer21.Add( bSizer2111, 0, wx.EXPAND, 5 )
bSizer22.Add( bSizer21, 1, wx.EXPAND, 5 )
bSizer19.Add( bSizer22, 0, wx.ALL|wx.EXPAND, 4 )
self.m_panel_partselect.SetSizer( bSizer19 )
self.m_panel_partselect.Layout()
bSizer19.Fit( self.m_panel_partselect )
bSizer3.Add( self.m_panel_partselect, 1, wx.EXPAND |wx.ALL, 8 )
bSizer_blrlm_main.Add( bSizer3, 0, wx.EXPAND, 0 )
bSizer10 = wx.BoxSizer( wx.VERTICAL )
self.m_listCtrl_blrlm_selector = wx.ListCtrl( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.LC_HRULES|wx.LC_REPORT|wx.LC_SINGLE_SEL|wx.BORDER_SIMPLE )
self.m_listCtrl_blrlm_selector.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_WINDOWTEXT ) )
self.m_listCtrl_blrlm_selector.SetBackgroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_WINDOW ) )
self.m_listCtrl_blrlm_selector.SetMinSize( wx.Size( 720,480 ) )
bSizer10.Add( self.m_listCtrl_blrlm_selector, 1, wx.BOTTOM|wx.EXPAND|wx.RIGHT|wx.TOP, 8 )
self.m_panel11 = BitmapPanel( self, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.BORDER_STATIC )
bSizer11 = wx.BoxSizer( wx.HORIZONTAL )
bSizer14 = wx.BoxSizer( wx.VERTICAL )
bSizer12 = wx.BoxSizer( wx.HORIZONTAL )
self.m_staticText6 = wx.StaticText( self.m_panel11, wx.ID_ANY, wx.EmptyString, wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText6.Wrap( -1 )
self.m_staticText6.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizer12.Add( self.m_staticText6, 0, wx.LEFT, 4 )
bSizer14.Add( bSizer12, 1, wx.EXPAND, 5 )
bSizer11.Add( bSizer14, 1, wx.EXPAND, 5 )
bSizer15 = wx.BoxSizer( wx.HORIZONTAL )
bSizer15.SetMinSize( wx.Size( 512,-1 ) )
self.m_panel121 = wx.Panel( self.m_panel11, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, wx.TAB_TRAVERSAL )
self.m_panel121.Enable( False )
self.m_panel121.Hide()
bSizer121 = wx.BoxSizer( wx.HORIZONTAL )
self.m_staticText61 = wx.StaticText( self.m_panel121, wx.ID_ANY, u"Export Path:", wx.DefaultPosition, wx.DefaultSize, 0 )
self.m_staticText61.Wrap( -1 )
self.m_staticText61.SetForegroundColour( wx.SystemSettings.GetColour( wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
self.m_staticText61.Enable( False )
self.m_staticText61.Hide()
bSizer121.Add( self.m_staticText61, 0, wx.ALIGN_CENTER_VERTICAL|wx.LEFT, 4 )
self.m_dirPicker1 = wx.DirPickerCtrl( self.m_panel121, wx.ID_ANY, wx.EmptyString, u"Select a folder", wx.DefaultPosition, wx.DefaultSize, wx.DIRP_DIR_MUST_EXIST|wx.DIRP_USE_TEXTCTRL )
self.m_dirPicker1.Enable( False )
self.m_dirPicker1.Hide()
bSizer121.Add( self.m_dirPicker1, 0, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 4 )
self.m_button_export_loadout = wx.Button( self.m_panel121, wx.ID_ANY, u"Generate Loadout", wx.DefaultPosition, wx.DefaultSize, 0|wx.BORDER_THEME )
bSizer121.Add( self.m_button_export_loadout, 0, wx.ALIGN_CENTER_VERTICAL|wx.ALL, 4 )
self.m_panel121.SetSizer( bSizer121 )
self.m_panel121.Layout()
bSizer121.Fit( self.m_panel121 )
bSizer15.Add( self.m_panel121, 0, wx.ALL, 4 )
self.m_scintilla1 = wx.stc.StyledTextCtrl( self.m_panel11, wx.ID_ANY, wx.DefaultPosition, wx.DefaultSize, 0)
self.m_scintilla1.SetUseTabs ( False )
self.m_scintilla1.SetTabWidth ( 4 )
self.m_scintilla1.SetIndent ( 4 )
self.m_scintilla1.SetTabIndents( True )
self.m_scintilla1.SetBackSpaceUnIndents( True )
self.m_scintilla1.SetViewEOL( False )
self.m_scintilla1.SetViewWhiteSpace( False )
self.m_scintilla1.SetMarginWidth( 2, 0 )
self.m_scintilla1.SetIndentationGuides( False )
self.m_scintilla1.SetReadOnly( False );
self.m_scintilla1.SetMarginWidth( 1, 0 )
self.m_scintilla1.SetMarginWidth ( 0, 0 )
self.m_scintilla1.MarkerDefine( wx.stc.STC_MARKNUM_FOLDER, wx.stc.STC_MARK_BOXPLUS )
self.m_scintilla1.MarkerSetBackground( wx.stc.STC_MARKNUM_FOLDER, wx.BLACK)
self.m_scintilla1.MarkerSetForeground( wx.stc.STC_MARKNUM_FOLDER, wx.WHITE)
self.m_scintilla1.MarkerDefine( wx.stc.STC_MARKNUM_FOLDEROPEN, wx.stc.STC_MARK_BOXMINUS )
self.m_scintilla1.MarkerSetBackground( wx.stc.STC_MARKNUM_FOLDEROPEN, wx.BLACK )
self.m_scintilla1.MarkerSetForeground( wx.stc.STC_MARKNUM_FOLDEROPEN, wx.WHITE )
self.m_scintilla1.MarkerDefine( wx.stc.STC_MARKNUM_FOLDERSUB, wx.stc.STC_MARK_EMPTY )
self.m_scintilla1.MarkerDefine( wx.stc.STC_MARKNUM_FOLDEREND, wx.stc.STC_MARK_BOXPLUS )
self.m_scintilla1.MarkerSetBackground( wx.stc.STC_MARKNUM_FOLDEREND, wx.BLACK )
self.m_scintilla1.MarkerSetForeground( wx.stc.STC_MARKNUM_FOLDEREND, wx.WHITE )
self.m_scintilla1.MarkerDefine( wx.stc.STC_MARKNUM_FOLDEROPENMID, wx.stc.STC_MARK_BOXMINUS )
self.m_scintilla1.MarkerSetBackground( wx.stc.STC_MARKNUM_FOLDEROPENMID, wx.BLACK)
self.m_scintilla1.MarkerSetForeground( wx.stc.STC_MARKNUM_FOLDEROPENMID, wx.WHITE)
self.m_scintilla1.MarkerDefine( wx.stc.STC_MARKNUM_FOLDERMIDTAIL, wx.stc.STC_MARK_EMPTY )
self.m_scintilla1.MarkerDefine( wx.stc.STC_MARKNUM_FOLDERTAIL, wx.stc.STC_MARK_EMPTY )
self.m_scintilla1.SetSelBackground( True, wx.SystemSettings.GetColour(wx.SYS_COLOUR_HIGHLIGHT ) )
self.m_scintilla1.SetSelForeground( True, wx.SystemSettings.GetColour(wx.SYS_COLOUR_HIGHLIGHTTEXT ) )
bSizer15.Add( self.m_scintilla1, 1, wx.ALL|wx.EXPAND, 4 )
bSizer11.Add( bSizer15, 0, wx.EXPAND, 5 )
self.m_panel11.SetSizer( bSizer11 )
self.m_panel11.Layout()
bSizer11.Fit( self.m_panel11 )
bSizer10.Add( self.m_panel11, 1, wx.BOTTOM|wx.EXPAND|wx.RIGHT, 8 )
bSizer_blrlm_main.Add( bSizer10, 1, wx.EXPAND, 0 )
self.SetSizer( bSizer_blrlm_main )
self.Layout()
self.m_menubar1 = wx.MenuBar( 0|wx.BORDER_THEME|wx.CLIP_CHILDREN )
self.file = wx.Menu()
self.m_menuItem_file_playername = wx.MenuItem( self.file, wx.ID_ANY, u"Change Player Name", wx.EmptyString, wx.ITEM_NORMAL )
self.file.Append( self.m_menuItem_file_playername )
self.m_menuItem_file_playername.Enable( False )
self.m_menuItem_file_clearloadouts = wx.MenuItem( self.file, wx.ID_ANY, u"Clear All Loadouts", wx.EmptyString, wx.ITEM_NORMAL )
self.file.Append( self.m_menuItem_file_clearloadouts )
self.m_menuItem_file_clearloadouts.Enable( False )
self.m_menuItem_file_savesession = wx.MenuItem( self.file, wx.ID_ANY, u"Save Session", wx.EmptyString, wx.ITEM_NORMAL )
self.file.Append( self.m_menuItem_file_savesession )
self.m_menuItem_file_loadsession = wx.MenuItem( self.file, wx.ID_ANY, u"Load Session", wx.EmptyString, wx.ITEM_NORMAL )
self.file.Append( self.m_menuItem_file_loadsession )
self.m_menuItem_file_autosave = wx.MenuItem( self.file, wx.ID_ANY, u"Save Session on Exit", wx.EmptyString, wx.ITEM_CHECK )
self.file.Append( self.m_menuItem_file_autosave )
self.m_menuItem_file_autosave.Check( True )
self.m_menubar1.Append( self.file, u"File" )
self.edit = wx.Menu()
self.m_menuItem_edit_swapweapon = wx.MenuItem( self.edit, wx.ID_ANY, u"Swap Weapon", wx.EmptyString, wx.ITEM_NORMAL )
self.edit.Append( self.m_menuItem_edit_swapweapon )
self.m_menuItem_edit_swapweapon.Enable( False )
self.m_menubar1.Append( self.edit, u"Edit" )
self.view = wx.Menu()
self.m_menuItem_view_0 = wx.MenuItem( self.view, wx.ID_ANY, u"Some checkbox thing", wx.EmptyString, wx.ITEM_CHECK )
self.view.Append( self.m_menuItem_view_0 )
self.m_menuItem_view_0.Enable( False )
self.m_menubar1.Append( self.view, u"View" )
self.tools = wx.Menu()
self.m_menubar1.Append( self.tools, u"Tools" )
self.help = wx.Menu()
self.m_menuItem_about = wx.MenuItem( self.help, wx.ID_ANY, u"About", wx.EmptyString, wx.ITEM_NORMAL )
self.help.Append( self.m_menuItem_about )
self.m_menuItem_about.Enable( False )
self.m_menubar1.Append( self.help, u"Help" )
self.SetMenuBar( self.m_menubar1 )
self.Centre( wx.BOTH )
# Connect Events
self.Bind( wx.EVT_CLOSE, self.BLR_LMGR_FRAMEOnClose )
self.m_panel_partselect_re1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_re1OnLeftUp )
self.m_bmToggleBtn_blrlm_receiver.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_receiverOnToggleButton )
self.m_bitmap_blrlm_receiver.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_receiverOnLeftUp )
self.m_staticText_blrlm_receiver.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_receiverOnLeftUp )
self.m_bpButton_blrlm_receiver_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_receiver_resetOnButtonClick )
self.m_panel_partselect_mz1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_mz1OnLeftUp )
self.m_bmToggleBtn_blrlm_muzzle.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_muzzleOnToggleButton )
self.m_bitmap_blrlm_muzzle.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_muzzleOnLeftUp )
self.m_staticText_blrlm_muzzle.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_muzzleOnLeftUp )
self.m_bpButton_blrlm_muzzle_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_muzzle_resetOnButtonClick )
self.m_panel_partselect_gp1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_gp1OnLeftUp )
self.m_bmToggleBtn_blrlm_grip.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_gripOnToggleButton )
self.m_bitmap_blrlm_grip.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_gripOnLeftUp )
self.m_staticText_blrlm_grip.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_gripOnLeftUp )
self.m_bpButton_blrlm_grip_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_grip_resetOnButtonClick )
self.m_panel_partselect_ba1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_ba1OnLeftUp )
self.m_bmToggleBtn_blrlm_barrel.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_barrelOnToggleButton )
self.m_bitmap_blrlm_barrel.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_barrelOnLeftUp )
self.m_staticText_blrlm_barrel.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_barrelOnLeftUp )
self.m_bpButton_blrlm_barrel_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_barrel_resetOnButtonClick )
self.m_panel_partselect_mg1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_mg1OnLeftUp )
self.m_bmToggleBtn_blrlm_magazine.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_magazineOnToggleButton )
self.m_bitmap_blrlm_magazine.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_magazineOnLeftUp )
self.m_staticText_blrlm_magazine.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_magazineOnLeftUp )
self.m_bpButton_blrlm_magazine_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_magazine_resetOnButtonClick )
self.m_panel_partselect_sc1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_sc1OnLeftUp )
self.m_bmToggleBtn_blrlm_scope.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_scopeOnToggleButton )
self.m_bitmap_blrlm_scope.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_scopeOnLeftUp )
self.m_staticText_blrlm_scope.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_scopeOnLeftUp )
self.m_bpButton_blrlm_scope_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_scope_resetOnButtonClick )
self.m_panel_partselect_st1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_st1OnLeftUp )
self.m_bmToggleBtn_blrlm_stock.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_stockOnToggleButton )
self.m_bitmap_blrlm_stock.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_stockOnLeftUp )
self.m_staticText_blrlm_stock.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_stockOnLeftUp )
self.m_bpButton_blrlm_stock_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_stock_resetOnButtonClick )
self.m_panel_partselect_tg1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_tg1OnLeftUp )
self.m_bmToggleBtn_blrlm_tag.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_tagOnToggleButton )
self.m_bitmap_blrlm_tag.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_tagOnLeftUp )
self.m_staticText_blrlm_tag.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_tagOnLeftUp )
self.m_bpButton_blrlm_tag_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_tag_resetOnButtonClick )
self.m_panel_partselect_cm1.Bind( wx.EVT_LEFT_UP, self.m_panel_partselect_cm1OnLeftUp )
self.m_bmToggleBtn_blrlm_camo.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtn_blrlm_camoOnToggleButton )
self.m_bitmap_blrlm_camo.Bind( wx.EVT_LEFT_UP, self.m_bitmap_blrlm_camoOnLeftUp )
self.m_staticText_blrlm_camo.Bind( wx.EVT_LEFT_UP, self.m_staticText_blrlm_camoOnLeftUp )
self.m_bpButton_blrlm_camo_reset.Bind( wx.EVT_BUTTON, self.m_bpButton_blrlm_camo_resetOnButtonClick )
self.m_bmToggleBtnLoadout1.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnLoadout1OnToggleButton )
self.m_bmToggleBtnLoadout2.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnLoadout2OnToggleButton )
self.m_bmToggleBtnLoadout3.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnLoadout3OnToggleButton )
self.m_bmToggleBtnPrimary1.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnPrimary1OnToggleButton )
self.m_bmToggleBtnSecondary1.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnSecondary1OnToggleButton )
self.m_bmToggleBtnPrimary2.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnPrimary2OnToggleButton )
self.m_bmToggleBtnSecondary2.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnSecondary2OnToggleButton )
self.m_bmToggleBtnPrimary3.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnPrimary3OnToggleButton )
self.m_bmToggleBtnSecondary3.Bind( wx.EVT_TOGGLEBUTTON, self.m_bmToggleBtnSecondary3OnToggleButton )
self.m_listCtrl_blrlm_selector.Bind( wx.EVT_LIST_ITEM_ACTIVATED, self.m_listCtrl_blrlm_selectorOnListItemActivated )
self.m_listCtrl_blrlm_selector.Bind( wx.EVT_LIST_ITEM_FOCUSED, self.m_listCtrl_blrlm_selectorOnListItemFocused )
self.m_button_export_loadout.Bind( wx.EVT_BUTTON, self.m_button_export_loadoutOnButtonClick )
self.m_scintilla1.Bind( wx.EVT_LEFT_DCLICK, self.m_scintilla1OnLeftDClick )
self.Bind( wx.EVT_MENU, self.m_menuItem_file_playernameOnMenuSelection, id = self.m_menuItem_file_playername.GetId() )
self.Bind( wx.EVT_MENU, self.m_menuItem_file_clearloadoutsOnMenuSelection, id = self.m_menuItem_file_clearloadouts.GetId() )
self.Bind( wx.EVT_MENU, self.m_menuItem_file_savesessionOnMenuSelection, id = self.m_menuItem_file_savesession.GetId() )
self.Bind( wx.EVT_MENU, self.m_menuItem_file_loadsessionOnMenuSelection, id = self.m_menuItem_file_loadsession.GetId() )
self.Bind( wx.EVT_MENU, self.m_menuItem_file_autosaveOnMenuSelection, id = self.m_menuItem_file_autosave.GetId() )
self.Bind( wx.EVT_MENU, self.m_menuItem_aboutOnMenuSelection, id = self.m_menuItem_about.GetId() )
def __del__( self ):
pass
# Virtual event handlers, override them in your derived class
def BLR_LMGR_FRAMEOnClose( self, event ):
event.Skip()
def m_panel_partselect_re1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_receiverOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_receiverOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_receiverOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_receiver_resetOnButtonClick( self, event ):
event.Skip()
def m_panel_partselect_mz1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_muzzleOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_muzzleOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_muzzleOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_muzzle_resetOnButtonClick( self, event ):
event.Skip()
def m_panel_partselect_gp1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_gripOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_gripOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_gripOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_grip_resetOnButtonClick( self, event ):
event.Skip()
def m_panel_partselect_ba1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_barrelOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_barrelOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_barrelOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_barrel_resetOnButtonClick( self, event ):
event.Skip()
def m_panel_partselect_mg1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_magazineOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_magazineOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_magazineOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_magazine_resetOnButtonClick( self, event ):
event.Skip()
def m_panel_partselect_sc1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_scopeOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_scopeOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_scopeOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_scope_resetOnButtonClick( self, event ):
event.Skip()
def m_panel_partselect_st1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_stockOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_stockOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_stockOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_stock_resetOnButtonClick( self, event ):
event.Skip()
def m_panel_partselect_tg1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_tagOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_tagOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_tagOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_tag_resetOnButtonClick( self, event ):
event.Skip()
def m_panel_partselect_cm1OnLeftUp( self, event ):
event.Skip()
def m_bmToggleBtn_blrlm_camoOnToggleButton( self, event ):
event.Skip()
def m_bitmap_blrlm_camoOnLeftUp( self, event ):
event.Skip()
def m_staticText_blrlm_camoOnLeftUp( self, event ):
event.Skip()
def m_bpButton_blrlm_camo_resetOnButtonClick( self, event ):
event.Skip()
def m_bmToggleBtnLoadout1OnToggleButton( self, event ):
event.Skip()
def m_bmToggleBtnLoadout2OnToggleButton( self, event ):
event.Skip()
def m_bmToggleBtnLoadout3OnToggleButton( self, event ):
event.Skip()
def m_bmToggleBtnPrimary1OnToggleButton( self, event ):
event.Skip()
def m_bmToggleBtnSecondary1OnToggleButton( self, event ):
event.Skip()
def m_bmToggleBtnPrimary2OnToggleButton( self, event ):
event.Skip()
def m_bmToggleBtnSecondary2OnToggleButton( self, event ):
event.Skip()
def m_bmToggleBtnPrimary3OnToggleButton( self, event ):
event.Skip()
def m_bmToggleBtnSecondary3OnToggleButton( self, event ):
event.Skip()
def m_listCtrl_blrlm_selectorOnListItemActivated( self, event ):
event.Skip()
def m_listCtrl_blrlm_selectorOnListItemFocused( self, event ):
event.Skip()
def m_button_export_loadoutOnButtonClick( self, event ):
event.Skip()
def m_scintilla1OnLeftDClick( self, event ):
event.Skip()
def m_menuItem_file_playernameOnMenuSelection( self, event ):
event.Skip()
def m_menuItem_file_clearloadoutsOnMenuSelection( self, event ):
event.Skip()
def m_menuItem_file_savesessionOnMenuSelection( self, event ):
event.Skip()
def m_menuItem_file_loadsessionOnMenuSelection( self, event ):
event.Skip()
def m_menuItem_file_autosaveOnMenuSelection( self, event ):
event.Skip()
def m_menuItem_aboutOnMenuSelection( self, event ):
event.Skip()
| 50.318575 | 198 | 0.72819 | 6,207 | 46,595 | 5.15692 | 0.056549 | 0.082945 | 0.07098 | 0.083102 | 0.813771 | 0.661814 | 0.559561 | 0.496298 | 0.363023 | 0.263457 | 0 | 0.030332 | 0.168623 | 46,595 | 925 | 199 | 50.372973 | 0.795963 | 0.005365 | 0 | 0.115 | 1 | 0 | 0.00441 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111667 | false | 0.001667 | 0.008333 | 0 | 0.121667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
9d98e6f2359c70626136cd7b96f24ec664668729 | 74 | py | Python | poem.py | hvoort/mashup | 50dc81ed21707f2032670144de80ca9d96288359 | [
"MIT"
] | null | null | null | poem.py | hvoort/mashup | 50dc81ed21707f2032670144de80ca9d96288359 | [
"MIT"
] | null | null | null | poem.py | hvoort/mashup | 50dc81ed21707f2032670144de80ca9d96288359 | [
"MIT"
] | null | null | null | from lights import *
open_car()
horn()
start_engine()
stop_engine()
| 6.166667 | 20 | 0.689189 | 10 | 74 | 4.8 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.189189 | 74 | 11 | 21 | 6.727273 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.2 | 0 | 0.2 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
9d9c26447bfe565fc280d4204f8b5cc00c70b3c4 | 142 | py | Python | 2382.py | ShawonBarman/URI-Online-judge-Ad-Hoc-level-problem-solution-in-python | 9a0f0ad5efd4a9e73589c357ab4b34b7c73a11da | [
"MIT"
] | 1 | 2022-01-14T08:45:32.000Z | 2022-01-14T08:45:32.000Z | 2382.py | ShawonBarman/URI-Online-judge-Ad-Hoc-level-problem-solution-in-python | 9a0f0ad5efd4a9e73589c357ab4b34b7c73a11da | [
"MIT"
] | null | null | null | 2382.py | ShawonBarman/URI-Online-judge-Ad-Hoc-level-problem-solution-in-python | 9a0f0ad5efd4a9e73589c357ab4b34b7c73a11da | [
"MIT"
] | null | null | null | import math
l, a, p, r = map(int, input().split())
dia = math.sqrt((l*l)+(a*a)+(p*p))
if dia <= 2*r:
print("S")
else:
print("N") | 20.285714 | 39 | 0.492958 | 28 | 142 | 2.5 | 0.642857 | 0.057143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.009091 | 0.225352 | 142 | 7 | 40 | 20.285714 | 0.627273 | 0 | 0 | 0 | 0 | 0 | 0.014599 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 0 | 0.142857 | 0.285714 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
9d9f3b79e2a3d5c5392ba0cddc7547927747b4b6 | 1,673 | py | Python | apps/watch/main.py | cr0mbly/TTGO-esp32-micropython-watch | 3378ea3b15e19f6bab405b6fc07759f17dd6213d | [
"MIT"
] | 6 | 2020-09-10T20:04:49.000Z | 2021-10-10T06:26:05.000Z | apps/watch/main.py | cr0mbly/TTGO-esp32-micropython-watch | 3378ea3b15e19f6bab405b6fc07759f17dd6213d | [
"MIT"
] | null | null | null | apps/watch/main.py | cr0mbly/TTGO-esp32-micropython-watch | 3378ea3b15e19f6bab405b6fc07759f17dd6213d | [
"MIT"
] | null | null | null | from st7789 import BLACK, WHITE
import vga1_8x8 as font
from apps.utils import BaseApp
SECOND_TO_TRIGGER_DISPLAY_UPDATE = 59
SECOND_TO_RESET_DISPLAY_UPDATE = 0
class WatchDisplay(BaseApp):
has_already_updated = False
def setup(self):
self.lcd_display.enable_screen()
self.display_time()
def loop(self):
if self.current_second == SECOND_TO_TRIGGER_DISPLAY_UPDATE:
if self.has_already_updated:
return
else:
self.display_time()
self.has_already_updated = True
elif self.current_second == SECOND_TO_RESET_DISPLAY_UPDATE:
self.has_already_updated = False
else:
return
@property
def current_year(self):
return self.system_manager.system_time[0]
@property
def current_month(self):
return self.system_manager.system_time[1]
@property
def current_day(self):
return self.system_manager.system_time[2]
@property
def current_hour(self):
return self.system_manager.system_time[4]
@property
def current_minute(self):
return self.system_manager.system_time[5]
@property
def current_second(self):
return self.system_manager.system_time[6]
@property
def current_ms(self):
return self.system_manager.system_time[7]
@property
def formatted_time(self):
return str(self.current_hour) + ':' + str(self.current_minute)
def display_time(self):
self.lcd_display.st7789_display.text(
font,
self.formatted_time,
104,
1,
WHITE
)
| 23.9 | 70 | 0.641363 | 203 | 1,673 | 4.995074 | 0.29064 | 0.086785 | 0.12426 | 0.138067 | 0.395464 | 0.255424 | 0.255424 | 0 | 0 | 0 | 0 | 0.020886 | 0.284519 | 1,673 | 69 | 71 | 24.246377 | 0.826232 | 0 | 0 | 0.264151 | 0 | 0 | 0.000598 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.207547 | false | 0 | 0.056604 | 0.150943 | 0.490566 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 |
9dae0cb4d7df90ee936d3228545e48c4e9063a9f | 1,173 | py | Python | aj-accountant.py | Llona/aj-accountant | a367a3629f953a29bf0b4ee3930e46119b360a6c | [
"Apache-2.0"
] | null | null | null | aj-accountant.py | Llona/aj-accountant | a367a3629f953a29bf0b4ee3930e46119b360a6c | [
"Apache-2.0"
] | null | null | null | aj-accountant.py | Llona/aj-accountant | a367a3629f953a29bf0b4ee3930e46119b360a6c | [
"Apache-2.0"
] | null | null | null | # -*- coding: UTF-8 -*-
import openpyxl
import shutil
import os
import const_define
# active sheet name
# print(workbook.active)
# load excel file
workbook = openpyxl.load_workbook(const_define.DETAILED_LEDGER_FULL_PATH, data_only=True)
# get all sheet name
# worksheets = workbook.get_sheet_names()
worksheets = tuple(workbook.sheetnames)
print(worksheets)
for i in worksheets:
print(i)
# get sheet content
sheet = workbook[worksheets[0]]
# print(sheet)
# print(sheet.title)
# print(sheet.cell(row=2, column=2).value)
# print(sheet['J2'].value)
for rowOfCell in sheet['B2':'M2']:
for cell in rowOfCell:
# print(cell.coordinate, cell.value)
print(cell.value)
# shutil.copyfile(os.path.join('T:'), os.path.join('ttt.txt'))
# filename_netdriver = os.path.join(r"t:", 'vv')
# filename_netdriver = os.path.join(filename_netdriver, 'Roy')
# filename_netdriver = os.path.join(filename_netdriver, 'command.txt')
# print(filename_netdriver)
# shutil.copy(filename_netdriver, DATA_FOLDER_FULL_PATH)
# filename_netdriver = os.path.join(r"t:", r'vv\Roy\command.txt')
# print(filename_netdriver)
# shutil.copy(filename_netdriver, DATA_FOLDER_FULL_PATH)
| 27.27907 | 89 | 0.739983 | 167 | 1,173 | 5.047904 | 0.353293 | 0.201661 | 0.071174 | 0.109134 | 0.355872 | 0.355872 | 0.355872 | 0.182681 | 0.182681 | 0.182681 | 0 | 0.006763 | 0.117647 | 1,173 | 42 | 90 | 27.928571 | 0.807729 | 0.641091 | 0 | 0 | 0 | 0 | 0.010025 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.307692 | 0 | 0.307692 | 0.230769 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
9db4c960164ee219588ac7778e637683a166e153 | 597 | py | Python | celery-demo/celery_app/tasks.py | twtrubiks/docker-django-celery-tutorial | 4f9a1c897ad0c4c7f2d5cd0406e9d055281ad810 | [
"MIT"
] | 45 | 2018-03-04T18:55:52.000Z | 2022-01-14T01:41:53.000Z | celery-demo/celery_app/tasks.py | twtrubiks/docker-django-celery-tutorial | 4f9a1c897ad0c4c7f2d5cd0406e9d055281ad810 | [
"MIT"
] | 3 | 2018-05-31T17:37:26.000Z | 2021-01-11T09:54:16.000Z | celery-demo/celery_app/tasks.py | twtrubiks/docker-django-celery-tutorial | 4f9a1c897ad0c4c7f2d5cd0406e9d055281ad810 | [
"MIT"
] | 10 | 2018-03-04T16:32:27.000Z | 2021-11-21T15:16:00.000Z | import time
from celery import chain
from celery_app import app
@app.task
def add(x, y):
return x + y
'''
ref. http://docs.celeryq.org/en/latest/userguide/tasks.html#avoid-launching-synchronous-subtasks
'''
def chain_demo(x, y):
# add_demo -> mul_demo -> insert_db_demo
chain(add_demo.s(x, y), mul_demo.s(10), insert_db_demo.s())()
@app.task
def add_demo(x, y):
time.sleep(3)
return x + y
@app.task
def mul_demo(x, y):
time.sleep(3)
return x * y
@app.task(ignore_result=True)
def insert_db_demo(result):
print('insert db , result {}'.format(result))
| 15.710526 | 96 | 0.666667 | 102 | 597 | 3.754902 | 0.382353 | 0.041775 | 0.078329 | 0.067885 | 0.16188 | 0.16188 | 0.16188 | 0.16188 | 0.16188 | 0.16188 | 0 | 0.00818 | 0.180905 | 597 | 37 | 97 | 16.135135 | 0.775051 | 0.065327 | 0 | 0.368421 | 0 | 0 | 0.04646 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.263158 | false | 0 | 0.157895 | 0.052632 | 0.578947 | 0.052632 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
9dbc58906a8183ba8e298317d7256bb87acade34 | 2,025 | py | Python | log_async/stats.py | stevelr/python-log-async | 76ce1247647a013caba04257a42e8c451998a8ee | [
"MIT"
] | null | null | null | log_async/stats.py | stevelr/python-log-async | 76ce1247647a013caba04257a42e8c451998a8ee | [
"MIT"
] | null | null | null | log_async/stats.py | stevelr/python-log-async | 76ce1247647a013caba04257a42e8c451998a8ee | [
"MIT"
] | null | null | null | # stat counters for logging handlers
try:
from prometheus_client import Counter, Gauge
except ImportError:
# to avoid a forced dependency on prometheus_client,
# use a super-minimalist implementation of counter.
# since these are used within same thread, no mutexes are needed.
class Value:
def __init__(self, name, desc=''):
self._name = name
self._desc = desc
self._value = 0
def inc(self, n=1):
self._value += n
def dec(self, n=1):
self._value -= n
def val(self):
return (self._name, self._value)
def reset(self):
self._value = 0
class Counter(Value):
pass
class Gauge(Value):
def set(self, n):
self._value = n
class StatsCollector(object):
def __init__(self, prefix):
self._all = []
self.prefix = prefix
def get_stats(self):
return [v.val() for v in self._all]
class LogStats(StatsCollector):
def __init__(self, prefix):
super(LogStats, self).__init__(prefix)
self._events = Counter(prefix + "events_total", "events received")
self._discarded = Counter(prefix + "discarded_total", "events discarded")
self._buffered = Gauge(prefix + "buffered_events", "events currently buffered")
self._sent = Counter(prefix + "sent_total", "events sent to upstream collector")
self._all.extend([self._events, self._discarded, self._buffered, self._sent])
def event(self, n=1):
self._events.inc(n)
def send(self, n=1):
self._sent.inc(n)
def discard(self, n=1):
self._discarded.inc(n)
def buffer(self, n=1):
self._buffered.inc(n)
def unbuffer(self, n=1):
self._buffered.dec(min(self._buffered.val()[1], n))
# lookup - finds stat with s in the name. s should be lower case. Used for testing
def lookup(stats, s):
for (k, v) in stats:
if k.lower().find(s) != -1:
return v
| 27 | 88 | 0.602963 | 266 | 2,025 | 4.406015 | 0.338346 | 0.03413 | 0.035836 | 0.059727 | 0.06314 | 0.032423 | 0.032423 | 0 | 0 | 0 | 0 | 0.007571 | 0.282469 | 2,025 | 74 | 89 | 27.364865 | 0.799036 | 0.138272 | 0 | 0.081633 | 0 | 0 | 0.081081 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.306122 | false | 0.020408 | 0.040816 | 0.040816 | 0.510204 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
9dc47482a2e08888d340cc65ce103d2bbea2ee82 | 911 | py | Python | Models/nn/DiagLayer.py | ianxmason/Fewshot_Learning_of_Homogeneous_Human_Locomotion_Styles | 7fc993e9f918d30cfc19b6560963d7d7358209e1 | [
"MIT"
] | 25 | 2019-01-03T20:10:41.000Z | 2022-03-21T06:42:51.000Z | Models/nn/DiagLayer.py | ianxmason/Fewshot_Learning_of_Homogeneous_Human_Locomotion_Styles | 7fc993e9f918d30cfc19b6560963d7d7358209e1 | [
"MIT"
] | null | null | null | Models/nn/DiagLayer.py | ianxmason/Fewshot_Learning_of_Homogeneous_Human_Locomotion_Styles | 7fc993e9f918d30cfc19b6560963d7d7358209e1 | [
"MIT"
] | 1 | 2019-03-06T23:39:49.000Z | 2019-03-06T23:39:49.000Z | import numpy as np
import theano
import theano.tensor as T
from theano.tensor.shared_randomstreams import RandomStreams
from Layer import Layer
class DiagLayer(Layer):
def __init__(self, weights_shape, rng=np.random, gamma=0.01):
assert weights_shape[-2] == 1 # Diagonal weight matrix is the same as taking a vector of size input and doing an element wise multiplciation
W_bound = np.sqrt(6. / np.prod(weights_shape[-2:]))
W = np.asarray(
rng.uniform(low=-W_bound, high=W_bound, size=weights_shape),
dtype=theano.config.floatX)
self.W = theano.shared(name='W', value=W, borrow=True)
self.params = [self.W]
self.gamma = gamma
def cost(self, input):
return self.gamma * T.mean(abs(self.W))
def __call__(self, input):
return self.W * input # elementwise multiplication
| 29.387097 | 148 | 0.644347 | 127 | 911 | 4.496063 | 0.535433 | 0.084063 | 0.045534 | 0.06655 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01034 | 0.256861 | 911 | 31 | 149 | 29.387097 | 0.833087 | 0.148189 | 0 | 0 | 0 | 0 | 0.001294 | 0 | 0 | 0 | 0 | 0 | 0.052632 | 1 | 0.157895 | false | 0 | 0.263158 | 0.105263 | 0.578947 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 2 |
9dd8a3dcff8b5e6350fcf5cc34483e0164acbf82 | 56 | py | Python | Strings/Triple_Quoted_Strings.py | obareau/python_travaux_pratiques | 2205f4c253e96e409b56f5c23d6e23387ab46524 | [
"MIT"
] | 1 | 2021-11-01T12:45:50.000Z | 2021-11-01T12:45:50.000Z | Strings/Triple_Quoted_Strings.py | obareau/python_travaux_pratiques | 2205f4c253e96e409b56f5c23d6e23387ab46524 | [
"MIT"
] | null | null | null | Strings/Triple_Quoted_Strings.py | obareau/python_travaux_pratiques | 2205f4c253e96e409b56f5c23d6e23387ab46524 | [
"MIT"
] | null | null | null | text = """first row
second row
third row"""
print(text) | 11.2 | 19 | 0.678571 | 9 | 56 | 4.222222 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.160714 | 56 | 5 | 20 | 11.2 | 0.808511 | 0 | 0 | 0 | 0 | 0 | 0.526316 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.25 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
9de05726b18a48aa8bb64f9718ce6b019dddac57 | 340 | py | Python | indra/sources/isi/__init__.py | zebulon2/indra | 7727ddcab52ad8012eb6592635bfa114e904bd48 | [
"BSD-2-Clause"
] | 136 | 2016-02-11T22:06:37.000Z | 2022-03-31T17:26:20.000Z | indra/sources/isi/__init__.py | zebulon2/indra | 7727ddcab52ad8012eb6592635bfa114e904bd48 | [
"BSD-2-Clause"
] | 748 | 2016-02-03T16:27:56.000Z | 2022-03-09T14:27:54.000Z | indra/sources/isi/__init__.py | zebulon2/indra | 7727ddcab52ad8012eb6592635bfa114e904bd48 | [
"BSD-2-Clause"
] | 56 | 2015-08-28T14:03:44.000Z | 2022-02-04T06:15:55.000Z | """
This module provides an input interface and processor to the ISI reading
system.
The reader is set up to run within a Docker container.
For the ISI reader to run, set the Docker memory and swap space to the maximum.
"""
from .api import process_text, process_nxml, process_preprocessed, \
process_output_folder, process_json_file
| 30.909091 | 79 | 0.785294 | 55 | 340 | 4.727273 | 0.690909 | 0.038462 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.167647 | 340 | 10 | 80 | 34 | 0.918728 | 0.635294 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
9de1b7ae0c9d7b9b421ab7c15947bb373739bf2a | 317 | py | Python | crawl_trulia/__init__.py | MacHu-GWU/crawl_trulia-project | 2e089442be5fa006f7d8ee00395446cbbfe711e9 | [
"MIT"
] | 1 | 2018-03-11T01:56:16.000Z | 2018-03-11T01:56:16.000Z | crawl_trulia/__init__.py | MacHu-GWU/crawl_trulia-project | 2e089442be5fa006f7d8ee00395446cbbfe711e9 | [
"MIT"
] | null | null | null | crawl_trulia/__init__.py | MacHu-GWU/crawl_trulia-project | 2e089442be5fa006f7d8ee00395446cbbfe711e9 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
__version__ = "0.0.4"
__author__ = "Sanhe Hu"
__license__ = "MIT"
__short_description__ = "Trulia Crawler Tool Set"
try:
from .urlencoder import urlencoder as trulia_urlencoder
from .htmlparser import htmlparser as trulia_htmlparser
except ImportError:
pass | 24.384615 | 59 | 0.735016 | 40 | 317 | 5.35 | 0.75 | 0.074766 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.015094 | 0.164038 | 317 | 13 | 60 | 24.384615 | 0.792453 | 0.132492 | 0 | 0 | 0 | 0 | 0.142336 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.111111 | 0.333333 | 0 | 0.333333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 2 |
9dfa5699a1409df51a017cce04c4f141c661f9f1 | 532 | py | Python | base/forms.py | vishnusayanth/django-app | 6f95f3140188d5cdeb260b66b2b8fdfffc8cf52b | [
"MIT"
] | null | null | null | base/forms.py | vishnusayanth/django-app | 6f95f3140188d5cdeb260b66b2b8fdfffc8cf52b | [
"MIT"
] | null | null | null | base/forms.py | vishnusayanth/django-app | 6f95f3140188d5cdeb260b66b2b8fdfffc8cf52b | [
"MIT"
] | null | null | null | from django import forms
from base.models import Developer
class RegistrationForm(forms.ModelForm):
password = forms.CharField(widget=forms.PasswordInput())
password2 = forms.CharField(widget=forms.PasswordInput())
class Meta:
model = Developer
fields = 'username', 'password', 'password2'
def __init__(self, *args, **kwargs):
super(RegistrationForm, self).__init__(*args, **kwargs)
for field in self.fields:
self.fields[field].widget.attrs['class'] = 'form-control'
| 29.555556 | 69 | 0.680451 | 57 | 532 | 6.210526 | 0.54386 | 0.079096 | 0.112994 | 0.141243 | 0.214689 | 0 | 0 | 0 | 0 | 0 | 0 | 0.004684 | 0.197368 | 532 | 17 | 70 | 31.294118 | 0.824356 | 0 | 0 | 0 | 0 | 0 | 0.078947 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.083333 | false | 0.25 | 0.166667 | 0 | 0.583333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 2 |
3b02763f40d9a8c733145bc1025dfe89a4d187c0 | 1,370 | py | Python | tests/register_test.py | ClementWalter/pandas-addons | 3965e19f374aa8f6d38f9a0047e71e8a27bacb1a | [
"MIT"
] | 2 | 2021-01-01T16:00:22.000Z | 2021-02-10T08:36:54.000Z | tests/register_test.py | ClementWalter/pandas-addons | 3965e19f374aa8f6d38f9a0047e71e8a27bacb1a | [
"MIT"
] | 4 | 2020-12-21T17:06:39.000Z | 2021-01-27T18:09:38.000Z | tests/register_test.py | ClementWalter/pandas-addons | 3965e19f374aa8f6d38f9a0047e71e8a27bacb1a | [
"MIT"
] | null | null | null | import itertools
from unittest.mock import patch
import pytest
from pandas_addons.register import DEFAULT_PANDAS_OBJECTS, accessors, register
class TestRegister:
def test_should_return_input_function(self):
def accessor():
pass
assert accessor == register()(accessor)
@patch.dict(accessors, {}, clear=True)
def test_should_use_default_value_when_no_args(self):
def accessor():
pass
register()(accessor)
assert accessors == {"accessor": {pdo: accessor for pdo in DEFAULT_PANDAS_OBJECTS}}
@patch.dict(accessors, {}, clear=True)
def test_should_register_when_register_is_called_on_decorated(self):
def accessor():
pass
register(accessor)
assert accessors == {"accessor": {pdo: accessor for pdo in DEFAULT_PANDAS_OBJECTS}}
@patch.dict(accessors, {}, clear=True)
@pytest.mark.parametrize(
"pandas_objects",
itertools.chain.from_iterable(
itertools.combinations(DEFAULT_PANDAS_OBJECTS, i + 1)
for i in range(len(DEFAULT_PANDAS_OBJECTS))
),
)
def test_should_register_given_pandas_object(self, pandas_objects):
def accessor():
pass
register(*pandas_objects)(accessor)
assert accessors == {"accessor": {pdo: accessor for pdo in pandas_objects}}
| 28.541667 | 91 | 0.667883 | 154 | 1,370 | 5.681818 | 0.331169 | 0.133714 | 0.114286 | 0.065143 | 0.401143 | 0.401143 | 0.401143 | 0.401143 | 0.340571 | 0.283429 | 0 | 0.000961 | 0.240146 | 1,370 | 47 | 92 | 29.148936 | 0.839577 | 0 | 0 | 0.382353 | 0 | 0 | 0.027737 | 0 | 0 | 0 | 0 | 0 | 0.117647 | 1 | 0.235294 | false | 0.117647 | 0.117647 | 0 | 0.382353 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
3b03e13769cfd86c85788b11953c3338fbd323d8 | 232 | py | Python | app/main/error.py | Waithera-m/partage | 293905385839b7c36847a46c91e142cb2df2a3ae | [
"Unlicense"
] | null | null | null | app/main/error.py | Waithera-m/partage | 293905385839b7c36847a46c91e142cb2df2a3ae | [
"Unlicense"
] | null | null | null | app/main/error.py | Waithera-m/partage | 293905385839b7c36847a46c91e142cb2df2a3ae | [
"Unlicense"
] | 1 | 2021-08-06T05:54:25.000Z | 2021-08-06T05:54:25.000Z | from flask import render_template
from . import main
@main.app_errorhandler(404)
def lost_not_found(error):
'''
Function renders 404 page if user enters and invalid url
'''
return render_template('error.html'),404 | 21.090909 | 60 | 0.728448 | 33 | 232 | 4.969697 | 0.757576 | 0.170732 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.047619 | 0.185345 | 232 | 11 | 61 | 21.090909 | 0.820106 | 0.241379 | 0 | 0 | 0 | 0 | 0.062112 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.4 | 0 | 0.8 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
d1786dfa704fa4cac3a7a01c36b29219d15878f2 | 15,417 | py | Python | src/polyswarm/formatters/text.py | polyswarm/polyswarm-cli | f783b77180a7436bc993171b46691a223f175260 | [
"MIT"
] | 2 | 2021-04-14T01:42:48.000Z | 2022-03-12T16:20:23.000Z | src/polyswarm/formatters/text.py | polyswarm/polyswarm-cli | f783b77180a7436bc993171b46691a223f175260 | [
"MIT"
] | 11 | 2019-10-22T23:23:27.000Z | 2021-06-07T21:40:10.000Z | src/polyswarm/formatters/text.py | polyswarm/polyswarm-cli | f783b77180a7436bc993171b46691a223f175260 | [
"MIT"
] | 1 | 2021-04-26T10:58:01.000Z | 2021-04-26T10:58:01.000Z | from __future__ import absolute_import, unicode_literals
import sys
import functools
import json
import click
from polyswarm.formatters import base
def is_grouped(fn):
@functools.wraps(fn)
def wrapper(self, text):
return self._depth*'\t'+fn(self, text)
return wrapper
class TextOutput(base.BaseOutput):
name = 'text'
def __init__(self, color=True, output=sys.stdout, **kwargs):
super(TextOutput, self).__init__(output)
self.color = color
self._depth = 0
self.color = color
def _get_score_format(self, score):
if score < 0.15:
return self._white
elif score < 0.4:
return self._yellow
else:
return self._red
def _output(self, output, write):
if write:
click.echo('\n'.join(output) + '\n', file=self.out)
else:
return output
def artifact(self, artifact, write=True):
output = []
output.append(self._blue('SHA256: {hash}'.format(hash=artifact.sha256)))
output.append(self._white('SHA1: {hash}'.format(hash=artifact.sha1)))
output.append(self._white('MD5: {hash}'.format(hash=artifact.md5)))
output.append(self._white('File type: mimetype: {mimetype}, extended_info: {extended_type}'.
format(mimetype=artifact.mimetype, extended_type=artifact.extended_type)))
h = artifact.metadata.hash
if 'ssdeep' in h:
output.append(self._white('SSDEEP: {}'.format(h['ssdeep'])))
if 'tlsh' in h:
output.append(self._white('TLSH: {}'.format(h['tlsh'])))
if 'authentihash' in h:
output.append(self._white('Authentihash: {}'.format(h['authentihash'])))
p = artifact.metadata.pefile
if 'imphash' in p:
output.append(self._white('Imphash: {}'.format(p['imphash'])))
output.append(self._white('First seen: {}'.format(artifact.first_seen)))
output.append(self._white('Last scanned: {}'.format(artifact.last_scanned)))
# Deprecated
output.append(self._white('Last seen: {}'.format(artifact.last_scanned)))
return self._output(output, write)
def artifact_instance(self, instance, write=True, timeout=False):
output = []
output.append(self._white('============================= Artifact Instance ============================='))
output.append(self._white('Scan permalink: {}'.format(instance.permalink)))
if instance.community == 'stream':
output.append(self._white('Detections: This artifact has not been scanned. You can trigger a scan now.'))
elif len(instance.valid_assertions) == 0 and instance.window_closed and not instance.failed:
output.append(self._white('Detections: No engines responded to this scan. You can trigger a rescan now.'))
elif len(instance.valid_assertions) > 0 and instance.window_closed and not instance.failed:
malicious = 'Detections: {}/{} engines reported malicious'\
.format(len(instance.malicious_assertions), len(instance.valid_assertions))
if len(instance.malicious_assertions) > 0:
output.append(self._red(malicious))
else:
output.append(self._white(malicious))
elif not instance.window_closed and not instance.failed:
output.append(self._white('Detections: This scan has not finished running yet.'))
else:
output.append(self._white('Detections: This scan has failed. Please try again.'))
self._open_group()
for assertion in instance.assertions:
if assertion.verdict is False:
output.append('%s: %s' % (self._green(assertion.engine_name), 'Clean'))
elif assertion.verdict is None or assertion.mask is False:
output.append('%s: %s' % (self._blue(assertion.engine_name), 'Engine chose not respond to this bounty.'))
else:
value = 'Malicious'
if assertion.metadata:
value += ', metadata: %s' % json.dumps(assertion.metadata, sort_keys=True)
output.append('%s: %s' % (self._red(assertion.engine_name), value))
self._close_group()
output.append(self._blue('Scan id: {}'.format(instance.id)))
output.extend(self.artifact(instance, write=False))
if instance.failed:
output.append(self._red('Status: Failed'))
elif instance.window_closed:
output.append(self._white('Status: Assertion window closed'))
elif instance.community == 'stream':
output.append(self._white('Status: This artifact has not been scanned. You can trigger a scan now.'))
elif timeout:
output.append(self._yellow('Status: Lookup timed-out, please retry'))
else:
output.append(self._white('Status: Running'))
if instance.type == 'URL':
output.append(self._white('URL: {}'.format(instance.filename)))
else:
output.append(self._white('Filename: {}'.format(instance.filename)))
output.append(self._white('Community: {}'.format(instance.community)))
output.append(self._white('Country: {}'.format(instance.country)))
if instance.polyscore is not None:
formatter = self._get_score_format(instance.polyscore)
output.append(formatter('PolyScore: {:.20f}'.format(instance.polyscore)))
return self._output(output, write)
def hunt(self, result, write=True):
output = []
output.append(self._blue('Hunt Id: {}'.format(result.id)))
if result.active is not None:
output.append(self._white('Active: {}'.format(result.active)))
if result.ruleset_name is not None:
output.append(self._white('Ruleset Name: {}'.format(result.ruleset_name)))
output.append(self._white('Created at: {}'.format(result.created)))
return self._output(output, write)
def hunt_deletion(self, result, write=True):
output = []
output.append(self._yellow('Successfully deleted Hunt:'))
output.extend(self.hunt(result, write=False))
return self._output(output, write)
def hunt_result(self, result, write=True):
output = []
output.append(self._white('Match on rule {name}'.format(name=result.rule_name) +
(', tags: {result_tags}'.format(
result_tags=result.tags) if result.tags != '' else '')))
output.extend(self.artifact_instance(result.artifact, write=False))
return self._output(output, write)
def ruleset(self, result, write=True, contents=False):
output = []
output.append(self._blue('Ruleset Id: {}'.format(result.id)))
output.append(self._white('Name: {}'.format(result.name)))
output.append(self._white('Description: {}'.format(result.description)))
output.append(self._white('Created at: {}'.format(result.created)))
output.append(self._white('Modified at: {}'.format(result.modified)))
if contents:
output.append(self._white('Contents:\n{}'.format(result.yara)))
return self._output(output, write)
def tag_link(self, result, write=True):
output = []
output.append(self._blue('SHA256: {}'.format(result.sha256)))
output.append(self._white('First seen: {}'.format(result.first_seen)))
output.append(self._white('Tags: {}'.format(result.tags)))
output.append(self._white('Families: {}'.format(result.families)))
output.append(self._white('Emerging: {}'.format(result.emerging)))
return self._output(output, write)
def family(self, result, write=True):
output = []
output.append(self._blue('Family: {}'.format(result.name)))
output.append(self._white('Emerging: {}'.format(result.emerging)))
return self._output(output, write)
def tag(self, result, write=True):
output = []
output.append(self._blue('Tag: {}'.format(result.name)))
return self._output(output, write)
def local_artifact(self, artifact, write=True):
output = []
output.append(self._white('Successfully downloaded artifact {} to {}'
.format(artifact.artifact_name, artifact.name)))
return self._output(output, write)
def _dfs_mapping_render(self, output, path, tree, depth=0):
tree_string = (' | ' * (depth - 1)) + ' +-' if depth > 0 else ''
current_path = '.'.join(path)
if not tree:
output.append(self._white(tree_string + current_path))
else:
if path:
output.append(self._white(tree_string + current_path))
for k, v in tree.items():
self._dfs_mapping_render(output, path + [k], v, depth=depth + 1)
def mapping(self, mapping, write=True):
output = []
output.append(self._white('============================= Mapping ============================='))
self._dfs_mapping_render(output, [], mapping.json)
return self._output(output, write)
def metadata(self, instance, write=True):
output = []
output.append(self._white('============================= Metadata ============================='))
output.append(self._blue('Artifact id: {}'.format(instance.id)))
output.append(self._white('Created: {}'.format(instance.created)))
if instance.sha256:
output.append(self._white('SHA256: {}'.format(instance.sha256)))
if instance.sha1:
output.append(self._white('SHA1: {}'.format(instance.sha1)))
if instance.md5:
output.append(self._white('MD5: {}'.format(instance.md5)))
if instance.ssdeep:
output.append(self._white('SSDEEP: {}'.format(instance.ssdeep)))
if instance.tlsh:
output.append(self._white('TLSH: {}'.format(instance.tlsh)))
if instance.first_seen:
output.append(self._white('First seen: {}'.format(instance.first_seen)))
if instance.last_scanned:
output.append(self._white('Last scanned: {}'.format(instance.last_scanned)))
# Deprecated
output.append(self._white('Last seen: {}'.format(instance.last_scanned)))
if instance.mimetype:
output.append(self._white('Mimetype: {}'.format(instance.mimetype)))
if instance.extended_mimetype:
output.append(self._white('Extended mimetype: {}'.format(instance.extended_mimetype)))
if instance.malicious:
output.append(self._white('Malicious: {}'.format(instance.malicious)))
if instance.benign:
output.append(self._white('Benign: {}'.format(instance.benign)))
if instance.total_detections:
output.append(self._white('Total detections: {}'.format(instance.total_detections)))
if instance.domains:
output.append(self._white('Domains:'))
self._open_group()
output.append(self._white('{}'.format(', '.join(instance.domains))))
self._close_group()
if instance.ipv4:
output.append(self._white('Ipv4:'))
self._open_group()
output.append(self._white('{}'.format(', '.join(instance.ipv4))))
self._close_group()
if instance.ipv6:
output.append(self._white('Ipv6:'))
self._open_group()
output.append(self._white('{}'.format(', '.join(instance.ipv6))))
self._close_group()
if instance.urls:
output.append(self._white('Urls:'))
self._open_group()
output.append(self._white('{}'.format(', '.join(instance.urls))))
self._close_group()
if instance.filenames:
output.append(self._white('Filenames:'))
self._open_group()
output.append(self._white('{}'.format(', '.join(instance.filenames))))
self._close_group()
return self._output(output, write)
def assertions(self, instance, write=True):
output = []
output.append(self._white('============================= Assertions Job ============================='))
output.append(self._blue('Assertions Job id: {}'.format(instance.id)))
output.append(self._white('Engine id: {}'.format(instance.engine_id)))
output.append(self._white('Created at: {}'.format(instance.created)))
output.append(self._white('Start date: {}'.format(instance.date_start)))
output.append(self._white('End date: {}'.format(instance.date_end)))
if instance.storage_path is not None:
output.append(self._white('Download: {}'.format(instance.storage_path)))
output.append(self._white('True Positive: {}'.format(instance.true_positive)))
output.append(self._white('True Negative: {}'.format(instance.true_negative)))
output.append(self._white('False Positive: {}'.format(instance.false_positive)))
output.append(self._white('False Negative: {}'.format(instance.false_negative)))
output.append(self._white('Suspicious: {}'.format(instance.suspicious)))
output.append(self._white('Unknown: {}'.format(instance.unknown)))
output.append(self._white('Total: {}'.format(instance.total)))
return self._output(output, write)
def votes(self, instance, write=True):
output = []
output.append(self._white('============================= Votes Job ============================='))
output.append(self._blue('Votes Job id: {}'.format(instance.id)))
output.append(self._white('Engine id: {}'.format(instance.engine_id)))
output.append(self._white('Created at: {}'.format(instance.created)))
output.append(self._white('Start date: {}'.format(instance.date_start)))
output.append(self._white('End date: {}'.format(instance.date_end)))
if instance.storage_path is not None:
output.append(self._white('Download: {}'.format(instance.storage_path)))
output.append(self._white('True Positive: {}'.format(instance.true_positive)))
output.append(self._white('True Negative: {}'.format(instance.true_negative)))
output.append(self._white('False Positive: {}'.format(instance.false_positive)))
output.append(self._white('False Negative: {}'.format(instance.false_negative)))
output.append(self._white('Suspicious: {}'.format(instance.suspicious)))
output.append(self._white('Unknown: {}'.format(instance.unknown)))
output.append(self._white('Total: {}'.format(instance.total)))
return self._output(output, write)
@is_grouped
def _white(self, text):
return click.style(text, fg='white')
@is_grouped
def _yellow(self, text):
return click.style(text, fg='yellow')
@is_grouped
def _red(self, text):
return click.style(text, fg='red')
@is_grouped
def _blue(self, text):
return click.style(text, fg='blue')
@is_grouped
def _green(self, text):
return click.style(text, fg='green')
def _open_group(self):
self._depth += 1
def _close_group(self):
self._depth -= 1
| 46.020896 | 121 | 0.607252 | 1,721 | 15,417 | 5.285299 | 0.117374 | 0.146438 | 0.188215 | 0.21471 | 0.574758 | 0.476913 | 0.442172 | 0.353452 | 0.314534 | 0.256926 | 0 | 0.004543 | 0.228968 | 15,417 | 334 | 122 | 46.158683 | 0.760663 | 0.001362 | 0 | 0.30742 | 0 | 0 | 0.145326 | 0.01884 | 0 | 0 | 0 | 0 | 0.056537 | 1 | 0.095406 | false | 0 | 0.021201 | 0.021201 | 0.212014 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
d17f405e79a4111ff94ffedb4d4b111b78f9db83 | 11,014 | py | Python | lupa/tests/fixtures/osmapi.py | MinisterioPublicoRJ/api-cadg | a8998c4c234a65192f1dca8ea9a17a1d4a496556 | [
"MIT"
] | 6 | 2020-02-11T18:45:58.000Z | 2020-05-26T12:37:28.000Z | lupa/tests/fixtures/osmapi.py | MinisterioPublicoRJ/api-cadg | a8998c4c234a65192f1dca8ea9a17a1d4a496556 | [
"MIT"
] | 120 | 2019-07-01T14:45:32.000Z | 2022-01-25T19:10:16.000Z | lupa/tests/fixtures/osmapi.py | MinisterioPublicoRJ/apimpmapas | 196ad25a4922448b8ae7a66012a2843c7b7194ad | [
"MIT"
] | null | null | null | default_response = {
"features":[
{
"geometry":{
"coordinates":[
-43.21986610772104,
-22.8049732
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":5519132,
"osm_type":"R",
"extent":[
-43.265963,
-22.7757114,
-43.1557502,
-22.8339199
],
"country":"Brazil",
"osm_key":"place",
"city":"Rio de Janeiro",
"osm_value":"island",
"name":"Governador Island",
"state":"Rio de Janeiro"
}
},
{
"geometry":{
"coordinates":[
-62.92761666754802,
-0.9610612000000001
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":209813884,
"osm_type":"W",
"extent":[
-62.9292942,
-0.958921,
-62.9257127,
-0.9631287
],
"country":"Brazil",
"osm_key":"place",
"city":"Barcelos",
"osm_value":"islet",
"postcode":"69700000",
"name":"Ilha do Governador",
"state":"Amazonas"
}
},
{
"geometry":{
"coordinates":[
-42.10028206205817,
-19.0068657
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":286169517,
"osm_type":"W",
"extent":[
-42.1071179,
-19.001967,
-42.096832,
-19.0114867
],
"country":"Brazil",
"osm_key":"place",
"city":"Alpercata",
"osm_value":"island",
"name":"Ilha do Arroz",
"state":"Minas Gerais"
}
},
{
"geometry":{
"coordinates":[
-48.557870106181525,
-27.406375599999997
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":10773467,
"osm_type":"W",
"extent":[
-48.5588059,
-27.4058472,
-48.5570169,
-27.406895
],
"country":"Brazil",
"osm_key":"place",
"city":"Governador Celso Ramos",
"osm_value":"island",
"postcode":"88190-000",
"name":"Ilha do Maximiliano",
"state":"Santa Catarina"
}
},
{
"geometry":{
"coordinates":[
-41.94406791407067,
-18.86703455
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":250255623,
"osm_type":"W",
"extent":[
-41.9505911,
-18.8595339,
-41.9381017,
-18.8759379
],
"country":"Brazil",
"osm_key":"place",
"city":"Governador Valadares",
"osm_value":"island",
"name":"Ilha dos Araújos",
"state":"Minas Gerais"
}
},
{
"geometry":{
"coordinates":[
-41.9427495,
-18.865785
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":5548936,
"osm_type":"R",
"extent":[
-41.9522571,
-18.8591612,
-41.936979,
-18.8795156
],
"country":"Brazil",
"osm_key":"place",
"city":"Governador Valadares",
"osm_value":"suburb",
"name":"Ilha dos Araújos",
"state":"Minas Gerais"
}
},
{
"geometry":{
"coordinates":[
-42.089677830705526,
-18.98877025
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":286169516,
"osm_type":"W",
"extent":[
-42.0910104,
-18.9866293,
-42.088439,
-18.9910726
],
"country":"Brazil",
"osm_key":"place",
"city":"Alpercata",
"osm_value":"islet",
"name":"Ilha Funda",
"state":"Minas Gerais"
}
},
{
"geometry":{
"coordinates":[
-51.0641413,
-23.2929031
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":106941503,
"osm_type":"W",
"extent":[
-51.0641413,
-23.2924122,
-51.0623139,
-23.2929031
],
"country":"Brazil",
"osm_key":"highway",
"city":"Ibiporã",
"osm_value":"residential",
"postcode":"86200-981",
"name":"Rua Ilha do Governador",
"state":"Paraná"
}
},
{
"geometry":{
"coordinates":[
-46.9692001,
-22.8601013
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":142677919,
"osm_type":"W",
"extent":[
-46.969598,
-22.8600213,
-46.9689513,
-22.860149
],
"country":"Brazil",
"osm_key":"highway",
"city":"Campinas",
"osm_value":"residential",
"postcode":"13104-164",
"name":"Rua Ilha do Governador",
"state":"São Paulo"
}
},
{
"geometry":{
"coordinates":[
-40.8756976,
-14.8355181
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":223347577,
"osm_type":"W",
"extent":[
-40.8757429,
-14.8355181,
-40.8756976,
-14.8378329
],
"country":"Brazil",
"osm_key":"highway",
"city":"Vitória da Conquista",
"osm_value":"residential",
"postcode":"45085130",
"name":"Rua Ilha do Governador",
"state":"Bahia"
}
},
{
"geometry":{
"coordinates":[
-44.0756304,
-22.4904658
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":95304428,
"osm_type":"W",
"extent":[
-44.0758156,
-22.4902065,
-44.0755289,
-22.4909837
],
"country":"Brazil",
"osm_key":"highway",
"city":"Volta Redonda",
"osm_value":"residential",
"postcode":"27213-145",
"name":"Rua Ilha do Governador",
"state":"Rio de Janeiro"
}
},
{
"geometry":{
"coordinates":[
-46.8977948,
-23.5097169
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":173208053,
"osm_type":"W",
"extent":[
-46.8983151,
-23.5097058,
-46.8973236,
-23.5099122
],
"country":"Brazil",
"osm_key":"highway",
"city":"Barueri",
"osm_value":"residential",
"postcode":"06420-340",
"name":"Rua Ilha do Governador",
"state":"São Paulo"
}
},
{
"geometry":{
"coordinates":[
-46.8040744,
-23.6570636
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":439820004,
"osm_type":"W",
"extent":[
-46.8043329,
-23.6566816,
-46.8038392,
-23.6575009
],
"country":"Brazil",
"osm_key":"highway",
"city":"Embu das Artes",
"osm_value":"residential",
"postcode":"06814-160",
"name":"Rua Ilha do Governador",
"state":"São Paulo"
}
},
{
"geometry":{
"coordinates":[
-44.69132688556381,
-23.216495600000002
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":10936780,
"osm_type":"W",
"extent":[
-44.6933283,
-23.2148027,
-44.6896087,
-23.2180194
],
"country":"Brazil",
"osm_key":"boundary",
"city":"Paraty",
"street":"Rodovia Governador Mário Covas",
"osm_value":"protected_area",
"postcode":"23970-000",
"name":"Ilha da Bexiga",
"state":"Rio de Janeiro"
}
},
{
"geometry":{
"coordinates":[
-47.0308807,
-23.6626934
],
"type":"Point"
},
"type":"Feature",
"properties":{
"osm_id":225637207,
"osm_type":"W",
"extent":[
-47.0313205,
-23.6616765,
-47.0305328,
-23.6634982
],
"country":"Brazil",
"osm_key":"highway",
"city":"Cotia",
"osm_value":"residential",
"postcode":"06726-466",
"name":"Rua União da Ilha do Governador",
"state":"São Paulo"
}
}
],
"type":"FeatureCollection"
}
twoinoneout = {
"features":[
{
"geometry":{
"coordinates":[
-43.21986610772104,
-22.8049732
],
"type":"Point"
},
},
{
"geometry":{
"coordinates":[
-44.69132688556381,
-23.216495600000002
],
"type":"Point"
},
},
{
"geometry":{
"coordinates":[
-47.0308807,
-23.6626934
],
"type":"Point"
},
}
]
} | 25.088838 | 54 | 0.352914 | 728 | 11,014 | 5.254121 | 0.292582 | 0.089412 | 0.05098 | 0.078431 | 0.52 | 0.46719 | 0.346144 | 0.206013 | 0.155033 | 0.071895 | 0 | 0.209736 | 0.498275 | 11,014 | 439 | 55 | 25.088838 | 0.482447 | 0 | 0 | 0.533181 | 0 | 0 | 0.259192 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
d185a75ca724404968ce70d2fa05c5da741b28f1 | 405 | py | Python | FastDetector/MobiNetV3_test.py | Yoshi-E/Object-Localizer-Project | 0f55009581d207cce6345a3e2c44a8a91c9bb3c4 | [
"MIT"
] | null | null | null | FastDetector/MobiNetV3_test.py | Yoshi-E/Object-Localizer-Project | 0f55009581d207cce6345a3e2c44a8a91c9bb3c4 | [
"MIT"
] | null | null | null | FastDetector/MobiNetV3_test.py | Yoshi-E/Object-Localizer-Project | 0f55009581d207cce6345a3e2c44a8a91c9bb3c4 | [
"MIT"
] | null | null | null | from models import MobiNetV3
from models.Core import Config
import os
from glob import glob
config = Config()
model = MobiNetV3.FastModel(config)
config.WEIGHTS_FILE = "weights/MobiNetV3/weight-0.73.h5"
if __name__ == "__main__":
#model.test_image("FastDetector/datasets/10_rosbag/images/1565608339175915704.jpg")
model.test_images(glob("FastDetector/datasets/10_rosbag/images/*.jpg"), skip=100) | 33.75 | 87 | 0.785185 | 55 | 405 | 5.545455 | 0.545455 | 0.065574 | 0.144262 | 0.183607 | 0.222951 | 0 | 0 | 0 | 0 | 0 | 0 | 0.090164 | 0.096296 | 405 | 12 | 88 | 33.75 | 0.743169 | 0.202469 | 0 | 0 | 0 | 0 | 0.260062 | 0.235294 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.444444 | 0 | 0.444444 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
d1b73ff270948dd25b6790bf70638bfb1737da03 | 1,391 | py | Python | recipes/Python/577810_Named_Values/recipe-577810.py | tdiprima/code | 61a74f5f93da087d27c70b2efe779ac6bd2a3b4f | [
"MIT"
] | 2,023 | 2017-07-29T09:34:46.000Z | 2022-03-24T08:00:45.000Z | recipes/Python/577810_Named_Values/recipe-577810.py | unhacker/code | 73b09edc1b9850c557a79296655f140ce5e853db | [
"MIT"
] | 32 | 2017-09-02T17:20:08.000Z | 2022-02-11T17:49:37.000Z | recipes/Python/577810_Named_Values/recipe-577810.py | unhacker/code | 73b09edc1b9850c557a79296655f140ce5e853db | [
"MIT"
] | 780 | 2017-07-28T19:23:28.000Z | 2022-03-25T20:39:41.000Z | class NamedValue:
# defining __slots__ in a mixin doesn't play nicely with builtin types
# so a low overhead approach would have to use collections.namedtuple
# style templated code generation
def __new__(cls, *args, **kwds):
name, *args = args
self = super().__new__(cls, *args, **kwds)
self._name = name
return self
def __init__(self, *args, **kwds):
name, *args = args
super().__init__(*args, **kwds)
@property
def __name__(self):
return self._name
def __repr__(self):
# repr() is updated to include the name and type info
return "{}({!r}, {})".format(type(self).__name__,
self.__name__,
super().__repr__())
def __str__(self):
# str() is unchanged, even if it relies on the repr() fallback
base = super()
base_str = base.__str__
if base_str.__objclass__ is object:
return base.__repr__()
return base_str()
# Example usage
>>> class NamedFloat(NamedValue, float):
... pass
...
>>> import math
>>> tau = NamedFloat('tau', 2*math.pi)
>>> tau
NamedFloat(tau, 6.283185307179586)
>>> print(tau)
6.283185307179586
>>> class NamedList(NamedValue, list):
... pass
...
>>> data = NamedList('data', [])
>>> data
NamedList('data', [])
>>> print(data)
[]
| 28.979167 | 74 | 0.576564 | 159 | 1,391 | 4.660377 | 0.477987 | 0.043185 | 0.026991 | 0.037787 | 0.053981 | 0 | 0 | 0 | 0 | 0 | 0 | 0.033266 | 0.286844 | 1,391 | 47 | 75 | 29.595745 | 0.71371 | 0.212078 | 0 | 0.153846 | 0 | 0 | 0.02112 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.051282 | 0.025641 | null | null | 0.051282 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
d1c06633080b95b9f09cc4bc498d48dcbca6fbb3 | 17,362 | py | Python | tests.py | joemeister/httpagentparser | fcb9eb9c015f05554511890787432d51eca81397 | [
"MIT"
] | null | null | null | tests.py | joemeister/httpagentparser | fcb9eb9c015f05554511890787432d51eca81397 | [
"MIT"
] | null | null | null | tests.py | joemeister/httpagentparser | fcb9eb9c015f05554511890787432d51eca81397 | [
"MIT"
] | null | null | null | import unittest
import time
import httpagentparser
detect = httpagentparser.detect
simple_detect = httpagentparser.simple_detect
data = (
# tuple of tuples
# tuple (agent-string, expected result of simple_detect, expected result of detect)
("Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3861.0 Safari/537.36 Edg/77.0.230.2",
('Windows 10', 'ChromiumEdge 77.0.230.2'),
{'bot': False, 'os': {'version': '10', 'name': 'Windows'}, 'browser': {'version': '77.0.230.2', 'name': 'ChromiumEdge'}},),
("Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10.5; en-GB; rv:1.9.0.10) Gecko/2009042315 Firefox/3.0.10",
('MacOS Macintosh X 10.5', 'Firefox 3.0.10'),
{'bot': False, 'flavor': {'version': 'X 10.5', 'name': 'MacOS'}, 'os': {'name': 'Macintosh'}, 'browser': {'version': '3.0.10', 'name': 'Firefox'}},),
("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_6_6) AppleWebKit/534.24 (KHTML, like Gecko) Chrome/11.0.696.3 Safari/534.24,gzip(gfe)",
('MacOS Macintosh X 10.6.6', 'Chrome 11.0.696.3'),
{'bot': False, 'flavor': {'version': 'X 10.6.6', 'name': 'MacOS'}, 'os': {'name': 'Macintosh'}, 'browser': {'version': '11.0.696.3', 'name': 'Chrome'}},),
("Mozilla/5.0 (X11; U; Linux i686; en-US; rv:1.9.2) Gecko/20100308 Ubuntu/10.04 (lucid) Firefox/3.6 GTB7.1",
('Ubuntu Linux 10.04', 'Firefox 3.6'),
{'bot': False, 'dist': {'version': '10.04', 'name': 'Ubuntu'}, 'os': {'name': 'Linux'}, 'browser': {'version': '3.6', 'name': 'Firefox'}},),
("Mozilla/5.0 (Linux; U; Android 2.2.1; fr-ch; A43 Build/FROYO) AppleWebKit/533.1 (KHTML, like Gecko) Version/4.0 Mobile Safari/533.1",
('Android Linux 2.2.1', 'AndroidBrowser'),
{'bot': False, 'dist': {'version': '2.2.1', 'name': 'Android'}, 'os': {'name': 'Linux'}, 'browser': {'name': 'AndroidBrowser'}},),
("Mozilla/5.0 (iPhone; U; CPU like Mac OS X; en) AppleWebKit/420+ (KHTML, like Gecko) Version/3.0 Mobile/1A543a Safari/419.3",
('iPhone iOS', 'Safari 3.0'),
{'bot': False, 'os': {'name': 'iOS'}, 'dist': {'name': 'iPhone'}, 'browser': {'version': '3.0', 'name': 'Safari'}},),
("Mozilla/5.0 (X11; CrOS i686 0.0.0) AppleWebKit/534.24 (KHTML, like Gecko) Chrome/11.0.696.27 Safari/534.24,gzip(gfe)",
('ChromeOS 0.0.0', 'Chrome 11.0.696.27'),
{'bot': False, 'os': {'name': 'ChromeOS', 'version': '0.0.0'}, 'browser': {'name': 'Chrome', 'version': '11.0.696.27'}},),
("Mozilla/4.0 (compatible; MSIE 6.0; MSIE 5.5; Windows NT 5.1) Opera 7.02 [en]",
('Windows XP', 'Opera 7.02'),
{'bot': False, 'os': {'name': 'Windows', 'version': 'XP'}, 'browser': {'name': 'Opera', 'version': '7.02'}},),
("Opera/9.64(Windows NT 5.1; U; en) Presto/2.1.1",
('Windows XP', 'Opera 9.64'),
{'bot': False, 'os': {'name': 'Windows', 'version': 'XP'}, 'browser': {'name': 'Opera', 'version': '9.64'}},),
("Mozilla/5.0 (compatible; MSIE 10.0; Windows NT 6.1; WOW64; Trident/6.0)",
('Windows 7', 'Microsoft Internet Explorer 10.0'),
{'bot': False, 'os': {'version': '7', 'name': 'Windows'}, 'browser': {'version': '10.0', 'name': 'Microsoft Internet Explorer'}},),
("Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0; yie8)",
('Windows 7', 'Microsoft Internet Explorer 9.0'),
{'bot': False, 'os': {'version': '7', 'name': 'Windows'}, 'browser': {'version': '9.0', 'name': 'Microsoft Internet Explorer'}},),
("Mozilla/5.0 (MSIE 7.0; Macintosh; U; SunOS; X11; gu; SV1; InfoPath.2; .NET CLR 3.0.04506.30; .NET CLR 3.0.04506.648",
('Macintosh', 'Microsoft Internet Explorer 7.0'),
{'bot': False, 'os': {'name': 'Macintosh'}, 'browser': {'version': '7.0', 'name': 'Microsoft Internet Explorer'}}),
("Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; Trident/4.0; GTB6.5; QQDownload 534; Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1) ; SLCC2; .NET CLR 2.0.50727; Media Center PC 6.0; .NET CLR 3.5.30729; .NET CLR 3.0.30729)",
('Windows XP', 'Microsoft Internet Explorer 8.0'),
{'bot': False, 'os': {'version': 'XP', 'name': 'Windows'}, 'browser': {'version': '8.0', 'name': 'Microsoft Internet Explorer'}}),
('Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0; Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1) ; SLCC1; .NET CLR 2.0.50727; InfoPath.1; .NET CLR 3.5.30729; .NET CLR 3.0.30618; .NET4.0C)',
('Windows XP', 'Microsoft Internet Explorer 8.0'),
{'bot': False, 'os': {'version': 'XP', 'name': 'Windows'}, 'browser': {'version': '8.0', 'name': 'Microsoft Internet Explorer'}},),
("Opera/9.80 (X11; Linux i686; U; en) Presto/2.9.168 Version/11.50",
("Linux", "Opera 11.50"),
{'bot': False, "os": {"name": "Linux"}, "browser": {"name": "Opera", "version": "11.50"}},),
("Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.7.5) Gecko/20060127 Netscape/8.1",
("Windows XP", "Netscape 8.1"),
{'bot': False, 'os': {'name': 'Windows', 'version': 'XP'}, 'browser': {'name': 'Netscape', 'version': '8.1'}},),
("Mozilla/5.0 (hp-tablet; Linux; hpwOS/3.0.2; U; en-US) AppleWebKit/534.6 (KHTML, like Gecko) wOSBrowser/234.40.1 Safari/534.6 TouchPad/1.0",
("WebOS Linux 3.0.2", "WOSBrowser"),
{'bot': False, 'dist': {'name': 'WebOS', 'version': '3.0.2'}, 'os' : {'name' : 'Linux'}, 'browser': {'name': 'WOSBrowser'}},),
("Mozilla/5.0 (iPad; CPU OS 5_0_1 like Mac OS X) AppleWebKit/534.46 (KHTML, like Gecko) Version/5.1 Mobile/9A405 Safari/7534.48.3",
('IPad iOS 5.0.1', 'Safari 5.1'),
{'bot': False, 'os': {'name': 'iOS'}, 'dist': {'version': '5.0.1', 'name': 'IPad'}, 'browser': {'version': '5.1', 'name': 'Safari'}},),
("AppleCoreMedia/1.0.0.10B329 (iPad; U; CPU OS 6_1_3 like Mac OS X; en_us)",
('IPad iOS 6.1.3', 'Unknown Browser'),
{'bot': False, 'dist': {'name': 'IPad', 'version': '6.1.3'}, 'os': {'name': 'iOS'}},),
("Mozilla/5.0 (iPad; CPU OS 7_1 like Mac OS X) AppleWebKit/537.51.2 (KHTML, like Gecko) Version/7.0 Mobile/11D167 Safari/9537.53",
('IPad iOS 7.1', 'Safari 7.0'),
{'bot': False, 'browser': {'name': 'Safari', 'version': '7.0'}, 'dist': {'name': 'IPad', 'version': '7.1'}, 'os': {'name': 'iOS'}}),
("Mozilla/5.0 (Linux; U; Android 3.2.1; en-gb; Transformer TF101 Build/HTK75) AppleWebKit/534.13 (KHTML, like Gecko) Version/4.0 Safari/534.13",
('Android Linux 3.2.1', 'AndroidBrowser'),
{'bot': False, 'dist': {'version': '3.2.1', 'name': 'Android'}, 'os': {'name': 'Linux'}, 'browser': {'name': 'AndroidBrowser'}},),
("Mozilla/5.0 (BlackBerry; U; BlackBerry 9700; en-US) AppleWebKit/534.8+ (KHTML, like Gecko) Version/6.0.0.448 Mobile Safari/534.8+",
('Blackberry', 'Safari 6.0.0.448'),
{'bot': False, 'os': {'name': 'Blackberry'}, 'browser': {'version': '6.0.0.448', 'name': 'Safari'}},),
("Mozilla/5.0 (PlayBook; U; RIM Tablet OS 1.0.0; en-US) AppleWebKit/534.11+ (KHTML, like Gecko) Version/7.1.0.7 Safari/534.11+",
('BlackberryPlaybook', 'Safari 7.1.0.7'),
{'bot': False, 'dist': {'name': 'BlackberryPlaybook'}, 'browser': {'version': '7.1.0.7', 'name': 'Safari'}},),
("Opera/9.80 (Android 2.3.5; Linux; Opera Mobi/build-1203300859; U; en) Presto/2.10.254 Version/12.00",
('Android Linux 2.3.5', 'Opera Mobile 12.00'),
{'bot': False, 'dist': {'version': '2.3.5', 'name': 'Android'}, 'os': {'name': 'Linux'}, 'browser': {'version': '12.00', 'name': 'Opera Mobile'}},),
("Mozilla/5.0 (Linux; U; Android 2.3.5; en-in; HTC_DesireS_S510e Build/GRJ90) AppleWebKit/533.1 (KHTML, like Gecko) Version/4.0 Mobile Safari/533.1",
('Android Linux 2.3.5', 'AndroidBrowser'),
{'bot': False, 'dist': {'version': '2.3.5', 'name': 'Android'}, 'os': {'name': 'Linux'}, 'browser': {'name': 'AndroidBrowser'}},),
("Mozilla/5.0 (iPhone; U; CPU iPhone OS 5_1_1 like Mac OS X; es-es) AppleWebKit/534.46.0 (KHTML, like Gecko) CriOS/19.0.1084.60 Mobile/9B206 Safari/7534.48.3",
('iPhone iOS 5.1.1', 'ChromeiOS 19.0.1084.60'),
{'bot': False, 'os': {'name': 'iOS'}, 'dist': {'version': '5.1.1', 'name': 'iPhone'}, 'browser': {'version': '19.0.1084.60', 'name': 'ChromeiOS'}}),
("Mozilla/5.0 (X11; Linux x86_64; rv:7.0.1) Gecko/20111011 Firefox/7.0.1 SeaMonkey/2.4.1",
("Linux", "SeaMonkey 2.4.1"),
{'bot': False, "os" : {"name": "Linux"}, "browser": {"name": "SeaMonkey", "version": "2.4.1"}}),
("Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:16.0) Gecko/20100101 Firefox/16.0",
("Ubuntu Linux", "Firefox 16.0"),
{'bot': False, 'dist': {'name': 'Ubuntu'}, 'os': {'name': 'Linux'}, 'browser': {'version': '16.0', 'name': 'Firefox'}},),
("Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.17 (KHTML, like Gecko) Chrome/24.0.1312.1 Safari/537.17",
("Linux", "Chrome 24.0.1312.1"),
{'bot': False, "os" : {"name": "Linux"}, "browser": {"name": "Chrome", "version": "24.0.1312.1"}}),
("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_2) AppleWebKit/537.19 (KHTML, like Gecko) Chrome/25.0.1323.1 Safari/537.19",
("MacOS Macintosh X 10.8.2", "Chrome 25.0.1323.1"),
{'bot': False, 'flavor': {'name': 'MacOS', 'version': 'X 10.8.2'}, 'os': {'name': 'Macintosh'}, 'browser': {'version': '25.0.1323.1', 'name': 'Chrome'}},),
("Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_2) AppleWebKit/536.26.14 (KHTML, like Gecko) Version/6.0.1 Safari/536.26.14",
("MacOS Macintosh X 10.8.2", "Safari 6.0.1"),
{'bot': False, 'flavor': {'name': 'MacOS', 'version': 'X 10.8.2'}, 'os': {'name': 'Macintosh'}, 'browser': {'version': '6.0.1', 'name': 'Safari'}},),
("Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11",
("Windows 7", "Chrome 23.0.1271.64"),
{'bot': False, 'os': {'name': 'Windows', 'version': '7'}, 'browser': {'version': '23.0.1271.64', 'name': 'Chrome'}},),
("Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0)",
("Windows XP", "Microsoft Internet Explorer 8.0"),
{'bot': False, 'os': {'name': 'Windows', 'version': 'XP'}, 'browser': {'version': '8.0', 'name': 'Microsoft Internet Explorer'}},),
("Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; WOW64; Trident/5.0)",
("Windows 7", "Microsoft Internet Explorer 9.0"),
{'bot': False, 'os': {'name': 'Windows', 'version': '7'}, 'browser': {'version': '9.0', 'name': 'Microsoft Internet Explorer'}},),
("Mozilla/5.0 (Windows NT 6.1; WOW64; rv:15.0) Gecko/20100101 Firefox/15.0.1",
("Windows 7", "Firefox 15.0.1"),
{'bot': False, 'os': {'name': 'Windows', 'version': '7'}, 'browser': {'version': '15.0.1', 'name': 'Firefox'}},),
("Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/534.57.2 (KHTML, like Gecko) Version/5.1.7 Safari/534.57.2",
("Windows 7", "Safari 5.1.7"),
{'bot': False, 'os': {'name': 'Windows', 'version': '7'}, 'browser': {'version': '5.1.7', 'name': 'Safari'}},),
("Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/30.0.1599.101 Safari/537.36 OPR/17.0.1241.53",
("Windows 7", "Opera 17.0.1241.53"),
{'bot': False, 'os': {'name': 'Windows', 'version': '7'}, 'browser': {'version': '17.0.1241.53', 'name': 'Opera'}},),
('Mozilla/5.0+(X11;+CrOS+i686+2465.163.0)+AppleWebKit/537.1+(KHTML,+like+Gecko)+Chrome/21.0.1180.91+Safari/537.1',
('ChromeOS 2465.163.0', 'Chrome 21.0.1180.91'),
{'bot': False, 'os': {'version': '2465.163.0', 'name': 'ChromeOS'}, 'browser': {'version': '21.0.1180.91', 'name': 'Chrome'}},),
('Mozilla/5.0 (Linux; U; en-us; KFOT Build/IML74K) AppleWebKit/535.19 (KHTML, like Gecko) Silk/2.2 Safari/535.19 Silk-Accelerated=true',
('Linux', 'Safari 535.19'),
{'bot': False, 'os': {'name': 'Linux'}, 'browser': {'version': '535.19', 'name': 'Safari'}}),
('Mozilla/5.0 (Windows NT 6.3; Trident/7.0; rv:11.0) like Gecko',
('Windows 8.1', 'Microsoft Internet Explorer 11.0'),
{'bot': False, 'os': {'name': 'Windows', 'version': '8.1'}, 'browser': {'version': '11.0', 'name': 'Microsoft Internet Explorer'}},),
('Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)',
('Unknown OS', 'GoogleBot 2.1'),
{'bot': True, 'browser': {'name': 'GoogleBot', 'version': '2.1'}},),
('"Mozilla/5.0 (compatible; bingbot/2.0; +http://www.bing.com/bingbot.htm)"',
('Unknown OS', 'BingBot 2.0'),
{'bot': True, 'browser': {'name': 'BingBot', 'version': '2.0'}}),
('Mozilla/5.0 (compatible; YandexBot/3.0)',
('Unknown OS', 'YandexBot 3.0'),
{'bot': True, 'browser': {'name': 'YandexBot', 'version': '3.0'}}),
('Mozilla/5.0 (compatible; Baiduspider/2.0; +http://www.baidu.com/search/spider.html)',
('Unknown OS', 'BaiduBot 2.0'),
{'bot': True, 'browser': {'name': 'BaiduBot', 'version': '2.0'}}),
('Mozilla/5.0 (compatible; MSIE 9.0; Windows Phone OS 7.5; Trident/5.0; IEMobile/9.0; HTC; Radar 4G)',
('Windows Phone 7.5', 'Microsoft Internet Explorer 9.0'),
{'bot': False, 'browser': {'name': 'Microsoft Internet Explorer', 'version': '9.0'}, 'os': {'name': 'Windows Phone', 'version': '7.5'}}),
('Mozilla/4.0 (compatible; MSIE 7.0; Windows Phone OS 7.0; Trident/3.1; IEMobile/7.0; SAMSUNG; GT-i8700)',
('Windows Phone 7.0', 'Microsoft Internet Explorer 7.0'),
{'bot': False, 'browser': {'name': 'Microsoft Internet Explorer', 'version': '7.0'}, 'os': {'name': 'Windows Phone', 'version': '7.0'}}),
('Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; HTC_HD2_T8585; Windows Phone 6.5)',
('Windows Phone 6.5', 'Microsoft Internet Explorer 6.0'),
{'bot': False, 'browser': {'name': 'Microsoft Internet Explorer', 'version': '6.0'}, 'os': {'name': 'Windows Phone', 'version': '6.5'}}),
('Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; HTC_HD2_T8585; Windows Phone 6.5)',
('Windows Phone 6.5', 'Microsoft Internet Explorer 6.0'),
{'bot': False, 'browser': {'name': 'Microsoft Internet Explorer', 'version': '6.0'}, 'os': {'name': 'Windows Phone', 'version': '6.5'}}),
('Mozilla/5.0 (Windows NT 6.1; rv:6.0) Gecko/20110814 Firefox/6.0 Google (+https://developers.google.com/+/web/snippet/)',
('Windows 7', 'GoogleBot'),
{'bot': True, 'browser': {'name': 'GoogleBot'}, 'os': {'name': 'Windows', 'version': '7'}}),
('facebookexternalhit/1.1 (+http://www.facebook.com/externalhit_uatext.php)',
('Unknown OS', 'FacebookExternalHit 1.1'),
{'bot': True, 'browser': {'name': 'FacebookExternalHit', 'version': '1.1'},}),
('runscope-radar/2.0',
('Unknown OS', 'RunscopeRadar'),
{'bot': True, 'browser': {'name': 'RunscopeRadar'}}),
('Mozilla/5.0 (Mobile; Windows Phone 8.1; Android 4.0; ARM; Trident/7.0; Touch; rv:11.0; IEMobile/11.0; NOKIA; Lumia 720) like iPhone OS 7_0_3 Mac OS X AppleWebKit/537 (KHTML, like Gecko) Mobile Safari/537',
('Windows Phone 8.1', 'Microsoft Internet Explorer 11.0'),
{'os': {'version': '8.1', 'name': 'Windows Phone'}, 'bot': False, 'browser': {'version': '11.0', 'name': 'Microsoft Internet Explorer'}}),
('5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/47.0.2526.73 YaBrowser/16.2.0.1818 (beta) Safari/537.36',
('Linux', 'Yandex.Browser 16.2.0.1818'),
{'os': {'name': 'Linux'}, 'bot': False, 'browser': {'version': '16.2.0.1818', 'name': 'Yandex.Browser'}}),
('Mozilla/5.0 (Linux; Android 8.0.0; Nexus 5X Build/OPR6.170623.023) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.84 Mobile Safari/537.36',
('Android Linux 8.0.0', 'Chrome 62.0.3202.84'),
{'bot': False, 'browser': {'name': 'Chrome', 'version': '62.0.3202.84'}, 'dist': {'name': 'Android', 'version': '8.0.0'}, 'os': {'name': 'Linux'}}),
('Mozilla/5.0 (Android 6.0.1; Mobile; rv:63.0) Gecko/63.0 Firefox/63.0',
('Android 6.0.1', 'Firefox 63.0'),
{'dist': {'name': 'Android', 'version': '6.0.1'}, 'bot': False, 'browser': {'name': 'Firefox', 'version': '63.0'}}),
)
class TestHAP(unittest.TestCase):
def setUp(self):
self.harass_repeat = 1000
self.data = data
def test_simple_detect(self):
for agent, simple_res, res in data:
self.assertEqual(simple_detect(agent), simple_res)
def test_detect(self):
for agent, simple_res, res in data:
detected = detect(agent)
del detected['platform']
self.assertEqual(detected, res)
def test_bot(self):
s = 'Mozilla/5.0 (compatible; Googlebot/2.1; +http://www.google.com/bot.html)'
d = detect(s)
self.assertTrue(d['bot'])
def test_harass(self):
then = time.time()
for agent, simple_res, res in data * self.harass_repeat:
detect(agent)
time_taken = time.time() - then
no_of_tests = len(self.data) * self.harass_repeat
print("\nTime taken for %s detections: %s" %
(no_of_tests, time_taken))
print("Time taken for single detection: %f" %
(time_taken / (len(self.data) * self.harass_repeat)))
def test_fill_none(self):
self.assertEqual(detect(''), {'platform': {'version': None, 'name': None}}) # default
self.assertEqual(detect('', fill_none=False), {'platform': {'version': None, 'name': None}})
result = detect('', fill_none=True)
self.assertEqual(result['os']['name'], None)
self.assertEqual(result['browser']['version'], None)
result = detect('Linux; Android', fill_none=True)
self.assertEqual(result['os']['name'], 'Linux')
self.assertEqual(result['os']['version'], None)
self.assertEqual(result['browser']['name'], 'AndroidBrowser')
self.assertEqual(result['browser']['version'], None)
if __name__ == '__main__':
unittest.main()
| 77.856502 | 237 | 0.602638 | 2,650 | 17,362 | 3.924151 | 0.114717 | 0.009424 | 0.03635 | 0.026926 | 0.546206 | 0.455909 | 0.389557 | 0.314261 | 0.271084 | 0.213771 | 0 | 0.108945 | 0.143013 | 17,362 | 222 | 238 | 78.207207 | 0.589959 | 0.006048 | 0 | 0.056872 | 0 | 0.251185 | 0.647192 | 0.018142 | 0 | 0 | 0 | 0 | 0.052133 | 1 | 0.028436 | false | 0 | 0.014218 | 0 | 0.047393 | 0.009479 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
d1cc0e41e7a7df9b1cc86387c023f77ddf3a66e4 | 13,344 | py | Python | src/tuh_sz_download.py | xsthunder/TUH_EEG_Seizure_Detection | e19b9b788eda26db83269e5a076afa115b2d1db4 | [
"CC0-1.0"
] | null | null | null | src/tuh_sz_download.py | xsthunder/TUH_EEG_Seizure_Detection | e19b9b788eda26db83269e5a076afa115b2d1db4 | [
"CC0-1.0"
] | null | null | null | src/tuh_sz_download.py | xsthunder/TUH_EEG_Seizure_Detection | e19b9b788eda26db83269e5a076afa115b2d1db4 | [
"CC0-1.0"
] | 1 | 2021-06-29T12:33:40.000Z | 2021-06-29T12:33:40.000Z | # -*- coding: utf-8 -*-
"""TUH_SZ-Download.ipynb.
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1kc3U4ZxCUJ6PEeQFa9VTqNdeJPNmHXn0
http://python.omics.wiki/multiprocessing_map/multiprocessing_partial_function_multiple_arguments
"""
import multiprocessing as mp
import os
import re
import sys
from functools import partial
import requests
import tqdm
from requests.auth import HTTPBasicAuth
MAX_NUMBER_OF_CONNECTION = 100
# https://bramcohen.livejournal.com/70686.html
mylock = mp.Lock()
p = print
def print(*args, **kwargs):
"""Make print thread safe.
Args:
*args: multiple arguments.
**kwargs: keyword arguments.
"""
with mylock:
p(*args, **kwargs)
def list_all_links_in_page(source: str):
"""Return all the urls in 'src' and 'href' tags in the source.
Args:
source: a strings containing the source code of a webpage.
Returns:
A list of all the 'src' and 'href' links
in the source code of the webpage.
"""
return re.findall(
r'src\s*=\s*"([^"]+)"',
source,
) + re.findall(
r'href\s*=\s*"([^"]+)"',
source,
)
def is_link_displayed(link: str, source: str):
"""Check if the link is explicitly displayed in the source.
Args:
link: a string containing the link to find in the webpage source code.
source: the source code of the webpage.
Returns:
True is the link is visible in the webpage, False otherwise.
"""
return ('>' + link + '</a>') in source or (
'>' + link[:link.find('.')]) in source
def scrap_page(
url: str,
username: str,
password: str,
files_queue,
to_explore_queue):
"""Extract the url to explore and the url of the files to download.
Args:
url: a string which represents the URL of the webpage to download.
username: the username to use for the authentication.
password: the password to use for the authentication.
files_queue: a Queue where the URLs of the files will be stored.
to_explore_queue: a Queue whehe the URLs of the directories will
be stored.
"""
r = requests.get(url, auth=HTTPBasicAuth(username, password))
if r.status_code == 401:
print('Check the provided username and password.')
return
# Extract only the links displayed
links = []
for link in list_all_links_in_page(r.text):
if is_link_displayed(link, r.text):
links.append(link)
# Put the files in the 'files_queue'
# and the links in the 'to_explore_queue'
for link in links:
if '.' in link: # It's a file
files_queue.put(os.path.join(url, link).replace('\\', '/'))
else: # It's a folder
to_explore_queue.put(os.path.join(url, link).replace('\\', '/'))
def list_files_links_and_paths(base_url: str, username: str, password: str):
"""Find all the files, paths and folders.
1- Download the first page
2- Find the useful link
3- Download the useful link (while they are not files)
4- Repeat until reaching all the files (when all link are explored)
Args:
base_url: a string which represents the URL of the base of the server.
username: the username to use for the authentication.
password: the password to use for the authentication.
Returns:
A tuple with sorted list of the links, the path_to_files,
and folders
"""
# Init the exploration list
to_explore = [base_url]
# Set the number of workers in the pool
n_thread = 1.5 * os.cpu_count()
print('Max number of workers used:', n_thread)
manager = mp.Manager()
q_files = manager.Queue()
q_to_explore = manager.Queue()
reduced_scrap = partial(
scrap_page,
username=username,
password=password,
files_queue=q_files,
to_explore_queue=q_to_explore)
n_exploration = 0 # Store the number of iteration
while len(to_explore) > 0:
# Display the cycle number and the number
# of links to explore in the current cycle
n_exploration += 1
# Adjust the number of processes to use
if sys.platform != 'win32':
n_processes = min(len(to_explore), MAX_NUMBER_OF_CONNECTION)
else:
n_processes = min(
min(len(to_explore), MAX_NUMBER_OF_CONNECTION),
n_thread,
)
print(
'Exploration cycle number ',
n_exploration,
', ',
len(to_explore),
' link(s) to explore (using ',
n_processes,
' process(es)).',
sep='')
# Start pool
chunksize = max(1, round(n_processes ** 0.5))
with mp.Pool(processes=n_processes) as pool:
for _ in tqdm.tqdm(
pool.imap(
func=reduced_scrap,
iterable=to_explore,
chunksize=chunksize,
),
total=len(to_explore),
):
continue
# Wait for the pool to join
# Empty the to_explore list
to_explore = []
# Fill the to_explore list with the new values
while not q_to_explore.empty():
to_explore.append(q_to_explore.get())
# Extract all the files in the queue and add them in the list
files = []
while not q_files.empty():
files.append(q_files.get())
if not len(files):
# Wrong URL or authentication
exit(1)
print('Number of files:', len(files))
if(base_url[-1] == '/'):
base_url = base_url[:-1]
# Return a sorted list with all the files link, one with the path,
# relatively to the base URL and one with the folders
# (without duplicate, "tree")
return (
sorted(
list(
set(
files
),
),
),
sorted(
list(
{
filename[len(base_url):] for filename in files
},
),
),
sorted(
list(
{
filename[len(base_url): filename.rfind('/') + 1]
for filename in files
},
),
),
)
def make_all_dirs(dirs: list, base_path: str = None):
"""Make all the dirs for the dir in the dirs list.
Can expand each dir with a base_path.
Args:
dirs: a list of directory's path to create.
base_path: a base path to expand to the directory's path.
"""
if base_path is None:
base_path = os.getcwd()
for a_dir in dirs:
path = os.path.join(base_path, a_dir[1:])
if not os.path.exists(path):
os.makedirs(path)
def download_file(
link_and_path_tuple: tuple,
username: str,
password: str,
base_path: str = None):
"""Use the authentication and download the specified file
to the specified path.
Args:
link_and_path_tuple: a tuple containing the URL
of the file and the path to the file.
username: the username to use for the authentication.
password: the password to use for the authentication.
base_path: a string containing the base path
of where the files will be written.
"""
if base_path is None:
base_path = os.getcwd()
link, path = link_and_path_tuple
filename = os.path.basename(link)
path = os.path.join(base_path, path[1:])
try:
if filename not in os.listdir(path[:path.rfind('/')]):
print('Filename:', filename, '\nPath:', path, '\n')
with requests.get(
link,
stream=True,
auth=HTTPBasicAuth(username, password),
) as r:
with open(path + '.part', 'wb') as filehandler:
for chunk in r.iter_content(chunk_size=4096):
filehandler.write(chunk)
os.rename(path + '.part', path)
else:
print(
'Filename:',
filename,
'(already downloaded)\nPath:',
path,
'\n')
except OSError:
print('Error:', sys.exc_info(), '(' + filename + ')')
def download_all(
links: list,
paths: list,
base_path: str,
username: str,
password: str):
"""Download all the files and safe them in the path, using a base_path.
Args:
links: the list of all the files to download.
paths: the list of all the file's path.
base_path: a string containing the base path
of where the files will be written.
username: the username to use for the authentication.
password: the password to use for the authentication.
"""
n_thread = 1.5 * os.cpu_count()
# Adjust the number of processes to use
if sys.platform != 'win32':
n_processes = min(len(links), MAX_NUMBER_OF_CONNECTION)
else:
n_processes = min(
min(len(links), MAX_NUMBER_OF_CONNECTION),
n_thread,
)
print('Max number of workers used:', n_processes)
links_and_paths = list(zip(links, paths))
reduced_download_file = partial(
download_file,
username=username,
password=password,
base_path=base_path,
)
chunksize = max(1, round(n_processes ** 0.5))
with mp.Pool(processes=n_processes) as pool:
for _ in tqdm.tqdm(
pool.imap(
func=reduced_download_file,
iterable=links_and_paths,
chunksize=chunksize,
),
total=len(links_and_paths),
):
continue
def main(url: str, username: str, password: str, path: str = None):
"""Run the main functions to and download all the files.
Args:
url: a string which represents the URL of the base of the server.
username: the username to use for the authentication.
password: the password to use for the authentication.
path: a string containing the path to where the files will be written.
"""
links, path_to_files, folders = list_files_links_and_paths(
url,
username,
password,
)
make_all_dirs(
folders,
base_path=path,
)
download_all(
links,
path_to_files,
path,
username,
password,
)
def file_count(path: str):
"""Return the number of file in a path and subpaths.
Args:
path: a string containing the path in which to count the files.
Returns:
The number of files int the path.
"""
return sum(len(files) for r, d, files in os.walk(path))
if __name__ == '__main__':
"""
dataset_version = "v1.5.2"
path = "/content/" # "/content/drive/My Drive/Seizure_detection_project/"
+ dataset_version + "/TUH/"
base_url = 'https://www.isip.piconepress.com/projects/
tuh_eeg/downloads/tuh_eeg_seizure/' + dataset_version + '/edf'
your_username = "nedc_tuh_eeg"
your_password = "nedc_tuh_eeg"
"""
import argparse
parser = argparse.ArgumentParser(
prog='TUH dataset downloader',
description='Download all the folders and files under a base URL of'
' the Picone dataset (https://www.isip.piconepress.com/'
'projects/tuh_eeg/downloads/, is the base URL'
' to download everything).',
)
parser.add_argument(
'URL',
type=str,
nargs='+',
help='the base URL from which you want to start'
' to download the dataset',
)
parser.add_argument(
'-u',
'--username',
type=str,
help='the username you got by email after filling the request'
' form (https://www.isip.piconepress.com/projects/'
'tuh_eeg/html/request_access.php)',
)
parser.add_argument(
'-p',
'--password',
type=str,
help='the password you got by email after filling the request'
' form (https://www.isip.piconepress.com/projects/'
'tuh_eeg/html/request_access.php)',
)
parser.add_argument(
'--path',
type=str,
nargs='+',
help='by default the path is the current working directory,'
' but you can set it by yourself',
)
args = parser.parse_args()
urls = args.URL
usr = args.username
pwd = args.password
paths = args.path
if paths is None:
paths = [None]
# Paths can be a unique destination.
# Or one path per URL or one path
# per URL and current working directory for the rest.
if len(paths) < len(urls):
if len(paths) == 1:
for _ in range(len(urls) - 1):
paths.append(paths[0])
else:
for _ in range(len(urls) - len(paths)):
paths.append(None)
for url, path in zip(urls, paths):
main(url=url, username=usr, password=pwd, path=path)
# Count the number of files
# find -type f|wc -l
| 28.33121 | 96 | 0.578312 | 1,697 | 13,344 | 4.426635 | 0.182675 | 0.027556 | 0.01065 | 0.014643 | 0.305112 | 0.278621 | 0.24401 | 0.216054 | 0.202343 | 0.180777 | 0 | 0.006127 | 0.327263 | 13,344 | 470 | 97 | 28.391489 | 0.830678 | 0.313924 | 0 | 0.29588 | 1 | 0 | 0.116643 | 0.010906 | 0 | 0 | 0 | 0 | 0 | 1 | 0.037453 | false | 0.059925 | 0.033708 | 0 | 0.089888 | 0.037453 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
d1cee85492b347a562ae4ceb85089522980546dd | 145 | py | Python | ex016.py | honeyhugh/PythonCurso | e5b8efe04e100ea0b0c0aacde1caf7ae52489f40 | [
"MIT"
] | null | null | null | ex016.py | honeyhugh/PythonCurso | e5b8efe04e100ea0b0c0aacde1caf7ae52489f40 | [
"MIT"
] | null | null | null | ex016.py | honeyhugh/PythonCurso | e5b8efe04e100ea0b0c0aacde1caf7ae52489f40 | [
"MIT"
] | null | null | null | from math import trunc
num=float(input('Digite um número: '))
truncado=trunc(num)
print('O resultado truncado de {} é {}.'.format(num,truncado))
| 29 | 62 | 0.724138 | 22 | 145 | 4.772727 | 0.772727 | 0.152381 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.110345 | 145 | 4 | 63 | 36.25 | 0.813953 | 0 | 0 | 0 | 0 | 0 | 0.344828 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0.25 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
060cab58f46b546922772181541be5490ef229de | 206 | py | Python | Codeforces/B_Multiplication_Table.py | anubhab-code/Competitive-Programming | de28cb7d44044b9e7d8bdb475da61e37c018ac35 | [
"MIT"
] | null | null | null | Codeforces/B_Multiplication_Table.py | anubhab-code/Competitive-Programming | de28cb7d44044b9e7d8bdb475da61e37c018ac35 | [
"MIT"
] | null | null | null | Codeforces/B_Multiplication_Table.py | anubhab-code/Competitive-Programming | de28cb7d44044b9e7d8bdb475da61e37c018ac35 | [
"MIT"
] | null | null | null | n = int(input())
arr = [list(map(int,input().split())) for i in range(n)]
ans = [0]*n
ans[0] = int(pow((arr[0][1]*arr[0][2])//arr[1][2], 0.5))
for i in range(1,n):
ans[i]=(arr[0][i]//ans[0])
print(*ans) | 29.428571 | 56 | 0.533981 | 47 | 206 | 2.340426 | 0.382979 | 0.109091 | 0.109091 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.072222 | 0.126214 | 206 | 7 | 57 | 29.428571 | 0.538889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.142857 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ae2fe6ccc4d81d36fc6121d49060a96b53770f30 | 2,110 | py | Python | src/sportsdata/nba/teams/__init__.py | OrangeCardinal/sportsdata | e6e182e89c8f8a12ffe18b218a37b8bdb8971e03 | [
"Apache-2.0"
] | null | null | null | src/sportsdata/nba/teams/__init__.py | OrangeCardinal/sportsdata | e6e182e89c8f8a12ffe18b218a37b8bdb8971e03 | [
"Apache-2.0"
] | null | null | null | src/sportsdata/nba/teams/__init__.py | OrangeCardinal/sportsdata | e6e182e89c8f8a12ffe18b218a37b8bdb8971e03 | [
"Apache-2.0"
] | null | null | null | from .atlanta_hawks import AtlantaHawks
from .boston_celtics import BostonCeltics
from .brooklyn_nets import BrooklynNets
from .chicago_bulls import ChicagoBulls
from .cleveland_cavaliers import ClevelandCavaliers
from .denver_nuggets import DenverNuggets
from .detroit_pistons import DetroitPistons
from .golden_state_warriors import GoldenStateWarriors
from .houston_rockets import HoustonRockets
from .indiana_pacers import IndianaPacers
from .los_angeles_clippers import LosAngelesClippers
from .los_angeles_lakers import LosAngelesLakers
from .memphis_grizzlies import MemphisGrizzlies
from .miami_heat import MiamiHeat
from .milwaukee_bucks import MilwaukeeBucks
from .minnesota_timberwolves import MinnesotaTimberwolves
from .new_orleans_pelicans import NewOrleansPelicans
from .new_york_knickerbockers import NewYorkKnickerbockers
from .oklahoma_thunder import OklahomaThunder
from .orlando_magic import OrlandoMagic
from .philadelphia_76ers import Philadelphia76ers
from .phoenix_suns import PhoenixSuns
from .portland_trail_blazers import PortlandTrailBlazers
from .sacramento_kings import SacramentoKings
from .san_antonio_spurs import SanAntonioSpurs
from .toronto_raptors import TorontoRaptors
from .utah_jazz import UtahJazz
from .washington_wizards import WashingtonWizards
__all__ = ['AtlantaHawks','BostonCeltics','BrooklynNets','ChicagoBulls','ClevelandCavaliers','DenverNuggets',
'DetroitPistons','GoldenStateWarriors','HoustonRockets','IndianaPacers','LosAngelesClippers',
'LosAngelesLakers','MemphisGrizzlies','MiamiHeat','MilwaukeeBucks','MinnesotaTimberwolves',
'NewOrleansPelicans','NewYorkKnickerbockers','OklahomaThunder','OrlandoMagic','Philadelphia76ers',
'PhoenixSuns','PortlandTrailBlazers','SacramentoKings','SanAntonioSpurs','TorontoRaptors',
'UtahJazz','WashingtonWizards']
| 58.611111 | 109 | 0.745498 | 176 | 2,110 | 8.715909 | 0.517045 | 0.009126 | 0.018253 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003557 | 0.200474 | 2,110 | 35 | 110 | 60.285714 | 0.90575 | 0 | 0 | 0 | 0 | 0 | 0.19763 | 0.019905 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.823529 | 0 | 0.823529 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
ae3b5c33fb49bccecb1cb2c3dd69aa41885ac437 | 1,493 | py | Python | dockit/tests/backends/common.py | zbyte64/django-dockit | 8d00a46cb0b6237de622fcb6816067078106a0c4 | [
"BSD-3-Clause"
] | 5 | 2015-02-25T17:01:48.000Z | 2021-06-03T07:46:47.000Z | dockit/tests/backends/common.py | zbyte64/django-dockit | 8d00a46cb0b6237de622fcb6816067078106a0c4 | [
"BSD-3-Clause"
] | 1 | 2015-03-11T15:19:55.000Z | 2015-04-13T04:14:24.000Z | dockit/tests/backends/common.py | zbyte64/django-dockit | 8d00a46cb0b6237de622fcb6816067078106a0c4 | [
"BSD-3-Clause"
] | null | null | null | from dockit import schema
from dockit import backends
from django.utils import unittest
from mock import Mock, patch
class SimpleSchema(schema.Schema): #TODO make a more complex testcase
charfield = schema.CharField()
class SimpleDocument(schema.Document): #TODO make a more complex testcase
charfield = schema.CharField()
published = schema.BooleanField()
featured = schema.BooleanField()
class BackendTestCase(unittest.TestCase):
backend_name = None
def setUp(self):
self.patchers = list()
if self.backend_name not in backends.get_document_backends():
self.skipTest('Backend %s is not enabled' % self.backend_name)
def return_backend_name(*args, **kwargs):
return self.backend_name
mock = Mock(side_effect=return_backend_name)
self.patchers.append(patch.object(backends.DOCUMENT_ROUTER, 'get_storage_name_for_read', mock))
self.patchers.append(patch.object(backends.DOCUMENT_ROUTER, 'get_storage_name_for_write', mock))
self.patchers.append(patch.object(backends.INDEX_ROUTER, 'get_index_name_for_read', mock))
self.patchers.append(patch.object(backends.INDEX_ROUTER, 'get_index_name_for_write', mock))
self.mock_classes = list()
for patcher in self.patchers:
self.mock_classes.append(patcher.start())
def tearDown(self):
for patcher in self.patchers:
patcher.stop()
| 35.547619 | 104 | 0.691896 | 181 | 1,493 | 5.524862 | 0.325967 | 0.084 | 0.072 | 0.092 | 0.452 | 0.386 | 0.386 | 0.386 | 0.386 | 0.282 | 0 | 0 | 0.218352 | 1,493 | 41 | 105 | 36.414634 | 0.856898 | 0.044206 | 0 | 0.137931 | 0 | 0 | 0.086316 | 0.068772 | 0 | 0 | 0 | 0.02439 | 0 | 1 | 0.103448 | false | 0 | 0.137931 | 0.034483 | 0.551724 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
ae4e74103e32933f384e20b070862426b7ed93be | 3,126 | py | Python | tests/test_levels.py | msabramo/twiggy | 234617a9404a9bfce5f6128aac741d6420e380e9 | [
"BSD-3-Clause"
] | null | null | null | tests/test_levels.py | msabramo/twiggy | 234617a9404a9bfce5f6128aac741d6420e380e9 | [
"BSD-3-Clause"
] | null | null | null | tests/test_levels.py | msabramo/twiggy | 234617a9404a9bfce5f6128aac741d6420e380e9 | [
"BSD-3-Clause"
] | null | null | null | import sys
if sys.version_info >= (2, 7):
import unittest
else:
try:
import unittest2 as unittest
except ImportError:
raise RuntimeError("unittest2 is required for Python < 2.7")
import sys
from twiggy import levels
class LevelTestCase(unittest.TestCase):
def test_display(self):
assert str(levels.DEBUG) == 'DEBUG'
assert repr(levels.DEBUG) == '<LogLevel DEBUG>'
def test_name2level(self):
assert levels.name2level('debug') is levels.DEBUG
assert levels.name2level('Debug') is levels.DEBUG
def test_less_than(self):
assert levels.DEBUG < levels.INFO
assert levels.INFO < levels.NOTICE
assert levels.NOTICE < levels.WARNING
assert levels.WARNING < levels.ERROR
assert levels.ERROR < levels.CRITICAL
assert levels.CRITICAL < levels.DISABLED
def test_less_than_equals(self):
assert levels.DEBUG <= levels.INFO
assert levels.INFO <= levels.NOTICE
assert levels.NOTICE <= levels.WARNING
assert levels.WARNING <= levels.ERROR
assert levels.ERROR <= levels.CRITICAL
assert levels.CRITICAL <= levels.DISABLED
def test_greater_than(self):
assert levels.INFO > levels.DEBUG
assert levels.NOTICE > levels.INFO
assert levels.WARNING > levels.NOTICE
assert levels.ERROR > levels.WARNING
assert levels.CRITICAL > levels.ERROR
assert levels.DISABLED > levels.CRITICAL
def test_greater_than_equals(self):
assert levels.INFO >= levels.DEBUG
assert levels.NOTICE >= levels.INFO
assert levels.WARNING >= levels.NOTICE
assert levels.ERROR >= levels.WARNING
assert levels.CRITICAL >= levels.ERROR
assert levels.DISABLED >= levels.CRITICAL
def test_equality(self):
assert levels.DEBUG == levels.DEBUG
assert levels.INFO == levels.INFO
assert levels.NOTICE == levels.NOTICE
assert levels.WARNING == levels.WARNING
assert levels.ERROR == levels.ERROR
assert levels.CRITICAL == levels.CRITICAL
def test_inequality(self):
assert not levels.DEBUG != levels.DEBUG
assert not levels.INFO != levels.INFO
assert not levels.NOTICE != levels.NOTICE
assert not levels.WARNING != levels.WARNING
assert not levels.ERROR != levels.ERROR
assert not levels.CRITICAL != levels.CRITICAL
assert levels.INFO != levels.DEBUG
assert levels.NOTICE != levels.WARNING
assert levels.WARNING != levels.NOTICE
assert levels.ERROR != levels.WARNING
assert levels.CRITICAL != levels.ERROR
assert levels.DISABLED != levels.CRITICAL
def test_dict_key(self):
d={levels.DEBUG:42}
assert d[levels.DEBUG] == 42
def test_bogus_not_equals(self):
assert levels.DEBUG != 1
@unittest.skipIf(sys.version_info < (3,), "Python 2.x comparisons are insane")
def test_bogus_compare(self):
# XXX is there a comparable test for 2.x?
with self.assertRaises(TypeError):
levels.DEBUG < 42
| 34.733333 | 82 | 0.660909 | 373 | 3,126 | 5.477212 | 0.182306 | 0.229075 | 0.0744 | 0.085658 | 0.677435 | 0.508566 | 0.508566 | 0.469408 | 0.469408 | 0.441018 | 0 | 0.008127 | 0.252079 | 3,126 | 89 | 83 | 35.123596 | 0.865697 | 0.012476 | 0 | 0.027027 | 0 | 0 | 0.033063 | 0 | 0 | 0 | 0 | 0 | 0.662162 | 1 | 0.148649 | false | 0 | 0.081081 | 0 | 0.243243 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ae53b5149329b50270028dd7db19b6412b1d7eae | 692 | py | Python | real-world-examples/colorama_example.py | AlienCoders/learning-python | 255dc32400b79db83382e707c96df029cfe30b24 | [
"MIT"
] | 19 | 2019-08-30T06:51:52.000Z | 2022-03-11T18:44:29.000Z | real-world-examples/colorama_example.py | AlienCoders/learning-python | 255dc32400b79db83382e707c96df029cfe30b24 | [
"MIT"
] | 9 | 2020-02-14T09:21:20.000Z | 2022-03-08T09:38:09.000Z | real-world-examples/colorama_example.py | sumanchary86/learning-python | 99ae9c31d62a07d1363b67f22f93173730346d76 | [
"MIT"
] | 12 | 2020-07-20T18:49:45.000Z | 2021-12-18T11:20:03.000Z | #!/usr/bin/python
from colorama import init, Fore, Back, Style
init(autoreset=True)
print(Fore.RED + 'some red text')
print(Fore.GREEN + 'some green text')
print(Fore.BLUE + 'some blue text')
print(Fore.CYAN + 'some cyan text')
print(Fore.MAGENTA + 'some magenta text')
print(Back.GREEN + 'and with a green background')
print(Style.DIM + 'and in dim text')
print(Style.BRIGHT + Fore.GREEN + 'and green color in bright text')
print('automatically back to default color again')
# These are available color
"""
Fore: BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE, RESET.
Back: BLACK, RED, GREEN, YELLOW, BLUE, MAGENTA, CYAN, WHITE, RESET.
Style: DIM, NORMAL, BRIGHT, RESET_ALL
"""
| 27.68 | 67 | 0.715318 | 106 | 692 | 4.660377 | 0.386792 | 0.12753 | 0.105263 | 0.076923 | 0.178138 | 0.178138 | 0.178138 | 0.178138 | 0.178138 | 0 | 0 | 0 | 0.145954 | 692 | 24 | 68 | 28.833333 | 0.835871 | 0.060694 | 0 | 0 | 0 | 0 | 0.398287 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.090909 | 0 | 0.090909 | 0.818182 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
ae71e4810d9580382f2e755b86b5c3fe8502c560 | 146 | py | Python | wbb/utils/read_lines.py | Imran95942/userbotisl | 1614af1d1ba904dfd5e28dfd5b3e21d5e24bb55c | [
"MIT"
] | 1 | 2021-11-17T13:25:25.000Z | 2021-11-17T13:25:25.000Z | wbb/utils/read_lines.py | Imran95942/userbotisl | 1614af1d1ba904dfd5e28dfd5b3e21d5e24bb55c | [
"MIT"
] | null | null | null | wbb/utils/read_lines.py | Imran95942/userbotisl | 1614af1d1ba904dfd5e28dfd5b3e21d5e24bb55c | [
"MIT"
] | null | null | null | from random import choice
async def random_line(fname):
with open(fname) as f:
data = f.read().splitlines()
return choice(data)
| 18.25 | 36 | 0.664384 | 21 | 146 | 4.571429 | 0.761905 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.232877 | 146 | 7 | 37 | 20.857143 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.2 | 0 | 0.4 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ae8cb1092e1d60ae1025876274605853fe180b17 | 144 | py | Python | python_boilerplate/__init__.py | Mathanraj-Sharma/python_boilerplate | b7c37fd437adbb38cd3dece3c4dc3c30ff1601f5 | [
"MIT"
] | 4 | 2021-09-16T15:51:33.000Z | 2022-02-22T01:49:38.000Z | python_boilerplate/__init__.py | Mathanraj-Sharma/python_boilerplate | b7c37fd437adbb38cd3dece3c4dc3c30ff1601f5 | [
"MIT"
] | null | null | null | python_boilerplate/__init__.py | Mathanraj-Sharma/python_boilerplate | b7c37fd437adbb38cd3dece3c4dc3c30ff1601f5 | [
"MIT"
] | null | null | null | """Top-level package for Python Boilerplate."""
__author__ = """Mathanraj Sharma"""
__email__ = "rvmmathanraj@gmail.com"
__version__ = "0.1.0"
| 24 | 47 | 0.715278 | 17 | 144 | 5.352941 | 0.941176 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.023438 | 0.111111 | 144 | 5 | 48 | 28.8 | 0.6875 | 0.284722 | 0 | 0 | 0 | 0 | 0.443299 | 0.226804 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
88276d8f75916d3c3d56c6a9ddac193237bc937e | 930 | py | Python | backend/YouGrowGirl/plants/models.py | IsoHan/You-Grow-Girl | c6978bfdf0bcaba45f09470c6fef43e7223cf0b9 | [
"MIT"
] | 1 | 2021-09-04T23:06:32.000Z | 2021-09-04T23:06:32.000Z | backend/YouGrowGirl/plants/models.py | IsoHan/You-Grow-Girl | c6978bfdf0bcaba45f09470c6fef43e7223cf0b9 | [
"MIT"
] | null | null | null | backend/YouGrowGirl/plants/models.py | IsoHan/You-Grow-Girl | c6978bfdf0bcaba45f09470c6fef43e7223cf0b9 | [
"MIT"
] | 3 | 2021-05-07T15:56:56.000Z | 2021-09-13T01:18:24.000Z | from django.db import models
# Create your models here.
# example model
class Plant(models.Model):
common_name = models.CharField(max_length=100, unique=True)
img_name = models.CharField(max_length=100, default=False)
sunlight = models.CharField(max_length=100, blank=True)
moisture = models.CharField(max_length=500, default=False, blank=True)
toxic_to_dogs= models.BooleanField(default=False)
toxic_to_cats= models.BooleanField(default=False)
plant_habit = models.CharField(max_length=500, default=False, blank=True)
bloom_period = models.CharField(max_length=500, default=False, blank=True)
humidity = models.CharField(max_length=100, default=False, blank=True)
ph_soil = models.CharField(max_length=100, default=False, blank=True)
description = models.CharField(max_length=500, default=False, blank=True)
image = models.ImageField(upload_to="images/", null=True, blank=True)
| 46.5 | 78 | 0.762366 | 128 | 930 | 5.390625 | 0.34375 | 0.195652 | 0.234783 | 0.313043 | 0.563768 | 0.524638 | 0.473913 | 0.417391 | 0.417391 | 0 | 0 | 0.03317 | 0.124731 | 930 | 19 | 79 | 48.947368 | 0.814496 | 0.04086 | 0 | 0 | 0 | 0 | 0.007874 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.071429 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
882d7ccb95c3419ab48504c809908b56a5aa6922 | 497 | py | Python | core/wsgi.py | vlafranca/stream_framework_example | 3af636c591d4a278f3720f64118d86aeb8091714 | [
"MIT"
] | 102 | 2015-01-18T15:02:34.000Z | 2021-12-07T17:22:12.000Z | core/wsgi.py | vlafranca/stream_framework_example | 3af636c591d4a278f3720f64118d86aeb8091714 | [
"MIT"
] | 11 | 2015-01-04T14:42:11.000Z | 2022-01-13T04:58:10.000Z | core/wsgi.py | vlafranca/stream_framework_example | 3af636c591d4a278f3720f64118d86aeb8091714 | [
"MIT"
] | 53 | 2015-01-12T07:11:10.000Z | 2021-07-28T08:40:02.000Z | """
WSGI config for pinterest_example project.
It exposes the WSGI callable as a module-level variable named ``application``.
For more information on this file, see
https://docs.djangoproject.com/en/1.6/howto/deployment/wsgi/
"""
import os
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "core.settings")
from django.core.wsgi import get_wsgi_application
application = get_wsgi_application()
try:
from dj_static import Cling
except ImportError:
pass
else:
application = Cling(application)
| 22.590909 | 78 | 0.790744 | 70 | 497 | 5.5 | 0.7 | 0.051948 | 0.093506 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.004545 | 0.114688 | 497 | 21 | 79 | 23.666667 | 0.870455 | 0.448692 | 0 | 0 | 0 | 0 | 0.131579 | 0.082707 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.1 | 0.4 | 0 | 0.4 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 2 |
883b490eeac47f1e7d97a319be6df45ddc5bb1c2 | 13,831 | py | Python | path_planner/src/solver.py | eSpace-epfl/rospace-planning | fa9df6fda3d177e226b01385b86f81a1960eff82 | [
"Zlib"
] | null | null | null | path_planner/src/solver.py | eSpace-epfl/rospace-planning | fa9df6fda3d177e226b01385b86f81a1960eff82 | [
"Zlib"
] | null | null | null | path_planner/src/solver.py | eSpace-epfl/rospace-planning | fa9df6fda3d177e226b01385b86f81a1960eff82 | [
"Zlib"
] | null | null | null | # @copyright Copyright (c) 2017, Davide Frey (frey.davide.ae@gmail.com)
#
# @license zlib license
#
# This file is licensed under the terms of the zlib license.
# See the LICENSE.md file in the root of this repository
# for complete details.
"""Class holding the definition of the Solver, which outputs a manoeuvre plan given a scenario."""
from rospace_lib import Cartesian, KepOrbElem, CartesianLVLH, mu_earth
from state import Satellite, Chaser
from checkpoint import AbsoluteCP, RelativeCP
from scenario import Scenario
from datetime import datetime
from orbit_adjuster import *
class Solver(object):
"""
Base solver class, which takes a predefined scenario and some initial conditions and outputs one possible
manoeuvre plan that can be executed in order to achieve the final wanted position.
NOTE: This solver works with optimal solutions for each single manoeuvre, but it has to be noted that the
combination of all those optimal solutions may be sub-optimal!
For each manoeuvre it choose to apply the one that consumes the least delta-V within a certain given time
interval. Therefore, depending on the time interval chosen, the solution may not be the optimal one!
Attributes:
manoeuvre_plan (list): List of the manoeuvre that has to be executed to perform the scenario.
scenario (Scenario): The scenario that has to be solved.
chaser (Chaser): Chaser actual state, evolving in time according to the solver.
target (Satellite): Target actual state, evolving in time according to the solver.
epoch (datetime): Actual epoch, evolving in time according to the solver.
tot_dV (float64): Total amount of delta-V consumed in [km/s].
"""
def __init__(self):
self.manoeuvre_plan = []
self.scenario = None
self.chaser = Chaser()
self.target = Satellite()
self.epoch = None
self.tot_dV = 0.0
def initialize_solver(self, scenario):
"""
Given the scenario to be solved, initialize the solver attributes.
Args:
scenario (Scenario)
"""
self.scenario = scenario
self.epoch = scenario.date
self.target.initialize_satellite('target', scenario.ic_name, scenario.prop_type)
self.chaser.initialize_satellite('chaser', scenario.ic_name, scenario.prop_type, self.target)
def solve_scenario(self):
"""
Function that solve the scenario given in the solver object.
"""
print "\n+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++"
print " SOLVING SCENARIO: " + self.scenario.name
print "+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n"
print "Scenario overview: "
print self.scenario.overview
# Extract scenario checkpoints
checkpoints = self.scenario.checkpoints
print "\n------------------------Target initial state------------------------"
self._print_state(self.target)
print "---------------------------------------------------------------------\n"
print "\n------------------------Chaser initial state------------------------"
self._print_state(self.chaser)
print "---------------------------------------------------------------------\n"
# Start solving scenario by popping positions from position list
for checkpoint in checkpoints:
print "\n\n======================================================================="
print "[GOING TO CHECKPOINT NR. " + str(checkpoint.id) + "]"
print "======================================================================="
print "[CHECKPOINT]:"
self._print_checkpoint(checkpoint)
print "======================================================================="
if type(checkpoint) == AbsoluteCP:
self.absolute_solver(checkpoint)
elif type(checkpoint) == RelativeCP:
self.relative_solver(checkpoint)
else:
raise TypeError()
print "======================================================================="
print "[REACHED STATE]:"
print "\n--------------------Chaser-------------------"
self._print_state(self.chaser)
print "\n--------------------Target-------------------"
self._print_state(self.target)
print "=======================================================================\n"
self.tot_dV, tot_dt = self._print_result()
print "\n\n-----------------> Scenario elaborated <--------------------\n"
print "---> Scenario duration: " + str(tot_dt) + " seconds"
print "---> Total deltaV: " + str(self.tot_dV) + " km/s"
def absolute_solver(self, checkpoint):
"""
Absolute solver. Calculate the manoeuvre needed to go from an absolute position to another.
Args:
checkpoint (AbsoluteCP): Absolute checkpoint with the state defined as Mean Orbital Elements.
"""
orbit_adj = ArgumentOfPerigee()
if orbit_adj.is_necessary(self.chaser, checkpoint.abs_state):
self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
orbit_adj = HohmannTransfer()
if orbit_adj.is_necessary(self.chaser, checkpoint.abs_state):
self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
orbit_adj = PlaneOrientation()
if orbit_adj.is_necessary(self.chaser, checkpoint.abs_state):
self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
def relative_solver(self, checkpoint):
"""
Relative solver. Calculate the manoeuvre needed to go from a relative position to another.
Args:
checkpoint (RelativeCP)
"""
# Mean orbital elements
chaser_mean = self.chaser.get_mean_oe()
target_mean = self.target.get_mean_oe()
# Check if plane needs to be corrected again
# TODO: Remove changes in plane if it is drifting autonomously to the wanted direction
tol_i = 1.0 / chaser_mean.a
tol_O = 1.0 / chaser_mean.a
# At this point, inclination and raan should match the one of the target
di = target_mean.i - chaser_mean.i
dO = target_mean.O - chaser_mean.O
if abs(di) > tol_i or abs(dO) > tol_O:
checkpoint_abs = AbsoluteCP()
checkpoint_abs.abs_state.i = target_mean.i
checkpoint_abs.abs_state.O = target_mean.O
orbit_adj = PlaneOrientation()
orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint_abs, self.target)
if checkpoint.manoeuvre_type == 'standard':
print "Standard relative manoeuvre..."
if self.target.prop.prop_type == 'real-world':
orbit_adj = HamelDeLafontaine()
self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
elif self.target.prop.prop_type == '2-body':
# orbit_adj = ClohessyWiltshire()
# self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
# orbit_adj = TschaunerHempel()
# self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
orbit_adj = MultiLambert()
self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
else:
raise TypeError('Propagator type not recognized!')
elif checkpoint.manoeuvre_type == 'radial':
print "Radial manoeuvre..."
# Manoeuvre type is radial
# -> Transfer time is known to be half orbital period.
# -> Depending on the number of rotations wanted, transfer time is extended.
dt = np.pi * np.sqrt(target_mean.a ** 3.0 / mu_earth)
checkpoint.t_min = dt
checkpoint.t_max = dt + 1.0
if self.target.prop.prop_type == 'real-world':
orbit_adj = HamelDeLafontaine()
self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
elif self.target.prop.prop_type == '2-body':
# orbit_adj = ClohessyWiltshire()
# self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
# orbit_adj = TschaunerHempel()
# self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
orbit_adj = MultiLambert()
self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
else:
raise TypeError('Propagator type not recognized!')
elif checkpoint.manoeuvre_type == 'drift':
orbit_adj = Drift()
new_manoeuvre_plan = orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target, self.manoeuvre_plan)
self.manoeuvre_plan = new_manoeuvre_plan
print "Drifting manoeuvre"
elif checkpoint.manoeuvre_type == 'fly-around':
# Check if the checkpoint.rel_state.R[2] is zero:
# -> Yes: Fly-Around on plane, risky
# -> Radial manoeuvre
# -> Reinitialize propagator & "remove" last deltaV
# -> Let the spacecraft drift for a certain deltaT or until it reaches a certain position
# -> No: Diagonal fly-around, safe
# -> Radial manoeuvre 1/4 T
# -> Reinitialize propagator & "remove" last deltaV
# -> Out-of-plane manoeuvre to inclinate the relative orbit
# -> Reinitialize propagator & "remove" last deltaV
# -> Let the spacecraft drift for a certain deltaT or until it reaches a certain position
raise NotImplementedError()
elif checkpoint.manoeuvre_type == 'helix':
# Apply a certain deltaV out-of-plane
orbit_adj = Helix()
self.manoeuvre_plan += orbit_adj.evaluate_manoeuvre(self.chaser, checkpoint, self.target)
def _print_result(self):
"""
Print out results of the simulation and all the manoeuvres.
"""
tot_dv = 0
old_epoch = self.scenario.date
for it, man in enumerate(self.manoeuvre_plan):
print '\n[INFO]: Manoeuvre nr. ' + str(it) + ':'
print '--> DeltaV: ' + str(man.deltaV) + ' [km/s]'
print '--> 2-Norm DeltaV: ' + str(np.linalg.norm(man.deltaV)) + ' [km/s]'
print '--> 1-Norm DeltaV: ' + str(np.linalg.norm(man.deltaV, 1)) + ' [km/s]'
print '--> Execution Epoch: ' + str(man.execution_epoch)
print '--> Transfer duration: ' + str((man.execution_epoch - old_epoch).total_seconds()) + ' [s]'
old_epoch = man.execution_epoch
tot_dv += np.linalg.norm(man.deltaV)
return tot_dv, (man.execution_epoch - self.scenario.date).total_seconds()
@staticmethod
def _print_state(satellite):
"""
Print out satellite state.
Args:
satellite (Satellite)
"""
print " >> Cartesian: "
print " R: " + str(satellite.abs_state.R) + " [km]"
print " V: " + str(satellite.abs_state.V) + " [km/s]"
print ""
kep_osc = satellite.get_osc_oe()
print " >> Osculating orbital elements: "
print " a: " + str(kep_osc.a)
print " e: " + str(kep_osc.e)
print " i: " + str(kep_osc.i)
print " O: " + str(kep_osc.O)
print " w: " + str(kep_osc.w)
print " v: " + str(kep_osc.v)
print ""
kep_mean = satellite.get_mean_oe()
print " >> Mean orbital elements: "
print " a: " + str(kep_mean.a)
print " e: " + str(kep_mean.e)
print " i: " + str(kep_mean.i)
print " O: " + str(kep_mean.O)
print " w: " + str(kep_mean.w)
print " v: " + str(kep_mean.v)
if hasattr(satellite, 'rel_state'):
print ""
print " >> Cartesian LVLH: "
print " R: " + str(satellite.rel_state.R) + " [km]"
print " V: " + str(satellite.rel_state.V) + " [km/s]"
@staticmethod
def _print_checkpoint(checkpoint):
"""
Print out checkpoint informations.
Args:
checkpoint (CheckPoint)
"""
checkpoint_type = type(checkpoint)
if checkpoint_type == RelativeCP:
print " >> Cartesian LVLH: "
print " R : " + str(checkpoint.rel_state.R) + " [km]"
print " V : " + str(checkpoint.rel_state.V) + " [km/s]"
print ""
elif checkpoint_type == AbsoluteCP:
print " >> Mean orbital elements: "
print " a : " + str(checkpoint.abs_state.a)
print " e : " + str(checkpoint.abs_state.e)
print " i : " + str(checkpoint.abs_state.i)
print " O : " + str(checkpoint.abs_state.O)
print " w : " + str(checkpoint.abs_state.w)
print " v : " + str(checkpoint.abs_state.v)
else:
raise TypeError('CheckPoint type not recognized!')
| 43.768987 | 120 | 0.553395 | 1,482 | 13,831 | 5.030364 | 0.188259 | 0.033266 | 0.045607 | 0.046948 | 0.385781 | 0.339504 | 0.325017 | 0.270288 | 0.250168 | 0.238095 | 0 | 0.002561 | 0.294122 | 13,831 | 315 | 121 | 43.907937 | 0.761037 | 0.133107 | 0 | 0.269006 | 0 | 0 | 0.20797 | 0.096097 | 0 | 0 | 0 | 0.003175 | 0 | 0 | null | null | 0 | 0.035088 | null | null | 0.432749 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
883cefcf581ff75d9f584595e01bc4b11458a873 | 309,658 | py | Python | results/v161_cuda70_k40c.py | supreethms1809/magma-2.2.0 | b713d0b0a7a4724847e3a4050987c5ea9e7a7279 | [
"BSD-3-Clause"
] | 31 | 2015-06-19T14:41:12.000Z | 2021-02-15T12:47:57.000Z | results/v161_cuda70_k40c.py | supreethms1809/magma-2.2.0 | b713d0b0a7a4724847e3a4050987c5ea9e7a7279 | [
"BSD-3-Clause"
] | 3 | 2020-01-02T05:21:16.000Z | 2020-01-07T20:04:05.000Z | results/v161_cuda70_k40c.py | supreethms1809/magma-2.2.0 | b713d0b0a7a4724847e3a4050987c5ea9e7a7279 | [
"BSD-3-Clause"
] | 17 | 2015-04-01T14:26:48.000Z | 2021-12-27T06:12:15.000Z | import numpy
from numpy import array, nan, inf
version = '1.6.1'
cuda = '7.0'
device = 'Kepler K40c'
cpu = '2x8 core Sandy Bridge E5-2670'
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/cgeev.txt
# numactl --interleave=all ./testing_cgeev -RN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cgeev_RN = array([
[ 10, nan, 0.0005 ],
[ 20, nan, 0.0008 ],
[ 30, nan, 0.0013 ],
[ 40, nan, 0.0039 ],
[ 50, nan, 0.0047 ],
[ 60, nan, 0.0054 ],
[ 70, nan, 0.0080 ],
[ 80, nan, 0.0108 ],
[ 90, nan, 0.0124 ],
[ 100, nan, 0.0159 ],
[ 200, nan, 0.0589 ],
[ 300, nan, 0.0937 ],
[ 400, nan, 0.1403 ],
[ 500, nan, 0.1971 ],
[ 600, nan, 0.3611 ],
[ 700, nan, 0.4680 ],
[ 800, nan, 0.5535 ],
[ 900, nan, 0.6994 ],
[ 1000, nan, 0.7811 ],
[ 2000, nan, 2.4442 ],
[ 3000, nan, 7.2809 ],
[ 4000, nan, 11.6277 ],
[ 5000, nan, 17.5651 ],
[ 6000, nan, 31.0414 ],
[ 7000, nan, 41.7092 ],
[ 8000, nan, 53.7020 ],
[ 9000, nan, 67.8587 ],
[ 10000, nan, 81.7743 ],
[ 12000, nan, 124.0545 ],
[ 14000, nan, 167.2559 ],
[ 16000, nan, 230.2912 ],
[ 18000, nan, 290.8537 ],
[ 20000, nan, 373.4943 ],
])
# numactl --interleave=all ./testing_cgeev -RV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cgeev_RV = array([
[ 10, nan, 0.0019 ],
[ 20, nan, 0.0025 ],
[ 30, nan, 0.0027 ],
[ 40, nan, 0.0052 ],
[ 50, nan, 0.0078 ],
[ 60, nan, 0.0070 ],
[ 70, nan, 0.0097 ],
[ 80, nan, 0.0121 ],
[ 90, nan, 0.0143 ],
[ 100, nan, 0.0233 ],
[ 200, nan, 0.0717 ],
[ 300, nan, 0.1684 ],
[ 400, nan, 0.2235 ],
[ 500, nan, 0.2950 ],
[ 600, nan, 0.6602 ],
[ 700, nan, 0.7326 ],
[ 800, nan, 0.9360 ],
[ 900, nan, 1.1744 ],
[ 1000, nan, 0.9703 ],
[ 2000, nan, 3.8646 ],
[ 3000, nan, 11.9488 ],
[ 4000, nan, 17.3995 ],
[ 5000, nan, 29.6873 ],
[ 6000, nan, 47.0757 ],
[ 7000, nan, 66.3783 ],
[ 8000, nan, 86.6015 ],
[ 9000, nan, 111.6952 ],
[ 10000, nan, 148.4911 ],
[ 12000, nan, 218.9101 ],
[ 14000, nan, 318.8500 ],
[ 16000, nan, 446.7903 ],
[ 18000, nan, 611.1254 ],
[ 20000, nan, 799.2029 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/cgeqrf.txt
# numactl --interleave=all ./testing_cgeqrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cgeqrf = array([
[ 10, 10, nan, nan, 0.13, 0.00, nan ],
[ 20, 20, nan, nan, 0.80, 0.00, nan ],
[ 30, 30, nan, nan, 2.05, 0.00, nan ],
[ 40, 40, nan, nan, 3.58, 0.00, nan ],
[ 50, 50, nan, nan, 5.09, 0.00, nan ],
[ 60, 60, nan, nan, 6.83, 0.00, nan ],
[ 70, 70, nan, nan, 2.17, 0.00, nan ],
[ 80, 80, nan, nan, 3.26, 0.00, nan ],
[ 90, 90, nan, nan, 3.77, 0.00, nan ],
[ 100, 100, nan, nan, 5.51, 0.00, nan ],
[ 200, 200, nan, nan, 17.49, 0.00, nan ],
[ 300, 300, nan, nan, 40.92, 0.00, nan ],
[ 400, 400, nan, nan, 63.73, 0.01, nan ],
[ 500, 500, nan, nan, 93.16, 0.01, nan ],
[ 600, 600, nan, nan, 120.87, 0.01, nan ],
[ 700, 700, nan, nan, 153.14, 0.01, nan ],
[ 800, 800, nan, nan, 183.92, 0.01, nan ],
[ 900, 900, nan, nan, 214.53, 0.02, nan ],
[ 1000, 1000, nan, nan, 250.42, 0.02, nan ],
[ 2000, 2000, nan, nan, 626.11, 0.07, nan ],
[ 3000, 3000, nan, nan, 1017.00, 0.14, nan ],
[ 4000, 4000, nan, nan, 1393.34, 0.25, nan ],
[ 5000, 5000, nan, nan, 1484.88, 0.45, nan ],
[ 6000, 6000, nan, nan, 1779.15, 0.65, nan ],
[ 7000, 7000, nan, nan, 1943.20, 0.94, nan ],
[ 8000, 8000, nan, nan, 2076.82, 1.32, nan ],
[ 9000, 9000, nan, nan, 2162.67, 1.80, nan ],
[ 10000, 10000, nan, nan, 2229.67, 2.39, nan ],
[ 12000, 12000, nan, nan, 2325.79, 3.96, nan ],
[ 14000, 14000, nan, nan, 2379.66, 6.15, nan ],
[ 16000, 16000, nan, nan, 2403.02, 9.09, nan ],
[ 18000, 18000, nan, nan, 2416.62, 12.87, nan ],
[ 20000, 20000, nan, nan, 2456.26, 17.37, nan ],
])
# numactl --interleave=all ./testing_cgeqrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cgeqrf_gpu = array([
[ 10, 10, nan, nan, 0.01, 0.00, nan ],
[ 20, 20, nan, nan, 0.05, 0.00, nan ],
[ 30, 30, nan, nan, 0.17, 0.00, nan ],
[ 40, 40, nan, nan, 0.34, 0.00, nan ],
[ 50, 50, nan, nan, 0.63, 0.00, nan ],
[ 60, 60, nan, nan, 1.05, 0.00, nan ],
[ 70, 70, nan, nan, 1.20, 0.00, nan ],
[ 80, 80, nan, nan, 1.74, 0.00, nan ],
[ 90, 90, nan, nan, 2.59, 0.00, nan ],
[ 100, 100, nan, nan, 7.08, 0.00, nan ],
[ 200, 200, nan, nan, 14.62, 0.00, nan ],
[ 300, 300, nan, nan, 32.56, 0.00, nan ],
[ 400, 400, nan, nan, 50.97, 0.01, nan ],
[ 500, 500, nan, nan, 81.01, 0.01, nan ],
[ 600, 600, nan, nan, 109.60, 0.01, nan ],
[ 700, 700, nan, nan, 137.69, 0.01, nan ],
[ 800, 800, nan, nan, 169.58, 0.02, nan ],
[ 900, 900, nan, nan, 200.46, 0.02, nan ],
[ 1000, 1000, nan, nan, 231.75, 0.02, nan ],
[ 2000, 2000, nan, nan, 607.28, 0.07, nan ],
[ 3000, 3000, nan, nan, 1004.62, 0.14, nan ],
[ 4000, 4000, nan, nan, 1374.30, 0.25, nan ],
[ 5000, 5000, nan, nan, 1466.80, 0.45, nan ],
[ 6000, 6000, nan, nan, 1722.78, 0.67, nan ],
[ 7000, 7000, nan, nan, 1939.11, 0.94, nan ],
[ 8000, 8000, nan, nan, 2077.29, 1.31, nan ],
[ 9000, 9000, nan, nan, 2153.94, 1.81, nan ],
[ 10000, 10000, nan, nan, 2107.55, 2.53, nan ],
[ 12000, 12000, nan, nan, 2238.10, 4.12, nan ],
[ 14000, 14000, nan, nan, 2354.83, 6.22, nan ],
[ 16000, 16000, nan, nan, 2369.16, 9.22, nan ],
[ 18000, 18000, nan, nan, 2396.27, 12.98, nan ],
[ 20000, 20000, nan, nan, 2451.14, 17.41, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/cgesvd.txt
# numactl --interleave=all ./testing_cgesvd -UN -VN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
cgesvd_UN = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.02, nan ],
[ nan, 300, 300, nan, 0.03, nan ],
[ nan, 400, 400, nan, 0.05, nan ],
[ nan, 500, 500, nan, 0.08, nan ],
[ nan, 600, 600, nan, 0.11, nan ],
[ nan, 700, 700, nan, 0.15, nan ],
[ nan, 800, 800, nan, 0.22, nan ],
[ nan, 900, 900, nan, 0.24, nan ],
[ nan, 1000, 1000, nan, 0.29, nan ],
[ nan, 2000, 2000, nan, 1.14, nan ],
[ nan, 3000, 3000, nan, 2.95, nan ],
[ nan, 4000, 4000, nan, 5.86, nan ],
[ nan, 5000, 5000, nan, 10.14, nan ],
[ nan, 6000, 6000, nan, 16.08, nan ],
[ nan, 7000, 7000, nan, 23.93, nan ],
[ nan, 8000, 8000, nan, 34.23, nan ],
[ nan, 9000, 9000, nan, 46.92, nan ],
[ nan, 10000, 10000, nan, 62.76, nan ],
[ nan, 12000, 12000, nan, 106.69, nan ],
[ nan, 14000, 14000, nan, 163.72, nan ],
[ nan, 16000, 16000, nan, 249.04, nan ],
[ nan, 18000, 18000, nan, 350.21, nan ],
[ nan, 20000, 20000, nan, 491.80, nan ],
[ nan, 300, 100, nan, 0.00, nan ],
[ nan, 600, 200, nan, 0.02, nan ],
[ nan, 900, 300, nan, 0.04, nan ],
[ nan, 1200, 400, nan, 0.07, nan ],
[ nan, 1500, 500, nan, 0.10, nan ],
[ nan, 1800, 600, nan, 0.14, nan ],
[ nan, 2100, 700, nan, 0.19, nan ],
[ nan, 2400, 800, nan, 0.25, nan ],
[ nan, 2700, 900, nan, 0.32, nan ],
[ nan, 3000, 1000, nan, 0.43, nan ],
[ nan, 6000, 2000, nan, 2.01, nan ],
[ nan, 9000, 3000, nan, 4.67, nan ],
[ nan, 12000, 4000, nan, 9.60, nan ],
[ nan, 15000, 5000, nan, 17.07, nan ],
[ nan, 18000, 6000, nan, 27.45, nan ],
[ nan, 21000, 7000, nan, 41.71, nan ],
[ nan, 24000, 8000, nan, 60.60, nan ],
[ nan, 27000, 9000, nan, 83.55, nan ],
[ nan, 100, 300, nan, 0.00, nan ],
[ nan, 200, 600, nan, 0.02, nan ],
[ nan, 300, 900, nan, 0.04, nan ],
[ nan, 400, 1200, nan, 0.07, nan ],
[ nan, 500, 1500, nan, 0.11, nan ],
[ nan, 600, 1800, nan, 0.15, nan ],
[ nan, 700, 2100, nan, 0.21, nan ],
[ nan, 800, 2400, nan, 0.27, nan ],
[ nan, 900, 2700, nan, 0.33, nan ],
[ nan, 1000, 3000, nan, 0.41, nan ],
[ nan, 2000, 6000, nan, 1.76, nan ],
[ nan, 3000, 9000, nan, 4.75, nan ],
[ nan, 4000, 12000, nan, 9.77, nan ],
[ nan, 5000, 15000, nan, 17.43, nan ],
[ nan, 6000, 18000, nan, 28.71, nan ],
[ nan, 7000, 21000, nan, 43.55, nan ],
[ nan, 8000, 24000, nan, 61.50, nan ],
[ nan, 9000, 27000, nan, 96.95, nan ],
[ nan, 10000, 100, nan, 0.02, nan ],
[ nan, 20000, 200, nan, 0.08, nan ],
[ nan, 30000, 300, nan, 0.19, nan ],
[ nan, 40000, 400, nan, 0.51, nan ],
[ nan, 50000, 500, nan, 0.79, nan ],
[ nan, 60000, 600, nan, 1.17, nan ],
[ nan, 70000, 700, nan, 1.63, nan ],
[ nan, 80000, 800, nan, 2.23, nan ],
[ nan, 90000, 900, nan, 3.37, nan ],
[ nan, 100000, 1000, nan, 4.22, nan ],
[ nan, 200000, 2000, nan, 24.45, nan ],
[ nan, 100, 10000, nan, 0.02, nan ],
[ nan, 200, 20000, nan, 0.09, nan ],
[ nan, 300, 30000, nan, 0.24, nan ],
[ nan, 400, 40000, nan, 0.46, nan ],
[ nan, 500, 50000, nan, 0.80, nan ],
[ nan, 600, 60000, nan, 1.29, nan ],
[ nan, 700, 70000, nan, 1.94, nan ],
[ nan, 800, 80000, nan, 2.90, nan ],
[ nan, 900, 90000, nan, 3.60, nan ],
[ nan, 1000, 100000, nan, 4.87, nan ],
[ nan, 2000, 200000, nan, 29.54, nan ],
])
# numactl --interleave=all ./testing_cgesvd -US -VS -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
cgesvd_US = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.01, nan ],
[ nan, 60, 60, nan, 0.01, nan ],
[ nan, 70, 70, nan, 0.01, nan ],
[ nan, 80, 80, nan, 0.01, nan ],
[ nan, 90, 90, nan, 0.02, nan ],
[ nan, 100, 100, nan, 0.02, nan ],
[ nan, 200, 200, nan, 0.02, nan ],
[ nan, 300, 300, nan, 0.05, nan ],
[ nan, 400, 400, nan, 0.09, nan ],
[ nan, 500, 500, nan, 0.15, nan ],
[ nan, 600, 600, nan, 0.21, nan ],
[ nan, 700, 700, nan, 0.29, nan ],
[ nan, 800, 800, nan, 0.38, nan ],
[ nan, 900, 900, nan, 0.49, nan ],
[ nan, 1000, 1000, nan, 0.62, nan ],
[ nan, 2000, 2000, nan, 3.01, nan ],
[ nan, 3000, 3000, nan, 9.41, nan ],
[ nan, 4000, 4000, nan, 15.97, nan ],
[ nan, 5000, 5000, nan, 32.61, nan ],
[ nan, 6000, 6000, nan, 53.98, nan ],
[ nan, 7000, 7000, nan, 86.43, nan ],
[ nan, 8000, 8000, nan, 117.65, nan ],
[ nan, 9000, 9000, nan, 182.15, nan ],
[ nan, 10000, 10000, nan, 254.41, nan ],
[ nan, 12000, 12000, nan, 421.33, nan ],
[ nan, 14000, 14000, nan, 737.22, nan ],
[ nan, 16000, 16000, nan, 1059.89, nan ],
[ nan, 18000, 18000, nan, 1580.86, nan ],
[ nan, 20000, 20000, nan, 2092.23, nan ],
[ nan, 300, 100, nan, 0.03, nan ],
[ nan, 600, 200, nan, 0.03, nan ],
[ nan, 900, 300, nan, 0.07, nan ],
[ nan, 1200, 400, nan, 0.14, nan ],
[ nan, 1500, 500, nan, 0.22, nan ],
[ nan, 1800, 600, nan, 0.35, nan ],
[ nan, 2100, 700, nan, 0.48, nan ],
[ nan, 2400, 800, nan, 0.64, nan ],
[ nan, 2700, 900, nan, 0.85, nan ],
[ nan, 3000, 1000, nan, 0.98, nan ],
[ nan, 6000, 2000, nan, 4.89, nan ],
[ nan, 9000, 3000, nan, 14.56, nan ],
[ nan, 12000, 4000, nan, 28.84, nan ],
[ nan, 15000, 5000, nan, 55.04, nan ],
[ nan, 18000, 6000, nan, 91.95, nan ],
[ nan, 21000, 7000, nan, 143.34, nan ],
[ nan, 24000, 8000, nan, 209.27, nan ],
[ nan, 27000, 9000, nan, 292.32, nan ],
[ nan, 100, 300, nan, 0.07, nan ],
[ nan, 200, 600, nan, 0.07, nan ],
[ nan, 300, 900, nan, 0.20, nan ],
[ nan, 400, 1200, nan, 0.43, nan ],
[ nan, 500, 1500, nan, 0.79, nan ],
[ nan, 600, 1800, nan, 1.28, nan ],
[ nan, 700, 2100, nan, 1.97, nan ],
[ nan, 800, 2400, nan, 2.79, nan ],
[ nan, 900, 2700, nan, 4.02, nan ],
[ nan, 1000, 3000, nan, 5.70, nan ],
[ nan, 2000, 6000, nan, 45.69, nan ],
[ nan, 3000, 9000, nan, 150.04, nan ],
[ nan, 4000, 12000, nan, 347.69, nan ],
[ nan, 5000, 15000, nan, 661.10, nan ],
[ nan, 6000, 18000, nan, 1141.46, nan ],
[ nan, 7000, 21000, nan, 1767.70, nan ],
[ nan, 8000, 24000, nan, 2441.61, nan ],
[ nan, 9000, 27000, nan, 3646.59, nan ],
[ nan, 10000, 100, nan, 0.07, nan ],
[ nan, 20000, 200, nan, 0.20, nan ],
[ nan, 30000, 300, nan, 0.54, nan ],
[ nan, 40000, 400, nan, 1.18, nan ],
[ nan, 50000, 500, nan, 2.12, nan ],
[ nan, 60000, 600, nan, 3.14, nan ],
[ nan, 70000, 700, nan, 4.66, nan ],
[ nan, 80000, 800, nan, 6.44, nan ],
[ nan, 90000, 900, nan, 9.64, nan ],
[ nan, 100000, 1000, nan, 12.90, nan ],
[ nan, 200000, 2000, nan, 91.79, nan ],
[ nan, 100, 10000, nan, 0.25, nan ],
[ nan, 200, 20000, nan, 1.94, nan ],
[ nan, 300, 30000, nan, 6.23, nan ],
[ nan, 400, 40000, nan, 12.90, nan ],
[ nan, 500, 50000, nan, 25.83, nan ],
[ nan, 600, 60000, nan, 44.95, nan ],
[ nan, 700, 70000, nan, 70.03, nan ],
[ nan, 800, 80000, nan, 103.48, nan ],
[ nan, 900, 90000, nan, 137.84, nan ],
[ nan, 1000, 100000, nan, 196.71, nan ],
[ nan, 2000, 200000, nan, 1479.90, nan ],
])
# numactl --interleave=all ./testing_cgesdd -UN -VN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
cgesdd_UN = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.02, nan ],
[ nan, 300, 300, nan, 0.03, nan ],
[ nan, 400, 400, nan, 0.05, nan ],
[ nan, 500, 500, nan, 0.08, nan ],
[ nan, 600, 600, nan, 0.11, nan ],
[ nan, 700, 700, nan, 0.15, nan ],
[ nan, 800, 800, nan, 0.19, nan ],
[ nan, 900, 900, nan, 0.24, nan ],
[ nan, 1000, 1000, nan, 0.29, nan ],
[ nan, 2000, 2000, nan, 1.15, nan ],
[ nan, 3000, 3000, nan, 2.95, nan ],
[ nan, 4000, 4000, nan, 5.87, nan ],
[ nan, 5000, 5000, nan, 10.15, nan ],
[ nan, 6000, 6000, nan, 16.09, nan ],
[ nan, 7000, 7000, nan, 23.94, nan ],
[ nan, 8000, 8000, nan, 34.26, nan ],
[ nan, 9000, 9000, nan, 46.95, nan ],
[ nan, 10000, 10000, nan, 62.80, nan ],
[ nan, 12000, 12000, nan, 106.78, nan ],
[ nan, 14000, 14000, nan, 163.81, nan ],
[ nan, 16000, 16000, nan, 249.17, nan ],
[ nan, 18000, 18000, nan, 350.33, nan ],
[ nan, 20000, 20000, nan, 492.09, nan ],
[ nan, 300, 100, nan, 0.00, nan ],
[ nan, 600, 200, nan, 0.02, nan ],
[ nan, 900, 300, nan, 0.04, nan ],
[ nan, 1200, 400, nan, 0.07, nan ],
[ nan, 1500, 500, nan, 0.10, nan ],
[ nan, 1800, 600, nan, 0.14, nan ],
[ nan, 2100, 700, nan, 0.19, nan ],
[ nan, 2400, 800, nan, 0.25, nan ],
[ nan, 2700, 900, nan, 0.32, nan ],
[ nan, 3000, 1000, nan, 0.39, nan ],
[ nan, 6000, 2000, nan, 1.74, nan ],
[ nan, 9000, 3000, nan, 4.68, nan ],
[ nan, 12000, 4000, nan, 9.60, nan ],
[ nan, 15000, 5000, nan, 17.05, nan ],
[ nan, 18000, 6000, nan, 27.55, nan ],
[ nan, 21000, 7000, nan, 41.62, nan ],
[ nan, 24000, 8000, nan, 60.31, nan ],
[ nan, 27000, 9000, nan, 83.47, nan ],
[ nan, 100, 300, nan, 0.00, nan ],
[ nan, 200, 600, nan, 0.02, nan ],
[ nan, 300, 900, nan, 0.04, nan ],
[ nan, 400, 1200, nan, 0.07, nan ],
[ nan, 500, 1500, nan, 0.11, nan ],
[ nan, 600, 1800, nan, 0.15, nan ],
[ nan, 700, 2100, nan, 0.21, nan ],
[ nan, 800, 2400, nan, 0.26, nan ],
[ nan, 900, 2700, nan, 0.33, nan ],
[ nan, 1000, 3000, nan, 0.41, nan ],
[ nan, 2000, 6000, nan, 1.77, nan ],
[ nan, 3000, 9000, nan, 4.75, nan ],
[ nan, 4000, 12000, nan, 9.78, nan ],
[ nan, 5000, 15000, nan, 17.40, nan ],
[ nan, 6000, 18000, nan, 28.22, nan ],
[ nan, 7000, 21000, nan, 42.61, nan ],
[ nan, 8000, 24000, nan, 61.51, nan ],
[ nan, 9000, 27000, nan, 85.49, nan ],
[ nan, 10000, 100, nan, 0.02, nan ],
[ nan, 20000, 200, nan, 0.08, nan ],
[ nan, 30000, 300, nan, 0.19, nan ],
[ nan, 40000, 400, nan, 0.51, nan ],
[ nan, 50000, 500, nan, 0.79, nan ],
[ nan, 60000, 600, nan, 1.17, nan ],
[ nan, 70000, 700, nan, 1.62, nan ],
[ nan, 80000, 800, nan, 2.24, nan ],
[ nan, 90000, 900, nan, 3.36, nan ],
[ nan, 100000, 1000, nan, 4.18, nan ],
[ nan, 200000, 2000, nan, 24.15, nan ],
[ nan, 100, 10000, nan, 0.02, nan ],
[ nan, 200, 20000, nan, 0.09, nan ],
[ nan, 300, 30000, nan, 0.23, nan ],
[ nan, 400, 40000, nan, 0.45, nan ],
[ nan, 500, 50000, nan, 0.78, nan ],
[ nan, 600, 60000, nan, 1.28, nan ],
[ nan, 700, 70000, nan, 1.97, nan ],
[ nan, 800, 80000, nan, 2.87, nan ],
[ nan, 900, 90000, nan, 3.56, nan ],
[ nan, 1000, 100000, nan, 4.58, nan ],
[ nan, 2000, 200000, nan, 29.04, nan ],
])
# numactl --interleave=all ./testing_cgesdd -US -VS -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
cgesdd_US = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.02, nan ],
[ nan, 300, 300, nan, 0.05, nan ],
[ nan, 400, 400, nan, 0.08, nan ],
[ nan, 500, 500, nan, 0.12, nan ],
[ nan, 600, 600, nan, 0.16, nan ],
[ nan, 700, 700, nan, 0.21, nan ],
[ nan, 800, 800, nan, 0.27, nan ],
[ nan, 900, 900, nan, 0.34, nan ],
[ nan, 1000, 1000, nan, 0.42, nan ],
[ nan, 2000, 2000, nan, 1.72, nan ],
[ nan, 3000, 3000, nan, 4.21, nan ],
[ nan, 4000, 4000, nan, 8.28, nan ],
[ nan, 5000, 5000, nan, 14.75, nan ],
[ nan, 6000, 6000, nan, 21.63, nan ],
[ nan, 7000, 7000, nan, 31.80, nan ],
[ nan, 8000, 8000, nan, 44.88, nan ],
[ nan, 9000, 9000, nan, 60.96, nan ],
[ nan, 10000, 10000, nan, 80.32, nan ],
[ nan, 12000, 12000, nan, 133.62, nan ],
[ nan, 14000, 14000, nan, 203.80, nan ],
[ nan, 16000, 16000, nan, 301.93, nan ],
[ nan, 18000, 18000, nan, 418.26, nan ],
[ nan, 20000, 20000, nan, 577.48, nan ],
[ nan, 300, 100, nan, 0.01, nan ],
[ nan, 600, 200, nan, 0.03, nan ],
[ nan, 900, 300, nan, 0.06, nan ],
[ nan, 1200, 400, nan, 0.10, nan ],
[ nan, 1500, 500, nan, 0.16, nan ],
[ nan, 1800, 600, nan, 0.24, nan ],
[ nan, 2100, 700, nan, 0.34, nan ],
[ nan, 2400, 800, nan, 0.45, nan ],
[ nan, 2700, 900, nan, 0.60, nan ],
[ nan, 3000, 1000, nan, 0.75, nan ],
[ nan, 6000, 2000, nan, 3.62, nan ],
[ nan, 9000, 3000, nan, 8.22, nan ],
[ nan, 12000, 4000, nan, 17.26, nan ],
[ nan, 15000, 5000, nan, 32.23, nan ],
[ nan, 18000, 6000, nan, 50.46, nan ],
[ nan, 21000, 7000, nan, 76.61, nan ],
[ nan, 24000, 8000, nan, 110.93, nan ],
[ nan, 27000, 9000, nan, 153.92, nan ],
[ nan, 100, 300, nan, 0.01, nan ],
[ nan, 200, 600, nan, 0.03, nan ],
[ nan, 300, 900, nan, 0.06, nan ],
[ nan, 400, 1200, nan, 0.11, nan ],
[ nan, 500, 1500, nan, 0.16, nan ],
[ nan, 600, 1800, nan, 0.23, nan ],
[ nan, 700, 2100, nan, 0.32, nan ],
[ nan, 800, 2400, nan, 0.41, nan ],
[ nan, 900, 2700, nan, 0.52, nan ],
[ nan, 1000, 3000, nan, 0.65, nan ],
[ nan, 2000, 6000, nan, 3.06, nan ],
[ nan, 3000, 9000, nan, 8.40, nan ],
[ nan, 4000, 12000, nan, 17.64, nan ],
[ nan, 5000, 15000, nan, 31.56, nan ],
[ nan, 6000, 18000, nan, 51.43, nan ],
[ nan, 7000, 21000, nan, 80.42, nan ],
[ nan, 8000, 24000, nan, 116.60, nan ],
[ nan, 9000, 27000, nan, 159.90, nan ],
[ nan, 10000, 100, nan, 0.05, nan ],
[ nan, 20000, 200, nan, 0.18, nan ],
[ nan, 30000, 300, nan, 0.52, nan ],
[ nan, 40000, 400, nan, 1.30, nan ],
[ nan, 50000, 500, nan, 1.76, nan ],
[ nan, 60000, 600, nan, 2.13, nan ],
[ nan, 70000, 700, nan, 3.08, nan ],
[ nan, 80000, 800, nan, 4.29, nan ],
[ nan, 90000, 900, nan, 6.18, nan ],
[ nan, 100000, 1000, nan, 9.25, nan ],
[ nan, 200000, 2000, nan, 49.88, nan ],
[ nan, 100, 10000, nan, 0.04, nan ],
[ nan, 200, 20000, nan, 0.19, nan ],
[ nan, 300, 30000, nan, 0.48, nan ],
[ nan, 400, 40000, nan, 0.94, nan ],
[ nan, 500, 50000, nan, 1.62, nan ],
[ nan, 600, 60000, nan, 2.68, nan ],
[ nan, 700, 70000, nan, 4.05, nan ],
[ nan, 800, 80000, nan, 6.02, nan ],
[ nan, 900, 90000, nan, 7.48, nan ],
[ nan, 1000, 100000, nan, 9.54, nan ],
[ nan, 2000, 200000, nan, 58.30, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/cgetrf.txt
# numactl --interleave=all ./testing_cgetrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cgetrf = array([
[ 10, 10, nan, nan, 0.29, 0.00, nan ],
[ 20, 20, nan, nan, 0.77, 0.00, nan ],
[ 30, 30, nan, nan, 1.88, 0.00, nan ],
[ 40, 40, nan, nan, 3.53, 0.00, nan ],
[ 50, 50, nan, nan, 4.87, 0.00, nan ],
[ 60, 60, nan, nan, 5.66, 0.00, nan ],
[ 70, 70, nan, nan, 1.18, 0.00, nan ],
[ 80, 80, nan, nan, 1.77, 0.00, nan ],
[ 90, 90, nan, nan, 2.35, 0.00, nan ],
[ 100, 100, nan, nan, 3.09, 0.00, nan ],
[ 200, 200, nan, nan, 12.78, 0.00, nan ],
[ 300, 300, nan, nan, 28.80, 0.00, nan ],
[ 400, 400, nan, nan, 46.76, 0.00, nan ],
[ 500, 500, nan, nan, 68.58, 0.00, nan ],
[ 600, 600, nan, nan, 90.26, 0.01, nan ],
[ 700, 700, nan, nan, 115.63, 0.01, nan ],
[ 800, 800, nan, nan, 142.59, 0.01, nan ],
[ 900, 900, nan, nan, 168.11, 0.01, nan ],
[ 1000, 1000, nan, nan, 195.86, 0.01, nan ],
[ 2000, 2000, nan, nan, 498.64, 0.04, nan ],
[ 3000, 3000, nan, nan, 846.24, 0.09, nan ],
[ 4000, 4000, nan, nan, 1107.91, 0.15, nan ],
[ 5000, 5000, nan, nan, 1258.45, 0.26, nan ],
[ 6000, 6000, nan, nan, 1537.05, 0.37, nan ],
[ 7000, 7000, nan, nan, 1707.15, 0.54, nan ],
[ 8000, 8000, nan, nan, 1860.49, 0.73, nan ],
[ 9000, 9000, nan, nan, 1918.42, 1.01, nan ],
[ 10000, 10000, nan, nan, 2029.80, 1.31, nan ],
[ 12000, 12000, nan, nan, 2200.71, 2.09, nan ],
[ 14000, 14000, nan, nan, 2323.94, 3.15, nan ],
[ 16000, 16000, nan, nan, 2422.94, 4.51, nan ],
[ 18000, 18000, nan, nan, 2476.52, 6.28, nan ],
[ 20000, 20000, nan, nan, 2520.95, 8.46, nan ],
])
# numactl --interleave=all ./testing_cgetrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cgetrf_gpu = array([
[ 10, 10, nan, nan, 0.07, 0.00, nan ],
[ 20, 20, nan, nan, 0.39, 0.00, nan ],
[ 30, 30, nan, nan, 0.99, 0.00, nan ],
[ 40, 40, nan, nan, 2.12, 0.00, nan ],
[ 50, 50, nan, nan, 2.81, 0.00, nan ],
[ 60, 60, nan, nan, 3.82, 0.00, nan ],
[ 70, 70, nan, nan, 0.73, 0.00, nan ],
[ 80, 80, nan, nan, 0.93, 0.00, nan ],
[ 90, 90, nan, nan, 1.23, 0.00, nan ],
[ 100, 100, nan, nan, 1.95, 0.00, nan ],
[ 200, 200, nan, nan, 8.98, 0.00, nan ],
[ 300, 300, nan, nan, 23.12, 0.00, nan ],
[ 400, 400, nan, nan, 41.40, 0.00, nan ],
[ 500, 500, nan, nan, 67.82, 0.00, nan ],
[ 600, 600, nan, nan, 90.69, 0.01, nan ],
[ 700, 700, nan, nan, 116.90, 0.01, nan ],
[ 800, 800, nan, nan, 149.23, 0.01, nan ],
[ 900, 900, nan, nan, 181.15, 0.01, nan ],
[ 1000, 1000, nan, nan, 229.07, 0.01, nan ],
[ 2000, 2000, nan, nan, 590.46, 0.04, nan ],
[ 3000, 3000, nan, nan, 1028.34, 0.07, nan ],
[ 4000, 4000, nan, nan, 1328.21, 0.13, nan ],
[ 5000, 5000, nan, nan, 1458.62, 0.23, nan ],
[ 6000, 6000, nan, nan, 1688.65, 0.34, nan ],
[ 7000, 7000, nan, nan, 1900.68, 0.48, nan ],
[ 8000, 8000, nan, nan, 2107.74, 0.65, nan ],
[ 9000, 9000, nan, nan, 2129.66, 0.91, nan ],
[ 10000, 10000, nan, nan, 2228.35, 1.20, nan ],
[ 12000, 12000, nan, nan, 2443.86, 1.89, nan ],
[ 14000, 14000, nan, nan, 2583.52, 2.83, nan ],
[ 16000, 16000, nan, nan, 2643.80, 4.13, nan ],
[ 18000, 18000, nan, nan, 2683.00, 5.80, nan ],
[ 20000, 20000, nan, nan, 2724.53, 7.83, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/cheevd.txt
# numactl --interleave=all ./testing_cheevd -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cheevd_JN = array([
[ 10, nan, 0.0000 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0001 ],
[ 40, nan, 0.0001 ],
[ 50, nan, 0.0002 ],
[ 60, nan, 0.0003 ],
[ 70, nan, 0.0005 ],
[ 80, nan, 0.0007 ],
[ 90, nan, 0.0009 ],
[ 100, nan, 0.0011 ],
[ 200, nan, 0.0108 ],
[ 300, nan, 0.0203 ],
[ 400, nan, 0.0351 ],
[ 500, nan, 0.0492 ],
[ 600, nan, 0.0680 ],
[ 700, nan, 0.0878 ],
[ 800, nan, 0.1119 ],
[ 900, nan, 0.1375 ],
[ 1000, nan, 0.1640 ],
[ 2000, nan, 0.5694 ],
[ 3000, nan, 1.2952 ],
[ 4000, nan, 2.3348 ],
[ 5000, nan, 3.7632 ],
[ 6000, nan, 5.6444 ],
[ 7000, nan, 8.1125 ],
[ 8000, nan, 11.0722 ],
[ 9000, nan, 14.8193 ],
[ 10000, nan, 19.3837 ],
[ 12000, nan, 31.0675 ],
[ 14000, nan, 45.9363 ],
[ 16000, nan, 65.4731 ],
[ 18000, nan, 90.3068 ],
[ 20000, nan, 119.1788 ],
])
# numactl --interleave=all ./testing_cheevd -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cheevd_JV = array([
[ 10, nan, 0.0002 ],
[ 20, nan, 0.0002 ],
[ 30, nan, 0.0003 ],
[ 40, nan, 0.0005 ],
[ 50, nan, 0.0006 ],
[ 60, nan, 0.0008 ],
[ 70, nan, 0.0011 ],
[ 80, nan, 0.0014 ],
[ 90, nan, 0.0017 ],
[ 100, nan, 0.0021 ],
[ 200, nan, 0.0176 ],
[ 300, nan, 0.0302 ],
[ 400, nan, 0.0499 ],
[ 500, nan, 0.0678 ],
[ 600, nan, 0.0891 ],
[ 700, nan, 0.1137 ],
[ 800, nan, 0.1438 ],
[ 900, nan, 0.1778 ],
[ 1000, nan, 0.2086 ],
[ 2000, nan, 0.7005 ],
[ 3000, nan, 1.4685 ],
[ 4000, nan, 2.6798 ],
[ 5000, nan, 4.3095 ],
[ 6000, nan, 6.5492 ],
[ 7000, nan, 9.4248 ],
[ 8000, nan, 12.9559 ],
[ 9000, nan, 17.4774 ],
[ 10000, nan, 22.7936 ],
[ 12000, nan, 36.9305 ],
[ 14000, nan, 54.6267 ],
[ 16000, nan, 78.2375 ],
[ 18000, nan, 109.1700 ],
[ 20000, nan, 144.4371 ],
])
# numactl --interleave=all ./testing_cheevd_gpu -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cheevd_gpu_JN = array([
[ 10, nan, 0.0001 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0001 ],
[ 40, nan, 0.0002 ],
[ 50, nan, 0.0003 ],
[ 60, nan, 0.0004 ],
[ 70, nan, 0.0007 ],
[ 80, nan, 0.0009 ],
[ 90, nan, 0.0012 ],
[ 100, nan, 0.0014 ],
[ 200, nan, 0.0124 ],
[ 300, nan, 0.0235 ],
[ 400, nan, 0.0395 ],
[ 500, nan, 0.0542 ],
[ 600, nan, 0.0755 ],
[ 700, nan, 0.0957 ],
[ 800, nan, 0.1225 ],
[ 900, nan, 0.1491 ],
[ 1000, nan, 0.1775 ],
[ 2000, nan, 0.6002 ],
[ 3000, nan, 1.3481 ],
[ 4000, nan, 2.3962 ],
[ 5000, nan, 3.8576 ],
[ 6000, nan, 5.7451 ],
[ 7000, nan, 8.2436 ],
[ 8000, nan, 11.2046 ],
[ 9000, nan, 14.9632 ],
[ 10000, nan, 19.5209 ],
[ 12000, nan, 31.2815 ],
[ 14000, nan, 46.2188 ],
[ 16000, nan, 65.6012 ],
[ 18000, nan, 90.6014 ],
[ 20000, nan, 119.1913 ],
])
# numactl --interleave=all ./testing_cheevd_gpu -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cheevd_gpu_JV = array([
[ 10, nan, 0.0002 ],
[ 20, nan, 0.0002 ],
[ 30, nan, 0.0004 ],
[ 40, nan, 0.0005 ],
[ 50, nan, 0.0006 ],
[ 60, nan, 0.0009 ],
[ 70, nan, 0.0012 ],
[ 80, nan, 0.0014 ],
[ 90, nan, 0.0018 ],
[ 100, nan, 0.0021 ],
[ 200, nan, 0.0170 ],
[ 300, nan, 0.0293 ],
[ 400, nan, 0.0490 ],
[ 500, nan, 0.0665 ],
[ 600, nan, 0.0878 ],
[ 700, nan, 0.1103 ],
[ 800, nan, 0.1409 ],
[ 900, nan, 0.1734 ],
[ 1000, nan, 0.2023 ],
[ 2000, nan, 0.6659 ],
[ 3000, nan, 1.5009 ],
[ 4000, nan, 2.7090 ],
[ 5000, nan, 4.4119 ],
[ 6000, nan, 6.5324 ],
[ 7000, nan, 9.3413 ],
[ 8000, nan, 13.0797 ],
[ 9000, nan, 17.3712 ],
[ 10000, nan, 22.8849 ],
[ 12000, nan, 36.9572 ],
[ 14000, nan, 55.3174 ],
[ 16000, nan, 79.6378 ],
[ 18000, nan, 110.6351 ],
[ 20000, nan, 148.1050 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/cheevd_2stage.txt
# numactl --interleave=all ./testing_cheevdx_2stage -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cheevdx_2stage_JN = array([
[ 10, 0, 0.0002 ],
[ 20, 0, 0.0000 ],
[ 30, 0, 0.0000 ],
[ 40, 0, 0.0000 ],
[ 50, 0, 0.0000 ],
[ 60, 0, 0.0000 ],
[ 70, 0, 0.0000 ],
[ 80, 0, 0.0000 ],
[ 90, 0, 0.0000 ],
[ 100, 0, 0.0000 ],
[ 200, 200, 0.0055 ],
[ 300, 300, 0.0266 ],
[ 400, 400, 0.0508 ],
[ 500, 500, 0.0796 ],
[ 600, 600, 0.1112 ],
[ 700, 700, 0.1462 ],
[ 800, 800, 0.2094 ],
[ 900, 900, 0.3014 ],
[ 1000, 1000, 0.2985 ],
[ 2000, 2000, 0.6633 ],
[ 3000, 3000, 0.9995 ],
[ 4000, 4000, 1.4907 ],
[ 5000, 5000, 2.1478 ],
[ 6000, 6000, 2.7970 ],
[ 7000, 7000, 3.8473 ],
[ 8000, 8000, 4.6921 ],
[ 9000, 9000, 5.8242 ],
[ 10000, 10000, 7.1964 ],
[ 12000, 12000, 10.4989 ],
[ 14000, 14000, 14.6472 ],
[ 16000, 16000, 19.7530 ],
[ 18000, 18000, 26.0466 ],
[ 20000, 20000, 33.7255 ],
])
# numactl --interleave=all ./testing_cheevdx_2stage -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cheevdx_2stage_JV = array([
[ 10, 10, 0.0002 ],
[ 20, 20, 0.0002 ],
[ 30, 30, 0.0003 ],
[ 40, 40, 0.0004 ],
[ 50, 50, 0.0006 ],
[ 60, 60, 0.0008 ],
[ 70, 70, 0.0011 ],
[ 80, 80, 0.0014 ],
[ 90, 90, 0.0016 ],
[ 100, 100, 0.0020 ],
[ 200, 200, 0.0070 ],
[ 300, 300, 0.0463 ],
[ 400, 400, 0.0736 ],
[ 500, 500, 0.1048 ],
[ 600, 600, 0.1428 ],
[ 700, 700, 0.1758 ],
[ 800, 800, 0.2165 ],
[ 900, 900, 0.2532 ],
[ 1000, 1000, 0.2743 ],
[ 2000, 2000, 0.7273 ],
[ 3000, 3000, 1.4106 ],
[ 4000, 4000, 2.2832 ],
[ 5000, 5000, 3.5171 ],
[ 6000, 6000, 5.0641 ],
[ 7000, 7000, 7.9562 ],
[ 8000, 8000, 11.0187 ],
[ 9000, 9000, 14.1723 ],
[ 10000, 10000, 17.0228 ],
[ 12000, 12000, 29.7981 ],
[ 14000, 14000, 48.8108 ],
[ 16000, 16000, 60.3565 ],
[ 18000, 18000, 93.0945 ],
[ 20000, 20000, 110.9726 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/chemv.txt
# numactl --interleave=all ./testing_chemv -N 100 -N 1000 --range 10:90:1 --range 100:900:10 --range 1000:9000:100 --range 10000:20000:2000
chemv_L = array([
[ 10, 0.0249, 0.0370, 0.0341, 0.0269, 0.0402, 0.0229, 0.4823, 0.0019, 1.43e-07, 1.92e-07, 1.43e-07, nan ],
[ 11, 0.0332, 0.0331, 0.0439, 0.0250, 0.0501, 0.0219, 0.5767, 0.0019, 2.45e-07, 3.13e-07, 2.45e-07, nan ],
[ 12, 0.0391, 0.0331, 0.0518, 0.0250, 0.0591, 0.0219, 0.6795, 0.0019, 2.87e-07, 1.59e-07, 2.51e-07, nan ],
[ 13, 0.0445, 0.0339, 0.0580, 0.0260, 0.0688, 0.0219, 0.7028, 0.0021, 1.73e-07, 1.64e-07, 1.47e-07, nan ],
[ 14, 0.0528, 0.0329, 0.0668, 0.0260, 0.0783, 0.0222, 0.9102, 0.0019, 1.52e-07, 1.52e-07, 2.04e-07, nan ],
[ 15, 0.0581, 0.0341, 0.0762, 0.0260, 0.0933, 0.0212, 1.0381, 0.0019, 2.17e-07, 1.91e-07, 2.29e-07, nan ],
[ 16, 0.0622, 0.0360, 0.0862, 0.0260, 0.1010, 0.0222, 1.1744, 0.0019, 1.69e-07, 2.46e-07, 1.69e-07, nan ],
[ 17, 0.0738, 0.0341, 0.0934, 0.0269, 0.1055, 0.0238, 0.8794, 0.0029, 1.16e-07, 1.68e-07, 1.25e-07, nan ],
[ 18, 0.0760, 0.0370, 0.1033, 0.0272, 0.1178, 0.0238, 0.9815, 0.0029, 2.18e-07, 3.35e-07, 2.12e-07, nan ],
[ 19, 0.0920, 0.0339, 0.1157, 0.0269, 0.1294, 0.0241, 1.0891, 0.0029, 2.07e-07, 2.07e-07, 2.01e-07, nan ],
[ 20, 0.0931, 0.0370, 0.1277, 0.0269, 0.1374, 0.0250, 1.6032, 0.0021, 1.91e-07, 1.91e-07, 2.13e-07, nan ],
[ 21, 0.1079, 0.0350, 0.1403, 0.0269, 0.1510, 0.0250, 1.7616, 0.0021, 3.27e-07, 2.72e-07, 2.03e-07, nan ],
[ 22, 0.1213, 0.0341, 0.1470, 0.0281, 0.1735, 0.0238, 1.3344, 0.0031, 2.74e-07, 2.60e-07, 1.94e-07, nan ],
[ 23, 0.1286, 0.0350, 0.1673, 0.0269, 0.1801, 0.0250, 1.4545, 0.0031, 1.96e-07, 2.07e-07, 2.23e-07, nan ],
[ 24, 0.1446, 0.0339, 0.1755, 0.0279, 0.1956, 0.0250, 2.5669, 0.0019, 2.51e-07, 2.51e-07, 2.51e-07, nan ],
[ 25, 0.1472, 0.0360, 0.1967, 0.0269, 0.2117, 0.0250, 1.7100, 0.0031, 2.41e-07, 2.56e-07, 1.71e-07, nan ],
[ 26, 0.1589, 0.0360, 0.2051, 0.0279, 0.2285, 0.0250, 1.8455, 0.0031, 2.20e-07, 1.64e-07, 2.20e-07, nan ],
[ 27, 0.1666, 0.0370, 0.2207, 0.0279, 0.2369, 0.0260, 1.9862, 0.0031, 1.58e-07, 1.58e-07, 1.58e-07, nan ],
[ 28, 0.1885, 0.0350, 0.2349, 0.0281, 0.2543, 0.0260, 2.1320, 0.0031, 3.41e-07, 2.81e-07, 3.41e-07, nan ],
[ 29, 0.1902, 0.0372, 0.2515, 0.0281, 0.2603, 0.0272, 1.7458, 0.0041, 2.10e-07, 1.47e-07, 2.25e-07, nan ],
[ 30, 0.2157, 0.0350, 0.2599, 0.0291, 0.3020, 0.0250, 1.8652, 0.0041, 3.18e-07, 2.01e-07, 1.59e-07, nan ],
[ 31, 0.2381, 0.0339, 0.2889, 0.0279, 0.3220, 0.0250, 1.9886, 0.0041, 1.74e-07, 2.48e-07, 2.63e-07, nan ],
[ 32, 0.2382, 0.0360, 0.2973, 0.0288, 0.3426, 0.0250, 2.7670, 0.0031, 1.88e-07, 1.69e-07, 2.67e-07, nan ],
[ 33, 0.2530, 0.0360, 0.2690, 0.0339, 0.3237, 0.0281, 1.1236, 0.0081, 2.38e-07, 1.73e-07, 2.31e-07, nan ],
[ 34, 0.2774, 0.0348, 0.2832, 0.0341, 0.3553, 0.0272, 2.3824, 0.0041, 2.65e-07, 1.91e-07, 2.80e-07, nan ],
[ 35, 0.2696, 0.0379, 0.3106, 0.0329, 0.3793, 0.0269, 3.5721, 0.0029, 1.96e-07, 2.18e-07, 1.74e-07, nan ],
[ 36, 0.3168, 0.0341, 0.3282, 0.0329, 0.4156, 0.0260, 2.6646, 0.0041, 2.28e-07, 1.91e-07, 3.22e-07, nan ],
[ 37, 0.3165, 0.0360, 0.3567, 0.0319, 0.4385, 0.0260, 2.9874, 0.0038, 2.58e-07, 3.10e-07, 2.43e-07, nan ],
[ 38, 0.3522, 0.0341, 0.3759, 0.0319, 0.4621, 0.0260, 2.9627, 0.0041, 3.05e-07, 3.02e-07, 1.81e-07, nan ],
[ 39, 0.3813, 0.0331, 0.3841, 0.0329, 0.5048, 0.0250, 3.1176, 0.0041, 2.19e-07, 2.94e-07, 3.28e-07, nan ],
[ 40, 0.3923, 0.0339, 0.4007, 0.0331, 0.5110, 0.0260, 3.2765, 0.0041, 2.90e-07, 2.86e-07, 3.02e-07, nan ],
[ 41, 0.4118, 0.0339, 0.4363, 0.0319, 0.5129, 0.0272, 3.4393, 0.0041, 2.08e-07, 1.95e-07, 2.08e-07, nan ],
[ 42, 0.4442, 0.0329, 0.4575, 0.0319, 0.5624, 0.0260, 2.9192, 0.0050, 2.95e-07, 2.76e-07, 3.05e-07, nan ],
[ 43, 0.4653, 0.0329, 0.4792, 0.0319, 0.5890, 0.0260, 3.0574, 0.0050, 3.20e-07, 3.76e-07, 3.20e-07, nan ],
[ 44, 0.4570, 0.0350, 0.4976, 0.0322, 0.6398, 0.0250, 3.1989, 0.0050, 2.91e-07, 3.13e-07, 2.74e-07, nan ],
[ 45, 0.4945, 0.0339, 0.5088, 0.0329, 0.6442, 0.0260, 3.3435, 0.0050, 2.68e-07, 2.40e-07, 2.68e-07, nan ],
[ 46, 0.5127, 0.0341, 0.5471, 0.0319, 0.6983, 0.0250, 3.4913, 0.0050, 2.78e-07, 3.42e-07, 2.99e-07, nan ],
[ 47, 0.5349, 0.0341, 0.5543, 0.0329, 0.7285, 0.0250, 3.6423, 0.0050, 2.03e-07, 2.47e-07, 1.81e-07, nan ],
[ 48, 0.5144, 0.0370, 0.5575, 0.0341, 0.7055, 0.0269, 4.6897, 0.0041, 2.46e-07, 3.28e-07, 2.42e-07, nan ],
[ 49, 0.5806, 0.0341, 0.5847, 0.0339, 0.6806, 0.0291, 3.9538, 0.0050, 3.11e-07, 3.97e-07, 3.21e-07, nan ],
[ 50, 0.5574, 0.0370, 0.5878, 0.0350, 0.7141, 0.0288, 3.4561, 0.0060, 3.15e-07, 3.41e-07, 3.41e-07, nan ],
[ 51, 0.6112, 0.0350, 0.6283, 0.0341, 0.7364, 0.0291, 3.5937, 0.0060, 2.70e-07, 3.35e-07, 2.70e-07, nan ],
[ 52, 0.6022, 0.0370, 0.6350, 0.0350, 0.7978, 0.0279, 4.4452, 0.0050, 3.67e-07, 3.02e-07, 3.02e-07, nan ],
[ 53, 0.6213, 0.0372, 0.6593, 0.0350, 0.8010, 0.0288, 4.6153, 0.0050, 2.52e-07, 2.88e-07, 2.16e-07, nan ],
[ 54, 0.6660, 0.0360, 0.6841, 0.0350, 0.8522, 0.0281, 4.7887, 0.0050, 3.00e-07, 2.23e-07, 2.23e-07, nan ],
[ 55, 0.6905, 0.0360, 0.7292, 0.0341, 0.8617, 0.0288, 3.5955, 0.0069, 3.10e-07, 2.22e-07, 2.19e-07, nan ],
[ 56, 0.7350, 0.0350, 0.7556, 0.0341, 0.8929, 0.0288, 4.1556, 0.0062, 2.46e-07, 2.72e-07, 2.15e-07, nan ],
[ 57, 0.7824, 0.0341, 0.7824, 0.0341, 0.9171, 0.0291, 5.3280, 0.0050, 3.35e-07, 2.99e-07, 2.99e-07, nan ],
[ 58, 0.7471, 0.0370, 0.7931, 0.0348, 0.9492, 0.0291, 3.1296, 0.0088, 2.79e-07, 4.00e-07, 3.54e-07, nan ],
[ 59, 0.7727, 0.0370, 0.8148, 0.0350, 0.9506, 0.0300, 4.6066, 0.0062, 3.23e-07, 2.74e-07, 2.74e-07, nan ],
[ 60, 0.8423, 0.0350, 0.8423, 0.0350, 0.9905, 0.0298, 5.8960, 0.0050, 2.62e-07, 2.62e-07, 2.01e-07, nan ],
[ 61, 0.8702, 0.0350, 0.8472, 0.0360, 1.0234, 0.0298, 4.4113, 0.0069, 3.54e-07, 3.13e-07, 3.96e-07, nan ],
[ 62, 0.8523, 0.0370, 0.8749, 0.0360, 1.0568, 0.0298, 5.2842, 0.0060, 3.08e-07, 2.54e-07, 2.54e-07, nan ],
[ 63, 0.9275, 0.0350, 0.7747, 0.0420, 1.1176, 0.0291, 4.7017, 0.0069, 2.57e-07, 2.18e-07, 2.44e-07, nan ],
[ 64, 0.9075, 0.0370, 0.9569, 0.0350, 1.1530, 0.0291, 6.6981, 0.0050, 3.63e-07, 3.63e-07, 3.58e-07, nan ],
[ 65, 0.7840, 0.0441, 0.9297, 0.0372, 1.1157, 0.0310, 5.8016, 0.0060, 3.63e-07, 3.71e-07, 2.62e-07, nan ],
[ 66, 0.8305, 0.0429, 0.9900, 0.0360, 1.1156, 0.0319, 4.3966, 0.0081, 2.89e-07, 3.57e-07, 3.52e-07, nan ],
[ 67, 0.8953, 0.0410, 1.0476, 0.0350, 1.1159, 0.0329, 5.1333, 0.0072, 2.85e-07, 3.46e-07, 3.60e-07, nan ],
[ 68, 0.8810, 0.0429, 1.0502, 0.0360, 1.1834, 0.0319, 6.0992, 0.0062, 4.05e-07, 2.80e-07, 3.37e-07, nan ],
[ 69, 0.8823, 0.0441, 1.0463, 0.0372, 1.2556, 0.0310, 5.4409, 0.0072, 3.50e-07, 2.47e-07, 3.36e-07, nan ],
[ 70, 0.9542, 0.0420, 1.1122, 0.0360, 1.2918, 0.0310, 4.9394, 0.0081, 3.93e-07, 2.72e-07, 2.72e-07, nan ],
[ 71, 1.0281, 0.0401, 1.1750, 0.0350, 1.3185, 0.0312, 5.9559, 0.0069, 5.40e-07, 5.37e-07, 4.33e-07, nan ],
[ 72, 1.0570, 0.0401, 1.2417, 0.0341, 1.4093, 0.0300, 5.3809, 0.0079, 2.69e-07, 3.33e-07, 2.65e-07, nan ],
[ 73, 1.0927, 0.0398, 1.2085, 0.0360, 1.4483, 0.0300, 6.2926, 0.0069, 3.51e-07, 4.31e-07, 3.30e-07, nan ],
[ 74, 1.1159, 0.0401, 1.2753, 0.0350, 1.4421, 0.0310, 6.2490, 0.0072, 2.58e-07, 3.26e-07, 3.14e-07, nan ],
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[ 2900, 140.2577, 0.4799, 211.8070, 0.3178, 52.3043, 1.2870, 18.2225, 3.6941, 2.95e-06, 2.53e-06, 2.78e-06, nan ],
[ 3000, 143.5349, 0.5019, 217.0552, 0.3319, 53.8384, 1.3380, 17.4759, 4.1220, 3.20e-06, 2.67e-06, 3.06e-06, nan ],
[ 3100, 149.6355, 0.5140, 221.5756, 0.3471, 42.9980, 1.7889, 16.9868, 4.5280, 2.46e-06, 2.55e-06, 2.72e-06, nan ],
[ 3200, 152.9175, 0.5360, 237.5663, 0.3450, 45.1067, 1.8170, 17.6332, 4.6480, 2.75e-06, 2.92e-06, 2.90e-06, nan ],
[ 3300, 159.0835, 0.5479, 234.3422, 0.3719, 46.3867, 1.8790, 17.6973, 4.9250, 3.11e-06, 2.96e-06, 3.03e-06, nan ],
[ 3400, 162.5724, 0.5691, 239.1007, 0.3870, 47.2783, 1.9569, 17.7895, 5.2009, 2.59e-06, 2.88e-06, 2.86e-06, nan ],
[ 3500, 166.4850, 0.5889, 251.3557, 0.3901, 48.8035, 2.0089, 17.8256, 5.5001, 3.18e-06, 3.71e-06, 3.01e-06, nan ],
[ 3600, 171.6838, 0.6042, 250.0268, 0.4148, 49.9652, 2.0759, 16.5266, 6.2761, 3.40e-06, 3.27e-06, 3.22e-06, nan ],
[ 3700, 173.6103, 0.6311, 256.5865, 0.4270, 50.9136, 2.1520, 17.8098, 6.1519, 3.51e-06, 3.65e-06, 4.09e-06, nan ],
[ 3800, 176.7106, 0.6540, 258.5159, 0.4470, 52.3170, 2.2089, 17.8395, 6.4781, 2.91e-06, 3.01e-06, 2.65e-06, nan ],
[ 3900, 178.5172, 0.6819, 256.8205, 0.4740, 53.4561, 2.2771, 17.9087, 6.7971, 3.17e-06, 2.72e-06, 2.75e-06, nan ],
[ 4000, 178.7857, 0.7162, 263.0128, 0.4869, 54.9097, 2.3320, 17.4811, 7.3249, 4.09e-06, 3.94e-06, 3.94e-06, nan ],
[ 4100, 176.3301, 0.7629, 265.9078, 0.5059, 46.2316, 2.9099, 17.8896, 7.5200, 3.14e-06, 3.31e-06, 3.24e-06, nan ],
[ 4200, 177.5980, 0.7949, 261.8804, 0.5391, 47.2291, 2.9891, 17.8315, 7.9169, 3.37e-06, 3.49e-06, 3.26e-06, nan ],
[ 4300, 179.7908, 0.8230, 261.8725, 0.5651, 48.7693, 3.0341, 17.9645, 8.2369, 3.20e-06, 3.37e-06, 2.99e-06, nan ],
[ 4400, 181.6197, 0.8531, 259.9341, 0.5960, 49.3721, 3.1381, 17.9136, 8.6489, 3.44e-06, 3.55e-06, 3.22e-06, nan ],
[ 4500, 182.5198, 0.8879, 256.0089, 0.6330, 50.3559, 3.2182, 17.9740, 9.0160, 3.62e-06, 3.52e-06, 3.49e-06, nan ],
[ 4600, 187.8951, 0.9012, 255.0245, 0.6640, 51.4222, 3.2930, 16.7958, 10.0820, 3.91e-06, 3.50e-06, 3.45e-06, nan ],
[ 4700, 186.2482, 0.9491, 258.0766, 0.6850, 52.1783, 3.3879, 17.8059, 9.9280, 3.99e-06, 4.17e-06, 4.09e-06, nan ],
[ 4800, 187.3845, 0.9840, 261.1738, 0.7060, 52.8596, 3.4881, 17.8538, 10.3271, 4.05e-06, 3.51e-06, 3.61e-06, nan ],
[ 4900, 187.6341, 1.0240, 262.0776, 0.7331, 54.1701, 3.5470, 17.9653, 10.6950, 3.57e-06, 3.64e-06, 3.62e-06, nan ],
[ 5000, 188.0575, 1.0638, 260.8369, 0.7670, 55.0202, 3.6361, 17.6018, 11.3659, 4.27e-06, 4.90e-06, 4.33e-06, nan ],
[ 5100, 190.7796, 1.0910, 265.1906, 0.7849, 55.9083, 3.7229, 17.7961, 11.6959, 4.20e-06, 4.50e-06, 4.68e-06, nan ],
[ 5200, 191.3098, 1.1311, 265.5277, 0.8149, 49.0315, 4.4131, 17.5096, 12.3580, 3.88e-06, 3.88e-06, 3.79e-06, nan ],
[ 5300, 193.1198, 1.1640, 261.6738, 0.8590, 49.6086, 4.5311, 17.7260, 12.6810, 3.67e-06, 3.55e-06, 3.63e-06, nan ],
[ 5400, 193.8057, 1.2040, 266.6809, 0.8750, 49.8710, 4.6790, 17.5779, 13.2749, 4.65e-06, 4.40e-06, 4.29e-06, nan ],
[ 5500, 195.7013, 1.2369, 261.4054, 0.9260, 51.2622, 4.7221, 17.8464, 13.5639, 3.96e-06, 3.73e-06, 4.32e-06, nan ],
[ 5600, 198.2201, 1.2660, 267.2801, 0.9389, 52.4674, 4.7829, 17.8993, 14.0200, 4.03e-06, 4.28e-06, 4.32e-06, nan ],
[ 5700, 198.1593, 1.3120, 266.3582, 0.9761, 52.4592, 4.9560, 17.8283, 14.5829, 4.19e-06, 4.61e-06, 4.21e-06, nan ],
[ 5800, 199.9757, 1.3461, 266.5399, 1.0099, 53.9447, 4.9901, 17.6958, 15.2121, 4.50e-06, 4.40e-06, 4.13e-06, nan ],
[ 5900, 201.5399, 1.3821, 270.6966, 1.0290, 54.4142, 5.1191, 18.0278, 15.4512, 4.33e-06, 4.35e-06, 4.11e-06, nan ],
[ 6000, 202.2872, 1.4241, 267.4920, 1.0769, 55.4299, 5.1970, 17.4453, 16.5129, 4.16e-06, 4.41e-06, 3.83e-06, nan ],
[ 6100, 203.9300, 1.4601, 271.1393, 1.0982, 55.4880, 5.3661, 12.1920, 24.4219, 4.37e-06, 4.55e-06, 4.55e-06, nan ],
[ 6200, 205.7647, 1.4949, 269.1165, 1.1430, 50.0075, 6.1510, 17.7410, 17.3380, 3.80e-06, 3.64e-06, 3.88e-06, nan ],
[ 6300, 207.9770, 1.5271, 273.3058, 1.1621, 50.4027, 6.3012, 17.9433, 17.7000, 4.89e-06, 4.27e-06, 4.75e-06, nan ],
[ 6400, 207.1597, 1.5821, 276.6019, 1.1849, 51.1159, 6.4120, 19.5419, 16.7720, 4.76e-06, 4.43e-06, 4.15e-06, nan ],
[ 6500, 210.6361, 1.6050, 275.0731, 1.2290, 51.2543, 6.5961, 17.9972, 18.7850, 4.80e-06, 4.15e-06, 4.97e-06, nan ],
[ 6600, 213.3007, 1.6341, 278.1513, 1.2531, 52.4471, 6.6459, 17.8065, 19.5749, 4.36e-06, 4.63e-06, 4.43e-06, nan ],
[ 6700, 215.7210, 1.6651, 276.1356, 1.3008, 52.5532, 6.8350, 18.0312, 19.9211, 5.18e-06, 4.38e-06, 4.88e-06, nan ],
[ 6800, 212.6472, 1.7400, 279.2190, 1.3251, 54.3725, 6.8049, 17.7844, 20.8049, 4.36e-06, 3.81e-06, 4.20e-06, nan ],
[ 6900, 216.0749, 1.7631, 279.5441, 1.3628, 54.5238, 6.9871, 18.0253, 21.1349, 4.06e-06, 3.64e-06, 3.62e-06, nan ],
[ 7000, 216.3557, 1.8122, 281.0664, 1.3950, 54.6461, 7.1750, 18.0020, 21.7800, 4.19e-06, 4.06e-06, 3.99e-06, nan ],
[ 7100, 217.9078, 1.8511, 280.1053, 1.4400, 55.3756, 7.2842, 18.0153, 22.3901, 4.30e-06, 4.02e-06, 3.69e-06, nan ],
[ 7200, 220.7619, 1.8790, 282.5766, 1.4679, 49.8317, 8.3241, 17.6723, 23.4721, 4.07e-06, 4.35e-06, 4.07e-06, nan ],
[ 7300, 221.2648, 1.9271, 284.6543, 1.4980, 50.9873, 8.3630, 17.6099, 24.2140, 4.46e-06, 4.42e-06, 4.55e-06, nan ],
[ 7400, 223.5510, 1.9600, 285.9964, 1.5321, 52.0937, 8.4112, 17.6042, 24.8899, 4.27e-06, 4.18e-06, 4.23e-06, nan ],
[ 7500, 224.7130, 2.0030, 283.6259, 1.5869, 52.4641, 8.5790, 17.8679, 25.1899, 4.63e-06, 4.19e-06, 4.17e-06, nan ],
[ 7600, 227.3351, 2.0330, 284.4441, 1.6248, 53.0496, 8.7121, 17.2903, 26.7301, 3.98e-06, 3.88e-06, 4.23e-06, nan ],
[ 7700, 225.0430, 2.1081, 284.0991, 1.6699, 53.3466, 8.8930, 16.4898, 28.7700, 5.22e-06, 4.58e-06, 4.81e-06, nan ],
[ 7800, 225.4936, 2.1589, 284.3398, 1.7121, 54.0128, 9.0129, 17.4372, 27.9181, 4.48e-06, 5.09e-06, 4.66e-06, nan ],
[ 7900, 224.4460, 2.2249, 284.5442, 1.7550, 54.6190, 9.1429, 17.7423, 28.1460, 4.67e-06, 4.82e-06, 4.79e-06, nan ],
[ 8000, 224.3926, 2.2821, 281.0634, 1.8220, 54.6480, 9.3708, 17.8474, 28.6930, 4.53e-06, 4.92e-06, 5.01e-06, nan ],
[ 8100, 226.3015, 2.3198, 282.6953, 1.8570, 55.6995, 9.4252, 17.3214, 30.3080, 5.05e-06, 5.03e-06, 4.90e-06, nan ],
[ 8200, 226.5448, 2.3749, 284.6383, 1.8902, 50.1971, 10.7181, 16.4481, 32.7101, 5.15e-06, 5.52e-06, 5.19e-06, nan ],
[ 8300, 228.3440, 2.4140, 289.2147, 1.9059, 51.1568, 10.7751, 17.3667, 31.7400, 6.48e-06, 6.03e-06, 5.72e-06, nan ],
[ 8400, 225.5690, 2.5029, 289.2419, 1.9519, 51.7963, 10.9000, 16.9876, 33.2348, 4.66e-06, 4.62e-06, 4.80e-06, nan ],
[ 8500, 229.2244, 2.5220, 285.1959, 2.0270, 52.0676, 11.1029, 17.7638, 32.5439, 5.47e-06, 5.63e-06, 5.71e-06, nan ],
[ 8600, 227.8636, 2.5971, 280.5922, 2.1091, 53.0707, 11.1508, 16.6306, 35.5840, 5.47e-06, 5.26e-06, 5.22e-06, nan ],
[ 8700, 226.9835, 2.6681, 286.6042, 2.1131, 53.2141, 11.3809, 17.4280, 34.7500, 5.47e-06, 5.42e-06, 5.36e-06, nan ],
[ 8800, 225.8144, 2.7440, 282.8271, 2.1908, 53.2790, 11.6298, 17.8602, 34.6930, 5.95e-06, 5.68e-06, 5.61e-06, nan ],
[ 8900, 227.5742, 2.7850, 285.7459, 2.2180, 54.3607, 11.6589, 17.9127, 35.3820, 5.69e-06, 5.32e-06, 5.26e-06, nan ],
[ 9000, 227.8212, 2.8448, 283.7835, 2.2838, 54.6415, 11.8611, 17.5939, 36.8371, 5.18e-06, 5.31e-06, 5.75e-06, nan ],
[ 10000, 233.8802, 3.4211, 286.8821, 2.7890, 54.8743, 14.5810, 17.3314, 46.1659, 5.70e-06, 5.45e-06, 4.74e-06, nan ],
[ 12000, 238.6863, 4.8270, 290.7957, 3.9620, 54.5318, 21.1279, 17.3796, 66.2930, 6.72e-06, 6.68e-06, 6.35e-06, nan ],
[ 14000, 248.3621, 6.3140, 295.9981, 5.2979, 54.5143, 28.7662, 16.9389, 92.5779, 7.49e-06, 8.12e-06, 7.90e-06, nan ],
[ 16000, 252.4609, 8.1129, 293.8110, 6.9711, 54.6419, 37.4839, 15.6665, 130.7368, 6.96e-06, 6.64e-06, 6.96e-06, nan ],
[ 18000, 252.7499, 10.2561, 295.5780, 8.7700, 54.9235, 47.1969, 16.5584, 156.5499, 7.60e-06, 7.60e-06, 8.15e-06, nan ],
[ 20000, 261.2656, 12.2490, 294.5724, 10.8640, 54.0089, 59.2539, 17.2832, 185.1649, 9.59e-06, 9.18e-06, 9.22e-06, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/cpotrf.txt
# numactl --interleave=all ./testing_cpotrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cpotrf = array([
[ 10, nan, nan, 0.01, 0.00, nan ],
[ 20, nan, nan, 0.04, 0.00, nan ],
[ 30, nan, nan, 0.13, 0.00, nan ],
[ 40, nan, nan, 1.80, 0.00, nan ],
[ 50, nan, nan, 2.35, 0.00, nan ],
[ 60, nan, nan, 3.47, 0.00, nan ],
[ 70, nan, nan, 4.50, 0.00, nan ],
[ 80, nan, nan, 5.09, 0.00, nan ],
[ 90, nan, nan, 2.37, 0.00, nan ],
[ 100, nan, nan, 2.98, 0.00, nan ],
[ 200, nan, nan, 18.16, 0.00, nan ],
[ 300, nan, nan, 18.41, 0.00, nan ],
[ 400, nan, nan, 35.80, 0.00, nan ],
[ 500, nan, nan, 59.64, 0.00, nan ],
[ 600, nan, nan, 58.65, 0.00, nan ],
[ 700, nan, nan, 92.59, 0.00, nan ],
[ 800, nan, nan, 103.84, 0.01, nan ],
[ 900, nan, nan, 135.72, 0.01, nan ],
[ 1000, nan, nan, 173.93, 0.01, nan ],
[ 2000, nan, nan, 542.17, 0.02, nan ],
[ 3000, nan, nan, 985.20, 0.04, nan ],
[ 4000, nan, nan, 1292.83, 0.07, nan ],
[ 5000, nan, nan, 1526.84, 0.11, nan ],
[ 6000, nan, nan, 1740.43, 0.17, nan ],
[ 7000, nan, nan, 1876.94, 0.24, nan ],
[ 8000, nan, nan, 2023.99, 0.34, nan ],
[ 9000, nan, nan, 2126.79, 0.46, nan ],
[ 10000, nan, nan, 2216.49, 0.60, nan ],
[ 12000, nan, nan, 2363.24, 0.98, nan ],
[ 14000, nan, nan, 2494.30, 1.47, nan ],
[ 16000, nan, nan, 2586.92, 2.11, nan ],
[ 18000, nan, nan, 2644.91, 2.94, nan ],
[ 20000, nan, nan, 2706.00, 3.94, nan ],
])
# numactl --interleave=all ./testing_cpotrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
cpotrf_gpu = array([
[ 10, nan, nan, 0.00, 0.00, nan ],
[ 20, nan, nan, 0.01, 0.00, nan ],
[ 30, nan, nan, 0.05, 0.00, nan ],
[ 40, nan, nan, 0.10, 0.00, nan ],
[ 50, nan, nan, 0.19, 0.00, nan ],
[ 60, nan, nan, 0.33, 0.00, nan ],
[ 70, nan, nan, 0.50, 0.00, nan ],
[ 80, nan, nan, 0.71, 0.00, nan ],
[ 90, nan, nan, 1.00, 0.00, nan ],
[ 100, nan, nan, 1.30, 0.00, nan ],
[ 200, nan, nan, 24.85, 0.00, nan ],
[ 300, nan, nan, 14.57, 0.00, nan ],
[ 400, nan, nan, 28.90, 0.00, nan ],
[ 500, nan, nan, 49.90, 0.00, nan ],
[ 600, nan, nan, 64.01, 0.00, nan ],
[ 700, nan, nan, 94.00, 0.00, nan ],
[ 800, nan, nan, 105.97, 0.01, nan ],
[ 900, nan, nan, 140.86, 0.01, nan ],
[ 1000, nan, nan, 181.47, 0.01, nan ],
[ 2000, nan, nan, 624.18, 0.02, nan ],
[ 3000, nan, nan, 1151.31, 0.03, nan ],
[ 4000, nan, nan, 1509.14, 0.06, nan ],
[ 5000, nan, nan, 1762.60, 0.09, nan ],
[ 6000, nan, nan, 1986.88, 0.15, nan ],
[ 7000, nan, nan, 2119.76, 0.22, nan ],
[ 8000, nan, nan, 2253.88, 0.30, nan ],
[ 9000, nan, nan, 2313.50, 0.42, nan ],
[ 10000, nan, nan, 2416.80, 0.55, nan ],
[ 12000, nan, nan, 2565.33, 0.90, nan ],
[ 14000, nan, nan, 2676.10, 1.37, nan ],
[ 16000, nan, nan, 2759.86, 1.98, nan ],
[ 18000, nan, nan, 2793.26, 2.78, nan ],
[ 20000, nan, nan, 2840.93, 3.76, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/dgeev.txt
# numactl --interleave=all ./testing_dgeev -RN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dgeev_RN = array([
[ 10, nan, 0.0003 ],
[ 20, nan, 0.0005 ],
[ 30, nan, 0.0011 ],
[ 40, nan, 0.0035 ],
[ 50, nan, 0.0038 ],
[ 60, nan, 0.0029 ],
[ 70, nan, 0.0049 ],
[ 80, nan, 0.0069 ],
[ 90, nan, 0.0076 ],
[ 100, nan, 0.0105 ],
[ 200, nan, 0.0511 ],
[ 300, nan, 0.0940 ],
[ 400, nan, 0.1513 ],
[ 500, nan, 0.2043 ],
[ 600, nan, 0.4025 ],
[ 700, nan, 0.4948 ],
[ 800, nan, 0.6284 ],
[ 900, nan, 0.7352 ],
[ 1000, nan, 0.8453 ],
[ 2000, nan, 2.7113 ],
[ 3000, nan, 8.3927 ],
[ 4000, nan, 13.1533 ],
[ 5000, nan, 19.8204 ],
[ 6000, nan, 35.3721 ],
[ 7000, nan, 47.4245 ],
[ 8000, nan, 60.2085 ],
[ 9000, nan, 72.0642 ],
[ 10000, nan, 85.6638 ],
[ 12000, nan, 127.5793 ],
[ 14000, nan, 172.5071 ],
[ 16000, nan, 233.0806 ],
[ 18000, nan, 296.6084 ],
[ 20000, nan, 377.1261 ],
])
# numactl --interleave=all ./testing_dgeev -RV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dgeev_RV = array([
[ 10, nan, 0.0020 ],
[ 20, nan, 0.0025 ],
[ 30, nan, 0.0030 ],
[ 40, nan, 0.0073 ],
[ 50, nan, 0.0083 ],
[ 60, nan, 0.0070 ],
[ 70, nan, 0.0108 ],
[ 80, nan, 0.0126 ],
[ 90, nan, 0.0139 ],
[ 100, nan, 0.0160 ],
[ 200, nan, 0.0743 ],
[ 300, nan, 0.1380 ],
[ 400, nan, 0.2666 ],
[ 500, nan, 0.3481 ],
[ 600, nan, 0.4816 ],
[ 700, nan, 0.6642 ],
[ 800, nan, 0.7633 ],
[ 900, nan, 0.9096 ],
[ 1000, nan, 1.1074 ],
[ 2000, nan, 3.7380 ],
[ 3000, nan, 9.7185 ],
[ 4000, nan, 16.8563 ],
[ 5000, nan, 25.8547 ],
[ 6000, nan, 44.7942 ],
[ 7000, nan, 58.4372 ],
[ 8000, nan, 77.0922 ],
[ 9000, nan, 100.3287 ],
[ 10000, nan, 121.8376 ],
[ 12000, nan, 189.8740 ],
[ 14000, nan, 256.4798 ],
[ 16000, nan, 366.9515 ],
[ 18000, nan, 463.3130 ],
[ 20000, nan, 611.5157 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/dgeqrf.txt
# numactl --interleave=all ./testing_dgeqrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dgeqrf = array([
[ 10, 10, nan, nan, 0.03, 0.00, nan ],
[ 20, 20, nan, nan, 0.17, 0.00, nan ],
[ 30, 30, nan, nan, 0.46, 0.00, nan ],
[ 40, 40, nan, nan, 0.84, 0.00, nan ],
[ 50, 50, nan, nan, 1.25, 0.00, nan ],
[ 60, 60, nan, nan, 1.61, 0.00, nan ],
[ 70, 70, nan, nan, 0.47, 0.00, nan ],
[ 80, 80, nan, nan, 0.71, 0.00, nan ],
[ 90, 90, nan, nan, 0.96, 0.00, nan ],
[ 100, 100, nan, nan, 1.24, 0.00, nan ],
[ 200, 200, nan, nan, 4.54, 0.00, nan ],
[ 300, 300, nan, nan, 10.16, 0.00, nan ],
[ 400, 400, nan, nan, 16.67, 0.01, nan ],
[ 500, 500, nan, nan, 24.70, 0.01, nan ],
[ 600, 600, nan, nan, 32.95, 0.01, nan ],
[ 700, 700, nan, nan, 42.56, 0.01, nan ],
[ 800, 800, nan, nan, 51.44, 0.01, nan ],
[ 900, 900, nan, nan, 59.56, 0.02, nan ],
[ 1000, 1000, nan, nan, 71.06, 0.02, nan ],
[ 2000, 2000, nan, nan, 186.61, 0.06, nan ],
[ 3000, 3000, nan, nan, 305.99, 0.12, nan ],
[ 4000, 4000, nan, nan, 378.07, 0.23, nan ],
[ 5000, 5000, nan, nan, 483.83, 0.34, nan ],
[ 6000, 6000, nan, nan, 584.61, 0.49, nan ],
[ 7000, 7000, nan, nan, 707.00, 0.65, nan ],
[ 8000, 8000, nan, nan, 733.32, 0.93, nan ],
[ 9000, 9000, nan, nan, 779.32, 1.25, nan ],
[ 10000, 10000, nan, nan, 840.03, 1.59, nan ],
[ 12000, 12000, nan, nan, 901.33, 2.56, nan ],
[ 14000, 14000, nan, nan, 947.07, 3.86, nan ],
[ 16000, 16000, nan, nan, 962.32, 5.68, nan ],
[ 18000, 18000, nan, nan, 999.23, 7.78, nan ],
[ 20000, 20000, nan, nan, 1014.13, 10.52, nan ],
])
# numactl --interleave=all ./testing_dgeqrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dgeqrf_gpu = array([
[ 10, 10, nan, nan, 0.00, 0.00, nan ],
[ 20, 20, nan, nan, 0.01, 0.00, nan ],
[ 30, 30, nan, nan, 0.04, 0.00, nan ],
[ 40, 40, nan, nan, 0.08, 0.00, nan ],
[ 50, 50, nan, nan, 0.16, 0.00, nan ],
[ 60, 60, nan, nan, 0.27, 0.00, nan ],
[ 70, 70, nan, nan, 0.31, 0.00, nan ],
[ 80, 80, nan, nan, 0.46, 0.00, nan ],
[ 90, 90, nan, nan, 0.70, 0.00, nan ],
[ 100, 100, nan, nan, 2.03, 0.00, nan ],
[ 200, 200, nan, nan, 4.09, 0.00, nan ],
[ 300, 300, nan, nan, 9.35, 0.00, nan ],
[ 400, 400, nan, nan, 15.81, 0.01, nan ],
[ 500, 500, nan, nan, 24.34, 0.01, nan ],
[ 600, 600, nan, nan, 32.75, 0.01, nan ],
[ 700, 700, nan, nan, 42.67, 0.01, nan ],
[ 800, 800, nan, nan, 52.59, 0.01, nan ],
[ 900, 900, nan, nan, 61.51, 0.02, nan ],
[ 1000, 1000, nan, nan, 73.34, 0.02, nan ],
[ 2000, 2000, nan, nan, 195.61, 0.05, nan ],
[ 3000, 3000, nan, nan, 311.99, 0.12, nan ],
[ 4000, 4000, nan, nan, 400.75, 0.21, nan ],
[ 5000, 5000, nan, nan, 517.73, 0.32, nan ],
[ 6000, 6000, nan, nan, 622.53, 0.46, nan ],
[ 7000, 7000, nan, nan, 688.27, 0.66, nan ],
[ 8000, 8000, nan, nan, 749.37, 0.91, nan ],
[ 9000, 9000, nan, nan, 790.68, 1.23, nan ],
[ 10000, 10000, nan, nan, 825.02, 1.62, nan ],
[ 12000, 12000, nan, nan, 890.99, 2.59, nan ],
[ 14000, 14000, nan, nan, 938.17, 3.90, nan ],
[ 16000, 16000, nan, nan, 970.53, 5.63, nan ],
[ 18000, 18000, nan, nan, 985.13, 7.89, nan ],
[ 20000, 20000, nan, nan, 1002.88, 10.64, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/dgesvd.txt
# numactl --interleave=all ./testing_dgesvd -UN -VN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
dgesvd_UN = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.01, nan ],
[ nan, 300, 300, nan, 0.03, nan ],
[ nan, 400, 400, nan, 0.05, nan ],
[ nan, 500, 500, nan, 0.07, nan ],
[ nan, 600, 600, nan, 0.09, nan ],
[ nan, 700, 700, nan, 0.12, nan ],
[ nan, 800, 800, nan, 0.15, nan ],
[ nan, 900, 900, nan, 0.19, nan ],
[ nan, 1000, 1000, nan, 0.23, nan ],
[ nan, 2000, 2000, nan, 0.90, nan ],
[ nan, 3000, 3000, nan, 2.32, nan ],
[ nan, 4000, 4000, nan, 4.67, nan ],
[ nan, 5000, 5000, nan, 8.28, nan ],
[ nan, 6000, 6000, nan, 13.27, nan ],
[ nan, 7000, 7000, nan, 19.95, nan ],
[ nan, 8000, 8000, nan, 28.53, nan ],
[ nan, 9000, 9000, nan, 39.61, nan ],
[ nan, 10000, 10000, nan, 52.86, nan ],
[ nan, 12000, 12000, nan, 88.18, nan ],
[ nan, 14000, 14000, nan, 135.89, nan ],
[ nan, 16000, 16000, nan, 200.69, nan ],
[ nan, 18000, 18000, nan, 283.76, nan ],
[ nan, 20000, 20000, nan, 383.85, nan ],
[ nan, 300, 100, nan, 0.02, nan ],
[ nan, 600, 200, nan, 0.02, nan ],
[ nan, 900, 300, nan, 0.03, nan ],
[ nan, 1200, 400, nan, 0.06, nan ],
[ nan, 1500, 500, nan, 0.08, nan ],
[ nan, 1800, 600, nan, 0.11, nan ],
[ nan, 2100, 700, nan, 0.15, nan ],
[ nan, 2400, 800, nan, 0.19, nan ],
[ nan, 2700, 900, nan, 0.24, nan ],
[ nan, 3000, 1000, nan, 0.30, nan ],
[ nan, 6000, 2000, nan, 1.25, nan ],
[ nan, 9000, 3000, nan, 3.32, nan ],
[ nan, 12000, 4000, nan, 6.82, nan ],
[ nan, 15000, 5000, nan, 12.82, nan ],
[ nan, 18000, 6000, nan, 19.68, nan ],
[ nan, 21000, 7000, nan, 29.68, nan ],
[ nan, 24000, 8000, nan, 43.09, nan ],
[ nan, 27000, 9000, nan, 59.81, nan ],
[ nan, 100, 300, nan, 0.00, nan ],
[ nan, 200, 600, nan, 0.02, nan ],
[ nan, 300, 900, nan, 0.04, nan ],
[ nan, 400, 1200, nan, 0.06, nan ],
[ nan, 500, 1500, nan, 0.09, nan ],
[ nan, 600, 1800, nan, 0.13, nan ],
[ nan, 700, 2100, nan, 0.17, nan ],
[ nan, 800, 2400, nan, 0.21, nan ],
[ nan, 900, 2700, nan, 0.27, nan ],
[ nan, 1000, 3000, nan, 0.33, nan ],
[ nan, 2000, 6000, nan, 1.32, nan ],
[ nan, 3000, 9000, nan, 3.53, nan ],
[ nan, 4000, 12000, nan, 7.26, nan ],
[ nan, 5000, 15000, nan, 12.87, nan ],
[ nan, 6000, 18000, nan, 21.08, nan ],
[ nan, 7000, 21000, nan, 31.73, nan ],
[ nan, 8000, 24000, nan, 45.26, nan ],
[ nan, 9000, 27000, nan, 62.39, nan ],
[ nan, 10000, 100, nan, 0.01, nan ],
[ nan, 20000, 200, nan, 0.06, nan ],
[ nan, 30000, 300, nan, 0.15, nan ],
[ nan, 40000, 400, nan, 0.38, nan ],
[ nan, 50000, 500, nan, 0.61, nan ],
[ nan, 60000, 600, nan, 0.93, nan ],
[ nan, 70000, 700, nan, 1.30, nan ],
[ nan, 80000, 800, nan, 1.76, nan ],
[ nan, 90000, 900, nan, 2.47, nan ],
[ nan, 100000, 1000, nan, 3.23, nan ],
[ nan, 200000, 2000, nan, 18.50, nan ],
[ nan, 100, 10000, nan, 0.01, nan ],
[ nan, 200, 20000, nan, 0.05, nan ],
[ nan, 300, 30000, nan, 0.16, nan ],
[ nan, 400, 40000, nan, 0.33, nan ],
[ nan, 500, 50000, nan, 0.60, nan ],
[ nan, 600, 60000, nan, 0.91, nan ],
[ nan, 700, 70000, nan, 1.44, nan ],
[ nan, 800, 80000, nan, 1.92, nan ],
[ nan, 900, 90000, nan, 2.28, nan ],
[ nan, 1000, 100000, nan, 2.97, nan ],
[ nan, 2000, 200000, nan, 20.16, nan ],
])
# numactl --interleave=all ./testing_dgesvd -US -VS -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
dgesvd_US = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.01, nan ],
[ nan, 70, 70, nan, 0.01, nan ],
[ nan, 80, 80, nan, 0.01, nan ],
[ nan, 90, 90, nan, 0.01, nan ],
[ nan, 100, 100, nan, 0.02, nan ],
[ nan, 200, 200, nan, 0.07, nan ],
[ nan, 300, 300, nan, 0.08, nan ],
[ nan, 400, 400, nan, 0.10, nan ],
[ nan, 500, 500, nan, 0.15, nan ],
[ nan, 600, 600, nan, 0.23, nan ],
[ nan, 700, 700, nan, 0.31, nan ],
[ nan, 800, 800, nan, 0.40, nan ],
[ nan, 900, 900, nan, 0.52, nan ],
[ nan, 1000, 1000, nan, 0.65, nan ],
[ nan, 2000, 2000, nan, 3.15, nan ],
[ nan, 3000, 3000, nan, 8.73, nan ],
[ nan, 4000, 4000, nan, 17.19, nan ],
[ nan, 5000, 5000, nan, 30.02, nan ],
[ nan, 6000, 6000, nan, 43.31, nan ],
[ nan, 7000, 7000, nan, 58.08, nan ],
[ nan, 8000, 8000, nan, 80.02, nan ],
[ nan, 9000, 9000, nan, 109.74, nan ],
[ nan, 10000, 10000, nan, 145.96, nan ],
[ nan, 12000, 12000, nan, 234.26, nan ],
[ nan, 14000, 14000, nan, 361.08, nan ],
[ nan, 16000, 16000, nan, 505.16, nan ],
[ nan, 18000, 18000, nan, 718.19, nan ],
[ nan, 20000, 20000, nan, 924.63, nan ],
[ nan, 300, 100, nan, 0.04, nan ],
[ nan, 600, 200, nan, 0.10, nan ],
[ nan, 900, 300, nan, 0.10, nan ],
[ nan, 1200, 400, nan, 0.18, nan ],
[ nan, 1500, 500, nan, 0.22, nan ],
[ nan, 1800, 600, nan, 0.34, nan ],
[ nan, 2100, 700, nan, 0.48, nan ],
[ nan, 2400, 800, nan, 0.56, nan ],
[ nan, 2700, 900, nan, 0.73, nan ],
[ nan, 3000, 1000, nan, 0.99, nan ],
[ nan, 6000, 2000, nan, 4.82, nan ],
[ nan, 9000, 3000, nan, 12.88, nan ],
[ nan, 12000, 4000, nan, 27.43, nan ],
[ nan, 15000, 5000, nan, 46.47, nan ],
[ nan, 18000, 6000, nan, 78.11, nan ],
[ nan, 21000, 7000, nan, 117.80, nan ],
[ nan, 24000, 8000, nan, 158.32, nan ],
[ nan, 27000, 9000, nan, 228.24, nan ],
[ nan, 100, 300, nan, 0.02, nan ],
[ nan, 200, 600, nan, 0.08, nan ],
[ nan, 300, 900, nan, 0.09, nan ],
[ nan, 400, 1200, nan, 0.16, nan ],
[ nan, 500, 1500, nan, 0.25, nan ],
[ nan, 600, 1800, nan, 0.39, nan ],
[ nan, 700, 2100, nan, 0.52, nan ],
[ nan, 800, 2400, nan, 0.68, nan ],
[ nan, 900, 2700, nan, 0.83, nan ],
[ nan, 1000, 3000, nan, 1.11, nan ],
[ nan, 2000, 6000, nan, 6.02, nan ],
[ nan, 3000, 9000, nan, 15.63, nan ],
[ nan, 4000, 12000, nan, 31.95, nan ],
[ nan, 5000, 15000, nan, 55.06, nan ],
[ nan, 6000, 18000, nan, 101.32, nan ],
[ nan, 7000, 21000, nan, 139.57, nan ],
[ nan, 8000, 24000, nan, 272.79, nan ],
[ nan, 9000, 27000, nan, 289.58, nan ],
[ nan, 10000, 100, nan, 0.07, nan ],
[ nan, 20000, 200, nan, 0.29, nan ],
[ nan, 30000, 300, nan, 0.47, nan ],
[ nan, 40000, 400, nan, 1.23, nan ],
[ nan, 50000, 500, nan, 1.79, nan ],
[ nan, 60000, 600, nan, 2.65, nan ],
[ nan, 70000, 700, nan, 3.98, nan ],
[ nan, 80000, 800, nan, 5.43, nan ],
[ nan, 90000, 900, nan, 8.07, nan ],
[ nan, 100000, 1000, nan, 10.53, nan ],
[ nan, 200000, 2000, nan, 72.33, nan ],
[ nan, 100, 10000, nan, 0.06, nan ],
[ nan, 200, 20000, nan, 0.39, nan ],
[ nan, 300, 30000, nan, 0.62, nan ],
[ nan, 400, 40000, nan, 1.17, nan ],
[ nan, 500, 50000, nan, 3.24, nan ],
[ nan, 600, 60000, nan, 4.11, nan ],
[ nan, 700, 70000, nan, 5.45, nan ],
[ nan, 800, 80000, nan, 7.34, nan ],
[ nan, 900, 90000, nan, 8.96, nan ],
[ nan, 1000, 100000, nan, 14.89, nan ],
[ nan, 2000, 200000, nan, 100.00, nan ],
])
# numactl --interleave=all ./testing_dgesdd -UN -VN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
dgesdd_UN = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.01, nan ],
[ nan, 300, 300, nan, 0.03, nan ],
[ nan, 400, 400, nan, 0.05, nan ],
[ nan, 500, 500, nan, 0.07, nan ],
[ nan, 600, 600, nan, 0.09, nan ],
[ nan, 700, 700, nan, 0.12, nan ],
[ nan, 800, 800, nan, 0.15, nan ],
[ nan, 900, 900, nan, 0.19, nan ],
[ nan, 1000, 1000, nan, 0.23, nan ],
[ nan, 2000, 2000, nan, 0.91, nan ],
[ nan, 3000, 3000, nan, 2.35, nan ],
[ nan, 4000, 4000, nan, 4.73, nan ],
[ nan, 5000, 5000, nan, 8.37, nan ],
[ nan, 6000, 6000, nan, 13.39, nan ],
[ nan, 7000, 7000, nan, 20.14, nan ],
[ nan, 8000, 8000, nan, 28.75, nan ],
[ nan, 9000, 9000, nan, 39.93, nan ],
[ nan, 10000, 10000, nan, 53.33, nan ],
[ nan, 12000, 12000, nan, 88.78, nan ],
[ nan, 14000, 14000, nan, 136.82, nan ],
[ nan, 16000, 16000, nan, 201.80, nan ],
[ nan, 18000, 18000, nan, 285.32, nan ],
[ nan, 20000, 20000, nan, 385.63, nan ],
[ nan, 300, 100, nan, 0.00, nan ],
[ nan, 600, 200, nan, 0.02, nan ],
[ nan, 900, 300, nan, 0.03, nan ],
[ nan, 1200, 400, nan, 0.06, nan ],
[ nan, 1500, 500, nan, 0.08, nan ],
[ nan, 1800, 600, nan, 0.12, nan ],
[ nan, 2100, 700, nan, 0.15, nan ],
[ nan, 2400, 800, nan, 0.20, nan ],
[ nan, 2700, 900, nan, 0.25, nan ],
[ nan, 3000, 1000, nan, 0.31, nan ],
[ nan, 6000, 2000, nan, 1.39, nan ],
[ nan, 9000, 3000, nan, 3.34, nan ],
[ nan, 12000, 4000, nan, 6.83, nan ],
[ nan, 15000, 5000, nan, 12.18, nan ],
[ nan, 18000, 6000, nan, 19.68, nan ],
[ nan, 21000, 7000, nan, 29.76, nan ],
[ nan, 24000, 8000, nan, 43.26, nan ],
[ nan, 27000, 9000, nan, 59.81, nan ],
[ nan, 100, 300, nan, 0.00, nan ],
[ nan, 200, 600, nan, 0.02, nan ],
[ nan, 300, 900, nan, 0.04, nan ],
[ nan, 400, 1200, nan, 0.06, nan ],
[ nan, 500, 1500, nan, 0.10, nan ],
[ nan, 600, 1800, nan, 0.13, nan ],
[ nan, 700, 2100, nan, 0.17, nan ],
[ nan, 800, 2400, nan, 0.21, nan ],
[ nan, 900, 2700, nan, 0.27, nan ],
[ nan, 1000, 3000, nan, 0.32, nan ],
[ nan, 2000, 6000, nan, 1.35, nan ],
[ nan, 3000, 9000, nan, 3.57, nan ],
[ nan, 4000, 12000, nan, 7.31, nan ],
[ nan, 5000, 15000, nan, 12.97, nan ],
[ nan, 6000, 18000, nan, 21.20, nan ],
[ nan, 7000, 21000, nan, 31.85, nan ],
[ nan, 8000, 24000, nan, 45.32, nan ],
[ nan, 9000, 27000, nan, 62.50, nan ],
[ nan, 10000, 100, nan, 0.01, nan ],
[ nan, 20000, 200, nan, 0.06, nan ],
[ nan, 30000, 300, nan, 0.15, nan ],
[ nan, 40000, 400, nan, 0.38, nan ],
[ nan, 50000, 500, nan, 0.61, nan ],
[ nan, 60000, 600, nan, 0.93, nan ],
[ nan, 70000, 700, nan, 1.30, nan ],
[ nan, 80000, 800, nan, 1.77, nan ],
[ nan, 90000, 900, nan, 2.40, nan ],
[ nan, 100000, 1000, nan, 3.25, nan ],
[ nan, 200000, 2000, nan, 18.60, nan ],
[ nan, 100, 10000, nan, 0.01, nan ],
[ nan, 200, 20000, nan, 0.05, nan ],
[ nan, 300, 30000, nan, 0.16, nan ],
[ nan, 400, 40000, nan, 0.33, nan ],
[ nan, 500, 50000, nan, 0.59, nan ],
[ nan, 600, 60000, nan, 0.91, nan ],
[ nan, 700, 70000, nan, 1.44, nan ],
[ nan, 800, 80000, nan, 1.92, nan ],
[ nan, 900, 90000, nan, 2.31, nan ],
[ nan, 1000, 100000, nan, 2.98, nan ],
[ nan, 2000, 200000, nan, 20.24, nan ],
])
# numactl --interleave=all ./testing_dgesdd -US -VS -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
dgesdd_US = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.01, nan ],
[ nan, 80, 80, nan, 0.01, nan ],
[ nan, 90, 90, nan, 0.01, nan ],
[ nan, 100, 100, nan, 0.01, nan ],
[ nan, 200, 200, nan, 0.02, nan ],
[ nan, 300, 300, nan, 0.05, nan ],
[ nan, 400, 400, nan, 0.08, nan ],
[ nan, 500, 500, nan, 0.13, nan ],
[ nan, 600, 600, nan, 0.18, nan ],
[ nan, 700, 700, nan, 0.23, nan ],
[ nan, 800, 800, nan, 0.30, nan ],
[ nan, 900, 900, nan, 0.38, nan ],
[ nan, 1000, 1000, nan, 0.48, nan ],
[ nan, 2000, 2000, nan, 1.92, nan ],
[ nan, 3000, 3000, nan, 5.59, nan ],
[ nan, 4000, 4000, nan, 8.84, nan ],
[ nan, 5000, 5000, nan, 14.96, nan ],
[ nan, 6000, 6000, nan, 23.32, nan ],
[ nan, 7000, 7000, nan, 34.05, nan ],
[ nan, 8000, 8000, nan, 47.88, nan ],
[ nan, 9000, 9000, nan, 64.61, nan ],
[ nan, 10000, 10000, nan, 85.09, nan ],
[ nan, 12000, 12000, nan, 137.52, nan ],
[ nan, 14000, 14000, nan, 206.75, nan ],
[ nan, 16000, 16000, nan, 302.89, nan ],
[ nan, 18000, 18000, nan, 414.03, nan ],
[ nan, 20000, 20000, nan, 552.59, nan ],
[ nan, 300, 100, nan, 0.01, nan ],
[ nan, 600, 200, nan, 0.03, nan ],
[ nan, 900, 300, nan, 0.06, nan ],
[ nan, 1200, 400, nan, 0.10, nan ],
[ nan, 1500, 500, nan, 0.16, nan ],
[ nan, 1800, 600, nan, 0.21, nan ],
[ nan, 2100, 700, nan, 0.30, nan ],
[ nan, 2400, 800, nan, 0.37, nan ],
[ nan, 2700, 900, nan, 0.48, nan ],
[ nan, 3000, 1000, nan, 0.62, nan ],
[ nan, 6000, 2000, nan, 2.68, nan ],
[ nan, 9000, 3000, nan, 6.93, nan ],
[ nan, 12000, 4000, nan, 13.88, nan ],
[ nan, 15000, 5000, nan, 24.22, nan ],
[ nan, 18000, 6000, nan, 39.57, nan ],
[ nan, 21000, 7000, nan, 58.84, nan ],
[ nan, 24000, 8000, nan, 84.25, nan ],
[ nan, 27000, 9000, nan, 114.81, nan ],
[ nan, 100, 300, nan, 0.01, nan ],
[ nan, 200, 600, nan, 0.03, nan ],
[ nan, 300, 900, nan, 0.07, nan ],
[ nan, 400, 1200, nan, 0.11, nan ],
[ nan, 500, 1500, nan, 0.17, nan ],
[ nan, 600, 1800, nan, 0.23, nan ],
[ nan, 700, 2100, nan, 0.33, nan ],
[ nan, 800, 2400, nan, 0.40, nan ],
[ nan, 900, 2700, nan, 0.51, nan ],
[ nan, 1000, 3000, nan, 0.64, nan ],
[ nan, 2000, 6000, nan, 3.24, nan ],
[ nan, 3000, 9000, nan, 7.45, nan ],
[ nan, 4000, 12000, nan, 14.28, nan ],
[ nan, 5000, 15000, nan, 24.86, nan ],
[ nan, 6000, 18000, nan, 41.14, nan ],
[ nan, 7000, 21000, nan, 61.94, nan ],
[ nan, 8000, 24000, nan, 86.26, nan ],
[ nan, 9000, 27000, nan, 117.24, nan ],
[ nan, 10000, 100, nan, 0.03, nan ],
[ nan, 20000, 200, nan, 0.18, nan ],
[ nan, 30000, 300, nan, 0.32, nan ],
[ nan, 40000, 400, nan, 0.64, nan ],
[ nan, 50000, 500, nan, 1.55, nan ],
[ nan, 60000, 600, nan, 1.95, nan ],
[ nan, 70000, 700, nan, 2.49, nan ],
[ nan, 80000, 800, nan, 3.13, nan ],
[ nan, 90000, 900, nan, 4.08, nan ],
[ nan, 100000, 1000, nan, 6.83, nan ],
[ nan, 200000, 2000, nan, 36.24, nan ],
[ nan, 100, 10000, nan, 0.04, nan ],
[ nan, 200, 20000, nan, 0.25, nan ],
[ nan, 300, 30000, nan, 0.48, nan ],
[ nan, 400, 40000, nan, 0.82, nan ],
[ nan, 500, 50000, nan, 2.82, nan ],
[ nan, 600, 60000, nan, 3.20, nan ],
[ nan, 700, 70000, nan, 5.06, nan ],
[ nan, 800, 80000, nan, 4.80, nan ],
[ nan, 900, 90000, nan, 6.14, nan ],
[ nan, 1000, 100000, nan, 10.03, nan ],
[ nan, 2000, 200000, nan, 42.18, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/dgetrf.txt
# numactl --interleave=all ./testing_dgetrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dgetrf = array([
[ 10, 10, nan, nan, 0.03, 0.00, nan ],
[ 20, 20, nan, nan, 0.16, 0.00, nan ],
[ 30, 30, nan, nan, 0.27, 0.00, nan ],
[ 40, 40, nan, nan, 0.65, 0.00, nan ],
[ 50, 50, nan, nan, 0.88, 0.00, nan ],
[ 60, 60, nan, nan, 1.25, 0.00, nan ],
[ 70, 70, nan, nan, 1.56, 0.00, nan ],
[ 80, 80, nan, nan, 2.11, 0.00, nan ],
[ 90, 90, nan, nan, 2.66, 0.00, nan ],
[ 100, 100, nan, nan, 3.39, 0.00, nan ],
[ 200, 200, nan, nan, 3.64, 0.00, nan ],
[ 300, 300, nan, nan, 8.18, 0.00, nan ],
[ 400, 400, nan, nan, 13.61, 0.00, nan ],
[ 500, 500, nan, nan, 20.78, 0.00, nan ],
[ 600, 600, nan, nan, 27.95, 0.01, nan ],
[ 700, 700, nan, nan, 34.96, 0.01, nan ],
[ 800, 800, nan, nan, 43.26, 0.01, nan ],
[ 900, 900, nan, nan, 50.68, 0.01, nan ],
[ 1000, 1000, nan, nan, 59.98, 0.01, nan ],
[ 2000, 2000, nan, nan, 149.36, 0.04, nan ],
[ 3000, 3000, nan, nan, 243.92, 0.07, nan ],
[ 4000, 4000, nan, nan, 329.38, 0.13, nan ],
[ 5000, 5000, nan, nan, 423.25, 0.20, nan ],
[ 6000, 6000, nan, nan, 507.92, 0.28, nan ],
[ 7000, 7000, nan, nan, 585.92, 0.39, nan ],
[ 8000, 8000, nan, nan, 645.88, 0.53, nan ],
[ 9000, 9000, nan, nan, 689.11, 0.71, nan ],
[ 10000, 10000, nan, nan, 732.19, 0.91, nan ],
[ 12000, 12000, nan, nan, 801.39, 1.44, nan ],
[ 14000, 14000, nan, nan, 849.90, 2.15, nan ],
[ 16000, 16000, nan, nan, 887.67, 3.08, nan ],
[ 18000, 18000, nan, nan, 916.90, 4.24, nan ],
[ 20000, 20000, nan, nan, 942.07, 5.66, nan ],
])
# numactl --interleave=all ./testing_dgetrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dgetrf_gpu = array([
[ 10, 10, nan, nan, 0.01, 0.00, nan ],
[ 20, 20, nan, nan, 0.09, 0.00, nan ],
[ 30, 30, nan, nan, 0.19, 0.00, nan ],
[ 40, 40, nan, nan, 0.48, 0.00, nan ],
[ 50, 50, nan, nan, 0.71, 0.00, nan ],
[ 60, 60, nan, nan, 1.06, 0.00, nan ],
[ 70, 70, nan, nan, 1.13, 0.00, nan ],
[ 80, 80, nan, nan, 1.62, 0.00, nan ],
[ 90, 90, nan, nan, 1.85, 0.00, nan ],
[ 100, 100, nan, nan, 2.06, 0.00, nan ],
[ 200, 200, nan, nan, 2.60, 0.00, nan ],
[ 300, 300, nan, nan, 6.64, 0.00, nan ],
[ 400, 400, nan, nan, 12.08, 0.00, nan ],
[ 500, 500, nan, nan, 18.94, 0.00, nan ],
[ 600, 600, nan, nan, 26.94, 0.01, nan ],
[ 700, 700, nan, nan, 35.93, 0.01, nan ],
[ 800, 800, nan, nan, 45.45, 0.01, nan ],
[ 900, 900, nan, nan, 54.81, 0.01, nan ],
[ 1000, 1000, nan, nan, 63.56, 0.01, nan ],
[ 2000, 2000, nan, nan, 175.77, 0.03, nan ],
[ 3000, 3000, nan, nan, 299.53, 0.06, nan ],
[ 4000, 4000, nan, nan, 396.98, 0.11, nan ],
[ 5000, 5000, nan, nan, 517.63, 0.16, nan ],
[ 6000, 6000, nan, nan, 624.88, 0.23, nan ],
[ 7000, 7000, nan, nan, 709.62, 0.32, nan ],
[ 8000, 8000, nan, nan, 775.59, 0.44, nan ],
[ 9000, 9000, nan, nan, 789.00, 0.62, nan ],
[ 10000, 10000, nan, nan, 837.81, 0.80, nan ],
[ 12000, 12000, nan, nan, 919.89, 1.25, nan ],
[ 14000, 14000, nan, nan, 976.29, 1.87, nan ],
[ 16000, 16000, nan, nan, 1008.44, 2.71, nan ],
[ 18000, 18000, nan, nan, 1027.63, 3.78, nan ],
[ 20000, 20000, nan, nan, 1046.16, 5.10, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/dpotrf.txt
# numactl --interleave=all ./testing_dpotrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dpotrf = array([
[ 10, nan, nan, 0.00, 0.00, nan ],
[ 20, nan, nan, 0.01, 0.00, nan ],
[ 30, nan, nan, 0.03, 0.00, nan ],
[ 40, nan, nan, 0.43, 0.00, nan ],
[ 50, nan, nan, 0.78, 0.00, nan ],
[ 60, nan, nan, 1.17, 0.00, nan ],
[ 70, nan, nan, 1.12, 0.00, nan ],
[ 80, nan, nan, 1.60, 0.00, nan ],
[ 90, nan, nan, 0.61, 0.00, nan ],
[ 100, nan, nan, 0.79, 0.00, nan ],
[ 200, nan, nan, 5.21, 0.00, nan ],
[ 300, nan, nan, 5.35, 0.00, nan ],
[ 400, nan, nan, 10.32, 0.00, nan ],
[ 500, nan, nan, 17.48, 0.00, nan ],
[ 600, nan, nan, 20.77, 0.00, nan ],
[ 700, nan, nan, 28.51, 0.00, nan ],
[ 800, nan, nan, 33.17, 0.01, nan ],
[ 900, nan, nan, 42.04, 0.01, nan ],
[ 1000, nan, nan, 54.57, 0.01, nan ],
[ 2000, nan, nan, 172.74, 0.02, nan ],
[ 3000, nan, nan, 304.93, 0.03, nan ],
[ 4000, nan, nan, 485.42, 0.04, nan ],
[ 5000, nan, nan, 574.53, 0.07, nan ],
[ 6000, nan, nan, 668.13, 0.11, nan ],
[ 7000, nan, nan, 723.38, 0.16, nan ],
[ 8000, nan, nan, 786.98, 0.22, nan ],
[ 9000, nan, nan, 827.85, 0.29, nan ],
[ 10000, nan, nan, 859.69, 0.39, nan ],
[ 12000, nan, nan, 930.60, 0.62, nan ],
[ 14000, nan, nan, 980.75, 0.93, nan ],
[ 16000, nan, nan, 1021.07, 1.34, nan ],
[ 18000, nan, nan, 1041.93, 1.87, nan ],
[ 20000, nan, nan, 1070.15, 2.49, nan ],
])
# numactl --interleave=all ./testing_dpotrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dpotrf_gpu = array([
[ 10, nan, nan, 0.00, 0.00, nan ],
[ 20, nan, nan, 0.00, 0.00, nan ],
[ 30, nan, nan, 0.01, 0.00, nan ],
[ 40, nan, nan, 0.02, 0.00, nan ],
[ 50, nan, nan, 0.04, 0.00, nan ],
[ 60, nan, nan, 0.06, 0.00, nan ],
[ 70, nan, nan, 0.09, 0.00, nan ],
[ 80, nan, nan, 0.14, 0.00, nan ],
[ 90, nan, nan, 0.19, 0.00, nan ],
[ 100, nan, nan, 0.24, 0.00, nan ],
[ 200, nan, nan, 7.26, 0.00, nan ],
[ 300, nan, nan, 3.55, 0.00, nan ],
[ 400, nan, nan, 7.02, 0.00, nan ],
[ 500, nan, nan, 12.70, 0.00, nan ],
[ 600, nan, nan, 16.31, 0.00, nan ],
[ 700, nan, nan, 24.13, 0.00, nan ],
[ 800, nan, nan, 28.65, 0.01, nan ],
[ 900, nan, nan, 37.23, 0.01, nan ],
[ 1000, nan, nan, 49.58, 0.01, nan ],
[ 2000, nan, nan, 179.61, 0.01, nan ],
[ 3000, nan, nan, 339.19, 0.03, nan ],
[ 4000, nan, nan, 564.63, 0.04, nan ],
[ 5000, nan, nan, 674.93, 0.06, nan ],
[ 6000, nan, nan, 789.98, 0.09, nan ],
[ 7000, nan, nan, 839.24, 0.14, nan ],
[ 8000, nan, nan, 924.44, 0.18, nan ],
[ 9000, nan, nan, 959.69, 0.25, nan ],
[ 10000, nan, nan, 991.06, 0.34, nan ],
[ 12000, nan, nan, 1050.65, 0.55, nan ],
[ 14000, nan, nan, 1094.66, 0.84, nan ],
[ 16000, nan, nan, 1126.74, 1.21, nan ],
[ 18000, nan, nan, 1137.74, 1.71, nan ],
[ 20000, nan, nan, 1158.20, 2.30, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/dsyevd.txt
# numactl --interleave=all ./testing_dsyevd -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dsyevd_JN = array([
[ 10, nan, 0.0000 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0001 ],
[ 40, nan, 0.0002 ],
[ 50, nan, 0.0002 ],
[ 60, nan, 0.0003 ],
[ 70, nan, 0.0004 ],
[ 80, nan, 0.0006 ],
[ 90, nan, 0.0008 ],
[ 100, nan, 0.0011 ],
[ 200, nan, 0.0128 ],
[ 300, nan, 0.0231 ],
[ 400, nan, 0.0393 ],
[ 500, nan, 0.0544 ],
[ 600, nan, 0.0755 ],
[ 700, nan, 0.0954 ],
[ 800, nan, 0.1220 ],
[ 900, nan, 0.1502 ],
[ 1000, nan, 0.1776 ],
[ 2000, nan, 0.5980 ],
[ 3000, nan, 1.3180 ],
[ 4000, nan, 2.3626 ],
[ 5000, nan, 3.8870 ],
[ 6000, nan, 5.7710 ],
[ 7000, nan, 8.1626 ],
[ 8000, nan, 11.0315 ],
[ 9000, nan, 14.6957 ],
[ 10000, nan, 19.0375 ],
[ 12000, nan, 30.2727 ],
[ 14000, nan, 44.6141 ],
[ 16000, nan, 63.2342 ],
[ 18000, nan, 87.2691 ],
[ 20000, nan, 114.5946 ],
])
# numactl --interleave=all ./testing_dsyevd -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dsyevd_JV = array([
[ 10, nan, 0.0001 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0003 ],
[ 40, nan, 0.0004 ],
[ 50, nan, 0.0005 ],
[ 60, nan, 0.0007 ],
[ 70, nan, 0.0009 ],
[ 80, nan, 0.0012 ],
[ 90, nan, 0.0016 ],
[ 100, nan, 0.0020 ],
[ 200, nan, 0.0164 ],
[ 300, nan, 0.0268 ],
[ 400, nan, 0.0441 ],
[ 500, nan, 0.0617 ],
[ 600, nan, 0.0784 ],
[ 700, nan, 0.1002 ],
[ 800, nan, 0.1273 ],
[ 900, nan, 0.1599 ],
[ 1000, nan, 0.1884 ],
[ 2000, nan, 0.6370 ],
[ 3000, nan, 1.4418 ],
[ 4000, nan, 2.5225 ],
[ 5000, nan, 4.0450 ],
[ 6000, nan, 6.1427 ],
[ 7000, nan, 8.8017 ],
[ 8000, nan, 12.1769 ],
[ 9000, nan, 16.1912 ],
[ 10000, nan, 21.2096 ],
[ 12000, nan, 34.1056 ],
[ 14000, nan, 49.1354 ],
[ 16000, nan, 70.6249 ],
[ 18000, nan, 98.2735 ],
[ 20000, nan, 130.3086 ],
])
# numactl --interleave=all ./testing_dsyevd_gpu -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dsyevd_gpu_JN = array([
[ 10, nan, 0.0001 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0001 ],
[ 40, nan, 0.0002 ],
[ 50, nan, 0.0002 ],
[ 60, nan, 0.0003 ],
[ 70, nan, 0.0005 ],
[ 80, nan, 0.0006 ],
[ 90, nan, 0.0008 ],
[ 100, nan, 0.0011 ],
[ 200, nan, 0.0114 ],
[ 300, nan, 0.0208 ],
[ 400, nan, 0.0354 ],
[ 500, nan, 0.0492 ],
[ 600, nan, 0.0687 ],
[ 700, nan, 0.0880 ],
[ 800, nan, 0.1129 ],
[ 900, nan, 0.1399 ],
[ 1000, nan, 0.1666 ],
[ 2000, nan, 0.5797 ],
[ 3000, nan, 1.3182 ],
[ 4000, nan, 2.3436 ],
[ 5000, nan, 3.8155 ],
[ 6000, nan, 5.6934 ],
[ 7000, nan, 8.1011 ],
[ 8000, nan, 11.0384 ],
[ 9000, nan, 14.7141 ],
[ 10000, nan, 18.9900 ],
[ 12000, nan, 30.3040 ],
[ 14000, nan, 44.5872 ],
[ 16000, nan, 63.3596 ],
[ 18000, nan, 87.1945 ],
[ 20000, nan, 114.6432 ],
])
# numactl --interleave=all ./testing_dsyevd_gpu -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dsyevd_gpu_JV = array([
[ 10, nan, 0.0001 ],
[ 20, nan, 0.0002 ],
[ 30, nan, 0.0003 ],
[ 40, nan, 0.0004 ],
[ 50, nan, 0.0006 ],
[ 60, nan, 0.0009 ],
[ 70, nan, 0.0010 ],
[ 80, nan, 0.0013 ],
[ 90, nan, 0.0018 ],
[ 100, nan, 0.0021 ],
[ 200, nan, 0.0155 ],
[ 300, nan, 0.0255 ],
[ 400, nan, 0.0422 ],
[ 500, nan, 0.0592 ],
[ 600, nan, 0.0752 ],
[ 700, nan, 0.0993 ],
[ 800, nan, 0.1229 ],
[ 900, nan, 0.1558 ],
[ 1000, nan, 0.1836 ],
[ 2000, nan, 0.6367 ],
[ 3000, nan, 1.3501 ],
[ 4000, nan, 2.4675 ],
[ 5000, nan, 3.9757 ],
[ 6000, nan, 6.1173 ],
[ 7000, nan, 8.8302 ],
[ 8000, nan, 12.3120 ],
[ 9000, nan, 16.4472 ],
[ 10000, nan, 22.3377 ],
[ 12000, nan, 35.1828 ],
[ 14000, nan, 52.9599 ],
[ 16000, nan, 76.0177 ],
[ 18000, nan, 105.7984 ],
[ 20000, nan, 142.2281 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/dsyevd_2stage.txt
# numactl --interleave=all ./testing_dsyevdx_2stage -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dsyevdx_2stage_JN = array([
[ 10, 0, 0.0002 ],
[ 20, 0, 0.0000 ],
[ 30, 0, 0.0000 ],
[ 40, 0, 0.0000 ],
[ 50, 0, 0.0000 ],
[ 60, 0, 0.0000 ],
[ 70, 70, 0.0004 ],
[ 80, 80, 0.0005 ],
[ 90, 90, 0.0007 ],
[ 100, 100, 0.0009 ],
[ 200, 200, 0.0042 ],
[ 300, 300, 0.0245 ],
[ 400, 400, 0.0463 ],
[ 500, 500, 0.0487 ],
[ 600, 600, 0.0815 ],
[ 700, 700, 0.1056 ],
[ 800, 800, 0.1401 ],
[ 900, 900, 0.1503 ],
[ 1000, 1000, 0.1824 ],
[ 2000, 2000, 0.6132 ],
[ 3000, 3000, 1.0271 ],
[ 4000, 4000, 1.5903 ],
[ 5000, 5000, 2.1931 ],
[ 6000, 6000, 2.9508 ],
[ 7000, 7000, 3.9075 ],
[ 8000, 8000, 4.9290 ],
[ 9000, 9000, 6.2685 ],
[ 10000, 10000, 7.7161 ],
[ 12000, 12000, 10.5474 ],
[ 14000, 14000, 14.8071 ],
[ 16000, 16000, 19.2503 ],
[ 18000, 18000, 28.0243 ],
[ 20000, 20000, 32.2358 ],
])
# numactl --interleave=all ./testing_dsyevdx_2stage -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
dsyevdx_2stage_JV = array([
[ 10, 10, 0.0001 ],
[ 20, 20, 0.0001 ],
[ 30, 30, 0.0003 ],
[ 40, 40, 0.0004 ],
[ 50, 50, 0.0005 ],
[ 60, 60, 0.0007 ],
[ 70, 70, 0.0009 ],
[ 80, 80, 0.0012 ],
[ 90, 90, 0.0016 ],
[ 100, 100, 0.0019 ],
[ 200, 200, 0.0075 ],
[ 300, 300, 0.0289 ],
[ 400, 400, 0.0480 ],
[ 500, 500, 0.0937 ],
[ 600, 600, 0.0977 ],
[ 700, 700, 0.1251 ],
[ 800, 800, 0.1576 ],
[ 900, 900, 0.2928 ],
[ 1000, 1000, 0.2289 ],
[ 2000, 2000, 0.7339 ],
[ 3000, 3000, 1.2198 ],
[ 4000, 4000, 2.0875 ],
[ 5000, 5000, 3.2698 ],
[ 6000, 6000, 4.8135 ],
[ 7000, 7000, 6.3343 ],
[ 8000, 8000, 8.8363 ],
[ 9000, 9000, 11.7228 ],
[ 10000, 10000, 14.6346 ],
[ 12000, 12000, 24.3806 ],
[ 14000, 14000, 36.2935 ],
[ 16000, 16000, 53.0486 ],
[ 18000, 18000, 66.8810 ],
[ 20000, 20000, 88.8894 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/dsymv.txt
# numactl --interleave=all ./testing_dsymv -N 100 -N 1000 --range 10:90:1 --range 100:900:10 --range 1000:9000:100 --range 10000:20000:2000
dsymv_L = array([
[ 10, 0.0058, 0.0379, 0.0082, 0.0269, 0.0095, 0.0231, 0.1153, 0.0019, 8.88e-17, 8.88e-17, 8.88e-17, nan ],
[ 11, 0.0075, 0.0350, 0.0102, 0.0260, 0.0120, 0.0219, 0.1230, 0.0021, 8.07e-17, 8.07e-17, 8.07e-17, nan ],
[ 12, 0.0087, 0.0360, 0.0120, 0.0260, 0.0149, 0.0210, 0.1636, 0.0019, 7.40e-17, 7.40e-17, 7.40e-17, nan ],
[ 13, 0.0098, 0.0370, 0.0140, 0.0260, 0.0166, 0.0219, 0.1696, 0.0021, 6.83e-17, 1.37e-16, 6.83e-17, nan ],
[ 14, 0.0127, 0.0331, 0.0168, 0.0250, 0.0210, 0.0200, 0.1957, 0.0021, 1.27e-16, 1.27e-16, 1.27e-16, nan ],
[ 15, 0.0137, 0.0350, 0.0185, 0.0260, 0.0229, 0.0210, 0.2517, 0.0019, 5.92e-17, 5.92e-17, 5.92e-17, nan ],
[ 16, 0.0156, 0.0348, 0.0209, 0.0260, 0.0248, 0.0219, 0.1755, 0.0031, 1.11e-16, 1.11e-16, 5.55e-17, nan ],
[ 17, 0.0185, 0.0331, 0.0244, 0.0250, 0.0306, 0.0200, 0.3209, 0.0019, 1.04e-16, 1.04e-16, 2.09e-16, nan ],
[ 18, 0.0206, 0.0331, 0.0263, 0.0260, 0.0322, 0.0212, 0.3586, 0.0019, 9.87e-17, 9.87e-17, 9.87e-17, nan ],
[ 19, 0.0213, 0.0358, 0.0292, 0.0260, 0.0362, 0.0210, 0.3985, 0.0019, 1.40e-16, 9.35e-17, 1.40e-16, nan ],
[ 20, 0.0248, 0.0339, 0.0323, 0.0260, 0.0400, 0.0210, 0.3915, 0.0021, 8.88e-17, 8.88e-17, 8.88e-17, nan ],
[ 21, 0.0273, 0.0339, 0.0356, 0.0260, 0.0440, 0.0210, 0.3230, 0.0029, 8.46e-17, 1.27e-16, 1.69e-16, nan ],
[ 22, 0.0247, 0.0410, 0.0360, 0.0281, 0.0461, 0.0219, 0.3537, 0.0029, 8.07e-17, 8.07e-17, 8.07e-17, nan ],
[ 23, 0.0299, 0.0370, 0.0396, 0.0279, 0.0498, 0.0222, 0.3562, 0.0031, 7.72e-17, 1.16e-16, 1.16e-16, nan ],
[ 24, 0.0323, 0.0372, 0.0427, 0.0281, 0.0541, 0.0222, 0.3872, 0.0031, 1.11e-16, 7.40e-17, 1.11e-16, nan ],
[ 25, 0.0371, 0.0350, 0.0483, 0.0269, 0.0568, 0.0229, 0.4544, 0.0029, 1.42e-16, 1.42e-16, 7.11e-17, nan ],
[ 26, 0.0415, 0.0339, 0.0499, 0.0281, 0.0640, 0.0219, 0.4907, 0.0029, 1.37e-16, 1.37e-16, 1.37e-16, nan ],
[ 27, 0.0409, 0.0370, 0.0542, 0.0279, 0.0689, 0.0219, 0.5285, 0.0029, 1.32e-16, 1.32e-16, 1.32e-16, nan ],
[ 28, 0.0439, 0.0370, 0.0603, 0.0269, 0.0710, 0.0229, 0.8514, 0.0019, 1.90e-16, 1.27e-16, 1.27e-16, nan ],
[ 29, 0.0496, 0.0350, 0.0624, 0.0279, 0.0760, 0.0229, 0.6082, 0.0029, 1.84e-16, 1.84e-16, 1.23e-16, nan ],
[ 30, 0.0503, 0.0370, 0.0667, 0.0279, 0.0804, 0.0231, 0.6001, 0.0031, 5.92e-17, 1.18e-16, 1.18e-16, nan ],
[ 31, 0.0537, 0.0370, 0.0711, 0.0279, 0.0858, 0.0231, 0.6935, 0.0029, 1.15e-16, 1.15e-16, 1.15e-16, nan ],
[ 32, 0.0572, 0.0370, 0.0726, 0.0291, 0.0953, 0.0222, 0.6814, 0.0031, 1.67e-16, 1.11e-16, 1.67e-16, nan ],
[ 33, 0.0623, 0.0360, 0.0623, 0.0360, 0.0941, 0.0238, 0.7240, 0.0031, 1.08e-16, 1.08e-16, 1.08e-16, nan ],
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[ 700, 8.4523, 0.1161, 10.5546, 0.0930, 11.9660, 0.0820, 9.6175, 0.1020, 2.44e-16, 2.44e-16, 3.25e-16, nan ],
[ 710, 8.6245, 0.1171, 10.7479, 0.0939, 12.1685, 0.0830, 9.7125, 0.1040, 2.40e-16, 2.40e-16, 2.40e-16, nan ],
[ 720, 8.8871, 0.1168, 11.1373, 0.0932, 12.5135, 0.0830, 9.6987, 0.1070, 2.37e-16, 2.37e-16, 2.37e-16, nan ],
[ 730, 8.8818, 0.1202, 10.9986, 0.0970, 12.2641, 0.0870, 9.9036, 0.1078, 2.34e-16, 3.11e-16, 2.34e-16, nan ],
[ 740, 9.2925, 0.1180, 11.5573, 0.0949, 12.9208, 0.0849, 10.0433, 0.1092, 3.07e-16, 3.07e-16, 2.30e-16, nan ],
[ 750, 9.3010, 0.1211, 11.6091, 0.0970, 12.5328, 0.0899, 10.1610, 0.1109, 3.03e-16, 3.79e-16, 3.79e-16, nan ],
[ 760, 9.4759, 0.1221, 11.8045, 0.0980, 13.0071, 0.0889, 10.4336, 0.1109, 2.99e-16, 2.24e-16, 2.24e-16, nan ],
[ 770, 9.4141, 0.1261, 11.9713, 0.0992, 13.3514, 0.0889, 10.2470, 0.1159, 2.95e-16, 2.95e-16, 2.95e-16, nan ],
[ 780, 9.7337, 0.1252, 12.3137, 0.0989, 13.1030, 0.0930, 10.5148, 0.1159, 2.19e-16, 2.19e-16, 2.19e-16, nan ],
[ 790, 9.9279, 0.1259, 12.3631, 0.1011, 13.7584, 0.0908, 10.4839, 0.1192, 2.88e-16, 2.16e-16, 2.88e-16, nan ],
[ 800, 10.1615, 0.1261, 12.6779, 0.1011, 14.0718, 0.0911, 10.0101, 0.1280, 2.84e-16, 2.84e-16, 3.55e-16, nan ],
[ 810, 10.0192, 0.1311, 12.6100, 0.1042, 13.6738, 0.0961, 10.6794, 0.1230, 2.81e-16, 2.81e-16, 2.11e-16, nan ],
[ 820, 10.3622, 0.1299, 13.0726, 0.1030, 14.3334, 0.0939, 10.9445, 0.1230, 2.77e-16, 2.77e-16, 2.77e-16, nan ],
[ 830, 10.4438, 0.1321, 13.0312, 0.1059, 14.2159, 0.0970, 10.3690, 0.1330, 2.74e-16, 2.74e-16, 2.74e-16, nan ],
[ 840, 10.4516, 0.1352, 13.4683, 0.1049, 14.7048, 0.0961, 10.7943, 0.1309, 2.71e-16, 3.38e-16, 2.71e-16, nan ],
[ 850, 10.7970, 0.1340, 13.6357, 0.1061, 14.9088, 0.0970, 10.7207, 0.1349, 2.67e-16, 2.67e-16, 2.67e-16, nan ],
[ 860, 11.0327, 0.1342, 13.8339, 0.1070, 15.2615, 0.0970, 11.0524, 0.1340, 2.64e-16, 2.64e-16, 2.64e-16, nan ],
[ 870, 11.1520, 0.1359, 14.0323, 0.1080, 15.4663, 0.0980, 10.7557, 0.1409, 3.27e-16, 3.27e-16, 3.92e-16, nan ],
[ 880, 11.1553, 0.1390, 14.3566, 0.1080, 15.6711, 0.0989, 10.8573, 0.1428, 3.23e-16, 2.58e-16, 2.58e-16, nan ],
[ 890, 11.5890, 0.1369, 14.4297, 0.1099, 15.8383, 0.1001, 11.3131, 0.1402, 3.19e-16, 2.55e-16, 2.55e-16, nan ],
[ 900, 11.2621, 0.1440, 14.4730, 0.1121, 16.0811, 0.1009, 11.4325, 0.1419, 2.53e-16, 2.53e-16, 2.53e-16, nan ],
[ 1000, 12.8394, 0.1559, 16.8276, 0.1190, 17.7152, 0.1130, 11.5661, 0.1731, 2.84e-16, 2.84e-16, 2.84e-16, nan ],
[ 1100, 14.2289, 0.1702, 18.9542, 0.1278, 12.0515, 0.2010, 12.6676, 0.1912, 3.10e-16, 3.10e-16, 3.10e-16, nan ],
[ 1200, 15.7623, 0.1829, 21.0621, 0.1369, 13.0982, 0.2201, 12.9857, 0.2220, 3.32e-16, 2.84e-16, 2.84e-16, nan ],
[ 1300, 17.1556, 0.1972, 22.8465, 0.1481, 13.9780, 0.2420, 13.9780, 0.2420, 3.50e-16, 2.62e-16, 3.06e-16, nan ],
[ 1400, 18.7610, 0.2091, 25.3129, 0.1550, 15.3198, 0.2561, 13.9082, 0.2820, 3.25e-16, 3.25e-16, 3.25e-16, nan ],
[ 1500, 19.8392, 0.2270, 26.4894, 0.1700, 15.9653, 0.2820, 14.4396, 0.3119, 3.79e-16, 3.03e-16, 3.79e-16, nan ],
[ 1600, 20.6618, 0.2480, 28.1629, 0.1819, 16.4787, 0.3109, 13.7745, 0.3719, 3.55e-16, 3.55e-16, 3.55e-16, nan ],
[ 1700, 22.0722, 0.2620, 29.9473, 0.1931, 17.1067, 0.3381, 14.4217, 0.4010, 3.34e-16, 3.34e-16, 4.01e-16, nan ],
[ 1800, 23.6677, 0.2739, 31.6212, 0.2050, 18.2634, 0.3550, 18.0213, 0.3598, 3.79e-16, 3.79e-16, 3.79e-16, nan ],
[ 1900, 24.8148, 0.2911, 33.5907, 0.2151, 19.3232, 0.3738, 16.2373, 0.4449, 3.59e-16, 3.59e-16, 2.99e-16, nan ],
[ 2000, 25.9839, 0.3080, 34.6452, 0.2310, 20.3709, 0.3929, 18.1172, 0.4418, 3.98e-16, 4.55e-16, 3.41e-16, nan ],
[ 2100, 27.2343, 0.3240, 36.0383, 0.2449, 15.1873, 0.5810, 18.2232, 0.4842, 4.33e-16, 3.25e-16, 3.25e-16, nan ],
[ 2200, 28.7265, 0.3371, 37.6803, 0.2570, 16.2218, 0.5970, 18.1986, 0.5322, 5.17e-16, 3.62e-16, 3.62e-16, nan ],
[ 2300, 30.1597, 0.3510, 39.4974, 0.2680, 16.6711, 0.6349, 19.4204, 0.5450, 3.95e-16, 4.45e-16, 3.95e-16, nan ],
[ 2400, 31.6766, 0.3638, 40.5865, 0.2840, 17.5649, 0.6561, 18.2409, 0.6318, 4.26e-16, 4.26e-16, 3.79e-16, nan ],
[ 2500, 32.7402, 0.3819, 41.8260, 0.2990, 18.1739, 0.6881, 18.8600, 0.6630, 4.55e-16, 4.09e-16, 4.09e-16, nan ],
[ 2600, 33.6470, 0.4020, 43.7722, 0.3090, 18.8155, 0.7188, 20.0314, 0.6752, 5.25e-16, 3.94e-16, 4.81e-16, nan ],
[ 2700, 34.9775, 0.4170, 45.0152, 0.3240, 19.4517, 0.7498, 19.8172, 0.7360, 4.21e-16, 4.21e-16, 4.63e-16, nan ],
[ 2800, 35.7167, 0.4392, 44.5733, 0.3519, 20.0275, 0.7832, 20.2618, 0.7741, 4.06e-16, 4.47e-16, 4.06e-16, nan ],
[ 2900, 36.9877, 0.4549, 47.8134, 0.3519, 20.8733, 0.8061, 21.4311, 0.7851, 5.49e-16, 4.70e-16, 4.70e-16, nan ],
[ 3000, 38.5516, 0.4671, 48.5364, 0.3710, 21.6957, 0.8299, 21.3040, 0.8452, 5.31e-16, 4.55e-16, 5.31e-16, nan ],
[ 3100, 39.6463, 0.4849, 49.6861, 0.3870, 17.4320, 1.1029, 21.6252, 0.8891, 5.13e-16, 5.13e-16, 5.87e-16, nan ],
[ 3200, 40.3978, 0.5071, 50.9645, 0.4020, 18.0669, 1.1339, 21.1225, 0.9699, 4.97e-16, 4.97e-16, 5.68e-16, nan ],
[ 3300, 42.4627, 0.5131, 52.4869, 0.4151, 18.6375, 1.1690, 21.4204, 1.0171, 4.82e-16, 4.82e-16, 4.82e-16, nan ],
[ 3400, 43.0732, 0.5369, 53.7699, 0.4301, 19.0796, 1.2121, 21.7735, 1.0622, 5.35e-16, 4.68e-16, 5.35e-16, nan ],
[ 3500, 43.8336, 0.5591, 55.2040, 0.4439, 19.6201, 1.2491, 20.6116, 1.1890, 5.20e-16, 5.85e-16, 5.20e-16, nan ],
[ 3600, 45.4816, 0.5701, 56.8461, 0.4561, 20.1943, 1.2839, 18.7753, 1.3809, 5.68e-16, 4.42e-16, 4.42e-16, nan ],
[ 3700, 45.5657, 0.6011, 57.1498, 0.4792, 20.6566, 1.3258, 20.4397, 1.3399, 6.76e-16, 6.15e-16, 5.53e-16, nan ],
[ 3800, 47.2004, 0.6120, 58.7316, 0.4919, 20.8722, 1.3840, 19.4922, 1.4820, 5.39e-16, 5.98e-16, 4.79e-16, nan ],
[ 3900, 47.3205, 0.6430, 58.6235, 0.5190, 21.7973, 1.3959, 21.8122, 1.3950, 4.66e-16, 6.41e-16, 4.66e-16, nan ],
[ 4000, 47.5731, 0.6728, 59.4822, 0.5381, 22.1208, 1.4470, 19.5303, 1.6389, 5.12e-16, 5.68e-16, 5.12e-16, nan ],
[ 4100, 46.7817, 0.7188, 58.5743, 0.5741, 18.2278, 1.8449, 22.0214, 1.5271, 4.99e-16, 5.55e-16, 5.55e-16, nan ],
[ 4200, 46.9874, 0.7510, 63.6877, 0.5541, 18.8596, 1.8711, 20.8553, 1.6921, 7.04e-16, 5.41e-16, 5.41e-16, nan ],
[ 4300, 47.0696, 0.7858, 63.3489, 0.5839, 19.4486, 1.9019, 23.7728, 1.5559, 6.35e-16, 6.35e-16, 4.76e-16, nan ],
[ 4400, 48.2879, 0.8020, 64.0285, 0.6049, 19.9216, 1.9441, 24.7660, 1.5638, 5.68e-16, 5.17e-16, 5.68e-16, nan ],
[ 4500, 48.4480, 0.8361, 64.1885, 0.6311, 20.1145, 2.0139, 26.0474, 1.5552, 6.06e-16, 6.57e-16, 5.56e-16, nan ],
[ 4600, 49.2760, 0.8590, 64.8198, 0.6530, 20.7602, 2.0390, 26.9451, 1.5709, 4.94e-16, 6.43e-16, 5.93e-16, nan ],
[ 4700, 48.6722, 0.9079, 64.6022, 0.6840, 21.1943, 2.0850, 25.4978, 1.7331, 5.81e-16, 5.32e-16, 5.81e-16, nan ],
[ 4800, 50.0943, 0.9201, 66.3169, 0.6950, 21.4080, 2.1529, 25.7477, 1.7900, 6.16e-16, 5.68e-16, 5.68e-16, nan ],
[ 4900, 49.9756, 0.9611, 66.0714, 0.7269, 21.8399, 2.1992, 26.3198, 1.8249, 6.50e-16, 6.50e-16, 6.03e-16, nan ],
[ 5000, 49.8709, 1.0028, 66.2530, 0.7548, 22.3170, 2.2409, 26.8438, 1.8630, 6.37e-16, 5.46e-16, 6.37e-16, nan ],
[ 5100, 50.9170, 1.0219, 65.6135, 0.7930, 22.7394, 2.2881, 26.0015, 2.0010, 8.47e-16, 7.58e-16, 6.24e-16, nan ],
[ 5200, 50.8909, 1.0629, 66.8646, 0.8090, 19.7847, 2.7339, 25.9430, 2.0850, 7.00e-16, 6.12e-16, 7.43e-16, nan ],
[ 5300, 51.0352, 1.1010, 66.7272, 0.8421, 20.1402, 2.7900, 21.0843, 2.6650, 6.44e-16, 6.44e-16, 5.58e-16, nan ],
[ 5400, 51.2586, 1.1380, 67.3430, 0.8662, 20.3660, 2.8641, 26.8441, 2.1729, 8.42e-16, 6.74e-16, 7.58e-16, nan ],
[ 5500, 51.3249, 1.1790, 67.3929, 0.8979, 20.8530, 2.9018, 26.1732, 2.3119, 8.27e-16, 6.61e-16, 6.61e-16, nan ],
[ 5600, 52.6333, 1.1919, 67.0183, 0.9360, 21.2137, 2.9571, 27.4649, 2.2840, 7.31e-16, 6.50e-16, 7.31e-16, nan ],
[ 5700, 52.7975, 1.2310, 67.7757, 0.9589, 21.3297, 3.0470, 26.4834, 2.4540, 7.18e-16, 6.38e-16, 5.58e-16, nan ],
[ 5800, 52.9832, 1.2701, 67.7650, 0.9930, 21.6161, 3.1130, 26.7350, 2.5170, 7.84e-16, 7.84e-16, 7.84e-16, nan ],
[ 5900, 53.2368, 1.3080, 67.1550, 1.0369, 22.0987, 3.1509, 27.4490, 2.5368, 7.71e-16, 7.71e-16, 6.94e-16, nan ],
[ 6000, 53.5817, 1.3440, 67.1051, 1.0731, 22.5101, 3.1991, 26.7316, 2.6939, 6.82e-16, 6.82e-16, 6.06e-16, nan ],
[ 6100, 54.0123, 1.3781, 68.2833, 1.0900, 22.7131, 3.2771, 26.1357, 2.8479, 7.45e-16, 6.71e-16, 7.45e-16, nan ],
[ 6200, 54.3770, 1.4141, 67.1616, 1.1449, 20.2137, 3.8040, 25.8380, 2.9759, 8.07e-16, 7.33e-16, 6.60e-16, nan ],
[ 6300, 55.2050, 1.4381, 66.5594, 1.1928, 20.5897, 3.8559, 26.9132, 2.9500, 8.66e-16, 7.22e-16, 8.66e-16, nan ],
[ 6400, 55.2139, 1.4839, 67.2639, 1.2181, 20.8210, 3.9351, 27.7093, 2.9569, 7.11e-16, 8.53e-16, 7.11e-16, nan ],
[ 6500, 55.9724, 1.5099, 68.2073, 1.2391, 20.9092, 4.0419, 26.0126, 3.2489, 7.70e-16, 8.40e-16, 7.70e-16, nan ],
[ 6600, 56.8372, 1.5330, 68.4004, 1.2739, 21.3621, 4.0789, 27.3060, 3.1910, 8.27e-16, 7.58e-16, 6.89e-16, nan ],
[ 6700, 56.9000, 1.5781, 68.1790, 1.3170, 21.6312, 4.1511, 26.8440, 3.3450, 8.14e-16, 7.47e-16, 6.79e-16, nan ],
[ 6800, 55.6195, 1.6630, 68.3124, 1.3540, 21.8549, 4.2322, 27.4051, 3.3751, 7.36e-16, 6.69e-16, 6.69e-16, nan ],
[ 6900, 57.5395, 1.6551, 67.6443, 1.4079, 22.1677, 4.2961, 27.5970, 3.4509, 7.25e-16, 7.25e-16, 7.25e-16, nan ],
[ 7000, 57.1529, 1.7149, 68.4369, 1.4322, 22.5113, 4.3540, 27.9242, 3.5100, 8.45e-16, 8.45e-16, 8.45e-16, nan ],
[ 7100, 57.6827, 1.7481, 68.1704, 1.4791, 22.7675, 4.4289, 26.5559, 3.7971, 7.69e-16, 8.97e-16, 7.05e-16, nan ],
[ 7200, 58.5522, 1.7710, 68.8937, 1.5051, 20.4123, 5.0800, 27.1371, 3.8211, 7.58e-16, 9.47e-16, 8.21e-16, nan ],
[ 7300, 58.6040, 1.8189, 69.1234, 1.5421, 20.7101, 5.1470, 28.1561, 3.7858, 8.72e-16, 9.34e-16, 8.10e-16, nan ],
[ 7400, 59.0821, 1.8539, 68.8892, 1.5900, 20.5044, 5.3420, 27.5962, 3.9692, 7.37e-16, 8.60e-16, 7.37e-16, nan ],
[ 7500, 59.1604, 1.9019, 68.4342, 1.6441, 21.0661, 5.3411, 26.3555, 4.2691, 8.49e-16, 8.49e-16, 6.67e-16, nan ],
[ 7600, 60.3024, 1.9159, 69.6050, 1.6599, 21.6518, 5.3360, 27.7654, 4.1611, 8.38e-16, 7.78e-16, 6.58e-16, nan ],
[ 7700, 59.2384, 2.0020, 68.9910, 1.7190, 21.6847, 5.4691, 27.6778, 4.2849, 9.45e-16, 7.68e-16, 8.27e-16, nan ],
[ 7800, 59.5947, 2.0421, 69.1825, 1.7591, 22.1550, 5.4929, 27.5030, 4.4248, 8.16e-16, 7.58e-16, 7.00e-16, nan ],
[ 7900, 58.9705, 2.1169, 69.8132, 1.7881, 22.3122, 5.5950, 26.8471, 4.6499, 8.63e-16, 8.63e-16, 6.91e-16, nan ],
[ 8000, 59.4287, 2.1541, 69.3898, 1.8449, 22.5216, 5.6841, 27.6558, 4.6289, 8.53e-16, 8.53e-16, 7.39e-16, nan ],
[ 8100, 60.2830, 2.1770, 70.1114, 1.8718, 22.7842, 5.7600, 28.1313, 4.6651, 7.86e-16, 7.86e-16, 7.30e-16, nan ],
[ 8200, 59.6194, 2.2559, 70.0856, 1.9190, 20.5868, 6.5331, 22.7734, 5.9059, 7.21e-16, 9.43e-16, 7.76e-16, nan ],
[ 8300, 60.4056, 2.2812, 72.1009, 1.9112, 21.0061, 6.5598, 28.1274, 4.8990, 9.31e-16, 8.22e-16, 6.57e-16, nan ],
[ 8400, 59.3990, 2.3761, 71.9721, 1.9610, 21.2427, 6.6440, 27.4365, 5.1441, 8.12e-16, 7.58e-16, 6.50e-16, nan ],
[ 8500, 60.9255, 2.3720, 71.1943, 2.0299, 21.3967, 6.7542, 28.2534, 5.1150, 8.02e-16, 8.56e-16, 6.95e-16, nan ],
[ 8600, 60.3065, 2.4531, 71.5019, 2.0690, 21.7138, 6.8130, 28.5035, 5.1901, 9.52e-16, 1.22e-15, 1.00e-15, nan ],
[ 8700, 59.8386, 2.5301, 72.5142, 2.0878, 21.8689, 6.9230, 27.6078, 5.4839, 8.89e-16, 7.84e-16, 6.27e-16, nan ],
[ 8800, 59.3485, 2.6100, 71.5515, 2.1648, 22.1313, 6.9990, 28.6370, 5.4090, 9.30e-16, 7.75e-16, 9.82e-16, nan ],
[ 8900, 59.9221, 2.6441, 72.4843, 2.1858, 22.3374, 7.0930, 27.1905, 5.8270, 1.02e-15, 9.20e-16, 7.66e-16, nan ],
[ 9000, 60.3618, 2.6841, 72.7183, 2.2280, 22.2585, 7.2789, 28.3845, 5.7080, 8.59e-16, 8.08e-16, 8.08e-16, nan ],
[ 10000, 61.7143, 3.2411, 73.0279, 2.7390, 22.5196, 8.8820, 28.5462, 7.0069, 1.14e-15, 9.09e-16, 8.64e-16, nan ],
[ 12000, 63.0545, 4.5679, 72.7879, 3.9570, 21.8069, 13.2079, 29.3753, 9.8050, 1.14e-15, 9.09e-16, 9.09e-16, nan ],
[ 14000, 65.7109, 5.9659, 74.4863, 5.2631, 21.9859, 17.8308, 28.8446, 13.5911, 1.30e-15, 1.10e-15, 1.17e-15, nan ],
[ 16000, 66.5144, 7.6981, 74.4563, 6.8769, 22.5446, 22.7120, 27.4934, 18.6238, 1.14e-15, 1.08e-15, 1.02e-15, nan ],
[ 18000, 66.7238, 9.7122, 74.8839, 8.6539, 22.1036, 29.3181, 28.9651, 22.3730, 1.26e-15, 1.52e-15, 1.16e-15, nan ],
[ 20000, 68.4330, 11.6909, 75.0797, 10.6559, 21.3961, 37.3919, 29.8946, 26.7620, 1.50e-15, 1.27e-15, 1.27e-15, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/log.txt
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/setup.txt
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/sgeev.txt
# numactl --interleave=all ./testing_sgeev -RN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
sgeev_RN = array([
[ 10, nan, 0.0004 ],
[ 20, nan, 0.0006 ],
[ 30, nan, 0.0011 ],
[ 40, nan, 0.0036 ],
[ 50, nan, 0.0042 ],
[ 60, nan, 0.0034 ],
[ 70, nan, 0.0053 ],
[ 80, nan, 0.0086 ],
[ 90, nan, 0.0090 ],
[ 100, nan, 0.0116 ],
[ 200, nan, 0.0490 ],
[ 300, nan, 0.0948 ],
[ 400, nan, 0.1523 ],
[ 500, nan, 0.1948 ],
[ 600, nan, 0.4105 ],
[ 700, nan, 0.4940 ],
[ 800, nan, 0.6075 ],
[ 900, nan, 0.7507 ],
[ 1000, nan, 0.8398 ],
[ 2000, nan, 1.6267 ],
[ 3000, nan, 4.3466 ],
[ 4000, nan, 6.6281 ],
[ 5000, nan, 10.1955 ],
[ 6000, nan, 19.1285 ],
[ 7000, nan, 24.9622 ],
[ 8000, nan, 32.9550 ],
[ 9000, nan, 41.3171 ],
[ 10000, nan, 47.8675 ],
[ 12000, nan, 67.5161 ],
[ 14000, nan, 93.7432 ],
[ 16000, nan, 126.4203 ],
[ 18000, nan, 160.5888 ],
[ 20000, nan, 206.5202 ],
])
# numactl --interleave=all ./testing_sgeev -RV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
sgeev_RV = array([
[ 10, nan, 0.0015 ],
[ 20, nan, 0.0016 ],
[ 30, nan, 0.0021 ],
[ 40, nan, 0.0041 ],
[ 50, nan, 0.0062 ],
[ 60, nan, 0.0053 ],
[ 70, nan, 0.0061 ],
[ 80, nan, 0.0083 ],
[ 90, nan, 0.0091 ],
[ 100, nan, 0.0121 ],
[ 200, nan, 0.0433 ],
[ 300, nan, 0.1046 ],
[ 400, nan, 0.1237 ],
[ 500, nan, 0.1746 ],
[ 600, nan, 0.2825 ],
[ 700, nan, 0.4077 ],
[ 800, nan, 0.4491 ],
[ 900, nan, 0.6653 ],
[ 1000, nan, 0.6913 ],
[ 2000, nan, 2.1403 ],
[ 3000, nan, 5.4876 ],
[ 4000, nan, 12.0730 ],
[ 5000, nan, 14.5700 ],
[ 6000, nan, 25.0527 ],
[ 7000, nan, 33.2062 ],
[ 8000, nan, 44.9840 ],
[ 9000, nan, 55.8217 ],
[ 10000, nan, 67.7477 ],
[ 12000, nan, 98.0590 ],
[ 14000, nan, 138.1966 ],
[ 16000, nan, 186.6003 ],
[ 18000, nan, 251.4918 ],
[ 20000, nan, 323.1083 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/sgeqrf.txt
# numactl --interleave=all ./testing_sgeqrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
sgeqrf = array([
[ 10, 10, nan, nan, 0.01, 0.00, nan ],
[ 20, 20, nan, nan, 0.04, 0.00, nan ],
[ 30, 30, nan, nan, 0.12, 0.00, nan ],
[ 40, 40, nan, nan, 1.03, 0.00, nan ],
[ 50, 50, nan, nan, 1.44, 0.00, nan ],
[ 60, 60, nan, nan, 2.17, 0.00, nan ],
[ 70, 70, nan, nan, 2.50, 0.00, nan ],
[ 80, 80, nan, nan, 1.47, 0.00, nan ],
[ 90, 90, nan, nan, 1.75, 0.00, nan ],
[ 100, 100, nan, nan, 1.50, 0.00, nan ],
[ 200, 200, nan, nan, 6.31, 0.00, nan ],
[ 300, 300, nan, nan, 14.22, 0.00, nan ],
[ 400, 400, nan, nan, 25.10, 0.00, nan ],
[ 500, 500, nan, nan, 37.82, 0.00, nan ],
[ 600, 600, nan, nan, 54.27, 0.01, nan ],
[ 700, 700, nan, nan, 68.37, 0.01, nan ],
[ 800, 800, nan, nan, 84.13, 0.01, nan ],
[ 900, 900, nan, nan, 103.83, 0.01, nan ],
[ 1000, 1000, nan, nan, 119.84, 0.01, nan ],
[ 2000, 2000, nan, nan, 338.30, 0.03, nan ],
[ 3000, 3000, nan, nan, 571.34, 0.06, nan ],
[ 4000, 4000, nan, nan, 729.00, 0.12, nan ],
[ 5000, 5000, nan, nan, 904.31, 0.18, nan ],
[ 6000, 6000, nan, nan, 1031.58, 0.28, nan ],
[ 7000, 7000, nan, nan, 1109.99, 0.41, nan ],
[ 8000, 8000, nan, nan, 1303.37, 0.52, nan ],
[ 9000, 9000, nan, nan, 1431.33, 0.68, nan ],
[ 10000, 10000, nan, nan, 1526.08, 0.87, nan ],
[ 12000, 12000, nan, nan, 1685.03, 1.37, nan ],
[ 14000, 14000, nan, nan, 1767.31, 2.07, nan ],
[ 16000, 16000, nan, nan, 1886.81, 2.89, nan ],
[ 18000, 18000, nan, nan, 1885.45, 4.12, nan ],
[ 20000, 20000, nan, nan, 1989.43, 5.36, nan ],
])
# numactl --interleave=all ./testing_sgeqrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
sgeqrf_gpu = array([
[ 10, 10, nan, nan, 0.00, 0.00, nan ],
[ 20, 20, nan, nan, 0.01, 0.00, nan ],
[ 30, 30, nan, nan, 0.03, 0.00, nan ],
[ 40, 40, nan, nan, 0.07, 0.00, nan ],
[ 50, 50, nan, nan, 0.13, 0.00, nan ],
[ 60, 60, nan, nan, 0.20, 0.00, nan ],
[ 70, 70, nan, nan, 0.30, 0.00, nan ],
[ 80, 80, nan, nan, 0.43, 0.00, nan ],
[ 90, 90, nan, nan, 0.57, 0.00, nan ],
[ 100, 100, nan, nan, 0.61, 0.00, nan ],
[ 200, 200, nan, nan, 6.25, 0.00, nan ],
[ 300, 300, nan, nan, 13.31, 0.00, nan ],
[ 400, 400, nan, nan, 21.97, 0.00, nan ],
[ 500, 500, nan, nan, 25.64, 0.01, nan ],
[ 600, 600, nan, nan, 38.07, 0.01, nan ],
[ 700, 700, nan, nan, 48.45, 0.01, nan ],
[ 800, 800, nan, nan, 62.14, 0.01, nan ],
[ 900, 900, nan, nan, 74.98, 0.01, nan ],
[ 1000, 1000, nan, nan, 90.56, 0.01, nan ],
[ 2000, 2000, nan, nan, 257.53, 0.04, nan ],
[ 3000, 3000, nan, nan, 455.14, 0.08, nan ],
[ 4000, 4000, nan, nan, 643.10, 0.13, nan ],
[ 5000, 5000, nan, nan, 846.73, 0.20, nan ],
[ 6000, 6000, nan, nan, 986.20, 0.29, nan ],
[ 7000, 7000, nan, nan, 1062.77, 0.43, nan ],
[ 8000, 8000, nan, nan, 1305.88, 0.52, nan ],
[ 9000, 9000, nan, nan, 1409.01, 0.69, nan ],
[ 10000, 10000, nan, nan, 1480.54, 0.90, nan ],
[ 12000, 12000, nan, nan, 1568.22, 1.47, nan ],
[ 14000, 14000, nan, nan, 1680.74, 2.18, nan ],
[ 16000, 16000, nan, nan, 1836.92, 2.97, nan ],
[ 18000, 18000, nan, nan, 1877.23, 4.14, nan ],
[ 20000, 20000, nan, nan, 1970.03, 5.41, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/sgesvd.txt
# numactl --interleave=all ./testing_sgesvd -UN -VN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
sgesvd_UN = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.01, nan ],
[ nan, 300, 300, nan, 0.03, nan ],
[ nan, 400, 400, nan, 0.04, nan ],
[ nan, 500, 500, nan, 0.06, nan ],
[ nan, 600, 600, nan, 0.08, nan ],
[ nan, 700, 700, nan, 0.11, nan ],
[ nan, 800, 800, nan, 0.14, nan ],
[ nan, 900, 900, nan, 0.17, nan ],
[ nan, 1000, 1000, nan, 0.21, nan ],
[ nan, 2000, 2000, nan, 0.76, nan ],
[ nan, 3000, 3000, nan, 1.77, nan ],
[ nan, 4000, 4000, nan, 3.33, nan ],
[ nan, 5000, 5000, nan, 6.01, nan ],
[ nan, 6000, 6000, nan, 9.44, nan ],
[ nan, 7000, 7000, nan, 14.09, nan ],
[ nan, 8000, 8000, nan, 19.90, nan ],
[ nan, 9000, 9000, nan, 27.19, nan ],
[ nan, 10000, 10000, nan, 36.20, nan ],
[ nan, 12000, 12000, nan, 58.91, nan ],
[ nan, 14000, 14000, nan, 90.76, nan ],
[ nan, 16000, 16000, nan, 132.79, nan ],
[ nan, 18000, 18000, nan, 187.07, nan ],
[ nan, 20000, 20000, nan, 252.82, nan ],
[ nan, 300, 100, nan, 0.03, nan ],
[ nan, 600, 200, nan, 0.01, nan ],
[ nan, 900, 300, nan, 0.03, nan ],
[ nan, 1200, 400, nan, 0.05, nan ],
[ nan, 1500, 500, nan, 0.07, nan ],
[ nan, 1800, 600, nan, 0.10, nan ],
[ nan, 2100, 700, nan, 0.13, nan ],
[ nan, 2400, 800, nan, 0.16, nan ],
[ nan, 2700, 900, nan, 0.21, nan ],
[ nan, 3000, 1000, nan, 0.25, nan ],
[ nan, 6000, 2000, nan, 0.98, nan ],
[ nan, 9000, 3000, nan, 2.41, nan ],
[ nan, 12000, 4000, nan, 4.98, nan ],
[ nan, 15000, 5000, nan, 8.80, nan ],
[ nan, 18000, 6000, nan, 14.20, nan ],
[ nan, 21000, 7000, nan, 19.71, nan ],
[ nan, 24000, 8000, nan, 29.24, nan ],
[ nan, 27000, 9000, nan, 38.47, nan ],
[ nan, 100, 300, nan, 0.00, nan ],
[ nan, 200, 600, nan, 0.02, nan ],
[ nan, 300, 900, nan, 0.04, nan ],
[ nan, 400, 1200, nan, 0.06, nan ],
[ nan, 500, 1500, nan, 0.08, nan ],
[ nan, 600, 1800, nan, 0.11, nan ],
[ nan, 700, 2100, nan, 0.15, nan ],
[ nan, 800, 2400, nan, 0.18, nan ],
[ nan, 900, 2700, nan, 0.23, nan ],
[ nan, 1000, 3000, nan, 0.29, nan ],
[ nan, 2000, 6000, nan, 1.07, nan ],
[ nan, 3000, 9000, nan, 2.65, nan ],
[ nan, 4000, 12000, nan, 5.15, nan ],
[ nan, 5000, 15000, nan, 9.39, nan ],
[ nan, 6000, 18000, nan, 14.60, nan ],
[ nan, 7000, 21000, nan, 22.08, nan ],
[ nan, 8000, 24000, nan, 31.03, nan ],
[ nan, 9000, 27000, nan, 42.65, nan ],
[ nan, 10000, 100, nan, 0.01, nan ],
[ nan, 20000, 200, nan, 0.04, nan ],
[ nan, 30000, 300, nan, 0.09, nan ],
[ nan, 40000, 400, nan, 0.21, nan ],
[ nan, 50000, 500, nan, 0.33, nan ],
[ nan, 60000, 600, nan, 0.49, nan ],
[ nan, 70000, 700, nan, 0.69, nan ],
[ nan, 80000, 800, nan, 0.96, nan ],
[ nan, 90000, 900, nan, 1.32, nan ],
[ nan, 100000, 1000, nan, 1.67, nan ],
[ nan, 200000, 2000, nan, 9.11, nan ],
[ nan, 100, 10000, nan, 0.01, nan ],
[ nan, 200, 20000, nan, 0.05, nan ],
[ nan, 300, 30000, nan, 0.13, nan ],
[ nan, 400, 40000, nan, 0.26, nan ],
[ nan, 500, 50000, nan, 0.45, nan ],
[ nan, 600, 60000, nan, 0.68, nan ],
[ nan, 700, 70000, nan, 1.07, nan ],
[ nan, 800, 80000, nan, 1.31, nan ],
[ nan, 900, 90000, nan, 1.64, nan ],
[ nan, 1000, 100000, nan, 2.05, nan ],
[ nan, 2000, 200000, nan, 12.39, nan ],
])
# numactl --interleave=all ./testing_sgesvd -US -VS -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
sgesvd_US = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.01, nan ],
[ nan, 70, 70, nan, 0.01, nan ],
[ nan, 80, 80, nan, 0.01, nan ],
[ nan, 90, 90, nan, 0.02, nan ],
[ nan, 100, 100, nan, 0.02, nan ],
[ nan, 200, 200, nan, 0.08, nan ],
[ nan, 300, 300, nan, 0.05, nan ],
[ nan, 400, 400, nan, 0.08, nan ],
[ nan, 500, 500, nan, 0.12, nan ],
[ nan, 600, 600, nan, 0.18, nan ],
[ nan, 700, 700, nan, 0.24, nan ],
[ nan, 800, 800, nan, 0.29, nan ],
[ nan, 900, 900, nan, 0.37, nan ],
[ nan, 1000, 1000, nan, 0.50, nan ],
[ nan, 2000, 2000, nan, 2.26, nan ],
[ nan, 3000, 3000, nan, 6.63, nan ],
[ nan, 4000, 4000, nan, 15.08, nan ],
[ nan, 5000, 5000, nan, 26.60, nan ],
[ nan, 6000, 6000, nan, 47.03, nan ],
[ nan, 7000, 7000, nan, 71.89, nan ],
[ nan, 8000, 8000, nan, 99.61, nan ],
[ nan, 9000, 9000, nan, 139.39, nan ],
[ nan, 10000, 10000, nan, 191.95, nan ],
[ nan, 12000, 12000, nan, 320.06, nan ],
[ nan, 14000, 14000, nan, 493.71, nan ],
[ nan, 16000, 16000, nan, 659.14, nan ],
[ nan, 18000, 18000, nan, 1009.44, nan ],
[ nan, 20000, 20000, nan, 1340.65, nan ],
[ nan, 300, 100, nan, 0.10, nan ],
[ nan, 600, 200, nan, 0.08, nan ],
[ nan, 900, 300, nan, 0.07, nan ],
[ nan, 1200, 400, nan, 0.10, nan ],
[ nan, 1500, 500, nan, 0.16, nan ],
[ nan, 1800, 600, nan, 0.24, nan ],
[ nan, 2100, 700, nan, 0.33, nan ],
[ nan, 2400, 800, nan, 0.41, nan ],
[ nan, 2700, 900, nan, 0.53, nan ],
[ nan, 3000, 1000, nan, 0.67, nan ],
[ nan, 6000, 2000, nan, 3.38, nan ],
[ nan, 9000, 3000, nan, 8.20, nan ],
[ nan, 12000, 4000, nan, 18.20, nan ],
[ nan, 15000, 5000, nan, 31.61, nan ],
[ nan, 18000, 6000, nan, 56.63, nan ],
[ nan, 21000, 7000, nan, 83.85, nan ],
[ nan, 24000, 8000, nan, 112.83, nan ],
[ nan, 27000, 9000, nan, 169.79, nan ],
[ nan, 100, 300, nan, 0.02, nan ],
[ nan, 200, 600, nan, 0.08, nan ],
[ nan, 300, 900, nan, 0.07, nan ],
[ nan, 400, 1200, nan, 0.12, nan ],
[ nan, 500, 1500, nan, 0.19, nan ],
[ nan, 600, 1800, nan, 0.28, nan ],
[ nan, 700, 2100, nan, 0.40, nan ],
[ nan, 800, 2400, nan, 0.50, nan ],
[ nan, 900, 2700, nan, 0.64, nan ],
[ nan, 1000, 3000, nan, 0.80, nan ],
[ nan, 2000, 6000, nan, 3.90, nan ],
[ nan, 3000, 9000, nan, 9.64, nan ],
[ nan, 4000, 12000, nan, 20.47, nan ],
[ nan, 5000, 15000, nan, 37.20, nan ],
[ nan, 6000, 18000, nan, 65.37, nan ],
[ nan, 7000, 21000, nan, 97.80, nan ],
[ nan, 8000, 24000, nan, 150.90, nan ],
[ nan, 9000, 27000, nan, 217.87, nan ],
[ nan, 10000, 100, nan, 0.04, nan ],
[ nan, 20000, 200, nan, 0.21, nan ],
[ nan, 30000, 300, nan, 0.29, nan ],
[ nan, 40000, 400, nan, 0.58, nan ],
[ nan, 50000, 500, nan, 1.00, nan ],
[ nan, 60000, 600, nan, 1.53, nan ],
[ nan, 70000, 700, nan, 2.22, nan ],
[ nan, 80000, 800, nan, 3.21, nan ],
[ nan, 90000, 900, nan, 4.54, nan ],
[ nan, 100000, 1000, nan, 5.80, nan ],
[ nan, 200000, 2000, nan, 40.23, nan ],
[ nan, 100, 10000, nan, 0.07, nan ],
[ nan, 200, 20000, nan, 0.35, nan ],
[ nan, 300, 30000, nan, 0.52, nan ],
[ nan, 400, 40000, nan, 0.91, nan ],
[ nan, 500, 50000, nan, 2.52, nan ],
[ nan, 600, 60000, nan, 3.43, nan ],
[ nan, 700, 70000, nan, 4.40, nan ],
[ nan, 800, 80000, nan, 5.69, nan ],
[ nan, 900, 90000, nan, 7.78, nan ],
[ nan, 1000, 100000, nan, 15.10, nan ],
[ nan, 2000, 200000, nan, 89.97, nan ],
])
# numactl --interleave=all ./testing_sgesdd -UN -VN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
sgesdd_UN = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.01, nan ],
[ nan, 300, 300, nan, 0.03, nan ],
[ nan, 400, 400, nan, 0.04, nan ],
[ nan, 500, 500, nan, 0.06, nan ],
[ nan, 600, 600, nan, 0.08, nan ],
[ nan, 700, 700, nan, 0.10, nan ],
[ nan, 800, 800, nan, 0.13, nan ],
[ nan, 900, 900, nan, 0.17, nan ],
[ nan, 1000, 1000, nan, 0.20, nan ],
[ nan, 2000, 2000, nan, 0.75, nan ],
[ nan, 3000, 3000, nan, 1.76, nan ],
[ nan, 4000, 4000, nan, 3.32, nan ],
[ nan, 5000, 5000, nan, 5.97, nan ],
[ nan, 6000, 6000, nan, 9.46, nan ],
[ nan, 7000, 7000, nan, 14.06, nan ],
[ nan, 8000, 8000, nan, 19.93, nan ],
[ nan, 9000, 9000, nan, 27.21, nan ],
[ nan, 10000, 10000, nan, 36.27, nan ],
[ nan, 12000, 12000, nan, 59.08, nan ],
[ nan, 14000, 14000, nan, 91.02, nan ],
[ nan, 16000, 16000, nan, 133.15, nan ],
[ nan, 18000, 18000, nan, 187.29, nan ],
[ nan, 20000, 20000, nan, 253.30, nan ],
[ nan, 300, 100, nan, 0.00, nan ],
[ nan, 600, 200, nan, 0.02, nan ],
[ nan, 900, 300, nan, 0.03, nan ],
[ nan, 1200, 400, nan, 0.05, nan ],
[ nan, 1500, 500, nan, 0.07, nan ],
[ nan, 1800, 600, nan, 0.09, nan ],
[ nan, 2100, 700, nan, 0.12, nan ],
[ nan, 2400, 800, nan, 0.15, nan ],
[ nan, 2700, 900, nan, 0.20, nan ],
[ nan, 3000, 1000, nan, 0.24, nan ],
[ nan, 6000, 2000, nan, 0.97, nan ],
[ nan, 9000, 3000, nan, 2.39, nan ],
[ nan, 12000, 4000, nan, 4.61, nan ],
[ nan, 15000, 5000, nan, 8.27, nan ],
[ nan, 18000, 6000, nan, 13.19, nan ],
[ nan, 21000, 7000, nan, 19.71, nan ],
[ nan, 24000, 8000, nan, 28.21, nan ],
[ nan, 27000, 9000, nan, 38.61, nan ],
[ nan, 100, 300, nan, 0.00, nan ],
[ nan, 200, 600, nan, 0.02, nan ],
[ nan, 300, 900, nan, 0.04, nan ],
[ nan, 400, 1200, nan, 0.06, nan ],
[ nan, 500, 1500, nan, 0.08, nan ],
[ nan, 600, 1800, nan, 0.11, nan ],
[ nan, 700, 2100, nan, 0.14, nan ],
[ nan, 800, 2400, nan, 0.18, nan ],
[ nan, 900, 2700, nan, 0.22, nan ],
[ nan, 1000, 3000, nan, 0.27, nan ],
[ nan, 2000, 6000, nan, 1.05, nan ],
[ nan, 3000, 9000, nan, 2.63, nan ],
[ nan, 4000, 12000, nan, 5.01, nan ],
[ nan, 5000, 15000, nan, 9.11, nan ],
[ nan, 6000, 18000, nan, 14.50, nan ],
[ nan, 7000, 21000, nan, 21.97, nan ],
[ nan, 8000, 24000, nan, 30.87, nan ],
[ nan, 9000, 27000, nan, 42.54, nan ],
[ nan, 10000, 100, nan, 0.01, nan ],
[ nan, 20000, 200, nan, 0.04, nan ],
[ nan, 30000, 300, nan, 0.09, nan ],
[ nan, 40000, 400, nan, 0.21, nan ],
[ nan, 50000, 500, nan, 0.33, nan ],
[ nan, 60000, 600, nan, 0.49, nan ],
[ nan, 70000, 700, nan, 0.70, nan ],
[ nan, 80000, 800, nan, 0.96, nan ],
[ nan, 90000, 900, nan, 1.31, nan ],
[ nan, 100000, 1000, nan, 1.65, nan ],
[ nan, 200000, 2000, nan, 9.10, nan ],
[ nan, 100, 10000, nan, 0.01, nan ],
[ nan, 200, 20000, nan, 0.05, nan ],
[ nan, 300, 30000, nan, 0.13, nan ],
[ nan, 400, 40000, nan, 0.25, nan ],
[ nan, 500, 50000, nan, 0.44, nan ],
[ nan, 600, 60000, nan, 0.68, nan ],
[ nan, 700, 70000, nan, 1.06, nan ],
[ nan, 800, 80000, nan, 1.29, nan ],
[ nan, 900, 90000, nan, 1.61, nan ],
[ nan, 1000, 100000, nan, 2.02, nan ],
[ nan, 2000, 200000, nan, 12.42, nan ],
])
# numactl --interleave=all ./testing_sgesdd -US -VS -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
sgesdd_US = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.02, nan ],
[ nan, 300, 300, nan, 0.04, nan ],
[ nan, 400, 400, nan, 0.06, nan ],
[ nan, 500, 500, nan, 0.09, nan ],
[ nan, 600, 600, nan, 0.12, nan ],
[ nan, 700, 700, nan, 0.16, nan ],
[ nan, 800, 800, nan, 0.21, nan ],
[ nan, 900, 900, nan, 0.27, nan ],
[ nan, 1000, 1000, nan, 0.32, nan ],
[ nan, 2000, 2000, nan, 1.23, nan ],
[ nan, 3000, 3000, nan, 2.88, nan ],
[ nan, 4000, 4000, nan, 5.40, nan ],
[ nan, 5000, 5000, nan, 9.84, nan ],
[ nan, 6000, 6000, nan, 14.44, nan ],
[ nan, 7000, 7000, nan, 0.00, nan ],
[ nan, 8000, 8000, nan, 29.12, nan ],
[ nan, 9000, 9000, nan, 38.77, nan ],
[ nan, 10000, 10000, nan, 50.51, nan ],
[ nan, 12000, 12000, nan, 79.90, nan ],
[ nan, 14000, 14000, nan, 0.00, nan ],
[ nan, 16000, 16000, nan, 170.35, nan ],
[ nan, 18000, 18000, nan, 234.33, nan ],
[ nan, 20000, 20000, nan, 310.26, nan ],
[ nan, 300, 100, nan, 0.01, nan ],
[ nan, 600, 200, nan, 0.02, nan ],
[ nan, 900, 300, nan, 0.04, nan ],
[ nan, 1200, 400, nan, 0.07, nan ],
[ nan, 1500, 500, nan, 0.10, nan ],
[ nan, 1800, 600, nan, 0.15, nan ],
[ nan, 2100, 700, nan, 0.20, nan ],
[ nan, 2400, 800, nan, 0.24, nan ],
[ nan, 2700, 900, nan, 0.33, nan ],
[ nan, 3000, 1000, nan, 0.41, nan ],
[ nan, 6000, 2000, nan, 1.77, nan ],
[ nan, 9000, 3000, nan, 4.21, nan ],
[ nan, 12000, 4000, nan, 8.15, nan ],
[ nan, 15000, 5000, nan, 14.27, nan ],
[ nan, 18000, 6000, nan, 23.12, nan ],
[ nan, 21000, 7000, nan, 0.00, nan ],
[ nan, 24000, 8000, nan, 48.00, nan ],
[ nan, 27000, 9000, nan, 64.77, nan ],
[ nan, 100, 300, nan, 0.01, nan ],
[ nan, 200, 600, nan, 0.02, nan ],
[ nan, 300, 900, nan, 0.05, nan ],
[ nan, 400, 1200, nan, 0.08, nan ],
[ nan, 500, 1500, nan, 0.12, nan ],
[ nan, 600, 1800, nan, 0.17, nan ],
[ nan, 700, 2100, nan, 0.22, nan ],
[ nan, 800, 2400, nan, 0.28, nan ],
[ nan, 900, 2700, nan, 0.36, nan ],
[ nan, 1000, 3000, nan, 0.45, nan ],
[ nan, 2000, 6000, nan, 1.77, nan ],
[ nan, 3000, 9000, nan, 4.40, nan ],
[ nan, 4000, 12000, nan, 8.43, nan ],
[ nan, 5000, 15000, nan, 14.94, nan ],
[ nan, 6000, 18000, nan, 25.70, nan ],
[ nan, 7000, 21000, nan, 0.00, nan ],
[ nan, 8000, 24000, nan, 50.43, nan ],
[ nan, 9000, 27000, nan, 68.50, nan ],
[ nan, 10000, 100, nan, 0.02, nan ],
[ nan, 20000, 200, nan, 0.10, nan ],
[ nan, 30000, 300, nan, 0.18, nan ],
[ nan, 40000, 400, nan, 0.34, nan ],
[ nan, 50000, 500, nan, 0.76, nan ],
[ nan, 60000, 600, nan, 0.99, nan ],
[ nan, 70000, 700, nan, 1.30, nan ],
[ nan, 80000, 800, nan, 1.63, nan ],
[ nan, 90000, 900, nan, 2.18, nan ],
[ nan, 100000, 1000, nan, 3.48, nan ],
[ nan, 200000, 2000, nan, 18.28, nan ],
[ nan, 100, 10000, nan, 0.04, nan ],
[ nan, 200, 20000, nan, 0.18, nan ],
[ nan, 300, 30000, nan, 0.34, nan ],
[ nan, 400, 40000, nan, 0.50, nan ],
[ nan, 500, 50000, nan, 1.85, nan ],
[ nan, 600, 60000, nan, 2.18, nan ],
[ nan, 700, 70000, nan, 2.55, nan ],
[ nan, 800, 80000, nan, 2.72, nan ],
[ nan, 900, 90000, nan, 3.10, nan ],
[ nan, 1000, 100000, nan, 6.57, nan ],
[ nan, 2000, 200000, nan, 26.70, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/sgetrf.txt
# numactl --interleave=all ./testing_sgetrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
sgetrf = array([
[ 10, 10, nan, nan, 0.03, 0.00, nan ],
[ 20, 20, nan, nan, 0.08, 0.00, nan ],
[ 30, 30, nan, nan, 0.45, 0.00, nan ],
[ 40, 40, nan, nan, 0.66, 0.00, nan ],
[ 50, 50, nan, nan, 1.61, 0.00, nan ],
[ 60, 60, nan, nan, 2.50, 0.00, nan ],
[ 70, 70, nan, nan, 2.10, 0.00, nan ],
[ 80, 80, nan, nan, 3.39, 0.00, nan ],
[ 90, 90, nan, nan, 3.33, 0.00, nan ],
[ 100, 100, nan, nan, 4.60, 0.00, nan ],
[ 200, 200, nan, nan, 16.24, 0.00, nan ],
[ 300, 300, nan, nan, 10.97, 0.00, nan ],
[ 400, 400, nan, nan, 21.24, 0.00, nan ],
[ 500, 500, nan, nan, 31.72, 0.00, nan ],
[ 600, 600, nan, nan, 41.11, 0.00, nan ],
[ 700, 700, nan, nan, 54.26, 0.00, nan ],
[ 800, 800, nan, nan, 65.93, 0.01, nan ],
[ 900, 900, nan, nan, 78.59, 0.01, nan ],
[ 1000, 1000, nan, nan, 94.05, 0.01, nan ],
[ 2000, 2000, nan, nan, 240.35, 0.02, nan ],
[ 3000, 3000, nan, nan, 403.41, 0.04, nan ],
[ 4000, 4000, nan, nan, 564.04, 0.08, nan ],
[ 5000, 5000, nan, nan, 656.71, 0.13, nan ],
[ 6000, 6000, nan, nan, 848.49, 0.17, nan ],
[ 7000, 7000, nan, nan, 996.31, 0.23, nan ],
[ 8000, 8000, nan, nan, 1136.85, 0.30, nan ],
[ 9000, 9000, nan, nan, 1244.66, 0.39, nan ],
[ 10000, 10000, nan, nan, 1334.36, 0.50, nan ],
[ 12000, 12000, nan, nan, 1482.65, 0.78, nan ],
[ 14000, 14000, nan, nan, 1598.32, 1.14, nan ],
[ 16000, 16000, nan, nan, 1682.82, 1.62, nan ],
[ 18000, 18000, nan, nan, 1757.24, 2.21, nan ],
[ 20000, 20000, nan, nan, 1896.00, 2.81, nan ],
])
# numactl --interleave=all ./testing_sgetrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
sgetrf_gpu = array([
[ 10, 10, nan, nan, 0.01, 0.00, nan ],
[ 20, 20, nan, nan, 0.05, 0.00, nan ],
[ 30, 30, nan, nan, 0.26, 0.00, nan ],
[ 40, 40, nan, nan, 0.44, 0.00, nan ],
[ 50, 50, nan, nan, 0.84, 0.00, nan ],
[ 60, 60, nan, nan, 1.32, 0.00, nan ],
[ 70, 70, nan, nan, 1.15, 0.00, nan ],
[ 80, 80, nan, nan, 2.17, 0.00, nan ],
[ 90, 90, nan, nan, 2.44, 0.00, nan ],
[ 100, 100, nan, nan, 3.18, 0.00, nan ],
[ 200, 200, nan, nan, 9.15, 0.00, nan ],
[ 300, 300, nan, nan, 8.51, 0.00, nan ],
[ 400, 400, nan, nan, 15.48, 0.00, nan ],
[ 500, 500, nan, nan, 24.88, 0.00, nan ],
[ 600, 600, nan, nan, 34.61, 0.00, nan ],
[ 700, 700, nan, nan, 47.36, 0.00, nan ],
[ 800, 800, nan, nan, 59.18, 0.01, nan ],
[ 900, 900, nan, nan, 73.60, 0.01, nan ],
[ 1000, 1000, nan, nan, 87.99, 0.01, nan ],
[ 2000, 2000, nan, nan, 252.59, 0.02, nan ],
[ 3000, 3000, nan, nan, 455.66, 0.04, nan ],
[ 4000, 4000, nan, nan, 656.97, 0.06, nan ],
[ 5000, 5000, nan, nan, 729.49, 0.11, nan ],
[ 6000, 6000, nan, nan, 944.08, 0.15, nan ],
[ 7000, 7000, nan, nan, 1121.09, 0.20, nan ],
[ 8000, 8000, nan, nan, 1204.28, 0.28, nan ],
[ 9000, 9000, nan, nan, 1418.28, 0.34, nan ],
[ 10000, 10000, nan, nan, 1537.15, 0.43, nan ],
[ 12000, 12000, nan, nan, 1703.22, 0.68, nan ],
[ 14000, 14000, nan, nan, 1819.34, 1.01, nan ],
[ 16000, 16000, nan, nan, 1890.63, 1.44, nan ],
[ 18000, 18000, nan, nan, 1965.96, 1.98, nan ],
[ 20000, 20000, nan, nan, 2106.88, 2.53, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/spotrf.txt
# numactl --interleave=all ./testing_spotrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
spotrf = array([
[ 10, nan, nan, 0.00, 0.00, nan ],
[ 20, nan, nan, 0.01, 0.00, nan ],
[ 30, nan, nan, 0.03, 0.00, nan ],
[ 40, nan, nan, 0.07, 0.00, nan ],
[ 50, nan, nan, 0.14, 0.00, nan ],
[ 60, nan, nan, 0.24, 0.00, nan ],
[ 70, nan, nan, 1.70, 0.00, nan ],
[ 80, nan, nan, 2.26, 0.00, nan ],
[ 90, nan, nan, 2.78, 0.00, nan ],
[ 100, nan, nan, 3.42, 0.00, nan ],
[ 200, nan, nan, 5.43, 0.00, nan ],
[ 300, nan, nan, 6.17, 0.00, nan ],
[ 400, nan, nan, 13.90, 0.00, nan ],
[ 500, nan, nan, 23.99, 0.00, nan ],
[ 600, nan, nan, 25.77, 0.00, nan ],
[ 700, nan, nan, 38.10, 0.00, nan ],
[ 800, nan, nan, 42.09, 0.00, nan ],
[ 900, nan, nan, 53.65, 0.00, nan ],
[ 1000, nan, nan, 72.40, 0.00, nan ],
[ 2000, nan, nan, 285.20, 0.01, nan ],
[ 3000, nan, nan, 537.14, 0.02, nan ],
[ 4000, nan, nan, 817.18, 0.03, nan ],
[ 5000, nan, nan, 1014.83, 0.04, nan ],
[ 6000, nan, nan, 1204.58, 0.06, nan ],
[ 7000, nan, nan, 1345.66, 0.08, nan ],
[ 8000, nan, nan, 1493.26, 0.11, nan ],
[ 9000, nan, nan, 1591.92, 0.15, nan ],
[ 10000, nan, nan, 1687.21, 0.20, nan ],
[ 12000, nan, nan, 1844.47, 0.31, nan ],
[ 14000, nan, nan, 1983.09, 0.46, nan ],
[ 16000, nan, nan, 2086.46, 0.65, nan ],
[ 18000, nan, nan, 2170.56, 0.90, nan ],
[ 20000, nan, nan, 2258.64, 1.18, nan ],
])
# numactl --interleave=all ./testing_spotrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
spotrf_gpu = array([
[ 10, nan, nan, 0.00, 0.00, nan ],
[ 20, nan, nan, 0.00, 0.00, nan ],
[ 30, nan, nan, 0.01, 0.00, nan ],
[ 40, nan, nan, 0.03, 0.00, nan ],
[ 50, nan, nan, 0.05, 0.00, nan ],
[ 60, nan, nan, 0.08, 0.00, nan ],
[ 70, nan, nan, 0.13, 0.00, nan ],
[ 80, nan, nan, 0.19, 0.00, nan ],
[ 90, nan, nan, 0.27, 0.00, nan ],
[ 100, nan, nan, 0.36, 0.00, nan ],
[ 200, nan, nan, 8.99, 0.00, nan ],
[ 300, nan, nan, 4.95, 0.00, nan ],
[ 400, nan, nan, 10.83, 0.00, nan ],
[ 500, nan, nan, 19.35, 0.00, nan ],
[ 600, nan, nan, 22.63, 0.00, nan ],
[ 700, nan, nan, 34.72, 0.00, nan ],
[ 800, nan, nan, 39.50, 0.00, nan ],
[ 900, nan, nan, 53.08, 0.00, nan ],
[ 1000, nan, nan, 68.66, 0.00, nan ],
[ 2000, nan, nan, 287.91, 0.01, nan ],
[ 3000, nan, nan, 592.52, 0.02, nan ],
[ 4000, nan, nan, 916.09, 0.02, nan ],
[ 5000, nan, nan, 1133.76, 0.04, nan ],
[ 6000, nan, nan, 1368.93, 0.05, nan ],
[ 7000, nan, nan, 1511.83, 0.08, nan ],
[ 8000, nan, nan, 1725.48, 0.10, nan ],
[ 9000, nan, nan, 1856.69, 0.13, nan ],
[ 10000, nan, nan, 1950.79, 0.17, nan ],
[ 12000, nan, nan, 2105.77, 0.27, nan ],
[ 14000, nan, nan, 2230.78, 0.41, nan ],
[ 16000, nan, nan, 2336.12, 0.58, nan ],
[ 18000, nan, nan, 2397.51, 0.81, nan ],
[ 20000, nan, nan, 2475.24, 1.08, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/ssyevd.txt
# numactl --interleave=all ./testing_ssyevd -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
ssyevd_JN = array([
[ 10, nan, 0.0000 ],
[ 20, nan, 0.0000 ],
[ 30, nan, 0.0001 ],
[ 40, nan, 0.0001 ],
[ 50, nan, 0.0002 ],
[ 60, nan, 0.0002 ],
[ 70, nan, 0.0003 ],
[ 80, nan, 0.0004 ],
[ 90, nan, 0.0005 ],
[ 100, nan, 0.0006 ],
[ 200, nan, 0.0103 ],
[ 300, nan, 0.0185 ],
[ 400, nan, 0.0315 ],
[ 500, nan, 0.0430 ],
[ 600, nan, 0.0585 ],
[ 700, nan, 0.0732 ],
[ 800, nan, 0.1004 ],
[ 900, nan, 0.1142 ],
[ 1000, nan, 0.1332 ],
[ 2000, nan, 0.4478 ],
[ 3000, nan, 0.9329 ],
[ 4000, nan, 1.5652 ],
[ 5000, nan, 2.5726 ],
[ 6000, nan, 3.8303 ],
[ 7000, nan, 5.3957 ],
[ 8000, nan, 7.2237 ],
[ 9000, nan, 9.5361 ],
[ 10000, nan, 12.2019 ],
[ 12000, nan, 19.3860 ],
[ 14000, nan, 28.1998 ],
[ 16000, nan, 39.8069 ],
[ 18000, nan, 54.8997 ],
[ 20000, nan, 71.6659 ],
])
# numactl --interleave=all ./testing_ssyevd -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
ssyevd_JV = array([
[ 10, nan, 0.0001 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0002 ],
[ 40, nan, 0.0003 ],
[ 50, nan, 0.0004 ],
[ 60, nan, 0.0005 ],
[ 70, nan, 0.0006 ],
[ 80, nan, 0.0007 ],
[ 90, nan, 0.0009 ],
[ 100, nan, 0.0010 ],
[ 200, nan, 0.0131 ],
[ 300, nan, 0.0208 ],
[ 400, nan, 0.0345 ],
[ 500, nan, 0.0467 ],
[ 600, nan, 0.0601 ],
[ 700, nan, 0.0757 ],
[ 800, nan, 0.0954 ],
[ 900, nan, 0.1183 ],
[ 1000, nan, 0.1358 ],
[ 2000, nan, 0.4480 ],
[ 3000, nan, 0.9326 ],
[ 4000, nan, 1.6237 ],
[ 5000, nan, 2.5988 ],
[ 6000, nan, 3.9168 ],
[ 7000, nan, 5.6690 ],
[ 8000, nan, 7.4417 ],
[ 9000, nan, 9.8196 ],
[ 10000, nan, 12.6641 ],
[ 12000, nan, 20.2119 ],
[ 14000, nan, 29.8157 ],
[ 16000, nan, 42.1683 ],
[ 18000, nan, 58.2346 ],
[ 20000, nan, 75.8294 ],
])
# numactl --interleave=all ./testing_ssyevd_gpu -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
ssyevd_gpu_JN = array([
[ 10, nan, 0.0001 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0001 ],
[ 40, nan, 0.0002 ],
[ 50, nan, 0.0002 ],
[ 60, nan, 0.0003 ],
[ 70, nan, 0.0004 ],
[ 80, nan, 0.0005 ],
[ 90, nan, 0.0006 ],
[ 100, nan, 0.0007 ],
[ 200, nan, 0.0101 ],
[ 300, nan, 0.0183 ],
[ 400, nan, 0.0314 ],
[ 500, nan, 0.0431 ],
[ 600, nan, 0.0586 ],
[ 700, nan, 0.0731 ],
[ 800, nan, 0.0938 ],
[ 900, nan, 0.1147 ],
[ 1000, nan, 0.1341 ],
[ 2000, nan, 0.4268 ],
[ 3000, nan, 0.8961 ],
[ 4000, nan, 1.5610 ],
[ 5000, nan, 2.5132 ],
[ 6000, nan, 3.7655 ],
[ 7000, nan, 5.3641 ],
[ 8000, nan, 7.2363 ],
[ 9000, nan, 9.5510 ],
[ 10000, nan, 12.2405 ],
[ 12000, nan, 19.4162 ],
[ 14000, nan, 28.2947 ],
[ 16000, nan, 39.8984 ],
[ 18000, nan, 55.1168 ],
[ 20000, nan, 71.8349 ],
])
# numactl --interleave=all ./testing_ssyevd_gpu -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
ssyevd_gpu_JV = array([
[ 10, nan, 0.0001 ],
[ 20, nan, 0.0002 ],
[ 30, nan, 0.0004 ],
[ 40, nan, 0.0003 ],
[ 50, nan, 0.0004 ],
[ 60, nan, 0.0006 ],
[ 70, nan, 0.0007 ],
[ 80, nan, 0.0008 ],
[ 90, nan, 0.0009 ],
[ 100, nan, 0.0011 ],
[ 200, nan, 0.0123 ],
[ 300, nan, 0.0200 ],
[ 400, nan, 0.0339 ],
[ 500, nan, 0.0466 ],
[ 600, nan, 0.0596 ],
[ 700, nan, 0.0747 ],
[ 800, nan, 0.1215 ],
[ 900, nan, 0.1182 ],
[ 1000, nan, 0.1369 ],
[ 2000, nan, 0.4472 ],
[ 3000, nan, 0.9319 ],
[ 4000, nan, 1.6236 ],
[ 5000, nan, 2.6221 ],
[ 6000, nan, 3.9895 ],
[ 7000, nan, 5.6979 ],
[ 8000, nan, 7.7891 ],
[ 9000, nan, 10.3995 ],
[ 10000, nan, 13.3980 ],
[ 12000, nan, 21.3793 ],
[ 14000, nan, 31.4721 ],
[ 16000, nan, 45.0187 ],
[ 18000, nan, 62.8949 ],
[ 20000, nan, 83.1238 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/ssyevd_2stage.txt
# numactl --interleave=all ./testing_ssyevdx_2stage -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
ssyevdx_2stage_JN = array([
[ 10, 0, 0.0000 ],
[ 20, 0, 0.0000 ],
[ 30, 0, 0.0000 ],
[ 40, 0, 0.0000 ],
[ 50, 0, 0.0000 ],
[ 60, 0, 0.0000 ],
[ 70, 70, 0.0003 ],
[ 80, 80, 0.0004 ],
[ 90, 90, 0.0004 ],
[ 100, 100, 0.0005 ],
[ 200, 200, 0.0028 ],
[ 300, 300, 0.0156 ],
[ 400, 400, 0.0272 ],
[ 500, 500, 0.0442 ],
[ 600, 600, 0.0605 ],
[ 700, 700, 0.0795 ],
[ 800, 800, 0.0963 ],
[ 900, 900, 0.1214 ],
[ 1000, 1000, 0.1235 ],
[ 2000, 2000, 0.5216 ],
[ 3000, 3000, 0.7768 ],
[ 4000, 4000, 1.1041 ],
[ 5000, 5000, 1.3587 ],
[ 6000, 6000, 1.8045 ],
[ 7000, 7000, 2.3656 ],
[ 8000, 8000, 2.9823 ],
[ 9000, 9000, 3.7799 ],
[ 10000, 10000, 4.4917 ],
[ 12000, 12000, 6.5610 ],
[ 14000, 14000, 8.9986 ],
[ 16000, 16000, 12.0558 ],
[ 18000, 18000, 15.9094 ],
[ 20000, 20000, 20.1123 ],
])
# numactl --interleave=all ./testing_ssyevdx_2stage -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
ssyevdx_2stage_JV = array([
[ 10, 10, 0.0001 ],
[ 20, 20, 0.0001 ],
[ 30, 30, 0.0002 ],
[ 40, 40, 0.0003 ],
[ 50, 50, 0.0003 ],
[ 60, 60, 0.0005 ],
[ 70, 70, 0.0006 ],
[ 80, 80, 0.0007 ],
[ 90, 90, 0.0009 ],
[ 100, 100, 0.0010 ],
[ 200, 200, 0.0048 ],
[ 300, 300, 0.0382 ],
[ 400, 400, 0.0558 ],
[ 500, 500, 0.0750 ],
[ 600, 600, 0.0928 ],
[ 700, 700, 0.0948 ],
[ 800, 800, 0.1354 ],
[ 900, 900, 0.1444 ],
[ 1000, 1000, 0.1599 ],
[ 2000, 2000, 0.6484 ],
[ 3000, 3000, 0.9724 ],
[ 4000, 4000, 1.6108 ],
[ 5000, 5000, 2.1483 ],
[ 6000, 6000, 3.2763 ],
[ 7000, 7000, 4.0355 ],
[ 8000, 8000, 5.1646 ],
[ 9000, 9000, 7.5894 ],
[ 10000, 10000, 10.0678 ],
[ 12000, 12000, 14.1138 ],
[ 14000, 14000, 22.1149 ],
[ 16000, 16000, 33.2558 ],
[ 18000, 18000, 40.8178 ],
[ 20000, 20000, 54.7261 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/ssymv.txt
# numactl --interleave=all ./testing_ssymv -N 100 -N 1000 --range 10:90:1 --range 100:900:10 --range 1000:9000:100 --range 10000:20000:2000
ssymv_L = array([
[ 10, 0.0067, 0.0329, 0.0082, 0.0269, 0.0105, 0.0210, 0.1025, 0.0021, 4.77e-08, 4.77e-08, 4.77e-08, nan ],
[ 11, 0.0085, 0.0310, 0.0105, 0.0250, 0.0140, 0.0188, 0.1384, 0.0019, 4.33e-08, 4.33e-08, 4.33e-08, nan ],
[ 12, 0.0101, 0.0310, 0.0120, 0.0260, 0.0149, 0.0210, 0.1636, 0.0019, 3.97e-08, 1.99e-08, 1.99e-08, nan ],
[ 13, 0.0121, 0.0300, 0.0140, 0.0260, 0.0182, 0.0200, 0.1908, 0.0019, 7.34e-08, 7.34e-08, 7.34e-08, nan ],
[ 14, 0.0128, 0.0329, 0.0162, 0.0260, 0.0210, 0.0200, 0.1957, 0.0021, 6.81e-08, 6.81e-08, 6.81e-08, nan ],
[ 15, 0.0155, 0.0310, 0.0185, 0.0260, 0.0252, 0.0191, 0.2517, 0.0019, 3.18e-08, 4.77e-08, 6.36e-08, nan ],
[ 16, 0.0181, 0.0300, 0.0209, 0.0260, 0.0275, 0.0198, 0.2852, 0.0019, 5.96e-08, 5.96e-08, 5.96e-08, nan ],
[ 17, 0.0204, 0.0300, 0.0225, 0.0272, 0.0306, 0.0200, 0.2139, 0.0029, 5.61e-08, 2.80e-08, 5.61e-08, nan ],
[ 18, 0.0201, 0.0341, 0.0254, 0.0269, 0.0312, 0.0219, 0.3586, 0.0019, 7.95e-08, 2.65e-08, 5.30e-08, nan ],
[ 19, 0.0229, 0.0331, 0.0270, 0.0281, 0.0362, 0.0210, 0.2452, 0.0031, 5.02e-08, 5.02e-08, 5.02e-08, nan ],
[ 20, 0.0271, 0.0310, 0.0299, 0.0281, 0.0396, 0.0212, 0.4404, 0.0019, 4.77e-08, 4.77e-08, 4.77e-08, nan ],
[ 21, 0.0281, 0.0329, 0.0331, 0.0279, 0.0440, 0.0210, 0.4844, 0.0019, 9.08e-08, 6.81e-08, 4.54e-08, nan ],
[ 22, 0.0327, 0.0310, 0.0363, 0.0279, 0.0461, 0.0219, 0.3265, 0.0031, 6.50e-08, 4.33e-08, 6.50e-08, nan ],
[ 23, 0.0346, 0.0319, 0.0392, 0.0281, 0.0477, 0.0231, 0.3562, 0.0031, 4.15e-08, 8.29e-08, 4.15e-08, nan ],
[ 24, 0.0354, 0.0339, 0.0416, 0.0288, 0.0547, 0.0219, 0.6291, 0.0019, 7.95e-08, 3.97e-08, 3.97e-08, nan ],
[ 25, 0.0419, 0.0310, 0.0436, 0.0298, 0.0593, 0.0219, 0.6816, 0.0019, 7.63e-08, 7.63e-08, 5.72e-08, nan ],
[ 26, 0.0415, 0.0339, 0.0487, 0.0288, 0.0669, 0.0210, 0.4907, 0.0029, 7.34e-08, 7.34e-08, 7.34e-08, nan ],
[ 27, 0.0460, 0.0329, 0.0520, 0.0291, 0.0689, 0.0219, 0.7046, 0.0021, 7.06e-08, 7.06e-08, 7.06e-08, nan ],
[ 28, 0.0480, 0.0339, 0.0541, 0.0300, 0.0732, 0.0222, 0.5676, 0.0029, 6.81e-08, 6.81e-08, 1.02e-07, nan ],
[ 29, 0.0561, 0.0310, 0.0584, 0.0298, 0.0793, 0.0219, 0.5614, 0.0031, 6.58e-08, 6.58e-08, 9.87e-08, nan ],
[ 30, 0.0561, 0.0331, 0.0619, 0.0300, 0.0848, 0.0219, 0.6001, 0.0031, 9.54e-08, 9.54e-08, 1.27e-07, nan ],
[ 31, 0.0599, 0.0331, 0.0666, 0.0298, 0.0905, 0.0219, 0.6401, 0.0031, 9.23e-08, 6.15e-08, 9.23e-08, nan ],
[ 32, 0.0681, 0.0310, 0.0681, 0.0310, 0.0923, 0.0229, 0.6814, 0.0031, 5.96e-08, 5.96e-08, 5.96e-08, nan ],
[ 33, 0.0702, 0.0319, 0.0747, 0.0300, 0.0980, 0.0229, 0.7240, 0.0031, 8.67e-08, 1.16e-07, 5.78e-08, nan ],
[ 34, 0.0723, 0.0329, 0.0768, 0.0310, 0.0998, 0.0238, 0.7679, 0.0031, 5.61e-08, 8.41e-08, 5.61e-08, nan ],
[ 35, 0.0744, 0.0339, 0.0839, 0.0300, 0.1101, 0.0229, 0.8808, 0.0029, 5.45e-08, 5.45e-08, 5.45e-08, nan ],
[ 36, 0.0834, 0.0319, 0.0887, 0.0300, 0.1164, 0.0229, 0.6573, 0.0041, 7.95e-08, 5.30e-08, 5.30e-08, nan ],
[ 37, 0.0907, 0.0310, 0.0967, 0.0291, 0.1282, 0.0219, 0.6938, 0.0041, 1.03e-07, 1.03e-07, 1.03e-07, nan ],
[ 38, 0.0956, 0.0310, 0.1019, 0.0291, 0.1282, 0.0231, 0.7313, 0.0041, 7.53e-08, 5.02e-08, 7.53e-08, nan ],
[ 39, 0.0948, 0.0329, 0.1118, 0.0279, 0.1363, 0.0229, 0.7698, 0.0041, 4.89e-08, 4.89e-08, 4.89e-08, nan ],
[ 40, 0.1058, 0.0310, 0.1092, 0.0300, 0.1362, 0.0241, 1.0583, 0.0031, 7.15e-08, 9.54e-08, 7.15e-08, nan ],
[ 41, 0.1078, 0.0319, 0.1156, 0.0298, 0.1570, 0.0219, 1.1112, 0.0031, 6.98e-08, 6.98e-08, 6.98e-08, nan ],
[ 42, 0.1165, 0.0310, 0.1202, 0.0300, 0.1629, 0.0222, 1.1654, 0.0031, 9.08e-08, 9.08e-08, 9.08e-08, nan ],
[ 43, 0.1184, 0.0319, 0.1260, 0.0300, 0.1571, 0.0241, 0.9336, 0.0041, 8.87e-08, 8.87e-08, 8.87e-08, nan ],
[ 44, 0.1240, 0.0319, 0.1278, 0.0310, 0.1329, 0.0298, 1.0381, 0.0038, 8.67e-08, 8.67e-08, 8.67e-08, nan ],
[ 45, 0.1223, 0.0339, 0.1336, 0.0310, 0.1736, 0.0238, 1.0214, 0.0041, 8.48e-08, 8.48e-08, 8.48e-08, nan ],
[ 46, 0.1268, 0.0341, 0.1395, 0.0310, 0.1796, 0.0241, 0.8636, 0.0050, 8.29e-08, 1.24e-07, 8.29e-08, nan ],
[ 47, 0.1412, 0.0319, 0.1514, 0.0298, 0.1874, 0.0241, 1.1828, 0.0038, 8.12e-08, 8.12e-08, 8.12e-08, nan ],
[ 48, 0.1389, 0.0339, 0.1566, 0.0300, 0.1973, 0.0238, 1.1606, 0.0041, 7.95e-08, 3.97e-08, 7.95e-08, nan ],
[ 49, 0.1479, 0.0331, 0.1569, 0.0312, 0.1976, 0.0248, 1.2089, 0.0041, 7.79e-08, 7.79e-08, 7.79e-08, nan ],
[ 50, 0.1455, 0.0350, 0.1645, 0.0310, 0.2037, 0.0250, 1.0186, 0.0050, 3.81e-08, 5.72e-08, 5.72e-08, nan ],
[ 51, 0.1648, 0.0322, 0.1711, 0.0310, 0.2119, 0.0250, 1.3086, 0.0041, 7.48e-08, 5.61e-08, 7.48e-08, nan ],
[ 52, 0.1628, 0.0339, 0.1778, 0.0310, 0.2121, 0.0260, 1.3599, 0.0041, 1.10e-07, 1.10e-07, 1.10e-07, nan ],
[ 53, 0.1691, 0.0339, 0.1847, 0.0310, 0.2203, 0.0260, 1.1432, 0.0050, 9.00e-08, 1.08e-07, 7.20e-08, nan ],
[ 54, 0.1695, 0.0350, 0.1916, 0.0310, 0.2373, 0.0250, 1.1864, 0.0050, 1.06e-07, 1.06e-07, 1.06e-07, nan ],
[ 55, 0.1872, 0.0329, 0.2051, 0.0300, 0.2370, 0.0260, 1.2303, 0.0050, 6.94e-08, 6.94e-08, 6.94e-08, nan ],
[ 56, 0.1872, 0.0341, 0.2060, 0.0310, 0.2457, 0.0260, 1.5751, 0.0041, 6.81e-08, 6.81e-08, 3.41e-08, nan ],
[ 57, 0.1900, 0.0348, 0.1887, 0.0350, 0.2641, 0.0250, 1.6313, 0.0041, 6.69e-08, 6.69e-08, 6.69e-08, nan ],
[ 58, 0.2142, 0.0319, 0.2208, 0.0310, 0.2634, 0.0260, 1.3669, 0.0050, 9.87e-08, 1.32e-07, 9.87e-08, nan ],
[ 59, 0.2034, 0.0348, 0.2284, 0.0310, 0.2724, 0.0260, 1.4141, 0.0050, 9.70e-08, 6.47e-08, 6.47e-08, nan ],
[ 60, 0.2089, 0.0350, 0.2362, 0.0310, 0.2817, 0.0260, 1.4620, 0.0050, 1.27e-07, 9.54e-08, 9.54e-08, nan ],
[ 61, 0.2440, 0.0310, 0.2440, 0.0310, 0.2808, 0.0269, 1.5107, 0.0050, 1.25e-07, 1.25e-07, 9.38e-08, nan ],
[ 62, 0.2445, 0.0319, 0.2520, 0.0310, 0.2900, 0.0269, 1.3106, 0.0060, 9.23e-08, 9.23e-08, 1.23e-07, nan ],
[ 63, 0.2524, 0.0319, 0.2706, 0.0298, 0.3221, 0.0250, 1.3529, 0.0060, 9.08e-08, 9.08e-08, 1.51e-07, nan ],
[ 64, 0.2664, 0.0312, 0.2792, 0.0298, 0.3202, 0.0260, 1.6617, 0.0050, 8.94e-08, 5.96e-08, 8.94e-08, nan ],
[ 65, 0.2448, 0.0350, 0.2263, 0.0379, 0.3185, 0.0269, 1.7137, 0.0050, 5.87e-08, 5.87e-08, 8.80e-08, nan ],
[ 66, 0.2523, 0.0350, 0.1297, 0.0682, 0.3283, 0.0269, 1.7664, 0.0050, 8.67e-08, 8.67e-08, 8.67e-08, nan ],
[ 67, 0.2600, 0.0350, 0.2531, 0.0360, 0.3133, 0.0291, 1.5287, 0.0060, 1.14e-07, 1.14e-07, 1.14e-07, nan ],
[ 68, 0.2607, 0.0360, 0.2607, 0.0360, 0.3364, 0.0279, 1.5744, 0.0060, 1.40e-07, 1.12e-07, 1.40e-07, nan ],
[ 69, 0.2833, 0.0341, 0.2683, 0.0360, 0.3434, 0.0281, 1.9294, 0.0050, 8.29e-08, 8.29e-08, 1.11e-07, nan ],
[ 70, 0.2690, 0.0370, 0.2690, 0.0370, 0.3563, 0.0279, 1.6677, 0.0060, 1.36e-07, 1.63e-07, 1.63e-07, nan ],
[ 71, 0.2697, 0.0379, 0.2767, 0.0370, 0.3544, 0.0288, 1.7153, 0.0060, 8.06e-08, 1.61e-07, 1.07e-07, nan ],
[ 72, 0.2756, 0.0381, 0.2845, 0.0370, 0.3614, 0.0291, 2.5936, 0.0041, 1.06e-07, 1.06e-07, 1.32e-07, nan ],
[ 73, 0.3001, 0.0360, 0.2850, 0.0379, 0.3596, 0.0300, 2.1579, 0.0050, 1.05e-07, 7.84e-08, 1.05e-07, nan ],
[ 74, 0.2928, 0.0379, 0.3004, 0.0370, 0.3945, 0.0281, 1.7906, 0.0062, 1.29e-07, 1.29e-07, 1.29e-07, nan ],
[ 75, 0.3253, 0.0350, 0.3065, 0.0372, 0.4052, 0.0281, 1.9126, 0.0060, 1.27e-07, 7.63e-08, 7.63e-08, nan ],
[ 76, 0.3167, 0.0370, 0.3251, 0.0360, 0.4057, 0.0288, 1.9636, 0.0060, 1.00e-07, 1.00e-07, 7.53e-08, nan ],
[ 77, 0.3250, 0.0370, 0.3250, 0.0370, 0.4306, 0.0279, 1.9378, 0.0062, 9.91e-08, 9.91e-08, 9.91e-08, nan ],
[ 78, 0.3516, 0.0350, 0.3251, 0.0379, 0.4418, 0.0279, 2.4615, 0.0050, 7.34e-08, 7.34e-08, 7.34e-08, nan ],
[ 79, 0.3420, 0.0370, 0.3420, 0.0370, 0.4346, 0.0291, 2.1206, 0.0060, 9.66e-08, 1.45e-07, 1.21e-07, nan ],
[ 80, 0.3600, 0.0360, 0.3484, 0.0372, 0.4607, 0.0281, 2.7179, 0.0048, 9.54e-08, 9.54e-08, 9.54e-08, nan ],
[ 81, 0.3690, 0.0360, 0.3504, 0.0379, 0.4762, 0.0279, 2.6532, 0.0050, 9.42e-08, 1.18e-07, 1.18e-07, nan ],
[ 82, 0.3591, 0.0379, 0.3683, 0.0370, 0.4838, 0.0281, 2.2837, 0.0060, 1.40e-07, 1.40e-07, 9.30e-08, nan ],
[ 83, 0.3873, 0.0360, 0.3655, 0.0381, 0.4794, 0.0291, 2.7850, 0.0050, 1.15e-07, 9.19e-08, 9.19e-08, nan ],
[ 84, 0.3767, 0.0379, 0.3864, 0.0370, 0.5119, 0.0279, 2.3958, 0.0060, 9.08e-08, 9.08e-08, 9.08e-08, nan ],
[ 85, 0.3931, 0.0372, 0.3484, 0.0420, 0.5197, 0.0281, 2.1145, 0.0069, 8.98e-08, 8.98e-08, 1.35e-07, nan ],
[ 86, 0.4270, 0.0350, 0.4049, 0.0370, 0.5364, 0.0279, 2.1643, 0.0069, 1.33e-07, 1.33e-07, 8.87e-08, nan ],
[ 87, 0.4369, 0.0350, 0.4143, 0.0370, 0.5489, 0.0279, 2.2146, 0.0069, 8.77e-08, 6.58e-08, 8.77e-08, nan ],
[ 88, 0.4351, 0.0360, 0.4239, 0.0370, 0.5385, 0.0291, 3.1286, 0.0050, 1.30e-07, 8.67e-08, 8.67e-08, nan ],
[ 89, 0.4335, 0.0370, 0.4307, 0.0372, 0.5508, 0.0291, 2.6877, 0.0060, 1.29e-07, 1.29e-07, 1.29e-07, nan ],
[ 90, 0.4432, 0.0370, 0.4432, 0.0370, 0.5872, 0.0279, 2.3691, 0.0069, 1.27e-07, 1.27e-07, 1.27e-07, nan ],
[ 100, 0.5295, 0.0381, 0.5295, 0.0381, 0.6778, 0.0298, 2.9215, 0.0069, 1.14e-07, 1.14e-07, 1.14e-07, nan ],
[ 110, 0.6442, 0.0379, 0.6245, 0.0391, 0.7879, 0.0310, 3.0125, 0.0081, 1.39e-07, 1.39e-07, 1.04e-07, nan ],
[ 120, 0.7858, 0.0370, 0.7427, 0.0391, 0.9369, 0.0310, 3.5824, 0.0081, 9.54e-08, 1.27e-07, 1.27e-07, nan ],
[ 130, 0.8554, 0.0398, 0.9217, 0.0370, 1.0582, 0.0322, 3.7594, 0.0091, 1.47e-07, 1.47e-07, 1.47e-07, nan ],
[ 140, 0.9627, 0.0410, 1.0415, 0.0379, 1.1999, 0.0329, 5.0179, 0.0079, 2.18e-07, 1.63e-07, 1.63e-07, nan ],
[ 150, 1.1047, 0.0410, 1.1875, 0.0381, 1.3669, 0.0331, 4.1305, 0.0110, 1.53e-07, 1.27e-07, 1.53e-07, nan ],
[ 160, 1.2563, 0.0410, 1.3591, 0.0379, 1.5218, 0.0339, 5.6866, 0.0091, 1.43e-07, 1.43e-07, 1.43e-07, nan ],
[ 170, 1.3253, 0.0439, 1.4515, 0.0401, 1.6149, 0.0360, 5.8061, 0.0100, 1.35e-07, 1.35e-07, 1.35e-07, nan ],
[ 180, 1.5441, 0.0422, 1.5890, 0.0410, 1.8099, 0.0360, 6.5072, 0.0100, 1.70e-07, 1.27e-07, 1.27e-07, nan ],
[ 190, 1.6819, 0.0432, 1.7699, 0.0410, 2.0160, 0.0360, 5.9691, 0.0122, 2.41e-07, 2.01e-07, 1.61e-07, nan ],
[ 200, 1.7473, 0.0460, 1.9606, 0.0410, 2.1756, 0.0370, 8.8743, 0.0091, 1.53e-07, 1.53e-07, 1.53e-07, nan ],
[ 210, 1.9259, 0.0460, 2.1610, 0.0410, 2.2804, 0.0389, 7.4340, 0.0119, 1.82e-07, 1.82e-07, 1.82e-07, nan ],
[ 220, 2.1132, 0.0460, 2.3712, 0.0410, 2.5651, 0.0379, 8.8664, 0.0110, 1.73e-07, 2.08e-07, 1.73e-07, nan ],
[ 230, 2.2624, 0.0470, 2.5912, 0.0410, 2.7176, 0.0391, 7.5540, 0.0141, 2.32e-07, 1.66e-07, 1.66e-07, nan ],
[ 240, 2.5140, 0.0460, 2.8209, 0.0410, 2.9054, 0.0398, 8.3655, 0.0138, 2.23e-07, 2.54e-07, 2.23e-07, nan ],
[ 250, 2.6720, 0.0470, 2.9739, 0.0422, 3.2899, 0.0381, 8.3553, 0.0150, 2.75e-07, 2.75e-07, 3.05e-07, nan ],
[ 260, 2.6601, 0.0510, 3.2344, 0.0420, 3.2344, 0.0420, 4.0953, 0.0331, 1.17e-07, 8.80e-08, 8.80e-08, nan ],
[ 270, 2.8682, 0.0510, 3.4875, 0.0420, 3.4100, 0.0429, 5.2016, 0.0281, 1.13e-07, 5.65e-08, 8.48e-08, nan ],
[ 280, 3.0276, 0.0520, 3.6668, 0.0429, 3.7501, 0.0420, 5.2801, 0.0298, 8.17e-08, 5.45e-08, 8.17e-08, nan ],
[ 290, 3.1888, 0.0529, 3.9329, 0.0429, 3.9111, 0.0432, 4.9505, 0.0341, 1.05e-07, 7.89e-08, 1.05e-07, nan ],
[ 300, 3.4747, 0.0520, 4.2083, 0.0429, 4.3039, 0.0420, 5.2971, 0.0341, 1.02e-07, 7.63e-08, 1.02e-07, nan ],
[ 310, 3.7098, 0.0520, 4.3716, 0.0441, 4.3954, 0.0439, 5.8183, 0.0331, 9.84e-08, 7.38e-08, 1.23e-07, nan ],
[ 320, 4.0265, 0.0510, 4.7871, 0.0429, 4.6577, 0.0441, 5.2541, 0.0391, 9.54e-08, 9.54e-08, 1.43e-07, nan ],
[ 330, 3.8991, 0.0560, 4.8481, 0.0451, 4.7476, 0.0460, 5.6214, 0.0389, 1.16e-07, 9.25e-08, 9.25e-08, nan ],
[ 340, 4.0694, 0.0570, 5.1733, 0.0448, 5.0392, 0.0460, 5.8238, 0.0398, 1.12e-07, 8.98e-08, 1.12e-07, nan ],
[ 350, 4.4806, 0.0548, 5.4526, 0.0451, 5.4526, 0.0451, 5.9915, 0.0410, 8.72e-08, 8.72e-08, 8.72e-08, nan ],
[ 360, 4.4864, 0.0579, 5.5339, 0.0470, 5.4238, 0.0479, 6.3383, 0.0410, 1.48e-07, 1.06e-07, 8.48e-08, nan ],
[ 370, 4.7387, 0.0579, 6.1250, 0.0448, 5.8452, 0.0470, 7.2422, 0.0379, 1.24e-07, 1.65e-07, 1.24e-07, nan ],
[ 380, 4.8195, 0.0601, 6.1650, 0.0470, 6.0124, 0.0482, 7.6384, 0.0379, 1.20e-07, 1.20e-07, 1.20e-07, nan ],
[ 390, 5.1580, 0.0591, 6.8041, 0.0448, 6.3641, 0.0479, 8.5279, 0.0358, 1.17e-07, 1.17e-07, 1.17e-07, nan ],
[ 400, 5.2560, 0.0610, 6.8301, 0.0470, 6.4073, 0.0501, 9.2160, 0.0348, 1.14e-07, 1.14e-07, 1.14e-07, nan ],
[ 410, 5.5434, 0.0608, 7.3242, 0.0460, 6.7313, 0.0501, 9.3614, 0.0360, 1.12e-07, 1.12e-07, 1.12e-07, nan ],
[ 420, 5.7940, 0.0610, 7.3795, 0.0479, 6.9312, 0.0510, 9.5082, 0.0372, 1.09e-07, 1.45e-07, 1.09e-07, nan ],
[ 430, 5.8889, 0.0629, 7.8917, 0.0470, 7.2648, 0.0510, 10.0301, 0.0370, 1.42e-07, 1.06e-07, 1.06e-07, nan ],
[ 440, 6.1656, 0.0629, 8.0580, 0.0482, 7.6062, 0.0510, 10.1733, 0.0381, 1.04e-07, 1.04e-07, 1.04e-07, nan ],
[ 450, 6.2591, 0.0648, 8.2644, 0.0491, 7.6688, 0.0529, 11.2746, 0.0360, 1.02e-07, 1.36e-07, 1.02e-07, nan ],
[ 460, 6.5161, 0.0651, 8.8502, 0.0479, 8.0130, 0.0529, 11.4031, 0.0372, 9.95e-08, 1.33e-07, 9.95e-08, nan ],
[ 470, 6.8272, 0.0648, 9.1930, 0.0482, 8.2168, 0.0539, 11.9806, 0.0370, 9.74e-08, 9.74e-08, 9.74e-08, nan ],
[ 480, 6.9919, 0.0660, 9.4018, 0.0491, 8.5697, 0.0539, 11.0043, 0.0420, 9.54e-08, 9.54e-08, 9.54e-08, nan ],
[ 490, 7.3927, 0.0651, 9.8450, 0.0489, 9.0911, 0.0529, 10.9686, 0.0439, 9.34e-08, 1.25e-07, 1.25e-07, nan ],
[ 500, 7.3731, 0.0679, 10.2505, 0.0489, 8.7556, 0.0572, 12.2171, 0.0410, 9.16e-08, 1.22e-07, 1.53e-07, nan ],
[ 510, 7.8923, 0.0660, 10.4601, 0.0498, 8.9965, 0.0579, 12.0782, 0.0432, 8.98e-08, 8.98e-08, 8.98e-08, nan ],
[ 520, 7.7565, 0.0699, 10.6198, 0.0510, 9.0184, 0.0601, 11.3067, 0.0479, 1.47e-07, 8.80e-08, 1.17e-07, nan ],
[ 530, 7.9488, 0.0708, 11.2419, 0.0501, 9.3683, 0.0601, 12.2322, 0.0460, 1.44e-07, 1.15e-07, 1.15e-07, nan ],
[ 540, 8.4505, 0.0691, 12.1319, 0.0482, 9.5728, 0.0610, 12.6977, 0.0460, 1.13e-07, 1.13e-07, 1.13e-07, nan ],
[ 550, 8.4178, 0.0720, 11.8793, 0.0510, 9.6294, 0.0629, 12.4008, 0.0489, 1.39e-07, 1.11e-07, 1.11e-07, nan ],
[ 560, 8.9638, 0.0701, 12.7930, 0.0491, 10.2944, 0.0610, 12.7930, 0.0491, 1.36e-07, 1.09e-07, 1.09e-07, nan ],
[ 570, 9.1619, 0.0710, 12.2984, 0.0529, 10.1875, 0.0639, 13.0011, 0.0501, 1.34e-07, 1.07e-07, 1.07e-07, nan ],
[ 580, 8.6446, 0.0780, 12.9669, 0.0520, 10.0598, 0.0670, 13.7892, 0.0489, 1.05e-07, 1.05e-07, 1.05e-07, nan ],
[ 590, 9.2858, 0.0751, 13.1758, 0.0529, 10.7144, 0.0651, 13.1167, 0.0532, 1.29e-07, 1.03e-07, 1.29e-07, nan ],
[ 600, 9.6335, 0.0749, 13.5647, 0.0532, 10.9203, 0.0660, 13.6258, 0.0529, 1.27e-07, 1.53e-07, 1.27e-07, nan ],
[ 610, 9.5612, 0.0780, 13.7732, 0.0541, 10.8184, 0.0689, 14.0834, 0.0529, 1.25e-07, 1.00e-07, 1.25e-07, nan ],
[ 620, 9.8469, 0.0782, 13.9817, 0.0551, 11.1372, 0.0691, 13.9817, 0.0551, 1.23e-07, 9.84e-08, 1.23e-07, nan ],
[ 630, 9.9544, 0.0799, 14.4360, 0.0551, 11.1903, 0.0710, 14.7554, 0.0539, 1.21e-07, 1.21e-07, 1.21e-07, nan ],
[ 640, 10.6874, 0.0768, 15.5015, 0.0529, 11.7052, 0.0701, 14.8976, 0.0551, 9.54e-08, 1.19e-07, 1.19e-07, nan ],
[ 650, 10.2001, 0.0830, 15.3664, 0.0551, 11.6001, 0.0730, 14.6076, 0.0579, 1.17e-07, 1.17e-07, 1.41e-07, nan ],
[ 660, 10.9242, 0.0799, 16.1216, 0.0541, 12.1179, 0.0720, 15.3122, 0.0570, 1.39e-07, 1.16e-07, 1.16e-07, nan ],
[ 670, 10.7138, 0.0839, 16.0479, 0.0560, 11.8222, 0.0761, 14.5049, 0.0620, 1.37e-07, 9.11e-08, 9.11e-08, nan ],
[ 680, 11.1626, 0.0830, 16.8164, 0.0551, 12.3321, 0.0751, 15.9860, 0.0579, 1.12e-07, 1.35e-07, 1.35e-07, nan ],
[ 690, 11.2034, 0.0851, 17.0196, 0.0560, 12.5379, 0.0761, 15.6235, 0.0610, 1.33e-07, 1.33e-07, 1.33e-07, nan ],
[ 700, 11.9660, 0.0820, 17.2230, 0.0570, 12.7439, 0.0770, 15.0780, 0.0651, 1.31e-07, 1.31e-07, 1.31e-07, nan ],
[ 710, 11.8951, 0.0849, 18.0198, 0.0560, 13.1104, 0.0770, 15.5686, 0.0648, 1.29e-07, 1.29e-07, 1.29e-07, nan ],
[ 720, 11.8013, 0.0880, 18.1446, 0.0572, 13.3171, 0.0780, 16.2489, 0.0639, 1.27e-07, 1.27e-07, 1.27e-07, nan ],
[ 730, 12.4000, 0.0861, 18.7298, 0.0570, 13.6893, 0.0780, 16.3971, 0.0651, 1.25e-07, 1.25e-07, 1.25e-07, nan ],
[ 740, 11.9166, 0.0920, 18.9293, 0.0579, 13.5289, 0.0811, 17.0997, 0.0641, 1.24e-07, 1.24e-07, 1.24e-07, nan ],
[ 750, 12.8046, 0.0880, 19.4440, 0.0579, 14.2746, 0.0789, 16.3491, 0.0689, 1.22e-07, 1.22e-07, 1.63e-07, nan ],
[ 760, 12.7006, 0.0911, 19.6422, 0.0589, 14.3116, 0.0808, 16.2807, 0.0710, 1.20e-07, 1.20e-07, 1.20e-07, nan ],
[ 770, 13.0368, 0.0911, 19.7622, 0.0601, 14.3105, 0.0830, 16.2747, 0.0730, 1.19e-07, 1.19e-07, 1.59e-07, nan ],
[ 780, 13.1030, 0.0930, 20.2785, 0.0601, 14.6423, 0.0832, 16.0193, 0.0761, 1.57e-07, 1.17e-07, 1.57e-07, nan ],
[ 790, 13.4409, 0.0930, 21.2225, 0.0589, 15.2382, 0.0820, 16.2290, 0.0770, 1.55e-07, 1.55e-07, 1.16e-07, nan ],
[ 800, 13.9260, 0.0920, 21.3310, 0.0601, 15.4466, 0.0830, 16.2399, 0.0789, 1.53e-07, 1.14e-07, 1.53e-07, nan ],
[ 810, 13.7079, 0.0958, 21.1945, 0.0620, 15.2647, 0.0861, 17.0606, 0.0770, 1.13e-07, 1.13e-07, 1.51e-07, nan ],
[ 820, 13.8756, 0.0970, 22.0601, 0.0610, 15.6437, 0.0861, 17.2703, 0.0780, 1.49e-07, 1.12e-07, 1.49e-07, nan ],
[ 830, 14.3570, 0.0961, 22.6011, 0.0610, 16.2525, 0.0849, 16.8194, 0.0820, 1.47e-07, 1.10e-07, 1.10e-07, nan ],
[ 840, 14.1096, 0.1001, 22.4472, 0.0629, 16.0163, 0.0882, 16.9801, 0.0832, 1.45e-07, 1.45e-07, 1.09e-07, nan ],
[ 850, 14.0461, 0.1030, 22.8977, 0.0632, 16.4442, 0.0880, 17.2384, 0.0839, 1.08e-07, 1.44e-07, 1.08e-07, nan ],
[ 860, 14.6842, 0.1009, 23.8901, 0.0620, 16.8331, 0.0880, 17.0176, 0.0870, 1.42e-07, 1.42e-07, 1.06e-07, nan ],
[ 870, 14.5794, 0.1040, 23.6306, 0.0641, 16.9964, 0.0892, 17.4154, 0.0870, 1.40e-07, 1.40e-07, 1.40e-07, nan ],
[ 880, 14.8822, 0.1042, 24.2669, 0.0639, 17.2507, 0.0899, 17.6247, 0.0880, 1.39e-07, 1.39e-07, 1.39e-07, nan ],
[ 890, 15.2571, 0.1040, 24.8212, 0.0639, 17.8340, 0.0889, 17.5981, 0.0901, 1.03e-07, 1.37e-07, 1.03e-07, nan ],
[ 900, 14.7556, 0.1099, 24.5571, 0.0660, 17.6226, 0.0920, 18.0433, 0.0899, 1.36e-07, 1.36e-07, 1.36e-07, nan ],
[ 1000, 17.2778, 0.1159, 28.5612, 0.0701, 19.2592, 0.1040, 18.7016, 0.1070, 1.22e-07, 1.22e-07, 1.53e-07, nan ],
[ 1100, 18.3383, 0.1321, 31.4534, 0.0770, 20.3596, 0.1190, 20.6913, 0.1171, 1.66e-07, 1.39e-07, 1.39e-07, nan ],
[ 1200, 20.7370, 0.1390, 36.5247, 0.0789, 23.7985, 0.1211, 18.5709, 0.1552, 1.78e-07, 1.27e-07, 1.27e-07, nan ],
[ 1300, 22.0991, 0.1531, 39.7413, 0.0851, 26.0324, 0.1299, 24.5037, 0.1380, 1.64e-07, 1.17e-07, 1.64e-07, nan ],
[ 1400, 24.5207, 0.1600, 44.1110, 0.0889, 29.0696, 0.1349, 23.7766, 0.1650, 1.74e-07, 1.74e-07, 1.31e-07, nan ],
[ 1500, 26.6389, 0.1690, 48.9299, 0.0920, 29.8372, 0.1509, 24.5924, 0.1831, 2.03e-07, 1.63e-07, 1.63e-07, nan ],
[ 1600, 28.3113, 0.1810, 53.3207, 0.0961, 31.8345, 0.1609, 26.2693, 0.1950, 1.91e-07, 1.53e-07, 1.53e-07, nan ],
[ 1700, 29.9473, 0.1931, 54.6336, 0.1059, 32.5165, 0.1779, 27.4094, 0.2110, 1.80e-07, 2.15e-07, 1.80e-07, nan ],
[ 1800, 31.7689, 0.2041, 58.4821, 0.1109, 36.0188, 0.1800, 26.1483, 0.2480, 1.70e-07, 1.70e-07, 1.70e-07, nan ],
[ 1900, 33.9292, 0.2129, 64.4656, 0.1121, 38.0161, 0.1900, 24.9784, 0.2892, 2.25e-07, 1.61e-07, 1.61e-07, nan ],
[ 2000, 35.5627, 0.2251, 62.9854, 0.1271, 37.0543, 0.2160, 27.0300, 0.2961, 2.14e-07, 1.53e-07, 1.53e-07, nan ],
[ 2100, 37.9994, 0.2322, 65.8565, 0.1340, 24.3817, 0.3619, 25.7381, 0.3428, 2.03e-07, 1.74e-07, 1.74e-07, nan ],
[ 2200, 38.4289, 0.2520, 68.2678, 0.1419, 25.3554, 0.3819, 27.0435, 0.3581, 2.50e-07, 1.66e-07, 1.39e-07, nan ],
[ 2300, 41.0305, 0.2580, 71.4896, 0.1481, 25.8863, 0.4089, 29.6560, 0.3569, 2.92e-07, 1.86e-07, 1.86e-07, nan ],
[ 2400, 41.7431, 0.2761, 74.2527, 0.1552, 27.1717, 0.4241, 30.6522, 0.3760, 2.29e-07, 1.78e-07, 1.78e-07, nan ],
[ 2500, 43.5629, 0.2871, 79.7109, 0.1569, 27.9732, 0.4470, 4.3862, 2.8510, 2.69e-07, 1.71e-07, 1.46e-07, nan ],
[ 2600, 45.9715, 0.2942, 80.9255, 0.1671, 29.0321, 0.4659, 31.0163, 0.4361, 2.11e-07, 1.88e-07, 1.88e-07, nan ],
[ 2700, 47.2034, 0.3090, 82.8938, 0.1760, 30.1358, 0.4840, 34.0811, 0.4280, 2.26e-07, 1.81e-07, 1.58e-07, nan ],
[ 2800, 49.1705, 0.3190, 88.5467, 0.1771, 31.4334, 0.4990, 32.2027, 0.4871, 2.62e-07, 1.74e-07, 1.74e-07, nan ],
[ 2900, 50.8448, 0.3309, 90.9440, 0.1850, 32.4770, 0.5181, 33.5261, 0.5019, 2.53e-07, 2.10e-07, 1.68e-07, nan ],
[ 3000, 52.5192, 0.3428, 94.2854, 0.1910, 33.5955, 0.5360, 34.7710, 0.5178, 3.26e-07, 2.44e-07, 2.03e-07, nan ],
[ 3100, 54.1575, 0.3550, 97.6278, 0.1969, 34.4470, 0.5581, 35.2758, 0.5450, 2.36e-07, 2.36e-07, 1.97e-07, nan ],
[ 3200, 55.6517, 0.3681, 100.9708, 0.2029, 35.5655, 0.5760, 35.8773, 0.5710, 2.67e-07, 1.91e-07, 1.53e-07, nan ],
[ 3300, 57.4715, 0.3791, 103.7226, 0.2100, 36.1184, 0.6032, 36.9211, 0.5901, 2.96e-07, 2.22e-07, 1.85e-07, nan ],
[ 3400, 59.7664, 0.3870, 104.6395, 0.2210, 37.8466, 0.6111, 31.9924, 0.7229, 2.87e-07, 2.15e-07, 2.15e-07, nan ],
[ 3500, 60.9667, 0.4020, 107.8592, 0.2272, 38.4692, 0.6371, 32.5387, 0.7532, 3.14e-07, 2.09e-07, 1.74e-07, nan ],
[ 3600, 62.1764, 0.4170, 111.3066, 0.2329, 39.4724, 0.6568, 35.7132, 0.7260, 2.71e-07, 2.37e-07, 2.03e-07, nan ],
])
# numactl --interleave=all ./testing_ssymv -N 100 -N 1000 --range 10:90:1 --range 100:900:10 --range 1000:9000:100 --range 10000:20000:2000
ssymv_L = array([
[ 10, 0.0054, 0.0410, 0.0065, 0.0339, 0.0082, 0.0269, 0.1025, 0.0021, 4.77e-08, 4.77e-08, 4.77e-08, nan ],
[ 11, 0.0069, 0.0381, 0.0080, 0.0331, 0.0105, 0.0250, 0.0923, 0.0029, 4.33e-08, 4.33e-08, 4.33e-08, nan ],
[ 12, 0.0082, 0.0379, 0.0097, 0.0322, 0.0120, 0.0260, 0.1091, 0.0029, 3.97e-08, 1.99e-08, 1.99e-08, nan ],
[ 13, 0.0096, 0.0379, 0.0108, 0.0339, 0.0135, 0.0269, 0.1272, 0.0029, 7.34e-08, 7.34e-08, 7.34e-08, nan ],
[ 14, 0.0108, 0.0389, 0.0128, 0.0329, 0.0169, 0.0248, 0.1468, 0.0029, 6.81e-08, 6.81e-08, 6.81e-08, nan ],
[ 15, 0.0120, 0.0401, 0.0141, 0.0341, 0.0192, 0.0250, 0.1678, 0.0029, 3.18e-08, 4.77e-08, 6.36e-08, nan ],
[ 16, 0.0137, 0.0398, 0.0161, 0.0339, 0.0209, 0.0260, 0.2852, 0.0019, 5.96e-08, 5.96e-08, 5.96e-08, nan ],
[ 17, 0.0161, 0.0379, 0.0181, 0.0339, 0.0227, 0.0269, 0.2139, 0.0029, 5.61e-08, 2.80e-08, 5.61e-08, nan ],
[ 18, 0.0185, 0.0370, 0.0202, 0.0339, 0.0254, 0.0269, 0.2207, 0.0031, 7.95e-08, 2.65e-08, 5.30e-08, nan ],
[ 19, 0.0206, 0.0370, 0.0229, 0.0331, 0.0304, 0.0250, 0.2656, 0.0029, 5.02e-08, 5.02e-08, 5.02e-08, nan ],
[ 20, 0.0233, 0.0360, 0.0263, 0.0319, 0.0323, 0.0260, 0.2710, 0.0031, 4.77e-08, 4.77e-08, 4.77e-08, nan ],
[ 21, 0.0248, 0.0372, 0.0273, 0.0339, 0.0356, 0.0260, 0.3230, 0.0029, 9.08e-08, 6.81e-08, 4.54e-08, nan ],
[ 22, 0.0281, 0.0360, 0.0305, 0.0331, 0.0389, 0.0260, 0.3537, 0.0029, 6.50e-08, 4.33e-08, 6.50e-08, nan ],
[ 23, 0.0299, 0.0370, 0.0336, 0.0329, 0.0425, 0.0260, 0.3562, 0.0031, 4.15e-08, 8.29e-08, 4.15e-08, nan ],
[ 24, 0.0333, 0.0360, 0.0333, 0.0360, 0.0445, 0.0269, 0.2961, 0.0041, 7.95e-08, 3.97e-08, 3.97e-08, nan ],
[ 25, 0.0350, 0.0372, 0.0361, 0.0360, 0.0483, 0.0269, 0.2596, 0.0050, 7.63e-08, 7.63e-08, 5.72e-08, nan ],
[ 26, 0.0370, 0.0379, 0.0401, 0.0350, 0.0521, 0.0269, 0.3464, 0.0041, 7.34e-08, 7.34e-08, 7.34e-08, nan ],
[ 27, 0.0369, 0.0410, 0.0420, 0.0360, 0.0542, 0.0279, 0.3020, 0.0050, 7.06e-08, 7.06e-08, 7.06e-08, nan ],
[ 28, 0.0428, 0.0379, 0.0439, 0.0370, 0.0577, 0.0281, 0.4257, 0.0038, 6.81e-08, 6.81e-08, 1.02e-07, nan ],
[ 29, 0.0445, 0.0391, 0.0483, 0.0360, 0.0646, 0.0269, 0.2919, 0.0060, 6.58e-08, 6.58e-08, 9.87e-08, nan ],
[ 30, 0.0464, 0.0401, 0.0531, 0.0350, 0.0661, 0.0281, 0.3715, 0.0050, 9.54e-08, 9.54e-08, 1.27e-07, nan ],
[ 31, 0.0484, 0.0410, 0.0566, 0.0350, 0.0711, 0.0279, 0.3329, 0.0060, 9.23e-08, 6.15e-08, 9.23e-08, nan ],
[ 32, 0.0572, 0.0370, 0.0637, 0.0331, 0.0852, 0.0248, 0.4218, 0.0050, 5.96e-08, 5.96e-08, 5.96e-08, nan ],
[ 33, 0.0607, 0.0370, 0.0640, 0.0350, 0.0771, 0.0291, 0.3765, 0.0060, 8.67e-08, 1.16e-07, 5.78e-08, nan ],
[ 34, 0.0644, 0.0370, 0.0768, 0.0310, 0.1040, 0.0229, 0.5872, 0.0041, 5.61e-08, 8.41e-08, 5.61e-08, nan ],
[ 35, 0.0789, 0.0319, 0.0846, 0.0298, 0.1046, 0.0241, 0.3645, 0.0069, 5.45e-08, 5.45e-08, 5.45e-08, nan ],
[ 36, 0.0721, 0.0370, 0.0834, 0.0319, 0.1106, 0.0241, 0.3725, 0.0072, 7.95e-08, 5.30e-08, 5.30e-08, nan ],
[ 37, 0.0849, 0.0331, 0.0936, 0.0300, 0.1168, 0.0241, 0.6938, 0.0041, 1.03e-07, 1.03e-07, 1.03e-07, nan ],
[ 38, 0.0928, 0.0319, 0.0987, 0.0300, 0.1231, 0.0241, 0.7313, 0.0041, 7.53e-08, 5.02e-08, 7.53e-08, nan ],
[ 39, 0.0977, 0.0319, 0.0948, 0.0329, 0.1296, 0.0241, 0.8179, 0.0038, 4.89e-08, 4.89e-08, 4.89e-08, nan ],
[ 40, 0.1092, 0.0300, 0.1137, 0.0288, 0.1495, 0.0219, 1.0583, 0.0031, 7.15e-08, 9.54e-08, 7.15e-08, nan ],
[ 41, 0.1078, 0.0319, 0.1184, 0.0291, 0.1489, 0.0231, 1.1112, 0.0031, 6.98e-08, 6.98e-08, 6.98e-08, nan ],
[ 42, 0.1156, 0.0312, 0.1252, 0.0288, 0.1578, 0.0229, 1.2625, 0.0029, 9.08e-08, 9.08e-08, 9.08e-08, nan ],
[ 43, 0.1184, 0.0319, 0.1345, 0.0281, 0.1653, 0.0229, 0.9336, 0.0041, 8.87e-08, 8.87e-08, 8.87e-08, nan ],
[ 44, 0.1278, 0.0310, 0.1240, 0.0319, 0.1730, 0.0229, 0.9770, 0.0041, 8.67e-08, 8.67e-08, 8.67e-08, nan ],
[ 45, 0.1336, 0.0310, 0.1378, 0.0300, 0.1887, 0.0219, 1.0214, 0.0041, 8.48e-08, 8.48e-08, 8.48e-08, nan ],
[ 46, 0.1268, 0.0341, 0.1395, 0.0310, 0.1814, 0.0238, 0.8636, 0.0050, 8.29e-08, 1.24e-07, 8.29e-08, nan ],
[ 47, 0.1412, 0.0319, 0.1456, 0.0310, 0.1874, 0.0241, 1.1828, 0.0038, 8.12e-08, 8.12e-08, 8.12e-08, nan ],
[ 48, 0.1380, 0.0341, 0.1518, 0.0310, 0.1973, 0.0238, 1.1606, 0.0041, 7.95e-08, 3.97e-08, 7.95e-08, nan ],
[ 49, 0.1534, 0.0319, 0.1581, 0.0310, 0.1957, 0.0250, 1.2089, 0.0041, 7.79e-08, 7.79e-08, 7.79e-08, nan ],
[ 50, 0.1550, 0.0329, 0.1645, 0.0310, 0.2037, 0.0250, 1.2583, 0.0041, 3.81e-08, 5.72e-08, 5.72e-08, nan ],
[ 51, 0.1660, 0.0319, 0.1711, 0.0310, 0.2119, 0.0250, 1.3086, 0.0041, 7.48e-08, 5.61e-08, 7.48e-08, nan ],
[ 52, 0.1725, 0.0319, 0.1778, 0.0310, 0.2202, 0.0250, 1.4449, 0.0038, 1.10e-07, 1.10e-07, 1.10e-07, nan ],
[ 53, 0.1847, 0.0310, 0.1847, 0.0310, 0.2308, 0.0248, 1.1432, 0.0050, 9.00e-08, 1.08e-07, 7.20e-08, nan ],
[ 54, 0.1755, 0.0339, 0.1977, 0.0300, 0.2373, 0.0250, 1.1864, 0.0050, 1.06e-07, 1.06e-07, 1.06e-07, nan ],
[ 55, 0.1872, 0.0329, 0.2051, 0.0300, 0.2461, 0.0250, 1.5198, 0.0041, 6.94e-08, 6.94e-08, 6.94e-08, nan ],
[ 56, 0.1998, 0.0319, 0.2125, 0.0300, 0.2550, 0.0250, 1.5751, 0.0041, 6.81e-08, 6.81e-08, 3.41e-08, nan ],
[ 57, 0.1691, 0.0391, 0.2133, 0.0310, 0.2544, 0.0260, 1.3206, 0.0050, 6.69e-08, 6.69e-08, 6.69e-08, nan ],
[ 58, 0.2142, 0.0319, 0.2208, 0.0310, 0.2734, 0.0250, 1.3669, 0.0050, 9.87e-08, 1.32e-07, 9.87e-08, nan ],
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[ 1300, 22.4134, 0.1509, 39.7413, 0.0851, 26.0324, 0.1299, 31.3193, 0.1080, 1.64e-07, 1.17e-07, 1.64e-07, nan ],
[ 1400, 24.3754, 0.1609, 43.5276, 0.0901, 28.6146, 0.1371, 31.3996, 0.1249, 1.74e-07, 1.74e-07, 1.31e-07, nan ],
[ 1500, 26.0510, 0.1729, 46.8659, 0.0961, 28.8791, 0.1559, 33.6067, 0.1340, 2.03e-07, 1.63e-07, 1.63e-07, nan ],
[ 1600, 28.4613, 0.1800, 52.7967, 0.0970, 31.6469, 0.1619, 30.1378, 0.1700, 1.91e-07, 1.53e-07, 1.53e-07, nan ],
[ 1700, 30.4358, 0.1900, 54.6336, 0.1059, 33.4123, 0.1731, 34.6533, 0.1669, 1.80e-07, 2.15e-07, 1.80e-07, nan ],
[ 1800, 32.4126, 0.2000, 56.3027, 0.1152, 36.0188, 0.1800, 36.0188, 0.1800, 1.70e-07, 1.70e-07, 1.70e-07, nan ],
[ 1900, 34.2359, 0.2110, 61.7084, 0.1171, 38.4015, 0.1881, 32.8264, 0.2201, 2.25e-07, 1.61e-07, 1.28e-07, nan ],
[ 2000, 35.5627, 0.2251, 60.7074, 0.1318, 37.5937, 0.2129, 36.5302, 0.2191, 2.14e-07, 1.53e-07, 1.53e-07, nan ],
[ 2100, 37.5369, 0.2351, 64.3676, 0.1371, 24.6414, 0.3581, 36.4644, 0.2420, 2.03e-07, 1.74e-07, 1.74e-07, nan ],
[ 2200, 39.0570, 0.2480, 68.7298, 0.1409, 25.8393, 0.3748, 36.2672, 0.2670, 2.50e-07, 1.66e-07, 1.39e-07, nan ],
[ 2300, 40.8794, 0.2589, 72.0699, 0.1469, 26.3942, 0.4010, 37.5275, 0.2820, 2.92e-07, 1.86e-07, 1.86e-07, nan ],
[ 2400, 42.6642, 0.2701, 74.8274, 0.1540, 27.4963, 0.4191, 40.0153, 0.2880, 2.29e-07, 1.78e-07, 1.78e-07, nan ],
[ 2500, 43.7446, 0.2859, 78.1666, 0.1600, 28.5519, 0.4380, 38.4811, 0.3250, 2.69e-07, 1.71e-07, 1.71e-07, nan ],
[ 2600, 45.2022, 0.2992, 81.5069, 0.1659, 29.1515, 0.4640, 41.7430, 0.3240, 2.11e-07, 1.88e-07, 1.88e-07, nan ],
[ 2700, 47.2034, 0.3090, 82.8938, 0.1760, 30.4508, 0.4790, 40.0626, 0.3641, 2.26e-07, 1.81e-07, 1.58e-07, nan ],
[ 2800, 49.1705, 0.3190, 87.1393, 0.1800, 31.6147, 0.4961, 35.4091, 0.4430, 2.62e-07, 1.74e-07, 1.74e-07, nan ],
[ 2900, 50.3730, 0.3340, 90.9440, 0.1850, 32.5519, 0.5169, 36.5093, 0.4609, 2.53e-07, 2.10e-07, 1.68e-07, nan ],
[ 3000, 52.1926, 0.3450, 91.8767, 0.1960, 33.4615, 0.5381, 38.8891, 0.4630, 3.26e-07, 2.44e-07, 2.03e-07, nan ],
[ 3100, 54.1575, 0.3550, 99.0670, 0.1941, 34.4030, 0.5589, 35.4153, 0.5429, 2.36e-07, 2.36e-07, 1.97e-07, nan ],
[ 3200, 55.5079, 0.3691, 101.3281, 0.2022, 35.7579, 0.5729, 41.3903, 0.4950, 2.67e-07, 1.91e-07, 1.53e-07, nan ],
[ 3300, 58.2407, 0.3741, 103.7226, 0.2100, 36.4353, 0.5980, 37.4353, 0.5820, 2.96e-07, 2.22e-07, 1.85e-07, nan ],
[ 3400, 60.2490, 0.3839, 104.6395, 0.2210, 37.6702, 0.6139, 39.1290, 0.5910, 2.87e-07, 2.15e-07, 1.80e-07, nan ],
[ 3500, 60.5002, 0.4051, 106.0782, 0.2310, 38.5269, 0.6361, 40.7734, 0.6011, 3.14e-07, 2.09e-07, 1.74e-07, nan ],
[ 3600, 62.3547, 0.4158, 110.2906, 0.2351, 39.3439, 0.6590, 38.9354, 0.6659, 2.71e-07, 2.37e-07, 1.70e-07, nan ],
[ 3700, 65.1936, 0.4201, 113.1735, 0.2420, 40.3907, 0.6781, 41.0694, 0.6669, 2.64e-07, 2.31e-07, 1.98e-07, nan ],
[ 3800, 66.1011, 0.4370, 115.5037, 0.2501, 41.5085, 0.6959, 38.8220, 0.7441, 2.89e-07, 2.89e-07, 1.93e-07, nan ],
[ 3900, 67.7407, 0.4492, 111.9504, 0.2718, 42.7836, 0.7112, 38.6621, 0.7870, 2.50e-07, 2.19e-07, 1.88e-07, nan ],
[ 4000, 67.9753, 0.4709, 113.4838, 0.2820, 43.4892, 0.7360, 42.5654, 0.7520, 3.05e-07, 2.14e-07, 1.53e-07, nan ],
[ 4100, 68.5026, 0.4909, 114.3933, 0.2940, 31.6320, 1.0631, 43.4525, 0.7739, 3.28e-07, 2.08e-07, 2.08e-07, nan ],
[ 4200, 70.7168, 0.4990, 112.7268, 0.3130, 32.7674, 1.0769, 42.6174, 0.8280, 2.91e-07, 2.33e-07, 2.03e-07, nan ],
[ 4300, 73.7014, 0.5019, 114.1585, 0.3240, 33.5949, 1.1010, 40.2547, 0.9189, 3.41e-07, 2.55e-07, 1.99e-07, nan ],
[ 4400, 74.7540, 0.5181, 111.9506, 0.3459, 34.4008, 1.1258, 43.6668, 0.8869, 2.77e-07, 2.77e-07, 2.22e-07, nan ],
[ 4500, 74.6188, 0.5429, 114.7246, 0.3531, 35.0685, 1.1551, 46.8322, 0.8650, 2.71e-07, 2.44e-07, 1.90e-07, nan ],
[ 4600, 77.9375, 0.5431, 116.6502, 0.3629, 35.7155, 1.1852, 45.6170, 0.9279, 3.18e-07, 2.39e-07, 2.12e-07, nan ],
[ 4700, 78.6355, 0.5620, 114.4804, 0.3860, 36.6147, 1.2069, 45.6062, 0.9689, 3.12e-07, 2.60e-07, 2.08e-07, nan ],
[ 4800, 80.4469, 0.5729, 118.1625, 0.3901, 37.4349, 1.2312, 46.3249, 0.9949, 3.05e-07, 2.29e-07, 1.78e-07, nan ],
[ 4900, 78.8460, 0.6092, 114.3961, 0.4199, 38.0313, 1.2629, 48.0333, 0.9999, 3.99e-07, 2.24e-07, 2.49e-07, nan ],
[ 5000, 79.5137, 0.6289, 117.3795, 0.4261, 39.0391, 1.2810, 49.2157, 1.0161, 3.17e-07, 2.44e-07, 2.20e-07, nan ],
[ 5100, 80.1728, 0.6490, 117.4545, 0.4430, 39.5991, 1.3139, 50.9170, 1.0219, 3.35e-07, 2.15e-07, 2.15e-07, nan ],
[ 5200, 80.3654, 0.6731, 117.3676, 0.4609, 40.1259, 1.3480, 49.1277, 1.1010, 3.29e-07, 2.58e-07, 2.35e-07, nan ],
[ 5300, 80.8509, 0.6950, 118.5515, 0.4740, 40.6907, 1.3809, 49.4193, 1.1370, 3.92e-07, 2.53e-07, 2.53e-07, nan ],
[ 5400, 80.4528, 0.7250, 122.0235, 0.4780, 41.7290, 1.3978, 49.2664, 1.1840, 3.84e-07, 2.49e-07, 2.03e-07, nan ],
[ 5500, 80.8800, 0.7482, 120.5708, 0.5019, 42.4915, 1.4241, 49.0343, 1.2341, 3.11e-07, 2.66e-07, 2.22e-07, nan ],
[ 5600, 82.2230, 0.7629, 123.0078, 0.5100, 42.9995, 1.4589, 47.8563, 1.3108, 4.36e-07, 3.05e-07, 2.18e-07, nan ],
[ 5700, 82.2800, 0.7899, 122.1845, 0.5319, 43.3239, 1.5001, 51.0953, 1.2720, 3.43e-07, 2.57e-07, 2.14e-07, nan ],
[ 5800, 81.1738, 0.8290, 121.0298, 0.5560, 44.3010, 1.5190, 49.6991, 1.3540, 3.79e-07, 2.53e-07, 2.53e-07, nan ],
[ 5900, 81.7171, 0.8521, 123.0231, 0.5660, 44.5820, 1.5619, 52.5944, 1.3239, 3.72e-07, 3.31e-07, 2.48e-07, nan ],
[ 6000, 82.9781, 0.8678, 125.9026, 0.5720, 45.8679, 1.5700, 51.4024, 1.4009, 4.07e-07, 2.85e-07, 2.44e-07, nan ],
[ 6100, 83.6301, 0.8900, 124.8765, 0.5960, 45.8027, 1.6251, 50.5983, 1.4710, 4.00e-07, 2.80e-07, 2.40e-07, nan ],
[ 6200, 85.1399, 0.9031, 126.8726, 0.6061, 36.7365, 2.0931, 51.2979, 1.4989, 3.94e-07, 2.76e-07, 3.15e-07, nan ],
[ 6300, 85.4495, 0.9291, 127.8789, 0.6208, 37.3818, 2.1238, 52.2676, 1.5190, 3.49e-07, 2.71e-07, 2.33e-07, nan ],
[ 6400, 86.2578, 0.9499, 124.6920, 0.6571, 38.3582, 2.1360, 52.1236, 1.5719, 3.43e-07, 2.67e-07, 2.67e-07, nan ],
[ 6500, 86.5836, 0.9761, 125.9677, 0.6709, 38.5046, 2.1949, 52.0442, 1.6239, 3.76e-07, 3.00e-07, 3.00e-07, nan ],
[ 6600, 86.7877, 1.0040, 126.2830, 0.6900, 39.2676, 2.2190, 52.3961, 1.6630, 3.70e-07, 2.96e-07, 2.59e-07, nan ],
[ 6700, 86.8390, 1.0340, 128.2768, 0.7000, 39.3338, 2.2829, 51.7550, 1.7350, 3.64e-07, 2.55e-07, 2.55e-07, nan ],
[ 6800, 87.2574, 1.0600, 130.0524, 0.7112, 40.3019, 2.2950, 52.4039, 1.7650, 3.59e-07, 3.95e-07, 2.87e-07, nan ],
[ 6900, 87.8661, 1.0839, 130.4505, 0.7300, 39.4508, 2.4140, 52.4957, 1.8141, 3.54e-07, 3.18e-07, 2.83e-07, nan ],
[ 7000, 87.7482, 1.1170, 130.3426, 0.7520, 41.9063, 2.3389, 52.3295, 1.8730, 4.53e-07, 3.14e-07, 2.44e-07, nan ],
[ 7100, 88.8320, 1.1351, 131.3037, 0.7679, 42.0156, 2.3999, 53.7804, 1.8749, 4.47e-07, 3.09e-07, 2.75e-07, nan ],
[ 7200, 89.6385, 1.1568, 132.9642, 0.7799, 41.8118, 2.4800, 54.0885, 1.9171, 3.73e-07, 2.71e-07, 3.39e-07, nan ],
[ 7300, 89.4180, 1.1921, 132.2752, 0.8059, 41.4740, 2.5702, 52.5865, 2.0270, 4.68e-07, 3.01e-07, 3.01e-07, nan ],
[ 7400, 89.8713, 1.2188, 133.2431, 0.8221, 43.3458, 2.5270, 51.3321, 2.1338, 3.96e-07, 2.97e-07, 2.97e-07, nan ],
[ 7500, 92.0106, 1.2228, 132.3393, 0.8502, 42.7466, 2.6321, 54.0699, 2.0809, 3.91e-07, 2.93e-07, 2.60e-07, nan ],
[ 7600, 91.2598, 1.2660, 132.6553, 0.8709, 44.4537, 2.5990, 52.2976, 2.2092, 4.50e-07, 3.21e-07, 2.89e-07, nan ],
[ 7700, 91.7251, 1.2929, 131.9080, 0.8991, 44.7365, 2.6510, 51.0756, 2.3220, 4.12e-07, 3.17e-07, 2.54e-07, nan ],
[ 7800, 92.5527, 1.3149, 132.4068, 0.9191, 45.3271, 2.6848, 51.5636, 2.3601, 4.38e-07, 3.13e-07, 3.13e-07, nan ],
[ 7900, 93.0182, 1.3421, 133.4011, 0.9358, 45.8774, 2.7211, 51.9547, 2.4028, 4.02e-07, 3.09e-07, 2.47e-07, nan ],
[ 8000, 92.5755, 1.3828, 134.0335, 0.9551, 46.2320, 2.7690, 53.9908, 2.3711, 3.97e-07, 3.36e-07, 2.44e-07, nan ],
[ 8100, 94.7572, 1.3850, 134.4515, 0.9761, 45.2557, 2.8999, 53.1779, 2.4679, 4.22e-07, 3.92e-07, 2.71e-07, nan ],
[ 8200, 95.9875, 1.4012, 134.6346, 0.9990, 38.3493, 3.5071, 54.6521, 2.4610, 3.87e-07, 2.98e-07, 2.98e-07, nan ],
[ 8300, 95.5623, 1.4420, 134.0354, 1.0281, 39.1705, 3.5179, 54.7882, 2.5151, 4.12e-07, 3.53e-07, 2.94e-07, nan ],
[ 8400, 96.4750, 1.4629, 135.2149, 1.0438, 40.3497, 3.4978, 53.7862, 2.6240, 4.36e-07, 3.78e-07, 2.91e-07, nan ],
[ 8500, 97.3107, 1.4851, 133.4247, 1.0831, 40.5613, 3.5629, 55.0343, 2.6259, 5.17e-07, 3.45e-07, 2.87e-07, nan ],
[ 8600, 98.1638, 1.5070, 134.7435, 1.0979, 41.2782, 3.5839, 53.8156, 2.7490, 4.26e-07, 3.12e-07, 2.84e-07, nan ],
[ 8700, 95.9515, 1.5779, 134.1091, 1.1289, 40.7526, 3.7150, 55.2132, 2.7421, 4.21e-07, 3.37e-07, 2.53e-07, nan ],
[ 8800, 97.4775, 1.5891, 134.9299, 1.1480, 41.7055, 3.7141, 54.9094, 2.8210, 3.88e-07, 3.05e-07, 2.77e-07, nan ],
[ 8900, 97.6254, 1.6229, 134.7124, 1.1761, 41.8263, 3.7880, 54.5417, 2.9049, 4.11e-07, 3.29e-07, 2.74e-07, nan ],
[ 9000, 98.9736, 1.6370, 134.3521, 1.2059, 42.6935, 3.7949, 54.7938, 2.9569, 4.88e-07, 3.80e-07, 3.53e-07, nan ],
[ 10000, 101.1630, 1.9772, 135.7076, 1.4739, 46.8868, 4.2660, 54.8294, 3.6480, 4.88e-07, 3.91e-07, 3.66e-07, nan ],
[ 12000, 102.5344, 2.8090, 139.8056, 2.0602, 45.2220, 6.3691, 56.0481, 5.1389, 5.70e-07, 4.48e-07, 3.26e-07, nan ],
[ 14000, 109.5678, 3.5779, 140.6213, 2.7878, 45.6530, 8.5871, 57.3221, 6.8390, 5.58e-07, 4.19e-07, 3.84e-07, nan ],
[ 16000, 111.1891, 4.6051, 139.4014, 3.6731, 46.3468, 11.0478, 57.5846, 8.8918, 5.49e-07, 4.27e-07, 4.27e-07, nan ],
[ 18000, 111.7302, 5.8000, 143.3425, 4.5209, 46.0969, 14.0581, 58.3926, 11.0979, 6.51e-07, 5.70e-07, 4.61e-07, nan ],
[ 20000, 115.6310, 6.9189, 144.2591, 5.5459, 46.4573, 17.2210, 57.3050, 13.9611, 7.08e-07, 5.13e-07, 4.15e-07, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/zgeev.txt
# numactl --interleave=all ./testing_zgeev -RN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zgeev_RN = array([
[ 10, nan, 0.0004 ],
[ 20, nan, 0.0007 ],
[ 30, nan, 0.0012 ],
[ 40, nan, 0.0036 ],
[ 50, nan, 0.0042 ],
[ 60, nan, 0.0049 ],
[ 70, nan, 0.0077 ],
[ 80, nan, 0.0115 ],
[ 90, nan, 0.0139 ],
[ 100, nan, 0.0175 ],
[ 200, nan, 0.0881 ],
[ 300, nan, 0.1800 ],
[ 400, nan, 0.3027 ],
[ 500, nan, 0.4473 ],
[ 600, nan, 0.8902 ],
[ 700, nan, 1.0337 ],
[ 800, nan, 1.2890 ],
[ 900, nan, 1.5493 ],
[ 1000, nan, 1.8565 ],
[ 2000, nan, 5.9068 ],
[ 3000, nan, 16.8003 ],
[ 4000, nan, 28.0323 ],
[ 5000, nan, 42.1905 ],
[ 6000, nan, 78.2203 ],
[ 7000, nan, 102.5614 ],
[ 8000, nan, 134.8554 ],
[ 9000, nan, 166.1584 ],
[ 10000, nan, 203.7712 ],
[ 12000, nan, 296.8788 ],
[ 14000, nan, 413.8873 ],
[ 16000, nan, 569.2293 ],
[ 18000, nan, 753.6494 ],
[ 20000, nan, 957.9114 ],
])
# numactl --interleave=all ./testing_zgeev -RV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zgeev_RV = array([
[ 10, nan, 0.0014 ],
[ 20, nan, 0.0017 ],
[ 30, nan, 0.0024 ],
[ 40, nan, 0.0064 ],
[ 50, nan, 0.0073 ],
[ 60, nan, 0.0089 ],
[ 70, nan, 0.0180 ],
[ 80, nan, 0.0186 ],
[ 90, nan, 0.0219 ],
[ 100, nan, 0.0281 ],
[ 200, nan, 0.1264 ],
[ 300, nan, 0.2381 ],
[ 400, nan, 0.3755 ],
[ 500, nan, 0.6030 ],
[ 600, nan, 1.0214 ],
[ 700, nan, 1.2375 ],
[ 800, nan, 1.5965 ],
[ 900, nan, 1.9500 ],
[ 1000, nan, 2.3635 ],
[ 2000, nan, 9.0155 ],
[ 3000, nan, 22.4971 ],
[ 4000, nan, 40.0431 ],
[ 5000, nan, 65.5690 ],
[ 6000, nan, 110.9951 ],
[ 7000, nan, 152.6330 ],
[ 8000, nan, 205.9501 ],
[ 9000, nan, 254.2981 ],
[ 10000, nan, 354.4332 ],
[ 12000, nan, 489.7992 ],
[ 14000, nan, 727.0022 ],
[ 16000, nan, 1010.3870 ],
[ 18000, nan, 1488.6314 ],
[ 20000, nan, 1793.5032 ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/zgeqrf.txt
# numactl --interleave=all ./testing_zgeqrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zgeqrf = array([
[ 10, 10, nan, nan, 0.12, 0.00, nan ],
[ 20, 20, nan, nan, 0.76, 0.00, nan ],
[ 30, 30, nan, nan, 1.83, 0.00, nan ],
[ 40, 40, nan, nan, 0.92, 0.00, nan ],
[ 50, 50, nan, nan, 1.59, 0.00, nan ],
[ 60, 60, nan, nan, 2.22, 0.00, nan ],
[ 70, 70, nan, nan, 1.67, 0.00, nan ],
[ 80, 80, nan, nan, 2.62, 0.00, nan ],
[ 90, 90, nan, nan, 3.44, 0.00, nan ],
[ 100, 100, nan, nan, 4.35, 0.00, nan ],
[ 200, 200, nan, nan, 13.96, 0.00, nan ],
[ 300, 300, nan, nan, 29.51, 0.00, nan ],
[ 400, 400, nan, nan, 46.09, 0.01, nan ],
[ 500, 500, nan, nan, 64.51, 0.01, nan ],
[ 600, 600, nan, nan, 83.67, 0.01, nan ],
[ 700, 700, nan, nan, 104.68, 0.02, nan ],
[ 800, 800, nan, nan, 123.91, 0.02, nan ],
[ 900, 900, nan, nan, 141.81, 0.03, nan ],
[ 1000, 1000, nan, nan, 164.11, 0.03, nan ],
[ 2000, 2000, nan, nan, 382.23, 0.11, nan ],
[ 3000, 3000, nan, nan, 545.03, 0.26, nan ],
[ 4000, 4000, nan, nan, 746.75, 0.46, nan ],
[ 5000, 5000, nan, nan, 827.59, 0.81, nan ],
[ 6000, 6000, nan, nan, 908.51, 1.27, nan ],
[ 7000, 7000, nan, nan, 956.59, 1.91, nan ],
[ 8000, 8000, nan, nan, 997.48, 2.74, nan ],
[ 9000, 9000, nan, nan, 1009.93, 3.85, nan ],
[ 10000, 10000, nan, nan, 1021.70, 5.22, nan ],
[ 12000, 12000, nan, nan, 1057.49, 8.72, nan ],
[ 14000, 14000, nan, nan, 1063.87, 13.76, nan ],
[ 16000, 16000, nan, nan, 1073.69, 20.35, nan ],
[ 18000, 18000, nan, nan, 1050.56, 29.61, nan ],
[ 20000, 20000, nan, nan, 1072.71, 39.78, nan ],
])
# numactl --interleave=all ./testing_zgeqrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zgeqrf_gpu = array([
[ 10, 10, nan, nan, 0.01, 0.00, nan ],
[ 20, 20, nan, nan, 0.05, 0.00, nan ],
[ 30, 30, nan, nan, 0.15, 0.00, nan ],
[ 40, 40, nan, nan, 0.33, 0.00, nan ],
[ 50, 50, nan, nan, 0.60, 0.00, nan ],
[ 60, 60, nan, nan, 0.95, 0.00, nan ],
[ 70, 70, nan, nan, 2.09, 0.00, nan ],
[ 80, 80, nan, nan, 3.12, 0.00, nan ],
[ 90, 90, nan, nan, 3.54, 0.00, nan ],
[ 100, 100, nan, nan, 2.70, 0.00, nan ],
[ 200, 200, nan, nan, 11.33, 0.00, nan ],
[ 300, 300, nan, nan, 25.13, 0.01, nan ],
[ 400, 400, nan, nan, 37.00, 0.01, nan ],
[ 500, 500, nan, nan, 57.51, 0.01, nan ],
[ 600, 600, nan, nan, 70.94, 0.02, nan ],
[ 700, 700, nan, nan, 92.71, 0.02, nan ],
[ 800, 800, nan, nan, 106.65, 0.03, nan ],
[ 900, 900, nan, nan, 128.17, 0.03, nan ],
[ 1000, 1000, nan, nan, 150.61, 0.04, nan ],
[ 2000, 2000, nan, nan, 347.84, 0.12, nan ],
[ 3000, 3000, nan, nan, 605.55, 0.24, nan ],
[ 4000, 4000, nan, nan, 741.14, 0.46, nan ],
[ 5000, 5000, nan, nan, 799.79, 0.83, nan ],
[ 6000, 6000, nan, nan, 877.47, 1.31, nan ],
[ 7000, 7000, nan, nan, 937.07, 1.95, nan ],
[ 8000, 8000, nan, nan, 981.20, 2.78, nan ],
[ 9000, 9000, nan, nan, 996.99, 3.90, nan ],
[ 10000, 10000, nan, nan, 1013.21, 5.26, nan ],
[ 12000, 12000, nan, nan, 1052.16, 8.76, nan ],
[ 14000, 14000, nan, nan, 1063.70, 13.76, nan ],
[ 16000, 16000, nan, nan, 1085.06, 20.14, nan ],
[ 18000, 18000, nan, nan, 1049.97, 29.63, nan ],
[ 20000, 20000, nan, nan, 1070.26, 39.87, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/zgesvd.txt
# numactl --interleave=all ./testing_zgesvd -UN -VN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000 -N 300,100 -N 600,200 -N 900,300 -N 1200,400 -N 1500,500 -N 1800,600 -N 2100,700 -N 2400,800 -N 2700,900 -N 3000,1000 -N 6000,2000 -N 9000,3000 -N 12000,4000 -N 15000,5000 -N 18000,6000 -N 21000,7000 -N 24000,8000 -N 27000,9000 -N 100,300 -N 200,600 -N 300,900 -N 400,1200 -N 500,1500 -N 600,1800 -N 700,2100 -N 800,2400 -N 900,2700 -N 1000,3000 -N 2000,6000 -N 3000,9000 -N 4000,12000 -N 5000,15000 -N 6000,18000 -N 7000,21000 -N 8000,24000 -N 9000,27000 -N 10000,100 -N 20000,200 -N 30000,300 -N 40000,400 -N 50000,500 -N 60000,600 -N 70000,700 -N 80000,800 -N 90000,900 -N 100000,1000 -N 200000,2000 -N 100,10000 -N 200,20000 -N 300,30000 -N 400,40000 -N 500,50000 -N 600,60000 -N 700,70000 -N 800,80000 -N 900,90000 -N 1000,100000 -N 2000,200000
zgesvd_UN = array([
[ nan, 10, 10, nan, 0.00, nan ],
[ nan, 20, 20, nan, 0.00, nan ],
[ nan, 30, 30, nan, 0.00, nan ],
[ nan, 40, 40, nan, 0.00, nan ],
[ nan, 50, 50, nan, 0.00, nan ],
[ nan, 60, 60, nan, 0.00, nan ],
[ nan, 70, 70, nan, 0.00, nan ],
[ nan, 80, 80, nan, 0.00, nan ],
[ nan, 90, 90, nan, 0.00, nan ],
[ nan, 100, 100, nan, 0.00, nan ],
[ nan, 200, 200, nan, 0.02, nan ],
[ nan, 300, 300, nan, 0.05, nan ],
[ nan, 400, 400, nan, 0.08, nan ],
[ nan, 500, 500, nan, 0.15, nan ],
[ nan, 600, 600, nan, 0.15, nan ],
[ nan, 700, 700, nan, 0.20, nan ],
[ nan, 800, 800, nan, 0.31, nan ],
[ nan, 900, 900, nan, 0.32, nan ],
[ nan, 1000, 1000, nan, 0.39, nan ],
[ nan, 2000, 2000, nan, 1.69, nan ],
[ nan, 3000, 3000, nan, 4.50, nan ],
[ nan, 4000, 4000, nan, 9.26, nan ],
[ nan, 5000, 5000, nan, 16.58, nan ],
[ nan, 6000, 6000, nan, 27.12, nan ],
[ nan, 7000, 7000, nan, 40.84, nan ],
[ nan, 8000, 8000, nan, 59.67, nan ],
[ nan, 9000, 9000, nan, 82.25, nan ],
[ nan, 10000, 10000, nan, 113.55, nan ],
[ nan, 12000, 12000, nan, 204.99, nan ],
[ nan, 14000, 14000, nan, 302.73, nan ],
[ nan, 16000, 16000, nan, 460.29, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/zgetrf.txt
# numactl --interleave=all ./testing_zgetrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zgetrf = array([
[ 10, 10, nan, nan, 0.26, 0.00, nan ],
[ 20, 20, nan, nan, 0.75, 0.00, nan ],
[ 30, 30, nan, nan, 1.27, 0.00, nan ],
[ 40, 40, nan, nan, 3.09, 0.00, nan ],
[ 50, 50, nan, nan, 2.22, 0.00, nan ],
[ 60, 60, nan, nan, 3.92, 0.00, nan ],
[ 70, 70, nan, nan, 1.11, 0.00, nan ],
[ 80, 80, nan, nan, 1.59, 0.00, nan ],
[ 90, 90, nan, nan, 2.07, 0.00, nan ],
[ 100, 100, nan, nan, 2.71, 0.00, nan ],
[ 200, 200, nan, nan, 10.69, 0.00, nan ],
[ 300, 300, nan, nan, 23.03, 0.00, nan ],
[ 400, 400, nan, nan, 36.86, 0.00, nan ],
[ 500, 500, nan, nan, 52.48, 0.01, nan ],
[ 600, 600, nan, nan, 68.63, 0.01, nan ],
[ 700, 700, nan, nan, 87.08, 0.01, nan ],
[ 800, 800, nan, nan, 105.82, 0.01, nan ],
[ 900, 900, nan, nan, 123.14, 0.02, nan ],
[ 1000, 1000, nan, nan, 142.71, 0.02, nan ],
[ 2000, 2000, nan, nan, 339.72, 0.06, nan ],
[ 3000, 3000, nan, nan, 518.56, 0.14, nan ],
[ 4000, 4000, nan, nan, 627.35, 0.27, nan ],
[ 5000, 5000, nan, nan, 684.01, 0.49, nan ],
[ 6000, 6000, nan, nan, 772.08, 0.75, nan ],
[ 7000, 7000, nan, nan, 829.56, 1.10, nan ],
[ 8000, 8000, nan, nan, 882.56, 1.55, nan ],
[ 9000, 9000, nan, nan, 906.12, 2.15, nan ],
[ 10000, 10000, nan, nan, 944.31, 2.82, nan ],
[ 12000, 12000, nan, nan, 994.15, 4.63, nan ],
[ 14000, 14000, nan, nan, 1027.60, 7.12, nan ],
[ 16000, 16000, nan, nan, 1053.91, 10.36, nan ],
[ 18000, 18000, nan, nan, 1063.89, 14.62, nan ],
[ 20000, 20000, nan, nan, 1071.63, 19.91, nan ],
])
# numactl --interleave=all ./testing_zgetrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zgetrf_gpu = array([
[ 10, 10, nan, nan, 0.06, 0.00, nan ],
[ 20, 20, nan, nan, 0.36, 0.00, nan ],
[ 30, 30, nan, nan, 0.69, 0.00, nan ],
[ 40, 40, nan, nan, 1.38, 0.00, nan ],
[ 50, 50, nan, nan, 1.19, 0.00, nan ],
[ 60, 60, nan, nan, 2.64, 0.00, nan ],
[ 70, 70, nan, nan, 0.67, 0.00, nan ],
[ 80, 80, nan, nan, 1.02, 0.00, nan ],
[ 90, 90, nan, nan, 1.35, 0.00, nan ],
[ 100, 100, nan, nan, 1.79, 0.00, nan ],
[ 200, 200, nan, nan, 7.88, 0.00, nan ],
[ 300, 300, nan, nan, 18.82, 0.00, nan ],
[ 400, 400, nan, nan, 32.03, 0.01, nan ],
[ 500, 500, nan, nan, 50.66, 0.01, nan ],
[ 600, 600, nan, nan, 68.52, 0.01, nan ],
[ 700, 700, nan, nan, 89.21, 0.01, nan ],
[ 800, 800, nan, nan, 110.91, 0.01, nan ],
[ 900, 900, nan, nan, 133.32, 0.01, nan ],
[ 1000, 1000, nan, nan, 161.19, 0.02, nan ],
[ 2000, 2000, nan, nan, 405.92, 0.05, nan ],
[ 3000, 3000, nan, nan, 630.44, 0.11, nan ],
[ 4000, 4000, nan, nan, 753.23, 0.23, nan ],
[ 5000, 5000, nan, nan, 725.11, 0.46, nan ],
[ 6000, 6000, nan, nan, 884.64, 0.65, nan ],
[ 7000, 7000, nan, nan, 945.01, 0.97, nan ],
[ 8000, 8000, nan, nan, 996.60, 1.37, nan ],
[ 9000, 9000, nan, nan, 986.27, 1.97, nan ],
[ 10000, 10000, nan, nan, 1021.82, 2.61, nan ],
[ 12000, 12000, nan, nan, 1076.85, 4.28, nan ],
[ 14000, 14000, nan, nan, 1110.41, 6.59, nan ],
[ 16000, 16000, nan, nan, 1120.76, 9.75, nan ],
[ 18000, 18000, nan, nan, 1133.20, 13.72, nan ],
[ 20000, 20000, nan, nan, 1120.56, 19.04, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/zheevd.txt
# numactl --interleave=all ./testing_zheevd -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zheevd_JN = array([
[ 10, nan, 0.0000 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0001 ],
[ 40, nan, 0.0002 ],
[ 50, nan, 0.0003 ],
[ 60, nan, 0.0004 ],
[ 70, nan, 0.0007 ],
[ 80, nan, 0.0009 ],
[ 90, nan, 0.0013 ],
[ 100, nan, 0.0016 ],
[ 200, nan, 0.0148 ],
[ 300, nan, 0.0275 ],
[ 400, nan, 0.0471 ],
[ 500, nan, 0.0672 ],
[ 600, nan, 0.0942 ],
[ 700, nan, 0.1218 ],
[ 800, nan, 0.1559 ],
[ 900, nan, 0.1931 ],
[ 1000, nan, 0.2313 ],
[ 2000, nan, 0.8349 ],
[ 3000, nan, 2.0546 ],
[ 4000, nan, 3.9284 ],
[ 5000, nan, 6.6537 ],
[ 6000, nan, 10.3261 ],
[ 7000, nan, 15.1780 ],
[ 8000, nan, 21.2056 ],
[ 9000, nan, 28.8199 ],
[ 10000, nan, 37.7967 ],
[ 12000, nan, 61.5253 ],
[ 14000, nan, 93.0888 ],
[ 16000, nan, 135.2279 ],
[ 18000, nan, 189.0661 ],
[ 20000, nan, 256.5293 ],
])
# numactl --interleave=all ./testing_zheevd -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zheevd_JV = array([
[ 10, nan, 0.0002 ],
[ 20, nan, 0.0002 ],
[ 30, nan, 0.0003 ],
[ 40, nan, 0.0005 ],
[ 50, nan, 0.0007 ],
[ 60, nan, 0.0009 ],
[ 70, nan, 0.0014 ],
[ 80, nan, 0.0018 ],
[ 90, nan, 0.0022 ],
[ 100, nan, 0.0027 ],
[ 200, nan, 0.0201 ],
[ 300, nan, 0.0345 ],
[ 400, nan, 0.0567 ],
[ 500, nan, 0.0815 ],
[ 600, nan, 0.1100 ],
[ 700, nan, 0.1416 ],
[ 800, nan, 0.1816 ],
[ 900, nan, 0.2242 ],
[ 1000, nan, 0.2697 ],
[ 2000, nan, 1.0056 ],
[ 3000, nan, 2.3441 ],
[ 4000, nan, 4.5146 ],
[ 5000, nan, 7.7003 ],
[ 6000, nan, 12.1018 ],
[ 7000, nan, 18.2927 ],
[ 8000, nan, 25.3105 ],
[ 9000, nan, 34.7899 ],
[ 10000, nan, 45.9261 ],
[ 12000, nan, 74.9215 ],
[ 14000, nan, 114.9891 ],
[ 16000, nan, 167.8138 ],
[ 18000, nan, 236.7416 ],
[ 20000, nan, 321.9395 ],
])
# numactl --interleave=all ./testing_zheevd_gpu -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zheevd_gpu_JN = array([
[ 10, nan, 0.0001 ],
[ 20, nan, 0.0001 ],
[ 30, nan, 0.0002 ],
[ 40, nan, 0.0002 ],
[ 50, nan, 0.0003 ],
[ 60, nan, 0.0005 ],
[ 70, nan, 0.0008 ],
[ 80, nan, 0.0010 ],
[ 90, nan, 0.0014 ],
[ 100, nan, 0.0017 ],
[ 200, nan, 0.0148 ],
[ 300, nan, 0.0271 ],
[ 400, nan, 0.0465 ],
[ 500, nan, 0.0666 ],
[ 600, nan, 0.0933 ],
[ 700, nan, 0.1251 ],
[ 800, nan, 0.1540 ],
[ 900, nan, 0.1913 ],
[ 1000, nan, 0.2276 ],
[ 2000, nan, 0.8259 ],
[ 3000, nan, 2.0320 ],
[ 4000, nan, 3.9013 ],
[ 5000, nan, 6.5860 ],
[ 6000, nan, 10.2309 ],
[ 7000, nan, 14.9722 ],
[ 8000, nan, 21.0334 ],
[ 9000, nan, 28.4432 ],
[ 10000, nan, 37.5093 ],
[ 12000, nan, 60.9586 ],
[ 14000, nan, 92.5242 ],
[ 16000, nan, 134.1422 ],
[ 18000, nan, 187.9327 ],
[ 20000, nan, nan ], # malloc failed?
])
# numactl --interleave=all ./testing_zheevd_gpu -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zheevd_gpu_JV = array([
[ 10, nan, 0.0002 ],
[ 20, nan, 0.0002 ],
[ 30, nan, 0.0004 ],
[ 40, nan, 0.0006 ],
[ 50, nan, 0.0007 ],
[ 60, nan, 0.0010 ],
[ 70, nan, 0.0015 ],
[ 80, nan, 0.0019 ],
[ 90, nan, 0.0023 ],
[ 100, nan, 0.0029 ],
[ 200, nan, 0.0195 ],
[ 300, nan, 0.0338 ],
[ 400, nan, 0.0564 ],
[ 500, nan, 0.0801 ],
[ 600, nan, 0.1067 ],
[ 700, nan, 0.1368 ],
[ 800, nan, 0.1755 ],
[ 900, nan, 0.2180 ],
[ 1000, nan, 0.2612 ],
[ 2000, nan, 0.9518 ],
[ 3000, nan, 2.3471 ],
[ 4000, nan, 4.5293 ],
[ 5000, nan, 7.8989 ],
[ 6000, nan, 12.3295 ],
[ 7000, nan, 17.7410 ],
[ 8000, nan, 25.4602 ],
[ 9000, nan, 34.6644 ],
[ 10000, nan, 45.8345 ],
[ 12000, nan, 74.5212 ],
[ 14000, nan, 116.1441 ],
[ 16000, nan, 167.4060 ],
[ 18000, nan, 237.8173 ],
[ 20000, nan, nan ], # malloc failed?
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/zheevd_2stage.txt
# numactl --interleave=all ./testing_zheevdx_2stage -JN -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zheevdx_2stage_JN = array([
[ 10, 0, 0.0002 ],
[ 20, 0, 0.0000 ],
[ 30, 0, 0.0000 ],
[ 40, 0, 0.0000 ],
[ 50, 0, 0.0000 ],
[ 60, 0, 0.0000 ],
[ 70, 0, 0.0000 ],
[ 80, 0, 0.0000 ],
[ 90, 0, 0.0000 ],
[ 100, 0, 0.0000 ],
[ 200, 200, 0.0068 ],
[ 300, 300, 0.0415 ],
[ 400, 400, 0.0791 ],
[ 500, 500, 0.1287 ],
[ 600, 600, 0.1797 ],
[ 700, 700, 0.2359 ],
[ 800, 800, 0.2890 ],
[ 900, 900, 0.3333 ],
[ 1000, 1000, 0.3589 ],
[ 2000, 2000, 0.8954 ],
[ 3000, 3000, 1.7160 ],
[ 4000, 4000, 2.5617 ],
[ 5000, 5000, 3.6103 ],
[ 6000, 6000, 4.9139 ],
[ 7000, 7000, 6.5160 ],
[ 8000, 8000, 8.4061 ],
[ 9000, 9000, 10.5946 ],
[ 10000, 10000, 13.3940 ],
[ 12000, 12000, 20.1843 ],
[ 14000, 14000, 30.0964 ],
[ 16000, 16000, 41.2036 ],
[ 18000, 18000, 56.8361 ],
[ 20000, 20000, 73.6939 ],
])
# numactl --interleave=all ./testing_zheevdx_2stage -JV -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zheevdx_2stage_JV = array([
[ 10, 10, 0.0002 ],
[ 20, 20, 0.0002 ],
[ 30, 30, 0.0003 ],
[ 40, 40, 0.0005 ],
[ 50, 50, 0.0007 ],
[ 60, 60, 0.0010 ],
[ 70, 70, 0.0014 ],
[ 80, 80, 0.0018 ],
[ 90, 90, 0.0022 ],
[ 100, 100, 0.0027 ],
[ 200, 200, 0.0107 ],
[ 300, 300, 0.0485 ],
[ 400, 400, 0.0860 ],
[ 500, 500, 0.1354 ],
[ 600, 600, 0.1774 ],
[ 700, 700, 0.2385 ],
[ 800, 800, 0.3178 ],
[ 900, 900, 0.3811 ],
[ 1000, 1000, 0.4447 ],
[ 2000, 2000, 1.4069 ],
[ 3000, 3000, 2.6774 ],
[ 4000, 4000, 4.1303 ],
[ 5000, 5000, 6.3914 ],
[ 6000, 6000, 10.9810 ],
[ 7000, 7000, 15.2683 ],
[ 8000, 8000, 20.8768 ],
[ 9000, 9000, 27.3412 ],
[ 10000, 10000, 33.2341 ],
[ 12000, 12000, 54.8366 ],
[ 14000, 14000, 94.2965 ],
[ 16000, 16000, 129.5659 ],
[ 18000, 18000, 174.3231 ],
[ 20000, 20000, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/zhemv.txt
# numactl --interleave=all ./testing_zhemv -N 100 -N 1000 --range 10:90:1 --range 100:900:10 --range 1000:9000:100 --range 10000:20000:2000
zhemv_L = array([
[ 10, 0.0214, 0.0429, 0.0297, 0.0310, 0.0341, 0.0269, 0.2968, 0.0031, 1.99e-16, 2.51e-16, 3.20e-16, nan ],
[ 11, 0.0275, 0.0401, 0.0381, 0.0288, 0.0423, 0.0260, 0.5126, 0.0021, 3.61e-16, 3.33e-16, 2.28e-16, nan ],
[ 12, 0.0324, 0.0401, 0.0435, 0.0298, 0.0518, 0.0250, 0.6795, 0.0019, 3.70e-16, 3.70e-16, 4.74e-16, nan ],
[ 13, 0.0388, 0.0389, 0.0487, 0.0310, 0.0580, 0.0260, 0.4865, 0.0031, 1.93e-16, 3.06e-16, 1.93e-16, nan ],
[ 14, 0.0433, 0.0401, 0.0578, 0.0300, 0.0668, 0.0260, 0.5601, 0.0031, 2.54e-16, 3.92e-16, 2.84e-16, nan ],
[ 15, 0.0494, 0.0401, 0.0664, 0.0298, 0.0762, 0.0260, 1.0381, 0.0019, 2.65e-16, 2.65e-16, 2.65e-16, nan ],
[ 16, 0.0559, 0.0401, 0.0746, 0.0300, 0.0862, 0.0260, 1.1744, 0.0019, 3.14e-16, 4.45e-16, 4.74e-16, nan ],
[ 17, 0.0628, 0.0401, 0.0838, 0.0300, 0.0902, 0.0279, 0.8794, 0.0029, 4.31e-16, 4.21e-16, 4.46e-16, nan ],
[ 18, 0.0669, 0.0420, 0.0935, 0.0300, 0.1007, 0.0279, 1.4722, 0.0019, 3.21e-16, 4.02e-16, 2.96e-16, nan ],
[ 19, 0.0743, 0.0420, 0.1005, 0.0310, 0.0920, 0.0339, 1.0891, 0.0029, 4.67e-16, 5.91e-16, 4.41e-16, nan ],
[ 20, 0.0802, 0.0429, 0.1145, 0.0300, 0.1223, 0.0281, 1.2024, 0.0029, 3.97e-16, 4.87e-16, 3.97e-16, nan ],
[ 21, 0.0973, 0.0389, 0.1258, 0.0300, 0.1391, 0.0272, 0.9909, 0.0038, 5.08e-16, 3.61e-16, 4.79e-16, nan ],
[ 22, 0.1039, 0.0398, 0.1377, 0.0300, 0.1535, 0.0269, 1.0204, 0.0041, 3.61e-16, 3.23e-16, 4.04e-16, nan ],
[ 23, 0.1189, 0.0379, 0.1501, 0.0300, 0.1735, 0.0260, 1.1122, 0.0041, 5.36e-16, 3.45e-16, 4.37e-16, nan ],
[ 24, 0.1283, 0.0381, 0.1630, 0.0300, 0.1817, 0.0269, 1.5796, 0.0031, 5.92e-16, 5.34e-16, 4.44e-16, nan ],
[ 25, 0.1355, 0.0391, 0.1764, 0.0300, 0.1884, 0.0281, 1.3894, 0.0038, 3.18e-16, 3.18e-16, 3.18e-16, nan ],
[ 26, 0.1395, 0.0410, 0.1845, 0.0310, 0.2051, 0.0279, 1.4113, 0.0041, 3.86e-16, 5.63e-16, 3.86e-16, nan ],
[ 27, 0.1537, 0.0401, 0.2049, 0.0300, 0.2134, 0.0288, 1.5188, 0.0041, 3.72e-16, 4.00e-16, 3.72e-16, nan ],
[ 28, 0.1575, 0.0420, 0.2132, 0.0310, 0.2272, 0.0291, 1.6304, 0.0041, 3.81e-16, 2.84e-16, 4.26e-16, nan ],
[ 29, 0.1777, 0.0398, 0.2283, 0.0310, 0.2374, 0.0298, 1.7458, 0.0041, 3.47e-16, 3.73e-16, 3.47e-16, nan ],
[ 30, 0.1899, 0.0398, 0.2349, 0.0322, 0.2621, 0.0288, 1.5099, 0.0050, 4.27e-16, 2.65e-16, 2.65e-16, nan ],
[ 31, 0.2074, 0.0389, 0.2523, 0.0319, 0.2771, 0.0291, 1.6098, 0.0050, 4.90e-16, 4.73e-16, 3.05e-16, nan ],
[ 32, 0.2141, 0.0401, 0.2767, 0.0310, 0.3074, 0.0279, 1.7129, 0.0050, 3.55e-16, 4.58e-16, 5.39e-16, nan ],
[ 33, 0.2274, 0.0401, 0.2122, 0.0429, 0.3032, 0.0300, 1.8191, 0.0050, 3.05e-16, 3.88e-16, 4.81e-16, nan ],
[ 34, 0.2355, 0.0410, 0.2425, 0.0398, 0.3214, 0.0300, 1.9286, 0.0050, 3.35e-16, 4.67e-16, 3.77e-16, nan ],
[ 35, 0.2492, 0.0410, 0.2552, 0.0401, 0.3402, 0.0300, 1.0206, 0.0100, 4.06e-16, 4.19e-16, 4.19e-16, nan ],
[ 36, 0.2574, 0.0420, 0.2762, 0.0391, 0.3484, 0.0310, 1.8119, 0.0060, 4.93e-16, 4.02e-16, 3.98e-16, nan ],
[ 37, 0.2845, 0.0401, 0.2845, 0.0401, 0.3794, 0.0300, 1.9119, 0.0060, 4.80e-16, 4.80e-16, 3.84e-16, nan ],
[ 38, 0.3016, 0.0398, 0.2998, 0.0401, 0.3997, 0.0300, 2.0146, 0.0060, 3.92e-16, 3.74e-16, 4.18e-16, nan ],
[ 39, 0.2994, 0.0422, 0.3232, 0.0391, 0.4240, 0.0298, 2.0384, 0.0062, 5.15e-16, 6.57e-16, 5.83e-16, nan ],
[ 40, 0.3077, 0.0432, 0.3315, 0.0401, 0.4566, 0.0291, 2.2280, 0.0060, 3.20e-16, 3.97e-16, 3.55e-16, nan ],
[ 41, 0.3480, 0.0401, 0.3480, 0.0401, 0.4793, 0.0291, 2.3387, 0.0060, 4.90e-16, 5.48e-16, 5.20e-16, nan ],
[ 42, 0.3406, 0.0429, 0.3649, 0.0401, 0.4865, 0.0300, 2.4522, 0.0060, 5.42e-16, 4.23e-16, 4.79e-16, nan ],
[ 43, 0.3822, 0.0401, 0.3822, 0.0401, 0.5096, 0.0300, 2.2140, 0.0069, 6.61e-16, 3.69e-16, 3.41e-16, nan ],
[ 44, 0.3999, 0.0401, 0.3906, 0.0410, 0.5331, 0.0300, 2.2392, 0.0072, 5.42e-16, 6.51e-16, 5.42e-16, nan ],
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[ 800, 27.2688, 0.1881, 32.8977, 0.1559, 35.3286, 0.1452, 6.2708, 0.8180, 2.11e-15, 2.15e-15, 2.01e-15, nan ],
[ 810, 27.8132, 0.1891, 33.0672, 0.1590, 36.2760, 0.1450, 6.2147, 0.8461, 2.16e-15, 1.98e-15, 2.11e-15, nan ],
[ 820, 28.2188, 0.1910, 33.6859, 0.1600, 36.1652, 0.1490, 6.2148, 0.8671, 2.23e-15, 2.21e-15, 2.10e-15, nan ],
[ 830, 28.7670, 0.1919, 34.5118, 0.1600, 37.0519, 0.1490, 6.1770, 0.8938, 2.17e-15, 2.30e-15, 2.43e-15, nan ],
[ 840, 28.8193, 0.1962, 34.2255, 0.1652, 36.9444, 0.1531, 6.2139, 0.9100, 2.00e-15, 2.19e-15, 2.10e-15, nan ],
[ 850, 29.0849, 0.1991, 34.8935, 0.1659, 37.1343, 0.1559, 6.2383, 0.9282, 2.78e-15, 2.56e-15, 2.56e-15, nan ],
[ 860, 29.6307, 0.2000, 36.3985, 0.1628, 37.7814, 0.1569, 10.6788, 0.5550, 2.25e-15, 2.66e-15, 2.31e-15, nan ],
[ 870, 30.6520, 0.1979, 36.2926, 0.1671, 38.6057, 0.1571, 10.6404, 0.5701, 2.03e-15, 2.28e-15, 2.03e-15, nan ],
[ 880, 31.1723, 0.1991, 37.1841, 0.1669, 39.7995, 0.1559, 10.6284, 0.5839, 2.34e-15, 2.34e-15, 2.33e-15, nan ],
[ 890, 31.2480, 0.2031, 37.9790, 0.1671, 40.4609, 0.1569, 10.5439, 0.6020, 2.43e-15, 2.33e-15, 2.31e-15, nan ],
[ 900, 31.3645, 0.2069, 37.7069, 0.1721, 40.5729, 0.1600, 10.6553, 0.6092, 2.84e-15, 2.38e-15, 2.49e-15, nan ],
[ 1000, 34.3959, 0.2329, 42.1641, 0.1900, 44.5096, 0.1800, 10.3911, 0.7710, 3.31e-15, 2.96e-15, 3.23e-15, nan ],
[ 1100, 37.5751, 0.2580, 45.9392, 0.2110, 28.3516, 0.3419, 10.6180, 0.9129, 3.19e-15, 3.24e-15, 3.24e-15, nan ],
[ 1200, 41.3494, 0.2789, 51.3031, 0.2248, 30.9130, 0.3731, 9.4306, 1.2231, 3.04e-15, 3.44e-15, 3.23e-15, nan ],
[ 1300, 44.2153, 0.3061, 54.3797, 0.2489, 32.6278, 0.4148, 8.5346, 1.5860, 3.33e-15, 3.15e-15, 3.22e-15, nan ],
[ 1400, 48.4453, 0.3240, 60.6235, 0.2589, 34.6511, 0.4530, 8.1877, 1.9171, 3.45e-15, 4.07e-15, 3.90e-15, nan ],
[ 1500, 52.2273, 0.3450, 65.4878, 0.2751, 37.5425, 0.4799, 8.4392, 2.1350, 3.54e-15, 2.77e-15, 3.06e-15, nan ],
[ 1600, 55.3994, 0.3700, 68.7839, 0.2980, 38.8171, 0.5281, 8.3468, 2.4559, 3.14e-15, 3.04e-15, 2.70e-15, nan ],
[ 1700, 59.1816, 0.3910, 73.4730, 0.3150, 40.1730, 0.5760, 8.3938, 2.7568, 3.76e-15, 3.66e-15, 3.27e-15, nan ],
[ 1800, 63.4073, 0.4091, 75.8765, 0.3419, 42.6694, 0.6080, 7.8635, 3.2990, 3.33e-15, 3.62e-15, 3.41e-15, nan ],
[ 1900, 65.5636, 0.4408, 77.4614, 0.3731, 44.9489, 0.6430, 8.4414, 3.4239, 5.07e-15, 5.00e-15, 4.89e-15, nan ],
[ 2000, 64.4213, 0.4971, 76.9733, 0.4160, 44.4910, 0.7198, 8.2323, 3.8900, 3.93e-15, 4.00e-15, 3.81e-15, nan ],
[ 2100, 66.4934, 0.5310, 78.1017, 0.4520, 35.0238, 1.0080, 8.4584, 4.1740, 3.76e-15, 3.51e-15, 3.81e-15, nan ],
[ 2200, 67.2658, 0.5760, 78.7757, 0.4919, 37.2910, 1.0390, 8.1846, 4.7340, 4.15e-15, 4.37e-15, 4.17e-15, nan ],
[ 2300, 68.2886, 0.6201, 78.4189, 0.5400, 38.4290, 1.1020, 7.7971, 5.4312, 4.35e-15, 4.95e-15, 4.55e-15, nan ],
[ 2400, 70.8145, 0.6511, 78.6795, 0.5860, 40.0237, 1.1520, 8.4681, 5.4450, 5.39e-15, 5.73e-15, 6.04e-15, nan ],
[ 2500, 71.1808, 0.7029, 78.7987, 0.6349, 42.0018, 1.1911, 8.4583, 5.9149, 5.28e-15, 5.28e-15, 4.73e-15, nan ],
[ 2600, 71.4831, 0.7570, 79.6906, 0.6790, 42.5415, 1.2720, 8.2829, 6.5329, 5.84e-15, 4.69e-15, 5.07e-15, nan ],
[ 2700, 73.4757, 0.7942, 79.2834, 0.7360, 44.0987, 1.3232, 8.3515, 6.9871, 4.90e-15, 4.24e-15, 4.53e-15, nan ],
[ 2800, 75.4393, 0.8318, 80.4670, 0.7799, 40.5371, 1.5481, 8.4630, 7.4151, 6.08e-15, 5.87e-15, 5.04e-15, nan ],
[ 2900, 75.6332, 0.8900, 81.6008, 0.8249, 45.9760, 1.4641, 8.5134, 7.9069, 4.26e-15, 4.58e-15, 4.71e-15, nan ],
[ 3000, 77.3728, 0.9310, 82.5071, 0.8731, 46.1213, 1.5619, 8.2487, 8.7330, 5.07e-15, 4.46e-15, 5.37e-15, nan ],
[ 3100, 78.2474, 0.9830, 83.6872, 0.9191, 38.5533, 1.9951, 8.4146, 9.1410, 4.85e-15, 5.16e-15, 4.85e-15, nan ],
[ 3200, 80.2799, 1.0209, 84.0691, 0.9749, 40.7152, 2.0130, 9.0613, 9.0449, 5.78e-15, 5.55e-15, 5.57e-15, nan ],
[ 3300, 82.0040, 1.0629, 85.5344, 1.0190, 41.5236, 2.0990, 8.5677, 10.1731, 5.83e-15, 6.03e-15, 6.08e-15, nan ],
[ 3400, 82.8304, 1.1170, 86.3892, 1.0710, 42.1118, 2.1970, 8.4019, 11.0118, 6.40e-15, 5.89e-15, 6.04e-15, nan ],
[ 3500, 84.0765, 1.1661, 87.4560, 1.1210, 43.9852, 2.2290, 8.4583, 11.5912, 5.33e-15, 4.88e-15, 4.68e-15, nan ],
[ 3600, 86.2161, 1.2031, 87.8882, 1.1802, 44.6889, 2.3210, 8.3011, 12.4950, 4.98e-15, 5.08e-15, 5.21e-15, nan ],
[ 3700, 88.2894, 1.2410, 87.6495, 1.2500, 44.7030, 2.4509, 8.4580, 12.9540, 7.14e-15, 6.15e-15, 6.24e-15, nan ],
[ 3800, 89.5800, 1.2901, 88.6138, 1.3041, 45.7669, 2.5251, 8.2229, 14.0541, 4.79e-15, 5.35e-15, 5.03e-15, nan ],
[ 3900, 88.0882, 1.3819, 88.5926, 1.3740, 47.1605, 2.5811, 8.4119, 14.4708, 6.18e-15, 6.43e-15, 5.60e-15, nan ],
[ 4000, 88.3052, 1.4501, 88.6697, 1.4441, 46.9551, 2.7270, 8.4542, 15.1460, 8.13e-15, 7.03e-15, 7.12e-15, nan ],
[ 4100, 87.9315, 1.5299, 87.9863, 1.5290, 38.9035, 3.4580, 7.9547, 16.9120, 6.49e-15, 6.29e-15, 6.51e-15, nan ],
[ 4200, 89.1197, 1.5841, 88.4013, 1.5969, 41.2679, 3.4208, 8.3409, 16.9251, 7.64e-15, 7.16e-15, 7.21e-15, nan ],
[ 4300, 90.4984, 1.6351, 88.5613, 1.6708, 42.8647, 3.4521, 8.4257, 17.5619, 6.87e-15, 7.02e-15, 7.41e-15, nan ],
[ 4400, 90.7211, 1.7078, 89.6696, 1.7278, 44.4453, 3.4859, 8.4524, 18.3301, 6.15e-15, 6.33e-15, 6.45e-15, nan ],
[ 4500, 91.8643, 1.7641, 89.7773, 1.8051, 43.9881, 3.6840, 8.4744, 19.1228, 6.38e-15, 6.61e-15, 6.14e-15, nan ],
[ 4600, 91.9290, 1.8420, 89.9725, 1.8821, 45.5459, 3.7179, 8.2800, 20.4511, 7.94e-15, 7.22e-15, 6.91e-15, nan ],
[ 4700, 92.6933, 1.9071, 89.4180, 1.9770, 45.8679, 3.8540, 8.5943, 20.5691, 6.17e-15, 6.62e-15, 6.32e-15, nan ],
[ 4800, 92.8374, 1.9860, 90.2060, 2.0440, 46.0950, 3.9999, 8.5913, 21.4610, 7.29e-15, 6.77e-15, 6.09e-15, nan ],
[ 4900, 92.7695, 2.0711, 89.9128, 2.1369, 47.4890, 4.0460, 8.6061, 22.3260, 8.60e-15, 7.83e-15, 7.27e-15, nan ],
[ 5000, 94.2399, 2.1229, 90.6463, 2.2070, 47.7827, 4.1869, 8.4930, 23.5560, 7.46e-15, 6.79e-15, 6.76e-15, nan ],
[ 5100, 93.9627, 2.2151, 90.5328, 2.2991, 48.8150, 4.2639, 8.5444, 24.3599, 8.21e-15, 7.87e-15, 7.45e-15, nan ],
[ 5200, 95.7861, 2.2590, 91.8411, 2.3561, 43.3106, 4.9961, 8.6132, 25.1222, 7.62e-15, 8.81e-15, 8.19e-15, nan ],
[ 5300, 96.6391, 2.3260, 91.8292, 2.4478, 43.8700, 5.1239, 8.6323, 26.0398, 8.09e-15, 7.39e-15, 7.75e-15, nan ],
[ 5400, 96.6636, 2.4140, 91.7606, 2.5430, 43.4870, 5.3658, 8.3082, 28.0859, 7.52e-15, 7.13e-15, 7.19e-15, nan ],
[ 5500, 98.2769, 2.4631, 92.1073, 2.6281, 44.8771, 5.3940, 8.5884, 28.1851, 7.80e-15, 7.50e-15, 7.40e-15, nan ],
[ 5600, 99.3439, 2.5260, 91.3909, 2.7459, 46.0795, 5.4460, 8.6243, 29.0978, 6.73e-15, 6.82e-15, 8.29e-15, nan ],
[ 5700, 99.3776, 2.6162, 92.3580, 2.8150, 45.5959, 5.7020, 8.6504, 30.0550, 7.51e-15, 7.66e-15, 7.82e-15, nan ],
[ 5800, 98.4276, 2.7349, 91.7192, 2.9349, 47.2510, 5.6970, 8.5195, 31.5969, 9.77e-15, 9.50e-15, 8.77e-15, nan ],
[ 5900, 98.7764, 2.8200, 92.4236, 3.0138, 47.3160, 5.8870, 8.3164, 33.4940, 7.59e-15, 6.96e-15, 7.36e-15, nan ],
[ 6000, 99.5765, 2.8930, 92.8076, 3.1040, 48.7497, 5.9092, 8.7234, 33.0229, 7.65e-15, 8.34e-15, 8.60e-15, nan ],
[ 6100, 99.4876, 2.9929, 92.8181, 3.2079, 48.4696, 6.1431, 8.6965, 34.2381, 8.56e-15, 8.41e-15, 8.09e-15, nan ],
[ 6200, 99.4791, 3.0921, 92.7094, 3.3178, 43.7604, 7.0291, 8.1059, 37.9469, 8.77e-15, 7.33e-15, 7.14e-15, nan ],
[ 6300, 99.6851, 3.1860, 92.5386, 3.4320, 44.4876, 7.1390, 8.6725, 36.6211, 7.80e-15, 7.06e-15, 7.83e-15, nan ],
[ 6400, 100.0227, 3.2768, 91.8863, 3.5670, 44.3699, 7.3869, 9.1806, 35.7010, 7.25e-15, 7.02e-15, 6.82e-15, nan ],
[ 6500, 101.4090, 3.3338, 91.9229, 3.6778, 44.7602, 7.5531, 8.5447, 39.5660, 8.65e-15, 8.89e-15, 8.45e-15, nan ],
[ 6600, 101.1739, 3.4451, 92.4825, 3.7689, 45.8210, 7.6070, 8.1708, 42.6590, 7.22e-15, 7.57e-15, 7.65e-15, nan ],
[ 6700, 100.8701, 3.5610, 92.6737, 3.8760, 46.0465, 7.8008, 8.4464, 42.5270, 8.01e-15, 9.00e-15, 9.09e-15, nan ],
[ 6800, 100.8185, 3.6700, 92.0844, 4.0181, 46.2384, 8.0020, 8.4518, 43.7779, 9.13e-15, 8.55e-15, 8.76e-15, nan ],
[ 6900, 101.6718, 3.7470, 93.1433, 4.0901, 47.3950, 8.0380, 8.2127, 46.3870, 8.09e-15, 8.61e-15, 7.92e-15, nan ],
[ 7000, 101.7396, 3.8538, 92.6020, 4.2341, 47.8559, 8.1930, 8.3000, 47.2391, 7.82e-15, 7.37e-15, 7.80e-15, nan ],
[ 7100, 100.5908, 4.0100, 92.9631, 4.3390, 48.2321, 8.3630, 8.2241, 49.0470, 8.14e-15, 8.94e-15, 7.90e-15, nan ],
[ 7200, 102.6748, 4.0400, 92.3621, 4.4911, 44.0384, 9.4192, 8.3794, 49.5028, 7.41e-15, 8.43e-15, 7.95e-15, nan ],
[ 7300, 103.5481, 4.1180, 93.5106, 4.5600, 45.1557, 9.4430, 7.8723, 54.1658, 7.77e-15, 7.85e-15, 7.61e-15, nan ],
[ 7400, 103.5855, 4.2300, 92.8751, 4.7178, 44.9871, 9.7399, 8.0235, 54.6110, 7.64e-15, 7.63e-15, 7.41e-15, nan ],
[ 7500, 104.7447, 4.2970, 93.0875, 4.8351, 44.9330, 10.0169, 8.0909, 55.6290, 8.62e-15, 8.71e-15, 8.97e-15, nan ],
[ 7600, 105.2096, 4.3929, 93.0488, 4.9670, 45.5739, 10.1411, 8.1013, 57.0488, 7.76e-15, 8.67e-15, 7.84e-15, nan ],
[ 7700, 103.5130, 4.5831, 92.9306, 5.1050, 46.4924, 10.2041, 7.9385, 59.7610, 9.77e-15, 1.01e-14, 1.06e-14, nan ],
[ 7800, 102.8119, 4.7350, 93.2434, 5.2209, 47.0710, 10.3421, 7.4230, 65.5820, 8.48e-15, 8.56e-15, 8.45e-15, nan ],
[ 7900, 103.3468, 4.8320, 92.9415, 5.3730, 47.4058, 10.5340, 7.6943, 64.9021, 8.30e-15, 9.71e-15, 9.28e-15, nan ],
[ 8000, 103.8981, 4.9288, 93.4148, 5.4820, 47.4734, 10.7870, 7.5299, 68.0079, 8.46e-15, 9.30e-15, 9.18e-15, nan ],
[ 8100, 105.2037, 4.9901, 93.6307, 5.6069, 48.7991, 10.7579, 7.5352, 69.6700, 8.61e-15, 8.64e-15, 8.84e-15, nan ],
[ 8200, 105.0613, 5.1210, 93.2253, 5.7712, 44.0891, 12.2030, 7.3522, 73.1781, 8.71e-15, 8.97e-15, 9.19e-15, nan ],
[ 8300, 105.4159, 5.2290, 93.4097, 5.9011, 44.0101, 12.5248, 7.2936, 75.5761, 1.17e-14, 9.67e-15, 9.57e-15, nan ],
[ 8400, 104.9563, 5.3792, 93.4906, 6.0389, 45.1844, 12.4950, 7.6251, 74.0421, 8.88e-15, 9.15e-15, 9.60e-15, nan ],
[ 8500, 106.2316, 5.4419, 93.9856, 6.1510, 46.3293, 12.4781, 7.5885, 76.1809, 8.81e-15, 8.94e-15, 9.20e-15, nan ],
[ 8600, 105.6940, 5.5990, 93.0888, 6.3572, 46.4503, 12.7401, 7.5041, 78.8610, 9.75e-15, 8.71e-15, 8.47e-15, nan ],
[ 8700, 104.6890, 5.7850, 94.1153, 6.4349, 46.6549, 12.9809, 7.5398, 80.3242, 1.13e-14, 1.08e-14, 1.11e-14, nan ],
[ 8800, 105.9910, 5.8460, 93.0504, 6.6590, 46.7251, 13.2611, 7.9902, 77.5480, 1.13e-14, 1.15e-14, 1.23e-14, nan ],
[ 8900, 106.0730, 5.9750, 93.7439, 6.7608, 47.3292, 13.3910, 8.1088, 78.1600, 1.01e-14, 1.07e-14, 1.08e-14, nan ],
[ 9000, 106.9842, 6.0580, 93.9407, 6.8991, 48.0369, 13.4919, 7.9592, 81.4290, 1.03e-14, 1.01e-14, 1.06e-14, nan ],
[ 10000, 107.9048, 7.4151, 94.7767, 8.4422, 47.6799, 16.7811, 8.3239, 96.1230, 1.04e-14, 1.00e-14, 9.42e-15, nan ],
[ 12000, 111.0268, 10.3772, 93.7083, 12.2950, 48.1146, 23.9458, 8.3559, 137.8839, 1.17e-14, 1.09e-14, 1.18e-14, nan ],
[ 14000, 110.4031, 14.2040, 94.2236, 16.6430, 47.8462, 32.7752, 8.4701, 185.1411, 1.12e-14, 1.11e-14, 1.25e-14, nan ],
[ 16000, 108.1984, 18.9300, 94.0359, 21.7810, 47.0870, 43.4980, 8.5963, 238.2650, 1.50e-14, 1.39e-14, 1.39e-14, nan ],
[ 18000, 109.7560, 23.6180, 95.2462, 27.2160, 47.1499, 54.9781, 8.7234, 297.1561, 1.40e-14, 1.48e-14, 1.46e-14, nan ],
[ 20000, 107.8074, 29.6848, 94.2075, 33.9701, 46.9961, 68.0959, 8.2953, 385.7899, 1.77e-14, 1.88e-14, 1.88e-14, nan ],
])
# ------------------------------------------------------------
# file: v1.6.1/cuda7.0-k40c/zpotrf.txt
# numactl --interleave=all ./testing_zpotrf -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zpotrf = array([
[ 10, nan, nan, 0.01, 0.00, nan ],
[ 20, nan, nan, 0.04, 0.00, nan ],
[ 30, nan, nan, 0.12, 0.00, nan ],
[ 40, nan, nan, 1.33, 0.00, nan ],
[ 50, nan, nan, 2.18, 0.00, nan ],
[ 60, nan, nan, 2.99, 0.00, nan ],
[ 70, nan, nan, 1.19, 0.00, nan ],
[ 80, nan, nan, 1.63, 0.00, nan ],
[ 90, nan, nan, 2.09, 0.00, nan ],
[ 100, nan, nan, 2.61, 0.00, nan ],
[ 200, nan, nan, 14.08, 0.00, nan ],
[ 300, nan, nan, 13.48, 0.00, nan ],
[ 400, nan, nan, 27.34, 0.00, nan ],
[ 500, nan, nan, 44.14, 0.00, nan ],
[ 600, nan, nan, 53.18, 0.01, nan ],
[ 700, nan, nan, 73.23, 0.01, nan ],
[ 800, nan, nan, 79.44, 0.01, nan ],
[ 900, nan, nan, 107.34, 0.01, nan ],
[ 1000, nan, nan, 130.32, 0.01, nan ],
[ 2000, nan, nan, 373.50, 0.03, nan ],
[ 3000, nan, nan, 553.62, 0.07, nan ],
[ 4000, nan, nan, 679.90, 0.13, nan ],
[ 5000, nan, nan, 761.87, 0.22, nan ],
[ 6000, nan, nan, 829.55, 0.35, nan ],
[ 7000, nan, nan, 879.78, 0.52, nan ],
[ 8000, nan, nan, 923.14, 0.74, nan ],
[ 9000, nan, nan, 953.24, 1.02, nan ],
[ 10000, nan, nan, 981.67, 1.36, nan ],
[ 12000, nan, nan, 1029.55, 2.24, nan ],
[ 14000, nan, nan, 1062.63, 3.44, nan ],
[ 16000, nan, nan, 1088.09, 5.02, nan ],
[ 18000, nan, nan, 1104.05, 7.04, nan ],
[ 20000, nan, nan, 1113.50, 9.58, nan ],
])
# numactl --interleave=all ./testing_zpotrf_gpu -N 100 -N 1000 --range 10:90:10 --range 100:900:100 --range 1000:9000:1000 --range 10000:20000:2000
zpotrf_gpu = array([
[ 10, nan, nan, 0.00, 0.00, nan ],
[ 20, nan, nan, 0.01, 0.00, nan ],
[ 30, nan, nan, 0.04, 0.00, nan ],
[ 40, nan, nan, 0.10, 0.00, nan ],
[ 50, nan, nan, 0.19, 0.00, nan ],
[ 60, nan, nan, 0.32, 0.00, nan ],
[ 70, nan, nan, 0.48, 0.00, nan ],
[ 80, nan, nan, 0.70, 0.00, nan ],
[ 90, nan, nan, 0.93, 0.00, nan ],
[ 100, nan, nan, 1.21, 0.00, nan ],
[ 200, nan, nan, 7.38, 0.00, nan ],
[ 300, nan, nan, 11.55, 0.00, nan ],
[ 400, nan, nan, 25.28, 0.00, nan ],
[ 500, nan, nan, 42.68, 0.00, nan ],
[ 600, nan, nan, 54.18, 0.01, nan ],
[ 700, nan, nan, 77.27, 0.01, nan ],
[ 800, nan, nan, 84.58, 0.01, nan ],
[ 900, nan, nan, 111.70, 0.01, nan ],
[ 1000, nan, nan, 143.75, 0.01, nan ],
[ 2000, nan, nan, 441.50, 0.02, nan ],
[ 3000, nan, nan, 644.39, 0.06, nan ],
[ 4000, nan, nan, 779.69, 0.11, nan ],
[ 5000, nan, nan, 862.11, 0.19, nan ],
[ 6000, nan, nan, 917.14, 0.31, nan ],
[ 7000, nan, nan, 970.62, 0.47, nan ],
[ 8000, nan, nan, 1008.54, 0.68, nan ],
[ 9000, nan, nan, 1029.56, 0.94, nan ],
[ 10000, nan, nan, 1052.90, 1.27, nan ],
[ 12000, nan, nan, 1095.40, 2.10, nan ],
[ 14000, nan, nan, 1117.90, 3.27, nan ],
[ 16000, nan, nan, 1139.32, 4.79, nan ],
[ 18000, nan, nan, 1148.96, 6.77, nan ],
[ 20000, nan, nan, 1150.85, 9.27, nan ],
])
| 68.372268 | 901 | 0.476203 | 55,704 | 309,658 | 2.643903 | 0.099993 | 0.077569 | 0.018944 | 0.007578 | 0.491105 | 0.391021 | 0.31625 | 0.279862 | 0.250272 | 0.247033 | 0 | 0.534298 | 0.312703 | 309,658 | 4,528 | 902 | 68.387367 | 0.157701 | 0.07745 | 0 | 0.166357 | 0 | 0 | 0.000168 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.000464 | 0 | 0.000464 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
8843abc5edc83ecf733ce466de299b472de36f16 | 266 | py | Python | Linkedin/linkedin-become-a-programmer-foundations/2.programming-foundations-beyond-the-fundamentals/Ch07/07_07/plant.py | mohammedelzanaty/myRoad2BeFullStack | eea3a5edb6c6a999136b04fdaea6ce0c81137a58 | [
"MIT"
] | 2 | 2021-04-21T12:05:01.000Z | 2022-01-19T09:58:38.000Z | Linkedin/linkedin-become-a-programmer-foundations/2.programming-foundations-beyond-the-fundamentals/Ch07/07_07/plant.py | mohammedelzanaty/myRoad2BeFullStack | eea3a5edb6c6a999136b04fdaea6ce0c81137a58 | [
"MIT"
] | 34 | 2019-12-26T11:21:42.000Z | 2022-02-27T19:55:10.000Z | Linkedin/linkedin-become-a-programmer-foundations/2.programming-foundations-beyond-the-fundamentals/Ch07/07_07/plant.py | mohammedelzanaty/myRoad2BeFullStack | eea3a5edb6c6a999136b04fdaea6ce0c81137a58 | [
"MIT"
] | 2 | 2021-08-15T07:59:36.000Z | 2022-01-16T06:17:32.000Z | def plant_recommendation(care):
if care == 'low':
print('aloe')
elif care == 'medium':
print('pothos')
elif care == 'high':
print('orchid')
plant_recommendation('low')
plant_recommendation('medium')
plant_recommendation('high')
| 20.461538 | 31 | 0.62406 | 28 | 266 | 5.785714 | 0.464286 | 0.469136 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.218045 | 266 | 12 | 32 | 22.166667 | 0.778846 | 0 | 0 | 0 | 0 | 0 | 0.157895 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1 | false | 0 | 0 | 0 | 0.1 | 0.3 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
885df7d78368976c3f6bc513f2490f893d6be51c | 637 | py | Python | core/user/urls.py | henrryyanez/test2 | 7f49391160ad6797afe83f9dae9346d320484b52 | [
"MIT"
] | null | null | null | core/user/urls.py | henrryyanez/test2 | 7f49391160ad6797afe83f9dae9346d320484b52 | [
"MIT"
] | null | null | null | core/user/urls.py | henrryyanez/test2 | 7f49391160ad6797afe83f9dae9346d320484b52 | [
"MIT"
] | 1 | 2021-02-25T00:57:35.000Z | 2021-02-25T00:57:35.000Z | from django.urls import path
from core.user.views import *
app_name = 'user'
urlpatterns = [
# user
path('list/', UserListView.as_view(), name='user_list'),
path('add/', UserCreateView.as_view(), name='user_create'),
path('update/<int:pk>/', UserUpdateView.as_view(), name='user_update'),
path('delete/<int:pk>/', UserDeleteView.as_view(), name='user_delete'),
path('change/group/<int:pk>/', UserChangeGroup.as_view(), name='user_change_group'),
path('profile/', UserProfileView.as_view(), name='user_profile'),
path('change/password/', UserChangePasswordView.as_view(), name='user_change_password'),
]
| 39.8125 | 92 | 0.693878 | 81 | 637 | 5.246914 | 0.382716 | 0.150588 | 0.164706 | 0.230588 | 0.094118 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.11303 | 637 | 15 | 93 | 42.466667 | 0.752212 | 0.006279 | 0 | 0 | 0 | 0 | 0.288431 | 0.034865 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.083333 | 0.166667 | 0 | 0.166667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
8860553b40393b3ac182e6a8e58f4d8d92c5ee2b | 859 | py | Python | user_import/migrations/0002_foreign_relationships.py | everyvoter/everyvoter | 65d9b8bdf9b5c64057135c279f6e03b6c207e0fa | [
"MIT"
] | 5 | 2019-07-01T17:50:44.000Z | 2022-02-20T02:44:42.000Z | user_import/migrations/0002_foreign_relationships.py | everyvoter/everyvoter | 65d9b8bdf9b5c64057135c279f6e03b6c207e0fa | [
"MIT"
] | 3 | 2020-06-05T21:44:33.000Z | 2021-06-10T21:39:26.000Z | user_import/migrations/0002_foreign_relationships.py | everyvoter/everyvoter | 65d9b8bdf9b5c64057135c279f6e03b6c207e0fa | [
"MIT"
] | 1 | 2021-12-09T06:32:40.000Z | 2021-12-09T06:32:40.000Z | # -*- coding: utf-8 -*-
# Generated by Django 1.11.12 on 2018-04-30 16:35
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('accounts', '0001_initial'),
('user_import', '0001_initial'),
]
operations = [
migrations.AddField(
model_name='importrecordstatus',
name='account',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AddField(
model_name='userimport',
name='uploader',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
]
| 29.62069 | 121 | 0.653085 | 97 | 859 | 5.618557 | 0.505155 | 0.058716 | 0.077064 | 0.121101 | 0.326606 | 0.326606 | 0.326606 | 0.326606 | 0.326606 | 0.326606 | 0 | 0.039275 | 0.229336 | 859 | 28 | 122 | 30.678571 | 0.783988 | 0.080326 | 0 | 0.285714 | 1 | 0 | 0.109276 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.47619 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
889c61be59c3bb3d37b0212051da6bcbefab0a47 | 152 | py | Python | sol/sol_array_count9.py | igamberdievhasan/codingbat-notebooks | b0a41f22b9064efc7f7f7da55e8c99fc21ce364d | [
"Apache-2.0"
] | null | null | null | sol/sol_array_count9.py | igamberdievhasan/codingbat-notebooks | b0a41f22b9064efc7f7f7da55e8c99fc21ce364d | [
"Apache-2.0"
] | 6 | 2020-03-02T20:59:43.000Z | 2020-03-18T01:20:30.000Z | sol/sol_array_count9.py | igamberdievhasan/codingbat-notebooks | b0a41f22b9064efc7f7f7da55e8c99fc21ce364d | [
"Apache-2.0"
] | 1 | 2020-03-13T02:48:04.000Z | 2020-03-13T02:48:04.000Z | def array_count9(nums):
count = 0
# Standard loop to look at each value
for num in nums:
if num == 9:
count = count + 1
return count
| 16.888889 | 39 | 0.618421 | 25 | 152 | 3.72 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.038095 | 0.309211 | 152 | 8 | 40 | 19 | 0.847619 | 0.230263 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
88af6330a4bff7bc5d7b08485e02b47c8ee99efb | 1,247 | py | Python | psdaq/psdaq/seq/finite.py | slactjohnson/lcls2 | 87fb7a7a9b5030ed7a2a472fecfca6575e233889 | [
"BSD-3-Clause-LBNL"
] | null | null | null | psdaq/psdaq/seq/finite.py | slactjohnson/lcls2 | 87fb7a7a9b5030ed7a2a472fecfca6575e233889 | [
"BSD-3-Clause-LBNL"
] | null | null | null | psdaq/psdaq/seq/finite.py | slactjohnson/lcls2 | 87fb7a7a9b5030ed7a2a472fecfca6575e233889 | [
"BSD-3-Clause-LBNL"
] | null | null | null | from psdaq.seq.seq import *
sync_marker = 6
instrset = []
# Insert global sync instruction (1Hz?)
instrset.append(FixedRateSync(marker=sync_marker,occ=1))
for i in range(4):
sh = i*4
b0 = len(instrset)
instrset.append(ControlRequest(0xf<<sh))
instrset.append(FixedRateSync(marker=0,occ=i+1))
instrset.append(Branch.conditional(line=b0, counter=0, value=1))
b0 = len(instrset)
instrset.append(ControlRequest(0xe<<sh))
instrset.append(FixedRateSync(marker=0,occ=i+1))
instrset.append(Branch.conditional(line=b0, counter=0, value=1))
b0 = len(instrset)
instrset.append(ControlRequest(0xc<<sh))
instrset.append(FixedRateSync(marker=0,occ=i+1))
instrset.append(Branch.conditional(line=b0, counter=0, value=3))
b0 = len(instrset)
instrset.append(ControlRequest(0x8<<sh))
instrset.append(FixedRateSync(marker=0,occ=i+1))
instrset.append(Branch.conditional(line=b0, counter=0, value=7))
b0 = len(instrset)
instrset.append(Branch.unconditional(line=b0))
descset = []
for j in range(16):
descset.append('%d x %fus'%(2**(1+(j%4)),1.08*(j/4)))
i=0
for instr in instrset:
print('Put instruction(%d): '%i),
print(instr.print_())
i += 1
title = 'BurstTest'
| 26.531915 | 68 | 0.682438 | 180 | 1,247 | 4.711111 | 0.283333 | 0.231132 | 0.159198 | 0.194575 | 0.65684 | 0.625 | 0.528302 | 0.528302 | 0.528302 | 0.528302 | 0 | 0.044465 | 0.152366 | 1,247 | 46 | 69 | 27.108696 | 0.757805 | 0.029671 | 0 | 0.333333 | 0 | 0 | 0.032312 | 0 | 0 | 0 | 0.009942 | 0 | 0 | 1 | 0 | false | 0 | 0.030303 | 0 | 0.030303 | 0.060606 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
31f75736197b26c98f93790209584a0a9ebc60c9 | 224 | py | Python | labelbox/data/serialization/coco/categories.py | Cyniikal/labelbox-python | 526fb8235c245a3c6161af57c354a47d68385bab | [
"Apache-2.0"
] | null | null | null | labelbox/data/serialization/coco/categories.py | Cyniikal/labelbox-python | 526fb8235c245a3c6161af57c354a47d68385bab | [
"Apache-2.0"
] | null | null | null | labelbox/data/serialization/coco/categories.py | Cyniikal/labelbox-python | 526fb8235c245a3c6161af57c354a47d68385bab | [
"Apache-2.0"
] | null | null | null | import sys
from pydantic import BaseModel
class Categories(BaseModel):
id: int
name: str
supercategory: str
isthing: int = 1
def hash_category_name(name: str) -> int:
return hash(name) + sys.maxsize
| 14.933333 | 41 | 0.6875 | 30 | 224 | 5.066667 | 0.633333 | 0.092105 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005814 | 0.232143 | 224 | 14 | 42 | 16 | 0.877907 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111111 | false | 0 | 0.222222 | 0.111111 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 2 |
ee0fcc0dee298a3aa80b9e3f1e962112300b1eb7 | 219 | py | Python | common/db/chat.py | whyh/FavourDemo | 1b19882fb2e79dee9c3332594bf45c91e7476eaa | [
"Unlicense"
] | 1 | 2020-09-14T12:10:22.000Z | 2020-09-14T12:10:22.000Z | common/db/chat.py | whyh/FavourDemo | 1b19882fb2e79dee9c3332594bf45c91e7476eaa | [
"Unlicense"
] | 4 | 2021-04-30T20:54:31.000Z | 2021-06-02T00:28:04.000Z | common/db/chat.py | whyh/FavourDemo | 1b19882fb2e79dee9c3332594bf45c91e7476eaa | [
"Unlicense"
] | null | null | null | from .orm import *
__all__ = ("Chat", "LockedChat")
class Chat(Kind):
invite = StringField()
occupied = BooleanField(index=True, default=False)
class LockedChat(Chat):
_kind = "chat"
_p_lock = True
| 15.642857 | 54 | 0.657534 | 25 | 219 | 5.48 | 0.72 | 0.116788 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.210046 | 219 | 13 | 55 | 16.846154 | 0.791908 | 0 | 0 | 0 | 0 | 0 | 0.082192 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.125 | 0 | 0.875 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
ee2a17e9330820b896d5e20240921bf8a52c5b82 | 7,827 | py | Python | models.py | ShahkarHassan/DotaDatabase | fbc3907238871cc4e80f918a8d02553fc15e9bc4 | [
"MIT"
] | null | null | null | models.py | ShahkarHassan/DotaDatabase | fbc3907238871cc4e80f918a8d02553fc15e9bc4 | [
"MIT"
] | null | null | null | models.py | ShahkarHassan/DotaDatabase | fbc3907238871cc4e80f918a8d02553fc15e9bc4 | [
"MIT"
] | null | null | null | # This is an auto-generated Django model module.
# You'll have to do the following manually to clean this up:
# * Rearrange models' order
# * Make sure each model has one field with primary_key=True
# * Make sure each ForeignKey has `on_delete` set to the desired behavior.
# * Remove `managed = False` lines if you wish to allow Django to create, modify, and delete the table
# Feel free to rename the models, but don't rename db_table values or field names.
from django.db import models
class AuthGroup(models.Model):
name = models.CharField(unique=True, max_length=80)
class Meta:
managed = False
db_table = 'auth_group'
class AuthGroupPermissions(models.Model):
group = models.ForeignKey(AuthGroup, models.DO_NOTHING)
permission = models.ForeignKey('AuthPermission', models.DO_NOTHING)
class Meta:
managed = False
db_table = 'auth_group_permissions'
unique_together = (('group', 'permission'),)
class AuthPermission(models.Model):
name = models.CharField(max_length=255)
content_type = models.ForeignKey('DjangoContentType', models.DO_NOTHING)
codename = models.CharField(max_length=100)
class Meta:
managed = False
db_table = 'auth_permission'
unique_together = (('content_type', 'codename'),)
class AuthUser(models.Model):
password = models.CharField(max_length=128)
last_login = models.DateTimeField(blank=True, null=True)
is_superuser = models.IntegerField()
username = models.CharField(unique=True, max_length=150)
first_name = models.CharField(max_length=30)
last_name = models.CharField(max_length=150)
email = models.CharField(max_length=254)
is_staff = models.IntegerField()
is_active = models.IntegerField()
date_joined = models.DateTimeField()
class Meta:
managed = False
db_table = 'auth_user'
class AuthUserGroups(models.Model):
user = models.ForeignKey(AuthUser, models.DO_NOTHING)
group = models.ForeignKey(AuthGroup, models.DO_NOTHING)
class Meta:
managed = False
db_table = 'auth_user_groups'
unique_together = (('user', 'group'),)
class AuthUserUserPermissions(models.Model):
user = models.ForeignKey(AuthUser, models.DO_NOTHING)
permission = models.ForeignKey(AuthPermission, models.DO_NOTHING)
class Meta:
managed = False
db_table = 'auth_user_user_permissions'
unique_together = (('user', 'permission'),)
class DjangoAdminLog(models.Model):
action_time = models.DateTimeField()
object_id = models.TextField(blank=True, null=True)
object_repr = models.CharField(max_length=200)
action_flag = models.PositiveSmallIntegerField()
change_message = models.TextField()
content_type = models.ForeignKey('DjangoContentType', models.DO_NOTHING, blank=True, null=True)
user = models.ForeignKey(AuthUser, models.DO_NOTHING)
class Meta:
managed = False
db_table = 'django_admin_log'
class DjangoContentType(models.Model):
app_label = models.CharField(max_length=100)
model = models.CharField(max_length=100)
class Meta:
managed = False
db_table = 'django_content_type'
unique_together = (('app_label', 'model'),)
class DjangoMigrations(models.Model):
app = models.CharField(max_length=255)
name = models.CharField(max_length=255)
applied = models.DateTimeField()
class Meta:
managed = False
db_table = 'django_migrations'
class DjangoSession(models.Model):
session_key = models.CharField(primary_key=True, max_length=40)
session_data = models.TextField()
expire_date = models.DateTimeField()
class Meta:
managed = False
db_table = 'django_session'
class DotaAdmin(models.Model):
admin = models.ForeignKey('DotaUser', models.DO_NOTHING, primary_key=True)
admin_registration_number = models.CharField(unique=True, max_length=20)
class Meta:
managed = False
db_table = 'dota_admin'
class DotaGamer(models.Model):
gamer = models.ForeignKey('DotaUser', models.DO_NOTHING, primary_key=True)
gamer_ign = models.CharField(max_length=20)
class Meta:
managed = False
db_table = 'dota_gamer'
class DotaGamerMatch(models.Model):
matchid = models.ForeignKey('DotaMatch', models.DO_NOTHING, db_column='matchid', primary_key=True)
match_gpm = models.IntegerField(db_column='match_GPM') # Field name made lowercase.
match_kills = models.IntegerField(db_column='match_Kills') # Field name made lowercase.
match_xpm = models.IntegerField(db_column='match_XPM') # Field name made lowercase.
match_death = models.IntegerField()
match_assist = models.IntegerField()
gamerid = models.ForeignKey(DotaGamer, models.DO_NOTHING, db_column='gamerid')
dota_gamer_matchcol = models.CharField(max_length=45, blank=True, null=True)
match_status = models.CharField(max_length=45)
class Meta:
managed = False
db_table = 'dota_gamer_match'
class DotaMatch(models.Model):
match_id = models.IntegerField(db_column='match_ID', primary_key=True) # Field name made lowercase.
match_type = models.CharField(db_column='match_Type', max_length=15) # Field name made lowercase.
match_duration = models.CharField(db_column='match_Duration', max_length=50) # Field name made lowercase.
class Meta:
managed = False
db_table = 'dota_match'
class DotaMmr(models.Model):
mmr = models.ForeignKey(DotaGamer, models.DO_NOTHING, db_column='mmr_Id', primary_key=True) # Field name made lowercase.
mmr_score = models.BigIntegerField()
mmr_medal = models.CharField(max_length=30)
class Meta:
managed = False
db_table = 'dota_mmr'
class DotaPremiumuser(models.Model):
premiumuser_registration_number = models.BigIntegerField(db_column='premiumuser_Registration_Number', primary_key=True) # Field name made lowercase.
premiumuser_registrationexpirydate = models.CharField(db_column='premiumuser_RegistrationExpiryDate', max_length=30) # Field name made lowercase.
premiumuser_gamer = models.ForeignKey(DotaGamer, models.DO_NOTHING, db_column='premiumuser_Gamer_ID') # Field name made lowercase.
class Meta:
managed = False
db_table = 'dota_premiumuser'
class DotaTournament(models.Model):
tournament_id = models.IntegerField(db_column='Tournament_ID', primary_key=True) # Field name made lowercase.
tournament_name = models.CharField(db_column='Tournament_name', max_length=100) # Field name made lowercase.
tournament_starting_timedate = models.DateTimeField(db_column='Tournament_starting_timedate') # Field name made lowercase.
tournament_end_timedate = models.DateTimeField(db_column='Tournament_end_timedate') # Field name made lowercase.
tournament_prize = models.CharField(db_column='Tournament_prize', max_length=100) # Field name made lowercase.
class Meta:
managed = False
db_table = 'dota_tournament'
class DotaTournamentMatch(models.Model):
matchid = models.ForeignKey(DotaMatch, models.DO_NOTHING, db_column='Matchid', primary_key=True) # Field name made lowercase.
tournamentid = models.ForeignKey(DotaTournament, models.DO_NOTHING, db_column='Tournamentid') # Field name made lowercase.
class Meta:
managed = False
db_table = 'dota_tournament_match'
class DotaUser(models.Model):
user_id = models.BigIntegerField(primary_key=True)
user_name = models.CharField(max_length=45)
user_email = models.CharField(max_length=45)
user_username = models.CharField(unique=True, max_length=30)
user_password = models.CharField(max_length=30)
class Meta:
managed = False
db_table = 'dota_user'
| 36.236111 | 153 | 0.723649 | 949 | 7,827 | 5.758693 | 0.184405 | 0.076853 | 0.055627 | 0.07301 | 0.591217 | 0.455078 | 0.390851 | 0.33742 | 0.243184 | 0.179506 | 0 | 0.010761 | 0.180784 | 7,827 | 215 | 154 | 36.404651 | 0.841547 | 0.11652 | 0 | 0.298013 | 1 | 0 | 0.102177 | 0.026851 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.013245 | 0.006623 | 0 | 0.715232 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
ee3bd69dd38640637d851f350d5e2aa21be4666e | 10,439 | py | Python | pysnmp/OPTIX-SONET-EQPTMGT-MIB-V2.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 11 | 2021-02-02T16:27:16.000Z | 2021-08-31T06:22:49.000Z | pysnmp/OPTIX-SONET-EQPTMGT-MIB-V2.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 75 | 2021-02-24T17:30:31.000Z | 2021-12-08T00:01:18.000Z | pysnmp/OPTIX-SONET-EQPTMGT-MIB-V2.py | agustinhenze/mibs.snmplabs.com | 1fc5c07860542b89212f4c8ab807057d9a9206c7 | [
"Apache-2.0"
] | 10 | 2019-04-30T05:51:36.000Z | 2022-02-16T03:33:41.000Z | #
# PySNMP MIB module OPTIX-SONET-EQPTMGT-MIB-V2 (http://snmplabs.com/pysmi)
# ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/OPTIX-SONET-EQPTMGT-MIB-V2
# Produced by pysmi-0.3.4 at Mon Apr 29 20:26:05 2019
# On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4
# Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15)
#
OctetString, Integer, ObjectIdentifier = mibBuilder.importSymbols("ASN1", "OctetString", "Integer", "ObjectIdentifier")
NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues")
ConstraintsIntersection, ValueSizeConstraint, SingleValueConstraint, ValueRangeConstraint, ConstraintsUnion = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsIntersection", "ValueSizeConstraint", "SingleValueConstraint", "ValueRangeConstraint", "ConstraintsUnion")
optixProvisionSonet, = mibBuilder.importSymbols("OPTIX-OID-MIB", "optixProvisionSonet")
NotificationGroup, ObjectGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ObjectGroup", "ModuleCompliance")
Integer32, Unsigned32, NotificationType, ModuleIdentity, Bits, Counter32, IpAddress, Counter64, ObjectIdentity, Gauge32, iso, MibScalar, MibTable, MibTableRow, MibTableColumn, TimeTicks, MibIdentifier = mibBuilder.importSymbols("SNMPv2-SMI", "Integer32", "Unsigned32", "NotificationType", "ModuleIdentity", "Bits", "Counter32", "IpAddress", "Counter64", "ObjectIdentity", "Gauge32", "iso", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "TimeTicks", "MibIdentifier")
TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString")
optixsonetEqptMgt = ModuleIdentity((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3))
if mibBuilder.loadTexts: optixsonetEqptMgt.setLastUpdated('200605232006Z')
if mibBuilder.loadTexts: optixsonetEqptMgt.setOrganization('Your organization')
class IntfType(TextualConvention, Integer32):
status = 'current'
subtypeSpec = Integer32.subtypeSpec + ConstraintsUnion(SingleValueConstraint(1, 10, 12, 13, 17, 65, 100, 254))
namedValues = NamedValues(("ds1-asyn-vt1", 1), ("ds3-asyn-sts1", 10), ("ec", 12), ("ds3-tmux-ds1", 13), ("ds3-srv-ds1", 17), ("uas", 65), ("mix", 100), ("invalid", 254))
optixsonetCardInfoTable = MibTable((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1), )
if mibBuilder.loadTexts: optixsonetCardInfoTable.setStatus('current')
optixsonetCardInfoEntry = MibTableRow((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1), ).setIndexNames((0, "OPTIX-SONET-EQPTMGT-MIB-V2", "cardIndexSlotId"), (0, "OPTIX-SONET-EQPTMGT-MIB-V2", "cardIndexSfpId"))
if mibBuilder.loadTexts: optixsonetCardInfoEntry.setStatus('current')
cardIndexSlotId = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 1), Gauge32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardIndexSlotId.setStatus('current')
cardIndexSfpId = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 2), Gauge32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardIndexSfpId.setStatus('current')
cardProvisionType = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 3), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardProvisionType.setStatus('current')
cardPhysicalType = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 4), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 64))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardPhysicalType.setStatus('current')
cardInterfaceType = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 5), IntfType()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardInterfaceType.setStatus('current')
cardBandwidth = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 6), Integer32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardBandwidth.setStatus('current')
cardSerialNum = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 7), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardSerialNum.setStatus('current')
cardCLEICode = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 8), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardCLEICode.setStatus('current')
cardPartNum = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 9), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 20))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardPartNum.setStatus('current')
cardDOM = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 10), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardDOM.setStatus('current')
cardPCBVersion = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 11), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardPCBVersion.setStatus('current')
cardSWVersion = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 12), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 64))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardSWVersion.setStatus('current')
cardFPGAVersion = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 13), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardFPGAVersion.setStatus('current')
cardEPLDVersion = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 14), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 8))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardEPLDVersion.setStatus('current')
cardBIOSVersion = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 15), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 64))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardBIOSVersion.setStatus('current')
cardMAC = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 16), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardMAC.setStatus('current')
cardPSTState = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 17), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 16))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardPSTState.setStatus('current')
cardSSTState = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 18), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 32))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardSSTState.setStatus('current')
cardTPSPriority = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 19), Gauge32()).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardTPSPriority.setStatus('current')
cardSwitchState = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 20), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5, 6, 254, 255))).clone(namedValues=NamedValues(("stateDNR", 1), ("stateWTR", 2), ("stateMAN", 3), ("stateAUTOSW", 4), ("stateFRCD", 5), ("stateLOCK", 6), ("stateINVALID", 254), ("stateIDLE", 255)))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardSwitchState.setStatus('current')
cardDescription = MibTableColumn((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 1, 1, 21), OctetString().subtype(subtypeSpec=ValueSizeConstraint(0, 64))).setMaxAccess("readonly")
if mibBuilder.loadTexts: cardDescription.setStatus('current')
optixsonetEqptMgtConformance = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 2))
optixsonetEqptMgtGroups = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 2, 1))
currentObjectGroup = ObjectGroup((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 2, 1, 1)).setObjects(("OPTIX-SONET-EQPTMGT-MIB-V2", "cardIndexSlotId"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardIndexSfpId"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardProvisionType"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardPhysicalType"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardInterfaceType"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardBandwidth"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardSerialNum"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardCLEICode"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardPartNum"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardDOM"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardPCBVersion"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardSWVersion"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardFPGAVersion"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardEPLDVersion"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardBIOSVersion"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardMAC"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardPSTState"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardSSTState"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardTPSPriority"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardSwitchState"), ("OPTIX-SONET-EQPTMGT-MIB-V2", "cardDescription"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
currentObjectGroup = currentObjectGroup.setStatus('current')
optixsonetEqptMgtCompliances = MibIdentifier((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 2, 2))
basicCompliance = ModuleCompliance((1, 3, 6, 1, 4, 1, 2011, 2, 25, 4, 20, 3, 2, 2, 1)).setObjects(("OPTIX-SONET-EQPTMGT-MIB-V2", "currentObjectGroup"))
if getattr(mibBuilder, 'version', (0, 0, 0)) > (4, 4, 0):
basicCompliance = basicCompliance.setStatus('current')
mibBuilder.exportSymbols("OPTIX-SONET-EQPTMGT-MIB-V2", cardTPSPriority=cardTPSPriority, cardIndexSlotId=cardIndexSlotId, cardDOM=cardDOM, cardEPLDVersion=cardEPLDVersion, cardSerialNum=cardSerialNum, cardInterfaceType=cardInterfaceType, cardDescription=cardDescription, optixsonetEqptMgtGroups=optixsonetEqptMgtGroups, cardSSTState=cardSSTState, basicCompliance=basicCompliance, optixsonetCardInfoTable=optixsonetCardInfoTable, cardBandwidth=cardBandwidth, cardSWVersion=cardSWVersion, cardMAC=cardMAC, cardPSTState=cardPSTState, PYSNMP_MODULE_ID=optixsonetEqptMgt, cardPhysicalType=cardPhysicalType, optixsonetEqptMgt=optixsonetEqptMgt, cardPartNum=cardPartNum, cardBIOSVersion=cardBIOSVersion, cardFPGAVersion=cardFPGAVersion, cardPCBVersion=cardPCBVersion, currentObjectGroup=currentObjectGroup, cardSwitchState=cardSwitchState, optixsonetCardInfoEntry=optixsonetCardInfoEntry, cardCLEICode=cardCLEICode, cardProvisionType=cardProvisionType, optixsonetEqptMgtConformance=optixsonetEqptMgtConformance, cardIndexSfpId=cardIndexSfpId, IntfType=IntfType, optixsonetEqptMgtCompliances=optixsonetEqptMgtCompliances)
| 130.4875 | 1,134 | 0.743654 | 1,257 | 10,439 | 6.174224 | 0.14638 | 0.007731 | 0.01121 | 0.014947 | 0.493107 | 0.371859 | 0.327535 | 0.319031 | 0.319031 | 0.319031 | 0 | 0.086838 | 0.086598 | 10,439 | 79 | 1,135 | 132.139241 | 0.727111 | 0.033145 | 0 | 0.028571 | 0 | 0 | 0.197739 | 0.068822 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.1 | 0 | 0.157143 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ee445de2dc05d287260b24063507ab9ebd298878 | 3,915 | py | Python | pysimplegui/test_RiKi_setting.py | konsan1101/py-etc | bcca13119b0d2453866988404fd1c4976f55d4d5 | [
"MIT"
] | null | null | null | pysimplegui/test_RiKi_setting.py | konsan1101/py-etc | bcca13119b0d2453866988404fd1c4976f55d4d5 | [
"MIT"
] | 2 | 2020-06-06T00:30:56.000Z | 2021-06-10T22:30:37.000Z | pysimplegui/test_RiKi_setting.py | konsan1101/py-etc | bcca13119b0d2453866988404fd1c4976f55d4d5 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#https://pysimplegui.readthedocs.io/en/latest/cookbook/
import PySimpleGUI as sg
#import PySimpleGUIWeb as sg
# Very basic window. Return values using auto numbered keys
layout = [
# ＡＰＩ選択 free, google, watson, azure, nict, special
[sg.Frame(layout=[
[sg.Radio('free', 'API', default=True), sg.Radio('google', 'API', key='google'), sg.Radio('watson', 'API'),
sg.Radio('azure', 'API'), sg.Radio('nict', 'API'), sg.Radio('special', 'API')]
], title=u'ＡＰＩ選択'),
],
# モード選択 hud, live, translator, speech, number, camera, assistant
[sg.Frame(layout=[
[sg.Radio('hud', 'MODE', default=True), sg.Radio('live', 'MODE'), sg.Radio('translator', 'MODE'),
sg.Radio('speech', 'MODE'), sg.Radio('number', 'MODE'), sg.Radio('camera', 'MODE'), sg.Radio('assistant', 'MODE')]
], title=u'モード選択'),
],
[
# speech
sg.Frame(layout=[
[sg.Checkbox('main_speech', default=True)],
[sg.Checkbox('controls', default=True)],
[sg.Checkbox('adintool', default=True)],
[sg.Checkbox('voice2wav', default=True)],
[sg.Checkbox('coreSTT', default=True)],
[sg.Checkbox('coreTTS', default=True)],
[sg.Checkbox('playvoice', default=True)],
[sg.Checkbox('julius', default=True)],
[sg.Checkbox('sttreader', default=True)],
[sg.Checkbox('trareader', default=True)],
[sg.Text('')],
[sg.Text('')],
[sg.Text('')],
], title=u'speech 起動条件'),
# vision
sg.Frame(layout=[
[sg.Checkbox('main_vision', default=True)],
[sg.Checkbox('controlv', default=True)],
[sg.Checkbox('overlay', default=True)],
[sg.Checkbox('camera1', default=True)],
[sg.Checkbox('camera2', default=True)],
[sg.Checkbox('txt2img', default=True)],
[sg.Checkbox('cvreader', default=True)],
[sg.Checkbox('cvdetect1', default=True)],
[sg.Checkbox('cvdetect2', default=True)],
[sg.Checkbox('cv2dnn_yolo', default=True)],
[sg.Checkbox('cv2dnn_ssd', default=True)],
[sg.Checkbox('vin2jpg', default=True)],
[sg.Checkbox('coreCV', default=True)],
], title=u'vision 起動条件'),
# desktop
sg.Frame(layout=[
[sg.Checkbox('main_desktop', default=True)],
[sg.Checkbox('controld', default=True)],
[sg.Checkbox('capture', default=True)],
[sg.Checkbox('cvreader', default=True)],
[sg.Checkbox('recorder', default=True)],
[sg.Checkbox('uploader', default=True)],
[sg.Text('')],
[sg.Text('')],
[sg.Text('')],
[sg.Text('')],
[sg.Text('')],
[sg.Text('')],
[sg.Text('')],
], title=u'desktop 起動条件'),
],
[sg.Button(u'ＯＫ'), sg.Button(u'キャンセル')]
]
window = sg.Window(u'RiKi 設定入力', layout)
#window.Element('google').Update(1)
event, values = window.Read()
window.Close()
print(event, values[0], values[1], values[2]) # the input data looks like a simple list when auto numbered
print(event, values)
| 43.5 | 138 | 0.452363 | 359 | 3,915 | 4.91922 | 0.29805 | 0.193092 | 0.220838 | 0.309173 | 0.208947 | 0.155719 | 0.109853 | 0.109853 | 0.080408 | 0.023783 | 0 | 0.005761 | 0.37931 | 3,915 | 89 | 139 | 43.988764 | 0.720988 | 0.10447 | 0 | 0.30303 | 0 | 0 | 0.122887 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.015152 | 0 | 0.015152 | 0.030303 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ee6aefb851bd986a81d9acf431a14e5cb1663282 | 296 | py | Python | meiduoshop/apps/verify/urls.py | 1572990942/meiduoshop | 64f4fe04fbcec8ceecf9fa0ce24afe41388f6926 | [
"MIT"
] | null | null | null | meiduoshop/apps/verify/urls.py | 1572990942/meiduoshop | 64f4fe04fbcec8ceecf9fa0ce24afe41388f6926 | [
"MIT"
] | null | null | null | meiduoshop/apps/verify/urls.py | 1572990942/meiduoshop | 64f4fe04fbcec8ceecf9fa0ce24afe41388f6926 | [
"MIT"
] | null | null | null | from django.urls import path
from apps.verify import views
urlpatterns = [
# this.image_code_url = this.host + "/image_codes/" + this.image_code_id + "/";
path('image_codes/<uuid:uuid>/', views.ImageCode.as_view()),
path('sms_codes/<mobile:mobile>/', views.SmsCodeView.as_view()),
]
| 32.888889 | 83 | 0.695946 | 41 | 296 | 4.804878 | 0.560976 | 0.091371 | 0.13198 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.131757 | 296 | 8 | 84 | 37 | 0.766537 | 0.260135 | 0 | 0 | 0 | 0 | 0.230415 | 0.230415 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
ee6ce268d719954674c27b9ada4b3eb16f3a08b6 | 2,161 | py | Python | forms/migrations/0003_answer_entry.py | City-of-Helsinki/mvj | 6f786047805a968317ecc37b38c2262ada2c3805 | [
"MIT"
] | 1 | 2021-01-12T08:14:10.000Z | 2021-01-12T08:14:10.000Z | forms/migrations/0003_answer_entry.py | City-of-Helsinki/mvj | 6f786047805a968317ecc37b38c2262ada2c3805 | [
"MIT"
] | 249 | 2017-04-18T14:00:13.000Z | 2022-03-30T12:18:03.000Z | forms/migrations/0003_answer_entry.py | City-of-Helsinki/mvj | 6f786047805a968317ecc37b38c2262ada2c3805 | [
"MIT"
] | 7 | 2017-04-18T08:43:54.000Z | 2021-07-28T07:29:30.000Z | # Generated by Django 2.2.13 on 2021-09-14 11:16
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
("forms", "0002_add_translations"),
]
operations = [
migrations.CreateModel(
name="Answer",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("ready", models.BooleanField(default=False)),
(
"form",
models.ForeignKey(
on_delete=django.db.models.deletion.PROTECT, to="forms.Form"
),
),
(
"user",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
to=settings.AUTH_USER_MODEL,
),
),
],
),
migrations.CreateModel(
name="Entry",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("value", models.TextField()),
(
"answer",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE, to="forms.Answer"
),
),
(
"field",
models.ForeignKey(
on_delete=django.db.models.deletion.PROTECT, to="forms.Field"
),
),
],
),
]
| 30.013889 | 86 | 0.386395 | 145 | 2,161 | 5.641379 | 0.406897 | 0.05868 | 0.085575 | 0.134474 | 0.474328 | 0.474328 | 0.474328 | 0.474328 | 0.474328 | 0.474328 | 0 | 0.01938 | 0.522443 | 2,161 | 71 | 87 | 30.43662 | 0.773256 | 0.021286 | 0 | 0.553846 | 1 | 0 | 0.050639 | 0.009938 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.046154 | 0 | 0.092308 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ee75eadf5929c5868016a3262d7dadbdd89d9350 | 1,812 | py | Python | test/apartment_test.py | doruirimescu/helsinki-apartment-finder | 6beb93c358675e9c048861ee94fc008b80da006d | [
"BSD-2-Clause"
] | null | null | null | test/apartment_test.py | doruirimescu/helsinki-apartment-finder | 6beb93c358675e9c048861ee94fc008b80da006d | [
"BSD-2-Clause"
] | null | null | null | test/apartment_test.py | doruirimescu/helsinki-apartment-finder | 6beb93c358675e9c048861ee94fc008b80da006d | [
"BSD-2-Clause"
] | null | null | null | from apartment import Apartment, Apartments, Price, Area, Year, Vastike, Floor, Rooms, Zone, K, Parameter
import pytest
import unittest
class TestParameter(unittest.TestCase):
def test_K(self):
self.assertEqual(K, 1000)
def test_Parameter_Constructor_DefaultValues(self):
p = Parameter(150*K)
self.assertEqual(p.value, 150000)
self.assertEqual(p.is_increasing_better, True)
self.assertEqual(p.unit, "")
self.assertEqual(p.name, "")
self.assertEqual(p.range, None)
self.assertEqual(p.weight, 1.0)
self.assertEqual(p.normalized_value, 0.0)
def test_Parameter_Throw_Errors(self):
with pytest.raises(ValueError):
p = Parameter(10, range=(100,10))
with pytest.raises(ValueError):
p = Parameter(0, range=(10,100))
def test_Parameter_Constructor_CustomValues(self):
p = Parameter(120*K, False, "euro", "price", (100*K, 400*K), 2.0)
self.assertEqual(p.value, 120*K)
self.assertEqual(p.is_increasing_better, False)
self.assertEqual(p.unit, "euro")
self.assertEqual(p.name, "price")
self.assertEqual(p.range, (100*K, 400*K))
def test_Price(self):
price = Price(value=150 *K, range = None)
self.assertEqual(price.is_increasing_better, False)
self.assertEqual(price.value, 150 *K)
self.assertEqual(price.normalized_value, 0.0)
self.assertEqual(price.calculate_weighted_value(), 0.0)
price.normalize(150*K, 350*K)
self.assertEqual(price.normalized_value, 1.0)
self.assertEqual(price.calculate_weighted_value(), 1.0)
price.normalize(100*K, 200*K)
self.assertEqual(price.normalized_value, 0.5)
self.assertEqual(price.calculate_weighted_value(), 0.5)
| 36.979592 | 105 | 0.661148 | 235 | 1,812 | 4.982979 | 0.255319 | 0.269001 | 0.163962 | 0.0538 | 0.374039 | 0.374039 | 0.17421 | 0 | 0 | 0 | 0 | 0.056101 | 0.213024 | 1,812 | 48 | 106 | 37.75 | 0.765077 | 0 | 0 | 0.051282 | 0 | 0 | 0.009934 | 0 | 0 | 0 | 0 | 0 | 0.538462 | 1 | 0.128205 | false | 0 | 0.076923 | 0 | 0.230769 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
ee769c5383428aab54a73116140cd21e2d89a194 | 662 | py | Python | sable/view.py | HH-MWB/sable | 78ec3d1892af83992cdd6a719e16155706b0ea92 | [
"MIT"
] | null | null | null | sable/view.py | HH-MWB/sable | 78ec3d1892af83992cdd6a719e16155706b0ea92 | [
"MIT"
] | null | null | null | sable/view.py | HH-MWB/sable | 78ec3d1892af83992cdd6a719e16155706b0ea92 | [
"MIT"
] | null | null | null | """Sable Viewer"""
from typing import Iterable
from typer import colors, echo, style
from sable.data import TestCase
from sable.exec import test
TAG_PASS: str = style("Passed", fg=colors.WHITE, bg=colors.GREEN)
TAG_FAIL: str = style("Failed", fg=colors.WHITE, bg=colors.RED)
def view(cases: Iterable[TestCase]) -> None:
"""View the results of given test cases.
Parameters
----------
cases : Iterable[TestCase]
Test cases to be displayed
"""
for case in cases:
if test(case):
echo(f"{case.identifier:.<73}{TAG_PASS}")
else:
echo(f"{case.identifier:.<73}{TAG_FAIL}\n\t{case.message}")
| 24.518519 | 71 | 0.638973 | 92 | 662 | 4.554348 | 0.521739 | 0.042959 | 0.062053 | 0.071599 | 0.214797 | 0.114558 | 0 | 0 | 0 | 0 | 0 | 0.007707 | 0.216012 | 662 | 26 | 72 | 25.461538 | 0.799615 | 0.197885 | 0 | 0 | 0 | 0 | 0.188377 | 0.164329 | 0 | 0 | 0 | 0 | 0 | 1 | 0.083333 | false | 0.166667 | 0.333333 | 0 | 0.416667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 2 |
ee8176bf38cfb9197d92f6d6f39ea3c0d6ac7e37 | 505 | py | Python | fiubar/forms.py | maru/fiubar | be12547ae3f4560765c86ce5c49988931b09b19a | [
"MIT"
] | 5 | 2016-07-27T16:01:41.000Z | 2020-03-10T21:11:31.000Z | fiubar/forms.py | maru/fiubar | be12547ae3f4560765c86ce5c49988931b09b19a | [
"MIT"
] | 14 | 2015-07-22T16:41:58.000Z | 2019-03-28T20:45:17.000Z | fiubar/forms.py | maru/fiubar | be12547ae3f4560765c86ce5c49988931b09b19a | [
"MIT"
] | 3 | 2015-07-22T15:14:44.000Z | 2018-04-16T09:49:35.000Z | # -*- coding: utf-8 -*-
from captcha.fields import ReCaptchaField
from django import forms
from django.conf import settings
class SignupForm(forms.Form):
"""
Signup form with recaptcha field.
"""
field_order = ['username', 'email', 'password1', ]
if hasattr(settings, 'RECAPTCHA_PUBLIC_KEY'):
captcha = ReCaptchaField()
field_order.append('captcha')
def signup(self, request, user):
""" Required, or else it throws deprecation warnings """
pass
| 25.25 | 64 | 0.657426 | 56 | 505 | 5.857143 | 0.714286 | 0.060976 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005102 | 0.223762 | 505 | 19 | 65 | 26.578947 | 0.831633 | 0.209901 | 0 | 0 | 0 | 0 | 0.129973 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1 | false | 0.2 | 0.3 | 0 | 0.6 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 2 |
ee825f6ed994b458ea0b729d178c51519e6e0f2f | 633 | py | Python | seed_scraper/items.py | uoshvis/seed-scraper | e944ea885e2a001ef9822b62850dd07e01284214 | [
"MIT"
] | null | null | null | seed_scraper/items.py | uoshvis/seed-scraper | e944ea885e2a001ef9822b62850dd07e01284214 | [
"MIT"
] | null | null | null | seed_scraper/items.py | uoshvis/seed-scraper | e944ea885e2a001ef9822b62850dd07e01284214 | [
"MIT"
] | null | null | null | # Define here the models for your scraped items
#
# See documentation in:
# https://docs.scrapy.org/en/latest/topics/items.html
import scrapy
class EnforcementItem(scrapy.Item):
legal_case_name = scrapy.Field()
legal_case_detail_url = scrapy.Field()
defendant_name = scrapy.Field()
defendant_type = scrapy.Field()
first_doc_date = scrapy.Field()
first_resolution_date = scrapy.Field()
allegation_type = scrapy.Field()
initial_filling_format = scrapy.Field()
case_number = scrapy.Field()
federal_district_court = scrapy.Field()
# sic_code = scrapy.Field()
# cusip = scrapy.Field()
| 26.375 | 53 | 0.71564 | 80 | 633 | 5.4375 | 0.575 | 0.303448 | 0.068966 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.175355 | 633 | 23 | 54 | 27.521739 | 0.833333 | 0.265403 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.083333 | 0 | 1 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
ee85b6c767b2b5051baa3b53dc3067ba025d3e2e | 1,032 | py | Python | excel/book.py | cicicici/hopper | d0ed0307c50ab56631960b4488c43a2d098d6bb4 | [
"MIT"
] | null | null | null | excel/book.py | cicicici/hopper | d0ed0307c50ab56631960b4488c43a2d098d6bb4 | [
"MIT"
] | null | null | null | excel/book.py | cicicici/hopper | d0ed0307c50ab56631960b4488c43a2d098d6bb4 | [
"MIT"
] | null | null | null | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import sys
import datetime
from copy import copy, deepcopy
from openpyxl import load_workbook
from ..util.opt import Opt
from ..util.fs import file_exist
from ..debug import log, dump
from .sheet import load_sheet, clear_sheet_cache
def load_book(filename, title_sheet_map, title_field_map):
if not file_exist(filename):
return None
wb = load_workbook(filename)
sheets = Opt()
names = []
for sheetname in wb.sheetnames:
if sheetname in title_sheet_map:
name = title_sheet_map[sheetname]
else:
name = sheetname
sheets[name] = load_sheet(wb, sheetname, title_field_map)
names.append({sheetname: name})
log.trace(log.DC.STD, "Book: {}, sheets {}".format(filename, names))
return Opt(wb=wb, sheets=sheets)
def clear_book_cache(book):
for name, sheet in book.sheets.items():
clear_sheet_cache(sheet)
| 22.933333 | 72 | 0.705426 | 142 | 1,032 | 4.866197 | 0.359155 | 0.043415 | 0.069465 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.213178 | 1,032 | 44 | 73 | 23.454545 | 0.850985 | 0 | 0 | 0 | 0 | 0 | 0.018429 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.066667 | false | 0 | 0.4 | 0 | 0.533333 | 0.033333 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
c9953f6b6fe4d5aada78767e203a4d9be3ea3728 | 110 | py | Python | Problem Solving using Python Lab/11.sumOfN.py | narayan954/niet_codetantra | 6f4af58e9824b1f79b0c8dc391456fb4857558f0 | [
"MIT"
] | 2 | 2022-01-30T07:22:01.000Z | 2022-01-30T16:00:58.000Z | Problem Solving using Python Lab/11.sumOfN.py | narayan954/niet-codetantra | 1316b1c5a61c16d5cbe83b236b77d7a59e82c9c7 | [
"MIT"
] | null | null | null | Problem Solving using Python Lab/11.sumOfN.py | narayan954/niet-codetantra | 1316b1c5a61c16d5cbe83b236b77d7a59e82c9c7 | [
"MIT"
] | 1 | 2021-11-29T15:32:38.000Z | 2021-11-29T15:32:38.000Z | a=int(input('Enter number of terms '))
f=1
s=0
for i in range(1,a+1):
f=f*i
s+=f
print('Sum of series =',s)
| 13.75 | 38 | 0.609091 | 28 | 110 | 2.392857 | 0.642857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.043956 | 0.172727 | 110 | 7 | 39 | 15.714286 | 0.692308 | 0 | 0 | 0 | 0 | 0 | 0.336364 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.142857 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c996ff6ba045ea0bbb81604fe33182db4416b3fb | 168 | py | Python | moai/monads/human/pose/__init__.py | ai-in-motion/moai | e38cac046c059d2e2331ef4883bbabc5a500a5cf | [
"Apache-2.0"
] | 10 | 2021-04-02T11:21:33.000Z | 2022-01-18T18:32:32.000Z | moai/monads/human/pose/__init__.py | ai-in-motion/moai | e38cac046c059d2e2331ef4883bbabc5a500a5cf | [
"Apache-2.0"
] | 1 | 2022-03-22T20:10:55.000Z | 2022-03-24T13:11:02.000Z | moai/monads/human/pose/__init__.py | ai-in-motion/moai | e38cac046c059d2e2331ef4883bbabc5a500a5cf | [
"Apache-2.0"
] | 3 | 2021-05-16T20:47:40.000Z | 2021-12-01T21:15:36.000Z | from moai.monads.human.pose.openpose import (
Split as OpenposeSplit,
JointMap as OpenposeJointMap
)
__all__ = [
'OpenposeSplit',
'OpenposeJointMap',
] | 18.666667 | 45 | 0.708333 | 16 | 168 | 7.1875 | 0.8125 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.196429 | 168 | 9 | 46 | 18.666667 | 0.851852 | 0 | 0 | 0 | 0 | 0 | 0.171598 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.125 | 0 | 0.125 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c9982086806173b371f01b49ff966ab5bef44330 | 1,702 | py | Python | code/speakkey_v01.py | whoisguardsite/test | 62313665a9b673b5d5e5b1dbe9761c654751970c | [
"MIT"
] | 19 | 2015-01-12T22:30:53.000Z | 2020-07-29T19:10:20.000Z | code/speakkey_v01.py | whoisguardsite/test | 62313665a9b673b5d5e5b1dbe9761c654751970c | [
"MIT"
] | 8 | 2015-02-17T19:21:18.000Z | 2021-08-21T14:48:25.000Z | code/speakkey_v01.py | whoisguardsite/test | 62313665a9b673b5d5e5b1dbe9761c654751970c | [
"MIT"
] | 17 | 2015-02-17T14:55:33.000Z | 2022-02-16T06:08:14.000Z | #! /usr/bin/python3.5
# Copyright 2015 Chris Ballinger - CC0 1.0 Universal
import sys
# Octal / Emoji / Syllable Mapping
# `0 | 🌞 | ohm`
# `1 | 🌵 | ma`
# `2 | 🌲 | ni`
# `3 | 🌼 | pad`
# `4 | 🐅 | me`
# `5 | 🕊 | hum`
# `6 | 🐉 | free`
# `7 | 🌅 | dom`
# Input octal UTF-8 string (e.g. '012345670123456701234567') and receive
# an emoji representation.
def eyes_v01(o_string: str) -> str:
o_string = o_string.replace('0', '🌞')
o_string = o_string.replace('1', '🌵')
o_string = o_string.replace('2', '🌲')
o_string = o_string.replace('3', '🌼')
o_string = o_string.replace('4', '🐅')
o_string = o_string.replace('5', '🕊')
o_string = o_string.replace('6', '🐉')
o_string = o_string.replace('7', '🌅')
return o_string
# Input octal UTF-8 string (e.g. '012345670123456701234567') and receive
# an pronounceable syllable representation.
def ears_v01(o_string: str) -> str:
o_string = o_string.replace('0', 'ohm')
o_string = o_string.replace('1', 'ma')
o_string = o_string.replace('2', 'ni')
o_string = o_string.replace('3', 'pad')
o_string = o_string.replace('4', 'me')
o_string = o_string.replace('5', 'hum')
o_string = o_string.replace('6', 'free')
o_string = o_string.replace('7', 'dom')
return o_string
if __name__ == '__main__':
if len(sys.argv) < 2:
print('speakkey - v0.1\n\nUsage: speakkey.py "01234567 01234567 01234567" (octal only)')
else:
input_string = sys.argv[1]
print('Eyes v0.1: ' + input_string)
eyes = eyes_v01(input_string)
print(' : ' + eyes)
print('Ears v0.1: ' + input_string)
ears = ears_v01(input_string)
print(' : ' + ears)
| 29.859649 | 96 | 0.592244 | 254 | 1,702 | 3.822835 | 0.287402 | 0.259526 | 0.131823 | 0.23069 | 0.514933 | 0.514933 | 0.197734 | 0.197734 | 0.197734 | 0.197734 | 0 | 0.093679 | 0.228555 | 1,702 | 56 | 97 | 30.392857 | 0.633663 | 0.248531 | 0 | 0.0625 | 0 | 0.03125 | 0.140032 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.0625 | false | 0 | 0.03125 | 0 | 0.15625 | 0.15625 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c9a4127125271bb6a2a4d8bbde2525a8c1eeaff6 | 5,855 | py | Python | cdpy/cdp/media.py | MichaelBrunn3r/cdpy | d6130b01920149b5ab4a74462dfdba872586abd0 | [
"MIT"
] | 1 | 2021-07-14T22:23:46.000Z | 2021-07-14T22:23:46.000Z | cdpy/cdp/media.py | MichaelBrunn3r/cdpy | d6130b01920149b5ab4a74462dfdba872586abd0 | [
"MIT"
] | null | null | null | cdpy/cdp/media.py | MichaelBrunn3r/cdpy | d6130b01920149b5ab4a74462dfdba872586abd0 | [
"MIT"
] | null | null | null | from __future__ import annotations
import dataclasses
class PlayerId(str):
"""Players will get an ID that is unique within the agent context."""
def __repr__(self):
return f"PlayerId({super().__repr__()})"
class Timestamp(float):
""""""
def __repr__(self):
return f"Timestamp({super().__repr__()})"
@dataclasses.dataclass
class PlayerMessage:
"""Have one type per entry in MediaLogRecord::Type
Corresponds to kMessage
Attributes
----------
level: str
Keep in sync with MediaLogMessageLevel
We are currently keeping the message level 'error' separate from the
PlayerError type because right now they represent different things,
this one being a DVLOG(ERROR) style log message that gets printed
based on what log level is selected in the UI, and the other is a
representation of a media::PipelineStatus object. Soon however we're
going to be moving away from using PipelineStatus for errors and
introducing a new error type which should hopefully let us integrate
the error log level into the PlayerError type.
message: str
"""
level: str
message: str
@classmethod
def from_json(cls, json: dict) -> PlayerMessage:
return cls(json["level"], json["message"])
def to_json(self) -> dict:
return {"level": self.level, "message": self.message}
@dataclasses.dataclass
class PlayerProperty:
"""Corresponds to kMediaPropertyChange
Attributes
----------
name: str
value: str
"""
name: str
value: str
@classmethod
def from_json(cls, json: dict) -> PlayerProperty:
return cls(json["name"], json["value"])
def to_json(self) -> dict:
return {"name": self.name, "value": self.value}
@dataclasses.dataclass
class PlayerEvent:
"""Corresponds to kMediaEventTriggered
Attributes
----------
timestamp: Timestamp
value: str
"""
timestamp: Timestamp
value: str
@classmethod
def from_json(cls, json: dict) -> PlayerEvent:
return cls(Timestamp(json["timestamp"]), json["value"])
def to_json(self) -> dict:
return {"timestamp": float(self.timestamp), "value": self.value}
@dataclasses.dataclass
class PlayerError:
"""Corresponds to kMediaError
Attributes
----------
type: str
errorCode: str
When this switches to using media::Status instead of PipelineStatus
we can remove "errorCode" and replace it with the fields from
a Status instance. This also seems like a duplicate of the error
level enum - there is a todo bug to have that level removed and
use this instead. (crbug.com/1068454)
"""
type: str
errorCode: str
@classmethod
def from_json(cls, json: dict) -> PlayerError:
return cls(json["type"], json["errorCode"])
def to_json(self) -> dict:
return {"type": self.type, "errorCode": self.errorCode}
def enable() -> dict:
"""Enables the Media domain"""
return {"method": "Media.enable", "params": {}}
def disable() -> dict:
"""Disables the Media domain."""
return {"method": "Media.disable", "params": {}}
@dataclasses.dataclass
class PlayerPropertiesChanged:
"""This can be called multiple times, and can be used to set / override /
remove player properties. A null propValue indicates removal.
Attributes
----------
playerId: PlayerId
properties: list[PlayerProperty]
"""
playerId: PlayerId
properties: list[PlayerProperty]
@classmethod
def from_json(cls, json: dict) -> PlayerPropertiesChanged:
return cls(
PlayerId(json["playerId"]),
[PlayerProperty.from_json(p) for p in json["properties"]],
)
@dataclasses.dataclass
class PlayerEventsAdded:
"""Send events as a list, allowing them to be batched on the browser for less
congestion. If batched, events must ALWAYS be in chronological order.
Attributes
----------
playerId: PlayerId
events: list[PlayerEvent]
"""
playerId: PlayerId
events: list[PlayerEvent]
@classmethod
def from_json(cls, json: dict) -> PlayerEventsAdded:
return cls(
PlayerId(json["playerId"]),
[PlayerEvent.from_json(e) for e in json["events"]],
)
@dataclasses.dataclass
class PlayerMessagesLogged:
"""Send a list of any messages that need to be delivered.
Attributes
----------
playerId: PlayerId
messages: list[PlayerMessage]
"""
playerId: PlayerId
messages: list[PlayerMessage]
@classmethod
def from_json(cls, json: dict) -> PlayerMessagesLogged:
return cls(
PlayerId(json["playerId"]),
[PlayerMessage.from_json(m) for m in json["messages"]],
)
@dataclasses.dataclass
class PlayerErrorsRaised:
"""Send a list of any errors that need to be delivered.
Attributes
----------
playerId: PlayerId
errors: list[PlayerError]
"""
playerId: PlayerId
errors: list[PlayerError]
@classmethod
def from_json(cls, json: dict) -> PlayerErrorsRaised:
return cls(
PlayerId(json["playerId"]),
[PlayerError.from_json(e) for e in json["errors"]],
)
@dataclasses.dataclass
class PlayersCreated:
"""Called whenever a player is created, or when a new agent joins and recieves
a list of active players. If an agent is restored, it will recieve the full
list of player ids and all events again.
Attributes
----------
players: list[PlayerId]
"""
players: list[PlayerId]
@classmethod
def from_json(cls, json: dict) -> PlayersCreated:
return cls([PlayerId(p) for p in json["players"]])
| 25.34632 | 82 | 0.637062 | 667 | 5,855 | 5.536732 | 0.289355 | 0.028161 | 0.060926 | 0.053615 | 0.32196 | 0.189819 | 0.139453 | 0.084484 | 0.022204 | 0 | 0 | 0.001605 | 0.254996 | 5,855 | 230 | 83 | 25.456522 | 0.845025 | 0.402391 | 0 | 0.404255 | 0 | 0 | 0.086723 | 0.019237 | 0 | 0 | 0 | 0.004348 | 0 | 1 | 0.180851 | false | 0 | 0.021277 | 0.159574 | 0.680851 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 2 |
c9b21c5832143f8c59f97ba2e10ff36b25060d31 | 487 | py | Python | base/admin.py | sakthicse/agricultural_innovations | a7f8aaf617c09e73607e805b22b9b82ac05e3856 | [
"BSD-3-Clause"
] | null | null | null | base/admin.py | sakthicse/agricultural_innovations | a7f8aaf617c09e73607e805b22b9b82ac05e3856 | [
"BSD-3-Clause"
] | null | null | null | base/admin.py | sakthicse/agricultural_innovations | a7f8aaf617c09e73607e805b22b9b82ac05e3856 | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
from django.contrib import admin
from .models import Projects,SiteInfo
# Register your models here.
class ProjectsAdmin(admin.ModelAdmin):
list_display = ['name']
class SiteInfoAdmin(admin.ModelAdmin):
list_display = ['site_name']
# def has_add_permission(self, request):
# return False
admin.site.register(Projects,ProjectsAdmin)
admin.site.register(SiteInfo,SiteInfoAdmin) | 28.647059 | 56 | 0.749487 | 57 | 487 | 6.210526 | 0.596491 | 0.101695 | 0.107345 | 0.146893 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.002415 | 0.149897 | 487 | 17 | 57 | 28.647059 | 0.852657 | 0.213552 | 0 | 0 | 0 | 0 | 0.034301 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.777778 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
c9cf522309e05ec9c78538a39f58158eec54b803 | 251 | py | Python | taesko/web-server/setup.py | taesko/training-projects | 638649b0b5987ba971ae5ce1f171642de3cde739 | [
"Apache-2.0"
] | null | null | null | taesko/web-server/setup.py | taesko/training-projects | 638649b0b5987ba971ae5ce1f171642de3cde739 | [
"Apache-2.0"
] | null | null | null | taesko/web-server/setup.py | taesko/training-projects | 638649b0b5987ba971ae5ce1f171642de3cde739 | [
"Apache-2.0"
] | null | null | null | from setuptools import setup, find_packages
setup(
name='ws',
entry_points={
'console_scripts': [
'pyws = ws.server:main'
]
},
packages=find_packages(exclude=('conf.d',)),
tests_require=['openpyxl']
) | 17.928571 | 48 | 0.581673 | 26 | 251 | 5.423077 | 0.807692 | 0.170213 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.270916 | 251 | 14 | 49 | 17.928571 | 0.770492 | 0 | 0 | 0 | 0 | 0 | 0.206349 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.090909 | 0 | 0.090909 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c9d2d463f0ee01a054ea063e7a248ef3fb15153f | 1,330 | py | Python | config/settings/local.py | agnihotri7/demo-api | ffccd7e7a21b99cb8282045b4c3343ff5888c527 | [
"RSA-MD"
] | null | null | null | config/settings/local.py | agnihotri7/demo-api | ffccd7e7a21b99cb8282045b4c3343ff5888c527 | [
"RSA-MD"
] | null | null | null | config/settings/local.py | agnihotri7/demo-api | ffccd7e7a21b99cb8282045b4c3343ff5888c527 | [
"RSA-MD"
] | null | null | null | import os
from config.settings.dev import *
DEBUG = True
ENABLE_API_ROOT = True
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': BASE_DIR / 'tmp/db/sqlite3_db',
}
}
REST_FRAMEWORK = {
'DEFAULT_RENDERER_CLASSES': (
'rest_framework.renderers.JSONRenderer',
'rest_framework.renderers.BrowsableAPIRenderer',
),
'DEFAULT_PARSER_CLASSES': (
'rest_framework.parsers.JSONParser',
),
'DEFAULT_AUTHENTICATION_CLASSES': (
'rest_framework.authentication.BasicAuthentication',
'rest_framework.authentication.SessionAuthentication',
'rest_framework.authentication.TokenAuthentication',
),
'DEFAULT_FILTER_BACKENDS': (
'django_filters.rest_framework.DjangoFilterBackend',
'rest_framework.filters.SearchFilter',
'rest_framework.filters.OrderingFilter',
),
'DEFAULT_VERSIONING_CLASS': 'rest_framework.versioning.NamespaceVersioning',
'DEFAULT_VERSION': 'v1',
'ALLOWED_VERSIONS': ('v1',),
'DEFAULT_PAGINATION_CLASS': 'rest_framework.pagination.PageNumberPagination',
'PAGE_SIZE': 10,
'PAGINATE_BY_PARAM': 'page_size', # Allow client to override, using `?page_size=xxx`.
'MAX_PAGINATE_BY': 100 # Maximum limit allowed when using `?page_size=xxx`.
}
| 31.666667 | 91 | 0.690226 | 126 | 1,330 | 6.97619 | 0.531746 | 0.177474 | 0.068259 | 0.036405 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.008349 | 0.189474 | 1,330 | 41 | 92 | 32.439024 | 0.80705 | 0.075188 | 0 | 0.111111 | 0 | 0 | 0.625917 | 0.528932 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.055556 | 0 | 0.055556 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
c9e2520cd71660ad8f63941326fd72c4411f776e | 5,197 | py | Python | src/tests/authentication/testAuthentication.py | c3loc/squirrel | 8074dbc74a9a15fc665fcaef617b401759ea7e0c | [
"MIT"
] | 1 | 2019-12-13T13:22:06.000Z | 2019-12-13T13:22:06.000Z | src/tests/authentication/testAuthentication.py | c3loc/squirrel | 8074dbc74a9a15fc665fcaef617b401759ea7e0c | [
"MIT"
] | 23 | 2019-12-05T23:18:46.000Z | 2020-04-13T14:08:22.000Z | src/tests/authentication/testAuthentication.py | c3loc/squirrel | 8074dbc74a9a15fc665fcaef617b401759ea7e0c | [
"MIT"
] | 2 | 2019-12-06T08:14:31.000Z | 2020-06-18T20:30:26.000Z | from django.contrib.auth import views as auth_views
from django.contrib.auth.forms import PasswordChangeForm, PasswordResetForm
from django.contrib.auth.models import User
from django.core import mail
from django.test import TestCase
from django.urls import resolve, reverse
class PasswordResetTests(TestCase):
def setUp(self):
url = reverse("password_reset")
self.response = self.client.get(url)
def test_status_code(self):
self.assertEquals(self.response.status_code, 200)
def test_view_function(self):
view = resolve("/reset")
self.assertEquals(view.func.view_class, auth_views.PasswordResetView)
def test_csrf(self):
self.assertContains(self.response, "csrfmiddlewaretoken")
def test_contains_form(self):
form = self.response.context.get("form")
self.assertIsInstance(form, PasswordResetForm)
def test_form_inputs(self):
"""The view must contain two inputs: csrf and email"""
self.assertContains(self.response, "<input", 3)
self.assertContains(self.response, 'type="email"', 1)
class SuccessfulPasswordResetTests(TestCase):
def setUp(self):
email = "test@example.com"
User.objects.create_user(
username="test", email=email, password="ufgdlneginetriunae"
)
url = reverse("password_reset")
self.response = self.client.post(url, {"email": email})
def test_redirection(self):
"""A valid form submission should redirect the user to `password_reset_done` view"""
url = reverse("password_reset_done")
self.assertRedirects(self.response, url)
def test_send_password_reset_email(self):
self.assertEqual(1, len(mail.outbox))
class InvalidPasswordResetTests(TestCase):
def setUp(self):
url = reverse("password_reset")
self.response = self.client.post(url, {"email": "donotexist@email.com"})
def test_redirection(self):
"""Even invalid emails in the database should redirect the user to `password_reset_done` view"""
url = reverse("password_reset_done")
self.assertRedirects(self.response, url)
def test_no_reset_email_sent(self):
self.assertEqual(0, len(mail.outbox))
class PasswordResetDoneTests(TestCase):
def setUp(self):
url = reverse("password_reset_done")
self.response = self.client.get(url)
def test_status_code(self):
self.assertEquals(self.response.status_code, 200)
def test_view_function(self):
view = resolve("/reset/done")
self.assertEquals(view.func.view_class, auth_views.PasswordResetDoneView)
class PasswordChangeTests(TestCase):
def setUp(self):
self.user = User.objects.create_user(
username="any_user", password="uiafge489w9834sronuisw"
)
self.client.login(username="any_user", password="uiafge489w9834sronuisw")
url = reverse("password_change")
self.response = self.client.get(url)
def test_status_code(self):
self.assertEquals(self.response.status_code, 200)
def test_view_function(self):
view = resolve("/change")
self.assertEquals(view.func.view_class, auth_views.PasswordChangeView)
def test_csrf(self):
self.assertContains(self.response, "csrfmiddlewaretoken")
def test_contains_form(self):
print(repr(self.response))
form = self.response.context.get("form")
self.assertIsInstance(form, PasswordChangeForm)
def test_form_inputs(self):
"""The view must contain five inputs: csrf, old password, 2 * new password and the button"""
self.assertContains(self.response, "<input", 5)
self.assertContains(self.response, 'type="password"', 3)
class SuccessfulPasswordChangeTests(TestCase):
def setUp(self):
email = "test@example.com"
User.objects.create_user(
username="test", email=email, password="ufgdlneginetriunae"
)
url = reverse("password_change")
self.response = self.client.post(url, {"email": email})
class PasswordChangeDoneTests(TestCase):
def setUp(self):
url = reverse("password_change_done")
self.response = self.client.get(url)
def test_status_code(self):
self.assertEquals(self.response.status_code, 302)
def test_view_function(self):
view = resolve("/change/done")
self.assertEquals(view.func.view_class, auth_views.PasswordChangeDoneView)
class AuthenticatedFrontendViewTests(TestCase):
def setUp(self) -> None:
User.objects.create_user(username="test", password="ufgdlneginetriunae")
self.client.login(username="test", password="ufgdlneginetriunae")
def test_logout_button(self):
"""Frontend shows logout button to authenticated users"""
url = reverse("orders")
response = self.client.get(url)
self.assertContains(response, "Log out</a>")
def test_change_password_button(self):
"""Frontend shows change password button to authenticated users"""
url = reverse("orders")
response = self.client.get(url)
self.assertContains(response, "Change password</a>")
| 34.879195 | 104 | 0.687512 | 597 | 5,197 | 5.855946 | 0.19598 | 0.075515 | 0.046339 | 0.045767 | 0.662185 | 0.590961 | 0.581522 | 0.570652 | 0.5 | 0.420481 | 0 | 0.007942 | 0.2005 | 5,197 | 148 | 105 | 35.114865 | 0.833454 | 0.080431 | 0 | 0.533333 | 0 | 0 | 0.110994 | 0.009267 | 0 | 0 | 0 | 0 | 0.209524 | 1 | 0.266667 | false | 0.314286 | 0.057143 | 0 | 0.4 | 0.009524 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
c9e61bdbc8e131315741b8bc7b60aef4c5483f19 | 96,219 | py | Python | tests/test_data/hierarchical_optimizer_test_data.py | Algomorph/LevelSetFusion-Python | 46625cd185da4413f9afaf201096203ee72d3803 | [
"Apache-2.0"
] | 8 | 2019-01-30T19:01:25.000Z | 2021-03-05T14:10:51.000Z | tests/test_data/hierarchical_optimizer_test_data.py | Algomorph/LevelSetFusion-Python | 46625cd185da4413f9afaf201096203ee72d3803 | [
"Apache-2.0"
] | 58 | 2018-12-19T16:57:38.000Z | 2019-06-06T19:52:36.000Z | tests/test_data/hierarchical_optimizer_test_data.py | Algomorph/LevelSetFusion-Python | 46625cd185da4413f9afaf201096203ee72d3803 | [
"Apache-2.0"
] | 2 | 2019-03-06T06:30:30.000Z | 2019-06-03T11:00:15.000Z | # ================================================================
# Created by Gregory Kramida on 12/14/18.
# Copyright (c) 2018 Gregory Kramida
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ================================================================
# test fixtures for Hierarchical Non-rigid Slam Optimizer
import numpy as np
import pytest
# @pytest.fixture(scope="session")
# def live_field():
# return np.array(
live_field = np.array(
[[1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[9.50000405e-01, 1.00000000e+00, 9.50000405e-01,
9.50000405e-01, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[9.00000215e-01, 9.00000215e-01, 8.50000203e-01,
8.50000203e-01, 9.00000215e-01, 9.75000203e-01,
9.75000203e-01, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[8.00000012e-01, 8.00000012e-01, 7.50000000e-01,
8.00000012e-01, 8.00000012e-01, 8.75000000e-01,
9.00000036e-01, 9.00000036e-01, 9.75000024e-01,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[6.99999809e-01, 6.99999809e-01, 6.49999797e-01,
6.99999809e-01, 6.99999809e-01, 7.74999797e-01,
7.99999833e-01, 7.99999833e-01, 8.99999797e-01,
9.49999809e-01, 9.74999845e-01, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[5.99999607e-01, 5.49999595e-01, 5.49999595e-01,
5.99999607e-01, 6.24999642e-01, 6.74999595e-01,
6.99999630e-01, 6.99999630e-01, 7.99999595e-01,
8.49999607e-01, 8.74999642e-01, 9.49999630e-01,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[4.99999404e-01, 4.49999422e-01, 4.49999422e-01,
4.99999404e-01, 5.74999392e-01, 5.74999392e-01,
5.99999428e-01, 6.24999404e-01, 6.99999392e-01,
7.49999404e-01, 8.24999392e-01, 8.99999440e-01,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[4.00000691e-01, 3.50000709e-01, 3.50000709e-01,
4.00000691e-01, 4.75000709e-01, 4.75000709e-01,
5.00000715e-01, 5.25000691e-01, 6.00000679e-01,
6.50000691e-01, 7.25000679e-01, 8.00000727e-01,
9.25000727e-01, 9.50000703e-01, 1.00000000e+00,
1.00000000e+00],
[3.00000489e-01, 2.50000507e-01, 3.00000489e-01,
3.00000489e-01, 3.75000507e-01, 4.00000513e-01,
4.00000513e-01, 4.75000501e-01, 5.00000477e-01,
5.50000489e-01, 6.50000513e-01, 7.75000513e-01,
9.00000513e-01, 9.25000489e-01, 1.00000000e+00,
1.00000000e+00],
[1.50000304e-01, 1.50000304e-01, 2.00000301e-01,
2.25000292e-01, 2.75000304e-01, 3.00000310e-01,
3.00000310e-01, 4.00000304e-01, 4.50000286e-01,
4.75000292e-01, 5.50000310e-01, 6.75000310e-01,
8.00000310e-01, 8.25000286e-01, 9.50000286e-01,
1.00000000e+00],
[5.00000939e-02, 5.00000939e-02, 1.00000098e-01,
1.75000101e-01, 1.75000101e-01, 2.00000092e-01,
2.00000092e-01, 3.00000101e-01, 3.50000083e-01,
3.75000089e-01, 4.50000107e-01, 5.75000107e-01,
6.50000095e-01, 7.25000083e-01, 1.00000000e+00,
1.00000000e+00],
[-5.00001088e-02, -5.00001088e-02, -1.07288365e-07,
7.49998912e-02, 7.49998912e-02, 9.99998897e-02,
1.24999896e-01, 1.99999899e-01, 2.49999896e-01,
3.24999899e-01, 3.99999887e-01, 5.24999917e-01,
5.49999893e-01, 6.24999881e-01, 1.00000000e+00,
1.00000000e+00],
[-1.50000304e-01, -1.00000307e-01, -1.00000307e-01,
-2.50003096e-02, -3.09944141e-07, -3.09944141e-07,
7.49996901e-02, 9.99996886e-02, 1.49999693e-01,
2.24999696e-01, 2.99999684e-01, 4.24999684e-01,
4.49999690e-01, 5.74999690e-01, 1.00000000e+00,
1.00000000e+00],
[-2.50000507e-01, -2.00000510e-01, -1.75000519e-01,
-1.25000507e-01, -1.00000516e-01, -1.00000516e-01,
-2.50005126e-02, -5.12599968e-07, 4.99994867e-02,
1.49999484e-01, 2.74999499e-01, 3.99999499e-01,
3.49999487e-01, 4.74999487e-01, 1.00000000e+00,
1.00000000e+00]], dtype=np.float32)
# @pytest.fixture(scope="session")
# def canonical_field():
# return np.array(
canonical_field = np.array(
[[1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[9.50000405e-01, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[9.00000215e-01, 9.00000215e-01, 9.25000250e-01,
9.25000250e-01, 9.00000215e-01, 9.25000250e-01,
9.75000203e-01, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[8.00000012e-01, 8.00000012e-01, 8.25000048e-01,
8.00000012e-01, 8.00000012e-01, 8.25000048e-01,
8.75000000e-01, 9.00000036e-01, 9.75000024e-01,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[6.99999809e-01, 6.99999809e-01, 7.24999845e-01,
6.99999809e-01, 6.99999809e-01, 7.24999845e-01,
7.74999797e-01, 8.24999809e-01, 8.99999797e-01,
9.49999809e-01, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[5.99999607e-01, 5.99999607e-01, 6.24999642e-01,
5.99999607e-01, 5.99999607e-01, 6.74999595e-01,
6.99999630e-01, 7.24999607e-01, 7.99999595e-01,
8.49999607e-01, 9.24999595e-01, 9.49999630e-01,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[4.99999404e-01, 5.24999440e-01, 5.24999440e-01,
4.99999404e-01, 5.24999440e-01, 5.74999392e-01,
5.99999428e-01, 6.24999404e-01, 6.99999392e-01,
7.74999440e-01, 8.49999428e-01, 8.99999440e-01,
1.00000000e+00, 1.00000000e+00, 1.00000000e+00,
1.00000000e+00],
[4.00000691e-01, 4.25000697e-01, 4.25000697e-01,
4.00000691e-01, 4.25000697e-01, 4.75000709e-01,
5.00000715e-01, 5.25000691e-01, 6.00000679e-01,
6.75000727e-01, 7.50000715e-01, 8.00000727e-01,
9.25000727e-01, 9.50000703e-01, 1.00000000e+00,
1.00000000e+00],
[3.00000489e-01, 3.25000495e-01, 3.00000489e-01,
3.00000489e-01, 3.25000495e-01, 3.75000507e-01,
4.00000513e-01, 4.75000501e-01, 5.00000477e-01,
5.75000525e-01, 6.50000513e-01, 7.25000501e-01,
8.50000501e-01, 9.25000489e-01, 1.00000000e+00,
1.00000000e+00],
[2.00000301e-01, 2.25000292e-01, 2.00000301e-01,
2.00000301e-01, 2.75000304e-01, 3.00000310e-01,
3.25000286e-01, 4.00000304e-01, 4.50000286e-01,
5.25000274e-01, 5.50000310e-01, 6.25000298e-01,
7.50000298e-01, 8.25000286e-01, 1.00000000e+00,
1.00000000e+00],
[1.25000089e-01, 1.25000089e-01, 1.00000098e-01,
1.25000089e-01, 1.75000101e-01, 2.00000092e-01,
2.25000098e-01, 3.00000101e-01, 3.50000083e-01,
4.25000101e-01, 4.50000107e-01, 5.75000107e-01,
6.50000095e-01, 7.25000083e-01, 1.00000000e+00,
1.00000000e+00],
[2.49998923e-02, 2.49998923e-02, -1.07288365e-07,
2.49998923e-02, 7.49998912e-02, 9.99998897e-02,
1.24999896e-01, 1.99999899e-01, 2.74999887e-01,
3.49999905e-01, 3.99999887e-01, 5.24999917e-01,
5.49999893e-01, 6.24999881e-01, 1.00000000e+00,
1.00000000e+00],
[-7.50003085e-02, -1.00000307e-01, -1.00000307e-01,
-7.50003085e-02, -2.50003096e-02, -3.09944141e-07,
7.49996901e-02, 9.99996886e-02, 1.74999684e-01,
2.49999687e-01, 2.99999684e-01, 4.24999684e-01,
4.49999690e-01, 5.99999666e-01, 1.00000000e+00,
1.00000000e+00],
[-1.75000519e-01, -2.00000510e-01, -2.00000510e-01,
-1.75000519e-01, -1.25000507e-01, -1.00000516e-01,
-2.50005126e-02, -5.12599968e-07, 7.49994889e-02,
1.49999484e-01, 2.24999487e-01, 3.49999487e-01,
3.49999487e-01, 4.99999493e-01, 9.49999511e-01,
1.00000000e+00]], dtype=np.float32)
# @pytest.fixture(scope="session")
# def final_live_field():
# return np.array(
final_live_field = np.array([[1., 1., 1., 1., 1.,
1., 1., 1., 1., 1.,
1., 1., 1., 1., 1.,
1.],
[1., 1., 1., 1., 1.,
1., 1., 1., 1., 1.,
1., 1., 1., 1., 1.,
1.],
[1., 1., 1., 1., 1.,
1., 1., 1., 1., 1.,
1., 1., 1., 1., 1.,
1.],
[0.9501344, 0.99998045, 0.95563745, 0.9556796, 1.,
1., 1., 1., 1., 1.,
1., 1., 1., 1., 1.,
1.],
[0.9014509, 0.90249425, 0.8735871, 0.87183094, 0.89561236,
0.96108705, 0.97375935, 0.99825686, 1., 1.,
1., 1., 1., 1., 1.,
1.],
[0.8025613, 0.8024852, 0.7729278, 0.80527866, 0.796212,
0.85823464, 0.89420485, 0.8985412, 0.9751491, 1.,
1., 1., 1., 1., 1.,
1.],
[0.7043258, 0.7036076, 0.6713199, 0.7073472, 0.69752157,
0.7594382, 0.7953931, 0.806474, 0.90024775, 0.95017064,
0.97689474, 1., 1., 1., 1.,
1.],
[0.6036614, 0.57109785, 0.57245946, 0.6073731, 0.6208105,
0.6714098, 0.70005786, 0.70605624, 0.8002847, 0.8502639,
0.88739115, 0.9516738, 1., 1., 1.,
1.],
[0.5070281, 0.47254044, 0.47282413, 0.50756174, 0.5608865,
0.5712685, 0.59924257, 0.6242329, 0.7022431, 0.75868964,
0.83123755, 0.90223074, 0.9997653, 0.99993294, 0.9999998,
1.],
[0.40689468, 0.37217137, 0.370607, 0.40756115, 0.45926473,
0.4719974, 0.49924418, 0.52453893, 0.6022449, 0.6588246,
0.7337068, 0.8029369, 0.9247998, 0.9499263, 0.99989855,
1.],
[0.3084575, 0.2731813, 0.30076993, 0.30178022, 0.35970187,
0.3924762, 0.40023243, 0.47510353, 0.5030358, 0.56025034,
0.64544666, 0.75209594, 0.88126004, 0.92161745, 0.99999195,
1.],
[0.18090239, 0.17383796, 0.20150712, 0.22388586, 0.27161047,
0.29674137, 0.30673754, 0.40016794, 0.4516813, 0.48751667,
0.5458921, 0.65056527, 0.77401495, 0.82188004, 0.95451623,
1.],
[0.0745317, 0.0761954, 0.097394, 0.16237263, 0.17464648,
0.19960515, 0.20674457, 0.30051148, 0.35348395, 0.38974848,
0.45036337, 0.5753146, 0.6500007, 0.7250005, 0.9999994,
1.],
[-0.02597853, -0.02578622, -0.00260217, 0.06066618, 0.07471567,
0.09960751, 0.1255793, 0.20051758, 0.26036632, 0.33239287,
0.40030205, 0.52516353, 0.55000037, 0.6250003, 1.,
1.],
[-0.12794192, -0.09662973, -0.10520743, -0.04469248, -0.01413691,
-0.00914939, 0.07124515, 0.09684893, 0.15973292, 0.23461851,
0.2970746, 0.42060137, 0.4521276, 0.59846294, 0.9988471,
1.],
[-0.22680263, -0.1937151, 0.28203386, 0.4757796, 0.5330909,
0.4819764, 0.18177587, 0.20523289, 0.06094409, 0.15342687,
0.2936795, 0.4187874, 0.35232484, 0.49960482, 0.9524278,
1.]], dtype=np.float32)
# @pytest.fixture(scope="session")
# def warp_field():
# return np.array(
warp_field = np.array([[[3.99223063e-04, -2.58702761e-03],
[3.99223063e-04, -2.58702761e-03],
[3.99223063e-04, -2.58702761e-03],
[3.99223063e-04, -2.58702761e-03],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[3.99223063e-04, -2.58702761e-03],
[3.99223063e-04, -2.58702761e-03],
[3.99223063e-04, -2.58702761e-03],
[3.99223063e-04, -2.58702761e-03],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[3.92419024e-04, -2.57000909e-03],
[3.92419024e-04, -2.57000909e-03],
[4.00435616e-04, -2.68424191e-02],
[4.00435616e-04, -2.68424191e-02],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[2.51820893e-04, -2.42918753e-03],
[3.92416114e-04, -2.58952030e-03],
[-2.12121941e-02, -9.35134515e-02],
[2.22218968e-02, -9.34396759e-02],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[1.84272314e-04, -2.90076919e-02],
[1.58736110e-03, -2.57339124e-02],
[-2.44968385e-02, -2.23619848e-01],
[3.39246988e-02, -2.01344609e-01],
[-1.59015451e-02, 3.62156443e-02],
[-5.32566532e-02, 9.91887823e-02],
[-6.18701195e-03, 1.65104344e-02],
[-6.03775308e-03, 1.59462932e-02],
[2.46718479e-03, -3.80784390e-03],
[2.46718479e-03, -3.80784390e-03],
[2.47937441e-03, -3.82491923e-03],
[2.47937441e-03, -3.82491923e-03],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[2.29839599e-04, -2.56123822e-02],
[1.62350747e-03, -2.56639253e-02],
[-7.14249385e-04, -2.28920504e-01],
[1.38852641e-03, -1.05426207e-01],
[-1.88643243e-02, 3.78797203e-02],
[-5.98912425e-02, 1.22734822e-01],
[-1.19321784e-02, 5.49688675e-02],
[-5.29943639e-03, 1.45881874e-02],
[2.31517386e-03, -3.65559850e-03],
[2.46718479e-03, -3.80784390e-03],
[2.47937441e-03, -3.82491923e-03],
[2.47937441e-03, -3.82491923e-03],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[-2.22062296e-03, -3.66792679e-02],
[-1.72944987e-04, -3.60780954e-02],
[9.74072143e-03, -2.08330020e-01],
[5.37748123e-03, -7.34736845e-02],
[-1.43052815e-02, 3.28859724e-02],
[-5.47412746e-02, 1.16148934e-01],
[-6.43323082e-03, 4.44589965e-02],
[2.09001005e-02, -4.40714434e-02],
[1.44567410e-03, -2.34306185e-03],
[1.72433583e-03, -2.55655148e-03],
[2.66943052e-02, -5.04477806e-02],
[1.54490098e-02, -2.21852511e-02],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[1.94067147e-03, -3.75522301e-02],
[-2.01374572e-02, -1.34847462e-01],
[3.49270105e-02, -2.07134858e-01],
[3.44072329e-03, -7.29375407e-02],
[-3.26105133e-02, 6.53463230e-02],
[-1.33142164e-02, 2.94371285e-02],
[-7.21017132e-04, -7.62700103e-04],
[2.12629549e-02, -3.93032134e-02],
[1.36585976e-03, -2.16769986e-03],
[1.63642992e-03, -2.23383144e-03],
[5.66411465e-02, -8.38072300e-02],
[1.32946633e-02, -2.04605740e-02],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[-1.74354156e-03, -6.16765060e-02],
[-4.22191210e-02, -2.04300120e-01],
[5.41235991e-02, -2.01184794e-01],
[1.27413431e-02, -6.64910078e-02],
[-4.46518213e-02, 1.07641459e-01],
[-1.29681081e-02, 3.73093151e-02],
[-2.86546024e-03, 6.85238745e-03],
[-2.43876432e-03, 7.05553126e-03],
[1.18486723e-02, -1.65128149e-02],
[3.84466238e-02, -5.92056476e-02],
[5.02970479e-02, -4.93174270e-02],
[1.51160788e-02, -1.46142133e-02],
[-1.45919377e-03, 1.18344289e-03],
[-1.71378511e-03, 1.34053733e-03],
[-2.07823329e-03, 1.72119087e-03],
[-2.07823329e-03, 1.72119087e-03]],
[[-1.35422195e-03, -6.08978234e-02],
[-4.23076972e-02, -2.00555235e-01],
[5.49490862e-02, -1.78590521e-01],
[1.23651735e-02, -6.63316473e-02],
[-4.47240099e-02, 1.23816706e-01],
[-1.32030966e-02, 3.98683473e-02],
[-2.86409492e-03, 6.85405126e-03],
[-2.80167419e-03, 7.81217404e-03],
[1.18601164e-02, -1.65122785e-02],
[3.87393050e-02, -5.91855459e-02],
[4.81454469e-02, -5.09526432e-02],
[1.24037499e-02, -1.39002521e-02],
[-1.37753948e-03, 1.15023123e-03],
[-1.65700377e-03, 1.31763006e-03],
[-2.02677748e-03, 1.72094489e-03],
[-2.07823329e-03, 1.72119087e-03]],
[[7.82109331e-03, -8.84804279e-02],
[-7.25064054e-03, -2.28182152e-01],
[-4.75502294e-03, -2.00482570e-02],
[-5.82917128e-03, -1.78494621e-02],
[-5.07386886e-02, 1.16408616e-01],
[-1.69436336e-02, 7.10071921e-02],
[2.80047883e-03, -2.19302296e-04],
[2.89148255e-03, -6.13311247e-04],
[1.60101727e-02, -2.23481935e-02],
[4.50025387e-02, -5.81500120e-02],
[-2.69738398e-02, 1.86905917e-02],
[-1.24137096e-01, 7.38739818e-02],
[-8.46397504e-02, 8.16051289e-02],
[-2.32071169e-02, 2.80287564e-02],
[8.79966188e-03, 1.62738594e-04],
[8.79358035e-03, 1.66785263e-04]],
[[-5.68241207e-03, -1.74806654e-01],
[2.18310580e-02, -2.27460593e-01],
[-5.61808469e-03, -1.78771429e-02],
[-2.31726542e-02, 1.04598897e-02],
[-9.13501717e-03, 2.94654034e-02],
[-1.10138748e-02, 2.98357625e-02],
[2.43381765e-02, -4.32974435e-02],
[2.72006937e-03, -4.22156241e-04],
[1.72727015e-02, -2.47697048e-02],
[6.35446906e-02, -1.01196460e-01],
[-2.97305137e-02, 1.87837053e-02],
[-1.20273992e-01, 9.40074921e-02],
[-7.67609999e-02, 1.12137340e-01],
[-2.14547068e-02, 2.55643148e-02],
[9.01637450e-02, 1.70593121e-04],
[8.79358035e-03, 1.66785263e-04]],
[[2.09829286e-02, -2.45315596e-01],
[4.90596592e-02, -2.37422779e-01],
[-1.25929657e-02, 1.97644513e-02],
[-4.82313000e-02, 9.01009962e-02],
[-2.04636389e-03, 3.53614520e-03],
[-2.03452841e-03, 3.44079128e-03],
[2.60568969e-02, -4.13876921e-02],
[3.94379767e-03, -3.14201764e-03],
[2.26993002e-02, -2.91637424e-02],
[6.71805143e-02, -9.70984027e-02],
[1.45908503e-03, -1.80868793e-03],
[1.61956728e-03, -1.92842283e-03],
[-7.99494273e-07, -4.25305916e-06],
[-1.47421201e-06, -5.09348274e-06],
[1.10077208e-05, -1.23845921e-05],
[9.27685051e-06, -1.26992882e-05]],
[[2.09854860e-02, -2.40215331e-01],
[4.98216711e-02, -2.17227638e-01],
[-1.26408301e-02, 1.98254380e-02],
[-4.81206030e-02, 1.07246444e-01],
[-2.06842762e-03, 3.78697016e-03],
[-1.92570814e-03, 3.44396359e-03],
[4.19337768e-03, -3.52706830e-03],
[4.08441201e-03, -3.13463807e-03],
[4.65160236e-02, -7.04147741e-02],
[5.46285696e-02, -6.59161806e-02],
[1.63955963e-03, -1.94425695e-03],
[2.09460175e-03, -2.22062482e-03],
[-2.38616764e-07, -5.00169745e-06],
[-1.96803853e-06, -5.35602976e-06],
[9.27685051e-06, -1.26992882e-05],
[9.27685051e-06, -1.26992882e-05]],
[[7.97562748e-02, -1.88210756e-01],
[2.73629818e-02, -6.56157658e-02],
[-3.21300924e-02, 6.86923489e-02],
[-6.96211755e-02, 1.47268727e-01],
[-3.32090519e-02, 1.33063450e-01],
[-2.24811453e-02, 9.14906412e-02],
[-1.16509898e-02, 2.88071129e-02],
[-1.31998407e-02, 2.82075051e-02],
[4.70495224e-02, -6.20449744e-02],
[5.17655127e-02, -5.73639423e-02],
[-3.35510932e-02, 1.53222606e-02],
[-3.25333700e-02, 1.32656964e-02],
[1.37356836e-02, -4.13792068e-03],
[5.31211607e-02, -1.87300611e-02],
[-2.71264813e-03, 4.84526681e-05],
[-1.68603882e-02, 9.75996591e-05]],
[[8.70634988e-02, -1.88446581e-01],
[2.39985809e-02, -5.71974926e-02],
[-1.87225595e-01, 3.91389668e-01],
[-2.14346007e-01, 5.38423717e-01],
[-9.52014253e-02, 5.76453805e-01],
[-1.75683185e-01, 5.29069662e-01],
[-1.00779340e-01, 2.07576364e-01],
[-8.12411606e-02, 2.06844211e-01],
[5.01883365e-02, -6.00105487e-02],
[1.52863478e-02, -2.04293244e-02],
[-1.90030769e-01, 5.66725843e-02],
[-9.21593457e-02, 4.95614223e-02],
[1.54908346e-02, -3.89001286e-03],
[4.37500291e-02, -1.71142146e-02],
[-9.07565206e-02, 1.57411594e-03],
[-1.68603882e-02, 9.75996591e-05]]], dtype=np.float32)
field_A_16x16 = np.array(
[[0.91373026, 0.7631806, 0.08786197, 0.10263897, 0.13590212,
0.8593752, 0.8896638, 0.2719375, 0.9477815, 0.844249,
0.44680354, 0.72320014, 0.91686106, 0.6317498, 0.78991777,
0.15163644],
[0.5146971, 0.3253312, 0.97044516, 0.83075416, 0.29059306,
0.157082, 0.6153188, 0.7508671, 0.7753249, 0.9061798,
0.71732414, 0.3208247, 0.31425896, 0.44407454, 0.0251544,
0.9276875],
[0.7583217, 0.18427077, 0.9965386, 0.6091512, 0.28597274,
0.5911535, 0.86328685, 0.02117831, 0.09367206, 0.65002584,
0.11911005, 0.8599053, 0.16811769, 0.00334252, 0.32462037,
0.76539224],
[0.9246273, 0.47059137, 0.0624321, 0.7045868, 0.49657223,
0.07037203, 0.19789569, 0.13755776, 0.7977794, 0.7520082,
0.49519333, 0.6652541, 0.11336982, 0.8190655, 0.18693554,
0.5479334],
[0.8661758, 0.3582901, 0.56721294, 0.5557161, 0.5258801,
0.8566619, 0.91307145, 0.5432345, 0.7981101, 0.4385603,
0.23251879, 0.43203297, 0.753425, 0.8316272, 0.7360007,
0.92396367],
[0.89087427, 0.01101896, 0.96461254, 0.8389174, 0.27696067,
0.15572909, 0.25050437, 0.9694313, 0.827058, 0.09619189,
0.7794552, 0.10559788, 0.9247047, 0.43528184, 0.9743978,
0.06749944],
[0.8753066, 0.703833, 0.11616795, 0.06971734, 0.7136266,
0.96721244, 0.04542445, 0.8354135, 0.5037647, 0.5022158,
0.15594126, 0.80052304, 0.6979527, 0.6181056, 0.7586989,
0.36736614],
[0.8454999, 0.18426065, 0.33611932, 0.5157499, 0.79185313,
0.7149252, 0.09490626, 0.11735506, 0.2513307, 0.02406335,
0.14921829, 0.8318604, 0.5943496, 0.6345989, 0.8060292,
0.8396816],
[0.9422193, 0.9840896, 0.6639309, 0.13773157, 0.65439135,
0.7209409, 0.15291427, 0.03027239, 0.37073377, 0.3956663,
0.7791207, 0.6743447, 0.1529438, 0.34367964, 0.79867744,
0.84944177],
[0.8620148, 0.48429936, 0.29500124, 0.17493461, 0.7918412,
0.2368394, 0.7653702, 0.68646884, 0.6918225, 0.1426204,
0.01255776, 0.6964023, 0.9464172, 0.8880946, 0.7620122,
0.32834],
[0.00166922, 0.77315664, 0.37893042, 0.5802845, 0.09662131,
0.8704379, 0.8292256, 0.94926184, 0.87139356, 0.62903595,
0.3553147, 0.25048232, 0.8922809, 0.83649385, 0.6956004,
0.32032806],
[0.10994852, 0.90549064, 0.9330898, 0.99141043, 0.37472203,
0.7271425, 0.69821095, 0.54541427, 0.8521281, 0.51501006,
0.00878792, 0.54687524, 0.3497573, 0.6755401, 0.40384126,
0.28839406],
[0.22394936, 0.3545188, 0.06892869, 0.8924489, 0.4562973,
0.4135325, 0.8228336, 0.55103886, 0.84643346, 0.13937403,
0.24812876, 0.76347584, 0.3336846, 0.7995412, 0.25575867,
0.10004166],
[0.6865364, 0.76798236, 0.76032764, 0.5747156, 0.9401415,
0.03685811, 0.5637125, 0.18716684, 0.6944219, 0.60005254,
0.11739989, 0.6562824, 0.76317394, 0.8836002, 0.10866154,
0.74765366],
[0.5018622, 0.36515746, 0.0915058, 0.24618873, 0.5489385,
0.80023193, 0.37447423, 0.08787794, 0.9378552, 0.2841429,
0.9117465, 0.24413309, 0.88298357, 0.01785158, 0.56231743,
0.6028794],
[0.9267506, 0.90987325, 0.8734759, 0.4573191, 0.71733904,
0.57869774, 0.35476235, 0.49421957, 0.4568069, 0.7848754,
0.00992102, 0.55362827, 0.68313384, 0.59789115, 0.31711292,
0.07753057]], dtype=np.float32)
warp_field_A_16x16 = np.array(
[[[1.73157543e-01, 7.19841778e-01],
[8.51825297e-01, 1.45684421e-01],
[2.25969434e-01, 8.16127360e-02],
[7.73610413e-01, 9.58827615e-01],
[3.95637184e-01, 8.42441022e-01],
[7.24752188e-01, 4.78849947e-01],
[7.05444872e-01, 2.58462757e-01],
[2.85904199e-01, 8.24459553e-01],
[5.19597650e-01, 4.89987582e-01],
[1.60455316e-01, 9.44107533e-01],
[4.33971941e-01, 2.24923447e-01],
[9.87505019e-01, 7.11176574e-01],
[5.86804807e-01, 2.23756075e-01],
[1.49694324e-01, 6.73664391e-01],
[5.85952878e-01, 4.86144245e-01],
[9.82111245e-02, 7.45900512e-01]],
[[1.63857371e-01, 1.02073282e-01],
[3.47714037e-01, 7.61977255e-01],
[1.93956196e-01, 7.35142052e-01],
[9.49599326e-01, 4.07754093e-01],
[1.42573461e-01, 2.95739681e-01],
[7.60748625e-01, 4.64589924e-01],
[8.50738823e-01, 2.80425102e-01],
[7.36888766e-01, 4.88183856e-01],
[7.70152390e-01, 7.15010583e-01],
[1.23042785e-01, 9.91979837e-01],
[1.42882243e-01, 7.02945828e-01],
[9.73401070e-01, 1.63954929e-01],
[4.05514956e-01, 8.01079333e-01],
[9.02909815e-01, 2.37098083e-01],
[1.75384693e-02, 6.10820711e-01],
[9.56144989e-01, 9.04309154e-01]],
[[7.88338661e-01, 8.10386479e-01],
[1.81768797e-02, 7.42854476e-01],
[3.96431983e-01, 1.99433696e-02],
[8.10523808e-01, 9.38104510e-01],
[7.27113903e-01, 8.36036384e-01],
[1.86146319e-01, 7.67266393e-01],
[6.59489483e-02, 2.00159818e-01],
[7.96794832e-01, 1.66696310e-01],
[3.81922513e-01, 7.96498418e-01],
[4.49248962e-02, 9.95188653e-01],
[2.65819848e-01, 1.49980616e-02],
[6.89572573e-01, 7.52614439e-01],
[3.97666693e-01, 8.27410161e-01],
[3.96299958e-01, 7.17369020e-01],
[3.60011935e-01, 9.34164897e-02],
[8.87737691e-01, 8.39919567e-01]],
[[1.21136107e-01, 2.63832927e-01],
[8.32727015e-01, 7.20967591e-01],
[6.70219421e-01, 9.16788399e-01],
[7.95709670e-01, 8.59232008e-01],
[5.28492570e-01, 8.36180031e-01],
[1.33923426e-01, 3.82678479e-01],
[7.58522093e-01, 3.90571386e-01],
[4.15316552e-01, 4.26658630e-01],
[7.66514912e-02, 3.00836444e-01],
[6.06139302e-01, 8.17135572e-01],
[6.79135919e-01, 8.92381251e-01],
[4.05365884e-01, 3.29325110e-01],
[9.70078230e-01, 1.16345145e-01],
[3.91772956e-01, 8.71538043e-01],
[1.27621174e-01, 7.91660786e-01],
[4.67474788e-01, 6.96209192e-01]],
[[8.93825889e-01, 3.17042589e-01],
[9.72070396e-01, 3.76655430e-01],
[6.19705431e-02, 8.88957202e-01],
[1.59682393e-01, 4.51680094e-01],
[9.44114327e-01, 9.37228262e-01],
[3.60726148e-01, 9.33687329e-01],
[5.52968204e-01, 4.56895120e-02],
[5.09599686e-01, 3.04964930e-01],
[4.16250467e-01, 5.71180642e-01],
[8.00097525e-01, 4.52593595e-01],
[2.79801041e-01, 5.68222463e-01],
[1.68354243e-01, 8.60655129e-01],
[9.91807342e-01, 6.66935503e-01],
[1.85036674e-01, 5.64945638e-02],
[2.24479511e-01, 4.27200466e-01],
[4.76239443e-01, 9.74674404e-01]],
[[6.21011928e-02, 8.05418640e-02],
[1.40756398e-01, 4.88264114e-01],
[9.08101082e-01, 6.09841608e-02],
[7.59369791e-01, 6.77543700e-01],
[6.85424030e-01, 8.36703360e-01],
[7.37327874e-01, 6.94150925e-01],
[5.29041171e-01, 5.82427144e-01],
[4.25470769e-01, 3.53882253e-01],
[2.92196780e-01, 5.72306156e-01],
[5.81807315e-01, 2.91124851e-01],
[7.31737673e-01, 1.22744620e-01],
[2.32295975e-01, 1.63294777e-01],
[2.04817072e-01, 8.57605159e-01],
[7.40439057e-01, 5.13281345e-01],
[5.52101493e-01, 4.50047076e-01],
[1.37482285e-01, 4.27753568e-01]],
[[3.59929472e-01, 4.95265514e-01],
[9.17686403e-01, 4.26230401e-01],
[2.39188552e-01, 4.69455451e-01],
[1.49480581e-01, 1.42742217e-01],
[3.85575056e-01, 7.05356300e-01],
[6.99684143e-01, 4.31396127e-01],
[8.96201491e-01, 6.68193698e-01],
[8.81241798e-01, 3.74053359e-01],
[6.63454756e-02, 5.70128076e-02],
[1.04918219e-01, 9.87643242e-01],
[8.87520313e-01, 1.92835554e-02],
[3.39512169e-01, 5.81350267e-01],
[9.14291203e-01, 3.01563352e-01],
[1.83225274e-01, 8.02121162e-01],
[4.75696146e-01, 5.90080202e-01],
[6.02959454e-01, 7.35284805e-01]],
[[9.22051251e-01, 1.27511472e-01],
[5.72855234e-01, 3.73522252e-01],
[7.01477170e-01, 9.29893315e-01],
[8.74887109e-02, 6.78593814e-01],
[2.85323054e-01, 4.63607669e-01],
[4.71625417e-01, 3.40298176e-01],
[8.04928780e-01, 1.06936991e-02],
[3.64485830e-01, 9.26724374e-01],
[4.13415462e-01, 5.88850617e-01],
[8.36375117e-01, 7.45930374e-01],
[9.09174204e-01, 4.58617777e-01],
[8.23468924e-01, 3.74932826e-01],
[4.72223550e-01, 1.13871433e-01],
[2.84476429e-01, 8.04696500e-01],
[7.12410808e-01, 2.10113168e-01],
[9.83612776e-01, 1.25854433e-01]],
[[6.49569809e-01, 3.75683486e-01],
[7.58661330e-01, 5.21789551e-01],
[9.80462611e-01, 7.63358712e-01],
[5.10629177e-01, 5.82922280e-01],
[8.97050261e-01, 2.26755783e-01],
[2.11527884e-01, 8.18514168e-01],
[4.58555639e-01, 9.39463794e-01],
[7.66666234e-01, 6.32153034e-01],
[4.85867798e-01, 7.09144175e-01],
[2.48842537e-01, 5.85844874e-01],
[1.80062726e-01, 5.03837802e-02],
[6.67257249e-01, 2.55644768e-01],
[3.53679478e-01, 5.83170056e-01],
[2.63057500e-01, 1.71477646e-01],
[9.05430615e-01, 4.91425276e-01],
[4.74303424e-01, 9.31110561e-01]],
[[5.11565149e-01, 3.35441455e-02],
[5.67254782e-01, 2.78949082e-01],
[2.05964789e-01, 6.22083008e-01],
[1.53888583e-01, 1.73320651e-01],
[8.65545154e-01, 3.33191514e-01],
[2.88898521e-03, 1.70736507e-01],
[5.03370702e-01, 8.81274164e-01],
[6.05935395e-01, 7.77221143e-01],
[9.81306136e-01, 7.16982260e-02],
[5.44498026e-01, 2.45867297e-01],
[8.75583172e-01, 9.34868097e-01],
[6.32736534e-02, 7.77047276e-01],
[1.25000983e-01, 8.70258391e-01],
[6.39363468e-01, 5.95744133e-01],
[6.13187075e-01, 6.73594952e-01],
[3.37353838e-03, 7.25286126e-01]],
[[7.06908524e-01, 9.39027518e-02],
[2.60723531e-01, 9.19531107e-01],
[4.82208908e-01, 7.63498068e-01],
[4.01008815e-01, 5.69213986e-01],
[4.21226025e-01, 9.95880663e-01],
[6.02546692e-01, 9.69971895e-01],
[2.26023182e-01, 2.79686123e-01],
[2.49765307e-01, 4.59783316e-01],
[2.53804505e-01, 3.02870888e-02],
[7.31515586e-01, 6.39392734e-01],
[2.01958135e-01, 7.45364249e-01],
[3.45539689e-01, 6.18217587e-01],
[4.57539529e-01, 9.30734992e-01],
[5.88941813e-01, 7.73802876e-01],
[3.34176898e-01, 9.29643095e-01],
[7.11476505e-01, 8.02178904e-02]],
[[3.37231636e-01, 7.77236640e-01],
[4.48389590e-01, 7.26522088e-01],
[6.72160149e-01, 6.65733039e-01],
[4.99543667e-01, 7.39258885e-01],
[7.82610834e-01, 3.29786152e-01],
[7.97186375e-01, 1.18690254e-02],
[9.38765466e-01, 4.70145553e-01],
[3.25287342e-01, 9.90158439e-01],
[7.56165266e-01, 6.22630298e-01],
[1.42213494e-01, 6.46644831e-01],
[8.81188691e-01, 2.12766096e-01],
[3.25797319e-01, 1.53578654e-01],
[8.53827596e-01, 1.81522354e-01],
[1.92537144e-01, 5.36438227e-02],
[9.14640367e-01, 4.07608002e-01],
[3.89448851e-01, 2.41537273e-01]],
[[6.37342215e-01, 9.23982203e-01],
[6.41843081e-02, 6.12837195e-01],
[6.30319059e-01, 1.30595891e-02],
[9.71985519e-01, 1.54995605e-01],
[3.19256812e-01, 3.10355037e-01],
[1.82669595e-01, 4.56996970e-02],
[3.48756790e-01, 7.32120216e-01],
[3.27858746e-01, 5.31942129e-01],
[4.21362728e-01, 4.56120372e-01],
[6.50329590e-01, 3.29893887e-01],
[8.86907160e-01, 5.64786082e-04],
[1.55090347e-01, 1.73131555e-01],
[2.37182751e-01, 6.04311109e-01],
[9.41228271e-01, 7.24738181e-01],
[9.72652256e-01, 5.85646212e-01],
[1.14914298e-01, 5.93839467e-01]],
[[4.63296860e-01, 1.51738942e-01],
[2.21416339e-01, 2.60902792e-01],
[3.24792117e-01, 3.69714648e-01],
[2.59633690e-01, 4.36835021e-01],
[5.99924982e-01, 3.28689098e-01],
[3.79893407e-02, 9.29345250e-01],
[8.26568842e-01, 6.63829386e-01],
[5.82045138e-01, 9.55973208e-01],
[1.22237757e-01, 8.00417244e-01],
[7.98558414e-01, 8.14821243e-01],
[3.88384312e-01, 5.15764594e-01],
[2.15329647e-01, 8.39083016e-01],
[4.31886494e-01, 6.97088480e-01],
[7.64276981e-02, 7.94957697e-01],
[4.71630961e-01, 2.17381448e-01],
[8.75746727e-01, 9.20892581e-02]],
[[6.28598750e-01, 4.42908078e-01],
[4.57955927e-01, 1.69334397e-01],
[1.89398229e-01, 9.02493834e-01],
[3.45932990e-01, 6.73218727e-01],
[9.37485218e-01, 8.08174908e-01],
[3.77100736e-01, 7.98058569e-01],
[8.48248124e-01, 9.09627140e-01],
[2.17172831e-01, 8.25318933e-01],
[7.96472371e-01, 6.59555614e-01],
[3.21068257e-01, 8.07177663e-01],
[5.66782296e-01, 2.78329779e-03],
[3.09204131e-01, 7.69137621e-01],
[5.90736687e-01, 5.86777210e-01],
[4.76175845e-01, 1.26155078e-01],
[6.04767382e-01, 8.93359601e-01],
[7.33457506e-01, 7.98267543e-01]],
[[7.11843193e-01, 2.18922988e-01],
[8.73326957e-01, 3.77091676e-01],
[6.37558937e-01, 5.61423361e-01],
[7.89014876e-01, 3.82421553e-01],
[2.62791842e-01, 8.27157319e-01],
[2.25997373e-01, 3.78121108e-01],
[6.35148585e-03, 2.86818426e-02],
[8.82164657e-01, 1.13523372e-01],
[4.22458947e-01, 7.61713803e-01],
[5.06661236e-01, 2.76505709e-01],
[6.63157880e-01, 5.78615725e-01],
[5.82072556e-01, 1.41458362e-01],
[2.84659505e-01, 1.23177595e-01],
[4.23501074e-01, 3.37697059e-01],
[6.88509107e-01, 3.41954023e-01],
[6.43684924e-01, 7.58561254e-01]]], dtype=np.float32)
fA_resampled_with_wfA = np.array([[0.5955824, 0.2880019, 0.16038245, 0.40116602, 0.2668193,
0.69355226, 0.5203295, 0.7064798, 0.86915886, 0.87054473,
0.56191665, 0.487664, 0.6692009, 0.4708008, 0.48304242,
0.7569619],
[0.5021016, 0.48644897, 0.9272157, 0.31147435, 0.28868878,
0.64157456, 0.56693333, 0.4299478, 0.6230224, 0.58709246,
0.35438746, 0.2934613, 0.15413266, 0.11979096, 0.21895668,
0.9903923],
[0.5172196, 0.39525065, 0.8324764, 0.52430147, 0.23934089,
0.2215783, 0.68488574, 0.17640461, 0.68380964, 0.7399209,
0.31939325, 0.30897757, 0.3437072, 0.44479185, 0.4677586,
0.9531579],
[0.8524847, 0.42021763, 0.55395806, 0.53297365, 0.6303569,
0.3847021, 0.33976397, 0.51301754, 0.7871348, 0.36536112,
0.39413205, 0.48131338, 0.8015958, 0.7655485, 0.6501977,
0.898676],
[0.3146358, 0.7032267, 0.91348064, 0.6404888, 0.20491728,
0.23548, 0.7057985, 0.7413577, 0.5766998, 0.44078743,
0.46026796, 0.277309, 0.5697512, 0.79817677, 0.77504313,
0.52295357],
[0.8385235, 0.3775946, 0.8031155, 0.5114433, 0.774182,
0.2686073, 0.53329843, 0.83293056, 0.55043936, 0.43754148,
0.3282535, 0.37438902, 0.7019417, 0.7768444, 0.50472665,
0.30633608],
[0.71152, 0.23234487, 0.23370115, 0.221789, 0.77669144,
0.30450255, 0.3268464, 0.428043, 0.48841617, 0.04249161,
0.72854245, 0.7572832, 0.6268189, 0.66162753, 0.71976495,
0.8867055],
[0.33080232, 0.46900806, 0.30654377, 0.29766658, 0.7251544,
0.43290007, 0.11234738, 0.15523197, 0.28908095, 0.567077,
0.7304188, 0.48957005, 0.5711849, 0.5141786, 0.8310203,
0.99739295],
[0.83689284, 0.53221494, 0.17035432, 0.45307878, 0.61882657,
0.39439988, 0.69089955, 0.54369915, 0.41272762, 0.2679783,
0.72878665, 0.46366385, 0.63176346, 0.5305136, 0.611072,
0.66578233],
[0.6596495, 0.42506874, 0.3636654, 0.3107705, 0.46304172,
0.34626368, 0.8701779, 0.8547681, 0.18735097, 0.17216304,
0.2861778, 0.38498342, 0.89229006, 0.7710998, 0.4754768,
0.32481453],
[0.55880475, 0.89318764, 0.84646475, 0.5899856, 0.52275634,
0.7137906, 0.80246633, 0.78829527, 0.8085702, 0.24715061,
0.1726345, 0.47627625, 0.5243012, 0.56935805, 0.37967983,
0.8031596],
[0.29254094, 0.4155465, 0.7394009, 0.6768603, 0.5754375,
0.7045029, 0.5608409, 0.64710784, 0.41949287, 0.2566696,
0.5296045, 0.50427806, 0.64671195, 0.62706965, 0.22287576,
0.5377517],
[0.7056605, 0.6005067, 0.5887317, 0.54002905, 0.5075451,
0.4720668, 0.5115893, 0.49127656, 0.5969236, 0.23519507,
0.7051317, 0.6926713, 0.65421164, 0.1909567, 0.47084355,
0.54384387],
[0.6809117, 0.6458232, 0.49363184, 0.5189719, 0.49732468,
0.73267865, 0.17620495, 0.578192, 0.8230078, 0.6796405,
0.49471018, 0.42958587, 0.6019871, 0.21630266, 0.44729304,
0.96698856],
[0.6374776, 0.35047472, 0.72895163, 0.4831055, 0.62518466,
0.52361923, 0.4421774, 0.44877836, 0.61566025, 0.5263409,
0.53275585, 0.55858, 0.5249848, 0.30071393, 0.21643728,
0.78237087],
[0.9334027, 0.92405903, 0.8281444, 0.7915541, 0.9448468,
0.7065285, 0.3741293, 0.52238005, 0.90358996, 0.5602862,
0.73473215, 0.6814896, 0.70088845, 0.6549278, 0.44208118,
0.92064154]], dtype=np.float32)
field_B_16x16 = np.array([[0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.,
0.],
[0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.,
0.],
[0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.,
0.],
[0.04999959, 0., -0.0249998, 0.0249998, 0.0249998,
0., 0., 0., 0., 0.,
0., 0., 0., 0., 0.,
0.],
[0., -0.02500001, -0.02500001, 0.02500001, 0.0625,
0.03749999, 0.0124999, 0.0124999, 0., 0.,
0., 0., 0., 0., 0.,
0.],
[0., -0.02500001, 0., 0.02500001, 0.03749999,
0.05000001, 0.01250002, 0.03749999, 0.04999998, 0.01249999,
0., 0., 0., 0., 0.,
0.],
[0., -0.02500001, 0., 0.02500001, 0.03749999,
0.05000001, 0.01250002, 0.04999998, 0.07499999, 0.03750002,
0.0250001, 0.01250008, 0., 0., 0.,
0.],
[-0.05000001, -0.02500001, 0.02500001, 0.03750002, 0.03749999,
0.03749999, 0.01250002, 0.04999998, 0.07499999, 0.03750002,
0.05000001, 0.06250018, 0.02500018, 0., 0.,
0.],
[-0.04999998, -0.02499999, 0.02499999, 0.06249999, 0.03749999,
0.01250002, 0.02500001, 0.04999998, 0.0625, 0.0625,
0.07500002, 0.0875003, 0.05000028, 0., 0.,
0.],
[-0.04999998, -0.02499999, 0.02499999, 0.0625, 0.03750001,
0.0125, 0.02499999, 0.04999998, 0.0625, 0.0625,
0.07500002, 0.10000002, 0.07499999, 0.03749964, 0.02499965,
0.],
[-0.04999998, 0., 0.02499999, 0.03750001, 0.05000001,
0.0125, 0.03749999, 0.04999998, 0.03749999, 0.07500002,
0.11250001, 0.125, 0.07499999, 0.04999974, 0.03749976,
0.],
[0., 0.025, 0.03749999, 0.0375, 0.03750001,
0.0125, 0.05, 0.07499999, 0.03749999, 0.05000001,
0.10000001, 0.125, 0.07499999, 0.07499999, 0.08749986,
0.04999971],
[0., 0.025, 0.0625, 0.0375, 0.0125,
0.0125, 0.05, 0.075, 0.03749999, 0.05000001,
0.10000001, 0.09999999, 0.07499999, 0.17499995, 0.13749996,
0.],
[0., 0.025, 0.0625, 0.0375, 0.0125,
0.025, 0.05, 0.0625, 0.0625, 0.075,
0.10000001, 0.075, 0.04999998, 0.22500005, 0.18750006,
0.],
[0.05, 0.025, 0.0375, 0.05, 0.0125,
0.0375, 0.05, 0.0375, 0.0625, 0.075,
0.09999999, 0.075, 0.075, 0.27500015, 0.21250015,
0.],
[0.05, 0.03749999, 0.0375, 0.0375, 0.0125,
0.0375, 0.05, 0.0375, 0.075, 0.1125,
0.125, 0.03749999, 0.03749999, 0.32500026, 0.26250026,
0.]], dtype=np.float32)
warp_field_B_16x16 = np.array([[[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[-4.9949216e-04, -1.4987986e-03],
[4.9955456e-04, -1.4987986e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[-7.4915669e-04, -2.9960717e-03],
[7.4955472e-04, -2.2481787e-03],
[0.0000000e+00, 0.0000000e+00],
[-7.4949116e-04, 1.2492406e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[-5.6137679e-07, -2.9970077e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[-9.9856197e-04, 1.9972520e-03],
[-1.2489881e-04, 8.7424158e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, -2.9970077e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[-9.9843740e-04, 1.9971896e-03],
[-1.2488315e-04, 9.9897222e-04],
[4.9924949e-04, -9.9848583e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[2.4990112e-04, -6.2476780e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[-4.9906247e-04, -2.4949429e-03],
[7.4866600e-04, -2.9966328e-03],
[0.0000000e+00, 0.0000000e+00],
[-3.7484805e-04, 6.2480359e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[4.9934327e-04, -8.7384146e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[9.9874986e-04, -1.4980978e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[-7.4929651e-04, -2.9971702e-03],
[7.4936647e-04, -2.9966091e-03],
[0.0000000e+00, 0.0000000e+00],
[-7.4931933e-04, 1.4987218e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[6.2404014e-04, -9.9848839e-04],
[7.4927509e-04, -7.4929313e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[-7.4929622e-04, -2.9966086e-03],
[7.4955396e-04, -2.2485764e-03],
[0.0000000e+00, 0.0000000e+00],
[-7.4925751e-04, 1.9974271e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[6.2410242e-04, -9.9850795e-04],
[7.4896973e-04, -8.7366370e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, 0.0000000e+00],
[-5.6137577e-07, -2.9970058e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[-9.9843880e-04, 1.9971926e-03],
[-1.2489851e-04, 8.7424071e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[7.4882543e-04, -8.7360881e-04],
[0.0000000e+00, 0.0000000e+00],
[-2.4943762e-03, 1.2478144e-03],
[-1.4980306e-03, 1.2484409e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[-6.2265696e-07, -2.4953163e-03],
[7.4866507e-04, -2.9966303e-03],
[0.0000000e+00, 0.0000000e+00],
[-3.7484756e-04, 6.2480249e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[4.9924967e-04, -9.9848595e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[9.9943625e-04, -1.7482606e-03],
[0.0000000e+00, 0.0000000e+00],
[-2.4930353e-03, 1.9946313e-03],
[-1.4961546e-03, 2.4927878e-03],
[0.0000000e+00, 0.0000000e+00],
[1.7488936e-03, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, -2.9975672e-03],
[7.4936653e-04, -2.9966310e-03],
[0.0000000e+00, 0.0000000e+00],
[-7.4932032e-04, 1.4987380e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[4.9934385e-04, -8.7384193e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[9.9912495e-04, -1.4984104e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[0.0000000e+00, -2.9970063e-03],
[7.4955437e-04, -2.2485987e-03],
[0.0000000e+00, 0.0000000e+00],
[-7.4925699e-04, 1.9974413e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[6.2403921e-04, -9.9849422e-04],
[7.4929697e-04, -7.4929895e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[1.4967235e-03, -2.9959765e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[-9.9843810e-04, 1.9971917e-03],
[-1.2489842e-04, 8.7424030e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[6.2410138e-04, -9.9851354e-04],
[7.4896845e-04, -8.7367010e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[2.7163187e-03, -7.4045185e-04],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00]],
[[1.4979842e-03, -2.9962552e-03],
[0.0000000e+00, 0.0000000e+00],
[-3.7819784e-04, 7.5642159e-04],
[-7.5791392e-04, 2.0210119e-03],
[-1.2634706e-04, 1.0107150e-03],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[0.0000000e+00, 0.0000000e+00],
[7.4872654e-04, -9.9820551e-04],
[0.0000000e+00, 0.0000000e+00],
[-2.5001576e-03, 5.0069159e-04],
[-7.5100840e-04, 5.0045690e-04],
[0.0000000e+00, 0.0000000e+00],
[3.1906958e-03, -9.8109827e-04],
[-5.1793009e-03, 2.5527072e-06],
[0.0000000e+00, 0.0000000e+00]]], dtype=np.float32)
fB_resampled_with_wfB_replacement = np.array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[4.99995910e-02, 0.00000000e+00, -2.49498617e-02,
2.49623302e-02, 2.49997992e-02, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[0.00000000e+00, -2.50000097e-02, -2.49999538e-02,
2.50280537e-02, 6.25000000e-02, 3.75343077e-02,
1.24998996e-02, 1.24998996e-02, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[0.00000000e+00, -2.50000097e-02, -7.49392129e-05,
2.50000097e-02, 3.74999903e-02, 4.99875247e-02,
1.25047034e-02, 3.74999903e-02, 4.99999784e-02,
1.24999899e-02, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[0.00000000e+00, -2.50000097e-02, 0.00000000e+00,
2.50000097e-02, 3.74999903e-02, 4.99625877e-02,
1.25047015e-02, 4.99999709e-02, 7.49999881e-02,
3.75000201e-02, 2.49813572e-02, 1.25000803e-02,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[-5.00000082e-02, -2.50124242e-02, 2.49344800e-02,
3.75000201e-02, 3.74999978e-02, 3.74999903e-02,
1.25000197e-02, 5.00124618e-02, 7.49999881e-02,
3.75000201e-02, 4.99750040e-02, 6.25001788e-02,
2.50001792e-02, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[-4.99999784e-02, -2.50187218e-02, 2.50280350e-02,
6.24999888e-02, 3.75187248e-02, 1.25000197e-02,
2.50000097e-02, 4.99999784e-02, 6.25000000e-02,
6.24828376e-02, 7.49906525e-02, 8.75002965e-02,
5.00002801e-02, 0.00000000e+00, 0.00000000e+00,
0.00000000e+00],
[-4.99999784e-02, -2.50187218e-02, 2.50280984e-02,
6.25000000e-02, 3.75436507e-02, 1.25000002e-02,
2.49999892e-02, 4.99999784e-02, 6.25000000e-02,
6.25078008e-02, 7.50187337e-02, 1.00000016e-01,
7.49999881e-02, 3.74996401e-02, 2.49996502e-02,
0.00000000e+00],
[-4.99999784e-02, -7.49531391e-05, 2.49999892e-02,
3.75000089e-02, 4.99625877e-02, 1.25046829e-02,
3.74999903e-02, 4.99999784e-02, 3.74999903e-02,
7.50171617e-02, 1.12500012e-01, 1.24968782e-01,
7.50748888e-02, 4.99997400e-02, 3.74997593e-02,
0.00000000e+00],
[-1.24765691e-04, 2.49344707e-02, 3.74999903e-02,
3.75000089e-02, 3.75000089e-02, 1.25000002e-02,
4.99999933e-02, 7.49999881e-02, 3.74999903e-02,
5.00936657e-02, 1.00000009e-01, 1.24887936e-01,
7.50747025e-02, 7.49999881e-02, 8.74342695e-02,
4.99997102e-02],
[0.00000000e+00, 2.50280462e-02, 6.25000000e-02,
3.75187360e-02, 1.25000002e-02, 1.25000002e-02,
5.00124842e-02, 7.50000030e-02, 3.74999903e-02,
5.00499643e-02, 1.00000009e-01, 9.99999866e-02,
7.49999881e-02, 1.74999952e-01, 1.37499958e-01,
0.00000000e+00],
[0.00000000e+00, 2.50281096e-02, 6.25000000e-02,
3.75436433e-02, 1.25000002e-02, 2.50000004e-02,
5.00000007e-02, 6.25000000e-02, 6.24828376e-02,
7.50000179e-02, 1.00000009e-01, 7.50000030e-02,
4.99999784e-02, 2.25000054e-01, 1.87500060e-01,
0.00000000e+00],
[4.98130098e-02, 2.50000004e-02, 3.75000015e-02,
4.99625802e-02, 1.25046829e-02, 3.75000015e-02,
5.00000007e-02, 3.75000015e-02, 6.25078008e-02,
7.50187263e-02, 9.99999866e-02, 7.50000030e-02,
7.50000030e-02, 2.74793416e-01, 2.12500155e-01,
0.00000000e+00],
[4.99812216e-02, 3.74999903e-02, 3.74716371e-02,
3.74242142e-02, 1.24905221e-02, 3.75000015e-02,
5.00000007e-02, 3.75000015e-02, 7.50155821e-02,
1.12499997e-01, 1.24906175e-01, 3.75469029e-02,
3.74999903e-02, 3.24751794e-01, 2.62823284e-01,
0.00000000e+00]], dtype=np.float32)
iteration50_warp_field = np.array([[[3.99222947e-04, -2.58702622e-03],
[3.99222947e-04, -2.58702622e-03],
[3.99222947e-04, -2.58702622e-03],
[3.99222947e-04, -2.58702622e-03],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[3.99222947e-04, -2.58702622e-03],
[3.99222947e-04, -2.58702622e-03],
[3.99222947e-04, -2.58702622e-03],
[3.99222947e-04, -2.58702622e-03],
[1.00403367e-05, -5.74650439e-05],
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[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[3.92420799e-04, -2.57001258e-03],
[3.92420799e-04, -2.57001258e-03],
[4.00435471e-04, -2.68424172e-02],
[4.00435471e-04, -2.68424172e-02],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
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[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[3.18970007e-04, -2.49644229e-03],
[3.92419315e-04, -2.57996330e-03],
[-1.11224158e-02, -6.20664619e-02],
[1.19756768e-02, -6.20293207e-02],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.00403367e-05, -5.74650439e-05],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[2.05605058e-04, -3.00833564e-02],
[9.58597870e-04, -2.82838326e-02],
[-1.12477085e-02, -1.73112378e-01],
[1.98581740e-02, -1.60253271e-01],
[-1.86956730e-02, 4.07836027e-02],
[-3.85573097e-02, 7.41888955e-02],
[-6.34391466e-03, 1.71390083e-02],
[-6.26430847e-03, 1.68382768e-02],
[2.46718642e-03, -3.80784669e-03],
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[2.47937790e-03, -3.82492505e-03],
[2.47937790e-03, -3.82492505e-03],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[2.29688871e-04, -2.82336213e-02],
[9.79846227e-04, -2.82418262e-02],
[1.97803252e-03, -1.75259486e-01],
[2.70895800e-03, -1.09385274e-01],
[-2.03181673e-02, 4.17447053e-02],
[-4.26606312e-02, 8.78511369e-02],
[-9.38997045e-03, 3.75849605e-02],
[-5.86405070e-03, 1.60907358e-02],
[2.38872133e-03, -3.72926029e-03],
[2.46718642e-03, -3.80784669e-03],
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[2.47937790e-03, -3.82492505e-03],
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[1.69374493e-06, -2.47195635e-06],
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[1.69374493e-06, -2.47195635e-06]],
[[-2.22062180e-03, -4.11272161e-02],
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[[1.07391621e-04, -4.13723849e-02],
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[-2.47842167e-02, 5.19453026e-02],
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[-7.13494548e-04, -8.22823378e-04],
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[1.69374493e-06, -2.47195635e-06],
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[1.69374493e-06, -2.47195635e-06],
[1.69374493e-06, -2.47195635e-06]],
[[-5.84323099e-03, -6.98758289e-02],
[-2.81037055e-02, -1.47442862e-01],
[3.97488177e-02, -1.47041276e-01],
[1.75504629e-02, -7.44238943e-02],
[-3.03831026e-02, 7.86221474e-02],
[-1.34612946e-02, 4.11224030e-02],
[-3.06080841e-03, 7.63494847e-03],
[-2.83324020e-03, 7.74630345e-03],
[1.33223990e-02, -1.88627522e-02],
[2.78583616e-02, -4.21728715e-02],
[3.59412953e-02, -3.48719805e-02],
[1.71283428e-02, -1.63356271e-02],
[-1.57904357e-03, 1.27334276e-03],
[-1.71386672e-03, 1.35709182e-03],
[-2.07822863e-03, 1.72118505e-03],
[-2.07822863e-03, 1.72118505e-03]],
[[-5.48579264e-03, -6.91609457e-02],
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[-1.53344544e-03, 1.25418277e-03],
[-1.68464123e-03, 1.34524982e-03],
[-2.05182470e-03, 1.72105886e-03],
[-2.07822863e-03, 1.72118505e-03]],
[[3.37949116e-03, -9.94223058e-02],
[-4.42666840e-03, -1.74631715e-01],
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[-5.13831992e-03, -1.94475949e-02],
[-3.31670828e-02, 8.02597627e-02],
[-1.45977950e-02, 5.51379658e-02],
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[-2.49751005e-02, 3.02204248e-02],
[8.79670959e-03, 1.64702316e-04],
[8.79359152e-03, 1.66778453e-04]],
[[-3.97225423e-03, -1.48297474e-01],
[1.11059612e-02, -1.74503848e-01],
[-5.03498223e-03, -1.94373783e-02],
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[-1.04293674e-02, 3.29769179e-02],
[-1.14435814e-02, 3.32002230e-02],
[1.46774156e-02, -2.40484681e-02],
[2.84965825e-03, -5.73492958e-04],
[1.79093201e-02, -2.60388479e-02],
[4.23169918e-02, -6.69874400e-02],
[-3.40559036e-02, 2.31390074e-02],
[-8.59565660e-02, 6.61292598e-02],
[-5.55971600e-02, 7.87704960e-02],
[-2.39806697e-02, 2.88353637e-02],
[5.15249185e-02, 1.68791274e-04],
[8.79359152e-03, 1.66778453e-04]],
[[2.07110979e-02, -1.90376297e-01],
[3.57106254e-02, -1.86779365e-01],
[-1.42847998e-02, 2.24932358e-02],
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[-2.09210324e-03, 3.90022714e-03],
[-2.08567409e-03, 3.84850265e-03],
[1.63593423e-02, -2.44683251e-02],
[4.34590876e-03, -3.67905805e-03],
[2.40620058e-02, -3.27214859e-02],
[4.78163064e-02, -6.92240968e-02],
[1.85323076e-03, -2.10449169e-03],
[1.95215922e-03, -2.17831973e-03],
[-3.44321137e-07, -5.02412149e-06],
[-6.12539111e-07, -5.58470492e-06],
[1.01097494e-05, -1.25461702e-05],
[9.27381279e-06, -1.26981713e-05]],
[[2.07117200e-02, -1.87897414e-01],
[3.59370001e-02, -1.75080836e-01],
[-1.43139223e-02, 2.25309152e-02],
[-3.33853438e-02, 6.99410886e-02],
[-2.10455945e-03, 4.03894065e-03],
[-2.02721148e-03, 3.84954480e-03],
[4.48999600e-03, -3.89896100e-03],
[4.42350423e-03, -3.67682613e-03],
[3.70514467e-02, -5.51744848e-02],
[4.11001705e-02, -5.23496047e-02],
[1.96096231e-03, -2.18541804e-03],
[2.21832609e-03, -2.34443462e-03],
[3.38694868e-08, -5.56324676e-06],
[-1.00414343e-06, -5.67321285e-06],
[9.27381279e-06, -1.26981713e-05],
[9.27381279e-06, -1.26981713e-05]],
[[5.73590808e-02, -1.34265676e-01],
[2.82186177e-02, -6.81553334e-02],
[-3.40881199e-02, 7.32444376e-02],
[-5.44822849e-02, 1.15801059e-01],
[-3.16845328e-02, 1.23083346e-01],
[-2.59597097e-02, 1.00893430e-01],
[-1.35930367e-02, 3.17709073e-02],
[-1.44289462e-02, 3.14591452e-02],
[3.68927978e-02, -4.60180454e-02],
[3.94279063e-02, -4.34616208e-02],
[-3.65402773e-02, 1.72075983e-02],
[-3.59655879e-02, 1.60879418e-02],
[1.55280437e-02, -6.43344456e-03],
[4.52608950e-02, -1.66620389e-02],
[-6.63442211e-03, 5.49720862e-05],
[-1.68603882e-02, 9.76005831e-05]],
[[6.06149137e-02, -1.34554878e-01],
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[-1.68603882e-02, 9.76005831e-05]]], dtype=np.float32)
| 57.478495 | 96 | 0.431983 | 10,548 | 96,219 | 3.937808 | 0.228764 | 0.030118 | 0.101165 | 0.097361 | 0.41446 | 0.386917 | 0.374374 | 0.3457 | 0.326632 | 0.321408 | 0 | 0.678168 | 0.423503 | 96,219 | 1,673 | 97 | 57.512851 | 0.070633 | 0.011318 | 0 | 0.346887 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.001271 | 0 | 0.001271 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
a01407a36ac8a613a5ae30ceaa43cfa16d7c2bcc | 395 | py | Python | survivor_pool/models/pick_dict.py | bitedgeco/survivor-pool | ab767fc36a0509614f7edade5101389ed97fe251 | [
"MIT"
] | 2 | 2016-08-24T22:13:54.000Z | 2016-11-01T09:55:24.000Z | survivor_pool/models/pick_dict.py | bitedgecom/survivor-pool | ab767fc36a0509614f7edade5101389ed97fe251 | [
"MIT"
] | 41 | 2016-09-02T19:40:32.000Z | 2016-09-09T18:21:28.000Z | survivor_pool/models/pick_dict.py | bitedgeco/survivor-pool | ab767fc36a0509614f7edade5101389ed97fe251 | [
"MIT"
] | 1 | 2021-08-05T15:24:21.000Z | 2021-08-05T15:24:21.000Z | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
INITIAL_PICKS = [
{"user_id": 1, "event_id": 1, "team": "home", "week": 1},
{"user_id": 2, "event_id": 7, "team": "home", "week": 1},
{"user_id": 3, "event_id": 8, "team": "away", "week": 1},
{"user_id": 4, "event_id": 6, "team": "away", "week": 1},
{"user_id": 5, "event_id": 3, "team": "home", "week": 1},
]
| 35.909091 | 61 | 0.529114 | 60 | 395 | 3.216667 | 0.4 | 0.15544 | 0.186529 | 0.227979 | 0.393782 | 0.393782 | 0 | 0 | 0 | 0 | 0 | 0.049844 | 0.187342 | 395 | 10 | 62 | 39.5 | 0.551402 | 0.053165 | 0 | 0 | 0 | 0 | 0.362903 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.125 | 0 | 0.125 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
a015f617e5b4506acb8e239492c71152820e15eb | 243 | py | Python | output/models/nist_data/list_pkg/short/schema_instance/nistschema_sv_iv_list_short_min_length_5_xsd/__init__.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | 1 | 2021-08-14T17:59:21.000Z | 2021-08-14T17:59:21.000Z | output/models/nist_data/list_pkg/short/schema_instance/nistschema_sv_iv_list_short_min_length_5_xsd/__init__.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | 4 | 2020-02-12T21:30:44.000Z | 2020-04-15T20:06:46.000Z | output/models/nist_data/list_pkg/short/schema_instance/nistschema_sv_iv_list_short_min_length_5_xsd/__init__.py | tefra/xsdata-w3c-tests | b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f | [
"MIT"
] | null | null | null | from output.models.nist_data.list_pkg.short.schema_instance.nistschema_sv_iv_list_short_min_length_5_xsd.nistschema_sv_iv_list_short_min_length_5 import NistschemaSvIvListShortMinLength5
__all__ = [
"NistschemaSvIvListShortMinLength5",
]
| 40.5 | 186 | 0.888889 | 31 | 243 | 6.258065 | 0.645161 | 0.123711 | 0.14433 | 0.185567 | 0.340206 | 0.340206 | 0.340206 | 0.340206 | 0 | 0 | 0 | 0.017467 | 0.057613 | 243 | 5 | 187 | 48.6 | 0.829694 | 0 | 0 | 0 | 0 | 0 | 0.135802 | 0.135802 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4e42a0ab5f6807fe1b34e903db4ada9124652933 | 888 | py | Python | tests/test_cases.py | kpdemetriou/spectral-aead | 08c4705af74223832afe947ba9e20bf5bb9d6487 | [
"BSD-3-Clause"
] | null | null | null | tests/test_cases.py | kpdemetriou/spectral-aead | 08c4705af74223832afe947ba9e20bf5bb9d6487 | [
"BSD-3-Clause"
] | null | null | null | tests/test_cases.py | kpdemetriou/spectral-aead | 08c4705af74223832afe947ba9e20bf5bb9d6487 | [
"BSD-3-Clause"
] | 1 | 2018-06-26T05:57:06.000Z | 2018-06-26T05:57:06.000Z | import binascii
import spectral
def test_encryption(cases):
for key, nonce, plaintext, associated, ciphertext, mac in cases:
key, nonce, plaintext, associated, ciphertext, mac = map(
binascii.unhexlify, (key, nonce, plaintext, associated, ciphertext, mac)
)
computed_ciphertext, computed_mac = spectral.encrypt_disjoint(key, nonce, plaintext, associated)
assert computed_ciphertext == ciphertext
assert computed_mac == mac
def test_decryption(cases):
for key, nonce, plaintext, associated, ciphertext, mac in cases:
key, nonce, plaintext, associated, ciphertext, mac = map(
binascii.unhexlify, (key, nonce, plaintext, associated, ciphertext, mac)
)
computed_plaintext = spectral.decrypt_disjoint(key, nonce, ciphertext, mac, associated)
assert computed_plaintext == plaintext
| 34.153846 | 104 | 0.695946 | 93 | 888 | 6.537634 | 0.247312 | 0.105263 | 0.195724 | 0.310855 | 0.536184 | 0.536184 | 0.536184 | 0.536184 | 0.536184 | 0.536184 | 0 | 0 | 0.220721 | 888 | 25 | 105 | 35.52 | 0.878613 | 0 | 0 | 0.352941 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.176471 | 1 | 0.117647 | false | 0 | 0.117647 | 0 | 0.235294 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4e48136f139e9351e513296e8093ce84bfa4f170 | 1,377 | py | Python | app/realoem.py | ballon3/electricdisc | c18f463240d9b05d77ce1c00545810ca8bac65a7 | [
"MIT"
] | null | null | null | app/realoem.py | ballon3/electricdisc | c18f463240d9b05d77ce1c00545810ca8bac65a7 | [
"MIT"
] | 5 | 2020-05-26T08:19:15.000Z | 2020-05-26T08:20:15.000Z | app/realoem.py | ballon3/electricdisc | c18f463240d9b05d77ce1c00545810ca8bac65a7 | [
"MIT"
] | null | null | null | import httpx
import requests
from bs4 import BeautifulSoup as bso
class BMW:
BASE_URL = 'https://www.realoem.com/bmw/'
LANGUAGE = 'enUS'
URL = f"{BASE_URL}{LANGUAGE}"
'https://www.realoem.com/bmw/enUS/partgrp?id=0573-USA-12-1991-K569-BMW-K_75_RT_0565,0573_&mg=46'
'https://www.realoem.com/bmw/enUS/showparts?id=0573-USA-12-1991-K569-BMW-K_75_RT_0565,0573_&diagId=34_1906'
'https://www.realoem.com/bmw/enUS/showparts?id=0573-USA-12-1991-K569-BMW-K_75_RT_0565,0573_&diagId=34_1905'
def get_main_group(id):
params = {'id':id}
r = httpx.get(f'{URL}/partgrp', params=params)
print(r)
print(r.url)
return r.text
def get_sub_group(url, filter):
pass
def get_part(diagId):
pass
def extract_link(soupy):
soup = bso(soupy, "html.parser")
for links in soup.find_all("a"):
href = links.
print(href,title)
def test_main_group(id):
BASE_URL = 'https://www.realoem.com/bmw/'
LANGUAGE = 'enUS'
URL = f"{BASE_URL}{LANGUAGE}"
params = {'id':id}
r = httpx.get(f'{URL}/partgrp', params=params)
soup = bso(r.text, "html.parser")
for links in soup.find_all("div", {"class": "mg-thumb"}):
href = links.
print(href,title)
K75 = '0573-USA-12-1991-K569-BMW-K_75_RT_0565%2C0573_'
test_main_group(K75) | 27 | 111 | 0.625999 | 215 | 1,377 | 3.851163 | 0.32093 | 0.048309 | 0.09058 | 0.108696 | 0.667874 | 0.612319 | 0.582126 | 0.582126 | 0.507246 | 0.507246 | 0 | 0.103704 | 0.215686 | 1,377 | 51 | 112 | 27 | 0.662963 | 0 | 0 | 0.432432 | 0 | 0.081081 | 0.379536 | 0.033382 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0.054054 | 0.081081 | null | null | 0.108108 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
4e51a3c4018f1806f6ecbdac62369dc0a50a6f19 | 634 | py | Python | shreya/reference/cognitive_engine_connection.py | FYQ0919/Your_First_Decentralized_Application_Python | 21afb71a79c798c02a972eec6d54b4a17526358b | [
"MIT"
] | 2 | 2020-10-12T06:17:23.000Z | 2020-10-14T18:12:37.000Z | shreya/reference/cognitive_engine_connection.py | FYQ0919/Your_First_Decentralized_Application_Python | 21afb71a79c798c02a972eec6d54b4a17526358b | [
"MIT"
] | null | null | null | shreya/reference/cognitive_engine_connection.py | FYQ0919/Your_First_Decentralized_Application_Python | 21afb71a79c798c02a972eec6d54b4a17526358b | [
"MIT"
] | null | null | null | from flask import Blueprint, request
job_execution = Blueprint('job_execution')
@job_execution.route('/api/request_state_from_blockchain', methods=['POST'])
def request_state_from_blockchain():
'''
Checks if all executors involved have reported their results here.
Updates exec_step_status when the exec has reported results.
Updates state buffer with states and flag it as full when all related exec has reported.
:return:
'''
import random
from flask import jsonify
# unpack json data
data = request.get_json()
res = jsonify({"status": random.choice(["pass", "fail"])})
return res | 31.7 | 92 | 0.72082 | 84 | 634 | 5.297619 | 0.607143 | 0.080899 | 0.067416 | 0.116854 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.189274 | 634 | 20 | 93 | 31.7 | 0.865759 | 0.383281 | 0 | 0 | 0 | 0 | 0.178571 | 0.093407 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111111 | false | 0.111111 | 0.333333 | 0 | 0.555556 | 0.222222 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 2 |
4e564068e102a1b9819a2c1db20834ef7f028615 | 644 | py | Python | features/kill.py | magnusstubman/mal00 | e99cad410657bf0452cae02d81d89c211732a789 | [
"MIT"
] | 3 | 2021-03-29T13:28:31.000Z | 2021-10-12T09:33:14.000Z | features/kill.py | magnusstubman/mal00 | e99cad410657bf0452cae02d81d89c211732a789 | [
"MIT"
] | null | null | null | features/kill.py | magnusstubman/mal00 | e99cad410657bf0452cae02d81d89c211732a789 | [
"MIT"
] | 1 | 2021-04-05T10:19:34.000Z | 2021-04-05T10:19:34.000Z | from features import addFeature
import messages
from messages import OutgoingMessage
class KillCommand:
command = 'kill'
def run(arguments, implant):
if not implant:
print('use implant first!')
else:
message = OutgoingMessage(KillCommand.command, None)
implant.queueOutgoingMessage(message)
def help():
return 'Evaluate expressions in the implant\'s native language runtime. Usage: eval Msgbox "U HACKED!"'
def incoming(data, implant):
print('Received unencodable kill data from ' + implant.name + ': ' + data.hex())
def help():
return 'kills current implant'
addFeature(KillCommand)
| 23.851852 | 107 | 0.706522 | 73 | 644 | 6.232877 | 0.630137 | 0.079121 | 0.057143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.200311 | 644 | 26 | 108 | 24.769231 | 0.883495 | 0 | 0 | 0.111111 | 0 | 0 | 0.195652 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0 | 0.166667 | 0.111111 | 0.611111 | 0.111111 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 2 |
4e68d62d90de10a6efb1f72d67fe2a6de143a2f4 | 1,712 | py | Python | core/argo/core/network/s-vae/hyperspherical_vae/ops/ive.py | szokejokepu/natural-rws | bb1ad4ca3ec714e6bf071d2136593dc853492b68 | [
"MIT"
] | 164 | 2018-06-29T09:19:38.000Z | 2022-02-12T01:39:58.000Z | hyperspherical_vae_tensorflow/ops/ive.py | pimdh/svae-temp | 49d3974e66abc761312432f28ae57fe714d17451 | [
"MIT"
] | 2 | 2018-12-24T09:41:31.000Z | 2020-02-18T14:14:25.000Z | hyperspherical_vae_tensorflow/ops/ive.py | pimdh/svae-temp | 49d3974e66abc761312432f28ae57fe714d17451 | [
"MIT"
] | 27 | 2018-08-01T17:41:28.000Z | 2021-12-21T22:39:05.000Z | # Copyright 2016 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""The exponentially scaled modified Bessel function of the first kind."""
import numpy as np
import scipy.special
from tensorflow.python.ops import script_ops
from tensorflow.python.ops import array_ops
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops.custom_gradient import custom_gradient
@custom_gradient
def ive(v, z):
"""Exponentially scaled modified Bessel function of the first kind."""
output = array_ops.reshape(script_ops.py_func(
lambda v, z: np.select(condlist=[v == 0, v == 1],
choicelist=[scipy.special.i0e(z, dtype=z.dtype),
scipy.special.i1e(z, dtype=z.dtype)],
default=scipy.special.ive(v, z, dtype=z.dtype)), [v, z], z.dtype),
ops.convert_to_tensor(array_ops.shape(z), dtype=dtypes.int32))
def grad(dy):
return None, dy * (ive(v - 1, z) - ive(v, z) * (v + z) / z)
return output, grad
| 41.756098 | 97 | 0.65771 | 237 | 1,712 | 4.704641 | 0.468354 | 0.043049 | 0.089686 | 0.061883 | 0.239462 | 0.098655 | 0.098655 | 0.098655 | 0.098655 | 0 | 0 | 0.011021 | 0.205023 | 1,712 | 40 | 98 | 42.8 | 0.808229 | 0.464369 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111111 | false | 0 | 0.388889 | 0.055556 | 0.611111 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
4e9280c991c70e6fc2632ffb753bc8caa29142f8 | 407 | py | Python | manager/context_manager.py | chm10/MyShortcuts | db8185c68c069a344188b1aa9fea3d8f72ff862b | [
"BSD-2-Clause"
] | 1 | 2019-08-31T00:49:29.000Z | 2019-08-31T00:49:29.000Z | manager/context_manager.py | chm10/MyShortcuts | db8185c68c069a344188b1aa9fea3d8f72ff862b | [
"BSD-2-Clause"
] | null | null | null | manager/context_manager.py | chm10/MyShortcuts | db8185c68c069a344188b1aa9fea3d8f72ff862b | [
"BSD-2-Clause"
] | null | null | null | #!/us/bin/env python3
import time
class timer (object):
def __enter__(self):
self.start = time.time()
print('Timer starts at: %s' % self.start)
return self
def __exit__(self, type, value, traceback):
self.stop = time.time()
print('Timer stops at: %s' % self.stop)
print('Elapsed: %s' % (self.stop - self.start))
return self
| 25.4375 | 56 | 0.55774 | 51 | 407 | 4.294118 | 0.490196 | 0.123288 | 0.118721 | 0.164384 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003546 | 0.307125 | 407 | 15 | 57 | 27.133333 | 0.77305 | 0.04914 | 0 | 0.181818 | 0 | 0 | 0.12938 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.181818 | false | 0 | 0.090909 | 0 | 0.545455 | 0.272727 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
4ea5e43f900c21881240337948ce7431cfe3bd18 | 1,326 | py | Python | main.py | majickdave/musicmind_collector | 1669fb9e33a11db982ff331e542eef887a5cf9b7 | [
"MIT"
] | null | null | null | main.py | majickdave/musicmind_collector | 1669fb9e33a11db982ff331e542eef887a5cf9b7 | [
"MIT"
] | null | null | null | main.py | majickdave/musicmind_collector | 1669fb9e33a11db982ff331e542eef887a5cf9b7 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Sun Feb 05 20:42:19 2017
@author: david
"""
import audio_features0
import string
import json
import time
#Enter Artist Track and confirm lyrics and analysis
a = raw_input('Artist: ') ; b = raw_input('Track: ')
# a = 'london grammar'; b = 'oh woman'
if __name__=='__main__':
time.clock()
g = audio_features0.dumper_track(artist=a, track=b)
# if g:
# u_title = g['track']
# u_artist = g['artist']
# u_album = g['album']
# u_featured_artists = g['featured_artists']
# #import pdb; pdb.set_trace()
# print u_artist+' '+','.join(u_featured_artists)+' sing '+u_title
# lyrics = audio_features2.runner(artist=u_artist, track=u_title)
# if lyrics:
# print(lyrics[-1])
# for x in u_title:
# if x in '*()"|?\/:<>':
# title = string.replace(u_title, x, '')
# else:
# print "No Spotify Response"
# json = json
# file_name = u_artist+'-'+u_album+'-'+u_title
# with open(file_name+'.json', 'w') as fp:
# fp.write((json.dumps({ u'lyrics':lyrics, u'features':g}, indent=4)))
print 'These lyrics clocked ', time.clock(),
#
# | 26.52 | 79 | 0.525641 | 164 | 1,326 | 4.042683 | 0.463415 | 0.054299 | 0.036199 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.019978 | 0.320513 | 1,326 | 50 | 80 | 26.52 | 0.715871 | 0.574661 | 0 | 0 | 0 | 0 | 0.105263 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.444444 | null | null | 0.111111 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
4ecb24b4f01fed8915d22f24fbf14981ef6c859e | 407 | py | Python | django_extras/templatetags/humanize_extras.py | gem/django-extras | d692e87891fe4cb79726437d3185628c1a9e2f33 | [
"BSD-3-Clause"
] | 18 | 2015-08-22T08:59:48.000Z | 2020-10-08T17:15:23.000Z | django_extras/templatetags/humanize_extras.py | gem/django-extras | d692e87891fe4cb79726437d3185628c1a9e2f33 | [
"BSD-3-Clause"
] | 4 | 2018-01-06T23:19:20.000Z | 2020-10-09T02:22:45.000Z | django_extras/templatetags/humanize_extras.py | gem/django-extras | d692e87891fe4cb79726437d3185628c1a9e2f33 | [
"BSD-3-Clause"
] | 9 | 2015-06-15T17:28:03.000Z | 2021-08-29T07:26:50.000Z | from django import template
from django_extras.utils import humanize
register = template.Library()
@register.filter(is_safe=True)
def describe_seconds(value):
"""
Convert a seconds value into a human readable (ie week, day, hour) value.
:param value: integer value of the number of seconds.
:return: a string with the humanized value.
"""
return humanize.describe_seconds(value)
| 25.4375 | 77 | 0.734644 | 56 | 407 | 5.267857 | 0.625 | 0.122034 | 0.135593 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.184275 | 407 | 15 | 78 | 27.133333 | 0.888554 | 0.420147 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.333333 | 0 | 0.666667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
4ed32f803d69eba7c1f4fb283c955d8c4c02f0f6 | 2,585 | py | Python | src/docs.py | yaroslavNikolaev/A.R.M.O.R. | 443b50ad39b7ada7562db62c36824c7c4edb842b | [
"MIT"
] | 1 | 2020-03-29T20:53:28.000Z | 2020-03-29T20:53:28.000Z | src/docs.py | yaroslavNikolaev/A.R.M.O.R. | 443b50ad39b7ada7562db62c36824c7c4edb842b | [
"MIT"
] | null | null | null | src/docs.py | yaroslavNikolaev/A.R.M.O.R. | 443b50ad39b7ada7562db62c36824c7c4edb842b | [
"MIT"
] | null | null | null | from utils.configuration import Configuration
from scanners import CollectorFactory
INTRO = '''
## A.R.M.O.R. - Altered-Reality Monitoring and Operational Response
### Mission
Detect difference between current version of installed software and the newest one.
ARMOR is designed to help developers and devops to keep application up to date.
ARMOR can support any kind of storage in order to persist state of cluster
'''
STRUCTURE = '''
### Repository structure:
armor.py - entry endpoint.
scanners.py - contains classes which relay on reflection to collect set of
mutator.py - simple application to annotate your k8 cluster and check how A.R.M.O.R works.
package utils - contains main part of armor framework
- version.py - script with versions classes, which are used to store application version in A.R.O.R. format.
- collectors.py - contains common classes of collectors. Main responsibility to collect Application Versions.
- configuration.py - contains A.R.M.O.R configuration
- verifiers.py - contains common classes of verifiers. Main responsibility to highlight that how severe version lag.
- producer.py - contains common classes of producers. Main responsibility to provide prometheus client output.
packages gcp,az,party3rd,aws - contains collectors for external sources.
folder armor-io - contains helm chart for armor
'''
HOWTO = '''
### How to start to work with A.R.M.O.R
1. helm repository is hosted here: https://yaroslavnikolaev.github.io/A.R.M.O.R./
2. Deploy to your central cluster or to
'''
COLLECTORS = '''
### ARMOR supports following collectors:
<table style="width:100%"> <tr> <th>Application</th> <th>Armor annotation key</th> <th>Description</th> </tr>
'''
STORAGES = '''\n### ARMOR supports following storages:
- Prometheus \n'''
if __name__ == '__main__':
'''Automatically generate Readme.md'''
configuration = Configuration()
factory = CollectorFactory(configuration)
with open("./docs/README.md", "w") as readme:
readme.write(INTRO)
readme.write(STRUCTURE)
readme.write(HOWTO)
readme.write(COLLECTORS)
# todo add description to collectors and storages use __doc__
description = ""
for key in sorted(factory.collectors.keys()):
application = key.split(".")[-1]
readme.write(f'''<tr> <th>{application}</th> <th>armor.io/{key}</th> <th>{description}</th> </tr>\n''')
readme.write("""</table> \n""")
readme.write(STORAGES)
| 43.083333 | 125 | 0.68472 | 338 | 2,585 | 5.201183 | 0.455621 | 0.0438 | 0.008532 | 0.011377 | 0.109215 | 0.052332 | 0 | 0 | 0 | 0 | 0 | 0.003899 | 0.20619 | 2,585 | 59 | 126 | 43.813559 | 0.852827 | 0.022824 | 0 | 0.083333 | 0 | 0.125 | 0.732797 | 0.026962 | 0 | 0 | 0 | 0.016949 | 0 | 1 | 0 | false | 0 | 0.041667 | 0 | 0.041667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4ed581847003d9bff39a3e67099f5d2f0b035f9f | 507 | py | Python | CS2420/Notes/Feb/2-12.py | Davidjbennett/DavidBennett.github.io | 09a2652b7ace8741bf23c6432abd58ee790b9f0c | [
"MIT"
] | 3 | 2021-05-18T16:17:29.000Z | 2022-01-20T15:46:59.000Z | CS2420/Notes/Feb/2-12.py | Davidjbennett/DavidBennett | 09a2652b7ace8741bf23c6432abd58ee790b9f0c | [
"MIT"
] | null | null | null | CS2420/Notes/Feb/2-12.py | Davidjbennett/DavidBennett | 09a2652b7ace8741bf23c6432abd58ee790b9f0c | [
"MIT"
] | null | null | null |
#! Unordered List Abstract Data type (UML Diagram)
# add(item) adds new item to list
# remove(item) removes item from the list
# search(item) searchs for item in the list. returns true of false
# isEmpty() test if list is empty or not
# length() returns number of items in the list
# append() adds item to end of list
# index(item) returns postions of item in the list
# insert(pos, item) inserts item at pos in list
# pop() removes and returns last item in list
# pop(pos) removes and returns item at pos
| 39 | 66 | 0.739645 | 90 | 507 | 4.166667 | 0.5 | 0.074667 | 0.072 | 0.069333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.189349 | 507 | 12 | 67 | 42.25 | 0.912409 | 0.954635 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
4ed5abff6180a9474f661134ca38c21f4edc15d0 | 3,841 | py | Python | ecl/tests/unit/network/v2/test_quota.py | keiichi-hikita/eclsdk | c43afb982fd54eb1875cdc22d46044644d804c4a | [
"Apache-2.0"
] | 5 | 2017-04-07T06:23:04.000Z | 2019-11-19T00:52:34.000Z | ecl/tests/unit/network/v2/test_quota.py | keiichi-hikita/eclsdk | c43afb982fd54eb1875cdc22d46044644d804c4a | [
"Apache-2.0"
] | 16 | 2018-09-12T11:14:40.000Z | 2021-04-19T09:02:44.000Z | ecl/tests/unit/network/v2/test_quota.py | keiichi-hikita/eclsdk | c43afb982fd54eb1875cdc22d46044644d804c4a | [
"Apache-2.0"
] | 14 | 2017-05-11T14:26:26.000Z | 2021-07-14T14:00:06.000Z | # Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations
# under the License.
import testtools
from ecl.network.v2 import quota
IDENTIFIER = 'IDENTIFIER'
EXAMPLE = {
"colocation_logical_link": 2,
"common_function_gateway": 1,
"firewall": 2,
"id": IDENTIFIER,
"interdc_gateway": 1,
"internet_gateway": 1,
"load_balancer": 2,
"network": 2,
"port": 30,
"subnet": 5,
"tenant_id": IDENTIFIER,
"vpn_gateway": 1
}
class TestQuota(testtools.TestCase):
def test_basic(self):
sot = quota.Quota()
self.assertEqual('quota', sot.resource_key)
self.assertEqual('quotas', sot.resources_key)
self.assertEqual('/quotas', sot.base_path)
self.assertEqual('network', sot.service.service_type)
self.assertFalse(sot.allow_create)
self.assertTrue(sot.allow_get)
self.assertTrue(sot.allow_update)
self.assertTrue(sot.allow_delete)
self.assertTrue(sot.allow_list)
def test_make_it(self):
sot = quota.Quota(**EXAMPLE)
self.assertEqual(EXAMPLE['colocation_logical_link'], sot.colocation_logical_link)
self.assertEqual(EXAMPLE['common_function_gateway'], sot.common_function_gateway)
self.assertEqual(EXAMPLE['firewall'], sot.firewall)
self.assertEqual(EXAMPLE['id'], sot.id)
self.assertEqual(EXAMPLE['interdc_gateway'], sot.interdc_gateway)
self.assertEqual(EXAMPLE['interdc_gateway'], sot.internet_gateway)
self.assertEqual(EXAMPLE['load_balancer'], sot.load_balancer)
self.assertEqual(EXAMPLE['network'], sot.networks)
self.assertEqual(EXAMPLE['port'], sot.ports)
self.assertEqual(EXAMPLE['subnet'], sot.subnets)
self.assertEqual(EXAMPLE['tenant_id'], sot.project_id)
self.assertEqual(EXAMPLE['vpn_gateway'], sot.vpn_gateway)
class TestQuotaDefault(testtools.TestCase):
def test_basic(self):
default = quota.QuotaDefault()
self.assertEqual('quota', default.resource_key)
self.assertEqual('quotas', default.resources_key)
self.assertEqual('/quotas/%(project)s/default', default.base_path)
self.assertEqual('network', default.service.service_type)
self.assertFalse(default.allow_create)
self.assertTrue(default.allow_get)
self.assertFalse(default.allow_update)
self.assertFalse(default.allow_delete)
self.assertFalse(default.allow_list)
def test_make_it(self):
default = quota.QuotaDefault(**EXAMPLE)
self.assertEqual(EXAMPLE['colocation_logical_link'], default.colocation_logical_link)
self.assertEqual(EXAMPLE['common_function_gateway'], default.common_function_gateway)
self.assertEqual(EXAMPLE['firewall'], default.firewall)
self.assertEqual(EXAMPLE['id'], default.id)
self.assertEqual(EXAMPLE['interdc_gateway'], default.interdc_gateway)
self.assertEqual(EXAMPLE['interdc_gateway'], default.internet_gateway)
self.assertEqual(EXAMPLE['load_balancer'], default.load_balancer)
self.assertEqual(EXAMPLE['network'], default.networks)
self.assertEqual(EXAMPLE['port'], default.ports)
self.assertEqual(EXAMPLE['subnet'], default.subnets)
self.assertEqual(EXAMPLE['tenant_id'], default.project_id)
self.assertEqual(EXAMPLE['vpn_gateway'], default.vpn_gateway)
| 41.75 | 93 | 0.707628 | 453 | 3,841 | 5.847682 | 0.269316 | 0.1812 | 0.199321 | 0.065685 | 0.543601 | 0.369951 | 0.249906 | 0.04832 | 0.04832 | 0 | 0 | 0.005049 | 0.174954 | 3,841 | 91 | 94 | 42.208791 | 0.830861 | 0.135902 | 0 | 0.057971 | 0 | 0 | 0.147868 | 0.049894 | 0 | 0 | 0 | 0 | 0.608696 | 1 | 0.057971 | false | 0 | 0.028986 | 0 | 0.115942 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
14c72ec37a70b92517a8b215dd1e93abd24d6689 | 279 | py | Python | controllers/base_controller.py | allen-garvey/gae-library | e66210f2345c92c09e46b9d402a9e1c26bb46539 | [
"MIT"
] | null | null | null | controllers/base_controller.py | allen-garvey/gae-library | e66210f2345c92c09e46b9d402a9e1c26bb46539 | [
"MIT"
] | null | null | null | controllers/base_controller.py | allen-garvey/gae-library | e66210f2345c92c09e46b9d402a9e1c26bb46539 | [
"MIT"
] | null | null | null | import webapp2
import json
#base controller class
class BaseController(webapp2.RequestHandler):
#convenience method for writing json response
def write_json(self, json_string):
self.response.content_type = 'application/json'
self.response.write(json_string) | 27.9 | 55 | 0.774194 | 34 | 279 | 6.235294 | 0.588235 | 0.084906 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.008475 | 0.154122 | 279 | 10 | 56 | 27.9 | 0.889831 | 0.232975 | 0 | 0 | 0 | 0 | 0.075117 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.333333 | 0 | 0.666667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
14d28eaad6b3957f25c1f3701b03066124d73a33 | 246 | py | Python | Orest Lab 2/2d.py | PetroSidliar/Lab-2 | 0e95ef61b62cb54906500500bb042ab79ef28384 | [
"MIT"
] | null | null | null | Orest Lab 2/2d.py | PetroSidliar/Lab-2 | 0e95ef61b62cb54906500500bb042ab79ef28384 | [
"MIT"
] | null | null | null | Orest Lab 2/2d.py | PetroSidliar/Lab-2 | 0e95ef61b62cb54906500500bb042ab79ef28384 | [
"MIT"
] | null | null | null | grade = eval ( input ( ' Enter your credit: ' ))
if grade<=23:
print ( ' Freshman ' )
elif grade>=24 and grade<=53:
print ( ' Sophomore ' )
elif grade>=54 and grade<=83:
print ( ' Juniors ' )
elif grade>=84:
print ( ' Seniors ' )
| 24.6 | 48 | 0.577236 | 32 | 246 | 4.4375 | 0.625 | 0.190141 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.065934 | 0.260163 | 246 | 9 | 49 | 27.333333 | 0.714286 | 0 | 0 | 0 | 0 | 0 | 0.239837 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.444444 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 |
14e7b7ec50508b14ae420a7d360c77faab28cc50 | 3,838 | py | Python | niprov/repository.py | kambysese/niprov | 05b24b8e60e2e637fc2dec754681226d793d1a08 | [
"BSD-3-Clause"
] | null | null | null | niprov/repository.py | kambysese/niprov | 05b24b8e60e2e637fc2dec754681226d793d1a08 | [
"BSD-3-Clause"
] | null | null | null | niprov/repository.py | kambysese/niprov | 05b24b8e60e2e637fc2dec754681226d793d1a08 | [
"BSD-3-Clause"
] | null | null | null |
class Repository(object):
def byLocation(self, locationString): # pragma: no cover
"""Get the provenance for a file at the given location.
In the case of a dicom series, this returns the provenance for the
series.
Args:
locationString (str): Location of the image file.
Returns:
dict: Provenance for one image file.
"""
def knowsByLocation(self, locationString): # pragma: no cover
"""Whether the file at this location has provenance associated with it.
Returns:
bool: True if provenance is available for that path.
"""
def knows(self, image): # pragma: no cover
"""Whether this file has provenance associated with it.
Returns:
bool: True if provenance is available for this image.
"""
def getSeries(self, image): # pragma: no cover
"""Get the object that carries provenance for the series that the image
passed is in.
Args:
image (:class:`.DicomFile`): File that is part of a series.
Returns:
:class:`.DicomFile`: Image object that caries provenance for the series.
"""
def knowsSeries(self, image): # pragma: no cover
"""Whether this file is part of a series for which provenance
is available.
Args:
image (:class:`.BaseFile`): File for which the series is sought.
Returns:
bool: True if provenance is available for this series.
"""
def add(self, image): # pragma: no cover
"""Add the provenance for one file to storage.
Args:
image (:class:`.BaseFile`): Image file to store.
"""
def update(self, image): # pragma: no cover
"""Save changed provenance for this file..
Args:
image (:class:`.BaseFile`): Image file that has changed.
"""
def all(self): # pragma: no cover
"""Retrieve all known provenance from storage.
Returns:
list: List of provenance for known files.
"""
def bySubject(self, subject): # pragma: no cover
"""Get the provenance for all files of a given participant.
Args:
subject (str): The name or other ID string.
Returns:
list: List of provenance for known files imaging this subject.
"""
def byApproval(self, approvalStatus): # pragma: no cover
""""""
def updateApproval(self, locationString, approvalStatus): # pragma: no cover
""""""
def latest(self, n=20): # pragma: no cover
"""Get the images that have been registered last.
Args:
n (int): The number of files to retrieve. Defaults to 20.
Returns:
list: List of BaseFile objects.
"""
def byId(self, uid): # pragma: no cover
"""Get the provenance for a file with the given id.
Args:
uid (str): Unique id for the file.
Returns:
BaseFile: File with the given id.
"""
def byLocations(self, listOfLocations): # pragma: no cover
"""Get any files that match one of these locations
In the case of a dicom series, this returns the provenance for the
series.
Args:
listOfLocations (list): List of image locations.
Returns:
list: List with BaseFile objects
"""
| 31.203252 | 84 | 0.525013 | 413 | 3,838 | 4.878935 | 0.244552 | 0.055583 | 0.090323 | 0.047643 | 0.446154 | 0.316129 | 0.28536 | 0.269479 | 0.193052 | 0.13201 | 0 | 0.001737 | 0.399948 | 3,838 | 122 | 85 | 31.459016 | 0.873209 | 0.584158 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.933333 | false | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
14f19287990377720ae3bf1988ae4b6d52fae769 | 964 | py | Python | galaxy_dive/tests/test_read_data/test_rockstar.py | zhafen/galaxy-dive | e1127da25d10f699b3ada01b1b4635255f4f3917 | [
"MIT"
] | null | null | null | galaxy_dive/tests/test_read_data/test_rockstar.py | zhafen/galaxy-dive | e1127da25d10f699b3ada01b1b4635255f4f3917 | [
"MIT"
] | 1 | 2018-12-17T21:11:18.000Z | 2018-12-17T21:11:18.000Z | galaxy_dive/tests/test_read_data/test_rockstar.py | zhafen/galaxy-dive | e1127da25d10f699b3ada01b1b4635255f4f3917 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
'''Testing for read_rockstar.py
@author: Zach Hafen
@contact: zachary.h.hafen@gmail.com
@status: Development
'''
import glob
from mock import call, patch
import numpy as np
import numpy.testing as npt
import os
import pdb
import pytest
import unittest
import galaxy_dive.read_data.rockstar as read_rockstar
import galaxy_dive.utils.utilities as utilities
########################################################################
########################################################################
class TestRockstarReader( unittest.TestCase ):
def setUp( self ):
self.rockstar_reader = read_rockstar.RockstarReader(
'./tests/data/rockstar_dir',
)
########################################################################
def test_get_halos( self ):
self.rockstar_reader.get_halos( 600 )
expected = 51
actual = self.rockstar_reader.halos['Np'][6723]
npt.assert_allclose( expected, actual )
| 22.952381 | 74 | 0.573651 | 102 | 964 | 5.284314 | 0.568627 | 0.06679 | 0.100186 | 0.081633 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.010753 | 0.131743 | 964 | 41 | 75 | 23.512195 | 0.633214 | 0.131743 | 0 | 0 | 0 | 0 | 0.044046 | 0.040783 | 0 | 0 | 0 | 0 | 0.05 | 1 | 0.1 | false | 0 | 0.5 | 0 | 0.65 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
090f80e88e8a22418f4ed4d800950e4856fcf921 | 254 | py | Python | src/ui/cli/input.py | FilaCo/upg | b3a5ea617313d8ae481a1f8f65532b1b264738fb | [
"MIT"
] | null | null | null | src/ui/cli/input.py | FilaCo/upg | b3a5ea617313d8ae481a1f8f65532b1b264738fb | [
"MIT"
] | null | null | null | src/ui/cli/input.py | FilaCo/upg | b3a5ea617313d8ae481a1f8f65532b1b264738fb | [
"MIT"
] | null | null | null | import click
from ui.cli.command import Command
class Input(Command):
def __init__(self, title: str, value=None):
self.title = title
self.value = value
def render(self):
click.echo("%s\t%s" % (self.title, self.value))
| 19.538462 | 55 | 0.629921 | 36 | 254 | 4.333333 | 0.527778 | 0.173077 | 0.179487 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.240157 | 254 | 12 | 56 | 21.166667 | 0.80829 | 0 | 0 | 0 | 0 | 0 | 0.023622 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.625 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
091455babee31da6ab5b24ea51dd4bd05f27bdfc | 201 | py | Python | email_signals/urls.py | Salaah01/django-email-signals | c9a570a4c34321faa7642b94eedf60145e4fc2ff | [
"MIT"
] | 14 | 2021-12-12T16:33:27.000Z | 2022-03-25T06:42:06.000Z | email_signals/urls.py | webclinic017/django-email-signals | b58929ac10f30e3e34cc8dd97be22ab1d8b145c6 | [
"MIT"
] | 1 | 2022-03-18T11:53:08.000Z | 2022-03-18T18:54:38.000Z | email_signals/urls.py | webclinic017/django-email-signals | b58929ac10f30e3e34cc8dd97be22ab1d8b145c6 | [
"MIT"
] | 5 | 2021-12-07T23:35:23.000Z | 2022-03-27T17:17:42.000Z | from django.urls import path
from . import views
urlpatterns = [
path(
"model-attrs/<int:content_type_id>/",
views.model_attrs,
name="django_signals_model_attrs",
),
]
| 18.272727 | 45 | 0.636816 | 24 | 201 | 5.083333 | 0.625 | 0.245902 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.248756 | 201 | 10 | 46 | 20.1 | 0.807947 | 0 | 0 | 0 | 0 | 0 | 0.298507 | 0.298507 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.222222 | 0 | 0.222222 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
09154f715c718aa9ce03a606ae941c1521983c90 | 2,550 | py | Python | clients/python/tyckiting_client/ai/myai.py | HimanshuSingal/space_mission | 7d032f02b6144f412e23cd012d87965f68484fea | [
"MIT"
] | null | null | null | clients/python/tyckiting_client/ai/myai.py | HimanshuSingal/space_mission | 7d032f02b6144f412e23cd012d87965f68484fea | [
"MIT"
] | null | null | null | clients/python/tyckiting_client/ai/myai.py | HimanshuSingal/space_mission | 7d032f02b6144f412e23cd012d87965f68484fea | [
"MIT"
] | null | null | null | import random
from tyckiting_client.ai import base
from tyckiting_client import actions
class Ai(base.BaseAi):
a = 0
wait_list = []
def move(self, bots, events):
"""
Move the bot to a random legal positon.
Args:
bots: List of bot states for own team
events: List of events form previous round
Returns:
List of actions to perform this round.
"""
for e in events:
print e.__dict
response = []
if len(Ai.wait_list) != 0:
for wait in Ai.wait_list:
b_id = wait[0];pos = wait[-1]
b = (b for b in bots if b_id == b.bot_id).next()
bots.remove(b) # remove the intereted bot from event,bot,wait_list
Ai.wait_list.remove(wait)
for e in events:
if e.source == b_id or e.bot_id==b_id:
events.remove(e)
response.append(actions.Cannon(bot_id=b_id,x=pos.x,y=pos.y))
for e in events:
if e.event == 'see': # if see some bots
b = (b for b in bots if e.source == b.bot_id).next()
if b != None:
bots.remove(b)
events.remove(e)
response.append(self.on_see(e,b))
else:
print "I am none"
for bot in bots:
if not bot.alive:
continue
move_pos = random.choice(list(self.get_valid_moves(bot)))
response.append(actions.Move(bot_id=bot.bot_id,
x=move_pos.x,
y=move_pos.y))
return response
def get_far_pos(self,bot,tar_pos):
dis = []
pos_list = list(self.get_valid_moves(bot))
for pos in pos_list:
d = (pos.x - tar_pos.x)**2 + (pos.y - tar_pos.y)**2
dis.append(d)
pos = pos_list[dis.index(max(dis))]
return pos
#todo
def on_see(self,event,bot):
en_pos = event.pos
far_pos = self.get_far_pos(bot,en_pos) # get the farest pos, move
# and shoot next turn
Ai.wait_list.append([bot.bot_id,'cannon',en_pos])
print(Ai.wait_list)
return actions.Move(bot_id=bot.bot_id,x=far_pos.x,y=far_pos.y)
def on_radar_echo(self):
return
def on_detected(self):
return
def on_hit(self):
return
def give_priority(self,events,bots):
pass | 28.977273 | 82 | 0.512941 | 360 | 2,550 | 3.480556 | 0.255556 | 0.035914 | 0.039904 | 0.028731 | 0.167598 | 0.124501 | 0.062251 | 0.039904 | 0 | 0 | 0 | 0.003851 | 0.38902 | 2,550 | 88 | 83 | 28.977273 | 0.800385 | 0.045098 | 0 | 0.169492 | 0 | 0 | 0.008264 | 0 | 0 | 0 | 0 | 0.011364 | 0 | 0 | null | null | 0.016949 | 0.050847 | null | null | 0.050847 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
09327493d0c648a98a041898f56aea4b1d5dc17b | 69 | py | Python | Beginner/1016.py | pedrodanieljardim/DesafiosURI-feitos-em-JAVA | 4e727e1b08e01f527d0b7b884c268643f1472ded | [
"MIT"
] | 1 | 2022-03-19T18:06:25.000Z | 2022-03-19T18:06:25.000Z | Beginner/1016.py | pedrodanieljardim/beecrowd | 4e727e1b08e01f527d0b7b884c268643f1472ded | [
"MIT"
] | null | null | null | Beginner/1016.py | pedrodanieljardim/beecrowd | 4e727e1b08e01f527d0b7b884c268643f1472ded | [
"MIT"
] | null | null | null |
km = int(input())
minutes = 2*km
print("{} minutos".format(minutes)) | 17.25 | 35 | 0.652174 | 10 | 69 | 4.5 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.016393 | 0.115942 | 69 | 4 | 35 | 17.25 | 0.721311 | 0 | 0 | 0 | 0 | 0 | 0.144928 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.333333 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
0940acc5b7553481f6b2c0a210942f5b28d9f297 | 112 | py | Python | knightbook/splitting.py | beninato8/selenium | 56e8ed005999b8e29a4bae0ff69ae583f614fc17 | [
"MIT"
] | null | null | null | knightbook/splitting.py | beninato8/selenium | 56e8ed005999b8e29a4bae0ff69ae583f614fc17 | [
"MIT"
] | null | null | null | knightbook/splitting.py | beninato8/selenium | 56e8ed005999b8e29a4bae0ff69ae583f614fc17 | [
"MIT"
] | null | null | null | m = 'John Smithfather'
a = m[:-6]
b = m[-6:]
print(b.title() + ": " + a)
print('AsDf'.lower(), 'AsDf'.upper()) | 16 | 37 | 0.508929 | 18 | 112 | 3.166667 | 0.611111 | 0.070175 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021505 | 0.169643 | 112 | 7 | 37 | 16 | 0.591398 | 0 | 0 | 0 | 0 | 0 | 0.230089 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.4 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
094c4f81c2a9a1afcdb37545147e9a797d3defcc | 1,361 | py | Python | webup/content_type.py | cariad/webup | 29f636ffd50a605c2dc11d82d17cfcb6ce961f8c | [
"MIT"
] | null | null | null | webup/content_type.py | cariad/webup | 29f636ffd50a605c2dc11d82d17cfcb6ce961f8c | [
"MIT"
] | 5 | 2021-12-24T17:40:35.000Z | 2022-01-19T14:16:50.000Z | webup/content_type.py | cariad/webup | 29f636ffd50a605c2dc11d82d17cfcb6ce961f8c | [
"MIT"
] | null | null | null | from typing import Dict
from webup.suffix import normalize_suffix
_content_types: Dict[str, str] = {}
_default_content_type = ""
def set_default_content_type(type: str = "application/octet-stream") -> None:
"""
Sets the default Content-Type header for file types not registered via
`set_content_type`.
Defaults to "application/octet-stream".
"""
global _default_content_type
_default_content_type = type
def content_type(suffix: str) -> str:
"""
Gets the Content-Type header for a type of file.
Arguments:
suffix: Filename suffix.
"""
suffix = normalize_suffix(suffix)
return _content_types.get(suffix, _default_content_type)
def set_content_type(suffix: str, type: str) -> None:
"""
Registers the Content-Type header for files with the `suffix` filename
extension.
"""
suffix = normalize_suffix(suffix)
_content_types[suffix] = type
set_default_content_type()
# TODO: Update the `__init__.py` documentation if you change these defaults:
set_content_type("css", "text/css")
set_content_type("eot", "application/vnd.m-fontobject")
set_content_type("html", "text/html")
set_content_type("js", "text/javascript")
set_content_type("png", "image/png")
set_content_type("ttf", "font/ttf")
set_content_type("woff", "font/woff")
set_content_type("woff2", "font/woff2")
| 25.203704 | 77 | 0.71712 | 183 | 1,361 | 5.04918 | 0.349727 | 0.238095 | 0.151515 | 0.064935 | 0.101732 | 0 | 0 | 0 | 0 | 0 | 0 | 0.001761 | 0.16532 | 1,361 | 53 | 78 | 25.679245 | 0.81162 | 0.278472 | 0 | 0.090909 | 0 | 0 | 0.16048 | 0.056769 | 0 | 0 | 0 | 0.018868 | 0 | 1 | 0.136364 | false | 0 | 0.090909 | 0 | 0.272727 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
094d43508d084e8f2ebbda458321ec3a7354ae59 | 247 | py | Python | commanderbot_lib/database/mixins/yaml_file_database_mixin.py | CommanderBot-Dev/commanderbot-lib | 2716279b059056eaf0797085149b61f71b175ed5 | [
"MIT"
] | 1 | 2020-09-25T19:22:47.000Z | 2020-09-25T19:22:47.000Z | commanderbot_lib/database/mixins/yaml_file_database_mixin.py | CommanderBot-Dev/commanderbot-lib | 2716279b059056eaf0797085149b61f71b175ed5 | [
"MIT"
] | 1 | 2021-01-06T00:22:56.000Z | 2021-08-29T20:54:50.000Z | commanderbot_lib/database/mixins/yaml_file_database_mixin.py | CommanderBot-Dev/commanderbot-lib | 2716279b059056eaf0797085149b61f71b175ed5 | [
"MIT"
] | 2 | 2020-09-25T19:23:07.000Z | 2020-09-25T21:06:11.000Z | from typing import IO
import yaml
class YamlFileDatabaseMixin:
async def load_yaml(self, file: IO) -> dict:
return yaml.safe_load(file)
async def dump_yaml(self, data: dict, file: IO):
return yaml.safe_dump(data, file)
| 20.583333 | 52 | 0.688259 | 36 | 247 | 4.611111 | 0.472222 | 0.096386 | 0.168675 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.222672 | 247 | 11 | 53 | 22.454545 | 0.864583 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.285714 | 0 | 0.714286 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
09524d9528ae71f349ef595b6b56d130035c039f | 1,731 | py | Python | tests/datatypes/test_resolver_address.py | VIDA-NYU/openclean-pattern | 8d8a94691f9bfa5dcf8773b08ceb8e562fce52df | [
"BSD-3-Clause"
] | 4 | 2021-04-20T09:05:51.000Z | 2022-01-28T14:13:37.000Z | tests/datatypes/test_resolver_address.py | VIDA-NYU/openclean-pattern | 8d8a94691f9bfa5dcf8773b08ceb8e562fce52df | [
"BSD-3-Clause"
] | 1 | 2021-04-09T08:49:33.000Z | 2021-04-09T08:49:33.000Z | tests/datatypes/test_resolver_address.py | VIDA-NYU/openclean-pattern | 8d8a94691f9bfa5dcf8773b08ceb8e562fce52df | [
"BSD-3-Clause"
] | null | null | null | # This file is part of the Pattern and Anomaly Detection Library (openclean_pattern).
#
# Copyright (C) 2021 New York University.
#
# openclean_pattern is released under the Revised BSD License. See file LICENSE for
# full license details.
"""unit tests for address type resolver classs"""
from openclean_pattern.datatypes.base import SupportedDataTypes
from openclean_pattern.datatypes.resolver import AddressDesignatorResolver, DefaultTypeResolver
from openclean_pattern.tokenize.regex import RegexTokenizer
def test_default_ad_resolver(business):
dt = DefaultTypeResolver(interceptors=AddressDesignatorResolver())
rt = RegexTokenizer(type_resolver=dt)
business['Address_combined'] = business['Address '].astype(str) + ' | ' + business['Address Continued'].astype(str)
tokens = rt.tokens(business['Address_combined'].to_list()[2])
# LN -> _STREET_
# ['22207 SW SIR LANCELOT LN | nan'],
assert tokens[0].regex_type == SupportedDataTypes.DIGIT
assert tokens[1].regex_type == SupportedDataTypes.SPACE_REP
assert tokens[2].regex_type == SupportedDataTypes.ALPHA
assert tokens[3].regex_type == SupportedDataTypes.SPACE_REP
assert tokens[4].regex_type == SupportedDataTypes.ALPHA
assert tokens[5].regex_type == SupportedDataTypes.SPACE_REP
assert tokens[6].regex_type == SupportedDataTypes.ALPHA
assert tokens[7].regex_type == SupportedDataTypes.SPACE_REP
assert tokens[8].regex_type == SupportedDataTypes.STREET
assert tokens[9].regex_type == SupportedDataTypes.SPACE_REP
assert tokens[10].regex_type == SupportedDataTypes.PUNCTUATION
assert tokens[11].regex_type == SupportedDataTypes.SPACE_REP
assert tokens[12].regex_type == SupportedDataTypes.ALPHA
| 48.083333 | 119 | 0.774119 | 205 | 1,731 | 6.37561 | 0.409756 | 0.119357 | 0.268554 | 0.146901 | 0.316756 | 0.316756 | 0.215761 | 0 | 0 | 0 | 0 | 0.017276 | 0.13056 | 1,731 | 35 | 120 | 49.457143 | 0.851163 | 0.186597 | 0 | 0 | 0 | 0 | 0.043011 | 0 | 0 | 0 | 0 | 0 | 0.619048 | 1 | 0.047619 | false | 0 | 0.142857 | 0 | 0.190476 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
117cc054ca0616874ff5d9fc7e2de421c2407ed3 | 1,497 | py | Python | SecML/src/secml/core/tests/test_attr_utils.py | dsolanno/Poisoning-Attacks-on-Algorithmic-Fairness | 77698340906fd0ec68d857315283d849e236ebd7 | [
"MIT"
] | 5 | 2020-07-09T13:03:34.000Z | 2021-02-16T17:15:26.000Z | SecML/src/secml/core/tests/test_attr_utils.py | dsolanno/Poisoning-Attacks-on-Algorithmic-Fairness | 77698340906fd0ec68d857315283d849e236ebd7 | [
"MIT"
] | 1 | 2021-12-30T21:11:50.000Z | 2021-12-30T21:11:50.000Z | SecML/src/secml/core/tests/test_attr_utils.py | dsolanno/Poisoning-Attacks-on-Algorithmic-Fairness | 77698340906fd0ec68d857315283d849e236ebd7 | [
"MIT"
] | 2 | 2021-03-22T19:22:56.000Z | 2021-09-19T20:07:10.000Z | from secml.testing import CUnitTest
from secml.core.attr_utils import extract_attr
class TestAttributeUtilities(CUnitTest):
"""Unit test for secml.core.attr_utils."""
def test_extract_attr(self):
# Toy class for testing
class Foo:
def __init__(self):
self.a = 5
self._b = 5
self._c = 5
self._d = 5
@property
def b(self):
pass
@property
def c(self):
pass
@c.setter
def c(self):
pass
f = Foo()
self.logger.info(
"Testing attributes extraction based on accessibility...")
def check_attrs(code, expected):
self.assertTrue(
set(attr for attr in extract_attr(f, code)) == expected)
check_attrs('pub', {'a'})
check_attrs('r', {'_b'})
check_attrs('rw', {'_c'})
check_attrs('pub+r', {'a', '_b'})
check_attrs('pub+rw', {'a', '_c'})
check_attrs('pub+pro', {'a', '_d'})
check_attrs('r+rw', {'_b', '_c'})
check_attrs('r+pro', {'_b', '_d'})
check_attrs('rw+pro', {'_c', '_d'})
check_attrs('pub+r+rw', {'a', '_b', '_c'})
check_attrs('pub+r+pro', {'a', '_b', '_d'})
check_attrs('pub+rw+pro', {'a', '_c', '_d'})
check_attrs('pub+r+rw+pro', {'a', '_b', '_c', '_d'})
if __name__ == '__main__':
CUnitTest.main()
| 26.732143 | 72 | 0.480962 | 180 | 1,497 | 3.694444 | 0.272222 | 0.210526 | 0.156391 | 0.084211 | 0.099248 | 0.054135 | 0.054135 | 0 | 0 | 0 | 0 | 0.004103 | 0.348697 | 1,497 | 55 | 73 | 27.218182 | 0.677949 | 0.039412 | 0 | 0.175 | 0 | 0 | 0.131983 | 0 | 0 | 0 | 0 | 0 | 0.025 | 1 | 0.15 | false | 0.075 | 0.05 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
1183648424185e5329ae3eb63d9f938421255ca6 | 967 | py | Python | hyparam.py | Shihab-Shahriar/500-miles | 49fc9c6d037521f454da4bc02cccd62117c0ac5f | [
"MIT"
] | null | null | null | hyparam.py | Shihab-Shahriar/500-miles | 49fc9c6d037521f454da4bc02cccd62117c0ac5f | [
"MIT"
] | null | null | null | hyparam.py | Shihab-Shahriar/500-miles | 49fc9c6d037521f454da4bc02cccd62117c0ac5f | [
"MIT"
] | null | null | null | from time import perf_counter
import numpy as np
from sklearn.model_selection import RepeatedStratifiedKFold
from sklearn.metrics import *
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC
from sklearn.decomposition import PCA
from sklearn.manifold import TSNE
import matplotlib.pyplot as plt
from hpsklearn import HyperoptEstimator, svc, random_forest, knn
from hyperopt import tpe
from sklearn.metrics import f1_score
def scorer(yt, yp): return 1 - f1_score(yt, yp, average='macro')
if __name__=='__main__':
np.random.seed(42)
train_X = np.load('data/train_X.npy')
test_X = np.load('data/test_X.npy')
train_Y = np.load('data/train_Y.npy')
test_Y = np.load('data/test_Y.npy')
estim = HyperoptEstimator(classifier=random_forest('rf'),algo=tpe.suggest,loss_fn=scorer,max_evals=200,trial_timeout=1200)
estim.fit(train_X, train_Y)
yp = estim.predict(test_X)
print(f1_score(test_Y, yp, average='macro')) | 37.192308 | 126 | 0.76939 | 150 | 967 | 4.76 | 0.46 | 0.107843 | 0.056022 | 0.067227 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.015421 | 0.128232 | 967 | 26 | 127 | 37.192308 | 0.831554 | 0 | 0 | 0 | 0 | 0 | 0.084711 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.043478 | false | 0 | 0.521739 | 0.043478 | 0.565217 | 0.043478 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
11951835e0f5114e1283c50629572d6483a7d055 | 748 | py | Python | src/textdatasetcleaner/processors/normalize_unicode.py | ameyuuno/TextDatasetCleaner | 93f380748f348a8159e6111517b9afec839ec3fe | [
"MIT"
] | 27 | 2020-02-16T14:48:57.000Z | 2022-02-08T17:42:17.000Z | src/textdatasetcleaner/processors/normalize_unicode.py | ameyuuno/TextDatasetCleaner | 93f380748f348a8159e6111517b9afec839ec3fe | [
"MIT"
] | 6 | 2020-03-10T12:12:50.000Z | 2021-12-14T11:17:50.000Z | src/textdatasetcleaner/processors/normalize_unicode.py | ameyuuno/TextDatasetCleaner | 93f380748f348a8159e6111517b9afec839ec3fe | [
"MIT"
] | 9 | 2020-02-16T11:31:50.000Z | 2021-09-03T06:05:59.000Z | from pathlib import Path
from typing import Optional
from textacy.preprocessing import normalize_unicode # type: ignore
from textdatasetcleaner.exceptions import TDCValueError
from textdatasetcleaner.processors.base import BaseProcessor
class NormalizeUnicodeProcessor(BaseProcessor):
__processor_name__ = Path(__file__).resolve().stem
__processor_type__ = 'line'
def __init__(self, form: str = 'NFKC'):
allowed = ['NFC', 'NFD', 'NFKC', 'NFKD']
if form not in allowed:
raise TDCValueError(f'Wrong form for {self.name} processor: {form}, allowed only: {allowed}')
self.form = form
def process_line(self, line: str) -> Optional[str]:
return normalize_unicode(line, form=self.form)
| 31.166667 | 105 | 0.717914 | 86 | 748 | 6 | 0.534884 | 0.046512 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.185829 | 748 | 23 | 106 | 32.521739 | 0.847291 | 0.016043 | 0 | 0 | 0 | 0 | 0.123978 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.133333 | false | 0 | 0.333333 | 0.066667 | 0.733333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
119f2a22e0c199590833fa7a10ac8c7b65340d21 | 948 | py | Python | src/unicon/plugins/nd/__init__.py | nielsvanhooy/unicon.plugins | 3416fd8223f070cbb67a2cbe604e3c5d13584318 | [
"Apache-2.0"
] | null | null | null | src/unicon/plugins/nd/__init__.py | nielsvanhooy/unicon.plugins | 3416fd8223f070cbb67a2cbe604e3c5d13584318 | [
"Apache-2.0"
] | null | null | null | src/unicon/plugins/nd/__init__.py | nielsvanhooy/unicon.plugins | 3416fd8223f070cbb67a2cbe604e3c5d13584318 | [
"Apache-2.0"
] | null | null | null | """
Module:
unicon.plugins.nd
Authors:
pyATS TEAM (pyats-support-ext@cisco.com)
Description:
This subpackage implements ND
"""
# from unicon.plugins.linux import LinuxConnection
from unicon.plugins.linux import LinuxConnection,LinuxServiceList
from unicon.plugins.linux.statemachine import LinuxStateMachine
from unicon.plugins.linux.connection_provider import LinuxConnectionProvider
from unicon.plugins.linux.settings import LinuxSettings
# from unicon.plugins.confd import ConfdConnection, ConfdServiceList, ConfdConnectionProvider
# from unicon.plugins.confd.settings import ConfdSettings
class NDConnection(LinuxConnection):
"""
Connection class for ND connections.
Extends the Linux connection to function with 'nd' os.
"""
os = 'nd'
state_machine_class = LinuxStateMachine
connection_provider_class = LinuxConnectionProvider
subcommand_list = LinuxServiceList
settings = LinuxSettings()
| 29.625 | 93 | 0.793249 | 99 | 948 | 7.535354 | 0.464646 | 0.13941 | 0.159517 | 0.147453 | 0.115282 | 0.115282 | 0 | 0 | 0 | 0 | 0 | 0 | 0.140295 | 948 | 31 | 94 | 30.580645 | 0.915337 | 0.445148 | 0 | 0 | 0 | 0 | 0.004024 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.4 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
11a0d5fa91874e02aae223d81660a973405061b2 | 448 | py | Python | python/7kyu/binary_addition.py | momchilantonov/codewars | 73517569cc02478bb943f8182e6001ee9d941e78 | [
"MIT"
] | null | null | null | python/7kyu/binary_addition.py | momchilantonov/codewars | 73517569cc02478bb943f8182e6001ee9d941e78 | [
"MIT"
] | null | null | null | python/7kyu/binary_addition.py | momchilantonov/codewars | 73517569cc02478bb943f8182e6001ee9d941e78 | [
"MIT"
] | null | null | null | def add_binary(a, b):
"""
Implement a function that adds two numbers together and
returns their sum in binary.
The conversion can be done before, or after the addition.
The binary number returned should be a string.
"""
return str(bin(a+b)[2:])
# TESTS
assert add_binary(1, 1) == "10"
assert add_binary(0, 1) == "1"
assert add_binary(1, 0) == "1"
assert add_binary(2, 2) == "100"
assert add_binary(51, 12) == "111111"
| 26.352941 | 61 | 0.65625 | 74 | 448 | 3.891892 | 0.581081 | 0.1875 | 0.260417 | 0.111111 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.073864 | 0.214286 | 448 | 16 | 62 | 28 | 0.744318 | 0.4375 | 0 | 0 | 0 | 0 | 0.058036 | 0 | 0 | 0 | 0 | 0 | 0.714286 | 1 | 0.142857 | false | 0 | 0 | 0 | 0.285714 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
11abc1ce2a849ae61c5a961f90dabcbb00b5d4d0 | 406 | py | Python | callisto/web/status.py | isabella232/callisto | 182b9c3a56d13fbb3f8f199a984b4c4be6c17e9f | [
"MIT"
] | 84 | 2020-02-18T14:58:35.000Z | 2022-03-04T22:34:46.000Z | callisto/web/status.py | wrike/callisto | 182b9c3a56d13fbb3f8f199a984b4c4be6c17e9f | [
"MIT"
] | 6 | 2020-07-13T19:31:07.000Z | 2022-03-30T15:35:23.000Z | callisto/web/status.py | isabella232/callisto | 182b9c3a56d13fbb3f8f199a984b4c4be6c17e9f | [
"MIT"
] | 9 | 2021-03-08T10:17:29.000Z | 2022-03-04T12:21:53.000Z | from __future__ import annotations
import typing as t
import aiohttp.web as web
from ..libs.domains import consts
if t.TYPE_CHECKING:
from ..libs.use_cases.status import StatusUseCase
async def status_handler(request: web.Request) -> web.Response:
uc: StatusUseCase = request.app[consts.STATUS_USE_CASE_KEY]
status_data = uc.get_status()
return web.json_response(data=status_data)
| 20.3 | 63 | 0.768473 | 59 | 406 | 5.050847 | 0.542373 | 0.053691 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.152709 | 406 | 19 | 64 | 21.368421 | 0.866279 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.6 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 2 |
11ad8bad71ad68c81335de043281493d8fc37fc2 | 1,069 | py | Python | projects/ide/sublime/src/Bolt/ui/write/highlight.py | boltjs/bolt | c2666c876b34b1a61486a432eef3141ca8d1e411 | [
"BSD-3-Clause"
] | 11 | 2015-09-29T19:19:34.000Z | 2020-11-20T09:14:46.000Z | projects/ide/sublime/src/Bolt/ui/write/highlight.py | boltjs/bolt | c2666c876b34b1a61486a432eef3141ca8d1e411 | [
"BSD-3-Clause"
] | null | null | null | projects/ide/sublime/src/Bolt/ui/write/highlight.py | boltjs/bolt | c2666c876b34b1a61486a432eef3141ca8d1e411 | [
"BSD-3-Clause"
] | null | null | null | import sublime
from ui.read import regions as read_regions
from structs.highlight_list import *
# Hmmm....
def highlight(view, regions, info):
if regions != None:
view.add_regions(info.name, regions, info.format, info.icon, info.mode)
else:
remove_highlight(view, info)
def remove_highlight(view, x):
view.erase_regions(x.name)
def remove_highlights(view, xs):
map(lambda x: view.erase_regions(x.name), xs)
def regions(view, highlights):
missing_list = filter(lambda x: is_valid_spot(view, x), highlights.missing)
missing_regions = map(lambda x: sublime.Region(x.begin, x.end), missing_list)
incorrect_regions = dep_region(view, highlights.incorrect)
unused_regions = dep_region(view, highlights.unused)
return HighlightList(incorrect_regions, missing_regions, unused_regions)
def dep_region(view, plasmas):
return map(lambda x: read_regions.dep(view, x.dep), plasmas)
def is_valid_spot(view, spot):
return spot.begin < spot.end and view.substr(sublime.Region(spot.begin, spot.end)) == spot.token
| 29.694444 | 100 | 0.734331 | 154 | 1,069 | 4.941558 | 0.298701 | 0.036794 | 0.039422 | 0.044678 | 0.136662 | 0.057819 | 0 | 0 | 0 | 0 | 0 | 0 | 0.152479 | 1,069 | 35 | 101 | 30.542857 | 0.839956 | 0.007484 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.272727 | false | 0 | 0.136364 | 0.090909 | 0.545455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 2 |
11ba2ceabc4cb0d1b56066053ae044b8b829bcb8 | 620 | py | Python | haskpy/conftest.py | jluttine/haskpy | 79fca70b5f46d8551ed61b4bbd040de5f5ba0440 | [
"MIT"
] | 2 | 2021-04-08T18:34:39.000Z | 2022-02-24T18:02:45.000Z | haskpy/conftest.py | jluttine/haskpy | 79fca70b5f46d8551ed61b4bbd040de5f5ba0440 | [
"MIT"
] | null | null | null | haskpy/conftest.py | jluttine/haskpy | 79fca70b5f46d8551ed61b4bbd040de5f5ba0440 | [
"MIT"
] | null | null | null | import sys
import hypothesis.strategies as st
from hypothesis import given
def is_pytest():
return "pytest" in sys.modules
def pytest_configure(config):
# Workaround for Hypothesis bug causing flaky tests if they use characters
# or text: https://github.com/HypothesisWorks/hypothesis/issues/2108
@given(st.text())
def foo(x):
pass
foo()
return
# PYTEST_RUNNING = False
# def pytest_configure(config):
# global PYTEST_RUNNING
# PYTEST_RUNNING = True
# return
# def pytest_unconfigure(config):
# global PYTEST_RUNNING
# PYTEST_RUNNING = False
# return
| 19.375 | 78 | 0.698387 | 77 | 620 | 5.506494 | 0.545455 | 0.153302 | 0.084906 | 0.113208 | 0.179245 | 0.179245 | 0 | 0 | 0 | 0 | 0 | 0.008282 | 0.220968 | 620 | 31 | 79 | 20 | 0.869565 | 0.566129 | 0 | 0 | 0 | 0 | 0.023346 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.272727 | false | 0.090909 | 0.272727 | 0.090909 | 0.727273 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
11c1bef9e55ff165a33b521513766f8ed4bfe64d | 492 | py | Python | transmute_core/tests/frameworks/test_aiohttp/test_parsing.py | toumorokoshi/web-transmute | ff118e01e42bc224cdf2d7523c3b287aae40d669 | [
"MIT"
] | null | null | null | transmute_core/tests/frameworks/test_aiohttp/test_parsing.py | toumorokoshi/web-transmute | ff118e01e42bc224cdf2d7523c3b287aae40d669 | [
"MIT"
] | null | null | null | transmute_core/tests/frameworks/test_aiohttp/test_parsing.py | toumorokoshi/web-transmute | ff118e01e42bc224cdf2d7523c3b287aae40d669 | [
"MIT"
] | null | null | null | import pytest
@pytest.mark.asyncio
async def test_parsing_multiiple_query_params(cli):
resp = await cli.get("/multiple_query_params?tag=foo&tag=bar")
ret_value = await resp.json()
assert 200 == resp.status
assert ret_value == "foo,bar"
@pytest.mark.asyncio
async def test_parsing_multiple_query_params_single_tag(cli):
resp = await cli.get("/multiple_query_params?tag=foo")
ret_value = await resp.json()
assert 200 == resp.status
assert ret_value == "foo"
| 27.333333 | 66 | 0.729675 | 73 | 492 | 4.671233 | 0.356164 | 0.129032 | 0.167155 | 0.129032 | 0.797654 | 0.797654 | 0.797654 | 0.58651 | 0.58651 | 0.58651 | 0 | 0.014493 | 0.158537 | 492 | 17 | 67 | 28.941176 | 0.809179 | 0 | 0 | 0.461538 | 0 | 0 | 0.158537 | 0.138211 | 0 | 0 | 0 | 0 | 0.307692 | 1 | 0 | false | 0 | 0.076923 | 0 | 0.076923 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 |
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