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How to use evaluate_raw method in localstack
Best Python code snippet using localstack_python
proximal.py
Source:proximal.py 
...22 self._scale = scale23 self._shift = shift24 self._is_convex = None # TODO: Instantiate this here?25 @abstractmethod26 def evaluate_raw(self, v):27 pass28 @abstractmethod29 def prox_raw(self, rho, v):30 pass31 @abstractmethod32 def subdiff_raw(self, v):33 pass34 def evaluate(self, v):35 return self._weight * self.evaluate_raw(self._scale * v - self._shift)36 def prox(self, rho, equil_scaling, v):37 new_scale = equil_scaling * self._scale38 new_rho = rho / (self._weight * new_scale**2)39 return (40 self.prox_raw(new_rho, new_scale * v - self._shift) + self._shift41 ) / new_scale42 def subdiff(self, equil_scaling, obj_scale, v):43 g_ls, g_rs = self.subdiff_raw(self._scale * equil_scaling * v - self._shift)44 g_ls *= obj_scale * equil_scaling * self._weight * self._scale45 g_rs *= obj_scale * equil_scaling * self._weight * self._scale46 return g_ls, g_rs47class Zero(G):48 def __init__(self, weight, scale, shift):49 super().__init__(weight, scale, shift)50 self._is_convex = True51 def evaluate_raw(self, v):52 return np.zeros(np.asarray(v).shape)53 def prox_raw(self, rho, v):54 return np.asarray(v)55 def subdiff_raw(self, v):56 v = np.asarray(v)57 return np.zeros(v.shape), np.zeros(v.shape)58class Abs(G):59 def __init__(self, weight, scale, shift):60 super().__init__(weight, scale, shift)61 self._is_convex = True62 def evaluate_raw(self, v):63 return np.abs(v)64 def prox_raw(self, rho, v):65 return np.maximum(v - 1 / rho, 0) - np.maximum(-v - 1 / rho, 0)66 def subdiff_raw(self, v):67 v = np.asarray(v)68 ls = np.zeros(v.shape)69 rs = np.zeros(v.shape)70 ls[v < 0] = -171 rs[v < 0] = -172 ls[v > 0] = 173 rs[v > 0] = 174 ls[np.isclose(v, 0)] = -175 rs[np.isclose(v, 0)] = 176 return ls, rs77class IsPos(G):78 def __init__(self, weight, scale, shift):79 super().__init__(weight, scale, shift)80 self._is_convex = True81 def evaluate_raw(self, v):82 v = np.asarray(v)83 return np.where(v >= 0, 0, np.inf)84 def prox_raw(self, rho, v):85 v = np.asarray(v)86 return np.where(v < 0, 0, v)87 def subdiff_raw(self, v):88 v = np.asarray(v)89 ls = np.zeros(v.shape)90 rs = np.zeros(v.shape)91 ls[v < 0] = np.nan92 rs[v < 0] = np.nan93 ls[v == 0] = -np.inf94 rs[v == 0] = 095 return ls, rs96class IsNeg(G):97 def __init__(self, weight, scale, shift):98 super().__init__(weight, scale, shift)99 self._is_convex = True100 def evaluate_raw(self, v):101 v = np.asarray(v)102 return np.where(v <= 0, 0, np.inf)103 def prox_raw(self, rho, v):104 v = np.asarray(v)105 return np.where(v > 0, 0, v)106 def subdiff_raw(self, v):107 v = np.asarray(v)108 ls = np.zeros(v.shape)109 rs = np.zeros(v.shape)110 ls[v > 0] = np.nan111 rs[v > 0] = np.nan112 ls[v == 0] = 0113 rs[v == 0] = np.inf114 return ls, rs115class IsBound(G):116 def __init__(self, weight, scale, shift, lb, ub):117 super().__init__(weight, scale, shift)118 self._lb = lb119 self._ub = ub120 self._is_convex = True121 def evaluate_raw(self, v):122 return np.where((v >= self._lb) & (v <= self._ub), 0, np.inf)123 def prox_raw(self, rho, v):124 output = np.where(v >= self._ub, self._ub, v)125 output = np.where(output <= self._lb, self._lb, output)126 return output127 def subdiff_raw(self, v):128 v = np.asarray(v)129 ls = np.zeros(v.shape)130 rs = np.zeros(v.shape)131 ls[v > self._ub] = np.nan132 rs[v > self._ub] = np.nan133 ls[v == self._ub] = 0134 rs[v == self._ub] = np.inf135 ls[v < self._lb] = np.nan136 rs[v < self._lb] = np.nan137 ls[v == self._lb] = -np.inf138 rs[v == self._lb] = 0139 return ls, rs140class IsZero(G):141 def __init__(self, weight, scale, shift):142 super().__init__(weight, scale, shift)143 self._is_convex = True144 def evaluate_raw(self, v):145 return np.where(v == 0, 0, np.inf)146 def prox_raw(self, rho, v):147 return np.zeros(np.asarray(v).shape)148 def subdiff_raw(self, v):149 v = np.asarray(v)150 ls = np.nan * np.ones(v.shape)151 rs = np.nan * np.ones(v.shape)152 ls[v == 0] = -np.inf153 rs[v == 0] = np.inf154 return ls, rs155class Pos(G):156 def __init__(self, weight, scale, shift):157 super().__init__(weight, scale, shift)158 self._is_convex = True159 def evaluate_raw(self, v):160 return np.maximum(v, 0)161 def prox_raw(self, rho, v):162 output = np.where(v <= 0, v, 0)163 output = np.where(v > 1 / rho, v - 1 / rho, output)164 return output165 def subdiff_raw(self, v):166 v = np.asarray(v)167 ls = np.zeros(v.shape)168 rs = np.zeros(v.shape)169 ls[v > 0] = 1170 rs[v > 0] = 1171 # TODO: change this to is_close?172 ls[v == 0] = 0173 rs[v == 0] = 1174 return ls, rs175class Neg(G):176 def __init__(self, weight, scale, shift):177 super().__init__(weight, scale, shift)178 self._is_convex = True179 def evaluate_raw(self, v):180 return np.maximum(-v, 0)181 def prox_raw(self, rho, v):182 return np.where(v < -1 / rho, v + 1 / rho, v)183 def subdiff_raw(self, v):184 v = np.asarray(v)185 ls = np.zeros(v.shape)186 rs = np.zeros(v.shape)187 ls[v < 0] = -1188 rs[v < 0] = -1189 # TODO: change this to is_close?190 ls[v == 0] = -1191 rs[v == 0] = 0192 return ls, rs193class Card(G):194 def __init__(self, weight, scale, shift):195 super().__init__(weight, scale, shift)196 self._is_convex = False197 def evaluate_raw(self, v):198 # TODO: change this to isclose?199 return np.where(v == 0, 0, 1)200 def prox_raw(self, rho, v):201 return np.where(np.abs(v) < np.sqrt(2 / rho), 0, v)202 def subdiff_raw(self, v):203 v = np.asarray(v)204 ls = np.nan * np.ones(v.shape)205 rs = np.nan * np.ones(v.shape)206 ls[v == 0] = 0207 rs[v == 0] = 0208 return ls, rs209class Quantile(G):210 def __init__(self, weight, scale, shift, tau):211 super().__init__(weight, scale, shift)212 self._tau = tau213 self._is_convex = True214 def evaluate_raw(self, v):215 return 0.5 * np.abs(v) + (self._tau - 0.5) * v216 def prox_raw(self, rho, v):217 v_mod = np.asarray(v) + 1 / rho * (0.5 - self._tau)218 return np.where(219 np.abs(v_mod) <= 1 / (2 * rho), 0, v_mod - np.sign(v_mod) * 1 / (2 * rho)220 )221 def subdiff_raw(self, v):222 v = np.asarray(v)223 ls = np.zeros(v.shape)224 rs = np.zeros(v.shape)225 ls[v > 0] = self._tau226 rs[v > 0] = self._tau227 ls[v < 0] = self._tau - 1228 rs[v < 0] = self._tau - 1229 # TODO: change to is_close?230 ls[v == 0] = self._tau - 1231 rs[v == 0] = self._tau232 return ls, rs233class Huber(G):234 def __init__(self, weight, scale, shift, M):235 super().__init__(weight, scale, shift)236 self._M = M237 self._is_convex = True238 def evaluate_raw(self, v):239 abs_v = np.abs(v)240 return np.where(241 abs_v <= self._M, abs_v**2, 2 * self._M * abs_v - self._M * self._M242 )243 def prox_raw(self, rho, v):244 return np.where(245 np.abs(v) <= self._M * (rho + 2) / rho,246 rho / (2 + rho) * v,247 v - np.sign(v) * 2 * self._M / rho,248 )249 def subdiff_raw(self, v):250 v = np.asarray(v)251 ls = np.zeros(v.shape)252 rs = np.zeros(v.shape)253 abs_v = np.abs(v)254 ls[abs_v <= self._M] = 2 * v[abs_v <= self._M]255 rs[abs_v <= self._M] = 2 * v[abs_v <= self._M]256 ls[v > self._M] = 2 * self._M257 rs[v > self._M] = 2 * self._M258 ls[v < self._M] = -2 * self._M259 rs[v < self._M] = -2 * self._M260 return ls, rs261class IsInt(G):262 def __init__(self, weight, scale, shift):263 super().__init__(weight, scale, shift)264 self._is_convex = False265 def evaluate_raw(self, v):266 return np.where(267 np.isclose(np.mod(v, 1), 0) | np.isclose(np.mod(v, 1), 1), 0, np.inf268 )269 # TODO: change this to something like np.isclose(v, np.rint(v))270 def prox_raw(self, rho, v):271 return np.rint(v)272 def subdiff_raw(self, v):273 v = np.asarray(v)274 ls = np.nan * np.ones(v.shape)275 rs = np.nan * np.ones(v.shape)276 int_indices = self.evaluate_raw(v)277 ls[int_indices == 0] = 0278 rs[int_indices == 0] = 0279 return ls, rs280class IsFiniteSet(G):281 def __init__(self, weight, scale, shift, S):282 super().__init__(weight, scale, shift)283 self._S = np.array(list(S))284 self._is_convex = False285 def evaluate_raw(self, v):286 v = np.asarray(v)287 is_almost_in_S = np.isclose(v.reshape((-1, 1)), self._S.reshape((1, -1))).any(288 axis=1289 )290 return np.where(is_almost_in_S, 0, np.inf)291 def prox_raw(self, rho, v):292 v = np.asarray(v)293 diffs = np.subtract(v.reshape((-1, 1)), self._S.reshape((1, -1)))294 idx = np.argmin(np.abs(diffs), axis=1)295 return self._S[idx]296 def subdiff_raw(self, v):297 v = np.asarray(v)298 ls = np.nan * np.ones(v.shape)299 rs = np.nan * np.ones(v.shape)300 in_set_indices = self.evaluate_raw(v)301 ls[in_set_indices == 0] = 0302 rs[in_set_indices == 0] = 0303 return ls, rs304class IsBool(G):305 def __init__(self, weight, scale, shift):306 super().__init__(weight, scale, shift)307 self._S = np.array([0, 1])308 self._is_convex = False309 def evaluate_raw(self, v):310 v = np.asarray(v)311 is_almost_in_S = np.isclose(v.reshape((-1, 1)), self._S.reshape((1, -1))).any(312 axis=1313 )314 return np.where(is_almost_in_S, 0, np.inf)315 def prox_raw(self, rho, v):316 v = np.asarray(v)317 diffs = np.subtract(v.reshape((-1, 1)), self._S.reshape((1, -1)))318 idx = np.argmin(np.abs(diffs), axis=1)319 return self._S[idx]320 def subdiff_raw(self, v):321 v = np.asarray(v)322 ls = np.nan * np.ones(v.shape)323 rs = np.nan * np.ones(v.shape)324 is_bool_indices = self.evaluate_raw(v)325 ls[is_bool_indices == 0] = 0326 rs[is_bool_indices == 0] = 0327 return ls, rs328class GCollection:329 def __init__(self, g_list):330 self._g_list = []331 self._is_convex = True332 self._all_zeros = True333 for g in g_list:334 weight = 1335 scale = 1336 shift = 0337 if "args" in g and "weight" in g["args"]:338 weight = g["args"]["weight"]...
day18.py
Source:day18.py
...20 return value21# Regex to match open-parens ... closed-parens22# with no parens in between 23rgx = r"\([^\(]+?\)"24def evaluate_raw(raw: str) -> int:25 while (match := re.search(rgx, raw)):26 value = evaluate(match.group()[1:-1].split())27 raw = raw[:match.start()] + str(value) + raw[match.end():]28 else:29 tokens = raw.split()30 return evaluate(tokens)31def evaluate2(expression: Expression) -> int:32 """again assumes expression has no parens"""33 while len(expression) > 1:34 if "+" in expression:35 # find the plus and use it on the surrounding numbers36 i = expression.index("+")37 new_val = int(expression[i-1]) + int(expression[i+1])38 # and then put that result back39 expression = expression[:i-1] + [str(new_val)] + expression[i+2:]40 else:41 return evaluate(expression)42 return int(expression[0])43def evaluate_raw2(raw: str) -> int:44 while (match := re.search(rgx, raw)):45 value = evaluate2(match.group()[1:-1].split())46 raw = raw[:match.start()] + str(value) + raw[match.end():]47 else:48 tokens = raw.split()49 return evaluate2(tokens)50#51# unit tests52#53RAW = "1 + 2 * 3 + 4 * 5 + 6"54assert evaluate_raw(RAW) == 7155assert evaluate_raw2(RAW) == 23156RAW2 = "((2 + 4 * 9) * (6 + 9 * 8 + 6) + 6) + 2 + 4 * 2"57assert evaluate_raw(RAW2) == 1363258assert evaluate_raw2(RAW2) == 2334059#60# problem61#62with open('inputs/day18.txt') as f:63 raw = f.read()64 lines = raw.split("\n")65 print(sum(evaluate_raw(line) for line in lines))...
calc.py
Source:calc.py
...18 return value19# Regex to match open-parens ... closed-parens20# with no parens in between21rgx = r"\([^\(]+?\)"22def evaluate_raw(raw: str) -> int:23 while (match := re.search(rgx, raw)):24 value = evaluate(match.group()[1:-1].split())25 raw = raw[:match.start()] + str(value) + raw[match.end():]26 else:27 tokens = raw.split()28 return evaluate(tokens)29def evaluate2(expression: Expression) -> int:30 """again assumes expression has no parens"""31 while len(expression) > 1:32 if "+" in expression:33 # find the plus and use it on the surrounding numbers34 i = expression.index("+")35 new_val = int(expression[i-1]) + int(expression[i+1])36 # and then put that result back37 expression = expression[:i-1] + [str(new_val)] + expression[i+2:]38 else:39 return evaluate(expression)40 return int(expression[0])41def evaluate_raw2(raw: str) -> int:42 while (match := re.search(rgx, raw)):43 value = evaluate2(match.group()[1:-1].split())44 raw = raw[:match.start()] + str(value) + raw[match.end():]45 else:46 tokens = raw.split()47 return evaluate2(tokens)48#49# unit tests50#51RAW = "1 + 2 * 3 + 4 * 5 + 6"52assert evaluate_raw(RAW) == 7153assert evaluate_raw2(RAW) == 23154RAW2 = "((2 + 4 * 9) * (6 + 9 * 8 + 6) + 6) + 2 + 4 * 2"55assert evaluate_raw(RAW2) == 1363256assert evaluate_raw2(RAW2) == 2334057#58# problem59#60with open('input.txt') as f:61 raw = f.read()62 lines = raw.split("\n")63 print(sum(evaluate_raw(line) for line in lines))...
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