Shuntaro Ohno doraneko94
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| lst = [11, 10, 22, 10, 25] | |
| ans = 1 | |
| tolerance = 1e-4 | |
| size = len(lst) | |
| def n_merge(N): | |
| ans = N | |
| for i in range(1, N): | |
| ans *= i**2 | |
| return ans |
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| #include <iostream> | |
| using namespace std; | |
| int N, M, Q; | |
| int a[2010]; | |
| long long dp[2010][2010] = {0}; | |
| long long rdp[2010][2010] = {0}; | |
| long long accum[2010]; | |
| const long long mod = 1000000007; |
doraneko94
/ gamepad.py
Created
March 23, 2019 04:11
Controlling a mouse with a gamepad. This code is optimized for "LOGICOOL gamepad F301r".
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| import pygame | |
| from pygame.locals import * | |
| import time, sys | |
| import pyautogui | |
| def main(): | |
| pyautogui.FAILSAFE = False | |
| pygame.init() | |
| while True: |
doraneko94
/ roc_auc_ci.py
Last active
January 4, 2025 08:56
Calculating confidence interval of ROC-AUC.
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| from sklearn.metrics import roc_auc_score | |
| from math import sqrt | |
| def roc_auc_ci(y_true, y_score, positive=1): | |
| AUC = roc_auc_score(y_true, y_score) | |
| N1 = sum(y_true == positive) | |
| N2 = sum(y_true != positive) | |
| Q1 = AUC / (2 - AUC) | |
| Q2 = 2*AUC**2 / (1 + AUC) | |
| SE_AUC = sqrt((AUC*(1 - AUC) + (N1 - 1)*(Q1 - AUC**2) + (N2 - 1)*(Q2 - AUC**2)) / (N1*N2)) |
doraneko94
/ partial_transposition.py
Created
December 5, 2018 01:15
Calculating partial transposition.
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| import numpy as np | |
| from math import sqrt | |
| def partial_transposition(density_matrix: np.ndarray, basis_num_1: int=0, basis_num_2: int=0): | |
| if basis_num_1 == 0 and basis_num_2 == 0: | |
| basis_num_1 = int(sqrt(density_matrix.shape[0])) | |
| basis_num_2 = basis_num_1 | |
| elif basis_num_1 == 0: | |
| basis_num_1 = int((density_matrix.shape[0])/basis_num_2) | |
| elif basis_num_2 == 0: |
doraneko94
/ partial_dependence.py
Last active
December 7, 2018 01:50
Calculating partial dependence of any classifier which has an attribute of "n_features_" and "n_classes_".
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| import numpy as np | |
| from scipy.stats.mstats import mquantiles | |
| from math import sqrt, ceil | |
| from matplotlib import pyplot as plt | |
| def _grid_from_X(X, percentiles=(0.05, 0.95), grid_resolution=100): | |
| if len(percentiles) != 2: | |
| raise ValueError('percentile must be tuple of len 2') | |
| if not all(0. <= x <= 1. for x in percentiles): |
doraneko94
/ myfish.py
Created
November 25, 2018 22:04
"Hey, that's my fish!"-ish CUI game. Because this game is my study and not user-friendly, please buy this board game or official App if you want to really enjoy "Hey, that's my fish!"
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| import random | |
| alpha = ["A", "B", "C", "D"] | |
| fishes = [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, | |
| 2,2,2,2,2,2,2,2,2,2, | |
| 2,2,2,2,2,2,2,2,2,2, | |
| 3,3,3,3,3,3,3,3,3,3] | |
| f = random.sample(fishes, len(fishes)) |
doraneko94
/ caesar_dictionary.py
Last active
November 6, 2018 06:54
The improved version of "caesar.py" using a list of 153,484 words. "dictionary.pkl" is available from http://ushitora.net/archives/456 .
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| import pickle | |
| ALPHA = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"] | |
| alpha = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"] | |
| word = input("Please Enter Words: ") | |
| def plus_i(i, w): | |
| if w in alpha: | |
| n = alpha.index(w) + i |
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| import math, tkinter, time, sys | |
| g = 9.8 | |
| m1 = 1 | |
| m2 = 1 | |
| l1 = 150 | |
| l2 = 150 | |
| dt = 0.1 | |
| theta1 = math.pi / 2 | |
| theta2 = math.pi / 2 #+ 0.02 |
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| ALPHA = ["A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z"] | |
| alpha = ["a", "b", "c", "d", "e", "f", "g", "h", "i", "j", "k", "l", "m", "n", "o", "p", "q", "r", "s", "t", "u", "v", "w", "x", "y", "z"] | |
| word = input("Please Enter Words: ") | |
| for i in range(len(alpha)): | |
| process = "" | |
| for w in word: | |
| if w in alpha: | |
| n = alpha.index(w) + i | |
| if n > 25: |