code stringlengths 10 2.58M | original_code stringlengths 3 3.18M | original_language stringclasses 1
value | source stringclasses 7
values |
|---|---|---|---|
string @author: Yawar Azad
function knn data query k
begin
set neighbor_distances_and_indices = list
for tuple index example in enumerate data
begin
set distance = call euclidean_distance example at slice : - 1 : query
append neighbor_distances_and_indices tuple distance index
end
set sorted_neighbor_distances_and_i... | '''
@author: Yawar Azad
'''
def knn(data, query, k):
neighbor_distances_and_indices = []
for index, example in enumerate(data):
distance = euclidean_distance(example[:-1], query)
neighbor_distances_and_indices.append((distance, index))
sorted_neighbor_distances_and_indices = sorted(n... | Python | zaydzuhri_stack_edu_python |
comment Two arrays merged in ascending order
comment ex- arr=[1 ,2 ,4,6, 8 ]
comment arr1 = [3,5,6,7]
function place arr m
begin
set n = length arr
for i in range n
begin
if m <= arr at i
begin
append arr 0
for j in range n i - 1
begin
set arr at j = arr at j - 1
end
set arr at i = m
break
end
else
if arr at i <= m and... | #Two arrays merged in ascending order
#ex- arr=[1 ,2 ,4,6, 8 ]
# arr1 = [3,5,6,7]
def place(arr,m):
n = len(arr)
for i in range(n):
if m <= arr[i]:
arr.append(0)
for j in range(n,i,-1):
arr[j] = arr[j-1]
arr[i] = m
break
elif arr[i... | Python | zaydzuhri_stack_edu_python |
function adjust_transition_probabilities self probabilities min_prob penalty_multiplier=1.0
begin
set variable_region = 1 - min_prob
set scale_ratio = 1 / variable_region
set adjusted_probabilities = dict
for k in probabilities
begin
set adjusted_probabilities at k = probabilities at k * penalty_multiplier / scale_rat... | def adjust_transition_probabilities(self, probabilities, min_prob, penalty_multiplier=1.0):
variable_region = 1 - min_prob
scale_ratio = 1 / variable_region
adjusted_probabilities = {}
for k in probabilities:
adjusted_probabilities[k] = ((probabilities[k]*penalty_multiplier) ... | Python | nomic_cornstack_python_v1 |
import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.model_selection import KFold
function question_10_b_c set_d set_t sigma
begin
string :param set_d: :param set_t: :return:
set set_s = set_d at tuple slice : 500 : 0
set labels_s = set_d at tuple slice ... | import numpy as np
import matplotlib.pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.model_selection import KFold
def question_10_b_c(set_d, set_t, sigma):
"""
:param set_d:
:param set_t:
:return:
"""
set_s = set_d[:500, 0]
labels_s = set_d[:500, 1]
se... | Python | zaydzuhri_stack_edu_python |
from rest_framework import serializers
from django.contrib.auth.models import User
comment from .models import *
from django.db.models import Q
class UserProfileSerializer extends ModelSerializer
begin
class Meta
begin
set model = User
set fields = tuple string pk string password string last_login string is_superuser s... | from rest_framework import serializers
from django.contrib.auth.models import (User)
# from .models import *
from django.db.models import Q
class UserProfileSerializer(serializers.ModelSerializer):
class Meta:
model = User
fields = ('pk', 'password', 'last_login', 'is_superuser', 'username',
... | Python | zaydzuhri_stack_edu_python |
function PostMessage self codereview_url message
begin
raise call NotImplemented
end function | def PostMessage(self, codereview_url, message):
raise NotImplemented() | Python | nomic_cornstack_python_v1 |
import numpy as np
import pandas as pd
from sklearn import svm
set nsample = 4000
set X_train = array read csv string X_train.csv header=none
set y_train = array ix at tuple slice : : 0
set X_test = array read csv string X_test.csv header=none
comment use the first 4000 samples for training
set XTrain = X_train at t... | import numpy as np
import pandas as pd
from sklearn import svm
nsample = 4000
X_train = np.array(pd.read_csv("X_train.csv",header=None))
y_train = np.array(pd.read_csv("y_train.csv",header=None).ix[:,0])
X_test = np.array(pd.read_csv("X_test.csv",header=None))
XTrain = X_train[:nsample,:] #use the first 4000 samples... | Python | zaydzuhri_stack_edu_python |
function number_of_days_past_start_date config
begin
set start_date_parts = split config at string start_date string -
set start_date = call date integer start_date_parts at 2 integer start_date_parts at 1 integer start_date_parts at 0
comment Get the day - starting from one
set todays_date = today
set days_past_start_... | def number_of_days_past_start_date(config):
start_date_parts = config['start_date'].split('-')
start_date = date(int(start_date_parts[2]), int(start_date_parts[1]), int(start_date_parts[0]))
# Get the day - starting from one
todays_date = date.today()
days_past_start_date = (todays_date - start_dat... | Python | nomic_cornstack_python_v1 |
function remote_url self
begin
return get config string remote-server
end function | def remote_url(self):
return self.config.get('remote-server') | Python | nomic_cornstack_python_v1 |
function getInputSpecification cls
begin
set specs = call getInputSpecification
set description = string The \xmlNode{NuSVR} \textit{Nu-Support Vector Regression} is an Nu-Support Vector Regressor. It is very similar to SVC but with the addition of the hyper-parameter Nu for controlling the number of support vectors. H... | def getInputSpecification(cls):
specs = super(NuSVR, cls).getInputSpecification()
specs.description = r"""The \xmlNode{NuSVR} \textit{Nu-Support Vector Regression} is an Nu-Support Vector Regressor.
It is very similar to SVC but with the addition of the hyper-parameter Nu for control... | Python | nomic_cornstack_python_v1 |
import requests
from bs4 import BeautifulSoup
import os
set url = string https://en.wikipedia.org/wiki/Deep_learning
set source_code = get requests url
set plain_text = text
set soup = call BeautifulSoup plain_text string html.parser
comment result_list=soup.findALL("a")
for div in find all string a
begin
print get div... | import requests
from bs4 import BeautifulSoup
import os
url="https://en.wikipedia.org/wiki/Deep_learning"
source_code=requests.get(url)
plain_text=source_code.text
soup=BeautifulSoup(plain_text,"html.parser")
#result_list=soup.findALL("a")
for div in soup.findAll('a'):
print(div.get("href")) | Python | zaydzuhri_stack_edu_python |
string This Example sends harcoded data to Ubidots using the request HTTP library. Please install the library using pip install requests Made by Jose García @https://github.com/jotathebest/
import requests
import random
import time
string global variables
set ENDPOINT = string things.ubidots.com
set DEVICE_LABEL = stri... | '''
This Example sends harcoded data to Ubidots using the request HTTP
library.
Please install the library using pip install requests
Made by Jose García @https://github.com/jotathebest/
'''
import requests
import random
import time
'''
global variables
'''
ENDPOINT = "things.ubidots.com"
DEVICE_LABEL = "flaskServ... | Python | zaydzuhri_stack_edu_python |
comment ************************************************************************
comment Apple Store Data Set Preparation
comment ************************************************************************
comment Some of the exercises use the app store data set, which is available from Kaggla at
comment https://www.kaggl... | # ************************************************************************
# Apple Store Data Set Preparation
# ************************************************************************
# Some of the exercises use the app store data set, which is available from Kaggla at
# https://www.kaggle.com/ramamet4/app-store-appl... | Python | zaydzuhri_stack_edu_python |
function get_badges ids start_date=none end_date=none
begin
set path = string badges/%s % call __join ids
set params = call __translate copy locals _tag_badge_orders
return call fetch path string badges keyword params
end function | def get_badges(ids, start_date=None, end_date=None):
path = "badges/%s" % __join(ids)
params = __translate(locals().copy(), _tag_badge_orders)
return _site.fetch(path, "badges", **params) | Python | nomic_cornstack_python_v1 |
function download_fasta protein_list folder
begin
set sequence_folder = format string {}/protein_sequences folder
for protein in protein_list
begin
if ends with protein string .DS_Store
begin
continue
end
set url = string http://www.uniprot.org/uniprot/ + protein + string .fasta
set wait = uniform 0.1 1.0
set result = ... | def download_fasta(protein_list, folder):
sequence_folder = "{}/protein_sequences".format(folder)
for protein in protein_list:
if protein.endswith('.DS_Store'):
continue
url = 'http://www.uniprot.org/uniprot/' + protein + '.fasta'
wait = random.uniform(0.1, 1.0)
resul... | Python | nomic_cornstack_python_v1 |
comment 先練習小數除法、整數除法、餘數的語法
comment 小數除法
set x = 7 / 5
print string 這是 7 除以 5 的r: x
comment 整數除法
set x = 7 // 5
print string 這是 7 除以 5 的整除部分: x
comment 餘數
set x = 7 % 5
print string 這是 7 除以 5 的餘數: x | # 先練習小數除法、整數除法、餘數的語法
# 小數除法
x=7/5
print("這是 7 除以 5 的r: ", x)
# 整數除法
x=7//5
print("這是 7 除以 5 的整除部分: ", x)
# 餘數
x=7%5
print("這是 7 除以 5 的餘數: ", x)
| Python | zaydzuhri_stack_edu_python |
function get_coordinates self params
begin
set element = params at string element
set coordination = params at string coordination
set OH_frac = params at string OH
set OH2_frac = params at string OH2
set Nmax = params at string Nmax
set dMOH = params at string dMOH
set dMOH2 = params at string dMOH2
set angle = params... | def get_coordinates(self,params):
element = params['element']
coordination = params['coordination']
OH_frac = params['OH']
OH2_frac = params['OH2']
Nmax = params['Nmax']
dMOH = params['dMOH']
dMOH2 = params['dMOH2']
angle = params['<MOH']
if(coord... | Python | nomic_cornstack_python_v1 |
comment Escreva um programa que leia um valor em metros e exiba o valor convertido em centimetros e milimetros
set valor_metros = integer input string Digite um valor em metros:
print format string valor em centrimetros : {} valor em milimetros: {} valor_metros * 100 valor_metros * 1000 | #Escreva um programa que leia um valor em metros e exiba o valor convertido em centimetros e milimetros
valor_metros = int(input('Digite um valor em metros: '))
print('valor em centrimetros : {} valor em milimetros: {}'.format(valor_metros*100,valor_metros*1000)) | Python | zaydzuhri_stack_edu_python |
string Contains all the attacks on discretized inputs. The attacks implemented are Discrete Gradient Ascent (DGA) and Logit Space-Projected Gradient Ascent (LS-PGA).
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf
im... | """Contains all the attacks on discretized inputs.
The attacks implemented are Discrete Gradient Ascent (DGA) and
Logit Space-Projected Gradient Ascent (LS-PGA).
"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import tensorflow as tf... | Python | zaydzuhri_stack_edu_python |
function initWorker
begin
print string Initializing new poolWorker process: %s. % call current_process
comment Ignore signal interrupts in the poolWorker process
call signal SIGINT SIG_IGN
end function | def initWorker():
print("Initializing new poolWorker process: %s." % multiprocessing.current_process())
# Ignore signal interrupts in the poolWorker process
signal.signal(signal.SIGINT, signal.SIG_IGN) | Python | nomic_cornstack_python_v1 |
import sys
import os
set target_dir = argv at 1
set file_list = list directory target_dir
for file in file_list
begin
set f = open target_dir + file string r
comment print("file: %s" %file)
set dump = read f
if string 0000 in dump
begin
print file
end
close f
end | import sys
import os
target_dir=sys.argv[1]
file_list=os.listdir(target_dir)
for file in file_list:
f=open(target_dir+file, 'r')
#print("file: %s" %file)
dump=f.read()
if "0000" in dump:
print(file)
f.close()
| Python | zaydzuhri_stack_edu_python |
function get_contributors self
begin
raise NotImplementedError
end function | def get_contributors(self):
raise NotImplementedError | Python | nomic_cornstack_python_v1 |
function ferret_init id
begin
set axes_values = list AXIS_DOES_NOT_EXIST * MAX_FERRET_NDIM
set axes_values at 0 = AXIS_CUSTOM
set false_influences = list false * MAX_FERRET_NDIM
set retdict = dict string numargs 1 ; string descript string Returns the (unweighted) mean, variance, skew, and excess kurtosis of an array of... | def ferret_init(id):
axes_values = [ pyferret.AXIS_DOES_NOT_EXIST ] * pyferret.MAX_FERRET_NDIM
axes_values[0] = pyferret.AXIS_CUSTOM
false_influences = [ False ] * pyferret.MAX_FERRET_NDIM
retdict = { "numargs": 1,
"descript": "Returns the (unweighted) mean, variance, skew, and excess ku... | Python | nomic_cornstack_python_v1 |
function construct_seq ind_i
begin
set track_i = track_list at ind_i
set select_indices_i = call sample_rois
set seq_roi_list = list comprehension roi_list at i for i in select_indices_i
return seq_roi_list
end function | def construct_seq(ind_i):
track_i = track_list[ind_i]
select_indices_i = track_i.sample_rois()
seq_roi_list = [track_i.roi_list[i] for i in select_indices_i]
return seq_roi_list | Python | nomic_cornstack_python_v1 |
import re
print string dir(re): directory re
set matched_var = compile string \d\d-\d\d\d-\d\d\d
set str_var = string 11-111-111 is my number
set holder = search str_var
print string Searched Pattern: call group
set emails = string law@email.com is the orig and not the lawrence@yopmail.com also not this one 24.353
set ... | import re
print("dir(re): ", dir(re))
matched_var = re.compile(r'\d\d-\d\d\d-\d\d\d')
str_var = "11-111-111 is my number"
holder = matched_var.search(str_var)
print("Searched Pattern: ", holder.group())
emails = "law@email.com is the orig and not the lawrence@yopmail.com also not this one 24.353"
emails_holder = re.... | Python | zaydzuhri_stack_edu_python |
function test_create_order_status_code self
begin
assert equal status_code HTTP_201_CREATED
end function | def test_create_order_status_code(self):
self.assertEqual(self.response.status_code, status.HTTP_201_CREATED) | Python | nomic_cornstack_python_v1 |
from sklearn import svm , metrics
from sklearn.model_selection import train_test_split
import pandas as pd
set csv = read csv string iris.csv
set csv_data = csv at list string SepalLength string SepalWidth string PetalLength string PetalWidth
set csv_label = csv at string Name
set total_len = length csv
set train_len =... | from sklearn import svm, metrics
from sklearn.model_selection import train_test_split
import pandas as pd
csv = pd.read_csv('iris.csv')
csv_data = csv[["SepalLength","SepalWidth","PetalLength","PetalWidth"]]
csv_label = csv["Name"]
total_len = len(csv)
train_len = int(total_len *2 / 3)
train_data, test_data, train_l... | Python | zaydzuhri_stack_edu_python |
function setUp self
begin
set staff = call create_user email=string staff@curesio.com password=string staffpassword1234 username=string staffusername
set is_staff = true
save
call refresh_from_db
set client = call APIClient
call force_authenticate user=staff
set speciality = call create name=string Speciality
set paylo... | def setUp(self):
self.staff = get_user_model().objects.create_user(
email='staff@curesio.com',
password='staffpassword1234',
username='staffusername'
)
self.staff.is_staff = True
self.staff.save()
self.staff.refresh_from_db()
self.clie... | Python | nomic_cornstack_python_v1 |
function task_completed self completion_time
begin
set completed_tasks_count = completed_tasks_count + 1
set end_time = max completion_time end_time
assert completed_tasks_count <= num_tasks
return num_tasks == completed_tasks_count
end function | def task_completed(self, completion_time):
self.completed_tasks_count += 1
self.end_time = max(completion_time, self.end_time)
assert self.completed_tasks_count <= self.num_tasks
return self.num_tasks == self.completed_tasks_count | Python | nomic_cornstack_python_v1 |
function n_remaining_samples self
begin
return - 1
end function | def n_remaining_samples(self):
return -1 | Python | nomic_cornstack_python_v1 |
function can_remove_spec self cluster_spec
begin
set msg = call attempt_remove_spec cluster_spec
return length msg == 0
end function | def can_remove_spec(self, cluster_spec):
msg = self.attempt_remove_spec(cluster_spec)
return len(msg) == 0 | Python | nomic_cornstack_python_v1 |
function primary_key_tuple self item
begin
if hash_key is none
begin
raise call ValueError string Missing hash key
end
if range_key is none
begin
return tuple item at name
end
else
begin
return tuple item at name item at name
end
end function | def primary_key_tuple(self, item: Dict) -> Union[Tuple[str], Tuple[str, str]]:
if self.hash_key is None:
raise ValueError("Missing hash key")
if self.range_key is None:
return (item[self.hash_key.name],)
else:
return (item[self.hash_key.name], item[self.range_... | Python | nomic_cornstack_python_v1 |
import os , operator , sys
import pandas as pd
set dirpath = absolute path path argv at 0
set dirpath = join string / split dirpath string / at slice : - 1 : + string /csv files
comment make a generator for all file paths within dirpath
set all_files = generator expression join path basedir filename for tuple basedir ... | import os, operator, sys
import pandas as pd
dirpath = os.path.abspath(sys.argv[0])
dirpath = "/".join(dirpath.split("/")[:-1]) + "/csv files"
# make a generator for all file paths within dirpath
all_files = (os.path.join(basedir, filename) for basedir, dirs, files in os.walk(dirpath) for filename in files)
# sort f... | Python | zaydzuhri_stack_edu_python |
function create_subparser self parent storage
begin
call create_subparser parent storage
import argparse
comment Create 'cot deploy ... esxi' parser
set p = call add_parser string esxi parents=list generic_parser usage=call fill_usage string deploy PACKAGE esxi list string LOCATOR [-u USERNAME] [-p PASSWORD] [-c CONFIG... | def create_subparser(self, parent, storage):
super(COTDeployESXi, self).create_subparser(parent, storage)
import argparse
# Create 'cot deploy ... esxi' parser
p = self.subparsers.add_parser(
'esxi', parents=[self.generic_parser],
usage=self.UI.fill_usage("deploy... | Python | nomic_cornstack_python_v1 |
import urllib2 , socket
call setdefaulttimeout 180
set fproxy = string proxylist.txt
with open fproxy as f
begin
set proxyList = read lines f
end
set proxyList = list comprehension strip x for x in proxyList
set fsite = string urllist.txt
with open fsite as f
begin
set siteList = read lines f
end
set siteList = list co... | import urllib2, socket
socket.setdefaulttimeout(180)
fproxy = "proxylist.txt"
with open(fproxy) as f:
proxyList = f.readlines()
proxyList = [x.strip() for x in proxyList]
fsite = "urllist.txt"
with open(fsite) as f:
siteList = f.readlines()
siteList = [x.strip() for x in siteList]
| Python | zaydzuhri_stack_edu_python |
import json
import tensorflow as tf
import torch
from math import log
class Tokenizer
begin
function __init__ self
begin
set eos_token = string <|endoftext|>
set eos_token_id = 0
set name = string オリバー
comment Taken from https://stackoverflow.com/questions/8870261/how-to-split-text-without-spaces-into-list-of-words
set... | import json
import tensorflow as tf
import torch
from math import log
class Tokenizer:
def __init__(self) -> None:
self.eos_token = "<|endoftext|>"
self.eos_token_id = 0
self.name = "オリバー"
# Taken from https://stackoverflow.com/questions/8870261/how-to-split-text-without-spaces-int... | Python | zaydzuhri_stack_edu_python |
string You are given a number N, you have to print the number of integers less than N in the sample space S. The first line contains an integer N, denoting the number. Print the count 9 2 36 5 1000000 999 5 1 24 3 From sample: Numbers are 4 = 1^2 * 2^2, 9 = 1^2 * 3^2, 16 = 1^2 * 4^2, 25 = 1^2 * 5^2, 36 = 1^2 * 6^2 coun... | """
You are given a number N, you have to print the number of integers less than N in the sample space S.
The first line contains an integer N, denoting the number.
Print the count
9
2
36
5
1000000
999
5
1
24
3
From sample:
Numbers are 4 = 1^2 * 2^2,
9 = 1^2 * 3^2,
16 = 1^2 ... | Python | zaydzuhri_stack_edu_python |
comment -*- coding: utf-8 -*-
comment @Time : 2020/7/5 21:48
class Solution
begin
function lengthOfLongestSubstring self s
begin
comment 哈希集合，记录每个字符是否出现过
set occ = set
set n = length s
comment 右指针，初始值为 -1，相当于我们在字符串的左边界的左侧，还没有开始移动
set tuple rk ans = tuple - 1 0
for i in range n
begin
if i != 0
begin
comment 左指针向右移动一格，移除... | # -*- coding: utf-8 -*-
# @Time : 2020/7/5 21:48
class Solution:
def lengthOfLongestSubstring(self, s: str) -> int:
# 哈希集合，记录每个字符是否出现过
occ = set()
n = len(s)
# 右指针，初始值为 -1，相当于我们在字符串的左边界的左侧，还没有开始移动
rk, ans = -1, 0
for i in range(n):
if i != 0:
... | Python | zaydzuhri_stack_edu_python |
from Tkinter import *
import sys | from Tkinter import *
import sys
| Python | zaydzuhri_stack_edu_python |
function match_loop npc_boss
begin
string This is a description of the functions executed in a loop of each match looks like: shop(): Player decides whether to purchase the cards (items) in the shop prepare(): Player chooses the chamber to insert the bullet and spin the gun use_buff(): Player decides whether to use buf... | def match_loop(npc_boss):
"""
This is a description of the functions executed in a loop of each match looks like:
shop(): Player decides whether to purchase the cards (items) in the shop
prepare(): Player chooses the chamber to insert the bullet and spin the gun
use_... | Python | nomic_cornstack_python_v1 |
function test_save_dict test_app redis_service
begin
set test_dict = dict 1 string test ; 2 string test1 ; 3 string test2
assert not call save_dict test_dict
end function
function test_validate_for_keys test_app redis_service
begin
set test_keys = set literal string 1 string 2 string 3
set result = call validate_for_ke... | def test_save_dict(test_app, redis_service):
test_dict = {
1: 'test',
2: 'test1',
3: 'test2'
}
assert not redis_service.save_dict(test_dict)
def test_validate_for_keys(test_app, redis_service):
test_keys = {'1', '2', '3'}
result = redis_service.validate_for_keys(test_keys... | Python | zaydzuhri_stack_edu_python |
function compute_sum array
begin
set sum = 0
for element in array
begin
set sum = sum + element
end
return sum
end function
if __name__ == string __main__
begin
set array = list 1 2 3 4 5
print call compute_sum array
end | def compute_sum(array):
sum = 0
for element in array:
sum += element
return sum
if __name__ == '__main__':
array = [1, 2, 3, 4, 5]
print(compute_sum(array)) | Python | iamtarun_python_18k_alpaca |
function final_output self outputs keys_length
begin
comment [B, T, H]
set tuple batch_size hist_len _ = shape
set mask = repeat batch_size 1 == view keys_length - 1 1 - 1
return outputs at mask
end function | def final_output(self, outputs, keys_length):
batch_size, hist_len, _ = outputs.shape # [B, T, H]
mask = torch.arange(hist_len, device=keys_length.device).repeat(
batch_size, 1
) == (keys_length.view(-1, 1) - 1)
return outputs[mask] | Python | nomic_cornstack_python_v1 |
comment -*- coding:utf-8 -*-
import tensorflow as tf
import numpy as np
from utils.feature.normalization import Normalization as norm
comment 模型数据
comment 1.模型
class Linear
begin
function __init__ self dic_config
begin
set logger = get dic_config string logger none
set model_path = dic_config at string model_path
set m... | # -*- coding:utf-8 -*-
import tensorflow as tf
import numpy as np
from utils.feature.normalization import Normalization as norm
# 模型数据
# 1.模型
class Linear:
def __init__(self, dic_config):
self.logger = dic_config.get('logger', None)
self.model_path = dic_config['model_path']
self.mean_std_... | Python | zaydzuhri_stack_edu_python |
while f
begin
set ele = call raw_input string Enter the text:
write fd ele
write fd string
set opt = call raw_input string Do you want to continue: yes or no
if lower opt in list string yes string y
begin
set f = true
end
else
begin
set f = false
end
end
close fd | while f:
ele=raw_input("Enter the text:")
fd.write(ele)
fd.write('\n')
opt=raw_input("Do you want to continue: yes or no")
if opt.lower() in ['yes','y']:
f=True
else:
f=False
fd.close() | Python | zaydzuhri_stack_edu_python |
function get_results_json self
begin
set res = dictionary
set res at string test_name = test_name
set res at string test_duration = test_time
set res at string total_auths = total_auths
set res at string nanoseconds_since_auth = list
set res at string nanoseconds_since_registration = list
for name in call get_names
beg... | def get_results_json(self) -> str:
res = dict()
res["test_name"] = self.test_name
res["test_duration"] = self.test_time
res["total_auths"] = self.total_auths
res["nanoseconds_since_auth"] = list()
res["nanoseconds_since_registration"] = list()
for name in self.get... | Python | nomic_cornstack_python_v1 |
import numpy as np
from Bio.Seq import Seq
function hamming_distance s t
begin
set counter = 0
set first_seq = call Seq s
set second_seq = call Seq t
for i in range length first_seq
begin
if first_seq at i != second_seq at i
begin
set counter = counter + 1
end
else
begin
continue
end
end
return counter
end function
fun... | import numpy as np
from Bio.Seq import Seq
def hamming_distance(s,t):
counter=0
first_seq = Seq(s)
second_seq = Seq(t)
for i in range(len(first_seq)):
if first_seq[i]!= second_seq[i]:
counter+=1
else: continue
return counter
def LastSymbol(Pattern):
... | Python | zaydzuhri_stack_edu_python |
for i in range n
begin
append d at arr at i % k arr at i
end
set count = 0
if length d at 0 > 0
begin
set count = 1
end
set S = set list comprehension tuple x k - x for x in range 1 k // 2 + 1
for tuple i j in S
begin
if i != j
begin
if length d at i > length d at j
begin
set count = count + length d at i
end
else
begi... | for i in range(n): d[arr[i]%k].append(arr[i])
count = 0
if len(d[0]) > 0:
count = 1
S = set([(x,k-x) for x in range(1,k//2+1)])
for i,j in S:
if i != j:
if len(d[i]) > len(d[j]):
count += len(d[i])
else:
count += len(d[j])
else:
if len(d[i]) > 0:
... | Python | zaydzuhri_stack_edu_python |
function fastHealing self
begin
for q in _parsedSpecialQualities
begin
if type == string fastHealing
begin
return amount
end
end
end function | def fastHealing(self):
for q in self._parsedSpecialQualities:
if q.type == 'fastHealing':
return q.amount | Python | nomic_cornstack_python_v1 |
import urllib.request
from bs4 import BeautifulSoup
from JobDiary.scraper import dictionary
class MilkroundScraper
begin
function __init__ self url
begin
set page = url open url
set soup = call BeautifulSoup page string html.parser
end function
function get_credentials self
begin
return list call get_title call get_com... | import urllib.request
from bs4 import BeautifulSoup
from JobDiary.scraper import dictionary
class MilkroundScraper:
def __init__(self, url):
page = urllib.request.urlopen(url)
self.soup = BeautifulSoup(page, 'html.parser')
def get_credentials(self):
return [self.get_title(),
... | Python | zaydzuhri_stack_edu_python |
function delete key
begin
set path = string %s/%s % tuple DROPBOX_PROJECT_PATH key
while string // in path
begin
set path = replace path string // string /
end
try
begin
set res = call files_delete_v2 path
end
except ApiError as err
begin
raise call BadRequest DELETE_FAILED
end
set data = metadata
return data
end funct... | def delete(key):
path = '%s/%s' % (DROPBOX_PROJECT_PATH, key)
while '//' in path:
path = path.replace('//', '/')
try:
res = dbx.files_delete_v2(path)
except dropbox.exceptions.ApiError as err:
raise BadRequest(Code.DELETE_FAILED)
data = res.metadata
return data | Python | nomic_cornstack_python_v1 |
import tensorflow as tf
function extract_data file_path
begin
comment string input producer to read file a line
set filename_queue = call string_input_producer list file_path
comment skip the header skip_header_lines=1
set reader = call TextLineReader skip_header_lines=1
set tuple key value = read reader filename_queue... | import tensorflow as tf
def extract_data(file_path):
#string input producer to read file a line
filename_queue = tf.train.string_input_producer([file_path])
#skip the header skip_header_lines=1
reader = tf.TextLineReader(skip_header_lines=1)
key, value = reader.read(filename_queue)
rec... | Python | zaydzuhri_stack_edu_python |
comment !/usr/bin/env python3
class Solution
begin
function __init__ self
begin
set posX = 0
set posY = 0
end function
function validateInput self moves
begin
if type moves != str
begin
raise call TypeError string Moves shoud be string.
end
end function
function judgeCircle self moves
begin
call validateInput moves
for... | #!/usr/bin/env python3
class Solution:
def __init__(self):
self.posX = 0
self.posY = 0
def validateInput(self, moves):
if type(moves) != str:
raise TypeError("Moves shoud be string.")
def judgeCircle(self, moves: str) -> bool:
self.validateInput(moves)
... | Python | zaydzuhri_stack_edu_python |
function remove_repetidos lista_numeros
begin
set listaSemNumeroRepetido = list
for n in lista_numeros
begin
if not n in listaSemNumeroRepetido
begin
append listaSemNumeroRepetido n
end
end
return sorted listaSemNumeroRepetido
end function
print call remove_repetidos list 2 4 2 2 3 3 1 | def remove_repetidos(lista_numeros):
listaSemNumeroRepetido = []
for n in lista_numeros:
if not n in listaSemNumeroRepetido:
listaSemNumeroRepetido.append(n)
return sorted(listaSemNumeroRepetido)
print(remove_repetidos([2,4,2,2,3,3,1])) | Python | zaydzuhri_stack_edu_python |
string Created on Jun 2, 2014 @author: Sean
from math import sqrt
from sys import argv
import random
function add_vectors a b
begin
string Add vectors a and b
return list comprehension a at i + b at i for i in range length a
end function
function multiply_scalar_vector alpha vec
begin
string Multiply vector vec with sc... | '''
Created on Jun 2, 2014
@author: Sean
'''
from math import sqrt
from sys import argv
import random
def add_vectors(a, b):
'''Add vectors a and b '''
return [a[i]+b[i] for i in range(len(a))]
def multiply_scalar_vector(alpha, vec):
'''Multiply vector vec with scalar alpha '''
return [alpha*f for f... | Python | zaydzuhri_stack_edu_python |
comment noqa: E501 # noqa: E501
function __init__ self assign_names_using=none prestage_device_names=none device_name_prefix=none device_name_suffix=none single_device_name=none manage_names=none device_naming_configured=none local_vars_configuration=none
begin
if local_vars_configuration is none
begin
set local_vars_c... | def __init__(self, assign_names_using=None, prestage_device_names=None, device_name_prefix=None, device_name_suffix=None, single_device_name=None, manage_names=None, device_naming_configured=None, local_vars_configuration=None): # noqa: E501 # noqa: E501
if local_vars_configuration is None:
local_... | Python | nomic_cornstack_python_v1 |
function semver
begin
return join string . list comprehension string v for v in VERSION
end function | def semver():
return ".".join([str(v) for v in VERSION]) | Python | nomic_cornstack_python_v1 |
function guestCount self
begin
return length guests
end function | def guestCount(self):
return len( self.guests ) | Python | nomic_cornstack_python_v1 |
function get_retcode self
begin
if retcode is none
begin
set retcode = poll process
end
return retcode
end function | def get_retcode(self):
if self.retcode is None:
self.retcode = self.process.poll()
return self.retcode | Python | nomic_cornstack_python_v1 |
function _to_lems_unit unit
begin
if type unit == str
begin
set strunit = unit
end
else
begin
set strunit = call in_best_unit
comment here we substract '1. '
set strunit = strunit at slice 3 : :
end
comment in LEMS there is no ^
set strunit = replace strunit string ^ string
return strunit
end function | def _to_lems_unit(unit):
if type(unit) == str:
strunit = unit
else:
strunit = unit.in_best_unit()
strunit = strunit[3:] # here we substract '1. '
strunit = strunit.replace('^', '') # in LEMS there is no ^
return strunit | Python | nomic_cornstack_python_v1 |
string Implements armasubsets in R, using naive feature subset search (exhaustive, beam forward or beam backward) rather than R's regsubsets.
import numpy as np
import pandas as pd
from itertools import chain , combinations
import heapq
from statsmodels.tsa.ar_model import AutoReg
from statsmodels.regression.linear_mod... | """
Implements armasubsets in R, using naive feature subset search (exhaustive,
beam forward or beam backward) rather than R's regsubsets.
"""
import numpy as np
import pandas as pd
from itertools import chain, combinations
import heapq
from statsmodels.tsa.ar_model import AutoReg
from statsmodels.regression.linear_... | Python | zaydzuhri_stack_edu_python |
function reverse_string my_str
begin
set rev_str = string
for i in my_str
begin
set rev_str = i + rev_str
end
return rev_str
end function
set my_str = string Hello World
call reverse_string my_str | def reverse_string(my_str):
rev_str = ""
for i in my_str:
rev_str = i + rev_str
return rev_str
my_str = 'Hello World'
reverse_string(my_str) | Python | jtatman_500k |
function filter_by_freq tsv_name
begin
comment open the tsv to be filtered
set tsv = open tsv_name string r
comment create names for the new tsvs by adding _u1 and _u5 to the end of the original tsv name
set filtered_5_tsv_name = string u5.tsv
comment tsv_name.split('.')[0] + '_u5.tsv'
set filtered_1_tsv_name = string ... | def filter_by_freq(tsv_name):
#open the tsv to be filtered
tsv = open(tsv_name, 'r')
#create names for the new tsvs by adding _u1 and _u5 to the end of the original tsv name
filtered_5_tsv_name = 'u5.tsv'
#tsv_name.split('.')[0] + '_u5.tsv'
filtered_1_tsv_name = 'u1.tsv'
#tsv_name.spl... | Python | nomic_cornstack_python_v1 |
function amount_paid self
begin
return call Decimal sum list comprehension amount for x in all
end function | def amount_paid(self) -> Decimal:
return Decimal(sum([x.amount for x in self.payments.all()])) | Python | nomic_cornstack_python_v1 |
import math
function samesign a b
begin
return a * b > 0
end function
function bisect func low high
begin
assert not call samesign call func low call func high
for i in range 50
begin
set midpoint = low + high / 2.0
if call samesign call func low call func midpoint
begin
set low = midpoint
end
else
begin
set high = mid... | import math
def samesign(a,b):
return a*b >0
def bisect(func,low,high):
assert not samesign(func(low),func(high))
for i in range(50):
midpoint=(low + high)/2.0
if samesign(func(low),func(midpoint)):
low=midpoint
else:
high=midpoint
return midpoint
def f(x):
return 2*math.sin(0.9*x)-math.tan(x)
x=bi... | Python | zaydzuhri_stack_edu_python |
function _save_data self
begin
call export
end function | def _save_data(self):
self.widgets.exporter.export() | Python | nomic_cornstack_python_v1 |
function docstring_section obj section lines indent
begin
set docs = list
for line in lines
begin
set replaced = false
for tuple pattern replacer in PATTERNS
begin
set match = match pattern strip line
if match
begin
set key = call groups at 0
set context = lower __name__
if section
begin
set context = context + lower ... | def docstring_section(obj: Any, section: str, lines: List[str], indent: str):
docs = []
for line in lines:
replaced = False
for pattern, replacer in PATTERNS:
match = re.match(pattern, line.strip())
if match:
key = match.groups()[0]
context... | Python | nomic_cornstack_python_v1 |
import copy
import logging
from collections import Counter
from pathlib import Path
from typing import List , Optional , Union
import numpy as np
from tqdm import tqdm
from utils import loadpkl , savepkl
set LOGGER = call getLogger __name__
set __all__ = list string Vocab string prepare_unkprob
class Vocab
begin
string... | import copy
import logging
from collections import Counter
from pathlib import Path
from typing import List, Optional, Union
import numpy as np
from tqdm import tqdm
from utils import loadpkl, savepkl
LOGGER = logging.getLogger(__name__)
__all__ = [
'Vocab',
'prepare_unkprob',
]
class Vocab:
"""Simple... | Python | zaydzuhri_stack_edu_python |
function post_build self packet payload
begin
string Compute the 'sources_number' field when needed
if sources_number is none
begin
set srcnum = call pack string !H length sources
set packet = packet at slice : 26 : + srcnum + packet at slice 28 : :
end
return call post_build self packet payload
end function | def post_build(self, packet, payload):
"""Compute the 'sources_number' field when needed"""
if self.sources_number is None:
srcnum = struct.pack("!H", len(self.sources))
packet = packet[:26] + srcnum + packet[28:]
return _ICMPv6.post_build(self, packet, payload) | Python | jtatman_500k |
function transition_message transition
begin
set last = last
set fr = from_slot
set to = to_slot
return string { last } : { fr } -> { to }
end function | def transition_message(transition):
last = transition.player.last
fr = transition.from_slot
to = transition.to_slot
return f"{last}: {fr}->{to}" | Python | nomic_cornstack_python_v1 |
string Load some test data in the database, update, and test for expected results.
import json
import sys , os
import redis , time
import logging
from lazyupdredis import *
comment Note: don't call flushall on actualredis. This functionality isn't available
comment to the user and will blow away the version information... | """
Load some test data in the database, update, and test for expected results.
"""
import json
import sys, os
import redis, time
import logging
from lazyupdredis import *
# Note: don't call flushall on actualredis. This functionality isn't available
# to the user and will blow away the version information
def reset... | Python | zaydzuhri_stack_edu_python |
function stitch_pores network pores1 pores2 mode=string gabriel
begin
from openpnm.network import Delaunay , Gabriel
set pores1 = call _parse_indices pores1
set pores2 = call _parse_indices pores2
set C1 = coords at tuple pores1 slice : :
set C2 = coords at tuple pores2 slice : :
set crds = vertical stack tuple C... | def stitch_pores(network, pores1, pores2, mode='gabriel'):
from openpnm.network import Delaunay, Gabriel
pores1 = network._parse_indices(pores1)
pores2 = network._parse_indices(pores2)
C1 = network.coords[pores1, :]
C2 = network.coords[pores2, :]
crds = np.vstack((C1, C2))
if mode == 'delaun... | Python | nomic_cornstack_python_v1 |
function handleEvent self event
begin
if source_field not in event
begin
yield event
return
end
if not is instance event at source_field basestring
begin
warning string Data in event[%s] not of type string. Skipping. % source_field
yield event
return
end
set string_to_match = event at source_field
set matches_dict = fa... | def handleEvent(self, event):
if self.source_field not in event:
yield event
return
if not isinstance(event[self.source_field], basestring):
self.logger.warning("Data in event[%s] not of type string. Skipping." % self.source_field)
yield event
... | Python | nomic_cornstack_python_v1 |
function attachments self
begin
return call AttachmentCollectionRequestBuilder call append_to_request_url string attachments _client
end function | def attachments(self):
return attachment_collection.AttachmentCollectionRequestBuilder(self.append_to_request_url("attachments"), self._client) | Python | nomic_cornstack_python_v1 |
function call self inputs state
begin
with call variable_scope string gates
begin
set input_to_gates = dense inputs 2 * _num_units name=string input_proj kernel_initializer=call glorot_normal_initializer use_bias=use_input_bias
comment Nematus does the orthogonal initialization probably differently
set state_to_gates =... | def call(self, inputs, state):
with tf.variable_scope("gates"):
input_to_gates = tf.layers.dense(
inputs, 2 * self._num_units, name="input_proj",
kernel_initializer=tf.glorot_normal_initializer(),
use_bias=self.use_input_bias)
# Nematus do... | Python | nomic_cornstack_python_v1 |
import datetime
import boto3
from botocore.exceptions import ClientError
set sns = call client string sns
function lambda_handler event context
begin
set CurrentDate = now
set Leave = string 30/01/2020 15:00
set Leave = string parse time Leave string %d/%m/%Y %H:%M
set countdown = Leave - CurrentDate
call publish Topic... | import datetime
import boto3
from botocore.exceptions import ClientError
sns = boto3.client('sns')
def lambda_handler(event, context):
CurrentDate = datetime.datetime.now()
Leave = "30/01/2020 15:00"
Leave = datetime.datetime.strptime(Leave, "%d/%m/%Y %H:%M")
countdown = Leave - CurrentDate
sns.p... | Python | zaydzuhri_stack_edu_python |
function from_dataframe cls order
begin
return list comprehension item name width depth height weight for tuple _ i in call iterrows
end function | def from_dataframe(cls, order):
return [Item(i.name, i.width, i.depth, i.height, i.weight) for _, i in order.iterrows()] | Python | nomic_cornstack_python_v1 |
import hashlib
import struct
import binascii
import random
set ver = 541065216
set prev_block = string 00000000000000000006a4a234288a44e715275f1775b77b2fddb6c02eb6b72f
set mrkl_root = string 2dc60c563da5368e0668b81bc4d8dd369639a1134f68e425a9a74e428801e5b8
set time_ = 1572383582
set bits = 387223263
set exp = bits ? 24
... | import hashlib
import struct
import binascii
import random
ver = 0x20400000
prev_block = "00000000000000000006a4a234288a44e715275f1775b77b2fddb6c02eb6b72f"
mrkl_root = "2dc60c563da5368e0668b81bc4d8dd369639a1134f68e425a9a74e428801e5b8"
time_ = 0x5DB8AB5E
bits = 0x17148EDF
exp = bits >> 24
mant = bits & 0xffffff
target... | Python | zaydzuhri_stack_edu_python |
function test_trid self
begin
set fun = call get_problem string trid dimension=2
call assertAlmostEqual call fun array list 2.0 2.0 - 2.0
end function | def test_trid(self):
fun = get_problem('trid', dimension=2)
self.assertAlmostEqual(fun(np.array([2.0, 2.0])), -2.0) | Python | nomic_cornstack_python_v1 |
function sequentialSearch the_list item
begin
set position = 0
set found = false
while position < length the_list and not found
begin
if the_list at position == item
begin
found == true
end
else
begin
set position = position + 1
end
end
return found
end function
print call sequentialSearch eksamplelist 9 | def sequentialSearch(the_list, item):
position = 0
found = False
while position < len(the_list) and not found:
if the_list[position] == item:
found == True
else:
position += 1
return found
print(sequentialSearch(eksamplelist, 9)) | Python | zaydzuhri_stack_edu_python |
function getResultQueueSize self REQUEST=none
begin
set size = length _results
return size
end function | def getResultQueueSize(self, REQUEST=None):
size = len(self._results)
return size | Python | nomic_cornstack_python_v1 |
function __init__ self data_type src_path tgt_path fields src_seq_length=0 tgt_seq_length=0 src_seq_length_trunc=0 tgt_seq_length_trunc=0 use_filter_pred=true dynamic_dict=true src_dir=none sample_rate=0 window_size=0 window_stride=0 window=none normalize_audio=true **kwargs
begin
set data_type = data_type
if data_type... | def __init__(self, data_type, src_path, tgt_path, fields,
src_seq_length=0, tgt_seq_length=0,
src_seq_length_trunc=0, tgt_seq_length_trunc=0,
use_filter_pred=True, dynamic_dict=True,
src_dir=None, sample_rate=0, window_size=0,
window_s... | Python | nomic_cornstack_python_v1 |
function create_op_set_id_version_map table
begin
set result : VersionMapType = dict
function process release_version ir_version *args
begin
comment Unused
del release_version
for pair in zip list string ai.onnx string ai.onnx.ml string ai.onnx.training args
begin
if pair not in result
begin
set result at pair = ir_ve... | def create_op_set_id_version_map(table: VersionTableType) -> VersionMapType:
result: VersionMapType = {}
def process(release_version: str, ir_version: int, *args: Any) -> None:
del release_version # Unused
for pair in zip(["ai.onnx", "ai.onnx.ml", "ai.onnx.training"], args):
if pai... | Python | nomic_cornstack_python_v1 |
import requests
import os
import re
import bs4
import traceback
from bs4 import BeautifulSoup
function getHtmlText1 url
begin
try
begin
set hd = dict string user-agent string Chrome/10
set r = call request string GET url headers=hd
call raise_for_status
set encoding = string utf-8
comment print(r.text)
comment print(r.... | import requests
import os
import re
import bs4
import traceback
from bs4 import BeautifulSoup
def getHtmlText1(url):
try:
hd = {'user-agent':'Chrome/10'}
r = requests.request('GET',url,headers=hd)
r.raise_for_status()
r.encoding = 'utf-8'
# print(r.text)
# p... | Python | zaydzuhri_stack_edu_python |
comment -*- coding: utf-8 -*-
string This provides password hashing and validate functions which can be This uses passlib.hash sha512_crypt to implement strong passord hashing rather then some home brew approach.
from passlib.hash import sha512_crypt
function hash_password plaintext_password
begin
string Securely hash ... | # -*- coding: utf-8 -*-
"""
This provides password hashing and validate functions which can be
This uses passlib.hash sha512_crypt to implement strong passord hashing rather
then some home brew approach.
"""
from passlib.hash import sha512_crypt
def hash_password(plaintext_password):
"""Securely hash the plain ... | Python | zaydzuhri_stack_edu_python |
comment %%
try
begin
from tkinter import *
end
except any
begin
from Tkinter import *
end
import sys
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import tkinter.filedialog as tkFileDialog
from time import sleep
import datetime
from datetime import date , timedelta... | #%%
try:
from tkinter import *
except:
from Tkinter import *
import sys
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import tkinter.filedialog as tkFileDialog
from time import sleep
import datetime
from datetime import date, timedelta
... | Python | zaydzuhri_stack_edu_python |
function visit_subscript self node parent
begin
set newnode = call Subscript
call _lineno_parent node newnode parent
set tuple subcontext asscontext = tuple asscontext none
set value = call visit value newnode
set slice = call visit slice newnode
set asscontext = subcontext
call set_line_info call last_child
return new... | def visit_subscript(self, node, parent):
newnode = new.Subscript()
_lineno_parent(node, newnode, parent)
subcontext, self.asscontext = self.asscontext, None
newnode.value = self.visit(node.value, newnode)
newnode.slice = self.visit(node.slice, newnode)
self.assconte... | Python | nomic_cornstack_python_v1 |
comment !/usr/bin/python3
import codecs
set s = input string Message do Decode here:
print decode codecs s string rot-13 | #!/usr/bin/python3
import codecs
s = input("Message do Decode here:")
print(codecs.decode(s, "rot-13")) | Python | zaydzuhri_stack_edu_python |
import random
string take the least value in every iteration and swap it with ith index . Second loop start 1+i makes sense check it O(N2)
function selction_sort arr
begin
set l = length arr
for i in range l - 1
begin
set imin = i
for j in range i + 1 l
begin
if arr at j < arr at imin
begin
set imin = j
end
end
set tup... | import random
''' take the least value in every iteration and swap it with ith index . Second loop start 1+i makes sense check it
O(N2)'''
def selction_sort(arr):
l= len(arr)
for i in range(l-1):
imin = i
for j in range(i+1,l):
if arr[j] < arr[imin]:
imin=j
... | Python | zaydzuhri_stack_edu_python |
function __display_login_info self
begin
print string Your card has been created Your card number: { card_number } Your card PIN: { __account_pin }
end function
comment f'{self.__card_display()}\n' # uncomment this line and comment out line below for pretty display | def __display_login_info(self):
print(f'\nYour card has been created\n'
f'Your card number:\n'
# f'{self.__card_display()}\n' # uncomment this line and comment out line below for pretty display
f'{self.card_number}\n'
f'Your card PIN:\n'
f'... | Python | nomic_cornstack_python_v1 |
function sgd_choice self steps=1000
begin
comment local variables to track algorithm -----------------
set misses = 0
set tries = 0
function choice_heuristic search family_id cur_day n_day stp
begin
comment for the basic heuristic, I will move the family if delta_choice + .1 * delta_accounting > 0
comment parameter 1, ... | def sgd_choice(self, steps=1000):
# local variables to track algorithm -----------------
misses = 0
tries = 0
def choice_heuristic(search, family_id, cur_day, n_day, stp):
# for the basic heuristic, I will move the family if delta_choice + .1 * delta_accounting > 0
... | Python | nomic_cornstack_python_v1 |
function lockComponents self uids hashcheck uid=none ranges=tuple updates=false deletion=false sendEvent=false meta_type=none keys=none start=0 limit=50 sort=string name dir=string ASC name=none
begin
set data = copy locals
del data at string self
set resp = call make_request url_path string DeviceRouter string lockCo... | def lockComponents(self, uids, hashcheck, uid=None, ranges=(), updates=False, deletion=False, sendEvent=False, meta_type=None, keys=None, start=0, limit=50, sort='name', dir='ASC', name=None):
data = locals().copy()
del data["self"]
resp = client.make_request(self.url_path, "DeviceRouter", "lock... | Python | nomic_cornstack_python_v1 |
function get_class x mus Sigmas
begin
set C = length mus
return argument maximum list comprehension call pdf x mean=mus at c cov=Sigmas at c for c in range C
end function | def get_class(x, mus, Sigmas) -> int:
C = len(mus)
return np.argmax([stats.multivariate_normal.pdf(x, mean=mus[c], cov=Sigmas[c]) for c in range(C)]) | Python | nomic_cornstack_python_v1 |
import games
import heuristicas
set tuple player dif = tuple string 0
while player not in list string X string O
begin
set player = call raw_input string Who moves first? (X,O):
end
set difficulty = dict string Easy 2 ; string Normal 3 ; string Hard 5
while dif not in difficulty
begin
set dif = call raw_input string C... | import games
import heuristicas
player, dif = '', 0
while player not in ['X', 'O']:
player = raw_input("Who moves first? (X,O): ")
difficulty = {"Easy": 2, "Normal": 3, "Hard": 5}
while dif not in difficulty:
dif = raw_input("Choose difficulty (Easy, Normal, Hard): ")
# game = games.TicTacToe(h=3, v=3, k=3)... | Python | zaydzuhri_stack_edu_python |
function __rtruediv__ self value
begin
return call RasterCoverage___rtruediv__ self value
end function | def __rtruediv__(self, value):
return _ilwisobjects.RasterCoverage___rtruediv__(self, value) | Python | nomic_cornstack_python_v1 |
function __bool__ self
begin
return call __getValueWithType bool
end function | def __bool__(self):
return self.__getValueWithType(bool) | Python | nomic_cornstack_python_v1 |
function next_batch self batch_size shuffle=true
begin
set start = _index_in_epoch
comment Shuffle for first epoch
if _epochs_completed == 0 and start == 0 and shuffle
begin
set permute = array range _num_examples
shuffle random permute
set _X = _X at permute
set _y = _y at permute
end
comment Go to next batch
if start... | def next_batch(self, batch_size, shuffle=True):
start = self._index_in_epoch
# Shuffle for first epoch
if self._epochs_completed == 0 and start == 0 and shuffle:
permute = np.arange(self._num_examples)
np.random.shuffle(permute)
self._X = self._X[permute]
... | Python | nomic_cornstack_python_v1 |
string Poly: many Morphism: forms polymorphism: one thing with different forms Objects have different forms. uses: 1. Loose Coupling 2. Dependency Injection 3. Interface four ways of defining polymoorphism: 1. Duck typing 2. Operator Overloading 3. Method overloading 4. Method overriding
comment Duck Typing:
string If ... | """
Poly: many
Morphism: forms
polymorphism: one thing with different forms
Objects have different forms.
uses:
1. Loose Coupling
2. Dependency Injection
3. Interface
four ways of defining polymoorphism:
1. Duck typing
2. Operator Overloading
3. Method overloading
4. Method overriding
"""
# Duck Typi... | Python | zaydzuhri_stack_edu_python |
import gevent.monkey
call patch_all
import gevent
import requests
import pymongo
import json
import io
import time
from contextlib import suppress
import get_listings_by_location as l
import get_reviews_by_listing as r
set SAMPLES = list string Hollywood, LA string Venice, LA string Oakland, SF string Manhattan, NYC st... | import gevent.monkey
gevent.monkey.patch_all()
import gevent
import requests
import pymongo
import json
import io
import time
from contextlib import suppress
import get_listings_by_location as l
import get_reviews_by_listing as r
SAMPLES = ['Hollywood, LA', 'Venice, LA', 'Oakland, SF', 'Manhattan, NYC', 'Brooklyn, NYC... | Python | zaydzuhri_stack_edu_python |
function test_contributors_limit self
begin
call create_batch 110
set top_contributors = call with_translation_counts
call assert_equal count top_contributors 100
end function | def test_contributors_limit(self):
TranslationFactory.create_batch(110)
top_contributors = User.translators.with_translation_counts()
assert_equal(top_contributors.count(), 100) | Python | nomic_cornstack_python_v1 |
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