hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
355afe62432f0a74bd58314c8e4ac4738bb62955
| 39,701
|
py
|
Python
|
test.py
|
jakerockland/searching-and-sorting
|
5c5ed79a2c43c3c3a44a78ce02018531e9de3f30
|
[
"MIT"
] | 1
|
2016-02-03T15:50:42.000Z
|
2016-02-03T15:50:42.000Z
|
test.py
|
grahamplace/data-structure-essentials
|
5c5ed79a2c43c3c3a44a78ce02018531e9de3f30
|
[
"MIT"
] | null | null | null |
test.py
|
grahamplace/data-structure-essentials
|
5c5ed79a2c43c3c3a44a78ce02018531e9de3f30
|
[
"MIT"
] | 1
|
2018-04-06T17:56:19.000Z
|
2018-04-06T17:56:19.000Z
|
# Testing of various searching and sorting algorithms and data structures
# By: Jacob Rockland
import unittest
import searching
import sorting
from singly_linked_list import SinglyLinkedList
from doubly_linked_list import DoublyLinkedList
from stack import Stack
from queue import Queue
from hash_table import HashTableChaining, HashTableLinearProbing
from binary_search_tree import BinarySearchTree
from avl_tree import AVLTree
from heap import MinHeap, MaxHeap, heap_sort_accending, heap_sort_decending
from graph import Graph
# test graph data structure implementation
class TestGraph(unittest.TestCase):
def setUp(self):
self.graph = Graph()
self.directed_graph = Graph(directed = True)
def test_basic_initialization_and_get(self):
self.assertEqual(self.graph, {})
def test_add_vertex(self):
self.graph.add_vertex('A')
self.assertEqual(self.graph, {'A': set()})
self.graph.add_vertex('B')
self.assertEqual(self.graph, {'A': set(), 'B': set()})
self.graph.add_vertex('C')
self.assertEqual(self.graph, {'A': set(), 'B': set(), 'C': set()})
def test_add_connection(self):
self.graph.add_connection('A', 'B')
self.assertEqual(self.graph, {'A': {'B'}, 'B': {'A'}})
self.graph.add_connection('C', 'B')
self.assertEqual(self.graph, {'A': {'B'}, 'B': {'A', 'C'}, 'C': {'B'}})
self.graph.add_connection('A', 'C')
self.assertEqual(self.graph, {'A': {'B', 'C'}, 'B': {'A', 'C'}, 'C': {'B', 'A'}})
self.graph.add_connection('A', 'C')
self.assertEqual(self.graph, {'A': {'B', 'C'}, 'B': {'A', 'C'}, 'C': {'B', 'A'}})
self.graph.add_connection('B', 'D')
self.assertEqual(self.graph, {'A': {'B', 'C'}, 'B': {'A', 'C', 'D'}, 'C': {'B', 'A'}, 'D': {'B'}})
self.directed_graph.add_connection('A', 'B')
self.assertEqual(self.directed_graph, {'A': {'B'}})
self.directed_graph.add_connection('C', 'B')
self.assertEqual(self.directed_graph, {'A': {'B'}, 'C': {'B'}})
self.directed_graph.add_connection('A', 'C')
self.assertEqual(self.directed_graph, {'A': {'B', 'C'}, 'C': {'B'}})
self.directed_graph.add_connection('C', 'A')
self.assertEqual(self.directed_graph, {'A': {'B', 'C'}, 'C': {'B', 'A'}})
self.directed_graph.add_connection('B', 'D')
self.assertEqual(self.directed_graph, {'A': {'B', 'C'}, 'B': {'D'}, 'C': {'B', 'A'}})
def test_add_connections(self):
self.graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertEqual(self.graph, {'A': {'B', 'C'}, 'B': {'A', 'C', 'D'}, 'C': {'B', 'A'}, 'D': {'B'}})
self.directed_graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertEqual(self.directed_graph, {'A': {'B', 'C'}, 'B': {'D'}, 'C': {'B'}})
def test_remove_vertex(self):
self.graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertEqual(self.graph, {'A': {'B', 'C'}, 'B': {'A', 'C', 'D'}, 'C': {'B', 'A'}, 'D': {'B'}})
self.graph.remove_vertex('A')
self.assertEqual(self.graph, {'B': {'C', 'D'}, 'C': {'B'}, 'D': {'B'}})
self.graph.remove_vertex('A')
self.assertEqual(self.graph, {'B': {'C', 'D'}, 'C': {'B'}, 'D': {'B'}})
self.directed_graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertEqual(self.directed_graph, {'A': {'B', 'C'}, 'B': {'D'}, 'C': {'B'}})
self.directed_graph.remove_vertex('B')
self.assertEqual(self.directed_graph, {'A': {'C'}, 'C': set()})
self.directed_graph.remove_vertex('B')
self.assertEqual(self.directed_graph, {'A': {'C'}, 'C': set()})
def test_remove_connection(self):
self.graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertEqual(self.graph, {'A': {'B', 'C'}, 'B': {'A', 'C', 'D'}, 'C': {'B', 'A'}, 'D': {'B'}})
self.graph.remove_connection('D', 'B')
self.assertEqual(self.graph, {'A': {'B', 'C'}, 'B': {'A', 'C'}, 'C': {'B', 'A'}, 'D': set()})
self.graph.remove_connection('A', 'B')
self.assertEqual(self.graph, {'A': {'C'}, 'B': {'C'}, 'C': {'B', 'A'}, 'D': set()})
self.directed_graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertEqual(self.directed_graph, {'A': {'B', 'C'}, 'B': {'D'}, 'C': {'B'}})
self.directed_graph.remove_connection('A', 'B')
self.assertEqual(self.directed_graph, {'A': {'C'}, 'B': {'D'}, 'C': {'B'}})
self.directed_graph.remove_connection('B', 'D')
self.assertEqual(self.directed_graph, {'A': {'C'}, 'B': set(), 'C': {'B'}})
def test_remove_connections(self):
self.graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertEqual(self.graph, {'A': {'B', 'C'}, 'B': {'A', 'C', 'D'}, 'C': {'B', 'A'}, 'D': {'B'}})
self.graph.remove_connections([('A', 'B'), ('B', 'D')])
self.assertEqual(self.graph, {'A': {'C'}, 'B': {'C'}, 'C': {'B', 'A'}, 'D': set()})
self.directed_graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertEqual(self.directed_graph, {'A': {'B', 'C'}, 'B': {'D'}, 'C': {'B'}})
self.directed_graph.remove_connections([('A', 'B'), ('B', 'D')])
self.assertEqual(self.directed_graph, {'A': {'C'}, 'B': set(), 'C': {'B'}})
def test_is_connected(self):
self.graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertTrue(self.graph.is_connected('B', 'A'))
self.assertTrue(self.graph.is_connected('A', 'B'))
self.assertFalse(self.graph.is_connected('D', 'A'))
self.directed_graph.add_connections([('A', 'B'), ('C', 'B'), ('A', 'C'), ('B', 'D')])
self.assertTrue(self.directed_graph.is_connected('A', 'B'))
self.assertFalse(self.directed_graph.is_connected('B', 'A'))
self.assertFalse(self.directed_graph.is_connected('D', 'A'))
# test method for heap sort in accending order
class TestHeapSortAccending(unittest.TestCase):
def test_heap_sort_accending(self):
self.assertEqual([], heap_sort_accending([]))
self.assertEqual([-2, -1, 3, 4, 5], heap_sort_accending([3, -2, 4, -1, 5]))
self.assertEqual([-2, -1, 3, 4, 5], heap_sort_accending([-2, -1, 5, 3, 4]))
self.assertEqual([-2, -1, 3, 4, 5], heap_sort_accending([-1, -2, 3, 4, 5]))
self.assertEqual([-2, -1, 3, 4, 5], heap_sort_accending([5, 4, 3, -2, -1]))
# test method for heap sort in decending order
class TestHeapSortDecending(unittest.TestCase):
def test_heap_sort_decending(self):
self.assertEqual([], heap_sort_decending([]))
self.assertEqual([5, 4, 3, -1, -2], heap_sort_decending([3, -2, 4, -1, 5]))
self.assertEqual([5, 4, 3, -1, -2], heap_sort_decending([-2, -1, 5, 3, 4]))
self.assertEqual([5, 4, 3, -1, -2], heap_sort_decending([-1, -2, 3, 4, 5]))
self.assertEqual([5, 4, 3, -1, -2], heap_sort_decending([5, 4, 3, -2, -1]))
# test methods for max-heap
class TestMaxHeap(unittest.TestCase):
def setUp(self):
self.heap = MaxHeap()
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.heap), '[]')
def test_insert(self):
self.heap.insert(4)
self.assertEqual(repr(self.heap), '[4]')
self.assertEqual(self.heap.size, 1)
self.heap.insert(4)
self.assertEqual(repr(self.heap), '[4, 4]')
self.assertEqual(self.heap.size, 2)
self.heap.insert(6)
self.assertEqual(repr(self.heap), '[6, 4, 4]')
self.assertEqual(self.heap.size, 3)
self.heap.insert(1)
self.assertEqual(repr(self.heap), '[6, 4, 4, 1]')
self.assertEqual(self.heap.size, 4)
self.heap.insert(7)
self.assertEqual(repr(self.heap), '[7, 6, 4, 1, 4]')
self.assertEqual(self.heap.size, 5)
def test_get_max(self):
self.assertEqual(self.heap.get_max(), None)
self.heap.insert(-7)
self.assertEqual(self.heap.get_max(), -7)
self.heap.insert(7)
self.assertEqual(self.heap.get_max(), 7)
self.heap.insert(5)
self.assertEqual(self.heap.get_max(), 7)
self.heap.insert(12)
self.assertEqual(self.heap.get_max(), 12)
def test_extract_min(self):
self.heap.insert(4)
self.heap.insert(5)
self.heap.insert(7)
self.heap.insert(2)
self.heap.insert(-1)
self.assertEqual(self.heap.extract_max(), 7)
self.assertEqual(self.heap.extract_max(), 5)
self.assertEqual(self.heap.extract_max(), 4)
self.assertEqual(self.heap.extract_max(), 2)
self.assertEqual(self.heap.extract_max(), -1)
self.assertEqual(self.heap.extract_max(), None)
def test_build_heap(self):
self.heap.build_heap([4, 4, 6, 1, 7])
self.assertEqual(repr(self.heap), '[7, 4, 6, 1, 4]')
# test methods for min-heap
class TestMinHeap(unittest.TestCase):
def setUp(self):
self.heap = MinHeap()
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.heap), '[]')
def test_insert(self):
self.heap.insert(4)
self.assertEqual(repr(self.heap), '[4]')
self.assertEqual(self.heap.size, 1)
self.heap.insert(4)
self.assertEqual(repr(self.heap), '[4, 4]')
self.assertEqual(self.heap.size, 2)
self.heap.insert(6)
self.assertEqual(repr(self.heap), '[4, 4, 6]')
self.assertEqual(self.heap.size, 3)
self.heap.insert(1)
self.assertEqual(repr(self.heap), '[1, 4, 6, 4]')
self.assertEqual(self.heap.size, 4)
self.heap.insert(3)
self.assertEqual(repr(self.heap), '[1, 3, 6, 4, 4]')
self.assertEqual(self.heap.size, 5)
def test_get_min(self):
self.assertEqual(self.heap.get_min(), None)
self.heap.insert(4)
self.assertEqual(self.heap.get_min(), 4)
self.heap.insert(7)
self.assertEqual(self.heap.get_min(), 4)
self.heap.insert(2)
self.assertEqual(self.heap.get_min(), 2)
self.heap.insert(-1)
self.assertEqual(self.heap.get_min(), -1)
def test_extract_min(self):
self.heap.insert(4)
self.heap.insert(5)
self.heap.insert(7)
self.heap.insert(2)
self.heap.insert(-1)
self.assertEqual(self.heap.extract_min(), -1)
self.assertEqual(self.heap.extract_min(), 2)
self.assertEqual(self.heap.extract_min(), 4)
self.assertEqual(self.heap.extract_min(), 5)
self.assertEqual(self.heap.extract_min(), 7)
self.assertEqual(self.heap.extract_min(), None)
def test_build_heap(self):
self.heap.build_heap([4, 4, 6, 1, 3])
self.assertEqual(repr(self.heap), '[1, 3, 6, 4, 4]')
# test methods for AVL tree implementation
class TestAVLTree(unittest.TestCase):
def setUp(self):
self.tree = AVLTree()
# test methods for BST implementation
class TestBinarySearchTree(unittest.TestCase):
def setUp(self):
self.tree = BinarySearchTree()
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.tree), '')
def test_insert(self):
self.tree.insert('C')
self.assertEqual(repr(self.tree), 'C ')
self.tree.insert('D')
self.assertEqual(repr(self.tree), 'C D ')
self.tree.insert('A')
self.assertEqual(repr(self.tree), 'A C D ')
self.tree.insert('B')
self.assertEqual(repr(self.tree), 'A B C D ')
self.tree.insert('F')
self.assertEqual(repr(self.tree), 'A B C D F ')
self.tree.insert('E')
self.assertEqual(repr(self.tree), 'A B C D E F ')
def test_iterator(self):
letters = []
for node in self.tree:
letters.append(node)
self.assertEqual(letters, [])
self.tree.insert('C')
self.tree.insert('D')
self.tree.insert('A')
self.tree.insert('B')
self.tree.insert('F')
self.tree.insert('E')
for node in self.tree:
letters.append(node)
self.assertEqual(letters, ['A', 'B', 'C', 'D', 'E', 'F'])
def test_height(self):
self.assertEqual(self.tree.height(self.tree.root), -1)
self.tree.insert('C')
self.assertEqual(self.tree.height(self.tree.root), 0)
self.tree.insert('D')
self.assertEqual(self.tree.height(self.tree.root), 1)
self.tree.insert('A')
self.assertEqual(self.tree.height(self.tree.root), 1)
self.tree.insert('L')
self.assertEqual(self.tree.height(self.tree.root), 2)
self.tree.insert('X')
self.assertEqual(self.tree.height(self.tree.root), 3)
self.tree.insert('B')
self.assertEqual(self.tree.height(self.tree.root), 3)
def test_length(self):
self.assertEqual(self.tree.length(), 0)
self.assertEqual(len(self.tree), 0)
self.tree.insert('C')
self.assertEqual(self.tree.length(), 1)
self.assertEqual(len(self.tree), 1)
self.tree.insert('D')
self.assertEqual(self.tree.length(), 2)
self.assertEqual(len(self.tree), 2)
self.tree.insert('A')
self.assertEqual(self.tree.length(), 3)
self.assertEqual(len(self.tree), 3)
self.tree.insert('B')
self.assertEqual(self.tree.length(), 4)
self.assertEqual(len(self.tree), 4)
self.tree.remove('D')
self.assertEqual(self.tree.length(), 3)
self.assertEqual(len(self.tree), 3)
self.tree.remove('B')
self.assertEqual(self.tree.length(), 2)
self.assertEqual(len(self.tree), 2)
self.tree.remove('A')
self.assertEqual(self.tree.length(), 1)
self.assertEqual(len(self.tree), 1)
self.tree.remove('C')
self.assertEqual(self.tree.length(), 0)
self.assertEqual(len(self.tree), 0)
def test_contains(self):
self.tree.insert('C')
self.tree.insert('D')
self.tree.insert('A')
self.assertTrue('A' in self.tree)
self.assertTrue('C' in self.tree)
self.assertTrue('D' in self.tree)
self.assertFalse('B' in self.tree)
self.assertFalse(None in self.tree)
def test_search(self):
self.tree.insert('C')
self.tree.insert('D')
self.tree.insert('A')
self.tree.insert('B')
self.tree.insert('F')
self.tree.insert('E')
self.assertEqual(self.tree.search('A').data, 'A')
self.assertEqual(self.tree.search('B').data, 'B')
self.assertEqual(self.tree.search('C').data, 'C')
self.assertEqual(self.tree.search('D').data, 'D')
self.assertEqual(self.tree.search('E').data, 'E')
self.assertEqual(self.tree.search('F').data, 'F')
self.assertEqual(self.tree.search('G'), None)
def test_remove(self):
self.tree.insert('C')
self.tree.insert('D')
self.tree.insert('A')
self.tree.insert('B')
self.tree.insert('F')
self.tree.insert('E')
self.assertEqual(repr(self.tree), 'A B C D E F ')
self.tree.remove('E')
self.assertEqual(repr(self.tree), 'A B C D F ')
self.tree.remove('B')
self.assertEqual(repr(self.tree), 'A C D F ')
self.tree.remove('A')
self.assertEqual(repr(self.tree), 'C D F ')
self.tree.remove('C')
self.assertEqual(repr(self.tree), 'D F ')
self.tree.remove('D')
self.assertEqual(repr(self.tree), 'F ')
self.tree.remove('F')
self.assertEqual(repr(self.tree), '')
def test_in_order(self):
self.tree.insert('F')
self.tree.insert('G')
self.tree.insert('B')
self.tree.insert('A')
self.tree.insert('D')
self.tree.insert('I')
self.tree.insert('H')
self.tree.insert('E')
self.tree.insert('C')
self.assertEqual(self.tree.in_order(self.tree.root), 'A B C D E F G H I ')
def test_pre_order(self):
self.tree.insert('F')
self.tree.insert('G')
self.tree.insert('B')
self.tree.insert('A')
self.tree.insert('D')
self.tree.insert('I')
self.tree.insert('H')
self.tree.insert('E')
self.tree.insert('C')
self.assertEqual(self.tree.pre_order(self.tree.root), 'F B A D C E G I H ')
def test_post_order(self):
self.tree.insert('F')
self.tree.insert('G')
self.tree.insert('B')
self.tree.insert('A')
self.tree.insert('D')
self.tree.insert('I')
self.tree.insert('H')
self.tree.insert('E')
self.tree.insert('C')
self.assertEqual(self.tree.post_order(self.tree.root), 'A C E D B H I G F ')
# test methods for hash table implementation using linear probing
class TestHashTableLinearProbing(unittest.TestCase):
class Item(object):
def __init__(self, item):
self.item = item
self.key = item
def __repr__(self):
return repr(self.item)
def __eq__(self, other):
if isinstance(other, self.__class__):
return self.item == other.item
else:
return False
def setUp(self):
self.hash_table = HashTableLinearProbing(5)
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.hash_table), '[False, False, False, False, False]')
def test_hash(self):
self.assertEqual(self.hash_table.hash(17), 2)
self.assertEqual(self.hash_table.hash(27), 2)
self.assertEqual(self.hash_table.hash(12), 2)
self.assertEqual(self.hash_table.hash(14), 4)
self.assertEqual(self.hash_table.hash(1), 1)
self.assertEqual(self.hash_table.hash(13), 3)
self.assertEqual(self.hash_table.hash(20), 0)
def test_insert(self):
self.hash_table.insert(self.Item(3))
self.assertEqual(repr(self.hash_table), '[False, False, False, 3, False]')
self.hash_table.insert(self.Item(11))
self.assertEqual(repr(self.hash_table), '[False, 11, False, 3, False]')
self.hash_table.insert(self.Item(23))
self.assertEqual(repr(self.hash_table), '[False, 11, False, 3, 23]')
self.hash_table.insert(self.Item(33))
self.assertEqual(repr(self.hash_table), '[33, 11, False, 3, 23]')
self.hash_table.insert(self.Item(21))
self.assertEqual(repr(self.hash_table), '[33, 11, 21, 3, 23]')
def test_remove(self):
self.hash_table.insert(self.Item(3))
self.hash_table.insert(self.Item(11))
self.hash_table.insert(self.Item(23))
self.hash_table.insert(self.Item(33))
self.assertEqual(repr(self.hash_table), '[33, 11, False, 3, 23]')
self.hash_table.remove(33)
self.assertEqual(repr(self.hash_table), '[True, 11, False, 3, 23]')
self.hash_table.remove(21)
self.assertEqual(repr(self.hash_table), '[True, 11, False, 3, 23]')
self.hash_table.remove(21)
self.assertEqual(repr(self.hash_table), '[True, 11, False, 3, 23]')
self.hash_table.remove(11)
self.assertEqual(repr(self.hash_table), '[True, True, False, 3, 23]')
self.hash_table.remove(23)
self.assertEqual(repr(self.hash_table), '[True, True, False, 3, True]')
self.hash_table.remove(3)
self.assertEqual(repr(self.hash_table), '[True, True, False, True, True]')
def test_search(self):
self.hash_table.insert(self.Item(3))
self.hash_table.insert(self.Item(5))
self.assertEqual(self.hash_table.search(4), None)
self.assertEqual(self.hash_table.search(5), self.Item(5))
# test methods for hash table implementation using chaining
class TestHashTableChaining(unittest.TestCase):
class Item(object):
def __init__(self, item):
self.item = item
self.key = item
def __repr__(self):
return repr(self.item)
def __eq__(self, other):
if isinstance(other, self.__class__):
return self.item == other.item
else:
return False
def setUp(self):
self.hash_table = HashTableChaining(5)
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.hash_table), '[None, None, None, None, None]')
def test_hash(self):
self.assertEqual(self.hash_table.hash(17), 2)
self.assertEqual(self.hash_table.hash(27), 2)
self.assertEqual(self.hash_table.hash(12), 2)
self.assertEqual(self.hash_table.hash(14), 4)
self.assertEqual(self.hash_table.hash(1), 1)
self.assertEqual(self.hash_table.hash(13), 3)
self.assertEqual(self.hash_table.hash(20), 0)
def test_insert(self):
self.hash_table.insert(self.Item(3))
self.assertEqual(repr(self.hash_table), '[None, None, None, [3], None]')
self.hash_table.insert(self.Item(13))
self.assertEqual(repr(self.hash_table), '[None, None, None, [3, 13], None]')
self.hash_table.insert(self.Item(5))
self.assertEqual(repr(self.hash_table), '[[5], None, None, [3, 13], None]')
def test_remove(self):
self.hash_table.insert(self.Item(3))
self.hash_table.insert(self.Item(13))
self.hash_table.insert(self.Item(5))
self.assertEqual(repr(self.hash_table), '[[5], None, None, [3, 13], None]')
self.hash_table.remove(self.Item(13))
self.assertEqual(repr(self.hash_table), '[[5], None, None, [3], None]')
self.hash_table.remove(self.Item(5))
self.assertEqual(repr(self.hash_table), '[[], None, None, [3], None]')
def test_search(self):
self.hash_table.insert(self.Item(3))
self.hash_table.insert(self.Item(5))
self.assertEqual(self.hash_table.search(self.Item(4)), None)
self.assertEqual(self.hash_table.search(self.Item(5)), self.Item(5))
# test methods for queue ADT
class TestQueue(unittest.TestCase):
def setUp(self):
self.queue = Queue()
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.queue), '[]')
def test_push(self):
self.queue.push("!")
self.assertEqual(repr(self.queue), "['!']")
self.queue.push("world")
self.assertEqual(repr(self.queue), "['!', 'world']")
self.queue.push("Hello")
self.assertEqual(repr(self.queue), "['!', 'world', 'Hello']")
def test_pop(self):
self.queue.push("!")
self.queue.push("world")
self.queue.push("Hello")
self.assertEqual(repr(self.queue), "['!', 'world', 'Hello']")
self.assertEqual(self.queue.pop(), '!')
self.assertEqual(repr(self.queue), "['world', 'Hello']")
self.assertEqual(self.queue.pop(), 'world')
self.assertEqual(repr(self.queue), "['Hello']")
def test_peek(self):
self.queue.push("!")
self.assertEqual(self.queue.peek(), '!')
self.queue.push("world")
self.assertEqual(self.queue.peek(), '!')
def test_is_empty(self):
self.assertTrue(self.queue.is_empty())
self.queue.push("Hello world!")
self.assertFalse(self.queue.is_empty())
def test_get_length(self):
self.assertEqual(self.queue.get_length(), 0)
self.queue.push("Hello world!")
self.assertEqual(self.queue.get_length(), 1)
self.queue.push("Hello world!")
self.assertEqual(self.queue.get_length(), 2)
self.queue.pop()
self.assertEqual(self.queue.get_length(), 1)
self.queue.pop()
self.assertEqual(self.queue.get_length(), 0)
# test methods for stack ADT
class TestStack(unittest.TestCase):
def setUp(self):
self.stack = Stack()
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.stack), '[]')
def test_push(self):
self.stack.push("!")
self.assertEqual(repr(self.stack), "['!']")
self.stack.push("world")
self.assertEqual(repr(self.stack), "['world', '!']")
self.stack.push("Hello")
self.assertEqual(repr(self.stack), "['Hello', 'world', '!']")
def test_pop(self):
self.stack.push("!")
self.stack.push("world")
self.stack.push("Hello")
self.assertEqual(repr(self.stack), "['Hello', 'world', '!']")
self.assertEqual(self.stack.pop(), 'Hello')
self.assertEqual(repr(self.stack), "['world', '!']")
self.assertEqual(self.stack.pop(), 'world')
self.assertEqual(repr(self.stack), "['!']")
def test_peek(self):
self.stack.push('!')
self.assertEqual(self.stack.peek(), '!')
self.stack.push('world')
self.assertEqual(self.stack.peek(), 'world')
self.stack.push('Hello')
self.assertEqual(self.stack.peek(), 'Hello')
def test_is_empty(self):
self.assertTrue(self.stack.is_empty())
self.stack.push('Hello world!')
self.assertFalse(self.stack.is_empty())
def test_get_length(self):
self.assertEqual(self.stack.get_length(), 0)
self.stack.push('Hello world!')
self.assertEqual(self.stack.get_length(), 1)
self.stack.push('Hello world!')
self.assertEqual(self.stack.get_length(), 2)
self.stack.pop()
self.assertEqual(self.stack.get_length(), 1)
self.stack.pop()
self.assertEqual(self.stack.get_length(), 0)
# test methods for doubly linked list
class TestDoublyLinkedList(unittest.TestCase):
def setUp(self):
self.my_list = DoublyLinkedList()
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.my_list), '[]')
def test_append(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
def test_prepend(self):
self.my_list.prepend(4)
self.my_list.prepend(3)
self.my_list.prepend(7)
self.my_list.prepend(-17)
self.assertEqual(repr(self.my_list), '[-17, 7, 3, 4]')
def test_insert_after(self):
self.my_list.insert_after(None, 4)
self.my_list.insert_after(None, 3)
self.my_list.insert_after(self.my_list.tail, 7)
self.my_list.insert_after(self.my_list.head, -17)
self.assertEqual(repr(self.my_list), '[3, -17, 4, 7]')
def test_insert_sorted(self):
self.my_list.insert_after(None, 4)
self.my_list.insert_after(None, 3)
self.my_list.insert_after(None, 7)
self.assertEqual(repr(self.my_list), '[7, 3, 4]')
self.my_list.insert_sorted(2)
self.my_list.insert_sorted(8)
self.assertEqual(repr(self.my_list), '[2, 7, 3, 4, 8]')
self.my_list.remove(self.my_list.head)
self.my_list.remove(self.my_list.head)
self.my_list.remove(self.my_list.head)
self.my_list.remove(self.my_list.head)
self.my_list.remove(self.my_list.head)
self.my_list.insert_sorted(8)
self.my_list.insert_sorted(7)
self.my_list.insert_sorted(6)
self.my_list.insert_sorted(5)
self.assertEqual(repr(self.my_list), '[5, 6, 7, 8]')
def test_remove(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
self.my_list.remove(self.my_list.head)
self.assertEqual(repr(self.my_list), '[3, 7, -17]')
self.my_list.remove(self.my_list.head.next)
self.assertEqual(repr(self.my_list), '[3, -17]')
self.my_list.remove(self.my_list.tail)
self.assertEqual(repr(self.my_list), '[3]')
self.my_list.remove(self.my_list.head)
self.my_list.remove(self.my_list.head)
self.assertEqual(repr(self.my_list), '[]')
def test_array(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(self.my_list.array(), [4, 3, 7, -17])
def test_reverse_array(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(self.my_list.reverse_array(), [-17, 7, 3, 4])
def test_search(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(-17)
self.my_list.append(7)
self.assertEqual(self.my_list.search(4).data, 4)
self.assertEqual(self.my_list.search(3).data, 3)
self.assertEqual(self.my_list.search(-17).data, -17)
self.assertEqual(self.my_list.search(17), None)
def test_reverse(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
self.my_list.reverse()
self.assertEqual(repr(self.my_list), '[-17, 7, 3, 4]')
self.my_list.reverse()
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
def test_remove_duplicates(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(3)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(repr(self.my_list), '[4, 3, 3, 3, 7, -17]')
self.my_list.remove_duplicates()
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
# test methods for singly linked list
class TestSinglyLinkedList(unittest.TestCase):
def setUp(self):
self.my_list = SinglyLinkedList()
def test_basic_initialization_and_repr(self):
self.assertEqual(repr(self.my_list), '[]')
def test_append(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
def test_prepend(self):
self.my_list.prepend(4)
self.my_list.prepend(3)
self.my_list.prepend(7)
self.my_list.prepend(-17)
self.assertEqual(repr(self.my_list), '[-17, 7, 3, 4]')
def test_insert_after(self):
self.my_list.insert_after(None, 4)
self.my_list.insert_after(None, 3)
self.my_list.insert_after(self.my_list.tail, 7)
self.my_list.insert_after(self.my_list.head, -17)
self.assertEqual(repr(self.my_list), '[3, -17, 4, 7]')
def test_insert_sorted(self):
self.my_list.insert_after(None, 4)
self.my_list.insert_after(None, 3)
self.my_list.insert_after(None, 7)
self.assertEqual(repr(self.my_list), '[7, 3, 4]')
self.my_list.insert_sorted(2)
self.my_list.insert_sorted(8)
self.assertEqual(repr(self.my_list), '[2, 7, 3, 4, 8]')
self.my_list.remove_after(None)
self.my_list.remove_after(None)
self.my_list.remove_after(None)
self.my_list.remove_after(None)
self.my_list.remove_after(None)
self.my_list.insert_sorted(8)
self.my_list.insert_sorted(7)
self.my_list.insert_sorted(6)
self.my_list.insert_sorted(5)
self.assertEqual(repr(self.my_list), '[5, 6, 7, 8]')
self.my_list.reverse()
self.assertEqual(repr(self.my_list), '[8, 7, 6, 5]')
def test_remove_after(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
self.my_list.remove_after(None)
self.assertEqual(repr(self.my_list), '[3, 7, -17]')
self.my_list.remove_after(self.my_list.head)
self.assertEqual(repr(self.my_list), '[3, -17]')
self.my_list.remove_after(self.my_list.tail)
self.assertEqual(repr(self.my_list), '[3, -17]')
self.my_list.remove_after(None)
self.my_list.remove_after(None)
self.my_list.remove_after(None)
self.assertEqual(repr(self.my_list), '[]')
def test_array(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(self.my_list.array(), [4, 3, 7, -17])
def test_search(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(-17)
self.my_list.append(7)
self.assertEqual(self.my_list.search(4).data, 4)
self.assertEqual(self.my_list.search(3).data, 3)
self.assertEqual(self.my_list.search(-17).data, -17)
self.assertEqual(self.my_list.search(17), None)
def test_reverse(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
self.my_list.reverse()
self.assertEqual(repr(self.my_list), '[-17, 7, 3, 4]')
self.my_list.reverse()
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
def test_remove_duplicates(self):
self.my_list.append(4)
self.my_list.append(3)
self.my_list.append(3)
self.my_list.append(3)
self.my_list.append(7)
self.my_list.append(-17)
self.assertEqual(repr(self.my_list), '[4, 3, 3, 3, 7, -17]')
self.my_list.remove_duplicates()
self.assertEqual(repr(self.my_list), '[4, 3, 7, -17]')
# test methods from sorting module
class TestSortMethods(unittest.TestCase):
def setUp(self):
self.list_a = [30, 13, 57, 42, 21, 0, -11]
self.list_b = [57, 42, 30, 21, 13, 0, -11]
self.list_c = [-11, 0, 13, 21, 30, 42, 57]
self.list_d = [21, -11, 42, 13, 0, 57, 30]
self.list_one = [1]
self.list_two = [-5, -10]
self.list_sorted = [-11, 0, 13, 21, 30, 42, 57]
def test_selection_sort(self):
sorting.selection_sort(self.list_a)
sorting.selection_sort(self.list_b)
sorting.selection_sort(self.list_c)
sorting.selection_sort(self.list_d)
sorting.selection_sort(self.list_one)
sorting.selection_sort(self.list_two)
self.assertEqual(self.list_a, self.list_sorted)
self.assertEqual(self.list_b, self.list_sorted)
self.assertEqual(self.list_c, self.list_sorted)
self.assertEqual(self.list_d, self.list_sorted)
self.assertEqual(self.list_one, [1])
self.assertEqual(self.list_two, [-10, -5])
def test_bubble_sort(self):
sorting.bubble_sort(self.list_a)
sorting.bubble_sort(self.list_b)
sorting.bubble_sort(self.list_c)
sorting.bubble_sort(self.list_d)
sorting.bubble_sort(self.list_one)
sorting.bubble_sort(self.list_two)
self.assertEqual(self.list_a, self.list_sorted)
self.assertEqual(self.list_b, self.list_sorted)
self.assertEqual(self.list_c, self.list_sorted)
self.assertEqual(self.list_d, self.list_sorted)
self.assertEqual(self.list_one, [1])
self.assertEqual(self.list_two, [-10, -5])
def test_insertion_sort(self):
sorting.insertion_sort(self.list_a)
sorting.insertion_sort(self.list_b)
sorting.insertion_sort(self.list_c)
sorting.insertion_sort(self.list_d)
sorting.insertion_sort(self.list_one)
sorting.insertion_sort(self.list_two)
self.assertEqual(self.list_a, self.list_sorted)
self.assertEqual(self.list_b, self.list_sorted)
self.assertEqual(self.list_c, self.list_sorted)
self.assertEqual(self.list_d, self.list_sorted)
self.assertEqual(self.list_one, [1])
self.assertEqual(self.list_two, [-10, -5])
def test_quick_sort(self):
sorting.quick_sort(self.list_a)
sorting.quick_sort(self.list_b)
sorting.quick_sort(self.list_c)
sorting.quick_sort(self.list_d)
sorting.quick_sort(self.list_one)
sorting.quick_sort(self.list_two)
self.assertEqual(self.list_a, self.list_sorted)
self.assertEqual(self.list_b, self.list_sorted)
self.assertEqual(self.list_c, self.list_sorted)
self.assertEqual(self.list_d, self.list_sorted)
self.assertEqual(self.list_one, [1])
self.assertEqual(self.list_two, [-10, -5])
def test_merge_sort(self):
sorting.merge_sort(self.list_a)
sorting.merge_sort(self.list_b)
sorting.merge_sort(self.list_c)
sorting.merge_sort(self.list_d)
sorting.merge_sort(self.list_one)
sorting.merge_sort(self.list_two)
self.assertEqual(self.list_a, self.list_sorted)
self.assertEqual(self.list_b, self.list_sorted)
self.assertEqual(self.list_c, self.list_sorted)
self.assertEqual(self.list_d, self.list_sorted)
self.assertEqual(self.list_one, [1])
self.assertEqual(self.list_two, [-10, -5])
def test_heap_sort(self):
sorting.heap_sort(self.list_a)
sorting.heap_sort(self.list_b)
sorting.heap_sort(self.list_c)
sorting.heap_sort(self.list_d)
sorting.heap_sort(self.list_one)
sorting.heap_sort(self.list_two)
self.assertEqual(self.list_a, self.list_sorted)
self.assertEqual(self.list_b, self.list_sorted)
self.assertEqual(self.list_c, self.list_sorted)
self.assertEqual(self.list_d, self.list_sorted)
self.assertEqual(self.list_one, [1])
self.assertEqual(self.list_two, [-10, -5])
# test methods from searching module
class TestSearchMethods(unittest.TestCase):
def setUp(self):
self.list_even = [1, 2, 3, 4, 5, 6, 7, 8]
self.list_odd = [1, 2, 3, 4, 5, 6, 7]
self.list_one = [1]
def test_linear_search(self):
self.assertEqual(searching.linear_search(self.list_even, 2), 2)
self.assertEqual(searching.linear_search(self.list_even, 5), 5)
self.assertEqual(searching.linear_search(self.list_even, 4), 4)
self.assertEqual(searching.linear_search(self.list_even, 7), 7)
self.assertEqual(searching.linear_search(self.list_even, 9), None)
self.assertEqual(searching.linear_search(self.list_odd, 2), 2)
self.assertEqual(searching.linear_search(self.list_odd, 5), 5)
self.assertEqual(searching.linear_search(self.list_odd, 7), 7)
self.assertEqual(searching.linear_search(self.list_odd, 9), None)
self.assertEqual(searching.linear_search(self.list_one, 1), 1)
self.assertEqual(searching.linear_search(self.list_one, 2), None)
def test_binary_search(self):
self.assertEqual(searching.binary_search(self.list_even, 2), 2)
self.assertEqual(searching.binary_search(self.list_even, 5), 5)
self.assertEqual(searching.binary_search(self.list_even, 4), 4)
self.assertEqual(searching.binary_search(self.list_even, 7), 7)
self.assertEqual(searching.binary_search(self.list_even, 9), None)
self.assertEqual(searching.binary_search(self.list_odd, 2), 2)
self.assertEqual(searching.binary_search(self.list_odd, 5), 5)
self.assertEqual(searching.binary_search(self.list_odd, 7), 7)
self.assertEqual(searching.binary_search(self.list_odd, 9), None)
self.assertEqual(searching.binary_search(self.list_one, 1), 1)
self.assertEqual(searching.binary_search(self.list_one, 2), None)
if __name__ == '__main__':
unittest.main()
| 39.15286
| 106
| 0.606937
| 5,586
| 39,701
| 4.168278
| 0.03276
| 0.202285
| 0.078165
| 0.095817
| 0.913417
| 0.838473
| 0.773922
| 0.73033
| 0.689744
| 0.610376
| 0
| 0.026028
| 0.21808
| 39,701
| 1,013
| 107
| 39.19151
| 0.724028
| 0.016775
| 0
| 0.646989
| 0
| 0
| 0.05149
| 0
| 0
| 0
| 0
| 0
| 0.38843
| 1
| 0.119244
| false
| 0
| 0.014168
| 0.002361
| 0.160567
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
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| 0
| 0
| 0
| 0
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| 0
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| null | 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
35a67f3c935aadd667cf8b9b26942457ba209101
| 29
|
py
|
Python
|
kraskolba_base/__init__.py
|
TroLLik/odoo-kraskolba
|
81a3e34a3b1b9a0b6bbac1cb23fa84f303f53f6d
|
[
"MIT"
] | null | null | null |
kraskolba_base/__init__.py
|
TroLLik/odoo-kraskolba
|
81a3e34a3b1b9a0b6bbac1cb23fa84f303f53f6d
|
[
"MIT"
] | 1
|
2017-12-01T04:56:06.000Z
|
2017-12-01T04:56:06.000Z
|
kraskolba_base/__init__.py
|
TroLLik/odoo-kraskolba
|
81a3e34a3b1b9a0b6bbac1cb23fa84f303f53f6d
|
[
"MIT"
] | null | null | null |
# coding=utf-8
import models
| 9.666667
| 14
| 0.758621
| 5
| 29
| 4.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04
| 0.137931
| 29
| 3
| 15
| 9.666667
| 0.84
| 0.413793
| 0
| 0
| 0
| 0
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| true
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| null | 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
35b9ccf8ace9e393c5f300ccb28e21f34edb3caf
| 47
|
py
|
Python
|
RPG/main.py
|
lmello0/rpg-estudo
|
1ff5a5b03175ca303fd1683e5f59d552d0fdd539
|
[
"MIT"
] | null | null | null |
RPG/main.py
|
lmello0/rpg-estudo
|
1ff5a5b03175ca303fd1683e5f59d552d0fdd539
|
[
"MIT"
] | null | null | null |
RPG/main.py
|
lmello0/rpg-estudo
|
1ff5a5b03175ca303fd1683e5f59d552d0fdd539
|
[
"MIT"
] | null | null | null |
import classes
import funcs
funcs.menuTestes()
| 11.75
| 18
| 0.829787
| 6
| 47
| 6.5
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106383
| 47
| 4
| 18
| 11.75
| 0.928571
| 0
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| 0
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| true
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| 0.666667
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| null | 0
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| 0
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| 0
| 0
| 0
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| 0
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| 1
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| null | 0
| 0
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| 0
| 0
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| 1
| 0
| 1
| 0
|
0
| 6
|
35bc077a2c734c0114052ab7376f7ad601611de7
| 44,206
|
py
|
Python
|
common/servicechain/firewall/verify.py
|
vkolli/contrail-test-perf
|
db04b8924a2c330baabe3059788b149d957a7d67
|
[
"Apache-2.0"
] | 1
|
2017-06-13T04:42:34.000Z
|
2017-06-13T04:42:34.000Z
|
common/servicechain/firewall/verify.py
|
vkolli/contrail-test-perf
|
db04b8924a2c330baabe3059788b149d957a7d67
|
[
"Apache-2.0"
] | null | null | null |
common/servicechain/firewall/verify.py
|
vkolli/contrail-test-perf
|
db04b8924a2c330baabe3059788b149d957a7d67
|
[
"Apache-2.0"
] | null | null | null |
from time import sleep
from common.servicechain.config import ConfigSvcChain
from common.servicechain.verify import VerifySvcChain
from common.servicechain.mirror.verify import VerifySvcMirror
from common.servicechain.mirror.config import ConfigSvcMirror
from tcutils.util import get_random_cidr
from tcutils.util import get_random_name
from common.ecmp.ecmp_traffic import ECMPTraffic
from common.ecmp.ecmp_verify import ECMPVerify
class VerifySvcFirewall(VerifySvcMirror):
def verify_svc_span(self, in_net=False):
vn1_name = get_random_name("left_vn")
vn1_subnets = ['31.1.1.0/24']
vm1_name = get_random_name('left_vm')
vn2_name = get_random_name("right_vn")
vn2_subnets = ['41.2.2.0/24']
vm2_name = get_random_name('right_vm')
if in_net:
vn1_name = get_random_name("in_left_vn")
vn1_subnets = ['32.1.1.0/24']
vm1_name = get_random_name('in_left_vm')
vn2_name = get_random_name("in_right_vn")
vn2_subnets = ['42.2.2.0/24']
vm2_name = get_random_name('in_right_vm')
vn1_fixture = self.config_vn(vn1_name, vn1_subnets)
vn2_fixture = self.config_vn(vn2_name, vn2_subnets)
vm1_fixture = self.config_vm(vn1_fixture, vm1_name)
vm2_fixture = self.config_vm(vn2_fixture, vm2_name)
assert vm1_fixture.verify_on_setup()
assert vm2_fixture.verify_on_setup()
vm1_fixture.wait_till_vm_is_up()
vm2_fixture.wait_till_vm_is_up()
si_count = 3
st_name = get_random_name("tcp_svc_template")
si_prefix = "tcp_bridge_"
policy_name = get_random_name("allow_tcp")
if in_net:
st_name = get_random_name("in_tcp_svc_template")
si_prefix = "in_tcp_bridge_"
policy_name = get_random_name("in_allow_tcp")
tcp_st_fixture, tcp_si_fixtures = self.config_st_si(
st_name, si_prefix, si_count,
left_vn=vn1_name, right_vn=vn2_name)
else:
tcp_st_fixture, tcp_si_fixtures = self.config_st_si(
st_name, si_prefix, si_count)
action_list = self.chain_si(si_count, si_prefix)
# Update rule with specific port/protocol
rule = [{'direction': '<>',
'protocol': 'tcp',
'source_network': vn1_name,
'src_ports': [8000, 8000],
'dest_network': vn2_name,
'dst_ports': [9000, 9000],
'simple_action': None,
'action_list': {'apply_service': action_list}
}]
# Create new policy with rule to allow traffci from new VN's
tcp_policy_fixture = self.config_policy(policy_name, rule)
self.verify_si(tcp_si_fixtures)
st_name = get_random_name("udp_svc_template")
si_prefix = "udp_bridge_"
policy_name = get_random_name("allow_udp")
if in_net:
st_name = get_random_name("in_udp_svc_template")
si_prefix = "in_udp_bridge_"
policy_name = get_random_name("in_allow_udp")
udp_st_fixture, udp_si_fixtures = self.config_st_si(
st_name, si_prefix, si_count,
left_vn=vn1_name, right_vn=vn2_name)
else:
udp_st_fixture, udp_si_fixtures = self.config_st_si(
st_name, si_prefix, si_count)
action_list = self.chain_si(si_count, si_prefix)
# Update rule with specific port/protocol
rule = [{'direction': '<>',
'protocol': 'udp',
'source_network': vn1_name,
'src_ports': [8001, 8001],
'dest_network': vn2_name,
'dst_ports': [9001, 9001],
'simple_action': None,
'action_list': {'apply_service': action_list}
}]
# Create new policy with rule to allow traffci from new VN's
udp_policy_fixture = self.config_policy(policy_name, rule)
vn1_udp_policy_fix = self.attach_policy_to_vn(
[tcp_policy_fixture, udp_policy_fixture], vn1_fixture)
vn2_udp_policy_fix = self.attach_policy_to_vn(
[tcp_policy_fixture, udp_policy_fixture], vn2_fixture)
result, msg = self.validate_vn(vn1_name)
assert result, msg
result, msg = self.validate_vn(vn2_name)
assert result, msg
self.verify_si(udp_si_fixtures)
# Install traffic package in VM
vm1_fixture.install_pkg("Traffic")
vm2_fixture.install_pkg("Traffic")
sport = 8001
dport = 9001
sent, recv = self.verify_traffic(vm1_fixture, vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
sport = 8000
dport = 9000
sent, recv = self.verify_traffic(vm1_fixture, vm2_fixture,
'tcp', sport=sport, dport=dport)
errmsg = "TCP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
self.delete_si_st(tcp_si_fixtures, tcp_st_fixture)
sport = 8001
dport = 9001
sent, recv = self.verify_traffic(vm1_fixture, vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
sport = 8000
dport = 9000
sent, recv = self.verify_traffic(vm1_fixture, vm2_fixture,
'tcp', sport=sport, dport=dport)
errmsg = "TCP traffic with src port %s and dst port %s passed; Expected to fail" % (
sport, dport)
assert sent and recv == 0, errmsg
st_name = get_random_name("tcp_svc_template")
si_prefix = "tcp_bridge_"
policy_name = get_random_name("allow_tcp")
if in_net:
st_name = get_random_name("in_tcp_svc_template")
si_prefix = "in_tcp_bridge_"
policy_name = get_random_name("in_allow_tcp")
tcp_st_fixture, tcp_si_fixtures = self.config_st_si(
st_name, si_prefix, si_count,
left_vn=vn1_name, right_vn=vn2_name)
else:
tcp_st_fixture, tcp_si_fixtures = self.config_st_si(
st_name, si_prefix, si_count)
action_list = self.chain_si(si_count, si_prefix)
result, msg = self.validate_vn(vn1_name)
assert result, msg
result, msg = self.validate_vn(vn2_name)
assert result, msg
self.verify_si(tcp_si_fixtures)
sport = 8001
dport = 9001
sent, recv = self.verify_traffic(vm1_fixture, vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
sport = 8000
dport = 9000
sent, recv = self.verify_traffic(vm1_fixture, vm2_fixture,
'tcp', sport=sport, dport=dport)
errmsg = "TCP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
def verify_svc_transparent_datapath(
self, si_count=1, svc_scaling=False, max_inst=1,
svc_mode='transparent',
flavor=None, proto='any', src_ports=[0, -1],
dst_ports=[0, -1], svc_img_name=None, ci=False, st_version=1):
"""Validate the service chaining datapath"""
self.mgmt_vn_name = get_random_name("mgmt_vn")
self.mgmt_vn_subnets = [get_random_cidr(af=self.inputs.get_af())]
self.mgmt_vn_fixture = self.config_vn(
self.mgmt_vn_name, self.mgmt_vn_subnets)
self.vn1_name = get_random_name('bridge_vn1')
self.vn1_subnets = [get_random_cidr(af=self.inputs.get_af())]
self.vm1_name = get_random_name('bridge_vm1')
self.vn2_name = get_random_name('bridge_vn2')
self.vn2_subnets = [get_random_cidr(af=self.inputs.get_af())]
self.vm2_name = get_random_name('bridge_vm2')
self.action_list = []
self.if_list = []
self.st_name = get_random_name('service_template_1')
si_prefix = get_random_name('bridge_si') + '_'
self.policy_name = get_random_name('policy_transparent')
self.vn1_fixture = self.config_vn(self.vn1_name, self.vn1_subnets)
self.vn2_fixture = self.config_vn(self.vn2_name, self.vn2_subnets)
if st_version == 1:
(mgmt_vn, left_vn, right_vn) = (None, None, None)
else:
(mgmt_vn, left_vn, right_vn) = (self.mgmt_vn_fixture.vn_fq_name,
self.vn1_fixture.vn_fq_name, self.vn2_fixture.vn_fq_name)
self.st_fixture, self.si_fixtures = self.config_st_si(
self.st_name, si_prefix, si_count, svc_scaling, max_inst, svc_mode=svc_mode, flavor=flavor, project=self.inputs.project_name, svc_img_name=svc_img_name, st_version=st_version, mgmt_vn=mgmt_vn, left_vn=left_vn, right_vn=right_vn)
self.action_list = self.chain_si(
si_count, si_prefix, self.inputs.project_name)
self.rules = [
{
'direction': '<>',
'protocol': proto,
'source_network': self.vn1_name,
'src_ports': src_ports,
'dest_network': self.vn2_name,
'dst_ports': dst_ports,
'simple_action': None,
'action_list': {'apply_service': self.action_list}
},
]
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
if ci and self.inputs.get_af() == 'v4':
image_name = 'cirros-0.3.0-x86_64-uec'
else:
image_name = 'ubuntu-traffic'
self.vm1_fixture = self.config_and_verify_vm(
self.vm1_name, vn_fix=self.vn1_fixture, image_name=image_name)
self.vm2_fixture = self.config_and_verify_vm(
self.vm2_name, vn_fix=self.vn2_fixture, image_name=image_name)
result, msg = self.validate_vn(
self.vn1_name, project_name=self.inputs.project_name)
assert result, msg
result, msg = self.validate_vn(
self.vn2_name, project_name=self.inputs.project_name)
assert result, msg
if proto not in ['any', 'icmp']:
self.logger.info('Will skip Ping test')
else:
# Ping from left VM to right VM
errmsg = "Ping to Right VM %s from Left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip, count='3'), errmsg
return True
def verify_svc_in_network_datapath(self, si_count=1, svc_scaling=False,
max_inst=1, svc_mode='in-network-nat',
flavor=None,
static_route=[None, None, None],
ordered_interfaces=True,
svc_img_name=None,
vn1_subnets=None,
vn2_fixture=None,
vn2_subnets=None,
ci=False, st_version=1):
"""Validate the service chaining in network datapath"""
self.mgmt_vn_name = get_random_name("mgmt_vn")
self.mgmt_vn_subnets = [get_random_cidr(af=self.inputs.get_af())]
self.mgmt_vn_fixture = self.config_vn(
self.mgmt_vn_name, self.mgmt_vn_subnets)
self.vn1_subnets = vn1_subnets or [
get_random_cidr(af=self.inputs.get_af())]
self.vn1_name = get_random_name("in_network_vn1")
self.vn2_name = get_random_name("in_network_vn2")
self.vm1_name = get_random_name("in_network_vm1")
self.vn2_subnets = vn2_subnets or [
get_random_cidr(af=self.inputs.get_af())]
self.vm2_name = get_random_name("in_network_vm2")
self.action_list = []
self.if_list = [['management', False, False],
['left', True, False], ['right', True, False]]
for entry in static_route:
if entry != 'None':
self.if_list[static_route.index(entry)][2] = True
self.st_name = get_random_name("in_net_svc_template_1")
si_prefix = get_random_name("in_net_svc_instance") + "_"
self.policy_name = get_random_name("policy_in_network")
self.vn1_fixture = self.config_vn(self.vn1_name, self.vn1_subnets)
if vn2_fixture is None:
self.vn2_fixture = self.config_vn(self.vn2_name, self.vn2_subnets)
else:
self.vn2_fixture = vn2_fixture
self.vn2_fq_name = vn2_fixture.vn_fq_name
self.vn2_name = self.vn2_fq_name.split(':')[2]
self.st_fixture, self.si_fixtures = self.config_st_si(
self.st_name, si_prefix, si_count, svc_scaling, max_inst, mgmt_vn=self.mgmt_vn_fixture.vn_fq_name, left_vn=self.vn1_fixture.vn_fq_name,
right_vn=self.vn2_fixture.vn_fq_name, svc_mode=svc_mode, flavor=flavor, static_route=static_route, ordered_interfaces=ordered_interfaces, svc_img_name=svc_img_name, project=self.inputs.project_name, st_version=st_version)
self.action_list = self.chain_si(
si_count, si_prefix, self.inputs.project_name)
self.rules = [
{
'direction': '<>',
'protocol': 'any',
'source_network': self.vn1_fixture.vn_fq_name,
'src_ports': [0, -1],
'dest_network': self.vn2_fixture.vn_fq_name,
'dst_ports': [0, -1],
'simple_action': None,
'action_list': {'apply_service': self.action_list}
},
]
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
if ci and self.inputs.get_af() == 'v4' and self.inputs.orchestrator != 'vcenter':
image_name = 'cirros-0.3.0-x86_64-uec'
else:
image_name = 'ubuntu-traffic'
self.vm1_fixture = self.config_and_verify_vm(
self.vm1_name, vn_fix=self.vn1_fixture, image_name=image_name)
self.vm2_fixture = self.config_and_verify_vm(
self.vm2_name, vn_fix=self.vn2_fixture, image_name=image_name)
result, msg = self.validate_vn(
self.vn1_fixture.vn_name, project_name=self.vn1_fixture.project_name)
assert result, msg
result, msg = self.validate_vn(
self.vn2_fixture.vn_name, project_name=self.vn2_fixture.project_name, right_vn=True)
assert result, msg
# Ping from left VM to right VM
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
return True
def verify_multi_inline_svc(self, si_list=[('transparent', 1), ('in-network', 1), ('in-network-nat', 1)], flavor=None, ordered_interfaces=True, vn1_subnets=None, vn2_subnets=None, st_version=1, svc_img_name=None):
"""Validate in-line multi service chaining in network datapath"""
self.mgmt_vn_name = get_random_name("mgmt_vn")
self.mgmt_vn_subnets = [get_random_cidr(af=self.inputs.get_af())]
self.mgmt_vn_fixture = self.config_vn(
self.mgmt_vn_name, self.mgmt_vn_subnets)
vn1_subnets = vn1_subnets or [get_random_cidr(af=self.inputs.get_af())]
vn2_subnets = vn2_subnets or [get_random_cidr(af=self.inputs.get_af())]
self.vn1_name = get_random_name("in_network_vn1")
self.vn1_subnets = vn1_subnets
self.vm1_name = get_random_name("in_network_vm1")
self.vn2_name = get_random_name("in_network_vn2")
self.vn2_subnets = vn2_subnets
self.vm2_name = get_random_name("in_network_vm2")
self.action_list = []
self.si_list = []
self.policy_name = get_random_name("policy_in_network")
self.vn1_fixture = self.config_vn(self.vn1_name, self.vn1_subnets)
self.vn2_fixture = self.config_vn(self.vn2_name, self.vn2_subnets)
for si in si_list:
if st_version == 1:
(mgmt_vn, left_vn, right_vn) = (None, None, None)
else:
(mgmt_vn, left_vn, right_vn) = (self.mgmt_vn_fixture.vn_fq_name,
self.vn1_fixture.vn_fq_name, self.vn2_fixture.vn_fq_name)
self.if_list = [['management', False, False],
['left', True, False], ['right', True, False]]
svc_scaling = False
si_count = 1
self.st_name = get_random_name(
("multi_sc_") + si[0] + "_" + str(si_list.index(si)) + ("_st"))
si_prefix = get_random_name(
("multi_sc_") + si[0] + "_" + str(si_list.index(si)) + ("_si")) + "_"
max_inst = si[1]
if max_inst > 1:
svc_scaling = True
svc_mode = si[0]
(mgmt_vn, left_vn, right_vn) = (
None, self.vn1_fixture.vn_fq_name, self.vn2_fixture.vn_fq_name)
if svc_mode == 'transparent':
(mgmt_vn, left_vn, right_vn) = (None, None, None)
if st_version == 2:
(mgmt_vn, left_vn, right_vn) = (self.mgmt_vn_fixture.vn_fq_name,
self.vn1_fixture.vn_fq_name, self.vn2_fixture.vn_fq_name)
self.st_fixture, self.si_fixtures = self.config_st_si(
self.st_name, si_prefix, si_count, svc_scaling, max_inst, mgmt_vn=mgmt_vn, left_vn=left_vn,
right_vn=right_vn, svc_mode=svc_mode, flavor=flavor,
ordered_interfaces=ordered_interfaces, project=self.inputs.project_name, svc_img_name=svc_img_name, st_version=st_version)
action_step = self.chain_si(
si_count, si_prefix, self.inputs.project_name)
self.action_list += action_step
self.si_list += self.si_fixtures
self.rules = [
{
'direction': '<>',
'protocol': 'any',
'source_network': self.vn1_name,
'src_ports': [0, -1],
'dest_network': self.vn2_name,
'dst_ports': [0, -1],
'simple_action': None,
'action_list': {'apply_service': self.action_list}
},
]
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
self.vm1_fixture = self.config_and_verify_vm(
self.vm1_name, vn_fix=self.vn1_fixture)
self.vm2_fixture = self.config_and_verify_vm(
self.vm2_name, vn_fix=self.vn2_fixture)
result, msg = self.validate_vn(
self.vn1_name, project_name=self.inputs.project_name)
assert result, msg
result, msg = self.validate_vn(
self.vn2_name, project_name=self.inputs.project_name, right_vn=True)
assert result, msg
# Ping from left VM to right VM
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
return True
# end verify_multi_inline_svc
def verify_policy_delete_add(self):
# Delete policy
self.detach_policy(self.vn1_policy_fix)
self.detach_policy(self.vn2_policy_fix)
self.unconfig_policy(self.policy_fixture)
# Ping from left VM to right VM; expected to fail
errmsg = "Ping to right VM ip %s from left VM passed; expected to fail" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip, expectation=False), errmsg
# Create policy again
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
self.verify_si(self.si_fixtures)
# Wait for the existing flow entry to age
sleep(40)
# Ping from left VM to right VM
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
return True
def verify_protocol_port_change(self, mode='transparent'):
# Install traffic package in VM
self.vm1_fixture.install_pkg("Traffic")
self.vm2_fixture.install_pkg("Traffic")
sport = 8000
dport = 9000
sent, recv = self.verify_traffic(self.vm1_fixture, self.vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
sport = 8000
dport = 9001
sent, recv = self.verify_traffic(self.vm1_fixture, self.vm2_fixture,
'tcp', sport=sport, dport=dport)
errmsg = "TCP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
# Delete policy
self.detach_policy(self.vn1_policy_fix)
self.detach_policy(self.vn2_policy_fix)
self.unconfig_policy(self.policy_fixture)
# Update rule with specific port/protocol
action_list = {'apply_service': self.action_list}
new_rule = {'direction': '<>',
'protocol': 'tcp',
'source_network': self.vn1_name,
'src_ports': [8000, 8000],
'dest_network': self.vn2_name,
'dst_ports': [9001, 9001],
'simple_action': None,
'action_list': action_list
}
self.rules = [new_rule]
# Create new policy with rule to allow traffci from new VN's
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
self.verify_si(self.si_fixtures)
self.logger.debug("Send udp traffic; with policy rule %s", new_rule)
sport = 8000
dport = 9000
sent, recv = self.verify_traffic(self.vm1_fixture, self.vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s passed; Expected to fail" % (
sport, dport)
assert sent and recv == 0, errmsg
sport = 8000
dport = 9001
self.logger.debug("Send tcp traffic; with policy rule %s", new_rule)
sent, recv = self.verify_traffic(self.vm1_fixture, self.vm2_fixture,
'tcp', sport=sport, dport=dport)
errmsg = "TCP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
return True
def verify_add_new_vns(self):
# Delete policy
self.detach_policy(self.vn1_policy_fix)
self.detach_policy(self.vn2_policy_fix)
self.unconfig_policy(self.policy_fixture)
# Create one more left and right VN's
new_left_vn = "new_left_bridge_vn"
new_left_vn_net = [get_random_cidr(af=self.inputs.get_af())]
new_right_vn = "new_right_bridge_vn"
new_right_vn_net = [get_random_cidr(af=self.inputs.get_af())]
new_left_vn_fix = self.config_vn(new_left_vn, new_left_vn_net)
new_right_vn_fix = self.config_vn(new_right_vn, new_right_vn_net)
# Launch VMs in new left and right VN's
new_left_vm = 'new_left_bridge_vm'
new_right_vm = 'new_right_bridge_vm'
new_left_vm_fix = self.config_vm(new_left_vn_fix, new_left_vm)
new_right_vm_fix = self.config_vm(new_right_vn_fix, new_right_vm)
assert new_left_vm_fix.verify_on_setup()
assert new_right_vm_fix.verify_on_setup()
# Wait for VM's to come up
new_left_vm_fix.wait_till_vm_is_up()
new_right_vm_fix.wait_till_vm_is_up()
# Add rule to policy to allow traffic from new left_vn to right_vn
# through SI
new_rule = {'direction': '<>',
'protocol': 'any',
'source_network': new_left_vn,
'src_ports': [0, -1],
'dest_network': new_right_vn,
'dst_ports': [0, -1],
'simple_action': None,
'action_list': {'apply_service': self.action_list}
}
self.rules.append(new_rule)
# Create new policy with rule to allow traffci from new VN's
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
# attach policy to new VN's
new_policy_left_vn_fix = self.attach_policy_to_vn(
self.policy_fixture, new_left_vn_fix)
new_policy_right_vn_fix = self.attach_policy_to_vn(
self.policy_fixture, new_right_vn_fix)
self.verify_si(self.si_fixtures)
# Ping from left VM to right VM
sleep(5)
self.logger.info("Verfiy ICMP traffic between new VN's.")
errmsg = "Ping to right VM ip %s from left VM failed" % new_right_vm_fix.vm_ip
assert new_left_vm_fix.ping_with_certainty(
new_right_vm_fix.vm_ip), errmsg
self.logger.info(
"Verfiy ICMP traffic between new left VN and existing right VN.")
errmsg = "Ping to right VM ip %s from left VM passed; \
Expected tp Fail" % self.vm2_fixture.vm_ip
assert new_left_vm_fix.ping_with_certainty(self.vm2_fixture.vm_ip,
expectation=False), errmsg
self.logger.info(
"Verfiy ICMP traffic between existing VN's with allow all.")
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
self.logger.info(
"Verfiy ICMP traffic between existing left VN and new right VN.")
errmsg = "Ping to right VM ip %s from left VM passed; \
Expected to Fail" % new_right_vm_fix.vm_ip
assert self.vm1_fixture.ping_with_certainty(new_right_vm_fix.vm_ip,
expectation=False), errmsg
# Ping between left VN's
self.logger.info(
"Verfiy ICMP traffic between new left VN and existing left VN.")
errmsg = "Ping to left VM ip %s from another left VM in different VN \
passed; Expected to fail" % self.vm1_fixture.vm_ip
assert new_left_vm_fix.ping_with_certainty(self.vm1_fixture.vm_ip,
expectation=False), errmsg
self.logger.info(
"Verfiy ICMP traffic between new right VN and existing right VN.")
errmsg = "Ping to right VM ip %s from another right VM in different VN \
passed; Expected to fail" % self.vm2_fixture.vm_ip
assert new_right_vm_fix.ping_with_certainty(self.vm2_fixture.vm_ip,
expectation=False), errmsg
# Delete policy
self.detach_policy(self.vn1_policy_fix)
self.detach_policy(self.vn2_policy_fix)
self.detach_policy(new_policy_left_vn_fix)
self.detach_policy(new_policy_right_vn_fix)
self.unconfig_policy(self.policy_fixture)
# Add rule to policy to allow only tcp traffic from new left_vn to right_vn
# through SI
self.rules.remove(new_rule)
udp_rule = {'direction': '<>',
'protocol': 'udp',
'source_network': new_left_vn,
'src_ports': [8000, 8000],
'dest_network': new_right_vn,
'dst_ports': [9000, 9000],
'simple_action': None,
'action_list': {'apply_service': self.action_list}
}
self.rules.append(udp_rule)
# Create new policy with rule to allow traffci from new VN's
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
# attach policy to new VN's
new_policy_left_vn_fix = self.attach_policy_to_vn(
self.policy_fixture, new_left_vn_fix)
new_policy_right_vn_fix = self.attach_policy_to_vn(
self.policy_fixture, new_right_vn_fix)
self.verify_si(self.si_fixtures)
# Ping from left VM to right VM with udp rule
self.logger.info(
"Verify ICMP traffic with allow udp only rule from new left VN to new right VN")
errmsg = "Ping to right VM ip %s from left VM passed; Expected to fail" % new_right_vm_fix.vm_ip
assert new_left_vm_fix.ping_with_certainty(new_right_vm_fix.vm_ip,
expectation=False), errmsg
# Install traffic package in VM
self.vm1_fixture.install_pkg("Traffic")
self.vm2_fixture.install_pkg("Traffic")
new_left_vm_fix.install_pkg("Traffic")
new_right_vm_fix.install_pkg("Traffic")
self.logger.info(
"Verify UDP traffic with allow udp only rule from new left VN to new right VN")
sport = 8000
dport = 9000
sent, recv = self.verify_traffic(new_left_vm_fix, new_right_vm_fix,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
self.logger.info("Verfiy ICMP traffic with allow all.")
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
self.logger.info("Verify UDP traffic with allow all")
sport = 8001
dport = 9001
sent, recv = self.verify_traffic(self.vm1_fixture, self.vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
# Delete policy
self.delete_vm(new_left_vm_fix)
self.delete_vm(new_right_vm_fix)
self.detach_policy(new_policy_left_vn_fix)
self.detach_policy(new_policy_right_vn_fix)
self.delete_vn(new_left_vn_fix)
self.delete_vn(new_right_vn_fix)
self.verify_si(self.si_fixtures)
self.logger.info(
"Icmp traffic with allow all after deleting the new left and right VN.")
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
return True
def verify_add_new_vms(self):
# Launch VMs in new left and right VN's
new_left_vm = 'new_left_bridge_vm'
new_right_vm = 'new_right_bridge_vm'
new_left_vm_fix = self.config_vm(self.vn1_fixture, new_left_vm)
new_right_vm_fix = self.config_vm(self.vn2_fixture, new_right_vm)
assert new_left_vm_fix.verify_on_setup()
assert new_right_vm_fix.verify_on_setup()
# Wait for VM's to come up
new_left_vm_fix.wait_till_vm_is_up()
new_right_vm_fix.wait_till_vm_is_up()
# Ping from left VM to right VM
errmsg = "Ping to right VM ip %s from left VM failed" % new_right_vm_fix.vm_ip
assert new_left_vm_fix.ping_with_certainty(
new_right_vm_fix.vm_ip), errmsg
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert new_left_vm_fix.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
errmsg = "Ping to right VM ip %s from left VM failed" % new_right_vm_fix.vm_ip
assert self.vm1_fixture.ping_with_certainty(
new_right_vm_fix.vm_ip), errmsg
# Install traffic package in VM
self.vm1_fixture.install_pkg("Traffic")
self.vm2_fixture.install_pkg("Traffic")
self.logger.debug("Send udp traffic; with policy rule allow all")
sport = 8000
dport = 9000
sent, recv = self.verify_traffic(self.vm1_fixture, self.vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
# Delete policy
self.detach_policy(self.vn1_policy_fix)
self.detach_policy(self.vn2_policy_fix)
self.unconfig_policy(self.policy_fixture)
# Add rule to policy to allow traffic from new left_vn to right_vn
# through SI
new_rule = {'direction': '<>',
'protocol': 'udp',
'source_network': self.vn1_name,
'src_ports': [8000, 8000],
'dest_network': self.vn2_name,
'dst_ports': [9000, 9000],
'simple_action': None,
'action_list': {'apply_service': self.action_list}
}
self.rules = [new_rule]
# Create new policy with rule to allow traffci from new VN's
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
self.verify_si(self.si_fixtures)
# Install traffic package in VM
new_left_vm_fix.install_pkg("Traffic")
new_right_vm_fix.install_pkg("Traffic")
self.logger.debug("Send udp traffic; with policy rule %s", new_rule)
sport = 8000
dport = 9000
sent, recv = self.verify_traffic(self.vm1_fixture, self.vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
sent, recv = self.verify_traffic(self.vm1_fixture, new_right_vm_fix,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
sent, recv = self.verify_traffic(new_left_vm_fix, new_right_vm_fix,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
sent, recv = self.verify_traffic(new_left_vm_fix, self.vm2_fixture,
'udp', sport=sport, dport=dport)
errmsg = "UDP traffic with src port %s and dst port %s failed" % (
sport, dport)
assert sent and recv == sent, errmsg
# Ping from left VM to right VM
errmsg = "Ping to right VM ip %s from left VM failed; Expected to fail" % new_right_vm_fix.vm_ip
assert new_left_vm_fix.ping_with_certainty(
new_right_vm_fix.vm_ip, expectation=False), errmsg
errmsg = "Ping to right VM ip %s from left VM failed; Expected to fail" % self.vm2_fixture.vm_ip
assert new_left_vm_fix.ping_with_certainty(
self.vm2_fixture.vm_ip, expectation=False), errmsg
errmsg = "Ping to right VM ip %s from left VM failed; Expected to fail" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip, expectation=False), errmsg
errmsg = "Ping to right VM ip %s from left VM passed; Expected to fail" % new_right_vm_fix.vm_ip
assert self.vm1_fixture.ping_with_certainty(
new_right_vm_fix.vm_ip, expectation=False), errmsg
return True
def verify_firewall_with_mirroring(
self, si_count=1, svc_scaling=False, max_inst=1,
firewall_svc_mode='in-network', mirror_svc_mode='transparent', flavor='contrail_flavor_2cpu', vn1_subnets=None, vn2_subnets=None):
"""Validate the service chaining in network datapath"""
self.vn1_fq_name = "default-domain:" + self.inputs.project_name + \
":" + get_random_name("in_network_vn1")
self.vn1_name = self.vn1_fq_name.split(':')[2]
self.vn1_subnets = [
vn1_subnets or get_random_cidr(af=self.inputs.get_af())]
self.vm1_name = get_random_name("in_network_vm1")
self.vn2_fq_name = "default-domain:" + self.inputs.project_name + \
":" + get_random_name("in_network_vn2")
self.vn2_name = self.vn2_fq_name.split(':')[2]
self.vn2_subnets = [
vn2_subnets or get_random_cidr(af=self.inputs.get_af())]
self.vm2_name = get_random_name("in_network_vm2")
self.action_list = []
self.firewall_st_name = get_random_name("svc_firewall_template_1")
firewall_si_prefix = get_random_name("svc_firewall_instance") + "_"
self.mirror_st_name = get_random_name("svc_mirror_template_1")
mirror_si_prefix = get_random_name("svc_mirror_instance") + "_"
self.policy_name = get_random_name("policy_in_network")
self.vn1_fixture = self.config_vn(self.vn1_name, self.vn1_subnets)
self.vn2_fixture = self.config_vn(self.vn2_name, self.vn2_subnets)
if firewall_svc_mode == 'transparent':
self.if_list = []
self.st_fixture, self.firewall_si_fixtures = self.config_st_si(
self.firewall_st_name,
firewall_si_prefix, si_count,
svc_scaling, max_inst,
left_vn=None, right_vn=None,
svc_img_name='tiny_trans_fw',
svc_mode=firewall_svc_mode, flavor=flavor, project=self.inputs.project_name)
if firewall_svc_mode == 'in-network'or firewall_svc_mode == 'in-network-nat':
self.st_fixture, self.firewall_si_fixtures = self.config_st_si(
self.firewall_st_name,
firewall_si_prefix, si_count,
svc_scaling, max_inst,
left_vn=self.vn1_fq_name,
right_vn=self.vn2_fq_name,
svc_img_name='ubuntu-in-net',
svc_mode=firewall_svc_mode, flavor=flavor, project=self.inputs.project_name)
self.action_list = self.chain_si(
si_count, firewall_si_prefix, self.inputs.project_name)
self.st_fixture, self.mirror_si_fixtures = self.config_st_si(
self.mirror_st_name,
mirror_si_prefix, si_count,
left_vn=self.vn1_fq_name,
svc_type='analyzer',
svc_mode=mirror_svc_mode, flavor=flavor, project=self.inputs.project_name)
self.action_list += (self.chain_si(si_count,
mirror_si_prefix, self.inputs.project_name))
self.rules = [
{
'direction': '<>',
'protocol': 'any',
'source_network': self.vn1_name,
'src_ports': [0, -1],
'dest_network': self.vn2_name,
'dst_ports': [0, -1],
'simple_action': 'pass',
'action_list': {'simple_action': 'pass',
'mirror_to': {'analyzer_name': self.action_list[1]},
'apply_service': self.action_list[:1]}
},
]
self.policy_fixture = self.config_policy(self.policy_name, self.rules)
self.vn1_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn1_fixture)
self.vn2_policy_fix = self.attach_policy_to_vn(
self.policy_fixture, self.vn2_fixture)
self.vm1_fixture = self.config_vm(self.vn1_fixture, self.vm1_name)
self.vm2_fixture = self.config_vm(self.vn2_fixture, self.vm2_name)
self.vm1_fixture.wait_till_vm_is_up()
self.vm2_fixture.wait_till_vm_is_up()
result, msg = self.validate_vn(
self.vn1_name, project_name=self.inputs.project_name)
assert result, msg
result, msg = self.validate_vn(
self.vn2_name, project_name=self.inputs.project_name)
assert result, msg
self.verify_si(self.firewall_si_fixtures)
self.verify_si(self.mirror_si_fixtures)
for si_fix in self.firewall_si_fixtures:
svms = self.get_svms_in_si(si_fix, self.inputs.project_name)
for svm in svms:
svm_name = svm.name
host = self.get_svm_compute(svm_name)
svm_node_ip = host
# Ping from left VM to right VM
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
# Verify ICMP mirror
sessions = self.tcpdump_on_all_analyzer(
self.mirror_si_fixtures, mirror_si_prefix, si_count)
errmsg = "Ping to right VM ip %s from left VM failed" % self.vm2_fixture.vm_ip
assert self.vm1_fixture.ping_with_certainty(
self.vm2_fixture.vm_ip), errmsg
for svm_name, (session, pcap) in sessions.items():
if self.vm1_fixture.vm_node_ip == self.vm2_fixture.vm_node_ip:
if firewall_svc_mode == 'transparent':
count = 20
else:
count = 10
if self.vm1_fixture.vm_node_ip != self.vm2_fixture.vm_node_ip:
if firewall_svc_mode == 'in-network' and self.vm1_fixture.vm_node_ip == svm_node_ip:
count = 10
else:
count = 20
self.verify_icmp_mirror(svm_name, session, pcap, count)
return True
| 47.178228
| 240
| 0.611546
| 5,944
| 44,206
| 4.21568
| 0.039367
| 0.036435
| 0.028015
| 0.032564
| 0.893567
| 0.859845
| 0.816226
| 0.782584
| 0.769375
| 0.756246
| 0
| 0.020658
| 0.299168
| 44,206
| 936
| 241
| 47.228632
| 0.78816
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| 0.12277
| 0.003119
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| 0.074307
| 1
| 0.011335
| false
| 0.013854
| 0.011335
| 0
| 0.034005
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| 0
| 0
| null | 0
| 0
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| 0
|
0
| 6
|
ea555c13b928b17a4c61da927eefad325d7cbc29
| 6,369
|
py
|
Python
|
ClumpFinding.py
|
BlackAdder84/Bioinformatics
|
6cc662b6c4a3349a89f6fdd26f05f1f6228bd912
|
[
"MIT"
] | 1
|
2017-06-09T03:06:21.000Z
|
2017-06-09T03:06:21.000Z
|
ClumpFinding.py
|
BlackAdder84/Bioinformatics
|
6cc662b6c4a3349a89f6fdd26f05f1f6228bd912
|
[
"MIT"
] | null | null | null |
ClumpFinding.py
|
BlackAdder84/Bioinformatics
|
6cc662b6c4a3349a89f6fdd26f05f1f6228bd912
|
[
"MIT"
] | 1
|
2017-05-01T21:15:11.000Z
|
2017-05-01T21:15:11.000Z
|
"""
Passed all Tests (even E.Coli)
Solves E.Coli problem. Yeah!
"""
def ClumpFinding(seq,k,l,t):
kmers_dict = {}
valid_kmers = []
for i in range(l-k+1):
kmer = seq[i:i+k]
if kmer in kmers_dict.keys():
kmers_dict[kmer] += 1
if kmers_dict[kmer] >= t and kmer not in valid_kmers:
valid_kmers.append(kmer)
else:
kmers_dict[kmer] = 1
for i in range(l-k+1,len(seq)-k+1):
in_kmer = seq[i:i+k]
out_idx = i-l+k-1
out_kmer = seq[out_idx:out_idx+k]
kmers_dict[out_kmer] -= 1 # substract kmer going out of window
if in_kmer in kmers_dict.keys():
kmers_dict[in_kmer] += 1
if kmers_dict[in_kmer] >= t and in_kmer not in valid_kmers:
valid_kmers.append(in_kmer)
else:
kmers_dict[in_kmer] = 1
if kmers_dict[out_kmer] == 0:
kmers_dict.pop(out_kmer, None) # remove kmer from dict if count reaches 0
return valid_kmers
def TestCases():
# CGACA GAAGA
print Clump('CGGACTCGACAGATGTGAAGAACGACAATGTGAAGACTCGACACGACAGAGTGAAGAGAAGAGGAAACATTGTAA', 5, 50, 4)
# AAACCAGGTGG
print Clump('GCGGTTATGCACCGTTCAAATTAGCAAACCACTAAGCGACGTAGTCTGGATTGATTTCTCCCTACCAGTGACCCAAGACGCGTTAGTGAGTTAAGTTCATATCCAGTACCTGCCGCCCTCTGTACTTGGGCGTCCGATTCGCATGCTTACTCAGGTGGAGGACACGATAATCTGATTAAACTGAGCTAAACCAGGTGGAACCAGAAACCAGGTGGGGAGTCTCGCTTCAAGCCGTTCTTGCGATCAAACCAGGTGGTCCATTATGAAACCAGGTGGCTAAACCAGGTGGTCCAGATCCTCGAATGATGTCGGTGCACATCAAAACCAGGTGGGGTGGTGGAACGTAAAACCAGGTGGCATAAACCAGGTGGGCCGGTTCGTAAACCAGGTGAAACCAGGTGGGGTGGAAACCAGGTGGGTTACAAATTACGTTGAGATGGCCCAAACCAGGTGGTGGGCTTCACCCATGTCAACAAACCACCCTATGGAACTAAACCAGGTGGAACCAGGTGGTGAAGGCTTATCCTCAGGAAAAACCAGGTGGAGGTGGTGAAATAAAACCAGGTGGACCAGGTGGATAACCCTCGCCTCGCTTCTCAACCGAGACCTGGATAAACCAGGTGGGGTGGTCCACCGATTTTTGAGACACTAGAAACCAGGTGGGCGGGGAAACCAGGTGGCAAACCAGGTGGGGTGGACGGAAACCAGGTGGATATGTCATAAAACCAAACCAGGTGGTGCACCCCCATGGTGTGTCTTATCCGTGCGTATAAACCAGGTGGTCGCACGGCTTCCACTTGCTGAGAATAGGCCCGCAGGGTCAGTGCCATGCCCTCCGTCACTCGATATGTGTTGTAAGAGTGGTTACCCCTTCATTGAAGTCGCCCACAGCCCCACCTGCATTGCTAGACTATCACCCTACAGTAGGCCTTTTCGCCTTCTTCAAGCAGCAATCTCTTATCCGCGGATGGGCGCGGCGAGCGTGGCGTCCCCGAACATTTTTACCTAACGTGTTTTGTTGGCCGCAAGCCTTCCCTCTAGTCCACCTCAGCCATTCAGCCTAGTAGCTTTCAAGCCGAGCCTTCCATATCTAATGGACCGTCCAGAATTTCACACGTTTCACAGGGCTGTGTTCGACCGCCCGTAATGCTGTTTCACAGGCGATCGCCTTGCGGTTTTTTCACAGATCGCAGCCGATGGACATGCCAACTCGATTTTCACAGAGTTTTTCACAGCGGTTTCACAGCACAGCAGTGATTGTTTCACAGCAATTTTCACTTTCACAGGGGCCCTTTTCACAGCTCAGGGCTCTTTTCACTTTCACAGTTTCACAGCGCTCCTTTCACAGAGCGGGGAAATTTAAGGGAACACTCAAGGGAACAAGGGAACACACAAAGGGAACACAACACAACACATAAGGGAACACTTTCACAGAACACAAAAGTCCGAAATCATCAGCGGCGAAGGGATTTCACAGACAGACACTTTCACAGCGCATTTCACAGATACGTACTTTCACAGGCGTACTTTCACAGACTTTCACAGAGGACAAGCTCAATTTTCACAGACAGGCTGGATAAATTTCACAGCGGTAAGGGTTTCACAGCACACATAAGGGAACACGAATTTCACAGCAGGGAACACCTCTACGAGTAATCTATTACTCTACCTACTGAAGGGAACACACCGAAGACCTACTATTACCTATTACTCTTAAAGGGAACACATTACAAGGGAACACACTCTCTCGTCATATCTCACCTCTCTATTACTCTTAAGGGAACACCTTCTCGATCAACCTATTACTCTATGGAGATAGAGATATTCCAGACATATGGAGATAACATGGAGATATGGAGATAATGGAGATGGAGATAGCTCTTATATTTATCCTATGGAGATATGATACTATTAATGGAGATAATTCTAATGGAGATATAATTACTCTAAGAGGATGGGATCTCGGGCTATTACTCTAATGGAGATAAGCACTATTACTCTAGGAAATGGAGATATGTCAATGGAGATATGTAATGGAGATAGAGGGAGATGGAGTCGCCATTTCATAATCGCCATTTCATAGTTCAGGAATCGCCATTTCCGCCATTTCTAAGATGGAGTCGCCATTTCTACGTATGGAGATAGGATCGCCATTTCATACGACCCGTTGGATATCGCCATTTCCTCGCCATTTCTGGTGACATTTCTCGCCATTTCATTTCTGGAGATAGATGGATCTCGCCATTTCATAGGAATCGCCATTTCCACGTAGGGGGGGCCACAATCCGTAGGTCGGAATTCAGACTCGCCATTTCCCATCGCCATTTCTTCACCTGTATGCCGATCCCTTCGCCATTTCTCATGGAGATAACTCTCTCTCGCCATTTCTCGCCATTTCCATTTCACTCTCATTCGCCATCGCCATTTCCATTCGCCATTTCATCGCCATTTCTTCAGGATAAGATATCGCCATTTCGACTCTCATTCGCATACTGACTCTCATTCTCATCTCGCCATTTCTCATCTGACTCTCATCCTGGGGGAAACTTGCGACTCTCATCACACTTCCGTCGACTCTCATACTGGCGGATAGCATAGGAGCCATTTAAAGACTCTCATTCTCATTCGAGACTCTCATTCAAATCCTACGAGGACTCTCATATAGACTCTCATATCATTACGAGGACTCTCATATACGAGCCATGCATGTGGCGACGACTCTCATCTACGAGCCATGCAAGCAGAATCTACGAGCGACTCTCATTACGAGCCATGTGACCGTACGAGCCATGCATGCATGCCATGCTGACTCTCATCGAGTACGAGCCATGGAAGTTCTTGTTGGTTCGTAGCCCAAGAGCTGAAGTTACGAGCCTACGAGCCATGAAGTTACTTTTACGAGCCATGAAGCTTACGATACGAGCCATGCGAGCCATGCATCCGCGCTACGAGCCATGTTCCAGTACGAGCCATGTTAGTTGCTGAAGTTAAGTTTGGCGCTGAAGTTTGTACGAGCCATGTGCCCGCTGAAGTTTGTTGTACGAGCCATGCATGCTGAAGTTAATGGCTGAAGTTAGCGTTTGCGGGCAGATCCTCATTCTACGATACGAGCCATGCCATGCAGCTGAAGTTAAGTTGGGTTACGAGCCATGCGAGCCATGTGAAGTACGAGCCATGCTGGCTGAAGTTGTTTGTGCTGCTGAAGTTGCTCTTGTCTCTAGCTGAAGTTGCCAACAGGGCTGAAGCTGAAGTTTAAGCTGAAGTTGCGAGCAGGCTGAAGTTATCGGATTGGGGCTGAAGTTCAACCTCCCGTCCCCCCACACTATATTCCCGTCCCCCCCCGCGCACGCGCCGTCTCCCGTCCCCCCTATCCCGTGCGCACGCGACGCGATCCCGTCCCCCCAGAGTGCGCGCACGCGTCCCCCTTCCCGTCCCCCTCTCCCGGGCGCACGCGTCGCTCAACATTTCCGCGCACGCGTCGCGCACGCGGGCGCACGCGGGTCCCGTCCCCCCCCCTCTTCGGCGCACGCGGAATTCCCGTCGCGCACGCGTCCCGTCCCGCGCACGCGTCGCGCACGCGACTGCCCTAACCAACAGTGCGCACGCGCCGGTAACCCGGTAACCCGGTAACCGCGCACGCGGGCGCACGCGCGTAACCCGCGCACGCGCCGCGCACGCGGCCCGGTTCCCGTCCCCCCCGGTAACCCGGTAACTCCCGTCCCCCGTAACCCGGTGCGCACGCGCCCGGCGCACGCGGAGCGCACGCGCCCCCCCCGGTAATAGCGCACGCGCCCGGGCGCACGCGCCCGGTAACCCGGTAACCCGGGCGCGCGCACGCGGCGGCGCACGCGGCGCACGCGGCGCACGCG',11,566,18)
# AA FAILS
print Clump('AAAACGTCGAAAAA',2,4,2)
# A C G T
print Clump('ACGTACGT',1,5,2)
# AAA CAG CAT CCA GCC TTC
print Clump('CCACGCGGTGTACGCTGCAAAAAGCCTTGCTGAATCAAATAAGGTTCCAGCACATCCTCAATGGTTTCACGTTCTTCGCCAATGGCTGCCGCCAGGTTATCCAGACCTACAGGTCCACCAAAGAACTTATCGATTACCGCCAGCAACAATTTGCGGTCCATATAATCGAAACCTTCAGCATCGACATTCAACATATCCAGCG',3,25,3)
# Ecoli sequence must be loaded from file
# Change the function called by main to the desired one.
def main(args):
ClumpFinding(*args)
# from console, arguments must be passed inside a list formatted as string:
# python template.py "['hello', 5, {'age': 30}, [1, 2, 3, 4]]"
if __name__ == '__main__':
import sys, ast
if len(sys.argv) == 2 and type(sys.argv[1]) is str:
try:
args = ast.literal_eval(sys.argv[1])
except:
print "ERROR evaluating input parameters"
sys.exit()
main(args)
else:
print "Incorrect argument syntax."
print "There must be only one argument formatted as string with double quotes"
print "This string must contain a list with all parameters in the correct format"
print "Exampe:"
print " python template.py \"['hello', 5, {'age': 30}, [1, 2, 3, 4]] \" "
| 87.246575
| 3,898
| 0.853038
| 338
| 6,369
| 15.952663
| 0.399408
| 0.02003
| 0.001669
| 0.006677
| 0.055082
| 0.048405
| 0.048405
| 0.034496
| 0.011499
| 0.011499
| 0
| 0.008612
| 0.10661
| 6,369
| 72
| 3,899
| 88.458333
| 0.939016
| 0.058722
| 0
| 0.0625
| 0
| 0
| 0.746619
| 0.700811
| 0
| 1
| 0
| 0
| 0
| 0
| null | null | 0
| 0.020833
| null | null | 0.229167
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| null | 1
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| 0
|
0
| 6
|
ea5e1e44e8680ea6f28f1280ada65ab797f0b5c2
| 40
|
py
|
Python
|
extensions/iocompython/examples/asteroid-client-pyglet/game/__init__.py
|
iocafe/iocom
|
9762b78fa1591994c74ed1fc6fe23b9ef44e0dff
|
[
"MIT"
] | 1
|
2020-04-28T23:25:50.000Z
|
2020-04-28T23:25:50.000Z
|
extensions/iocompython/examples/asteroid-client-pyglet/game/__init__.py
|
iocafe/iocom
|
9762b78fa1591994c74ed1fc6fe23b9ef44e0dff
|
[
"MIT"
] | 11
|
2020-01-30T16:27:24.000Z
|
2020-08-09T06:25:06.000Z
|
extensions/iocompython/examples/asteroid-client-pyglet/game/__init__.py
|
iocafe/iocom
|
9762b78fa1591994c74ed1fc6fe23b9ef44e0dff
|
[
"MIT"
] | null | null | null |
from . import physicalobject, resources
| 20
| 39
| 0.825
| 4
| 40
| 8.25
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| 0.125
| 40
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| 40
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| 0
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| 1
| 0
| 1
| 0
|
0
| 6
|
ea957d7948390b4d23e2580e71838b479bcfc820
| 26,978
|
py
|
Python
|
tcrdist/rep_funcs.py
|
agartland/tcrdist3
|
34f8d50e7448b2bf7cf7cd9ab9a2d80759f47240
|
[
"MIT"
] | 26
|
2020-12-28T17:37:01.000Z
|
2022-01-29T01:31:13.000Z
|
tcrdist/rep_funcs.py
|
agartland/tcrdist3
|
34f8d50e7448b2bf7cf7cd9ab9a2d80759f47240
|
[
"MIT"
] | 31
|
2020-08-17T22:17:57.000Z
|
2022-03-18T23:47:34.000Z
|
tcrdist/rep_funcs.py
|
agartland/tcrdist3
|
34f8d50e7448b2bf7cf7cd9ab9a2d80759f47240
|
[
"MIT"
] | 7
|
2020-08-18T23:55:40.000Z
|
2021-09-22T18:15:54.000Z
|
"""
tcrdist3: Functional Programming Approach For Higher Memory Demand Use Cases
"""
import pwseqdist as pw
import pandas as pd
import numpy as np
from scipy import sparse
import os
from tcrdist import memory
import secrets
import parmap
import shutil
import multiprocessing
__all__ = ['_pw',
'_pws',
'compute_pw_sparse_out_of_memory',
'compute_pws_sparse',
'pw2dense']
def pw2dense(pw, maxd):
"""Make a pairwise distance matrix dense
assuming -1 is used to encode D = 0"""
pw = np.asarray(pw.todense())
pw[pw == 0] = maxd + 1
# pw[np.diag_indices_from(pw)] = 0
pw[pw == -1] = 0
return pw
def _pws(df, metrics, weights, kargs, df2 = None, cpu = 1, uniquify = True, store = False):
"""
_pws performs pairwise distance calculation across a multiple
columns of a Pandas DataFrame. This naturally permits calculation of
a CDR-weighted tcrdistance that incorporates dissimilarity across
multiple complimentarity determining regions (see example below):
Parameters
----------
df : pd.DataFrame
Clones DataFrame containing, at a minimum, columns with CDR sequences
df2 : pd.DataFrame or None
Second clones DataFrame containing, at a minimum, columns with CDR sequences
metrics : dict
Dictionary of functions, specifying the distance metrics to apply to each CDR
weights : dict
Weights determining the contributions of each CDR distance to the aggregate distance
kargs : dict
Dictionary of Dictionaries
cpu : int
Number of available cpus
use_numba : bool
If True, use must use a numba compatible metric
store : bool
If False, only full tcrdist is returned. If True,
all component distance matrices are returned.
Returns
-------
s : dictionary with tcr_distance.
Example
-------
import pwseqdist as pw
import pandas as pd
from tcrdist.rep_funcs import _pw, _pw2
# Define metrics for each region
metrics = { "cdr3_a_aa" : pw.metrics.nb_vector_tcrdist,
"pmhc_a_aa" : pw.metrics.nb_vector_tcrdist,
"cdr2_a_aa" : pw.metrics.nb_vector_tcrdist,
"cdr1_a_aa" : pw.metrics.nb_vector_tcrdist,
"cdr3_b_aa" : pw.metrics.nb_vector_tcrdist,
"pmhc_b_aa" : pw.metrics.nb_vector_tcrdist,
"cdr2_b_aa" : pw.metrics.nb_vector_tcrdist,
"cdr1_b_aa" : pw.metrics.nb_vector_tcrdist}
# Define weights
weights = {
"cdr3_a_aa" : 3,
"pmhc_a_aa" : 1,
"cdr2_a_aa" : 1,
"cdr1_a_aa" : 1,
"cdr3_b_aa" : 3,
"pmhc_b_aa" : 1,
"cdr2_b_aa" : 1,
"cdr1_b_aa" : 1}
kargs = { "cdr3_a_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':3, 'ctrim':2, 'fixed_gappos':False},
"pmhc_a_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr2_a_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr1_a_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr3_b_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':3, 'ctrim':2, 'fixed_gappos':False},
"pmhc_b_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr2_b_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr1_b_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True}}
df = pd.DataFrame("dash2.csv")
_pws(df = df, metrics = metrics, weights= weights, kargs=kargs, cpu = 1, store = False)
"""
metric_keys = list(metrics.keys())
weight_keys = list(weights.keys())
assert metric_keys == weight_keys, "metrics and weights keys must be identical"
if kargs is not None:
kargs_keys = list(kargs.keys())
assert metric_keys == kargs_keys, "metrics and kargs keys must be identical"
tcrdist = None
s = dict()
for k in metric_keys:
if df2 is None:
pw_mat = _pw(seqs1 = df[k].values, metric = metrics[k], ncpus = cpu, uniqify= uniquify, **kargs[k])
else:
pw_mat = _pw(seqs1 = df[k].values, seqs2 = df2[k].values, metric = metrics[k], ncpus = cpu, uniqify= uniquify, **kargs[k])
if store:
s[k] = pw_mat
if tcrdist is None:
tcrdist = np.zeros(pw_mat.shape, dtype=np.int16)
tcrdist = tcrdist + (weights[k] * pw_mat)
s['tcrdist'] = tcrdist
return s
def _pw(metric, seqs1, seqs2=None, ncpus=1, uniqify= True, use_numba = False, **kwargs):
"""
This is a wrapper for accessing pwseqdist version > 0.2.
No matter what, it returns squareform results
"""
pw_mat = pw.apply_pairwise_rect(metric = metric,
seqs1 = seqs1,
seqs2 = seqs2,
ncpus = ncpus,
uniqify = uniqify,
use_numba = use_numba,
**kwargs)
# if len(pw_mat.shape) == 1:
# from scipy.spatial.distance import squareform
# pw_mat = squareform(pw_mat)
return pw_mat
def compute_pws_sparse(df, metrics, weights, kargs, radius=50, df2=None, cpu=1, chunk_size=500, store=False, pm_pbar=True):
"""
compute_pw_sparse performs pairwise distance calculation across multiple
columns of a Pandas DataFrame. This naturally permits calculation of
a CDR-weighted tcrdistance that incorporates dissimilarity across
multiple complimentarity determining regions (see example below):
Radius is applied per chain.
TODO: allow for different radius per chain
Parameters
----------
df : pd.DataFrame
Clones DataFrame containing, at a minimum, columns with CDR sequences
df2 : pd.DataFrame or None
Second clones DataFrame containing, at a minimum, columns with CDR sequences
metrics : dict
Dictionary of functions, specifying the distance metrics to apply to each CDR
weights : dict
Weights determining the contributions of each CDR distance to the aggregate distance
kargs : dict
Dictionary of Dictionaries
cpu : int
Number of available cpus
radius : int
Only distances <= radius will be retained.
chunk_size : int
Number of rows that will make up each row chunk of [df x df2]
which will be computed densely.
store : bool
IGNORED
Returns
-------
s : dictionary with tcr_distance.
Example
-------
import pwseqdist as pw
import pandas as pd
from tcrdist.rep_funcs import _pw, _pw2
# Define metrics for each region
metrics = { "cdr3_a_aa" : pw.metrics.nb_vector_tcrdist,
"pmhc_a_aa" : pw.metrics.nb_vector_tcrdist,
"cdr2_a_aa" : pw.metrics.nb_vector_tcrdist,
"cdr1_a_aa" : pw.metrics.nb_vector_tcrdist,
"cdr3_b_aa" : pw.metrics.nb_vector_tcrdist,
"pmhc_b_aa" : pw.metrics.nb_vector_tcrdist,
"cdr2_b_aa" : pw.metrics.nb_vector_tcrdist,
"cdr1_b_aa" : pw.metrics.nb_vector_tcrdist}
# Define weights
weights = {
"cdr3_a_aa" : 3,
"pmhc_a_aa" : 1,
"cdr2_a_aa" : 1,
"cdr1_a_aa" : 1,
"cdr3_b_aa" : 3,
"pmhc_b_aa" : 1,
"cdr2_b_aa" : 1,
"cdr1_b_aa" : 1}
kargs = { "cdr3_a_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':3, 'ctrim':2, 'fixed_gappos':False},
"pmhc_a_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr2_a_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr1_a_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr3_b_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':3, 'ctrim':2, 'fixed_gappos':False},
"pmhc_b_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr2_b_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True},
"cdr1_b_aa" : {'use_numba': True, 'distance_matrix': pw.matrices.tcr_nb_distance_matrix, 'dist_weight': 1, 'gap_penalty':4, 'ntrim':0, 'ctrim':0, 'fixed_gappos':True}}
df = pd.DataFrame("dash2.csv")
_pws(df = df, metrics = metrics, weights= weights, kargs=kargs, cpu = 1, store = False)
"""
metric_keys = [k for k in metrics.keys() if not 'cdr3' in k]
weight_keys = [k for k in weights.keys() if not 'cdr3' in k]
assert metric_keys == weight_keys, "metrics and weights keys must be identical"
if kargs is not None:
kargs_keys = [k for k in kargs.keys() if not 'cdr3' in k]
assert metric_keys == kargs_keys, "metrics and kargs keys must be identical"
n1 = df.shape[0]
"""Compute all but CDR3 as normal, but do not reexpand.
Computing unique distances should not be memory or CPU intensive"""
tcrdist = None
components = dict()
for k in metric_keys:
if df2 is None:
seqs2 = None
else:
seqs2 = df2[k].values
"""With reexapnd = False, returns: pw_mat, uind_i1, uind_i2"""
pwmat, ind1, ind2 = pw.apply_pairwise_rect(metric=metrics[k],
seqs1=df[k].values,
seqs2=seqs2,
ncpus=min(cpu, 2),
uniqify=True,
reexpand=False,
**kargs[k])
components[k] = (pwmat * weights[k], ind1, ind2)
"""Can't do this because it will be huge. Also can't compute list of
potential D < radius because that also could be too large.
But need to pre-compute these non-CDR3 because otherwise the CDR3
matrix won't be sparse enough with the radius.
Solution: chunk the computation here. Only compute subsets of potential
seqs pairs sparsely and spread across processors."""
if cpu > 1 and n1 > chunk_size:
"""Chunk along df (rows) only"""
chunk_func = lambda l, n: [np.array(l[i:i + n], dtype=np.int64) for i in range(0, len(l), n)]
# chunksz = max(len(pw_indices) // cpu, 1)
"""Chunked indices is a list of arrays of indices"""
"""List of the chunked [chunk_size,] arrays"""
chunked_indices = chunk_func(np.arange(n1, dtype=np.int64), chunk_size)
with multiprocessing.Pool(cpu) as pool:
dists = parmap.map(memory._sparse_cdr3_tcrdist_shard,
chunked_indices,
components,
df,
metrics,
weights,
kargs,
radius,
df2,
pm_parallel=True,
pm_pool=pool,
pm_pbar=pm_pbar)
full_S = sparse.vstack(dists)
else:
full_S = memory._sparse_cdr3_tcrdist_shard(np.arange(n1, dtype=np.int64),
components,
df,
metrics,
weights,
kargs,
radius,
df2)
return {'tcrdist': full_S}
def compute_n_tally_out_of_memory(fragments,
matrix_name = "rw_beta",
to_file = False,
to_memory = True,
pm_processes = 2,
**kwargs):
"""
Parameters
---------
fragments : tuple
3-part tuple
0 : TCRrep instance
1 : list of rows in each fragment
2 : filename holding the distances as a .npz
matrix_name : str
For 'beta' chain dists use 'rw_beta'
to_file : bool
If True, than a file is written to disk containing all the n_tally
to_memory : bool
If True, the n_tally is loaded directly to memory
**kwargs
Keyword arguments are passed directly to tcridist.memory.gen_n_tally_on_fragment,
including:
x_cols : list
categorical variable 'epitope']
count_col : str
column for counts
knn_neighbors : bool
option to choose a fixed number of neighbors (NOT RECOMMENDED)
knn_radius : int
maximum radius for finding neighbors
Notes
-----
We envision that user may want to run nndif
multiple times with different categorical variables
and may not want to go through the computational
intensive steps of computing TCRdistance each time.
This can be accomodated via setting cleanup to False:
compute_pw_sparse_out_of_memory(cleanup=False)
Example
-------
from scipy import sparse
from tcrdist.repertoire import TCRrep
from tcrdist.rep_funcs import compute_pw_sparse_out_of_memory
df = pd.read_csv("dash.csv")
tr = TCRrep(cell_df = df,
organism = 'mouse',
chains = ['beta'],
db_file = 'alphabeta_gammadelta_db.tsv',
compute_distances = True,
store_all_cdr = False)
S, chunks = compute_pw_sparse_out_of_memory(tr, matrix_name = "rw_beta", max_distance = 1000, cleanup = False)
# dest contains all the shards
"""
# [(<tcrdist.repertoire.TCRrep at 0x14035b6d0>,
# range(0, 500),
# 'd3be945e8956/0.rw_beta.npz'),
# rearrange fragments in order (tr, ind, .npz, .csv)
fragments = [(x[0], x[1], x[2], f"{x[2]}.nndif.csv") for x in fragments ]
#fragments = [(tr, f"{dest}/{i}.{matrix_name}.npz", ind, f"{dest}/{i}.nndif.cvs") for i,ind in enumerate(row_chunks)]
csvfragments = parmap.starmap(memory.gen_n_tally_on_fragment, fragments, **kwargs, pm_pbar=True, pm_processes = pm_processes)
if to_file:
dest =os.path.dirname(csvfragments[0])
nndiff_file = memory._concat_to_file(dest =dest, fragments =csvfragments)
return nndiff_file
if to_memory:
nndiff = memory._concat_to_memory(fragments = csvfragments)
return nndiff
def compute_pw_sparse_out_of_memory(tr,
row_size = 500,
pm_processes = 2,
pm_pbar = True,
max_distance = 50,
matrix_name = 'rw_beta',
reassemble = True,
cleanup = True):
"""
Instead of calling TCRrep.compute_distances(), this
function permits a parallelizable approach that does
not require holding a large matrix in memory.
Default behavior is to reassemble a scipy
sparse matrix from a set of sub matrices written to disk fragment.
With <reassemble = True> function returns a scipy sparse matrix.
Space savings are achieved because any value above <max_distance> is set to zero.
True zero distances are set to 1.
Can be used to form a network of TCRs with tcrdistances < max_distance,
Parameters
----------
tr : TCRrep
TCRrep instance with clone_df
row_size : int
How many rows to process in memory at once
pm_processes : int
Numbe of concurrent parallel processes to run at once
pm_bar : bool
If True, show progress bar.
max_distance : int
Max distance
matrix_name : str
Name of matrix to return (i.e, 'rw_beta' or 'rw_alpha')
reassemble: True
If true, makes one matrix from all the sparse sub matrices.
cleanup: bool,
if True, deletes temporary files.
Returns
-------
csr_full : sparse scipy matrix
dest : str
name of the folder that holds fragments
Examples
--------
import numpy as np
import pandas as pd
from tcrdist.repertoire import TCRrep
from tcrdist.rep_funcs import compute_pw_sparse_out_of_memory
df = pd.read_csv("dash.csv")
#(1)
tr = TCRrep(cell_df = df, #(2)
organism = 'mouse',
chains = ['beta'],
db_file = 'alphabeta_gammadelta_db.tsv',
compute_distances = True,
store_all_cdr = False)
S = compute_pw_sparse_out_of_memory(tr, matrix_name = "rw_beta", max_distance = 1000)
# S is a <1920x1920 sparse matrix of type '<class 'numpy.int16'>'
M = S.todense()
M[M==1] = 0
np.all(M == tr.pw_beta)
S, chunks = compute_pw_sparse_out_of_memory(tr, matrix_name = "rw_beta", max_distance = 50)
print(S)
# S is a <1920x1920 sparse matrix of type '<class 'numpy.int16'>'
"""
dest = secrets.token_hex(6)
os.mkdir(dest)
print(f"CREATED /{dest}/ FOR HOLDING DISTANCE OUT OF MEMORY")
row_chunks = memory._partition(range(tr.clone_df.shape[0]), row_size)
smatrix_chunks = [(tr, ind, f"{dest}/{i}.{matrix_name}.npz") for i,ind in enumerate(row_chunks)]
csrfragments = parmap.starmap(memory.gen_sparse_rw_on_fragment,
smatrix_chunks,
matrix_name = matrix_name,
max_distance=max_distance,
pm_pbar=pm_pbar,
pm_processes = pm_processes)
if reassemble:
csr_full = memory.collapse_csrs([x[2] for x in smatrix_chunks])
print(f"RETURNING scipy.sparse csr_matrix w/dims {csr_full.shape}")
else:
csr_full = None
if cleanup:
assert os.path.isdir(dest)
print(f"CLEANING UP {dest}")
shutil.rmtree(dest)
return csr_full, smatrix_chunks
def compute_pw_sparse_out_of_memory2(tr,
row_size = 500,
pm_processes = 2,
pm_pbar = True,
max_distance = 50,
reassemble = True,
cleanup = True,
assign = True):
"""
Instead of calling TCRrep.compute_distances(), this
function permits a parallelizable approach that does
not require holding a large matrix in memory.
Default behavior is to reassemble a scipy
sparse matrix from a set of sub matrices written to disk fragment.
With <reassemble = True> function returns a scipy sparse matrix.
Space savings are achieved because any value above <max_distance> is set to zero.
True zero distances are set to -1.
Can be used to form a network of TCRs with tcrdistances < max_distance,
Parameters
----------
tr : TCRrep
TCRrep instance with clone_df
row_size : int
How many rows to process in memory at once
pm_processes : int
Numbe of concurrent parallel processes to run at once
pm_bar : bool
If True, show progress bar.
max_distance : int
Max distance
matrix_name : str
Name of matrix to return (i.e, 'rw_beta' or 'rw_alpha')
reassemble: True
If true, makes one matrix from all the sparse sub matrices.
cleanup: bool,
if True, deletes temporary files.
assign : bool
if True, assigns pw sparse matrices to TCRrep object.
That is TCRrep.pw_beta, TCRrep.pw_alpha will be assigned
the reassembled spare matrces.
Returns
-------
csr_full : sparse scipy matrix
dest : str
name of the folder that holds fragments
Examples
--------
import numpy as np
import pandas as pd
from tcrdist.repertoire import TCRrep
from tcrdist.rep_funcs import compute_pw_sparse_out_of_memory
df = pd.read_csv("dash.csv")
#(1)
tr = TCRrep(cell_df = df, #(2)
organism = 'mouse',
chains = ['beta'],
db_file = 'alphabeta_gammadelta_db.tsv',
compute_distances = True,
store_all_cdr = False)
S = compute_pw_sparse_out_of_memory(tr, matrix_name = "rw_beta", max_distance = 1000)
# S is a <1920x1920 sparse matrix of type '<class 'numpy.int16'>'
M = S.todense()
M[M==1] = 0
np.all(M == tr.pw_beta)
S, chunks = compute_pw_sparse_out_of_memory(tr, matrix_name = "rw_beta", max_distance = 50)
print(S)
# S is a <1920x1920 sparse matrix of type '<class 'numpy.int16'>'
"""
# Early warning to save heartache
if assign is True and reassemble is False:
raise ValueError("If you want to assign results to a TCRrep instance, you must set reassemble to True")
dest = secrets.token_hex(6)
os.mkdir(dest)
print(f"CREATED /{dest}/ FOR HOLDING DISTANCE OUT OF MEMORY")
row_chunks = memory._partition(range(tr.clone_df.shape[0]), row_size)
smatrix_chunks = [(tr, ind, f"{dest}/{i}") for i,ind in enumerate(row_chunks)]
csrfragments = parmap.starmap(memory.gen_sparse_rw_on_fragment2,
smatrix_chunks,
max_distance=max_distance,
pm_pbar=pm_pbar,
pm_processes = pm_processes)
if reassemble:
csr_full_dict = dict()
for chain in tr.chains:
chain_str = f"rw_{chain}"
csr_full = memory.collapse_csrs([f"{x[2]}.{chain_str}.npz" for x in smatrix_chunks])
print(f"RETURNING scipy.sparse csr_matrix w/dims {csr_full.shape}")
csr_full_dict[chain] = csr_full
else:
csr_full_dict= None
if assign:
for chain in tr.chains:
setattr(tr, f"pw_{chain}", csr_full_dict[chain])
if cleanup:
assert os.path.isdir(dest)
print(f"CLEANING UP {dest}")
shutil.rmtree(dest)
return csr_full_dict, smatrix_chunks
def compute_n_tally_out_of_memory2(fragments,
to_file = False,
to_memory = True,
pm_processes = 2,
**kwargs):
"""
Parameters
---------
fragments : tuple
3-part tuple
0 : TCRrep instance
1 : list of rows in each fragment
2 : filename holding the distances as a .npz
matrix_name : str
For 'beta' chain dists use 'rw_beta'
to_file : bool
If True, than a file is written to disk containing all the n_tally
to_memory : bool
If True, the n_tally is loaded directly to memory
**kwargs
Keyword arguments are passed directly to tcridist.memory.gen_n_tally_on_fragment,
including:
x_cols : list
categorical variable 'epitope']
count_col : str
column for counts
knn_neighbors : bool
option to choose a fixed number of neighbors (NOT RECOMMENDED)
knn_radius : int
maximum radius for finding neighbors
Notes
-----
We envision that user may want to run nndif
multiple times with different categorical variables
and may not want to go through the computational
intensive steps of computing TCRdistance each time.
This can be accomodated via setting cleanup to False:
compute_pw_sparse_out_of_memory(cleanup=False)
Example
-------
from scipy import sparse
from tcrdist.repertoire import TCRrep
from tcrdist.rep_funcs import compute_pw_sparse_out_of_memory
df = pd.read_csv("dash.csv")
tr = TCRrep(cell_df = df,
organism = 'mouse',
chains = ['beta'],
db_file = 'alphabeta_gammadelta_db.tsv',
compute_distances = True,
store_all_cdr = False)
S, chunks = compute_pw_sparse_out_of_memory(tr, matrix_name = "rw_beta", max_distance = 1000, cleanup = False)
# dest contains all the shards
"""
# [(<tcrdist.repertoire.TCRrep at 0x14035b6d0>,
# range(0, 500),
# 'd3be945e8956/0.rw_beta.npz'),
# rearrange fragments in order (tr, ind, .npz, .csv)
fragments = [(x[0], x[1], x[2], f"{x[2]}.nndif.csv") for x in fragments ]
#fragments = [(tr, f"{dest}/{i}.{matrix_name}.npz", ind, f"{dest}/{i}.nndif.cvs") for i,ind in enumerate(row_chunks)]
csvfragments = parmap.starmap(memory.gen_n_tally_on_fragment2, fragments, **kwargs, pm_pbar=True, pm_processes = pm_processes)
if to_file:
dest =os.path.dirname(csvfragments[0])
nndiff_file = memory._concat_to_file(dest =dest, fragments =csvfragments)
return nndiff_file
if to_memory:
nndiff = memory._concat_to_memory(fragments = csvfragments)
return nndiff
| 39.908284
| 184
| 0.583957
| 3,403
| 26,978
| 4.432853
| 0.130473
| 0.032483
| 0.012396
| 0.013789
| 0.804906
| 0.782168
| 0.770567
| 0.76122
| 0.7589
| 0.756778
| 0
| 0.019366
| 0.324338
| 26,978
| 675
| 185
| 39.967407
| 0.808207
| 0.570873
| 0
| 0.487179
| 0
| 0
| 0.076064
| 0.008617
| 0
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| 0
| 0.001481
| 0.030769
| 1
| 0.041026
| false
| 0
| 0.051282
| 0
| 0.14359
| 0.030769
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| 0
|
0
| 6
|
17aa5b165412fedb74e31472c5da01d5b63dcbbd
| 114
|
py
|
Python
|
main/migration_types.py
|
sotheara-leang/xFlask
|
b6899d4b6d1bdc4acfd812bfa8807e2cba7e8df0
|
[
"MIT"
] | 2
|
2020-02-11T08:29:49.000Z
|
2020-02-17T10:24:36.000Z
|
main/migration_types.py
|
sotheara-leang/xFlask
|
b6899d4b6d1bdc4acfd812bfa8807e2cba7e8df0
|
[
"MIT"
] | null | null | null |
main/migration_types.py
|
sotheara-leang/xFlask
|
b6899d4b6d1bdc4acfd812bfa8807e2cba7e8df0
|
[
"MIT"
] | null | null | null |
from xflask.sqlalchemy import StringEnum, IntegerEnum
from xflask.type import *
from main.type.edu_level import *
| 28.5
| 53
| 0.824561
| 16
| 114
| 5.8125
| 0.625
| 0.215054
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| 0
| 0.114035
| 114
| 3
| 54
| 38
| 0.920792
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| true
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| 1
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| 1
| 0
|
0
| 6
|
17b82f811308e8bc2294e9088b437ea3e3db1414
| 43
|
py
|
Python
|
test/fixture/python_scanner/from_import_simple_package_modules_no_space.py
|
Valkatraz/scons
|
5e70c65f633dcecc035751c9f0c6f894088df8a0
|
[
"MIT"
] | 1,403
|
2017-11-23T14:24:01.000Z
|
2022-03-30T20:59:39.000Z
|
test/fixture/python_scanner/from_import_simple_package_modules_no_space.py
|
Valkatraz/scons
|
5e70c65f633dcecc035751c9f0c6f894088df8a0
|
[
"MIT"
] | 3,708
|
2017-11-27T13:47:12.000Z
|
2022-03-29T17:21:17.000Z
|
test/fixture/python_scanner/from_import_simple_package_modules_no_space.py
|
Valkatraz/scons
|
5e70c65f633dcecc035751c9f0c6f894088df8a0
|
[
"MIT"
] | 281
|
2017-12-01T23:48:38.000Z
|
2022-03-31T15:25:44.000Z
|
from simple_package import module1,module2
| 21.5
| 42
| 0.883721
| 6
| 43
| 6.166667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.051282
| 0.093023
| 43
| 1
| 43
| 43
| 0.897436
| 0
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| 1
| 0
| true
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| 1
| 1
| 0
| null | 0
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| 0
| 0
| 0
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| 0
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| 1
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| null | 0
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| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
17eab0c2a4209e9e7a5979f04e487f2fe5a2456b
| 57
|
py
|
Python
|
models/__init__.py
|
heathher/neural_sequence_labeling
|
81c83443982f5b1723fde3d446eb94e8cb7a4c44
|
[
"MIT"
] | 240
|
2018-03-02T02:52:24.000Z
|
2022-02-15T02:51:58.000Z
|
models/__init__.py
|
heathher/neural_sequence_labeling
|
81c83443982f5b1723fde3d446eb94e8cb7a4c44
|
[
"MIT"
] | 15
|
2018-03-02T02:54:55.000Z
|
2022-01-10T08:09:03.000Z
|
models/__init__.py
|
heathher/neural_sequence_labeling
|
81c83443982f5b1723fde3d446eb94e8cb7a4c44
|
[
"MIT"
] | 53
|
2018-03-14T10:19:58.000Z
|
2021-11-09T16:43:13.000Z
|
from models.base_model import *
from models.nns import *
| 19
| 31
| 0.789474
| 9
| 57
| 4.888889
| 0.666667
| 0.454545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.140351
| 57
| 2
| 32
| 28.5
| 0.897959
| 0
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| 0
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| 0
| 0
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| 0
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| 0
| true
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| 0
| null | 1
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| 0
| 1
| 0
|
0
| 6
|
aa1fef3f046c36a22e39c297d8a977417eeb7261
| 85
|
py
|
Python
|
BatterySafe/__init__.py
|
skhillon/Battery-Safe
|
9eb3852e07bf9a0c7883a30dd4edf799c0af908d
|
[
"MIT"
] | 22
|
2020-07-27T18:19:54.000Z
|
2021-09-12T21:53:26.000Z
|
BatterySafe/__init__.py
|
skhillon/Battery-Safe
|
9eb3852e07bf9a0c7883a30dd4edf799c0af908d
|
[
"MIT"
] | null | null | null |
BatterySafe/__init__.py
|
skhillon/Battery-Safe
|
9eb3852e07bf9a0c7883a30dd4edf799c0af908d
|
[
"MIT"
] | 1
|
2020-07-28T04:19:52.000Z
|
2020-07-28T04:19:52.000Z
|
import BatterySafe.BatteryManager as BatteryManager
BatteryManager.BatteryManager()
| 21.25
| 51
| 0.882353
| 7
| 85
| 10.714286
| 0.571429
| 0.746667
| 0
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| 85
| 3
| 52
| 28.333333
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| 0
|
0
| 6
|
a4b847bbaa00007c316dfa2b9e114a49d490c30e
| 4,120
|
py
|
Python
|
Component/tests/test_component_list.py
|
mst-solar-car/kicad-bom-generator
|
2aae905056d06f3d25343a8d784049c141d05640
|
[
"MIT"
] | 3
|
2018-02-26T12:31:41.000Z
|
2020-10-10T14:14:11.000Z
|
Component/tests/test_component_list.py
|
mst-solar-car/kicad-bom-generator
|
2aae905056d06f3d25343a8d784049c141d05640
|
[
"MIT"
] | null | null | null |
Component/tests/test_component_list.py
|
mst-solar-car/kicad-bom-generator
|
2aae905056d06f3d25343a8d784049c141d05640
|
[
"MIT"
] | null | null | null |
from __future__ import absolute_import
from Component import *
def test_adding_single_component():
""" Tests adding a single component to a list """
# Arrange
component_list = KiCadComponentList()
component = KiCadComponent({
"name": "TestComponent"
})
# Act
component_list.Add(component)
# Assert
assert len(component_list) == 1
assert component_list[0] == component
def test_add_order():
""" Tests maintaining the order of adding components """
# Arrange
component1 = KiCadComponent({
"name": "TestComponent1"
})
component2 = KiCadComponent({
"name": "TestComponent2"
})
expected = [component1, component2]
# Act
actual = KiCadComponentList()
actual.Add(component1)
actual.Add(component2)
# Assert
assert len(actual) == len(expected)
for i in range(0, len(actual)):
assert actual[i] == expected[i]
def test_delete():
""" Tests deleting an item """
# Arrange
component1 = KiCadComponent({
"name": "TestComponent1"
})
component2 = KiCadComponent({
"name": "TestComponent2"
})
component3 = KiCadComponent({
"name": "TestComponent3"
})
expected = [component1, component3]
# Act
actual = KiCadComponentList()
actual.Add(component1)
actual.Add(component2)
actual.Add(component3)
del actual[1]
# Assert
assert len(actual) == len(expected)
for i in range(0, len(actual)):
assert actual[i] == expected[i]
def test_remove_with_component():
""" Tests removing an item """
# Arrange
component1 = KiCadComponent({
"name": "TestComponent1"
})
component2 = KiCadComponent({
"name": "TestComponent2"
})
component3 = KiCadComponent({
"name": "TestComponent3"
})
expected = [component1, component3]
# Act
actual = KiCadComponentList()
actual.Add(component1)
actual.Add(component2)
actual.Add(component3)
actual.Remove(component2)
# Assert
assert len(actual) == len(expected)
for i in range(0, len(actual)):
assert actual[i] == expected[i]
def test_remove_with_hash():
""" Tests removing an item with a hash """
# Arrange
component1 = KiCadComponent({
"name": "TestComponent1"
})
component2 = KiCadComponent({
"name": "TestComponent2"
})
component3 = KiCadComponent({
"name": "TestComponent3"
})
expected = [component1, component3]
# Act
actual = KiCadComponentList()
actual.Add(component1)
actual.Add(component2)
actual.Add(component3)
actual.Remove(component2.Hash())
# Assert
assert len(actual) == len(expected)
for i in range(0, len(actual)):
assert actual[i] == expected[i]
def test_remove_with_index():
""" Tests removing an item using index """
# Arrange
component1 = KiCadComponent({
"name": "TestComponent1"
})
component2 = KiCadComponent({
"name": "TestComponent2"
})
component3 = KiCadComponent({
"name": "TestComponent3"
})
expected = [component1, component3]
# Act
actual = KiCadComponentList()
actual.Add(component1)
actual.Add(component2)
actual.Add(component3)
actual.Remove(1)
# Assert
assert len(actual) == len(expected)
for i in range(0, len(actual)):
assert actual[i] == expected[i]
def test_iterator():
""" Tests iterating over the list """
# Arrange
component1 = KiCadComponent({
"name": "TestComponent1"
})
component2 = KiCadComponent({
"name": "TestComponent2"
})
component3 = KiCadComponent({
"name": "TestComponent3"
})
# Act
actual = KiCadComponentList()
actual.Add(component1)
actual.Add(component2)
actual.Add(component3)
# Assert
for c in actual:
assert type(c) is KiCadComponent
def test_constructor():
""" Test passing a list to the kicad component list """
# Arrange
expected = [
KiCadComponent({
"name": "TestComponent1"
}),
KiCadComponent({
"name": "TestComponent2"
}),
KiCadComponent({
"name": "TestComponent3"
})
]
# Act
actual = KiCadComponentList(expected)
# Assert
assert len(actual) == len(expected)
for i in range(0, len(actual)):
assert actual[i] == expected[i]
| 19.252336
| 58
| 0.661408
| 419
| 4,120
| 6.441527
| 0.145585
| 0.140052
| 0.038903
| 0.077807
| 0.739904
| 0.739904
| 0.718044
| 0.718044
| 0.718044
| 0.66395
| 0
| 0.023277
| 0.207524
| 4,120
| 213
| 59
| 19.342723
| 0.803369
| 0.10801
| 0
| 0.80303
| 0
| 0
| 0.104664
| 0
| 0
| 0
| 0
| 0
| 0.113636
| 1
| 0.060606
| false
| 0
| 0.015152
| 0
| 0.075758
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
a4c780facf1af27d179b1cb6f6307f6dc59e74d1
| 2,306
|
py
|
Python
|
epytope/Data/pssms/smm/mat/A_03_01_9.py
|
christopher-mohr/epytope
|
8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd
|
[
"BSD-3-Clause"
] | 7
|
2021-02-01T18:11:28.000Z
|
2022-01-31T19:14:07.000Z
|
epytope/Data/pssms/smm/mat/A_03_01_9.py
|
christopher-mohr/epytope
|
8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd
|
[
"BSD-3-Clause"
] | 22
|
2021-01-02T15:25:23.000Z
|
2022-03-14T11:32:53.000Z
|
epytope/Data/pssms/smm/mat/A_03_01_9.py
|
christopher-mohr/epytope
|
8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd
|
[
"BSD-3-Clause"
] | 4
|
2021-05-28T08:50:38.000Z
|
2022-03-14T11:45:32.000Z
|
A_03_01_9 = {0: {'A': -0.177, 'C': -0.209, 'E': 0.594, 'D': 0.762, 'G': -0.018, 'F': 0.085, 'I': -0.225, 'H': -0.259, 'K': -0.537, 'M': -0.46, 'L': -0.062, 'N': 0.396, 'Q': 0.067, 'P': 0.538, 'S': -0.075, 'R': -0.532, 'T': -0.127, 'W': 0.282, 'V': -0.162, 'Y': 0.118}, 1: {'A': -0.121, 'C': 0.398, 'E': 0.15, 'D': 0.443, 'G': 0.199, 'F': 0.12, 'I': -0.719, 'H': 0.456, 'K': 1.07, 'M': -1.044, 'L': -0.985, 'N': 0.287, 'Q': -0.177, 'P': 0.203, 'S': -0.419, 'R': 0.868, 'T': -0.569, 'W': 0.342, 'V': -0.695, 'Y': 0.193}, 2: {'A': -0.217, 'C': 0.085, 'E': 0.493, 'D': 0.354, 'G': 0.199, 'F': -0.56, 'I': 0.108, 'H': -0.058, 'K': 0.16, 'M': -0.322, 'L': -0.115, 'N': -0.191, 'Q': 0.268, 'P': 0.418, 'S': -0.078, 'R': -0.063, 'T': 0.205, 'W': -0.124, 'V': 0.256, 'Y': -0.817}, 3: {'A': -0.15, 'C': 0.053, 'E': 0.121, 'D': 0.127, 'G': -0.026, 'F': -0.132, 'I': 0.119, 'H': -0.081, 'K': -0.029, 'M': 0.041, 'L': 0.077, 'N': -0.038, 'Q': 0.087, 'P': -0.024, 'S': -0.059, 'R': -0.052, 'T': -0.045, 'W': -0.062, 'V': 0.072, 'Y': 0.002}, 4: {'A': 0.072, 'C': -0.086, 'E': 0.316, 'D': 0.247, 'G': 0.039, 'F': -0.092, 'I': -0.007, 'H': -0.195, 'K': 0.002, 'M': -0.01, 'L': 0.039, 'N': 0.106, 'Q': 0.035, 'P': -0.094, 'S': -0.121, 'R': -0.158, 'T': 0.079, 'W': -0.082, 'V': -0.063, 'Y': -0.028}, 5: {'A': -0.039, 'C': 0.039, 'E': 0.202, 'D': 0.433, 'G': 0.015, 'F': -0.156, 'I': -0.087, 'H': 0.011, 'K': 0.044, 'M': -0.118, 'L': -0.03, 'N': 0.114, 'Q': -0.055, 'P': -0.074, 'S': -0.076, 'R': 0.004, 'T': -0.111, 'W': -0.052, 'V': -0.072, 'Y': 0.008}, 6: {'A': -0.048, 'C': 0.1, 'E': 0.404, 'D': 0.473, 'G': -0.04, 'F': -0.187, 'I': -0.226, 'H': -0.006, 'K': 0.277, 'M': -0.473, 'L': -0.34, 'N': 0.165, 'Q': 0.113, 'P': -0.023, 'S': -0.24, 'R': 0.082, 'T': -0.127, 'W': 0.067, 'V': -0.018, 'Y': 0.046}, 7: {'A': -0.02, 'C': 0.127, 'E': 0.25, 'D': 0.318, 'G': 0.026, 'F': -0.307, 'I': 0.142, 'H': 0.071, 'K': 0.003, 'M': -0.013, 'L': -0.24, 'N': -0.056, 'Q': -0.024, 'P': 0.05, 'S': -0.019, 'R': -0.047, 'T': 0.098, 'W': -0.042, 'V': -0.021, 'Y': -0.297}, 8: {'A': 0.199, 'C': 0.228, 'E': 0.541, 'D': 0.294, 'G': 0.456, 'F': 0.04, 'I': 0.23, 'H': -0.738, 'K': -1.94, 'M': 0.221, 'L': 0.101, 'N': 0.644, 'Q': 0.652, 'P': 0.01, 'S': 0.484, 'R': -0.958, 'T': 0.437, 'W': -0.024, 'V': 0.148, 'Y': -1.025}, -1: {'con': 5.2158}}
| 2,306
| 2,306
| 0.392454
| 557
| 2,306
| 1.61939
| 0.319569
| 0.019956
| 0.011086
| 0.013304
| 0.062084
| 0
| 0
| 0
| 0
| 0
| 0
| 0.371443
| 0.161752
| 2,306
| 1
| 2,306
| 2,306
| 0.095189
| 0
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| 0
| 0
| 0
| 0.079324
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
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| 1
| null | 0
| 0
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| 0
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| 0
| 0
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| 0
| 1
| 0
| 0
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| 1
| 1
| 1
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
a4f142ea29b27c26e279fe1b55c065dba1d68205
| 251
|
py
|
Python
|
nmigen/vendor/lattice_ice40.py
|
psumesh/nmigen
|
7d611b8fc1d9e58853ff268ec38ff8f4131a9774
|
[
"BSD-2-Clause"
] | 528
|
2020-01-28T18:21:00.000Z
|
2021-12-09T06:27:51.000Z
|
nmigen/vendor/lattice_ice40.py
|
DX-MON/nmigen
|
a6a13dd612ee1c9215719c70a5aa410a8775ffdb
|
[
"BSD-2-Clause"
] | 360
|
2020-01-28T18:34:30.000Z
|
2021-12-10T08:03:32.000Z
|
nmigen/vendor/lattice_ice40.py
|
DX-MON/nmigen
|
a6a13dd612ee1c9215719c70a5aa410a8775ffdb
|
[
"BSD-2-Clause"
] | 100
|
2020-02-06T21:55:46.000Z
|
2021-11-25T19:20:44.000Z
|
from amaranth.vendor.lattice_ice40 import *
from amaranth.vendor.lattice_ice40 import __all__
import warnings
warnings.warn("instead of nmigen.vendor.lattice_ice40, use amaranth.vendor.lattice_ice40",
DeprecationWarning, stacklevel=2)
| 31.375
| 90
| 0.796813
| 31
| 251
| 6.193548
| 0.516129
| 0.270833
| 0.375
| 0.40625
| 0.375
| 0.375
| 0
| 0
| 0
| 0
| 0
| 0.041284
| 0.131474
| 251
| 7
| 91
| 35.857143
| 0.83945
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| 0
| 0.290837
| 0.227092
| 0
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| 0
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| 1
| 0
| true
| 0
| 0.6
| 0
| 0.6
| 0
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| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
102a7b10f42fa15fd1031dabb6c3eefb5d0c52c2
| 151
|
py
|
Python
|
src/DateTime/convertStringDateToTimestamp.py
|
mikeludemann/helperFunctions_Python
|
62b1e8279eee216f3603f55cf2d010d611e3be0e
|
[
"MIT"
] | null | null | null |
src/DateTime/convertStringDateToTimestamp.py
|
mikeludemann/helperFunctions_Python
|
62b1e8279eee216f3603f55cf2d010d611e3be0e
|
[
"MIT"
] | null | null | null |
src/DateTime/convertStringDateToTimestamp.py
|
mikeludemann/helperFunctions_Python
|
62b1e8279eee216f3603f55cf2d010d611e3be0e
|
[
"MIT"
] | null | null | null |
import time
import datetime
def convertStringDateToTimestamp(date):
return time.mktime(datetime.datetime.strptime(date, "%d/%m/%Y").timetuple())
| 21.571429
| 80
| 0.761589
| 18
| 151
| 6.388889
| 0.722222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.099338
| 151
| 6
| 81
| 25.166667
| 0.845588
| 0
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| 0
| 0
| 0.05298
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.5
| 0.25
| 1
| 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
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
52e7dd385cff2f1fe40b5105cd7d29d2f5293070
| 29
|
py
|
Python
|
ocean_model/__init__.py
|
Jaouadeddadsi/Paython-package-to-model-tidal-stream
|
e5c358459313f3c2d3b99acc4499711eeabc8b12
|
[
"MIT"
] | null | null | null |
ocean_model/__init__.py
|
Jaouadeddadsi/Paython-package-to-model-tidal-stream
|
e5c358459313f3c2d3b99acc4499711eeabc8b12
|
[
"MIT"
] | null | null | null |
ocean_model/__init__.py
|
Jaouadeddadsi/Paython-package-to-model-tidal-stream
|
e5c358459313f3c2d3b99acc4499711eeabc8b12
|
[
"MIT"
] | null | null | null |
from .Model_1DV import Model
| 14.5
| 28
| 0.827586
| 5
| 29
| 4.6
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04
| 0.137931
| 29
| 1
| 29
| 29
| 0.88
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| 1
| 1
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| null | 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
5e08579d02cdb274ce201a50149ddd272195fcb6
| 35
|
py
|
Python
|
engine/__init__.py
|
donnyyou/centerX
|
6e381cb669a6014d02e31a43915271237690531c
|
[
"Apache-2.0"
] | 350
|
2020-12-01T09:55:16.000Z
|
2020-12-23T13:47:43.000Z
|
engine/__init__.py
|
powerlic/centerX
|
1073753533f26483c3ab053a7d8753708fcacde7
|
[
"Apache-2.0"
] | 39
|
2020-12-24T13:42:29.000Z
|
2022-02-10T01:09:56.000Z
|
engine/__init__.py
|
powerlic/centerX
|
1073753533f26483c3ab053a7d8753708fcacde7
|
[
"Apache-2.0"
] | 49
|
2020-12-01T11:39:14.000Z
|
2020-12-21T01:45:39.000Z
|
from .defaults import CenterTrainer
| 35
| 35
| 0.885714
| 4
| 35
| 7.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085714
| 35
| 1
| 35
| 35
| 0.96875
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| 1
| 0
| true
| 0
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| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
eab25f6010ba93babf5464b5f1d6fbb4195f4031
| 10,842
|
py
|
Python
|
build/lib/ObjectAsString/ObjectAsString.py
|
DigitalCreativeApkDev/ObjectAsString
|
8a4d3f247fe7ce066af826fa072a168aeb69a91c
|
[
"MIT"
] | null | null | null |
build/lib/ObjectAsString/ObjectAsString.py
|
DigitalCreativeApkDev/ObjectAsString
|
8a4d3f247fe7ce066af826fa072a168aeb69a91c
|
[
"MIT"
] | null | null | null |
build/lib/ObjectAsString/ObjectAsString.py
|
DigitalCreativeApkDev/ObjectAsString
|
8a4d3f247fe7ce066af826fa072a168aeb69a91c
|
[
"MIT"
] | null | null | null |
"""
This file contains code for the library "ObjectAsString".
Author: DigitalCreativeApkDev
"""
# Importing necessary libraries
import copy
from mpmath import mp, mpf
mp.pretty = True
# Creating method to check whether an object is a number or not
def is_number(obj: object) -> bool:
try:
mpf(obj)
return True
except Exception:
return False
class ObjectAsString:
"""
This class contains attributes of string representation of an object.
"""
def __init__(self, obj):
# type: (object) -> None
self.obj: object = obj
def __len__(self):
# type: () -> int
if isinstance(self.obj, str) or isinstance(self.obj, list):
return len(self.obj)
raise Exception("Unsupported operation '__len__' for type '" + str(type(self.obj)) + "'!")
def __add__(self, other):
# type: (object) -> ObjectAsString
if isinstance(other, ObjectAsString):
try:
if is_number(self.obj) and is_number(other.obj):
return ObjectAsString(mpf(self.obj + other.obj))
elif isinstance(self.obj, list) and isinstance(other.obj, list):
return ObjectAsString(self.obj + other.obj)
else:
return ObjectAsString(str(self.obj + other.obj))
except TypeError:
return ObjectAsString(str(self.obj) + str(other.obj))
else:
try:
if is_number(self.obj) and is_number(other):
return ObjectAsString(mpf(self.obj + other))
elif isinstance(self.obj, list) and isinstance(other, list):
return ObjectAsString(self.obj + other)
else:
return ObjectAsString(str(self.obj + other))
except TypeError:
return ObjectAsString(str(self.obj) + str(other))
def __sub__(self, other):
# type: (object) -> ObjectAsString
if isinstance(other, ObjectAsString):
if dir(type(self.obj)).__contains__('__sub__') and \
dir(type(other.obj)).__contains__('__sub__'):
if is_number(self.obj) and is_number(other.obj):
return ObjectAsString(mpf(self.obj - other.obj))
return ObjectAsString(str(self.obj - other.obj))
else:
raise Exception("Unsupported operand type '-' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other.obj)) + "'!")
else:
if dir(type(self.obj)).__contains__('__sub__') and \
dir(type(other)).__contains__('__sub__'):
if is_number(self.obj) and is_number(other):
return ObjectAsString(mpf(self.obj - other))
return ObjectAsString(str(self.obj - other))
else:
raise Exception("Unsupported operand type '-' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other)) + "'!")
def __mul__(self, other):
# type: (object) -> ObjectAsString
if isinstance(other, ObjectAsString):
if dir(type(self.obj)).__contains__('__mul__') and \
dir(type(other.obj)).__contains__('__mul__'):
if is_number(self.obj) and is_number(other.obj):
return ObjectAsString(mpf(self.obj * other.obj))
elif isinstance(self.obj, list) and isinstance(other.obj, int):
return ObjectAsString(self.obj * other.obj)
elif isinstance(other.obj, list) and isinstance(self.obj, int):
return ObjectAsString(other.obj * self.obj)
else:
return ObjectAsString(str(self.obj * other.obj))
else:
raise Exception("Unsupported operand type '*' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other.obj)) + "'!")
else:
if dir(type(self.obj)).__contains__('__mul__') and \
dir(type(other)).__contains__('__mul__'):
if is_number(self.obj) and is_number(other):
return ObjectAsString(mpf(self.obj * other))
elif isinstance(self.obj, list) and isinstance(other, int):
return ObjectAsString(self.obj * other)
elif isinstance(other, list) and isinstance(self.obj, int):
return ObjectAsString(other * self.obj)
else:
return ObjectAsString(str(self.obj * other))
else:
raise Exception("Unsupported operand type '*' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other)) + "'!")
def __truediv__(self, other):
# type: (object) -> ObjectAsString
if isinstance(other, ObjectAsString):
if dir(type(self.obj)).__contains__('__truediv__') and \
dir(type(other.obj)).__contains__('__truediv__'):
if is_number(self.obj) and is_number(other.obj):
return ObjectAsString(mpf(self.obj / other.obj))
return ObjectAsString(str(self.obj / other.obj))
else:
raise Exception("Unsupported operand type '/' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other.obj)) + "'!")
else:
if dir(type(self.obj)).__contains__('__truediv__') and \
dir(type(other)).__contains__('__truediv__'):
if is_number(self.obj) and is_number(other):
return ObjectAsString(mpf(self.obj / other))
return ObjectAsString(str(self.obj / other))
else:
raise Exception("Unsupported operand type '/' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other)) + "'!")
def __floordiv__(self, other):
# type: (object) -> ObjectAsString
if isinstance(other, ObjectAsString):
if dir(type(self.obj)).__contains__('__floordiv__') and \
dir(type(other.obj)).__contains__('__floordiv__'):
if is_number(self.obj) and is_number(other.obj):
return ObjectAsString(mpf(self.obj // other.obj))
return ObjectAsString(str(self.obj // other.obj))
else:
raise Exception("Unsupported operand type '//' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other.obj)) + "'!")
else:
if dir(type(self.obj)).__contains__('__floordiv__') and \
dir(type(other)).__contains__('__floordiv__'):
if is_number(self.obj) and is_number(other):
return ObjectAsString(mpf(self.obj // other))
return ObjectAsString(str(self.obj // other))
else:
raise Exception("Unsupported operand type '//' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other)) + "'!")
def __mod__(self, other):
# type: (object) -> ObjectAsString
if isinstance(other, ObjectAsString):
if dir(type(self.obj)).__contains__('__mod__') and \
dir(type(other.obj)).__contains__('__mod__'):
if is_number(self.obj) and is_number(other.obj):
return ObjectAsString(mpf(self.obj % other.obj))
return ObjectAsString(str(self.obj % other.obj))
else:
raise Exception("Unsupported operand type '%' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other.obj)) + "'!")
else:
if dir(type(self.obj)).__contains__('__mod__') and \
dir(type(other)).__contains__('__mod__'):
if is_number(self.obj) and is_number(other):
return ObjectAsString(mpf(self.obj % other))
return ObjectAsString(str(self.obj % other))
else:
raise Exception("Unsupported operand type '%' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other)) + "'!")
def __pow__(self, other):
# type: (object) -> ObjectAsString
if isinstance(other, ObjectAsString):
if dir(type(self.obj)).__contains__('__pow__') and \
dir(type(other.obj)).__contains__('__pow__'):
if is_number(self.obj) and is_number(other.obj):
return ObjectAsString(mpf(self.obj ** other.obj))
return ObjectAsString(str(self.obj ** other.obj))
else:
raise Exception("Unsupported operand type '**' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other.obj)) + "'!")
else:
if dir(type(self.obj)).__contains__('__pow__') and \
dir(type(other)).__contains__('__pow__'):
if is_number(self.obj) and is_number(other):
return ObjectAsString(mpf(self.obj ** other))
return ObjectAsString(str(self.obj ** other))
else:
raise Exception("Unsupported operand type '**' for type '" + str(type(self.obj))
+ "' with type '" + str(type(other)) + "'!")
def __gt__(self, other):
# type: (object) -> bool
if isinstance(other, ObjectAsString):
return self.obj > other.obj
return self.obj > other
def __ge__(self, other):
# type: (object) -> bool
if isinstance(other, ObjectAsString):
return self.obj >= other.obj
return self.obj >= other
def __lt__(self, other):
# type: (object) -> bool
if isinstance(other, ObjectAsString):
return self.obj < other.obj
return self.obj < other
def __le__(self, other):
# type: (object) -> bool
if isinstance(other, ObjectAsString):
return self.obj <= other.obj
return self.obj <= other
def __eq__(self, other):
# type: (object) -> bool
if isinstance(other, ObjectAsString):
return self.obj == other.obj
return self.obj == other
def __ne__(self, other):
# type: (object) -> bool
if isinstance(other, ObjectAsString):
return self.obj != other.obj
return self.obj != other
def __str__(self):
# type: () -> str
return str(self.obj)
def clone(self):
# type: () -> ObjectAsString
return copy.deepcopy(self)
| 44.801653
| 98
| 0.536248
| 1,127
| 10,842
| 4.902396
| 0.07276
| 0.12543
| 0.095566
| 0.059729
| 0.88181
| 0.879276
| 0.843439
| 0.83638
| 0.83638
| 0.774661
| 0
| 0
| 0.339421
| 10,842
| 241
| 99
| 44.987552
| 0.771433
| 0.064656
| 0
| 0.481481
| 0
| 0
| 0.089109
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.095238
| false
| 0
| 0.010582
| 0.010582
| 0.391534
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
eac1712a4d9b18988eaded8b3799180c0e5d98ec
| 257,619
|
py
|
Python
|
instances/passenger_demand/pas-20210422-1717-int12e/75.py
|
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
|
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
|
[
"BSD-3-Clause"
] | null | null | null |
instances/passenger_demand/pas-20210422-1717-int12e/75.py
|
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
|
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
|
[
"BSD-3-Clause"
] | null | null | null |
instances/passenger_demand/pas-20210422-1717-int12e/75.py
|
LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure
|
bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11
|
[
"BSD-3-Clause"
] | null | null | null |
"""
PASSENGERS
"""
numPassengers = 22784
passenger_arriving = (
(7, 5, 3, 9, 2, 1, 2, 2, 4, 0, 1, 0, 0, 7, 6, 3, 5, 4, 1, 3, 2, 3, 2, 1, 0, 0), # 0
(6, 11, 5, 8, 5, 3, 0, 2, 0, 0, 2, 0, 0, 6, 9, 8, 4, 3, 4, 2, 0, 2, 3, 0, 3, 0), # 1
(4, 8, 4, 5, 8, 5, 4, 1, 2, 3, 1, 0, 0, 7, 10, 6, 2, 9, 4, 1, 0, 4, 3, 0, 1, 0), # 2
(7, 7, 2, 7, 5, 3, 1, 1, 2, 2, 2, 0, 0, 6, 3, 5, 2, 6, 4, 6, 1, 4, 3, 0, 0, 0), # 3
(6, 7, 8, 13, 8, 2, 5, 2, 5, 2, 0, 0, 0, 6, 9, 4, 7, 6, 3, 3, 2, 2, 4, 0, 3, 0), # 4
(5, 10, 8, 9, 4, 2, 0, 1, 2, 1, 1, 1, 0, 12, 7, 10, 9, 4, 4, 7, 3, 1, 1, 0, 1, 0), # 5
(9, 11, 8, 9, 8, 4, 3, 1, 6, 0, 2, 0, 0, 12, 5, 6, 7, 4, 3, 3, 2, 0, 4, 2, 1, 0), # 6
(7, 6, 11, 8, 8, 3, 3, 3, 2, 2, 5, 0, 0, 2, 9, 8, 2, 9, 3, 4, 3, 4, 1, 1, 2, 0), # 7
(9, 4, 8, 6, 4, 5, 3, 3, 3, 2, 2, 0, 0, 14, 6, 4, 9, 10, 7, 3, 2, 4, 2, 3, 3, 0), # 8
(16, 13, 7, 11, 9, 4, 1, 3, 4, 1, 0, 0, 0, 8, 8, 5, 1, 8, 6, 3, 3, 3, 5, 0, 0, 0), # 9
(8, 5, 8, 6, 7, 3, 5, 2, 2, 2, 0, 0, 0, 6, 9, 6, 4, 8, 4, 3, 4, 6, 2, 0, 2, 0), # 10
(8, 8, 8, 7, 6, 1, 4, 3, 2, 5, 1, 2, 0, 5, 7, 5, 3, 8, 3, 4, 4, 3, 8, 1, 1, 0), # 11
(13, 8, 6, 15, 5, 2, 4, 3, 4, 0, 3, 2, 0, 10, 9, 5, 8, 6, 6, 4, 1, 0, 2, 1, 0, 0), # 12
(10, 11, 10, 13, 3, 5, 4, 4, 4, 2, 1, 2, 0, 18, 11, 10, 7, 9, 6, 6, 1, 2, 6, 4, 1, 0), # 13
(8, 8, 7, 13, 7, 4, 5, 4, 3, 1, 0, 2, 0, 12, 13, 14, 9, 2, 5, 5, 0, 9, 6, 0, 0, 0), # 14
(9, 12, 8, 11, 8, 5, 4, 3, 8, 0, 1, 0, 0, 10, 12, 3, 6, 11, 8, 5, 0, 3, 5, 0, 2, 0), # 15
(13, 12, 6, 13, 9, 3, 6, 8, 3, 2, 4, 1, 0, 8, 12, 6, 3, 9, 6, 5, 5, 6, 6, 3, 0, 0), # 16
(13, 12, 15, 8, 6, 4, 6, 6, 7, 2, 4, 1, 0, 7, 10, 6, 7, 6, 5, 8, 5, 3, 4, 2, 0, 0), # 17
(13, 10, 9, 15, 12, 4, 3, 2, 5, 1, 0, 1, 0, 5, 10, 8, 3, 12, 0, 2, 3, 2, 2, 2, 3, 0), # 18
(12, 18, 6, 12, 4, 6, 5, 6, 4, 3, 0, 3, 0, 14, 13, 8, 12, 10, 2, 8, 2, 10, 3, 3, 0, 0), # 19
(8, 15, 12, 15, 6, 3, 7, 7, 2, 2, 4, 1, 0, 19, 12, 5, 4, 5, 9, 5, 2, 5, 4, 0, 1, 0), # 20
(11, 8, 9, 8, 10, 2, 3, 5, 5, 2, 0, 3, 0, 12, 12, 9, 6, 8, 3, 6, 1, 8, 5, 3, 0, 0), # 21
(15, 10, 15, 12, 9, 4, 6, 2, 8, 3, 2, 1, 0, 15, 8, 6, 3, 10, 9, 7, 5, 6, 2, 3, 1, 0), # 22
(8, 10, 11, 10, 14, 5, 2, 4, 4, 4, 0, 0, 0, 10, 5, 7, 7, 7, 7, 4, 3, 4, 4, 2, 1, 0), # 23
(10, 12, 11, 11, 4, 6, 4, 4, 3, 2, 2, 2, 0, 12, 9, 11, 5, 6, 6, 6, 3, 7, 2, 4, 1, 0), # 24
(12, 10, 5, 7, 14, 1, 9, 7, 5, 0, 1, 0, 0, 11, 11, 11, 9, 8, 4, 4, 5, 4, 1, 1, 0, 0), # 25
(11, 7, 8, 13, 10, 0, 2, 2, 4, 4, 2, 0, 0, 16, 10, 5, 8, 13, 4, 2, 2, 3, 7, 0, 0, 0), # 26
(17, 18, 12, 9, 16, 5, 5, 7, 4, 3, 0, 0, 0, 7, 14, 8, 10, 10, 2, 4, 7, 6, 4, 1, 1, 0), # 27
(7, 10, 12, 10, 12, 5, 4, 4, 5, 6, 2, 1, 0, 15, 12, 5, 7, 6, 3, 5, 6, 3, 3, 4, 2, 0), # 28
(8, 12, 12, 8, 10, 6, 4, 6, 5, 4, 0, 0, 0, 15, 19, 8, 7, 9, 8, 9, 5, 7, 1, 1, 2, 0), # 29
(10, 8, 12, 10, 8, 5, 4, 9, 3, 2, 2, 1, 0, 14, 14, 6, 5, 11, 4, 5, 3, 8, 4, 4, 0, 0), # 30
(15, 7, 5, 11, 8, 2, 7, 4, 8, 0, 1, 1, 0, 6, 10, 4, 10, 17, 6, 5, 3, 6, 3, 2, 0, 0), # 31
(10, 6, 10, 11, 5, 2, 5, 5, 4, 1, 2, 2, 0, 12, 5, 6, 8, 8, 9, 3, 5, 4, 3, 1, 2, 0), # 32
(10, 8, 10, 19, 7, 5, 4, 0, 5, 2, 2, 0, 0, 8, 11, 6, 4, 12, 7, 5, 4, 5, 3, 5, 0, 0), # 33
(8, 14, 10, 11, 6, 4, 2, 6, 6, 1, 0, 0, 0, 7, 13, 6, 9, 4, 4, 4, 2, 2, 7, 1, 0, 0), # 34
(17, 12, 14, 10, 10, 2, 6, 2, 6, 2, 2, 0, 0, 13, 8, 11, 6, 7, 4, 3, 5, 6, 2, 0, 1, 0), # 35
(12, 14, 14, 7, 10, 4, 8, 5, 6, 5, 2, 1, 0, 11, 5, 8, 6, 5, 9, 6, 4, 7, 4, 4, 1, 0), # 36
(14, 14, 13, 11, 13, 2, 6, 3, 0, 0, 1, 1, 0, 13, 12, 7, 6, 14, 5, 2, 6, 7, 1, 3, 0, 0), # 37
(15, 11, 13, 6, 9, 6, 1, 6, 6, 5, 1, 1, 0, 11, 6, 10, 5, 8, 7, 5, 5, 3, 2, 2, 1, 0), # 38
(9, 16, 5, 11, 5, 4, 4, 2, 2, 0, 3, 0, 0, 18, 17, 4, 6, 8, 9, 7, 2, 6, 6, 2, 2, 0), # 39
(18, 12, 7, 10, 8, 2, 4, 3, 3, 1, 0, 1, 0, 10, 9, 9, 5, 10, 3, 9, 3, 2, 3, 2, 2, 0), # 40
(11, 15, 10, 7, 13, 1, 6, 5, 2, 2, 4, 1, 0, 9, 17, 9, 6, 14, 7, 9, 8, 5, 3, 2, 2, 0), # 41
(12, 5, 13, 15, 11, 2, 3, 3, 5, 4, 2, 0, 0, 13, 19, 7, 8, 14, 4, 9, 3, 5, 3, 1, 3, 0), # 42
(15, 11, 12, 8, 6, 4, 2, 5, 5, 0, 3, 0, 0, 10, 13, 12, 11, 16, 2, 3, 0, 4, 2, 2, 1, 0), # 43
(19, 12, 9, 11, 13, 5, 8, 5, 1, 0, 1, 0, 0, 7, 9, 5, 8, 14, 4, 5, 4, 6, 2, 2, 0, 0), # 44
(12, 12, 13, 12, 13, 6, 5, 4, 6, 4, 0, 1, 0, 9, 10, 8, 5, 17, 7, 3, 3, 7, 6, 0, 1, 0), # 45
(9, 12, 6, 12, 9, 5, 2, 4, 6, 0, 4, 4, 0, 12, 11, 7, 6, 9, 10, 4, 3, 3, 3, 1, 1, 0), # 46
(12, 12, 9, 9, 13, 3, 4, 4, 3, 4, 0, 1, 0, 12, 10, 7, 5, 11, 2, 4, 1, 7, 3, 3, 1, 0), # 47
(15, 16, 8, 12, 9, 1, 5, 5, 8, 3, 2, 2, 0, 8, 11, 11, 8, 15, 5, 3, 2, 6, 2, 0, 1, 0), # 48
(18, 16, 4, 12, 13, 7, 2, 3, 8, 0, 1, 0, 0, 9, 9, 10, 5, 11, 4, 2, 4, 10, 5, 1, 1, 0), # 49
(7, 11, 12, 13, 6, 7, 5, 6, 3, 4, 1, 3, 0, 9, 9, 8, 10, 9, 6, 6, 5, 6, 2, 2, 1, 0), # 50
(15, 7, 8, 17, 8, 7, 3, 5, 6, 4, 2, 0, 0, 16, 7, 16, 11, 13, 5, 3, 3, 2, 7, 2, 0, 0), # 51
(12, 11, 12, 17, 13, 2, 3, 2, 4, 0, 2, 2, 0, 8, 7, 8, 8, 10, 6, 1, 3, 3, 3, 2, 1, 0), # 52
(19, 11, 10, 7, 6, 5, 8, 3, 6, 3, 4, 1, 0, 12, 7, 6, 6, 11, 6, 4, 4, 8, 3, 2, 1, 0), # 53
(14, 15, 10, 10, 9, 6, 7, 3, 3, 3, 0, 0, 0, 10, 2, 11, 3, 8, 7, 6, 1, 5, 4, 2, 1, 0), # 54
(7, 11, 11, 13, 6, 3, 6, 7, 3, 2, 1, 0, 0, 13, 11, 12, 7, 9, 7, 7, 5, 2, 3, 1, 1, 0), # 55
(12, 9, 14, 13, 4, 3, 3, 2, 4, 1, 1, 1, 0, 18, 16, 12, 6, 9, 10, 6, 4, 5, 4, 1, 0, 0), # 56
(12, 9, 9, 8, 7, 3, 9, 2, 3, 3, 2, 2, 0, 3, 16, 6, 9, 4, 13, 4, 1, 2, 2, 2, 1, 0), # 57
(12, 10, 12, 8, 5, 3, 3, 8, 5, 4, 0, 0, 0, 9, 16, 2, 5, 7, 8, 4, 2, 2, 4, 2, 1, 0), # 58
(11, 12, 11, 7, 6, 4, 8, 2, 3, 0, 0, 0, 0, 14, 11, 6, 6, 12, 3, 5, 4, 3, 6, 5, 2, 0), # 59
(13, 10, 6, 13, 8, 4, 3, 6, 5, 3, 1, 2, 0, 7, 12, 7, 9, 15, 3, 3, 0, 5, 4, 3, 1, 0), # 60
(17, 11, 12, 11, 9, 4, 3, 4, 4, 3, 5, 0, 0, 10, 8, 10, 7, 15, 8, 1, 4, 6, 3, 1, 0, 0), # 61
(12, 11, 8, 10, 6, 5, 3, 1, 9, 3, 1, 0, 0, 12, 14, 4, 6, 11, 7, 5, 3, 2, 3, 0, 0, 0), # 62
(13, 8, 7, 17, 12, 2, 3, 3, 4, 0, 0, 1, 0, 15, 15, 4, 8, 5, 5, 3, 3, 1, 2, 5, 1, 0), # 63
(13, 12, 8, 16, 7, 1, 5, 2, 2, 3, 2, 0, 0, 9, 12, 8, 8, 5, 6, 2, 4, 2, 1, 4, 1, 0), # 64
(9, 18, 12, 8, 4, 2, 3, 3, 1, 2, 2, 1, 0, 8, 9, 6, 11, 9, 4, 2, 3, 7, 2, 3, 1, 0), # 65
(17, 9, 6, 9, 16, 3, 2, 4, 6, 5, 1, 0, 0, 11, 10, 6, 6, 8, 5, 5, 2, 5, 3, 1, 0, 0), # 66
(13, 8, 11, 8, 7, 7, 5, 0, 4, 3, 1, 0, 0, 14, 18, 5, 5, 13, 4, 3, 3, 9, 5, 2, 0, 0), # 67
(14, 9, 11, 7, 5, 5, 3, 2, 4, 2, 2, 1, 0, 16, 9, 4, 6, 6, 4, 9, 2, 4, 2, 0, 0, 0), # 68
(11, 15, 10, 10, 5, 7, 2, 1, 3, 0, 2, 0, 0, 14, 14, 3, 6, 10, 10, 5, 3, 6, 3, 0, 1, 0), # 69
(12, 9, 10, 8, 11, 5, 4, 2, 5, 1, 2, 1, 0, 6, 5, 8, 7, 15, 9, 3, 2, 9, 12, 1, 0, 0), # 70
(18, 15, 15, 13, 9, 3, 5, 3, 5, 1, 1, 1, 0, 10, 8, 4, 11, 4, 4, 5, 3, 8, 4, 0, 1, 0), # 71
(15, 9, 13, 12, 8, 10, 4, 4, 6, 2, 1, 1, 0, 16, 8, 4, 8, 9, 2, 2, 2, 5, 0, 0, 0, 0), # 72
(13, 15, 15, 6, 9, 6, 3, 5, 2, 0, 3, 2, 0, 12, 5, 8, 4, 18, 4, 9, 4, 5, 5, 2, 0, 0), # 73
(16, 12, 11, 10, 11, 5, 2, 5, 4, 3, 1, 3, 0, 12, 11, 5, 5, 13, 3, 3, 4, 4, 3, 4, 1, 0), # 74
(19, 10, 9, 5, 2, 1, 3, 3, 6, 1, 1, 0, 0, 10, 5, 10, 1, 14, 2, 3, 5, 3, 6, 2, 2, 0), # 75
(19, 7, 7, 11, 10, 6, 3, 8, 8, 1, 3, 1, 0, 15, 12, 2, 3, 8, 5, 3, 3, 2, 6, 2, 1, 0), # 76
(6, 9, 12, 10, 13, 4, 8, 1, 3, 3, 1, 1, 0, 13, 10, 5, 5, 9, 4, 4, 4, 6, 6, 3, 1, 0), # 77
(12, 13, 13, 14, 13, 2, 5, 3, 11, 1, 2, 0, 0, 14, 13, 5, 4, 11, 5, 2, 0, 1, 2, 1, 2, 0), # 78
(7, 8, 5, 10, 11, 1, 4, 1, 3, 1, 1, 2, 0, 16, 13, 8, 4, 7, 4, 3, 1, 4, 1, 2, 2, 0), # 79
(17, 6, 9, 9, 8, 6, 2, 4, 4, 3, 3, 0, 0, 13, 9, 13, 3, 10, 8, 6, 1, 1, 4, 3, 1, 0), # 80
(11, 16, 6, 13, 6, 7, 2, 2, 5, 0, 1, 1, 0, 9, 9, 10, 3, 14, 3, 2, 3, 6, 4, 2, 1, 0), # 81
(16, 12, 15, 14, 8, 3, 6, 0, 4, 2, 2, 0, 0, 15, 13, 5, 5, 10, 2, 7, 1, 5, 2, 2, 0, 0), # 82
(14, 15, 15, 12, 5, 3, 3, 3, 2, 5, 3, 1, 0, 9, 4, 9, 8, 9, 6, 5, 2, 5, 1, 3, 2, 0), # 83
(15, 14, 9, 9, 9, 1, 6, 4, 5, 1, 3, 0, 0, 16, 10, 8, 10, 6, 5, 5, 4, 3, 6, 0, 0, 0), # 84
(3, 12, 11, 9, 15, 2, 7, 7, 4, 1, 2, 0, 0, 11, 7, 6, 15, 7, 7, 2, 3, 2, 3, 1, 0, 0), # 85
(12, 9, 7, 14, 15, 4, 3, 5, 7, 1, 0, 0, 0, 13, 13, 14, 6, 14, 1, 3, 2, 5, 2, 2, 1, 0), # 86
(14, 10, 11, 4, 8, 2, 5, 4, 7, 3, 2, 0, 0, 10, 11, 10, 11, 9, 3, 8, 2, 6, 6, 1, 1, 0), # 87
(9, 6, 11, 13, 9, 10, 4, 3, 4, 3, 3, 0, 0, 12, 8, 9, 3, 11, 8, 7, 0, 5, 6, 4, 2, 0), # 88
(18, 9, 7, 8, 7, 7, 3, 5, 5, 1, 1, 0, 0, 12, 15, 8, 2, 11, 4, 5, 2, 6, 8, 1, 2, 0), # 89
(11, 7, 9, 11, 8, 4, 2, 4, 1, 2, 2, 0, 0, 13, 12, 10, 8, 8, 5, 3, 8, 4, 5, 3, 4, 0), # 90
(18, 10, 10, 8, 8, 3, 3, 1, 4, 3, 0, 0, 0, 10, 10, 4, 6, 7, 5, 0, 2, 8, 3, 1, 0, 0), # 91
(11, 14, 6, 7, 9, 11, 4, 0, 2, 3, 2, 0, 0, 6, 13, 10, 3, 5, 2, 5, 2, 3, 0, 0, 1, 0), # 92
(9, 12, 9, 8, 9, 3, 4, 4, 8, 2, 1, 0, 0, 16, 13, 10, 5, 8, 6, 3, 3, 5, 2, 2, 2, 0), # 93
(12, 11, 13, 13, 11, 1, 3, 2, 7, 5, 1, 2, 0, 13, 5, 9, 7, 3, 2, 8, 3, 4, 2, 0, 2, 0), # 94
(6, 7, 11, 12, 11, 1, 4, 3, 1, 3, 0, 1, 0, 10, 4, 3, 2, 9, 4, 2, 7, 7, 3, 1, 2, 0), # 95
(9, 10, 11, 8, 7, 2, 7, 1, 5, 0, 2, 0, 0, 12, 9, 6, 6, 7, 5, 3, 3, 2, 2, 3, 0, 0), # 96
(10, 11, 10, 10, 7, 5, 6, 5, 5, 2, 2, 0, 0, 11, 6, 14, 2, 9, 3, 7, 8, 5, 6, 0, 0, 0), # 97
(8, 7, 8, 14, 8, 1, 5, 2, 3, 6, 2, 0, 0, 9, 9, 8, 6, 5, 2, 6, 3, 4, 4, 4, 1, 0), # 98
(10, 13, 11, 14, 13, 5, 5, 3, 5, 0, 1, 0, 0, 9, 7, 4, 9, 11, 3, 7, 3, 7, 2, 2, 0, 0), # 99
(12, 12, 12, 16, 8, 2, 0, 0, 2, 1, 1, 1, 0, 11, 8, 11, 3, 9, 3, 3, 2, 4, 2, 3, 1, 0), # 100
(10, 11, 10, 7, 10, 1, 4, 1, 3, 3, 1, 1, 0, 15, 11, 13, 7, 10, 4, 4, 2, 4, 4, 2, 0, 0), # 101
(12, 15, 9, 11, 13, 7, 3, 4, 3, 3, 1, 2, 0, 6, 15, 5, 5, 11, 4, 3, 2, 4, 1, 2, 0, 0), # 102
(12, 11, 4, 4, 6, 5, 4, 4, 5, 1, 2, 0, 0, 11, 6, 14, 4, 5, 5, 3, 3, 2, 0, 1, 1, 0), # 103
(19, 7, 11, 11, 11, 2, 2, 1, 1, 1, 2, 2, 0, 13, 8, 7, 3, 13, 6, 4, 4, 9, 1, 1, 0, 0), # 104
(13, 13, 11, 12, 11, 6, 1, 2, 4, 0, 0, 0, 0, 9, 10, 4, 7, 7, 0, 2, 2, 5, 4, 0, 0, 0), # 105
(12, 14, 10, 11, 7, 5, 3, 6, 4, 3, 4, 0, 0, 10, 8, 6, 4, 4, 0, 5, 1, 7, 0, 5, 1, 0), # 106
(9, 8, 10, 8, 7, 4, 8, 0, 7, 1, 2, 2, 0, 13, 13, 7, 6, 12, 9, 2, 1, 1, 4, 3, 1, 0), # 107
(10, 13, 6, 8, 6, 4, 4, 2, 4, 1, 1, 0, 0, 11, 6, 7, 7, 8, 4, 7, 5, 4, 5, 4, 1, 0), # 108
(18, 9, 12, 11, 6, 2, 6, 5, 7, 1, 3, 0, 0, 11, 4, 6, 4, 13, 6, 1, 1, 4, 4, 1, 0, 0), # 109
(9, 9, 14, 4, 13, 5, 4, 1, 6, 4, 2, 1, 0, 15, 8, 8, 6, 8, 5, 0, 3, 6, 5, 0, 1, 0), # 110
(8, 11, 6, 5, 8, 1, 2, 4, 4, 2, 1, 0, 0, 17, 11, 9, 3, 8, 7, 7, 5, 4, 5, 1, 1, 0), # 111
(11, 3, 8, 11, 11, 5, 2, 4, 6, 0, 1, 0, 0, 5, 7, 8, 7, 11, 2, 3, 3, 3, 5, 1, 1, 0), # 112
(16, 6, 7, 5, 11, 8, 2, 4, 4, 2, 1, 1, 0, 5, 9, 8, 9, 6, 3, 6, 1, 7, 5, 3, 0, 0), # 113
(16, 5, 15, 13, 7, 2, 6, 4, 7, 1, 0, 1, 0, 9, 11, 8, 6, 8, 5, 5, 2, 4, 2, 1, 0, 0), # 114
(9, 7, 8, 8, 10, 7, 2, 2, 6, 2, 2, 1, 0, 11, 8, 2, 7, 8, 3, 0, 3, 6, 4, 0, 0, 0), # 115
(12, 6, 7, 15, 11, 6, 6, 1, 3, 0, 0, 1, 0, 9, 20, 8, 10, 10, 5, 1, 2, 3, 2, 3, 0, 0), # 116
(18, 12, 8, 9, 12, 2, 1, 2, 5, 1, 0, 0, 0, 8, 11, 9, 7, 9, 3, 1, 4, 4, 6, 3, 1, 0), # 117
(12, 7, 9, 11, 5, 2, 6, 3, 2, 3, 2, 1, 0, 14, 9, 6, 3, 9, 6, 2, 3, 5, 4, 1, 1, 0), # 118
(14, 15, 5, 4, 10, 6, 3, 1, 5, 0, 1, 2, 0, 16, 10, 6, 2, 8, 2, 2, 4, 2, 1, 3, 1, 0), # 119
(16, 9, 6, 8, 9, 3, 5, 6, 4, 3, 3, 1, 0, 8, 10, 6, 2, 6, 6, 1, 0, 4, 6, 1, 1, 0), # 120
(14, 6, 14, 12, 6, 4, 5, 2, 4, 2, 3, 3, 0, 13, 6, 3, 3, 8, 2, 1, 1, 5, 2, 1, 1, 0), # 121
(16, 8, 11, 16, 11, 4, 3, 3, 4, 4, 1, 1, 0, 8, 11, 4, 7, 4, 6, 3, 2, 3, 0, 1, 1, 0), # 122
(9, 10, 14, 9, 11, 2, 2, 0, 8, 2, 1, 0, 0, 13, 4, 9, 4, 6, 7, 5, 2, 6, 4, 2, 1, 0), # 123
(10, 11, 12, 11, 5, 7, 2, 1, 5, 2, 3, 0, 0, 17, 5, 5, 4, 9, 1, 0, 5, 10, 2, 2, 1, 0), # 124
(7, 12, 11, 7, 2, 7, 2, 4, 5, 1, 4, 0, 0, 10, 9, 7, 5, 9, 5, 4, 6, 3, 3, 1, 0, 0), # 125
(7, 5, 7, 9, 7, 3, 2, 2, 5, 1, 6, 0, 0, 14, 15, 5, 3, 4, 7, 2, 1, 2, 1, 0, 0, 0), # 126
(15, 10, 12, 11, 8, 6, 2, 3, 7, 0, 0, 0, 0, 9, 2, 6, 4, 11, 9, 4, 2, 2, 6, 3, 1, 0), # 127
(13, 8, 8, 13, 8, 4, 8, 1, 6, 1, 1, 0, 0, 10, 7, 7, 2, 3, 4, 4, 4, 3, 1, 4, 2, 0), # 128
(13, 6, 12, 5, 8, 1, 2, 1, 5, 0, 4, 0, 0, 11, 10, 7, 3, 9, 4, 5, 3, 2, 1, 0, 1, 0), # 129
(17, 5, 6, 6, 8, 3, 5, 3, 4, 1, 1, 0, 0, 11, 11, 4, 5, 10, 5, 6, 2, 3, 7, 2, 0, 0), # 130
(10, 5, 7, 9, 11, 4, 1, 5, 6, 1, 1, 0, 0, 7, 5, 9, 9, 15, 3, 4, 3, 5, 3, 1, 1, 0), # 131
(14, 7, 10, 12, 7, 1, 1, 4, 2, 3, 2, 1, 0, 11, 8, 7, 7, 9, 5, 2, 0, 1, 3, 2, 0, 0), # 132
(10, 7, 12, 12, 9, 8, 4, 3, 2, 0, 0, 2, 0, 10, 5, 9, 7, 14, 11, 6, 7, 6, 2, 3, 2, 0), # 133
(14, 12, 15, 11, 11, 5, 3, 4, 5, 0, 1, 2, 0, 9, 8, 8, 5, 8, 4, 4, 1, 5, 3, 3, 0, 0), # 134
(7, 8, 10, 9, 9, 4, 2, 2, 7, 2, 2, 0, 0, 19, 7, 6, 6, 5, 3, 3, 3, 3, 2, 3, 1, 0), # 135
(15, 10, 11, 10, 10, 6, 3, 4, 4, 1, 2, 1, 0, 12, 6, 10, 3, 6, 1, 3, 4, 3, 1, 0, 1, 0), # 136
(11, 7, 9, 6, 11, 2, 4, 4, 3, 1, 0, 1, 0, 9, 11, 3, 3, 1, 2, 3, 3, 3, 1, 1, 0, 0), # 137
(7, 6, 4, 6, 10, 8, 6, 0, 5, 3, 0, 1, 0, 18, 16, 9, 10, 5, 5, 4, 2, 8, 6, 1, 0, 0), # 138
(12, 8, 10, 10, 7, 2, 6, 4, 4, 1, 1, 1, 0, 13, 11, 12, 8, 14, 6, 3, 5, 5, 1, 1, 1, 0), # 139
(12, 14, 8, 9, 10, 3, 4, 2, 4, 2, 3, 1, 0, 8, 9, 3, 7, 5, 3, 3, 5, 2, 2, 0, 0, 0), # 140
(3, 8, 10, 3, 12, 4, 5, 2, 8, 2, 1, 0, 0, 7, 9, 12, 6, 11, 5, 0, 1, 3, 0, 0, 1, 0), # 141
(8, 10, 12, 12, 6, 1, 4, 4, 2, 3, 1, 1, 0, 12, 7, 5, 4, 8, 3, 6, 0, 2, 3, 1, 3, 0), # 142
(12, 11, 12, 9, 9, 3, 1, 3, 3, 1, 0, 0, 0, 6, 4, 6, 8, 3, 2, 4, 3, 2, 2, 1, 0, 0), # 143
(5, 7, 12, 10, 9, 5, 2, 3, 2, 2, 0, 1, 0, 12, 5, 6, 1, 3, 6, 5, 1, 3, 3, 0, 0, 0), # 144
(7, 13, 9, 12, 11, 5, 7, 6, 6, 0, 3, 2, 0, 7, 7, 11, 5, 8, 2, 7, 1, 4, 3, 3, 0, 0), # 145
(13, 6, 10, 10, 8, 3, 2, 3, 8, 3, 1, 1, 0, 9, 11, 4, 4, 8, 5, 4, 0, 3, 2, 1, 1, 0), # 146
(16, 9, 5, 17, 11, 2, 2, 4, 3, 1, 1, 1, 0, 8, 6, 4, 5, 4, 4, 4, 5, 0, 2, 1, 0, 0), # 147
(10, 6, 10, 5, 13, 4, 0, 5, 7, 0, 2, 0, 0, 11, 6, 7, 3, 7, 1, 6, 2, 7, 4, 0, 0, 0), # 148
(16, 4, 8, 13, 4, 2, 1, 5, 5, 4, 0, 0, 0, 14, 7, 8, 4, 11, 6, 2, 4, 1, 5, 3, 0, 0), # 149
(14, 10, 8, 8, 4, 5, 4, 4, 6, 2, 0, 3, 0, 8, 7, 2, 5, 10, 4, 2, 2, 2, 3, 2, 2, 0), # 150
(10, 7, 8, 8, 5, 3, 3, 2, 4, 2, 1, 0, 0, 13, 7, 7, 3, 8, 0, 2, 2, 4, 3, 0, 1, 0), # 151
(9, 4, 9, 5, 7, 2, 5, 3, 4, 1, 1, 2, 0, 8, 5, 6, 4, 14, 4, 2, 2, 3, 5, 4, 1, 0), # 152
(7, 4, 9, 8, 10, 3, 3, 0, 4, 1, 1, 1, 0, 12, 10, 6, 7, 2, 3, 4, 0, 6, 2, 1, 0, 0), # 153
(14, 8, 9, 3, 7, 5, 0, 1, 2, 0, 1, 0, 0, 15, 6, 4, 6, 11, 2, 5, 2, 1, 2, 3, 0, 0), # 154
(11, 5, 9, 5, 6, 4, 1, 3, 5, 0, 2, 0, 0, 8, 8, 11, 8, 5, 3, 6, 2, 2, 0, 1, 0, 0), # 155
(8, 3, 5, 4, 11, 6, 1, 2, 2, 0, 5, 1, 0, 8, 4, 4, 2, 13, 3, 3, 1, 2, 0, 0, 2, 0), # 156
(13, 10, 9, 9, 6, 2, 2, 2, 4, 1, 1, 0, 0, 14, 10, 3, 4, 11, 1, 6, 3, 5, 2, 1, 1, 0), # 157
(7, 3, 2, 5, 6, 2, 1, 1, 1, 1, 0, 0, 0, 11, 7, 5, 4, 12, 2, 4, 2, 3, 2, 4, 0, 0), # 158
(11, 6, 8, 9, 6, 4, 5, 1, 5, 1, 2, 0, 0, 7, 11, 7, 7, 9, 3, 3, 0, 3, 0, 0, 3, 0), # 159
(11, 3, 4, 6, 6, 2, 1, 2, 4, 4, 2, 3, 0, 6, 8, 5, 3, 5, 4, 1, 0, 3, 1, 2, 1, 0), # 160
(9, 6, 7, 7, 5, 7, 5, 6, 2, 0, 1, 0, 0, 14, 8, 3, 3, 6, 3, 1, 2, 2, 3, 1, 2, 0), # 161
(8, 9, 4, 8, 4, 3, 4, 2, 3, 2, 1, 0, 0, 7, 8, 1, 3, 10, 5, 0, 4, 3, 6, 0, 1, 0), # 162
(7, 5, 8, 8, 6, 1, 2, 6, 3, 2, 0, 1, 0, 7, 9, 4, 4, 15, 5, 3, 5, 3, 3, 4, 0, 0), # 163
(10, 4, 11, 6, 8, 2, 4, 4, 4, 1, 2, 0, 0, 10, 3, 10, 3, 5, 6, 4, 4, 3, 2, 3, 0, 0), # 164
(8, 5, 6, 10, 5, 3, 2, 1, 4, 1, 3, 0, 0, 7, 8, 3, 4, 11, 3, 2, 1, 1, 4, 2, 0, 0), # 165
(8, 9, 9, 7, 2, 1, 0, 1, 4, 1, 0, 1, 0, 9, 8, 8, 3, 6, 3, 3, 2, 3, 1, 3, 0, 0), # 166
(8, 5, 4, 6, 11, 4, 1, 5, 2, 1, 2, 0, 0, 6, 7, 4, 6, 6, 0, 2, 3, 6, 3, 1, 0, 0), # 167
(2, 4, 6, 8, 7, 4, 4, 3, 5, 1, 0, 0, 0, 7, 9, 2, 4, 4, 2, 3, 5, 0, 1, 0, 0, 0), # 168
(5, 3, 9, 7, 6, 3, 4, 4, 1, 2, 0, 2, 0, 3, 7, 3, 7, 8, 6, 1, 3, 2, 2, 3, 1, 0), # 169
(5, 3, 4, 4, 5, 2, 0, 2, 3, 1, 0, 0, 0, 9, 6, 10, 1, 13, 1, 1, 4, 3, 2, 1, 1, 0), # 170
(2, 2, 4, 3, 7, 1, 2, 4, 3, 1, 1, 0, 0, 7, 3, 4, 3, 9, 4, 6, 0, 3, 2, 2, 1, 0), # 171
(4, 6, 8, 6, 6, 5, 2, 2, 1, 2, 0, 1, 0, 5, 4, 8, 1, 4, 3, 5, 4, 2, 2, 1, 0, 0), # 172
(8, 6, 5, 6, 6, 6, 7, 1, 1, 2, 0, 0, 0, 6, 5, 6, 3, 5, 5, 1, 1, 2, 3, 1, 1, 0), # 173
(6, 4, 6, 8, 4, 3, 2, 0, 3, 2, 0, 0, 0, 2, 6, 2, 7, 2, 3, 2, 0, 3, 5, 0, 0, 0), # 174
(2, 3, 3, 5, 7, 2, 0, 1, 5, 2, 1, 0, 0, 5, 5, 7, 2, 3, 1, 1, 1, 4, 2, 1, 0, 0), # 175
(4, 2, 3, 2, 3, 4, 2, 2, 2, 1, 2, 0, 0, 2, 4, 3, 0, 7, 0, 0, 1, 2, 2, 1, 0, 0), # 176
(6, 2, 2, 7, 3, 3, 2, 2, 2, 0, 0, 1, 0, 5, 1, 6, 3, 9, 1, 1, 1, 4, 3, 1, 1, 0), # 177
(5, 2, 3, 7, 8, 3, 1, 2, 2, 1, 1, 0, 0, 3, 4, 3, 1, 4, 2, 0, 1, 2, 0, 0, 0, 0), # 178
(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), # 179
)
station_arriving_intensity = (
(6.025038694046121, 6.630346271631799, 6.253539875535008, 7.457601328636119, 6.665622729131534, 3.766385918444806, 4.9752427384486975, 5.583811407575308, 7.308118874601608, 4.749618018626843, 5.046318196662723, 5.877498093967408, 6.100656255094035), # 0
(6.425192582423969, 7.06807283297371, 6.666415909596182, 7.950173103931939, 7.106988404969084, 4.015180300851067, 5.303362729516432, 5.951416467486849, 7.79069439159949, 5.062776830732579, 5.3797153631473575, 6.265459992977225, 6.503749976927826), # 1
(6.8240676107756775, 7.504062205069175, 7.077650742656896, 8.440785245597752, 7.546755568499692, 4.262982137414934, 5.630182209552845, 6.317550297485303, 8.271344168253059, 5.3746965300246545, 5.711787778531575, 6.651879182463666, 6.905237793851628), # 2
(7.220109351775874, 7.936584602323736, 7.485613043183825, 8.927491689038488, 7.983194011202282, 4.508808747102135, 5.954404369977547, 6.680761388993408, 8.74816219310531, 5.684139238111417, 6.041218094192859, 7.035222821916553, 7.30352736750507), # 3
(7.611763378099177, 8.363910239142928, 7.8886714796436435, 9.408346369659084, 8.41457352455579, 4.751677448878401, 6.27473240221015, 7.039598233433898, 9.219242454699248, 5.9898670766012145, 6.36668896150869, 7.413958070825716, 7.69702635952778), # 4
(7.9974752624202115, 8.784309329932306, 8.285194720503021, 9.881403222864472, 8.839163900039136, 4.990605561709457, 6.589869497670269, 7.392609322229511, 9.682678941577871, 6.290642167102395, 6.686883031856559, 7.786552088680978, 8.084142431559393), # 5
(8.375690577413598, 9.196052089097401, 8.673551434228639, 10.344716184059582, 9.255234929131252, 5.224610404561036, 6.898518847777515, 7.738343146802986, 10.136565642284177, 6.58522663122331, 7.000482956613939, 8.15147203497217, 8.463283245239527), # 6
(8.744854895753962, 9.597408731043757, 9.052110289287162, 10.796339188649354, 9.661056403311065, 5.452709296398865, 7.199383643951502, 8.075348198577062, 10.578996545361173, 6.872382590572303, 7.306171387158321, 8.507185069189115, 8.832856462207822), # 7
(9.103413790115921, 9.986649470176918, 9.419239954145274, 11.234326172038713, 10.054898114057503, 5.673919556188667, 7.491167077611837, 8.402172968974469, 11.008065639351846, 7.150872166757728, 7.602630974867185, 8.852158350821643, 9.1912697441039), # 8
(9.449812833174102, 10.362044520902426, 9.773309097269644, 11.656731069632603, 10.43502985284949, 5.88725850289618, 7.772572340178144, 8.717365949417955, 11.421866912799208, 7.419457481387929, 7.888544371118013, 9.184859039359576, 9.536930752567395), # 9
(9.782497597603118, 10.721864097625819, 10.11268638712695, 12.061607816835945, 10.79972141116596, 6.091743455487129, 8.042302623070025, 9.019475631330252, 11.818494354246257, 7.676900656071257, 8.162594227288288, 9.503754294292742, 9.868247149237932), # 10
(10.099913656077605, 11.064378414752648, 10.435740492183857, 12.447010349053675, 11.14724258048584, 6.286391732927242, 8.2990611177071, 9.307050506134097, 12.196041952235992, 7.921963812416062, 8.423463194755499, 9.807311275110973, 10.183626595755133), # 11
(10.400506581272174, 11.387857686688436, 10.740840080907047, 12.810992601690733, 11.475863152288053, 6.470220654182243, 8.541551015508974, 9.578639065252224, 12.552603695311413, 8.153409072030685, 8.669833924897121, 10.093997141304081, 10.48147675375864), # 12
(10.68272194586145, 11.690572127838744, 11.026353821763193, 13.151608510152052, 11.78385291805152, 6.642247538217868, 8.768475507895266, 9.832789800107378, 12.886273572015517, 8.369998556523484, 8.900389069090641, 10.362279052361904, 10.760205284888082), # 13
(10.945005322520059, 11.970791952609106, 11.290650383218976, 13.46691200984255, 12.069481669255188, 6.801489703999841, 8.978537786285592, 10.068051202122295, 13.195145570891304, 8.5704943875028, 9.113811278713541, 10.610624167774272, 11.018219850783076), # 14
(11.185802283922625, 12.22678737540506, 11.53209843374105, 13.754957036167182, 12.33101919737797, 6.946964470493895, 9.17044104209955, 10.282971762719706, 13.477313680481783, 8.753658686576989, 9.308783205143303, 10.837499647031004, 11.253928113083257), # 15
(11.40355840274376, 12.456828610632158, 11.749066641796109, 14.01379752453086, 12.5667352938988, 7.077689156665751, 9.34288846675677, 10.476099973322352, 13.730871889329944, 8.918253575354395, 9.483987499757415, 11.041372649621927, 11.465737733428254), # 16
(11.59671925165809, 12.659185872695934, 11.939923675850823, 14.241487410338534, 12.774899750296605, 7.192681081481142, 9.494583251676852, 10.64598432535298, 13.95391418597878, 9.06304117544336, 9.638106813933359, 11.220710335036866, 11.652056373457699), # 17
(11.763730403340244, 12.832129376001928, 12.103038204371856, 14.436080628995134, 12.953782358050306, 7.290957563905803, 9.62422858827942, 10.791173310234312, 14.144534558971316, 9.186783608452243, 9.76982379904861, 11.373979862765658, 11.811291694811214), # 18
(11.903037430464838, 12.973929334955693, 12.236778895825895, 14.595631115905576, 13.101652908638838, 7.37153592290545, 9.730527667984072, 10.910215419389093, 14.300826996850533, 9.288242995989393, 9.877821106480653, 11.499648392298115, 11.941851359128435), # 19
(12.013085905706498, 13.082855963962754, 12.339514418679602, 14.718192806474825, 13.216781193541133, 7.4334334774458215, 9.812183682210435, 11.00165914424006, 14.420885488159437, 9.36618145966315, 9.96078138760698, 11.59618308312407, 12.042143028048988), # 20
(12.09232140173984, 13.15717947742867, 12.409613441399662, 14.801819636107782, 13.297437004236105, 7.475667546492642, 9.86789982237811, 11.064052976209947, 14.502804021441024, 9.419361121081865, 10.01738729380507, 11.662051094733352, 12.110574363212494), # 21
(12.139189491239494, 13.195170089758973, 12.445444632452743, 14.844565540209402, 13.341890132202689, 7.497255449011639, 9.89637927990672, 11.095945406721498, 14.544676585238298, 9.44654410185389, 10.046321476452407, 11.695719586615787, 12.145553026258591), # 22
(12.156472036011166, 13.199668312757202, 12.449907818930042, 14.849916975308643, 13.353278467239116, 7.5, 9.899764802711205, 11.099392592592592, 14.54991148148148, 9.44975072702332, 10.049949644594088, 11.69987709190672, 12.15), # 23
(12.169214895640982, 13.197044444444446, 12.449177777777777, 14.849258333333335, 13.359729136337823, 7.5, 9.8979045751634, 11.0946, 14.549209999999999, 9.44778074074074, 10.049549494949495, 11.698903703703703, 12.15), # 24
(12.181688676253897, 13.191872427983538, 12.447736625514404, 14.84795524691358, 13.366037934713404, 7.5, 9.894238683127572, 11.085185185185185, 14.547824074074073, 9.443902606310013, 10.048756079311634, 11.696982167352537, 12.15), # 25
(12.19389242285764, 13.184231275720165, 12.445604115226338, 14.846022530864197, 13.372204642105325, 7.5, 9.888824061970466, 11.071325925925926, 14.54577148148148, 9.438180850480109, 10.047576580621024, 11.694138820301784, 12.15), # 26
(12.205825180459962, 13.174199999999997, 12.4428, 14.843474999999998, 13.378229038253057, 7.5, 9.881717647058824, 11.0532, 14.54307, 9.430679999999999, 10.046018181818182, 11.6904, 12.15), # 27
(12.217485994068602, 13.161857613168722, 12.439344032921811, 14.8403274691358, 13.384110902896081, 7.5, 9.87297637375938, 11.030985185185186, 14.539737407407406, 9.421464581618656, 10.04408806584362, 11.685792043895749, 12.15), # 28
(12.2288739086913, 13.147283127572017, 12.43525596707819, 14.83659475308642, 13.389850015773865, 7.5, 9.862657177438878, 11.004859259259257, 14.535791481481482, 9.410599122085047, 10.041793415637859, 11.680341289437584, 12.15), # 29
(12.239987969335797, 13.130555555555555, 12.430555555555555, 14.832291666666666, 13.395446156625884, 7.5, 9.850816993464052, 10.974999999999998, 14.53125, 9.398148148148149, 10.039141414141413, 11.674074074074072, 12.15), # 30
(12.25082722100983, 13.11175390946502, 12.42526255144033, 14.827433024691356, 13.400899105191609, 7.5, 9.837512757201647, 10.941585185185184, 14.52613074074074, 9.384176186556926, 10.0361392442948, 11.667016735253773, 12.15), # 31
(12.261390708721144, 13.09095720164609, 12.419396707818928, 14.822033641975308, 13.406208641210513, 7.5, 9.822801404018398, 10.904792592592594, 14.520451481481482, 9.368747764060357, 10.032794089038532, 11.659195610425241, 12.15), # 32
(12.271677477477477, 13.068244444444444, 12.412977777777778, 14.816108333333332, 13.411374544422076, 7.5, 9.806739869281046, 10.8648, 14.51423, 9.351927407407407, 10.02911313131313, 11.650637037037034, 12.15), # 33
(12.28168657228657, 13.04369465020576, 12.406025514403291, 14.809671913580246, 13.416396594565759, 7.5, 9.789385088356331, 10.821785185185183, 14.507484074074075, 9.33377964334705, 10.025103554059108, 11.641367352537722, 12.15), # 34
(12.291417038156167, 13.01738683127572, 12.398559670781895, 14.802739197530862, 13.421274571381044, 7.5, 9.77079399661099, 10.775925925925925, 14.500231481481482, 9.314368998628257, 10.020772540216983, 11.631412894375858, 12.15), # 35
(12.300867920094007, 12.989399999999998, 12.3906, 14.795324999999998, 13.426008254607403, 7.5, 9.751023529411764, 10.727400000000001, 14.492489999999998, 9.293759999999999, 10.016127272727273, 11.620800000000001, 12.15), # 36
(12.310038263107828, 12.95981316872428, 12.382166255144032, 14.787444135802469, 13.430597423984304, 7.5, 9.730130622125392, 10.676385185185184, 14.484277407407406, 9.272017174211248, 10.01117493453049, 11.609555006858711, 12.15), # 37
(12.31892711220537, 12.928705349794239, 12.37327818930041, 14.779111419753086, 13.435041859251228, 7.5, 9.708172210118615, 10.62305925925926, 14.475611481481481, 9.249205048010975, 10.005922708567153, 11.597704252400549, 12.15), # 38
(12.327533512394384, 12.896155555555554, 12.363955555555556, 14.770341666666667, 13.439341340147644, 7.5, 9.68520522875817, 10.567599999999999, 14.466510000000001, 9.225388148148149, 10.000377777777777, 11.585274074074073, 12.15), # 39
(12.335856508682596, 12.86224279835391, 12.354218106995884, 14.761149691358025, 13.443495646413021, 7.5, 9.661286613410796, 10.510185185185186, 14.456990740740741, 9.200631001371743, 9.99454732510288, 11.572290809327848, 12.15), # 40
(12.343895146077754, 12.82704609053498, 12.344085596707819, 14.751550308641974, 13.447504557786841, 7.5, 9.636473299443233, 10.450992592592593, 14.44707148148148, 9.174998134430727, 9.988438533482979, 11.558780795610424, 12.15), # 41
(12.3516484695876, 12.790644444444444, 12.333577777777778, 14.741558333333334, 13.45136785400857, 7.5, 9.610822222222222, 10.3902, 14.436770000000001, 9.148554074074074, 9.982058585858585, 11.54477037037037, 12.15), # 42
(12.35911552421987, 12.753116872427984, 12.322714403292181, 14.731188580246913, 13.455085314817683, 7.5, 9.584390317114499, 10.327985185185186, 14.426104074074072, 9.121363347050755, 9.97541466517022, 11.530285871056241, 12.15), # 43
(12.366295354982311, 12.714542386831276, 12.31151522633745, 14.72045586419753, 13.458656719953654, 7.5, 9.557234519486807, 10.264525925925927, 14.415091481481479, 9.09349048010974, 9.968513954358398, 11.515353635116599, 12.15), # 44
(12.37318700688266, 12.674999999999999, 12.299999999999999, 14.709375, 13.462081849155954, 7.5, 9.529411764705882, 10.2, 14.403749999999999, 9.065, 9.961363636363636, 11.499999999999998, 12.15), # 45
(12.379789524928656, 12.634568724279836, 12.288188477366253, 14.697960802469135, 13.465360482164058, 7.5, 9.500978988138465, 10.134585185185186, 14.392097407407405, 9.035956433470506, 9.953970894126448, 11.484251303155007, 12.15), # 46
(12.386101954128042, 12.59332757201646, 12.276100411522634, 14.686228086419751, 13.46849239871744, 7.5, 9.471993125151295, 10.068459259259258, 14.380151481481482, 9.006424307270233, 9.946342910587354, 11.468133882030179, 12.15), # 47
(12.392123339488554, 12.551355555555554, 12.263755555555555, 14.674191666666667, 13.471477378555573, 7.5, 9.442511111111111, 10.001800000000001, 14.367930000000001, 8.976468148148147, 9.938486868686867, 11.451674074074074, 12.15), # 48
(12.397852726017943, 12.508731687242797, 12.251173662551441, 14.661866358024692, 13.474315201417928, 7.5, 9.412589881384651, 9.934785185185184, 14.355450740740741, 8.946152482853224, 9.930409951365506, 11.434898216735254, 12.15), # 49
(12.403289158723938, 12.46553497942387, 12.23837448559671, 14.649266975308642, 13.477005647043978, 7.5, 9.38228637133866, 9.867592592592592, 14.342731481481481, 8.91554183813443, 9.922119341563786, 11.417832647462278, 12.15), # 50
(12.408431682614292, 12.421844444444444, 12.225377777777776, 14.636408333333332, 13.479548495173196, 7.5, 9.351657516339868, 9.8004, 14.329790000000001, 8.88470074074074, 9.913622222222223, 11.400503703703704, 12.15), # 51
(12.413279342696734, 12.377739094650208, 12.21220329218107, 14.62330524691358, 13.481943525545056, 7.5, 9.320760251755022, 9.733385185185183, 14.316644074074073, 8.853693717421125, 9.904925776281331, 11.382937722908094, 12.15), # 52
(12.417831183979011, 12.333297942386832, 12.198870781893005, 14.609972530864196, 13.484190517899036, 7.5, 9.28965151295086, 9.666725925925926, 14.303311481481483, 8.822585294924554, 9.89603718668163, 11.365161042524004, 12.15), # 53
(12.42208625146886, 12.2886, 12.185399999999998, 14.596425, 13.486289251974602, 7.5, 9.258388235294117, 9.600599999999998, 14.28981, 8.79144, 9.886963636363634, 11.347199999999999, 12.15), # 54
(12.426043590174027, 12.24372427983539, 12.171810699588478, 14.5826774691358, 13.488239507511228, 7.5, 9.227027354151536, 9.535185185185185, 14.276157407407407, 8.760322359396433, 9.877712308267864, 11.329080932784636, 12.15), # 55
(12.429702245102245, 12.198749794238683, 12.158122633744856, 14.568744753086419, 13.49004106424839, 7.5, 9.195625804889858, 9.470659259259259, 14.262371481481482, 8.729296899862826, 9.868290385334829, 11.310830178326475, 12.15), # 56
(12.433061261261258, 12.153755555555556, 12.144355555555556, 14.554641666666665, 13.49169370192556, 7.5, 9.164240522875817, 9.407200000000001, 14.24847, 8.698428148148148, 9.85870505050505, 11.292474074074073, 12.15), # 57
(12.436119683658815, 12.108820576131688, 12.130529218106995, 14.540383024691355, 13.493197200282209, 7.5, 9.132928443476155, 9.344985185185184, 14.23447074074074, 8.667780631001373, 9.848963486719043, 11.274038957475994, 12.15), # 58
(12.438876557302644, 12.064023868312757, 12.116663374485597, 14.525983641975307, 13.494551339057814, 7.5, 9.101746502057614, 9.284192592592593, 14.220391481481482, 8.637418875171468, 9.839072876917319, 11.255551165980796, 12.15), # 59
(12.441330927200491, 12.019444444444444, 12.102777777777776, 14.511458333333334, 13.495755897991843, 7.5, 9.070751633986927, 9.225, 14.20625, 8.607407407407408, 9.829040404040404, 11.237037037037037, 12.15), # 60
(12.443481838360098, 11.975161316872429, 12.08889218106996, 14.496821913580245, 13.496810656823774, 7.5, 9.040000774630839, 9.167585185185185, 14.192064074074073, 8.577810754458161, 9.818873251028807, 11.218522908093279, 12.15), # 61
(12.445328335789204, 11.931253497942386, 12.075026337448561, 14.482089197530865, 13.497715395293081, 7.5, 9.009550859356088, 9.112125925925925, 14.177851481481481, 8.548693443072702, 9.808578600823045, 11.20003511659808, 12.15), # 62
(12.44686946449555, 11.887799999999999, 12.0612, 14.467275, 13.498469893139227, 7.5, 8.979458823529411, 9.0588, 14.16363, 8.520119999999999, 9.798163636363636, 11.1816, 12.15), # 63
(12.448104269486876, 11.844879835390946, 12.047432921810698, 14.452394135802468, 13.499073930101698, 7.5, 8.94978160251755, 9.007785185185186, 14.149417407407407, 8.492154951989026, 9.787635540591094, 11.1632438957476, 12.15), # 64
(12.449031795770926, 11.802572016460903, 12.033744855967079, 14.437461419753085, 13.49952728591996, 7.5, 8.920576131687243, 8.959259259259259, 14.135231481481481, 8.464862825788751, 9.777001496445942, 11.144993141289435, 12.15), # 65
(12.449651088355436, 11.760955555555556, 12.020155555555556, 14.422491666666666, 13.499829740333487, 7.5, 8.891899346405228, 8.913400000000001, 14.12109, 8.438308148148147, 9.766268686868687, 11.126874074074076, 12.15), # 66
(12.44996119224815, 11.720109465020576, 12.00668477366255, 14.407499691358023, 13.499981073081754, 7.5, 8.863808182038246, 8.870385185185187, 14.10701074074074, 8.412555445816187, 9.755444294799851, 11.108913031550067, 12.15), # 67
(12.44974993737699, 11.679898367184387, 11.993287139917694, 14.392370088566828, 13.499853546356814, 7.49986081390032, 8.836218233795575, 8.830012620027434, 14.092905418381346, 8.3875445299766, 9.74434318624845, 11.09103602627969, 12.149850180041152), # 68
(12.447770048309177, 11.639094623655915, 11.979586111111109, 14.376340217391302, 13.498692810457515, 7.49876049382716, 8.808321817615935, 8.790118518518518, 14.078157407407408, 8.362567668845314, 9.731835406698563, 11.072662768031188, 12.148663194444444), # 69
(12.443862945070673, 11.597510951812026, 11.965522119341562, 14.35930454911433, 13.49639917695473, 7.496593507087334, 8.779992161473643, 8.75034293552812, 14.062683470507546, 8.33750342935528, 9.717778663831295, 11.05370731355137, 12.14631880144033), # 70
(12.438083592771514, 11.555172202309835, 11.951100102880657, 14.341288204508858, 13.493001694504963, 7.49339497027892, 8.751241991446784, 8.710699039780522, 14.046506652949246, 8.312352431211167, 9.702224844940634, 11.034183524655257, 12.142847865226338), # 71
(12.430486956521738, 11.51210322580645, 11.936324999999998, 14.322316304347826, 13.488529411764706, 7.4892, 8.722084033613445, 8.671199999999999, 14.02965, 8.287115294117646, 9.685225837320575, 11.014105263157894, 12.13828125), # 72
(12.421128001431383, 11.46832887295898, 11.921201748971193, 14.302413969404187, 13.48301137739046, 7.48404371284865, 8.69253101405171, 8.631858984910837, 14.012136556927299, 8.261792637779392, 9.666833528265105, 10.993486390874303, 12.132649819958848), # 73
(12.410061692610485, 11.423873994424532, 11.905735288065841, 14.281606320450885, 13.47647664003873, 7.477961225422954, 8.662595658839667, 8.59268916323731, 13.993989368998628, 8.236385081901073, 9.647099805068226, 10.972340769619521, 12.125984439300412), # 74
(12.397342995169081, 11.378763440860213, 11.889930555555553, 14.25991847826087, 13.468954248366014, 7.470987654320988, 8.6322906940554, 8.553703703703704, 13.97523148148148, 8.210893246187362, 9.626076555023921, 10.950682261208575, 12.118315972222222), # 75
(12.383026874217212, 11.33302206292314, 11.873792489711933, 14.237375563607086, 13.460473251028805, 7.463158116140832, 8.601628845776993, 8.514915775034293, 13.955885939643347, 8.185317750342934, 9.60381566542619, 10.928524727456498, 12.10967528292181), # 76
(12.367168294864912, 11.286674711270411, 11.857326028806582, 14.214002697262478, 13.451062696683609, 7.454507727480566, 8.570622840082535, 8.476338545953361, 13.935975788751714, 8.15965921407246, 9.580369023569023, 10.905882030178327, 12.10009323559671), # 77
(12.349822222222222, 11.23974623655914, 11.84053611111111, 14.189824999999999, 13.440751633986928, 7.445071604938271, 8.53928540305011, 8.437985185185186, 13.915524074074073, 8.133918257080609, 9.55578851674641, 10.882768031189086, 12.089600694444444), # 78
(12.331043621399177, 11.192261489446436, 11.823427674897118, 14.164867592592591, 13.429569111595256, 7.434884865112025, 8.5076292607578, 8.399868861454047, 13.894553840877913, 8.108095499072055, 9.530126032252346, 10.859196592303805, 12.07822852366255), # 79
(12.310887457505816, 11.144245320589407, 11.806005658436213, 14.139155595813206, 13.417544178165095, 7.423982624599908, 8.475667139283697, 8.362002743484226, 13.873088134430727, 8.082191559751472, 9.503433457380826, 10.835181575337522, 12.066007587448558), # 80
(12.289408695652174, 11.09572258064516, 11.788274999999999, 14.112714130434783, 13.40470588235294, 7.412399999999999, 8.443411764705882, 8.3244, 13.851149999999999, 8.05620705882353, 9.475762679425838, 10.810736842105262, 12.052968749999998), # 81
(12.26666230094829, 11.046718120270809, 11.770240637860082, 14.085568317230273, 13.391083272815298, 7.40017210791038, 8.410875863102444, 8.28707379972565, 13.828762482853223, 8.030142615992899, 9.447165585681375, 10.785876254422064, 12.039142875514404), # 82
(12.242703238504205, 10.997256790123457, 11.751907510288065, 14.057743276972623, 13.376705398208665, 7.387334064929126, 8.378072160551463, 8.250037311385459, 13.805948628257887, 8.003998850964253, 9.417694063441433, 10.760613674102954, 12.0245608281893), # 83
(12.21758647342995, 10.947363440860215, 11.733280555555554, 14.029264130434782, 13.361601307189543, 7.373920987654321, 8.345013383131029, 8.213303703703703, 13.78273148148148, 7.977776383442266, 9.3874, 10.734962962962962, 12.009253472222222), # 84
(12.191366970835569, 10.897062923138192, 11.714364711934154, 14.000155998389696, 13.345800048414427, 7.359967992684042, 8.311712256919229, 8.176886145404664, 13.759134087791493, 7.951475833131606, 9.356335282651072, 10.708937982817124, 11.9932516718107), # 85
(12.164099695831096, 10.846380087614497, 11.695164917695474, 13.970444001610307, 13.32933067053982, 7.34551019661637, 8.278181507994145, 8.14079780521262, 13.73517949245542, 7.925097819736949, 9.32455179868864, 10.682552595480471, 11.976586291152262), # 86
(12.135839613526569, 10.795339784946236, 11.67568611111111, 13.940153260869563, 13.312222222222223, 7.330582716049382, 8.244433862433862, 8.10505185185185, 13.710890740740743, 7.8986429629629615, 9.292101435406698, 10.655820662768031, 11.959288194444444), # 87
(12.106641689032028, 10.74396686579052, 11.655933230452675, 13.90930889694042, 13.29450375211813, 7.315220667581161, 8.210482046316468, 8.069661454046638, 13.686290877914953, 7.8721118825143215, 9.259036080099238, 10.628756046494837, 11.941388245884776), # 88
(12.076560887457505, 10.69228618080446, 11.63591121399177, 13.877936030595812, 13.276204308884047, 7.299459167809785, 8.176338785720048, 8.034639780521262, 13.661402949245542, 7.845505198095699, 9.225407620060253, 10.601372608475922, 11.922917309670781), # 89
(12.045652173913043, 10.640322580645162, 11.615625, 13.846059782608696, 13.257352941176471, 7.283333333333333, 8.142016806722689, 7.999999999999999, 13.636250000000002, 7.818823529411764, 9.191267942583732, 10.573684210526315, 11.90390625), # 90
(12.013970513508676, 10.588100915969731, 11.59507952674897, 13.813705273752015, 13.237978697651899, 7.266878280749885, 8.107528835402473, 7.965755281207133, 13.610855075445818, 7.79206749616719, 9.15666893496367, 10.54570471446105, 11.884385931069957), # 91
(11.981570871354446, 10.535646037435285, 11.574279732510288, 13.78089762479871, 13.218110626966835, 7.250129126657521, 8.07288759783749, 7.9319187928669415, 13.585241220850481, 7.7652377180666505, 9.121662484494063, 10.517447982095156, 11.864387217078187), # 92
(11.948508212560386, 10.482982795698925, 11.553230555555555, 13.74766195652174, 13.197777777777778, 7.2331209876543205, 8.03810582010582, 7.898503703703704, 13.55943148148148, 7.738334814814813, 9.0863004784689, 10.488927875243665, 11.84394097222222), # 93
(11.914837502236535, 10.43013604141776, 11.531936934156379, 13.714023389694042, 13.177009198741224, 7.215888980338362, 8.003196228285553, 7.865523182441701, 13.53344890260631, 7.7113594061163555, 9.050634804182172, 10.460158255721609, 11.823078060699588), # 94
(11.880613705492932, 10.377130625248904, 11.510403806584362, 13.680007045088566, 13.155833938513677, 7.198468221307727, 7.968171548454772, 7.832990397805213, 13.507316529492455, 7.684312111675945, 9.014717348927874, 10.431152985344015, 11.801829346707818), # 95
(11.845891787439614, 10.323991397849465, 11.488636111111111, 13.645638043478261, 13.134281045751633, 7.180893827160493, 7.933044506691564, 7.800918518518519, 13.481057407407405, 7.657193551198256, 8.9786, 10.401925925925926, 11.780225694444445), # 96
(11.810726713186616, 10.270743209876544, 11.466638786008229, 13.610941505636069, 13.112379569111596, 7.163200914494741, 7.897827829074016, 7.769320713305898, 13.454694581618655, 7.63000434438796, 8.942334644692538, 10.372490939282363, 11.758297968106996), # 97
(11.775173447843981, 10.217410911987256, 11.444416769547324, 13.575942552334944, 13.090158557250062, 7.145424599908551, 7.86253424168021, 7.738210150891632, 13.428251097393689, 7.602745110949729, 8.905973170299486, 10.342861887228358, 11.736077031893004), # 98
(11.739286956521738, 10.16401935483871, 11.421975, 13.540666304347825, 13.06764705882353, 7.1276, 7.827176470588236, 7.707599999999999, 13.40175, 7.575416470588234, 8.869567464114832, 10.313052631578946, 11.71359375), # 99
(11.703122204329933, 10.110593389088011, 11.39931841563786, 13.505137882447665, 13.044874122488501, 7.109762231367169, 7.791767241876174, 7.677503429355281, 13.375214334705076, 7.548019043008149, 8.833169413432572, 10.28307703414916, 11.690878986625515), # 100
(11.6667341563786, 10.057157865392274, 11.376451954732511, 13.469382407407409, 13.021868796901476, 7.091946410608139, 7.756319281622114, 7.647933607681755, 13.348667146776405, 7.5205534479141445, 8.796830905546694, 10.252948956754024, 11.667963605967076), # 101
(11.630177777777778, 10.003737634408603, 11.353380555555555, 13.433425, 12.998660130718955, 7.074187654320988, 7.720845315904139, 7.618903703703703, 13.32213148148148, 7.4930203050108934, 8.760603827751195, 10.222682261208577, 11.644878472222222), # 102
(11.593508033637502, 9.950357546794105, 11.3301091563786, 13.39729078099839, 12.975277172597435, 7.056521079103795, 7.685358070800336, 7.590426886145404, 13.295630384087792, 7.465420234003066, 8.724540067340067, 10.192290809327847, 11.621654449588474), # 103
(11.556779889067812, 9.897042453205893, 11.30664269547325, 13.361004871175522, 12.951748971193416, 7.03898180155464, 7.649870272388791, 7.562516323731138, 13.269186899862826, 7.437753854595336, 8.6886915116073, 10.161788462926864, 11.598322402263374), # 104
(11.520048309178742, 9.843817204301073, 11.28298611111111, 13.324592391304348, 12.928104575163397, 7.021604938271605, 7.614394646747589, 7.535185185185185, 13.242824074074074, 7.410021786492375, 8.653110047846889, 10.131189083820663, 11.574913194444443), # 105
(11.483368259080336, 9.790706650736759, 11.259144341563784, 13.288078462157811, 12.904373033163884, 7.004425605852766, 7.578943919954813, 7.508446639231824, 13.216564951989024, 7.382224649398854, 8.617847563352825, 10.100506533824273, 11.551457690329217), # 106
(11.446794703882626, 9.737735643170053, 11.235122325102882, 13.251488204508856, 12.880583393851365, 6.987478920896206, 7.543530818088553, 7.482313854595337, 13.190432578875171, 7.354363063019446, 8.582955945419101, 10.069754674752724, 11.527986754115226), # 107
(11.410382608695652, 9.684929032258065, 11.210925000000001, 13.214846739130435, 12.856764705882352, 6.9708, 7.508168067226889, 7.4568, 13.16445, 7.326437647058824, 8.548487081339712, 10.038947368421054, 11.504531250000001), # 108
(11.374186938629451, 9.632311668657906, 11.18655730452675, 13.178179186795488, 12.832946017913338, 6.954423959762231, 7.472868393447913, 7.431918244170096, 13.138640260631002, 7.298449021221656, 8.514492858408648, 10.008098476644285, 11.48112204218107), # 109
(11.338262658794058, 9.579908403026684, 11.162024176954734, 13.141510668276974, 12.809156378600823, 6.938385916780978, 7.437644522829707, 7.407681755829903, 13.113026406035663, 7.270397805212619, 8.4810251639199, 9.977221861237457, 11.457789994855966), # 110
(11.302664734299517, 9.527744086021507, 11.137330555555558, 13.104866304347826, 12.785424836601306, 6.922720987654322, 7.402509181450357, 7.384103703703703, 13.087631481481482, 7.242284618736383, 8.448135885167463, 9.946331384015595, 11.434565972222222), # 111
(11.26744813025586, 9.47584356829948, 11.112481378600824, 13.068271215780998, 12.76178044057129, 6.907464288980339, 7.367475095387949, 7.361197256515775, 13.062478532235938, 7.214110081497618, 8.41587690944533, 9.915440906793732, 11.411480838477365), # 112
(11.232605068443652, 9.424318342543142, 11.087541393902482, 13.031800658990448, 12.738210816208445, 6.892643723057416, 7.332631156388123, 7.339023082536727, 13.037655373510344, 7.185965683935275, 8.38430868738344, 9.884631523805313, 11.388532681011865), # 113
(11.197777077480078, 9.373676620230642, 11.062854810025941, 12.995747305532804, 12.71447202547959, 6.8782255302358815, 7.298421850092694, 7.317853511406144, 13.013542842855673, 7.158378201495339, 8.353493204535836, 9.85429460653557, 11.365530496992042), # 114
(11.162861883604794, 9.323936638419655, 11.038436319248781, 12.960101406218135, 12.69048921346632, 6.864172214998518, 7.264871580229873, 7.297683185134451, 12.990149974402547, 7.131390393585692, 8.323385413712511, 9.824445099070621, 11.342407957992451), # 115
(11.127815847885161, 9.275025937550042, 11.014238627980648, 12.924799380319685, 12.666226231660534, 6.8504506527445175, 7.231925781033471, 7.278456375478791, 12.967417607073395, 7.104952030139456, 8.293927117525778, 9.795027836984815, 11.319128711707068), # 116
(11.092595331388527, 9.226872058061664, 10.990214442631183, 12.889777647110693, 12.641646931554133, 6.837027718873069, 7.199529886737303, 7.260117354196302, 12.945286579790643, 7.079012881089755, 8.26506011858794, 9.7659876558525, 11.295656405829869), # 117
(11.057156695182252, 9.179402540394388, 10.96631646961004, 12.8549726258644, 12.61671516463901, 6.8238702887833655, 7.167629331575178, 7.2426103930441155, 12.923697731476722, 7.053522716369711, 8.236726219511308, 9.737269391248018, 11.271954688054828), # 118
(11.02145630033369, 9.132544924988075, 10.942497415326867, 12.820320735854047, 12.591394782407065, 6.810945237874599, 7.136169549780907, 7.225879763779374, 12.902591901054052, 7.028431305912446, 8.208867222908193, 9.708817878745721, 11.247987206075917), # 119
(10.985450507910194, 9.08622675228259, 10.918709986191313, 12.785758396352874, 12.565649636350196, 6.7982194415459585, 7.105095975588303, 7.209869738159211, 12.88190992744507, 7.003688419651087, 8.181424931390898, 9.680577953919956, 11.223717607587115), # 120
(10.949095678979122, 9.040375562717795, 10.894906888613024, 12.75122202663412, 12.539443577960302, 6.7856597751966365, 7.0743540432311764, 7.1945245879407675, 12.861592649572199, 6.979243827518755, 8.154341147571738, 9.652494452345065, 11.199109540282393), # 121
(10.912348174607825, 8.994918896733553, 10.871040829001652, 12.716648045971025, 12.512740458729281, 6.773233114225823, 7.043889186943341, 7.179788584881178, 12.841580906357867, 6.955047299448572, 8.127557674063022, 9.6245122095954, 11.174126651855724), # 122
(10.875164355863662, 8.949784294769728, 10.847064513766842, 12.681972873636832, 12.485504130149028, 6.76090633403271, 7.013646840958606, 7.16560600073758, 12.821815536724504, 6.931048605373665, 8.101016313477052, 9.596576061245305, 11.148732590001085), # 123
(10.837500583813984, 8.904899297266184, 10.822930649318243, 12.647132928904783, 12.457698443711445, 6.748646310016486, 6.983572439510783, 7.151921107267111, 12.802237379594539, 6.9071975152271525, 8.074658868426143, 9.56863084286913, 11.122891002412453), # 124
(10.79931321952615, 8.860191444662783, 10.798591942065508, 12.612064631048112, 12.429287250908427, 6.736419917576347, 6.953611416833687, 7.138678176226909, 12.78278727389039, 6.88344379894216, 8.048427141522602, 9.540621390041217, 11.096565536783794), # 125
(10.760558624067514, 8.815588277399392, 10.774001098418278, 12.576704399340064, 12.400234403231872, 6.724194032111481, 6.923709207161124, 7.12582147937411, 12.763406058534501, 6.859737226451811, 8.022262935378736, 9.51249253833592, 11.069719840809094), # 126
(10.721193158505432, 8.771017335915868, 10.749110824786205, 12.540988653053878, 12.370503752173677, 6.711935529021078, 6.893811244726913, 7.113295288465854, 12.744034572449289, 6.836027567689229, 7.9961080526068535, 9.484189123327578, 11.042317562182317), # 127
(10.681173183907255, 8.72640616065208, 10.72387382757894, 12.504853811462798, 12.340059149225747, 6.699611283704333, 6.863862963764858, 7.101043875259275, 12.72461365455718, 6.8122645925875345, 7.969904295819269, 9.455655980590546, 11.014322348597444), # 128
(10.640455061340337, 8.681682292047888, 10.698242813206127, 12.468236293840057, 12.308864445879973, 6.687188171560433, 6.833809798508775, 7.089011511511512, 12.705084143780608, 6.788398071079854, 7.943593467628284, 9.426837945699162, 10.985697847748446), # 129
(10.598995151872039, 8.63677327054316, 10.672170488077414, 12.431072519458903, 12.276883493628256, 6.6746330679885695, 6.803597183192475, 7.077142468979701, 12.685386879042001, 6.764377773099308, 7.9171173706462135, 9.397679854227782, 10.956407707329298), # 130
(10.556749816569713, 8.591606636577751, 10.645609558602457, 12.39329890759257, 12.244080143962494, 6.661912848387936, 6.773170552049771, 7.06538101942098, 12.665462699263783, 6.740153468579022, 7.890417807485361, 9.36812654175075, 10.926415575033973), # 131
(10.51367541650071, 8.546109930591532, 10.618512731190895, 12.354851877514305, 12.210418248374584, 6.648994388157723, 6.7424753393144705, 7.053671434592488, 12.645252443368385, 6.715674927452118, 7.863436580758037, 9.33812284384241, 10.89568509855645), # 132
(10.469728312732395, 8.500210693024362, 10.59083271225238, 12.315667848497341, 12.175861658356423, 6.63584456269712, 6.711456979220387, 7.041957986251359, 12.624696950278231, 6.690891919651718, 7.8361154930765515, 9.307613596077111, 10.864179925590703), # 133
(10.424864866332113, 8.453836464316106, 10.562522208196564, 12.275683239814922, 12.14037422539991, 6.622430247405318, 6.6800609060013345, 7.0301849461547326, 12.603737058915753, 6.665754215110948, 7.808396347053214, 9.2765436340292, 10.831863703830699), # 134
(10.379041438367224, 8.406914784906629, 10.53353392543309, 12.234834470740294, 12.103919800996945, 6.60871831768151, 6.648232553891121, 7.018296586059743, 12.582313608203375, 6.640211583762931, 7.78022094530033, 9.244857793273022, 10.798700080970423), # 135
(10.332214389905081, 8.35937319523579, 10.50382057037161, 12.193057960546687, 12.066462236639419, 6.594675648924887, 6.615917357123561, 7.0062371777235315, 12.560367437063528, 6.6142137955407865, 7.751531090430213, 9.212500909382928, 10.764652704703844), # 136
(10.28434008201304, 8.311139235743456, 10.473334849421772, 12.150290128507349, 12.027965383819241, 6.580269116534637, 6.583060749932466, 6.993950992903235, 12.537839384418639, 6.587710620377641, 7.722268585055167, 9.179417817933263, 10.729685222724932), # 137
(10.235374875758456, 8.26214044686949, 10.442029468993221, 12.106467393895516, 11.988393094028302, 6.565465595909957, 6.5496081665516455, 6.981382303355987, 12.514670289191137, 6.560651828206615, 7.692375231787501, 9.145553354498373, 10.693761282727667), # 138
(10.185275132208682, 8.212304369053752, 10.409857135495608, 12.06152617598443, 11.947709218758497, 6.550231962450032, 6.515505041214911, 6.968475380838929, 12.490800990303445, 6.532987188960836, 7.661792833239527, 9.110852354652607, 10.656844532406023), # 139
(10.133997212431076, 8.16155854273611, 10.376770555338585, 12.015402894047332, 11.905877609501735, 6.534535091554055, 6.480696808156076, 6.955174497109195, 12.466172326677999, 6.5046664725734225, 7.630463192023552, 9.07525965397031, 10.618898619453978), # 140
(10.081497477492995, 8.109830508356424, 10.342722434931792, 11.968033967357464, 11.862862117749904, 6.518341858621218, 6.445128901608954, 6.9414239239239235, 12.440725137237216, 6.4756394489775015, 7.598328110751885, 9.03872008802583, 10.579887191565495), # 141
(10.027732288461786, 8.057047806354559, 10.307665480684884, 11.919355815188064, 11.818626594994903, 6.501619139050712, 6.408746755807351, 6.927167933040253, 12.41440026090353, 6.445855888106193, 7.565329392036836, 9.001178492393512, 10.539773896434559), # 142
(9.972658006404808, 8.003137977170377, 10.27155239900751, 11.86930485681237, 11.773134892728635, 6.484333808241727, 6.371495804985082, 6.912350796215319, 12.387138536599375, 6.415265559892623, 7.531408838490711, 8.962579702647707, 10.49852238175514), # 143
(9.916230992389421, 7.948028561243743, 10.234335896309313, 11.817817511503627, 11.726350862442994, 6.466452741593456, 6.333321483375959, 6.896916785206259, 12.358880803247171, 6.383818234269912, 7.496508252725821, 8.922868554362758, 10.456096295221217), # 144
(9.858407607482972, 7.891647099014518, 10.195968678999947, 11.764830198535073, 11.67823835562988, 6.4479428145050885, 6.294169225213792, 6.880810171770211, 12.329567899769344, 6.351463681171185, 7.460569437354474, 8.881989883113016, 10.41245928452676), # 145
(9.79914421275282, 7.83392113092257, 10.156403453489059, 11.71027933717995, 11.62876122378119, 6.428770902375816, 6.253984464732396, 6.863975227664311, 12.299140665088327, 6.318151670529565, 7.423534194988978, 8.839888524472823, 10.367574997365741), # 146
(9.73839716926632, 7.774778197407756, 10.115592926186292, 11.654101346711496, 11.577883318388821, 6.4089038806048295, 6.212712636165577, 6.846356224645698, 12.267539938126548, 6.283831972278175, 7.385344328241643, 8.796509314016532, 10.321407081432142), # 147
(9.676122838090825, 7.714145838909944, 10.0734898035013, 11.596232646402955, 11.525568490944673, 6.38830862459132, 6.170299173747152, 6.827897434471509, 12.234706557806435, 6.248454356350137, 7.345941639724779, 8.751797087318483, 10.27391918441993), # 148
(9.612277580293695, 7.651951595868995, 10.030046791843732, 11.536609655527563, 11.471780592940645, 6.366952009734479, 6.126689511710929, 6.80854312889888, 12.200581363050405, 6.211968592678576, 7.3052679320506915, 8.705696679953029, 10.225074954023084), # 149
(9.546817756942277, 7.588123008724775, 9.985216597623232, 11.475168793358565, 11.416483475868631, 6.344800911433499, 6.08182908429072, 6.788237579684948, 12.165105192780901, 6.174324451196612, 7.2632650078316905, 8.658152927494514, 10.174838037935576), # 150
(9.47969972910393, 7.522587617917144, 9.93895192724945, 11.411846479169196, 11.359640991220532, 6.321822205087566, 6.03566332572034, 6.7669250585868514, 12.128218885920345, 6.135471701837373, 7.2198746696800855, 8.609110665517285, 10.123172083851381), # 151
(9.41087985784601, 7.455272963885967, 9.89120548713204, 11.346579132232701, 11.301216990488243, 6.297982766095876, 5.9881376702335976, 6.744549837361729, 12.089863281391164, 6.095360114533979, 7.175038720208185, 8.558514729595691, 10.070040739464476), # 152
(9.340314504235872, 7.386106587071107, 9.841929983680641, 11.279303171822319, 11.241175325163667, 6.273249469857618, 5.939197552064303, 6.721056187766714, 12.049979218115787, 6.053939459219555, 7.128698962028299, 8.506309955304076, 10.015407652468832), # 153
(9.267960029340873, 7.315016027912428, 9.79107812330491, 11.209955017211291, 11.179479846738696, 6.247589191771985, 5.888788405446274, 6.696388381558948, 12.008507535016639, 6.011159505827223, 7.080797197752734, 8.45244117821679, 9.959236470558428), # 154
(9.193772794228362, 7.241928826849794, 9.73860261241449, 11.138471087672853, 11.116094406705235, 6.220968807238165, 5.836855664613313, 6.670490690495563, 11.965389071016153, 5.966970024290105, 7.0312752299938, 8.396853233908178, 9.901490841427231), # 155
(9.117709159965697, 7.166772524323065, 9.684456157419032, 11.06478780248025, 11.050982856555176, 6.193355191655353, 5.7833447637992395, 6.643307386333702, 11.920564665036752, 5.921320784541327, 6.980074861363805, 8.339490957952586, 9.842134412769221), # 156
(9.039725487620235, 7.089474660772107, 9.628591464728181, 10.988841580906724, 10.984109047780422, 6.164715220422736, 5.728201137237862, 6.614782740830498, 11.873975156000865, 5.874161556514009, 6.927137894475059, 8.280299185924363, 9.781130832278372), # 157
(8.957617135686286, 7.008543744926709, 9.568310344682827, 10.907723497981491, 10.912417327045196, 6.133229371580532, 5.6701280651134285, 6.582956342819247, 11.821994509918916, 5.824039099549372, 6.870714903046731, 8.217119477033206, 9.715783031298415), # 158
(8.858744120374082, 6.915678383519373, 9.488085382083584, 10.804772590546143, 10.818229571737954, 6.088427577608523, 5.601855316062859, 6.536656239317259, 11.743712713466573, 5.762737192918494, 6.800900322742793, 8.13763502841973, 9.630513176304232), # 159
(8.741846513885172, 6.810116074248857, 9.386305149547066, 10.67829301249063, 10.699704157616154, 6.0292095552572205, 5.5226924980605405, 6.4747190274328155, 11.636910272674381, 5.689446782235472, 6.716711410331447, 8.040602338665416, 9.523704730672296), # 160
(8.607866465503152, 6.692545041696563, 9.26405636629237, 10.529487004508074, 10.558071749138534, 5.956292689884377, 5.433217735208252, 6.397920639731736, 11.50299572039882, 5.604789831805125, 6.618889985519648, 7.926920962689085, 9.396448853782916), # 161
(8.457746124511628, 6.563653510443886, 9.122425751538595, 10.359556807291591, 10.394563010763845, 5.870394366847746, 5.334009151607771, 6.307037008779842, 11.343377589496363, 5.509388305932277, 6.508177868014344, 7.797490455409552, 9.2498367050164), # 162
(8.292427640194196, 6.424129705072228, 8.962500024504841, 10.16970466153432, 10.210408606950825, 5.772231971505087, 5.22564487136088, 6.20284406714295, 11.159464412823487, 5.40386416892175, 6.38531687752249, 7.653210371745638, 9.084959443753055), # 163
(8.11285316183446, 6.2746618501629845, 8.785365904410211, 9.961132807929381, 10.006839202158226, 5.662522889214155, 5.108703018569359, 6.086117747386882, 10.952664723236667, 5.2888393850783615, 6.251048833751035, 7.494980266616163, 8.902908229373192), # 164
(7.9199648387160195, 6.115938170297558, 8.592110110473802, 9.735043487169902, 9.785085460844789, 5.541984505332703, 4.983761717334986, 5.957633982077455, 10.724387053592375, 5.164935918706936, 6.106115556406933, 7.323699694939943, 8.704774221257123), # 165
(7.714704820122476, 5.948646890057345, 8.383819361914712, 9.492638939949002, 9.546378047469256, 5.41133420521849, 4.851399091759543, 5.818168703780493, 10.476039936747087, 5.0327757341122945, 5.9512588651971345, 7.140268211635801, 8.491648578785155), # 166
(7.498015255337426, 5.773476234023744, 8.161580377952045, 9.235121406959811, 9.291947626490375, 5.27128937422927, 4.712193265944809, 5.668497845061811, 10.209031905557278, 4.892980795599256, 5.787220579828592, 6.94558537162255, 8.264622461337595), # 167
(7.2708382936444735, 5.591114426778154, 7.926479877804897, 8.963693128895455, 9.02302486236689, 5.122567397722799, 4.5667223639925645, 5.509397338487231, 9.924771492879426, 4.746173067472646, 5.614742520008257, 6.740550729819013, 8.024787028294753), # 168
(7.034116084327218, 5.402249692901975, 7.67960458069237, 8.67955634644906, 8.740840419557543, 4.965885661056833, 4.4155645100045895, 5.341643116622574, 9.624667231570005, 4.592974514037284, 5.434566505443081, 6.526063841144007, 7.773233439036942), # 169
(6.78879077666926, 5.207570256976605, 7.422041205833562, 8.383913300313743, 8.44662496252108, 4.8019615495891275, 4.259297828082663, 5.166011112033656, 9.310127654485486, 4.434007099597989, 5.247434355840019, 6.3030242605163505, 7.5110528529444665), # 170
(6.5358045199542, 5.007764343583441, 7.154876472447573, 8.077966231182643, 8.141609155716246, 4.631512448677438, 4.098500442328566, 4.983277257286299, 8.982561294482347, 4.269892788459586, 5.054087890906017, 6.072331542854863, 7.239336429397638), # 171
(6.276099463465638, 4.803520177303883, 6.879197099753504, 7.762917379748876, 7.827023663601784, 4.45525574367952, 3.9337504768440783, 4.794217484946325, 8.643376684417062, 4.101253544926895, 4.855268930348032, 5.834885243078365, 6.959175327776763), # 172
(6.010617756487176, 4.59552598271933, 6.596089806970453, 7.43996898670557, 7.504099150636442, 4.27390881995313, 3.7656260557309795, 4.599607727579548, 8.293982357146106, 3.9287113333047374, 4.651719293873013, 5.59158491610567, 6.671660707462155), # 173
(5.740301548302412, 4.384469984411181, 6.306641313317521, 7.110323292745848, 7.174066281278959, 4.088189062856022, 3.5947053030910503, 4.400223917751792, 7.935786845525956, 3.752888117897936, 4.444180801187913, 5.3433301168556016, 6.37788372783412), # 174
(5.466092988194946, 4.171040406960834, 6.01193833801381, 6.775182538562841, 6.838155719988083, 3.898813857745954, 3.421566343026069, 4.196841988028875, 7.570198682413086, 3.574405863011309, 4.233395271999683, 5.091020400246977, 6.078935548272969), # 175
(5.188934225448382, 3.9559254749496873, 5.713067600278413, 6.43574896484967, 6.497598131222556, 3.7065005899806795, 3.2467872996378175, 3.9902378709766184, 7.1986264006639695, 3.3938865329496806, 4.020104526015276, 4.835555321198615, 5.7759073281590085), # 176
(4.909767409346319, 3.7398134129591414, 5.411115819330436, 6.09322481229946, 6.1536241794411275, 3.511966644917956, 3.0709462970280748, 3.781187499160839, 6.822478533135084, 3.2119520920178695, 3.8050503829416424, 4.5778344346293345, 5.4698902268725496), # 177
(4.629534689172356, 3.5233924455705936, 5.107169714388976, 5.748812321605339, 5.807464529102536, 3.3159294079155393, 2.894621459298621, 3.5704668051473587, 6.443163612682903, 3.0292245045207, 3.588974662485735, 4.318757295457952, 5.161975403793902), # 178
(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), # 179
)
passenger_arriving_acc = (
(7, 5, 3, 9, 2, 1, 2, 2, 4, 0, 1, 0, 0, 7, 6, 3, 5, 4, 1, 3, 2, 3, 2, 1, 0, 0), # 0
(13, 16, 8, 17, 7, 4, 2, 4, 4, 0, 3, 0, 0, 13, 15, 11, 9, 7, 5, 5, 2, 5, 5, 1, 3, 0), # 1
(17, 24, 12, 22, 15, 9, 6, 5, 6, 3, 4, 0, 0, 20, 25, 17, 11, 16, 9, 6, 2, 9, 8, 1, 4, 0), # 2
(24, 31, 14, 29, 20, 12, 7, 6, 8, 5, 6, 0, 0, 26, 28, 22, 13, 22, 13, 12, 3, 13, 11, 1, 4, 0), # 3
(30, 38, 22, 42, 28, 14, 12, 8, 13, 7, 6, 0, 0, 32, 37, 26, 20, 28, 16, 15, 5, 15, 15, 1, 7, 0), # 4
(35, 48, 30, 51, 32, 16, 12, 9, 15, 8, 7, 1, 0, 44, 44, 36, 29, 32, 20, 22, 8, 16, 16, 1, 8, 0), # 5
(44, 59, 38, 60, 40, 20, 15, 10, 21, 8, 9, 1, 0, 56, 49, 42, 36, 36, 23, 25, 10, 16, 20, 3, 9, 0), # 6
(51, 65, 49, 68, 48, 23, 18, 13, 23, 10, 14, 1, 0, 58, 58, 50, 38, 45, 26, 29, 13, 20, 21, 4, 11, 0), # 7
(60, 69, 57, 74, 52, 28, 21, 16, 26, 12, 16, 1, 0, 72, 64, 54, 47, 55, 33, 32, 15, 24, 23, 7, 14, 0), # 8
(76, 82, 64, 85, 61, 32, 22, 19, 30, 13, 16, 1, 0, 80, 72, 59, 48, 63, 39, 35, 18, 27, 28, 7, 14, 0), # 9
(84, 87, 72, 91, 68, 35, 27, 21, 32, 15, 16, 1, 0, 86, 81, 65, 52, 71, 43, 38, 22, 33, 30, 7, 16, 0), # 10
(92, 95, 80, 98, 74, 36, 31, 24, 34, 20, 17, 3, 0, 91, 88, 70, 55, 79, 46, 42, 26, 36, 38, 8, 17, 0), # 11
(105, 103, 86, 113, 79, 38, 35, 27, 38, 20, 20, 5, 0, 101, 97, 75, 63, 85, 52, 46, 27, 36, 40, 9, 17, 0), # 12
(115, 114, 96, 126, 82, 43, 39, 31, 42, 22, 21, 7, 0, 119, 108, 85, 70, 94, 58, 52, 28, 38, 46, 13, 18, 0), # 13
(123, 122, 103, 139, 89, 47, 44, 35, 45, 23, 21, 9, 0, 131, 121, 99, 79, 96, 63, 57, 28, 47, 52, 13, 18, 0), # 14
(132, 134, 111, 150, 97, 52, 48, 38, 53, 23, 22, 9, 0, 141, 133, 102, 85, 107, 71, 62, 28, 50, 57, 13, 20, 0), # 15
(145, 146, 117, 163, 106, 55, 54, 46, 56, 25, 26, 10, 0, 149, 145, 108, 88, 116, 77, 67, 33, 56, 63, 16, 20, 0), # 16
(158, 158, 132, 171, 112, 59, 60, 52, 63, 27, 30, 11, 0, 156, 155, 114, 95, 122, 82, 75, 38, 59, 67, 18, 20, 0), # 17
(171, 168, 141, 186, 124, 63, 63, 54, 68, 28, 30, 12, 0, 161, 165, 122, 98, 134, 82, 77, 41, 61, 69, 20, 23, 0), # 18
(183, 186, 147, 198, 128, 69, 68, 60, 72, 31, 30, 15, 0, 175, 178, 130, 110, 144, 84, 85, 43, 71, 72, 23, 23, 0), # 19
(191, 201, 159, 213, 134, 72, 75, 67, 74, 33, 34, 16, 0, 194, 190, 135, 114, 149, 93, 90, 45, 76, 76, 23, 24, 0), # 20
(202, 209, 168, 221, 144, 74, 78, 72, 79, 35, 34, 19, 0, 206, 202, 144, 120, 157, 96, 96, 46, 84, 81, 26, 24, 0), # 21
(217, 219, 183, 233, 153, 78, 84, 74, 87, 38, 36, 20, 0, 221, 210, 150, 123, 167, 105, 103, 51, 90, 83, 29, 25, 0), # 22
(225, 229, 194, 243, 167, 83, 86, 78, 91, 42, 36, 20, 0, 231, 215, 157, 130, 174, 112, 107, 54, 94, 87, 31, 26, 0), # 23
(235, 241, 205, 254, 171, 89, 90, 82, 94, 44, 38, 22, 0, 243, 224, 168, 135, 180, 118, 113, 57, 101, 89, 35, 27, 0), # 24
(247, 251, 210, 261, 185, 90, 99, 89, 99, 44, 39, 22, 0, 254, 235, 179, 144, 188, 122, 117, 62, 105, 90, 36, 27, 0), # 25
(258, 258, 218, 274, 195, 90, 101, 91, 103, 48, 41, 22, 0, 270, 245, 184, 152, 201, 126, 119, 64, 108, 97, 36, 27, 0), # 26
(275, 276, 230, 283, 211, 95, 106, 98, 107, 51, 41, 22, 0, 277, 259, 192, 162, 211, 128, 123, 71, 114, 101, 37, 28, 0), # 27
(282, 286, 242, 293, 223, 100, 110, 102, 112, 57, 43, 23, 0, 292, 271, 197, 169, 217, 131, 128, 77, 117, 104, 41, 30, 0), # 28
(290, 298, 254, 301, 233, 106, 114, 108, 117, 61, 43, 23, 0, 307, 290, 205, 176, 226, 139, 137, 82, 124, 105, 42, 32, 0), # 29
(300, 306, 266, 311, 241, 111, 118, 117, 120, 63, 45, 24, 0, 321, 304, 211, 181, 237, 143, 142, 85, 132, 109, 46, 32, 0), # 30
(315, 313, 271, 322, 249, 113, 125, 121, 128, 63, 46, 25, 0, 327, 314, 215, 191, 254, 149, 147, 88, 138, 112, 48, 32, 0), # 31
(325, 319, 281, 333, 254, 115, 130, 126, 132, 64, 48, 27, 0, 339, 319, 221, 199, 262, 158, 150, 93, 142, 115, 49, 34, 0), # 32
(335, 327, 291, 352, 261, 120, 134, 126, 137, 66, 50, 27, 0, 347, 330, 227, 203, 274, 165, 155, 97, 147, 118, 54, 34, 0), # 33
(343, 341, 301, 363, 267, 124, 136, 132, 143, 67, 50, 27, 0, 354, 343, 233, 212, 278, 169, 159, 99, 149, 125, 55, 34, 0), # 34
(360, 353, 315, 373, 277, 126, 142, 134, 149, 69, 52, 27, 0, 367, 351, 244, 218, 285, 173, 162, 104, 155, 127, 55, 35, 0), # 35
(372, 367, 329, 380, 287, 130, 150, 139, 155, 74, 54, 28, 0, 378, 356, 252, 224, 290, 182, 168, 108, 162, 131, 59, 36, 0), # 36
(386, 381, 342, 391, 300, 132, 156, 142, 155, 74, 55, 29, 0, 391, 368, 259, 230, 304, 187, 170, 114, 169, 132, 62, 36, 0), # 37
(401, 392, 355, 397, 309, 138, 157, 148, 161, 79, 56, 30, 0, 402, 374, 269, 235, 312, 194, 175, 119, 172, 134, 64, 37, 0), # 38
(410, 408, 360, 408, 314, 142, 161, 150, 163, 79, 59, 30, 0, 420, 391, 273, 241, 320, 203, 182, 121, 178, 140, 66, 39, 0), # 39
(428, 420, 367, 418, 322, 144, 165, 153, 166, 80, 59, 31, 0, 430, 400, 282, 246, 330, 206, 191, 124, 180, 143, 68, 41, 0), # 40
(439, 435, 377, 425, 335, 145, 171, 158, 168, 82, 63, 32, 0, 439, 417, 291, 252, 344, 213, 200, 132, 185, 146, 70, 43, 0), # 41
(451, 440, 390, 440, 346, 147, 174, 161, 173, 86, 65, 32, 0, 452, 436, 298, 260, 358, 217, 209, 135, 190, 149, 71, 46, 0), # 42
(466, 451, 402, 448, 352, 151, 176, 166, 178, 86, 68, 32, 0, 462, 449, 310, 271, 374, 219, 212, 135, 194, 151, 73, 47, 0), # 43
(485, 463, 411, 459, 365, 156, 184, 171, 179, 86, 69, 32, 0, 469, 458, 315, 279, 388, 223, 217, 139, 200, 153, 75, 47, 0), # 44
(497, 475, 424, 471, 378, 162, 189, 175, 185, 90, 69, 33, 0, 478, 468, 323, 284, 405, 230, 220, 142, 207, 159, 75, 48, 0), # 45
(506, 487, 430, 483, 387, 167, 191, 179, 191, 90, 73, 37, 0, 490, 479, 330, 290, 414, 240, 224, 145, 210, 162, 76, 49, 0), # 46
(518, 499, 439, 492, 400, 170, 195, 183, 194, 94, 73, 38, 0, 502, 489, 337, 295, 425, 242, 228, 146, 217, 165, 79, 50, 0), # 47
(533, 515, 447, 504, 409, 171, 200, 188, 202, 97, 75, 40, 0, 510, 500, 348, 303, 440, 247, 231, 148, 223, 167, 79, 51, 0), # 48
(551, 531, 451, 516, 422, 178, 202, 191, 210, 97, 76, 40, 0, 519, 509, 358, 308, 451, 251, 233, 152, 233, 172, 80, 52, 0), # 49
(558, 542, 463, 529, 428, 185, 207, 197, 213, 101, 77, 43, 0, 528, 518, 366, 318, 460, 257, 239, 157, 239, 174, 82, 53, 0), # 50
(573, 549, 471, 546, 436, 192, 210, 202, 219, 105, 79, 43, 0, 544, 525, 382, 329, 473, 262, 242, 160, 241, 181, 84, 53, 0), # 51
(585, 560, 483, 563, 449, 194, 213, 204, 223, 105, 81, 45, 0, 552, 532, 390, 337, 483, 268, 243, 163, 244, 184, 86, 54, 0), # 52
(604, 571, 493, 570, 455, 199, 221, 207, 229, 108, 85, 46, 0, 564, 539, 396, 343, 494, 274, 247, 167, 252, 187, 88, 55, 0), # 53
(618, 586, 503, 580, 464, 205, 228, 210, 232, 111, 85, 46, 0, 574, 541, 407, 346, 502, 281, 253, 168, 257, 191, 90, 56, 0), # 54
(625, 597, 514, 593, 470, 208, 234, 217, 235, 113, 86, 46, 0, 587, 552, 419, 353, 511, 288, 260, 173, 259, 194, 91, 57, 0), # 55
(637, 606, 528, 606, 474, 211, 237, 219, 239, 114, 87, 47, 0, 605, 568, 431, 359, 520, 298, 266, 177, 264, 198, 92, 57, 0), # 56
(649, 615, 537, 614, 481, 214, 246, 221, 242, 117, 89, 49, 0, 608, 584, 437, 368, 524, 311, 270, 178, 266, 200, 94, 58, 0), # 57
(661, 625, 549, 622, 486, 217, 249, 229, 247, 121, 89, 49, 0, 617, 600, 439, 373, 531, 319, 274, 180, 268, 204, 96, 59, 0), # 58
(672, 637, 560, 629, 492, 221, 257, 231, 250, 121, 89, 49, 0, 631, 611, 445, 379, 543, 322, 279, 184, 271, 210, 101, 61, 0), # 59
(685, 647, 566, 642, 500, 225, 260, 237, 255, 124, 90, 51, 0, 638, 623, 452, 388, 558, 325, 282, 184, 276, 214, 104, 62, 0), # 60
(702, 658, 578, 653, 509, 229, 263, 241, 259, 127, 95, 51, 0, 648, 631, 462, 395, 573, 333, 283, 188, 282, 217, 105, 62, 0), # 61
(714, 669, 586, 663, 515, 234, 266, 242, 268, 130, 96, 51, 0, 660, 645, 466, 401, 584, 340, 288, 191, 284, 220, 105, 62, 0), # 62
(727, 677, 593, 680, 527, 236, 269, 245, 272, 130, 96, 52, 0, 675, 660, 470, 409, 589, 345, 291, 194, 285, 222, 110, 63, 0), # 63
(740, 689, 601, 696, 534, 237, 274, 247, 274, 133, 98, 52, 0, 684, 672, 478, 417, 594, 351, 293, 198, 287, 223, 114, 64, 0), # 64
(749, 707, 613, 704, 538, 239, 277, 250, 275, 135, 100, 53, 0, 692, 681, 484, 428, 603, 355, 295, 201, 294, 225, 117, 65, 0), # 65
(766, 716, 619, 713, 554, 242, 279, 254, 281, 140, 101, 53, 0, 703, 691, 490, 434, 611, 360, 300, 203, 299, 228, 118, 65, 0), # 66
(779, 724, 630, 721, 561, 249, 284, 254, 285, 143, 102, 53, 0, 717, 709, 495, 439, 624, 364, 303, 206, 308, 233, 120, 65, 0), # 67
(793, 733, 641, 728, 566, 254, 287, 256, 289, 145, 104, 54, 0, 733, 718, 499, 445, 630, 368, 312, 208, 312, 235, 120, 65, 0), # 68
(804, 748, 651, 738, 571, 261, 289, 257, 292, 145, 106, 54, 0, 747, 732, 502, 451, 640, 378, 317, 211, 318, 238, 120, 66, 0), # 69
(816, 757, 661, 746, 582, 266, 293, 259, 297, 146, 108, 55, 0, 753, 737, 510, 458, 655, 387, 320, 213, 327, 250, 121, 66, 0), # 70
(834, 772, 676, 759, 591, 269, 298, 262, 302, 147, 109, 56, 0, 763, 745, 514, 469, 659, 391, 325, 216, 335, 254, 121, 67, 0), # 71
(849, 781, 689, 771, 599, 279, 302, 266, 308, 149, 110, 57, 0, 779, 753, 518, 477, 668, 393, 327, 218, 340, 254, 121, 67, 0), # 72
(862, 796, 704, 777, 608, 285, 305, 271, 310, 149, 113, 59, 0, 791, 758, 526, 481, 686, 397, 336, 222, 345, 259, 123, 67, 0), # 73
(878, 808, 715, 787, 619, 290, 307, 276, 314, 152, 114, 62, 0, 803, 769, 531, 486, 699, 400, 339, 226, 349, 262, 127, 68, 0), # 74
(897, 818, 724, 792, 621, 291, 310, 279, 320, 153, 115, 62, 0, 813, 774, 541, 487, 713, 402, 342, 231, 352, 268, 129, 70, 0), # 75
(916, 825, 731, 803, 631, 297, 313, 287, 328, 154, 118, 63, 0, 828, 786, 543, 490, 721, 407, 345, 234, 354, 274, 131, 71, 0), # 76
(922, 834, 743, 813, 644, 301, 321, 288, 331, 157, 119, 64, 0, 841, 796, 548, 495, 730, 411, 349, 238, 360, 280, 134, 72, 0), # 77
(934, 847, 756, 827, 657, 303, 326, 291, 342, 158, 121, 64, 0, 855, 809, 553, 499, 741, 416, 351, 238, 361, 282, 135, 74, 0), # 78
(941, 855, 761, 837, 668, 304, 330, 292, 345, 159, 122, 66, 0, 871, 822, 561, 503, 748, 420, 354, 239, 365, 283, 137, 76, 0), # 79
(958, 861, 770, 846, 676, 310, 332, 296, 349, 162, 125, 66, 0, 884, 831, 574, 506, 758, 428, 360, 240, 366, 287, 140, 77, 0), # 80
(969, 877, 776, 859, 682, 317, 334, 298, 354, 162, 126, 67, 0, 893, 840, 584, 509, 772, 431, 362, 243, 372, 291, 142, 78, 0), # 81
(985, 889, 791, 873, 690, 320, 340, 298, 358, 164, 128, 67, 0, 908, 853, 589, 514, 782, 433, 369, 244, 377, 293, 144, 78, 0), # 82
(999, 904, 806, 885, 695, 323, 343, 301, 360, 169, 131, 68, 0, 917, 857, 598, 522, 791, 439, 374, 246, 382, 294, 147, 80, 0), # 83
(1014, 918, 815, 894, 704, 324, 349, 305, 365, 170, 134, 68, 0, 933, 867, 606, 532, 797, 444, 379, 250, 385, 300, 147, 80, 0), # 84
(1017, 930, 826, 903, 719, 326, 356, 312, 369, 171, 136, 68, 0, 944, 874, 612, 547, 804, 451, 381, 253, 387, 303, 148, 80, 0), # 85
(1029, 939, 833, 917, 734, 330, 359, 317, 376, 172, 136, 68, 0, 957, 887, 626, 553, 818, 452, 384, 255, 392, 305, 150, 81, 0), # 86
(1043, 949, 844, 921, 742, 332, 364, 321, 383, 175, 138, 68, 0, 967, 898, 636, 564, 827, 455, 392, 257, 398, 311, 151, 82, 0), # 87
(1052, 955, 855, 934, 751, 342, 368, 324, 387, 178, 141, 68, 0, 979, 906, 645, 567, 838, 463, 399, 257, 403, 317, 155, 84, 0), # 88
(1070, 964, 862, 942, 758, 349, 371, 329, 392, 179, 142, 68, 0, 991, 921, 653, 569, 849, 467, 404, 259, 409, 325, 156, 86, 0), # 89
(1081, 971, 871, 953, 766, 353, 373, 333, 393, 181, 144, 68, 0, 1004, 933, 663, 577, 857, 472, 407, 267, 413, 330, 159, 90, 0), # 90
(1099, 981, 881, 961, 774, 356, 376, 334, 397, 184, 144, 68, 0, 1014, 943, 667, 583, 864, 477, 407, 269, 421, 333, 160, 90, 0), # 91
(1110, 995, 887, 968, 783, 367, 380, 334, 399, 187, 146, 68, 0, 1020, 956, 677, 586, 869, 479, 412, 271, 424, 333, 160, 91, 0), # 92
(1119, 1007, 896, 976, 792, 370, 384, 338, 407, 189, 147, 68, 0, 1036, 969, 687, 591, 877, 485, 415, 274, 429, 335, 162, 93, 0), # 93
(1131, 1018, 909, 989, 803, 371, 387, 340, 414, 194, 148, 70, 0, 1049, 974, 696, 598, 880, 487, 423, 277, 433, 337, 162, 95, 0), # 94
(1137, 1025, 920, 1001, 814, 372, 391, 343, 415, 197, 148, 71, 0, 1059, 978, 699, 600, 889, 491, 425, 284, 440, 340, 163, 97, 0), # 95
(1146, 1035, 931, 1009, 821, 374, 398, 344, 420, 197, 150, 71, 0, 1071, 987, 705, 606, 896, 496, 428, 287, 442, 342, 166, 97, 0), # 96
(1156, 1046, 941, 1019, 828, 379, 404, 349, 425, 199, 152, 71, 0, 1082, 993, 719, 608, 905, 499, 435, 295, 447, 348, 166, 97, 0), # 97
(1164, 1053, 949, 1033, 836, 380, 409, 351, 428, 205, 154, 71, 0, 1091, 1002, 727, 614, 910, 501, 441, 298, 451, 352, 170, 98, 0), # 98
(1174, 1066, 960, 1047, 849, 385, 414, 354, 433, 205, 155, 71, 0, 1100, 1009, 731, 623, 921, 504, 448, 301, 458, 354, 172, 98, 0), # 99
(1186, 1078, 972, 1063, 857, 387, 414, 354, 435, 206, 156, 72, 0, 1111, 1017, 742, 626, 930, 507, 451, 303, 462, 356, 175, 99, 0), # 100
(1196, 1089, 982, 1070, 867, 388, 418, 355, 438, 209, 157, 73, 0, 1126, 1028, 755, 633, 940, 511, 455, 305, 466, 360, 177, 99, 0), # 101
(1208, 1104, 991, 1081, 880, 395, 421, 359, 441, 212, 158, 75, 0, 1132, 1043, 760, 638, 951, 515, 458, 307, 470, 361, 179, 99, 0), # 102
(1220, 1115, 995, 1085, 886, 400, 425, 363, 446, 213, 160, 75, 0, 1143, 1049, 774, 642, 956, 520, 461, 310, 472, 361, 180, 100, 0), # 103
(1239, 1122, 1006, 1096, 897, 402, 427, 364, 447, 214, 162, 77, 0, 1156, 1057, 781, 645, 969, 526, 465, 314, 481, 362, 181, 100, 0), # 104
(1252, 1135, 1017, 1108, 908, 408, 428, 366, 451, 214, 162, 77, 0, 1165, 1067, 785, 652, 976, 526, 467, 316, 486, 366, 181, 100, 0), # 105
(1264, 1149, 1027, 1119, 915, 413, 431, 372, 455, 217, 166, 77, 0, 1175, 1075, 791, 656, 980, 526, 472, 317, 493, 366, 186, 101, 0), # 106
(1273, 1157, 1037, 1127, 922, 417, 439, 372, 462, 218, 168, 79, 0, 1188, 1088, 798, 662, 992, 535, 474, 318, 494, 370, 189, 102, 0), # 107
(1283, 1170, 1043, 1135, 928, 421, 443, 374, 466, 219, 169, 79, 0, 1199, 1094, 805, 669, 1000, 539, 481, 323, 498, 375, 193, 103, 0), # 108
(1301, 1179, 1055, 1146, 934, 423, 449, 379, 473, 220, 172, 79, 0, 1210, 1098, 811, 673, 1013, 545, 482, 324, 502, 379, 194, 103, 0), # 109
(1310, 1188, 1069, 1150, 947, 428, 453, 380, 479, 224, 174, 80, 0, 1225, 1106, 819, 679, 1021, 550, 482, 327, 508, 384, 194, 104, 0), # 110
(1318, 1199, 1075, 1155, 955, 429, 455, 384, 483, 226, 175, 80, 0, 1242, 1117, 828, 682, 1029, 557, 489, 332, 512, 389, 195, 105, 0), # 111
(1329, 1202, 1083, 1166, 966, 434, 457, 388, 489, 226, 176, 80, 0, 1247, 1124, 836, 689, 1040, 559, 492, 335, 515, 394, 196, 106, 0), # 112
(1345, 1208, 1090, 1171, 977, 442, 459, 392, 493, 228, 177, 81, 0, 1252, 1133, 844, 698, 1046, 562, 498, 336, 522, 399, 199, 106, 0), # 113
(1361, 1213, 1105, 1184, 984, 444, 465, 396, 500, 229, 177, 82, 0, 1261, 1144, 852, 704, 1054, 567, 503, 338, 526, 401, 200, 106, 0), # 114
(1370, 1220, 1113, 1192, 994, 451, 467, 398, 506, 231, 179, 83, 0, 1272, 1152, 854, 711, 1062, 570, 503, 341, 532, 405, 200, 106, 0), # 115
(1382, 1226, 1120, 1207, 1005, 457, 473, 399, 509, 231, 179, 84, 0, 1281, 1172, 862, 721, 1072, 575, 504, 343, 535, 407, 203, 106, 0), # 116
(1400, 1238, 1128, 1216, 1017, 459, 474, 401, 514, 232, 179, 84, 0, 1289, 1183, 871, 728, 1081, 578, 505, 347, 539, 413, 206, 107, 0), # 117
(1412, 1245, 1137, 1227, 1022, 461, 480, 404, 516, 235, 181, 85, 0, 1303, 1192, 877, 731, 1090, 584, 507, 350, 544, 417, 207, 108, 0), # 118
(1426, 1260, 1142, 1231, 1032, 467, 483, 405, 521, 235, 182, 87, 0, 1319, 1202, 883, 733, 1098, 586, 509, 354, 546, 418, 210, 109, 0), # 119
(1442, 1269, 1148, 1239, 1041, 470, 488, 411, 525, 238, 185, 88, 0, 1327, 1212, 889, 735, 1104, 592, 510, 354, 550, 424, 211, 110, 0), # 120
(1456, 1275, 1162, 1251, 1047, 474, 493, 413, 529, 240, 188, 91, 0, 1340, 1218, 892, 738, 1112, 594, 511, 355, 555, 426, 212, 111, 0), # 121
(1472, 1283, 1173, 1267, 1058, 478, 496, 416, 533, 244, 189, 92, 0, 1348, 1229, 896, 745, 1116, 600, 514, 357, 558, 426, 213, 112, 0), # 122
(1481, 1293, 1187, 1276, 1069, 480, 498, 416, 541, 246, 190, 92, 0, 1361, 1233, 905, 749, 1122, 607, 519, 359, 564, 430, 215, 113, 0), # 123
(1491, 1304, 1199, 1287, 1074, 487, 500, 417, 546, 248, 193, 92, 0, 1378, 1238, 910, 753, 1131, 608, 519, 364, 574, 432, 217, 114, 0), # 124
(1498, 1316, 1210, 1294, 1076, 494, 502, 421, 551, 249, 197, 92, 0, 1388, 1247, 917, 758, 1140, 613, 523, 370, 577, 435, 218, 114, 0), # 125
(1505, 1321, 1217, 1303, 1083, 497, 504, 423, 556, 250, 203, 92, 0, 1402, 1262, 922, 761, 1144, 620, 525, 371, 579, 436, 218, 114, 0), # 126
(1520, 1331, 1229, 1314, 1091, 503, 506, 426, 563, 250, 203, 92, 0, 1411, 1264, 928, 765, 1155, 629, 529, 373, 581, 442, 221, 115, 0), # 127
(1533, 1339, 1237, 1327, 1099, 507, 514, 427, 569, 251, 204, 92, 0, 1421, 1271, 935, 767, 1158, 633, 533, 377, 584, 443, 225, 117, 0), # 128
(1546, 1345, 1249, 1332, 1107, 508, 516, 428, 574, 251, 208, 92, 0, 1432, 1281, 942, 770, 1167, 637, 538, 380, 586, 444, 225, 118, 0), # 129
(1563, 1350, 1255, 1338, 1115, 511, 521, 431, 578, 252, 209, 92, 0, 1443, 1292, 946, 775, 1177, 642, 544, 382, 589, 451, 227, 118, 0), # 130
(1573, 1355, 1262, 1347, 1126, 515, 522, 436, 584, 253, 210, 92, 0, 1450, 1297, 955, 784, 1192, 645, 548, 385, 594, 454, 228, 119, 0), # 131
(1587, 1362, 1272, 1359, 1133, 516, 523, 440, 586, 256, 212, 93, 0, 1461, 1305, 962, 791, 1201, 650, 550, 385, 595, 457, 230, 119, 0), # 132
(1597, 1369, 1284, 1371, 1142, 524, 527, 443, 588, 256, 212, 95, 0, 1471, 1310, 971, 798, 1215, 661, 556, 392, 601, 459, 233, 121, 0), # 133
(1611, 1381, 1299, 1382, 1153, 529, 530, 447, 593, 256, 213, 97, 0, 1480, 1318, 979, 803, 1223, 665, 560, 393, 606, 462, 236, 121, 0), # 134
(1618, 1389, 1309, 1391, 1162, 533, 532, 449, 600, 258, 215, 97, 0, 1499, 1325, 985, 809, 1228, 668, 563, 396, 609, 464, 239, 122, 0), # 135
(1633, 1399, 1320, 1401, 1172, 539, 535, 453, 604, 259, 217, 98, 0, 1511, 1331, 995, 812, 1234, 669, 566, 400, 612, 465, 239, 123, 0), # 136
(1644, 1406, 1329, 1407, 1183, 541, 539, 457, 607, 260, 217, 99, 0, 1520, 1342, 998, 815, 1235, 671, 569, 403, 615, 466, 240, 123, 0), # 137
(1651, 1412, 1333, 1413, 1193, 549, 545, 457, 612, 263, 217, 100, 0, 1538, 1358, 1007, 825, 1240, 676, 573, 405, 623, 472, 241, 123, 0), # 138
(1663, 1420, 1343, 1423, 1200, 551, 551, 461, 616, 264, 218, 101, 0, 1551, 1369, 1019, 833, 1254, 682, 576, 410, 628, 473, 242, 124, 0), # 139
(1675, 1434, 1351, 1432, 1210, 554, 555, 463, 620, 266, 221, 102, 0, 1559, 1378, 1022, 840, 1259, 685, 579, 415, 630, 475, 242, 124, 0), # 140
(1678, 1442, 1361, 1435, 1222, 558, 560, 465, 628, 268, 222, 102, 0, 1566, 1387, 1034, 846, 1270, 690, 579, 416, 633, 475, 242, 125, 0), # 141
(1686, 1452, 1373, 1447, 1228, 559, 564, 469, 630, 271, 223, 103, 0, 1578, 1394, 1039, 850, 1278, 693, 585, 416, 635, 478, 243, 128, 0), # 142
(1698, 1463, 1385, 1456, 1237, 562, 565, 472, 633, 272, 223, 103, 0, 1584, 1398, 1045, 858, 1281, 695, 589, 419, 637, 480, 244, 128, 0), # 143
(1703, 1470, 1397, 1466, 1246, 567, 567, 475, 635, 274, 223, 104, 0, 1596, 1403, 1051, 859, 1284, 701, 594, 420, 640, 483, 244, 128, 0), # 144
(1710, 1483, 1406, 1478, 1257, 572, 574, 481, 641, 274, 226, 106, 0, 1603, 1410, 1062, 864, 1292, 703, 601, 421, 644, 486, 247, 128, 0), # 145
(1723, 1489, 1416, 1488, 1265, 575, 576, 484, 649, 277, 227, 107, 0, 1612, 1421, 1066, 868, 1300, 708, 605, 421, 647, 488, 248, 129, 0), # 146
(1739, 1498, 1421, 1505, 1276, 577, 578, 488, 652, 278, 228, 108, 0, 1620, 1427, 1070, 873, 1304, 712, 609, 426, 647, 490, 249, 129, 0), # 147
(1749, 1504, 1431, 1510, 1289, 581, 578, 493, 659, 278, 230, 108, 0, 1631, 1433, 1077, 876, 1311, 713, 615, 428, 654, 494, 249, 129, 0), # 148
(1765, 1508, 1439, 1523, 1293, 583, 579, 498, 664, 282, 230, 108, 0, 1645, 1440, 1085, 880, 1322, 719, 617, 432, 655, 499, 252, 129, 0), # 149
(1779, 1518, 1447, 1531, 1297, 588, 583, 502, 670, 284, 230, 111, 0, 1653, 1447, 1087, 885, 1332, 723, 619, 434, 657, 502, 254, 131, 0), # 150
(1789, 1525, 1455, 1539, 1302, 591, 586, 504, 674, 286, 231, 111, 0, 1666, 1454, 1094, 888, 1340, 723, 621, 436, 661, 505, 254, 132, 0), # 151
(1798, 1529, 1464, 1544, 1309, 593, 591, 507, 678, 287, 232, 113, 0, 1674, 1459, 1100, 892, 1354, 727, 623, 438, 664, 510, 258, 133, 0), # 152
(1805, 1533, 1473, 1552, 1319, 596, 594, 507, 682, 288, 233, 114, 0, 1686, 1469, 1106, 899, 1356, 730, 627, 438, 670, 512, 259, 133, 0), # 153
(1819, 1541, 1482, 1555, 1326, 601, 594, 508, 684, 288, 234, 114, 0, 1701, 1475, 1110, 905, 1367, 732, 632, 440, 671, 514, 262, 133, 0), # 154
(1830, 1546, 1491, 1560, 1332, 605, 595, 511, 689, 288, 236, 114, 0, 1709, 1483, 1121, 913, 1372, 735, 638, 442, 673, 514, 263, 133, 0), # 155
(1838, 1549, 1496, 1564, 1343, 611, 596, 513, 691, 288, 241, 115, 0, 1717, 1487, 1125, 915, 1385, 738, 641, 443, 675, 514, 263, 135, 0), # 156
(1851, 1559, 1505, 1573, 1349, 613, 598, 515, 695, 289, 242, 115, 0, 1731, 1497, 1128, 919, 1396, 739, 647, 446, 680, 516, 264, 136, 0), # 157
(1858, 1562, 1507, 1578, 1355, 615, 599, 516, 696, 290, 242, 115, 0, 1742, 1504, 1133, 923, 1408, 741, 651, 448, 683, 518, 268, 136, 0), # 158
(1869, 1568, 1515, 1587, 1361, 619, 604, 517, 701, 291, 244, 115, 0, 1749, 1515, 1140, 930, 1417, 744, 654, 448, 686, 518, 268, 139, 0), # 159
(1880, 1571, 1519, 1593, 1367, 621, 605, 519, 705, 295, 246, 118, 0, 1755, 1523, 1145, 933, 1422, 748, 655, 448, 689, 519, 270, 140, 0), # 160
(1889, 1577, 1526, 1600, 1372, 628, 610, 525, 707, 295, 247, 118, 0, 1769, 1531, 1148, 936, 1428, 751, 656, 450, 691, 522, 271, 142, 0), # 161
(1897, 1586, 1530, 1608, 1376, 631, 614, 527, 710, 297, 248, 118, 0, 1776, 1539, 1149, 939, 1438, 756, 656, 454, 694, 528, 271, 143, 0), # 162
(1904, 1591, 1538, 1616, 1382, 632, 616, 533, 713, 299, 248, 119, 0, 1783, 1548, 1153, 943, 1453, 761, 659, 459, 697, 531, 275, 143, 0), # 163
(1914, 1595, 1549, 1622, 1390, 634, 620, 537, 717, 300, 250, 119, 0, 1793, 1551, 1163, 946, 1458, 767, 663, 463, 700, 533, 278, 143, 0), # 164
(1922, 1600, 1555, 1632, 1395, 637, 622, 538, 721, 301, 253, 119, 0, 1800, 1559, 1166, 950, 1469, 770, 665, 464, 701, 537, 280, 143, 0), # 165
(1930, 1609, 1564, 1639, 1397, 638, 622, 539, 725, 302, 253, 120, 0, 1809, 1567, 1174, 953, 1475, 773, 668, 466, 704, 538, 283, 143, 0), # 166
(1938, 1614, 1568, 1645, 1408, 642, 623, 544, 727, 303, 255, 120, 0, 1815, 1574, 1178, 959, 1481, 773, 670, 469, 710, 541, 284, 143, 0), # 167
(1940, 1618, 1574, 1653, 1415, 646, 627, 547, 732, 304, 255, 120, 0, 1822, 1583, 1180, 963, 1485, 775, 673, 474, 710, 542, 284, 143, 0), # 168
(1945, 1621, 1583, 1660, 1421, 649, 631, 551, 733, 306, 255, 122, 0, 1825, 1590, 1183, 970, 1493, 781, 674, 477, 712, 544, 287, 144, 0), # 169
(1950, 1624, 1587, 1664, 1426, 651, 631, 553, 736, 307, 255, 122, 0, 1834, 1596, 1193, 971, 1506, 782, 675, 481, 715, 546, 288, 145, 0), # 170
(1952, 1626, 1591, 1667, 1433, 652, 633, 557, 739, 308, 256, 122, 0, 1841, 1599, 1197, 974, 1515, 786, 681, 481, 718, 548, 290, 146, 0), # 171
(1956, 1632, 1599, 1673, 1439, 657, 635, 559, 740, 310, 256, 123, 0, 1846, 1603, 1205, 975, 1519, 789, 686, 485, 720, 550, 291, 146, 0), # 172
(1964, 1638, 1604, 1679, 1445, 663, 642, 560, 741, 312, 256, 123, 0, 1852, 1608, 1211, 978, 1524, 794, 687, 486, 722, 553, 292, 147, 0), # 173
(1970, 1642, 1610, 1687, 1449, 666, 644, 560, 744, 314, 256, 123, 0, 1854, 1614, 1213, 985, 1526, 797, 689, 486, 725, 558, 292, 147, 0), # 174
(1972, 1645, 1613, 1692, 1456, 668, 644, 561, 749, 316, 257, 123, 0, 1859, 1619, 1220, 987, 1529, 798, 690, 487, 729, 560, 293, 147, 0), # 175
(1976, 1647, 1616, 1694, 1459, 672, 646, 563, 751, 317, 259, 123, 0, 1861, 1623, 1223, 987, 1536, 798, 690, 488, 731, 562, 294, 147, 0), # 176
(1982, 1649, 1618, 1701, 1462, 675, 648, 565, 753, 317, 259, 124, 0, 1866, 1624, 1229, 990, 1545, 799, 691, 489, 735, 565, 295, 148, 0), # 177
(1987, 1651, 1621, 1708, 1470, 678, 649, 567, 755, 318, 260, 124, 0, 1869, 1628, 1232, 991, 1549, 801, 691, 490, 737, 565, 295, 148, 0), # 178
(1987, 1651, 1621, 1708, 1470, 678, 649, 567, 755, 318, 260, 124, 0, 1869, 1628, 1232, 991, 1549, 801, 691, 490, 737, 565, 295, 148, 0), # 179
)
passenger_arriving_rate = (
(6.025038694046121, 6.077817415662483, 5.211283229612507, 5.593200996477089, 4.443748486087689, 2.197058452426137, 2.4876213692243487, 2.3265880864897115, 2.4360396248672025, 1.187404504656711, 0.8410530327771206, 0.4897915078306174, 0.0, 6.100656255094035, 5.38770658613679, 4.205265163885603, 3.562213513970132, 4.872079249734405, 3.257223321085596, 2.4876213692243487, 1.5693274660186693, 2.2218742430438443, 1.8644003321590301, 1.0422566459225016, 0.5525288559693167, 0.0), # 0
(6.425192582423969, 6.479066763559234, 5.555346591330152, 5.9626298279489545, 4.737992269979389, 2.342188508829789, 2.651681364758216, 2.479756861452854, 2.5968981305331633, 1.265694207683145, 0.8966192271912263, 0.5221216660814355, 0.0, 6.503749976927826, 5.743338326895789, 4.483096135956131, 3.7970826230494343, 5.193796261066327, 3.4716596060339957, 2.651681364758216, 1.6729917920212778, 2.3689961349896946, 1.9875432759829852, 1.1110693182660305, 0.589006069414476, 0.0), # 1
(6.8240676107756775, 6.878723687980077, 5.8980422855474135, 6.330588934198314, 5.031170378999795, 2.4867395801587113, 2.8150911047764224, 2.6323126239522097, 2.7571147227510195, 1.3436741325061639, 0.9519646297552626, 0.5543232652053055, 0.0, 6.905237793851628, 6.09755591725836, 4.759823148776313, 4.031022397518491, 5.514229445502039, 3.6852376735330936, 2.8150911047764224, 1.7762425572562224, 2.5155851894998973, 2.1101963113994384, 1.179608457109483, 0.625338517089098, 0.0), # 2
(7.220109351775874, 7.275202552130091, 6.238010869319854, 6.695618766778866, 5.322129340801521, 2.6301384358095787, 2.9772021849887733, 2.7836505787472534, 2.9160540643684367, 1.4210348095278544, 1.0068696823654766, 0.5862685684930461, 0.0, 7.30352736750507, 6.448954253423507, 5.0343484118273825, 4.263104428583563, 5.8321081287368735, 3.8971108102461547, 2.9772021849887733, 1.8786703112925562, 2.6610646704007603, 2.2318729222596225, 1.247602173863971, 0.6613820501936447, 0.0), # 3
(7.611763378099177, 7.666917719214351, 6.573892899703036, 7.056259777244312, 5.609715683037193, 2.7718118451790676, 3.137366201105075, 2.9331659305974576, 3.0730808182330827, 1.4974667691503039, 1.0611148269181152, 0.6178298392354764, 0.0, 7.69702635952778, 6.79612823159024, 5.305574134590575, 4.492400307450911, 6.146161636466165, 4.10643230283644, 3.137366201105075, 1.9798656036993338, 2.8048578415185963, 2.3520865924147714, 1.3147785799406073, 0.6969925199285775, 0.0), # 4
(7.9974752624202115, 8.052283552437947, 6.904328933752518, 7.411052417148355, 5.892775933359424, 2.9111865776638504, 3.2949347488351344, 3.080253884262296, 3.2275596471926233, 1.5726605417755992, 1.1144805053094267, 0.6488793407234149, 0.0, 8.084142431559393, 7.137672747957563, 5.572402526547132, 4.7179816253267965, 6.455119294385247, 4.312355437967215, 3.2949347488351344, 2.079418984045607, 2.946387966679712, 2.4703508057161185, 1.3808657867505036, 0.7320257774943589, 0.0), # 5
(8.375690577413598, 8.42971441500595, 7.227959528523866, 7.758537138044686, 6.170156619420834, 3.047689402660605, 3.4492594238887575, 3.2243096445012442, 3.3788552140947257, 1.6463066578058279, 1.1667471594356567, 0.6792893362476808, 0.0, 8.463283245239527, 7.472182698724488, 5.833735797178282, 4.938919973417482, 6.757710428189451, 4.514033502301742, 3.4492594238887575, 2.176921001900432, 3.085078309710417, 2.586179046014896, 1.4455919057047733, 0.7663376740914501, 0.0), # 6
(8.744854895753962, 8.797624670123444, 7.543425241072636, 8.097254391487015, 6.440704268874043, 3.1807470895660046, 3.599691821975751, 3.3647284160737763, 3.5263321817870574, 1.7180956476430762, 1.2176952311930538, 0.708932089099093, 0.0, 8.832856462207822, 7.798252980090021, 6.088476155965268, 5.154286942929227, 7.052664363574115, 4.7106197825032865, 3.599691821975751, 2.2719622068328604, 3.2203521344370216, 2.699084797162339, 1.508685048214527, 0.7997840609203132, 0.0), # 7
(9.103413790115921, 9.154428680995508, 7.849366628454395, 8.425744629029035, 6.703265409371668, 3.309786407776723, 3.7455835388059184, 3.5009054037393623, 3.669355213117282, 1.7877180416894325, 1.2671051624778642, 0.7376798625684703, 0.0, 9.1912697441039, 8.114478488253173, 6.335525812389321, 5.363154125068296, 7.338710426234564, 4.901267565235107, 3.7455835388059184, 2.3641331484119448, 3.351632704685834, 2.8085815430096788, 1.5698733256908792, 0.8322207891814098, 0.0), # 8
(9.449812833174102, 9.498540810827224, 8.144424247724704, 8.742548302224453, 6.956686568566327, 3.4342341266894385, 3.886286170089072, 3.6322358122574814, 3.8072889709330693, 1.8548643703469827, 1.3147573951863356, 0.7654049199466314, 0.0, 9.536930752567395, 8.419454119412945, 6.573786975931678, 5.564593111040947, 7.614577941866139, 5.0851301371604745, 3.886286170089072, 2.453024376206742, 3.4783432842831634, 2.914182767408151, 1.6288848495449408, 0.8635037100752023, 0.0), # 9
(9.782497597603118, 9.828375422823667, 8.427238655939124, 9.046205862626959, 7.19981427411064, 3.5535170157008253, 4.021151311535013, 3.7581148463876053, 3.9394981180820854, 1.9192251640178146, 1.3604323712147148, 0.7919795245243952, 0.0, 9.868247149237932, 8.711774769768347, 6.802161856073574, 5.757675492053442, 7.878996236164171, 5.261360784942648, 4.021151311535013, 2.5382264397863037, 3.59990713705532, 3.015401954208987, 1.685447731187825, 0.8934886748021517, 0.0), # 10
(10.099913656077605, 10.142346880189926, 8.696450410153215, 9.335257761790256, 7.431495053657226, 3.667061844207558, 4.14953055885355, 3.8779377108892072, 4.065347317411997, 1.980490953104016, 1.40391053245925, 0.8172759395925812, 0.0, 10.183626595755133, 8.99003533551839, 7.019552662296249, 5.9414728593120465, 8.130694634823994, 5.42911279524489, 4.14953055885355, 2.619329888719684, 3.715747526828613, 3.1117525872634197, 1.7392900820306432, 0.9220315345627208, 0.0), # 11
(10.400506581272174, 10.438869546131066, 8.95070006742254, 9.60824445126805, 7.650575434858702, 3.7742953816063087, 4.270775507754487, 3.99109961052176, 4.184201231770471, 2.0383522680076718, 1.444972320816187, 0.8411664284420068, 0.0, 10.48147675375864, 9.252830712862075, 7.224861604080934, 6.115056804023014, 8.368402463540942, 5.587539454730464, 4.270775507754487, 2.6959252725759346, 3.825287717429351, 3.2027481504226842, 1.790140013484508, 0.9489881405573698, 0.0), # 12
(10.68272194586145, 10.716357783852182, 9.188628184802662, 9.863706382614039, 7.85590194536768, 3.8746443972937565, 4.384237753947633, 4.096995750044741, 4.295424524005172, 2.0924996391308714, 1.4833981781817738, 0.8635232543634921, 0.0, 10.760205284888082, 9.498755797998411, 7.416990890908868, 6.277498917392613, 8.590849048010345, 5.735794050062637, 4.384237753947633, 2.7676031409241117, 3.92795097268384, 3.287902127538014, 1.8377256369605324, 0.974214343986562, 0.0), # 13
(10.945005322520059, 10.973225956558347, 9.408875319349146, 10.100184007381912, 8.046321112836791, 3.967535660666574, 4.489268893142796, 4.195021334217623, 4.398381856963768, 2.1426235968757004, 1.518968546452257, 0.8842186806478561, 0.0, 11.018219850783076, 9.726405487126415, 7.594842732261284, 6.4278707906271, 8.796763713927536, 5.873029867904672, 4.489268893142796, 2.833954043333267, 4.023160556418396, 3.3667280024606385, 1.8817750638698296, 0.997565996050759, 0.0), # 14
(11.185802283922625, 11.207888427454638, 9.610082028117542, 10.316217777125386, 8.220679464918646, 4.052395941121439, 4.585220521049775, 4.284571567799878, 4.4924378934939275, 2.1884146716442476, 1.551463867523884, 0.9031249705859171, 0.0, 11.253928113083257, 9.934374676445087, 7.757319337619419, 6.565244014932741, 8.984875786987855, 5.998400194919829, 4.585220521049775, 2.894568529372456, 4.110339732459323, 3.4387392590417964, 1.9220164056235085, 1.0188989479504218, 0.0), # 15
(11.40355840274376, 11.418759559746144, 9.790888868163425, 10.510348143398145, 8.377823529265866, 4.128652008055021, 4.671444233378385, 4.36504165555098, 4.5769572964433145, 2.2295633938385993, 1.5806645832929027, 0.920114387468494, 0.0, 11.465737733428254, 10.121258262153432, 7.9033229164645125, 6.688690181515796, 9.153914592886629, 6.111058317771373, 4.671444233378385, 2.9490371486107296, 4.188911764632933, 3.503449381132716, 1.958177773632685, 1.0380690508860133, 0.0), # 16
(11.59671925165809, 11.604253716637938, 9.949936396542352, 10.6811155577539, 8.51659983353107, 4.1957306308639994, 4.747291625838426, 4.435826802230409, 4.651304728659593, 2.2657602938608403, 1.60635113565556, 0.9350591945864056, 0.0, 11.652056373457699, 10.28565114045046, 8.031755678277799, 6.79728088158252, 9.302609457319186, 6.2101575231225725, 4.747291625838426, 2.9969504506171427, 4.258299916765535, 3.5603718525846344, 1.9899872793084707, 1.0549321560579947, 0.0), # 17
(11.763730403340244, 11.7627852613351, 10.08586517030988, 10.82706047174635, 8.63585490536687, 4.253058578945052, 4.81211429413971, 4.49632221259763, 4.7148448529904385, 2.2966959021130613, 1.6283039665081016, 0.9478316552304716, 0.0, 11.811291694811214, 10.426148207535187, 8.141519832540508, 6.890087706339182, 9.429689705980877, 6.294851097636682, 4.81211429413971, 3.0378989849607514, 4.317927452683435, 3.6090201572487843, 2.0171730340619765, 1.0693441146668274, 0.0), # 18
(11.903037430464838, 11.892768557042718, 10.197315746521578, 10.946723336929182, 8.734435272425891, 4.300062621694845, 4.865263833992036, 4.5459230914121225, 4.766942332283511, 2.3220607489973486, 1.6463035177467755, 0.9583040326915097, 0.0, 11.941851359128435, 10.541344359606605, 8.231517588733878, 6.9661822469920445, 9.533884664567022, 6.364292327976972, 4.865263833992036, 3.071473301210604, 4.367217636212946, 3.648907778976395, 2.039463149304316, 1.0811607779129746, 0.0), # 19
(12.013085905706498, 11.992617966965858, 10.282928682233003, 11.038644604856119, 8.811187462360754, 4.336169528510063, 4.9060918411052175, 4.5840246434333585, 4.806961829386479, 2.341545364915788, 1.66013023126783, 0.9663485902603393, 0.0, 12.042143028048988, 10.62983449286373, 8.30065115633915, 7.024636094747362, 9.613923658772958, 6.417634500806702, 4.9060918411052175, 3.097263948935759, 4.405593731180377, 3.679548201618707, 2.0565857364466007, 1.0902379969968963, 0.0), # 20
(12.09232140173984, 12.060747854309614, 10.341344534499719, 11.101364727080837, 8.86495800282407, 4.360806068787375, 4.933949911189055, 4.6100220734208115, 4.834268007147008, 2.3548402802704667, 1.669564548967512, 0.9718375912277795, 0.0, 12.110574363212494, 10.690213503505571, 8.34782274483756, 7.064520840811399, 9.668536014294016, 6.454030902789136, 4.933949911189055, 3.1148614777052677, 4.432479001412035, 3.7004549090269463, 2.068268906899944, 1.096431623119056, 0.0), # 21
(12.139189491239494, 12.095572582279058, 10.371203860377285, 11.133424155157051, 8.894593421468459, 4.373399011923457, 4.94818963995336, 4.623310586133957, 4.848225528412765, 2.361636025463473, 1.674386912742068, 0.9746432988846491, 0.0, 12.145553026258591, 10.721076287731139, 8.37193456371034, 7.084908076390418, 9.69645105682553, 6.47263482058754, 4.94818963995336, 3.1238564370881834, 4.447296710734229, 3.7111413850523514, 2.0742407720754574, 1.0995975074799145, 0.0), # 22
(12.156472036011166, 12.099695953360769, 10.374923182441702, 11.137437731481482, 8.902185644826076, 4.375, 4.949882401355603, 4.624746913580247, 4.8499704938271595, 2.3624376817558304, 1.6749916074323483, 0.9749897576588934, 0.0, 12.15, 10.724887334247827, 8.37495803716174, 7.087313045267489, 9.699940987654319, 6.474645679012346, 4.949882401355603, 3.125, 4.451092822413038, 3.7124792438271617, 2.0749846364883404, 1.0999723593964337, 0.0), # 23
(12.169214895640982, 12.09729074074074, 10.374314814814815, 11.13694375, 8.906486090891882, 4.375, 4.9489522875817, 4.62275, 4.849736666666666, 2.3619451851851854, 1.6749249158249162, 0.9749086419753087, 0.0, 12.15, 10.723995061728393, 8.37462457912458, 7.085835555555555, 9.699473333333332, 6.47185, 4.9489522875817, 3.125, 4.453243045445941, 3.7123145833333346, 2.074862962962963, 1.099753703703704, 0.0), # 24
(12.181688676253897, 12.092549725651576, 10.373113854595337, 11.135966435185185, 8.910691956475603, 4.375, 4.947119341563786, 4.618827160493828, 4.8492746913580245, 2.3609756515775038, 1.6747926798852726, 0.9747485139460449, 0.0, 12.15, 10.722233653406493, 8.373963399426362, 7.08292695473251, 9.698549382716049, 6.466358024691359, 4.947119341563786, 3.125, 4.455345978237801, 3.711988811728396, 2.0746227709190674, 1.0993227023319616, 0.0), # 25
(12.19389242285764, 12.085545336076818, 10.371336762688616, 11.134516898148147, 8.914803094736882, 4.375, 4.944412030985233, 4.613052469135803, 4.84859049382716, 2.3595452126200276, 1.674596096770171, 0.9745115683584822, 0.0, 12.15, 10.719627251943303, 8.372980483850855, 7.078635637860081, 9.69718098765432, 6.458273456790124, 4.944412030985233, 3.125, 4.457401547368441, 3.71150563271605, 2.0742673525377233, 1.0986859396433473, 0.0), # 26
(12.205825180459962, 12.076349999999996, 10.369, 11.132606249999998, 8.918819358835371, 4.375, 4.940858823529412, 4.6055, 4.84769, 2.35767, 1.674336363636364, 0.9742000000000002, 0.0, 12.15, 10.7162, 8.371681818181818, 7.073009999999999, 9.69538, 6.4477, 4.940858823529412, 3.125, 4.459409679417686, 3.7108687500000004, 2.0738000000000003, 1.09785, 0.0), # 27
(12.217485994068602, 12.065036145404662, 10.366120027434842, 11.13024560185185, 8.92274060193072, 4.375, 4.93648818687969, 4.596243827160494, 4.846579135802468, 2.3553661454046644, 1.6740146776406037, 0.9738160036579792, 0.0, 12.15, 10.711976040237769, 8.370073388203018, 7.066098436213991, 9.693158271604936, 6.434741358024692, 4.93648818687969, 3.125, 4.46137030096536, 3.710081867283951, 2.073224005486969, 1.0968214677640604, 0.0), # 28
(12.2288739086913, 12.051676200274349, 10.362713305898492, 11.127446064814816, 8.926566677182576, 4.375, 4.931328588719439, 4.585358024691358, 4.845263827160494, 2.3526497805212623, 1.6736322359396434, 0.9733617741197987, 0.0, 12.15, 10.706979515317785, 8.368161179698216, 7.057949341563786, 9.690527654320988, 6.419501234567901, 4.931328588719439, 3.125, 4.463283338591288, 3.709148688271606, 2.0725426611796984, 1.0956069272976683, 0.0), # 29
(12.239987969335797, 12.036342592592591, 10.358796296296296, 11.12421875, 8.930297437750589, 4.375, 4.925408496732026, 4.572916666666666, 4.84375, 2.3495370370370376, 1.6731902356902357, 0.9728395061728394, 0.0, 12.15, 10.701234567901233, 8.365951178451178, 7.048611111111112, 9.6875, 6.402083333333333, 4.925408496732026, 3.125, 4.4651487188752945, 3.7080729166666675, 2.0717592592592595, 1.094212962962963, 0.0), # 30
(12.25082722100983, 12.019107750342934, 10.354385459533608, 11.120574768518516, 8.933932736794405, 4.375, 4.918756378600824, 4.558993827160494, 4.842043580246913, 2.346044046639232, 1.6726898740491336, 0.9722513946044812, 0.0, 12.15, 10.694765340649292, 8.363449370245666, 7.038132139917694, 9.684087160493826, 6.382591358024691, 4.918756378600824, 3.125, 4.466966368397203, 3.70685825617284, 2.070877091906722, 1.0926461591220853, 0.0), # 31
(12.261390708721144, 12.000044101508914, 10.349497256515773, 11.11652523148148, 8.937472427473676, 4.375, 4.911400702009199, 4.543663580246914, 4.84015049382716, 2.3421869410150897, 1.672132348173089, 0.9715996342021036, 0.0, 12.15, 10.687595976223138, 8.360661740865444, 7.026560823045267, 9.68030098765432, 6.36112901234568, 4.911400702009199, 3.125, 4.468736213736838, 3.705508410493828, 2.069899451303155, 1.0909131001371744, 0.0), # 32
(12.271677477477477, 11.979224074074073, 10.344148148148149, 11.11208125, 8.94091636294805, 4.375, 4.903369934640523, 4.527, 4.838076666666666, 2.3379818518518523, 1.6715188552188551, 0.9708864197530863, 0.0, 12.15, 10.679750617283949, 8.357594276094275, 7.013945555555555, 9.676153333333332, 6.3378000000000005, 4.903369934640523, 3.125, 4.470458181474025, 3.704027083333334, 2.06882962962963, 1.0890203703703705, 0.0), # 33
(12.28168657228657, 11.956720096021947, 10.338354595336076, 11.107253935185184, 8.944264396377172, 4.375, 4.894692544178166, 4.509077160493827, 4.835828024691358, 2.333444910836763, 1.670850592343185, 0.9701139460448103, 0.0, 12.15, 10.671253406492912, 8.354252961715924, 7.000334732510288, 9.671656049382715, 6.312708024691357, 4.894692544178166, 3.125, 4.472132198188586, 3.7024179783950624, 2.0676709190672153, 1.0869745541838134, 0.0), # 34
(12.291417038156167, 11.932604595336077, 10.332133058984912, 11.102054398148146, 8.947516380920696, 4.375, 4.885396998305495, 4.489969135802469, 4.83341049382716, 2.328592249657065, 1.6701287567028307, 0.969284407864655, 0.0, 12.15, 10.662128486511202, 8.350643783514153, 6.985776748971193, 9.66682098765432, 6.285956790123457, 4.885396998305495, 3.125, 4.473758190460348, 3.7006847993827163, 2.0664266117969827, 1.0847822359396435, 0.0), # 35
(12.300867920094007, 11.906949999999998, 10.3255, 11.096493749999999, 8.950672169738269, 4.375, 4.875511764705882, 4.46975, 4.830829999999999, 2.32344, 1.6693545454545458, 0.9684000000000001, 0.0, 12.15, 10.6524, 8.346772727272727, 6.970319999999999, 9.661659999999998, 6.257650000000001, 4.875511764705882, 3.125, 4.475336084869134, 3.6988312500000005, 2.0651, 1.08245, 0.0), # 36
(12.310038263107828, 11.879828737997256, 10.318471879286694, 11.090583101851852, 8.953731615989536, 4.375, 4.865065311062696, 4.448493827160494, 4.828092469135802, 2.3180042935528125, 1.668529155755082, 0.9674629172382261, 0.0, 12.15, 10.642092089620485, 8.34264577877541, 6.954012880658436, 9.656184938271604, 6.227891358024691, 4.865065311062696, 3.125, 4.476865807994768, 3.696861033950618, 2.063694375857339, 1.0799844307270234, 0.0), # 37
(12.31892711220537, 11.851313237311386, 10.311065157750342, 11.084333564814814, 8.956694572834152, 4.375, 4.854086105059308, 4.426274691358025, 4.825203827160493, 2.312301262002744, 1.6676537847611925, 0.9664753543667125, 0.0, 12.15, 10.631228898033836, 8.33826892380596, 6.936903786008231, 9.650407654320986, 6.196784567901235, 4.854086105059308, 3.125, 4.478347286417076, 3.6947778549382724, 2.0622130315500686, 1.0773921124828534, 0.0), # 38
(12.327533512394384, 11.821475925925924, 10.303296296296297, 11.07775625, 8.959560893431762, 4.375, 4.842602614379085, 4.4031666666666665, 4.82217, 2.3063470370370376, 1.6667296296296297, 0.9654395061728396, 0.0, 12.15, 10.619834567901233, 8.333648148148148, 6.919041111111111, 9.64434, 6.164433333333333, 4.842602614379085, 3.125, 4.479780446715881, 3.6925854166666676, 2.0606592592592596, 1.0746796296296297, 0.0), # 39
(12.335856508682596, 11.790389231824417, 10.295181755829903, 11.070862268518518, 8.962330430942014, 4.375, 4.830643306705398, 4.3792438271604945, 4.818996913580246, 2.3001577503429362, 1.6657578875171468, 0.9643575674439875, 0.0, 12.15, 10.60793324188386, 8.328789437585733, 6.900473251028807, 9.637993827160493, 6.1309413580246925, 4.830643306705398, 3.125, 4.481165215471007, 3.690287422839507, 2.059036351165981, 1.0718535665294926, 0.0), # 40
(12.343895146077754, 11.758125582990397, 10.286737997256516, 11.06366273148148, 8.96500303852456, 4.375, 4.818236649721617, 4.354580246913581, 4.81569049382716, 2.293749533607682, 1.6647397555804966, 0.9632317329675355, 0.0, 12.15, 10.595549062642888, 8.323698777902482, 6.881248600823045, 9.63138098765432, 6.096412345679013, 4.818236649721617, 3.125, 4.48250151926228, 3.6878875771604944, 2.0573475994513033, 1.0689205075445818, 0.0), # 41
(12.3516484695876, 11.724757407407406, 10.277981481481483, 11.056168750000001, 8.967578569339047, 4.375, 4.805411111111111, 4.32925, 4.812256666666666, 2.287138518518519, 1.663676430976431, 0.9620641975308644, 0.0, 12.15, 10.582706172839506, 8.318382154882155, 6.861415555555555, 9.624513333333333, 6.06095, 4.805411111111111, 3.125, 4.483789284669523, 3.6853895833333343, 2.055596296296297, 1.0658870370370372, 0.0), # 42
(12.35911552421987, 11.690357133058985, 10.268928669410151, 11.048391435185184, 8.970056876545122, 4.375, 4.7921951585572495, 4.3033271604938275, 4.80870135802469, 2.280340836762689, 1.6625691108617036, 0.9608571559213536, 0.0, 12.15, 10.569428715134888, 8.312845554308517, 6.841022510288067, 9.61740271604938, 6.024658024691359, 4.7921951585572495, 3.125, 4.485028438272561, 3.682797145061729, 2.0537857338820307, 1.062759739368999, 0.0), # 43
(12.366295354982311, 11.65499718792867, 10.259596021947875, 11.040341898148148, 8.972437813302435, 4.375, 4.778617259743403, 4.2768858024691365, 4.805030493827159, 2.2733726200274353, 1.6614189923930665, 0.9596128029263833, 0.0, 12.15, 10.555740832190216, 8.307094961965332, 6.820117860082305, 9.610060987654318, 5.987640123456791, 4.778617259743403, 3.125, 4.486218906651217, 3.6801139660493836, 2.0519192043895753, 1.0595451989026066, 0.0), # 44
(12.37318700688266, 11.618749999999999, 10.25, 11.03203125, 8.974721232770635, 4.375, 4.764705882352941, 4.25, 4.80125, 2.2662500000000003, 1.6602272727272729, 0.9583333333333333, 0.0, 12.15, 10.541666666666664, 8.301136363636363, 6.79875, 9.6025, 5.95, 4.764705882352941, 3.125, 4.487360616385318, 3.677343750000001, 2.0500000000000003, 1.0562500000000001, 0.0), # 45
(12.379789524928656, 11.581687997256516, 10.240157064471878, 11.023470601851852, 8.976906988109372, 4.375, 4.750489494069233, 4.222743827160494, 4.797365802469135, 2.258989108367627, 1.6589951490210748, 0.9570209419295841, 0.0, 12.15, 10.527230361225422, 8.294975745105374, 6.77696732510288, 9.59473160493827, 5.9118413580246925, 4.750489494069233, 3.125, 4.488453494054686, 3.6744902006172846, 2.048031412894376, 1.0528807270233198, 0.0), # 46
(12.386101954128042, 11.543883607681755, 10.230083676268862, 11.014671064814813, 8.978994932478294, 4.375, 4.7359965625756475, 4.195191358024691, 4.793383827160493, 2.2516060768175588, 1.657723818431226, 0.955677823502515, 0.0, 12.15, 10.512456058527663, 8.288619092156129, 6.754818230452675, 9.586767654320987, 5.873267901234568, 4.7359965625756475, 3.125, 4.489497466239147, 3.6715570216049387, 2.046016735253773, 1.049443964334705, 0.0), # 47
(12.392123339488554, 11.505409259259258, 10.219796296296296, 11.00564375, 8.980984919037049, 4.375, 4.7212555555555555, 4.167416666666667, 4.78931, 2.244117037037037, 1.656414478114478, 0.9543061728395063, 0.0, 12.15, 10.497367901234567, 8.28207239057239, 6.73235111111111, 9.57862, 5.834383333333334, 4.7212555555555555, 3.125, 4.490492459518524, 3.6685479166666677, 2.0439592592592595, 1.0459462962962964, 0.0), # 48
(12.397852726017943, 11.466337379972563, 10.209311385459534, 10.996399768518518, 8.982876800945284, 4.375, 4.706294940692326, 4.139493827160494, 4.78515024691358, 2.2365381207133064, 1.6550683252275846, 0.9529081847279379, 0.0, 12.15, 10.481990032007316, 8.275341626137923, 6.709614362139918, 9.57030049382716, 5.795291358024691, 4.706294940692326, 3.125, 4.491438400472642, 3.665466589506174, 2.0418622770919073, 1.0423943072702333, 0.0), # 49
(12.403289158723938, 11.426740397805213, 10.198645404663925, 10.986950231481481, 8.984670431362652, 4.375, 4.69114318566933, 4.111496913580247, 4.78091049382716, 2.228885459533608, 1.6536865569272978, 0.9514860539551899, 0.0, 12.15, 10.466346593507089, 8.268432784636488, 6.686656378600823, 9.56182098765432, 5.756095679012346, 4.69114318566933, 3.125, 4.492335215681326, 3.6623167438271613, 2.0397290809327853, 1.038794581618656, 0.0), # 50
(12.408431682614292, 11.38669074074074, 10.187814814814814, 10.977306249999998, 8.986365663448797, 4.375, 4.675828758169934, 4.0835, 4.776596666666666, 2.2211751851851855, 1.6522703703703707, 0.9500419753086421, 0.0, 12.15, 10.450461728395062, 8.261351851851853, 6.663525555555555, 9.553193333333333, 5.7169, 4.675828758169934, 3.125, 4.493182831724399, 3.659102083333334, 2.037562962962963, 1.0351537037037037, 0.0), # 51
(12.413279342696734, 11.34626083676269, 10.176836076817558, 10.967478935185184, 8.98796235036337, 4.375, 4.660380125877511, 4.055577160493827, 4.772214691358024, 2.2134234293552817, 1.6508209627135553, 0.9485781435756746, 0.0, 12.15, 10.434359579332419, 8.254104813567777, 6.640270288065844, 9.544429382716048, 5.677808024691357, 4.660380125877511, 3.125, 4.493981175181685, 3.655826311728396, 2.035367215363512, 1.0314782578875175, 0.0), # 52
(12.417831183979011, 11.305523113854596, 10.165725651577505, 10.957479398148147, 8.989460345266023, 4.375, 4.64482575647543, 4.0278024691358025, 4.767770493827161, 2.205646323731139, 1.6493395311136052, 0.9470967535436672, 0.0, 12.15, 10.418064288980338, 8.246697655568026, 6.616938971193416, 9.535540987654322, 5.638923456790124, 4.64482575647543, 3.125, 4.4947301726330116, 3.65249313271605, 2.0331451303155013, 1.0277748285322361, 0.0), # 53
(12.42208625146886, 11.26455, 10.154499999999999, 10.94731875, 8.9908595013164, 4.375, 4.629194117647058, 4.000249999999999, 4.7632699999999994, 2.1978600000000004, 1.6478272727272725, 0.9456, 0.0, 12.15, 10.401599999999998, 8.239136363636362, 6.593579999999999, 9.526539999999999, 5.60035, 4.629194117647058, 3.125, 4.4954297506582, 3.649106250000001, 2.0309, 1.0240500000000001, 0.0), # 54
(12.426043590174027, 11.223413923182441, 10.143175582990398, 10.93700810185185, 8.992159671674152, 4.375, 4.613513677075768, 3.9729938271604937, 4.758719135802469, 2.1900805898491087, 1.6462853847113108, 0.9440900777320531, 0.0, 12.15, 10.384990855052584, 8.231426923556553, 6.570241769547325, 9.517438271604938, 5.562191358024691, 4.613513677075768, 3.125, 4.496079835837076, 3.645669367283951, 2.02863511659808, 1.0203103566529494, 0.0), # 55
(12.429702245102245, 11.182187311385459, 10.131768861454047, 10.926558564814814, 8.993360709498926, 4.375, 4.597812902444929, 3.946108024691358, 4.754123827160494, 2.182324224965707, 1.6447150642224717, 0.9425691815272064, 0.0, 12.15, 10.368260996799268, 8.223575321112358, 6.54697267489712, 9.508247654320988, 5.524551234567902, 4.597812902444929, 3.125, 4.496680354749463, 3.6421861882716056, 2.02635377229081, 1.0165624828532238, 0.0), # 56
(12.433061261261258, 11.140942592592593, 10.120296296296297, 10.915981249999998, 8.994462467950372, 4.375, 4.582120261437908, 3.9196666666666675, 4.74949, 2.1746070370370374, 1.6431175084175085, 0.9410395061728396, 0.0, 12.15, 10.351434567901233, 8.215587542087542, 6.523821111111111, 9.49898, 5.487533333333334, 4.582120261437908, 3.125, 4.497231233975186, 3.638660416666667, 2.0240592592592597, 1.0128129629629632, 0.0), # 57
(12.436119683658815, 11.09975219478738, 10.108774348422497, 10.905287268518517, 8.995464800188138, 4.375, 4.5664642217380775, 3.8937438271604936, 4.744823580246913, 2.1669451577503436, 1.641493914453174, 0.939503246456333, 0.0, 12.15, 10.334535711019662, 8.20746957226587, 6.50083547325103, 9.489647160493826, 5.451241358024691, 4.5664642217380775, 3.125, 4.497732400094069, 3.6350957561728396, 2.0217548696844996, 1.0090683813443075, 0.0), # 58
(12.438876557302644, 11.05868854595336, 10.097219478737998, 10.89448773148148, 8.996367559371876, 4.375, 4.550873251028807, 3.868413580246914, 4.74013049382716, 2.1593547187928674, 1.63984547948622, 0.9379625971650665, 0.0, 12.15, 10.31758856881573, 8.1992273974311, 6.478064156378601, 9.48026098765432, 5.41577901234568, 4.550873251028807, 3.125, 4.498183779685938, 3.6314959104938276, 2.0194438957476, 1.0053353223593966, 0.0), # 59
(12.441330927200491, 11.017824074074072, 10.085648148148147, 10.88359375, 8.997170598661228, 4.375, 4.535375816993463, 3.84375, 4.735416666666667, 2.1518518518518523, 1.6381734006734008, 0.9364197530864199, 0.0, 12.15, 10.300617283950617, 8.190867003367003, 6.455555555555556, 9.470833333333333, 5.3812500000000005, 4.535375816993463, 3.125, 4.498585299330614, 3.6278645833333343, 2.0171296296296295, 1.0016203703703705, 0.0), # 60
(12.443481838360098, 10.977231207133059, 10.0740768175583, 10.872616435185183, 8.997873771215849, 4.375, 4.520000387315419, 3.819827160493827, 4.730688024691357, 2.1444526886145407, 1.6364788751714678, 0.9348769090077733, 0.0, 12.15, 10.283645999085506, 8.182394375857339, 6.4333580658436205, 9.461376049382714, 5.347758024691358, 4.520000387315419, 3.125, 4.498936885607924, 3.624205478395062, 2.0148153635116604, 0.9979301097393691, 0.0), # 61
(12.445328335789204, 10.936982373113853, 10.062521947873801, 10.861566898148148, 8.998476930195388, 4.375, 4.504775429678044, 3.796719135802469, 4.72595049382716, 2.137173360768176, 1.6347631001371743, 0.9333362597165068, 0.0, 12.15, 10.266698856881574, 8.17381550068587, 6.411520082304527, 9.45190098765432, 5.315406790123457, 4.504775429678044, 3.125, 4.499238465097694, 3.620522299382717, 2.0125043895747603, 0.9942711248285323, 0.0), # 62
(12.44686946449555, 10.897149999999998, 10.051, 10.85045625, 8.998979928759484, 4.375, 4.4897294117647055, 3.7745, 4.721209999999999, 2.13003, 1.6330272727272728, 0.9318000000000001, 0.0, 12.15, 10.249799999999999, 8.165136363636364, 6.390089999999999, 9.442419999999998, 5.2843, 4.4897294117647055, 3.125, 4.499489964379742, 3.616818750000001, 2.0102, 0.99065, 0.0), # 63
(12.448104269486876, 10.857806515775033, 10.039527434842249, 10.839295601851852, 8.999382620067799, 4.375, 4.474890801258775, 3.7532438271604947, 4.716472469135802, 2.123038737997257, 1.6312725900985157, 0.9302703246456334, 0.0, 12.15, 10.232973571101967, 8.156362950492579, 6.369116213991769, 9.432944938271604, 5.254541358024692, 4.474890801258775, 3.125, 4.499691310033899, 3.613098533950618, 2.00790548696845, 0.9870733196159123, 0.0), # 64
(12.449031795770926, 10.819024348422495, 10.0281207133059, 10.828096064814813, 8.999684857279973, 4.375, 4.4602880658436215, 3.7330246913580245, 4.711743827160493, 2.1162157064471883, 1.6295002494076571, 0.9287494284407863, 0.0, 12.15, 10.216243712848648, 8.147501247038285, 6.348647119341564, 9.423487654320986, 5.226234567901234, 4.4602880658436215, 3.125, 4.499842428639987, 3.609365354938272, 2.0056241426611803, 0.9835476680384088, 0.0), # 65
(12.449651088355436, 10.780875925925926, 10.016796296296297, 10.81686875, 8.999886493555657, 4.375, 4.445949673202614, 3.7139166666666674, 4.70703, 2.1095770370370373, 1.6277114478114478, 0.9272395061728398, 0.0, 12.15, 10.199634567901235, 8.138557239057238, 6.328731111111111, 9.41406, 5.199483333333334, 4.445949673202614, 3.125, 4.499943246777828, 3.6056229166666673, 2.0033592592592595, 0.9800796296296298, 0.0), # 66
(12.44996119224815, 10.743433676268861, 10.005570644718793, 10.805624768518516, 8.999987382054503, 4.375, 4.431904091019123, 3.695993827160495, 4.702336913580247, 2.103138861454047, 1.625907382466642, 0.9257427526291724, 0.0, 12.15, 10.183170278920894, 8.12953691233321, 6.30941658436214, 9.404673827160494, 5.1743913580246925, 4.431904091019123, 3.125, 4.499993691027251, 3.6018749228395066, 2.0011141289437586, 0.9766757887517148, 0.0), # 67
(12.44974993737699, 10.706573503252354, 9.994405949931412, 10.794277566425121, 8.999902364237876, 4.37491880810852, 4.418109116897788, 3.6791719250114308, 4.6976351394604485, 2.0968861324941503, 1.624057197708075, 0.9242530021899743, 0.0, 12.149850180041152, 10.166783024089716, 8.120285988540376, 6.290658397482449, 9.395270278920897, 5.1508406950160035, 4.418109116897788, 3.1249420057918, 4.499951182118938, 3.598092522141708, 1.9988811899862826, 0.9733248639320324, 0.0), # 68
(12.447770048309177, 10.669170071684588, 9.982988425925925, 10.782255163043477, 8.999128540305009, 4.374276954732511, 4.404160908807968, 3.6625493827160494, 4.692719135802469, 2.090641917211329, 1.621972567783094, 0.9227218973359325, 0.0, 12.148663194444444, 10.149940870695255, 8.10986283891547, 6.271925751633985, 9.385438271604938, 5.127569135802469, 4.404160908807968, 3.1244835390946504, 4.499564270152504, 3.5940850543478264, 1.996597685185185, 0.9699245519713263, 0.0), # 69
(12.443862945070673, 10.63105170582769, 9.971268432784635, 10.769478411835749, 8.997599451303152, 4.373012879134278, 4.389996080736822, 3.645976223136717, 4.687561156835848, 2.0843758573388205, 1.619629777305216, 0.921142276129281, 0.0, 12.14631880144033, 10.13256503742209, 8.09814888652608, 6.25312757201646, 9.375122313671696, 5.104366712391404, 4.389996080736822, 3.123580627953056, 4.498799725651576, 3.5898261372785836, 1.9942536865569274, 0.9664592459843356, 0.0), # 70
(12.438083592771514, 10.592241185450682, 9.959250085733881, 10.755966153381644, 8.995334463003308, 4.371147065996037, 4.375620995723392, 3.629457933241884, 4.682168884316415, 2.078088107802792, 1.6170374741567726, 0.9195152937212715, 0.0, 12.142847865226338, 10.114668230933985, 8.085187370783862, 6.234264323408375, 9.36433776863283, 5.081241106538638, 4.375620995723392, 3.1222479042828835, 4.497667231501654, 3.5853220511272155, 1.9918500171467763, 0.962931016859153, 0.0), # 71
(12.430486956521738, 10.552761290322579, 9.946937499999999, 10.74173722826087, 8.99235294117647, 4.3687000000000005, 4.3610420168067225, 3.6129999999999995, 4.67655, 2.071778823529412, 1.614204306220096, 0.917842105263158, 0.0, 12.13828125, 10.096263157894736, 8.07102153110048, 6.215336470588234, 9.3531, 5.058199999999999, 4.3610420168067225, 3.1205000000000003, 4.496176470588235, 3.5805790760869574, 1.9893874999999999, 0.959341935483871, 0.0), # 72
(12.421128001431383, 10.512634800212398, 9.934334790809327, 10.72681047705314, 8.98867425159364, 4.36569216582838, 4.346265507025855, 3.5966079103795154, 4.670712185642433, 2.0654481594448484, 1.6111389213775176, 0.916123865906192, 0.0, 12.132649819958848, 10.07736252496811, 8.055694606887588, 6.196344478334543, 9.341424371284866, 5.035251074531322, 4.346265507025855, 3.118351547020271, 4.49433712579682, 3.5756034923510476, 1.9868669581618656, 0.9556940727465817, 0.0), # 73
(12.410061692610485, 10.471884494889155, 9.921446073388202, 10.711204740338164, 8.984317760025819, 4.3621440481633895, 4.331297829419833, 3.5802871513488794, 4.664663122999542, 2.0590962704752687, 1.607849967511371, 0.9143617308016269, 0.0, 12.125984439300412, 10.057979038817894, 8.039249837556856, 6.177288811425805, 9.329326245999084, 5.012402011888431, 4.331297829419833, 3.115817177259564, 4.4921588800129095, 3.5704015801127222, 1.9842892146776405, 0.9519894995353778, 0.0), # 74
(12.397342995169081, 10.430533154121862, 9.908275462962962, 10.694938858695652, 8.97930283224401, 4.358076131687243, 4.3161453470277, 3.5640432098765435, 4.6584104938271595, 2.052723311546841, 1.604346092503987, 0.9125568551007147, 0.0, 12.118315972222222, 10.038125406107861, 8.021730462519935, 6.158169934640522, 9.316820987654319, 4.989660493827161, 4.3161453470277, 3.112911522633745, 4.489651416122005, 3.5649796195652184, 1.9816550925925924, 0.9482302867383512, 0.0), # 75
(12.383026874217212, 10.388603557679545, 9.894827074759945, 10.678031672705314, 8.973648834019203, 4.353508901082153, 4.300814422888497, 3.5478815729309554, 4.651961979881115, 2.046329437585734, 1.6006359442376985, 0.9107103939547083, 0.0, 12.10967528292181, 10.01781433350179, 8.003179721188491, 6.138988312757201, 9.30392395976223, 4.967034202103338, 4.300814422888497, 3.1096492150586803, 4.486824417009601, 3.5593438909017725, 1.978965414951989, 0.9444185052435952, 0.0), # 76
(12.367168294864912, 10.34611848533121, 9.881105024005485, 10.660502022946858, 8.967375131122406, 4.34846284103033, 4.285311420041268, 3.531807727480567, 4.645325262917238, 2.0399148035181156, 1.5967281705948373, 0.9088235025148608, 0.0, 12.10009323559671, 9.997058527663466, 7.983640852974187, 6.119744410554345, 9.290650525834476, 4.944530818472794, 4.285311420041268, 3.106044886450236, 4.483687565561203, 3.5535006743156203, 1.9762210048010973, 0.9405562259392011, 0.0), # 77
(12.349822222222222, 10.30310071684588, 9.867113425925925, 10.64236875, 8.960501089324618, 4.3429584362139915, 4.269642701525055, 3.5158271604938274, 4.638508024691357, 2.0334795642701526, 1.5926314194577353, 0.9068973359324239, 0.0, 12.089600694444444, 9.975870695256662, 7.963157097288676, 6.100438692810457, 9.277016049382715, 4.922158024691359, 4.269642701525055, 3.1021131687242796, 4.480250544662309, 3.5474562500000006, 1.9734226851851853, 0.9366455197132618, 0.0), # 78
(12.331043621399177, 10.259573031992566, 9.8528563957476, 10.623650694444443, 8.953046074396838, 4.337016171315348, 4.2538146303789, 3.4999453589391867, 4.631517946959304, 2.0270238747680143, 1.5883543387087244, 0.9049330493586505, 0.0, 12.07822852366255, 9.954263542945155, 7.941771693543622, 6.081071624304041, 9.263035893918609, 4.899923502514861, 4.2538146303789, 3.097868693796677, 4.476523037198419, 3.5412168981481487, 1.97057127914952, 0.9326884574538697, 0.0), # 79
(12.310887457505816, 10.215558210540289, 9.838338048696844, 10.604366696859904, 8.945029452110063, 4.330656531016613, 4.2378335696418485, 3.4841678097850943, 4.624362711476909, 2.0205478899378684, 1.5839055762301377, 0.9029317979447936, 0.0, 12.066007587448558, 9.932249777392729, 7.919527881150689, 6.061643669813604, 9.248725422953818, 4.877834933699132, 4.2378335696418485, 3.093326093583295, 4.4725147260550315, 3.5347888989533023, 1.967667609739369, 0.9286871100491174, 0.0), # 80
(12.289408695652174, 10.171079032258064, 9.8235625, 10.584535597826088, 8.936470588235293, 4.3239, 4.221705882352941, 3.4685000000000006, 4.617049999999999, 2.014051764705883, 1.5792937799043065, 0.9008947368421053, 0.0, 12.052968749999998, 9.909842105263158, 7.8964688995215315, 6.042155294117647, 9.234099999999998, 4.855900000000001, 4.221705882352941, 3.0885, 4.468235294117647, 3.5281785326086967, 1.9647125, 0.9246435483870968, 0.0), # 81
(12.26666230094829, 10.126158276914907, 9.808533864883403, 10.564176237922705, 8.927388848543531, 4.316767062947722, 4.205437931551222, 3.4529474165523544, 4.6095874942844075, 2.007535653998225, 1.5745275976135626, 0.8988230212018388, 0.0, 12.039142875514404, 9.887053233220225, 7.8726379880678135, 6.022606961994674, 9.219174988568815, 4.834126383173296, 4.205437931551222, 3.0834050449626584, 4.4636944242717655, 3.521392079307569, 1.9617067729766806, 0.9205598433559008, 0.0), # 82
(12.242703238504205, 10.080818724279835, 9.793256258573388, 10.543307457729467, 8.917803598805776, 4.30927820454199, 4.189036080275732, 3.4375155464106077, 4.6019828760859625, 2.0009997127410637, 1.569615677240239, 0.8967178061752463, 0.0, 12.0245608281893, 9.863895867927708, 7.848078386201194, 6.00299913822319, 9.203965752171925, 4.812521764974851, 4.189036080275732, 3.078055860387136, 4.458901799402888, 3.5144358192431566, 1.9586512517146777, 0.9164380658436215, 0.0), # 83
(12.21758647342995, 10.035083154121864, 9.777733796296296, 10.521948097826087, 8.907734204793028, 4.301453909465021, 4.1725066915655145, 3.4222098765432096, 4.5942438271604935, 1.994444095860567, 1.5645666666666667, 0.8945802469135803, 0.0, 12.009253472222222, 9.840382716049382, 7.8228333333333335, 5.9833322875817, 9.188487654320987, 4.791093827160494, 4.1725066915655145, 3.0724670781893004, 4.453867102396514, 3.5073160326086965, 1.9555467592592592, 0.9122802867383514, 0.0), # 84
(12.191366970835569, 9.988974346210009, 9.761970593278463, 10.500116998792272, 8.897200032276285, 4.293314662399025, 4.1558561284596145, 3.4070358939186103, 4.58637802926383, 1.9878689582829019, 1.5593892137751788, 0.8924114985680938, 0.0, 11.9932516718107, 9.81652648424903, 7.796946068875894, 5.963606874848704, 9.17275605852766, 4.769850251486054, 4.1558561284596145, 3.0666533302850176, 4.448600016138142, 3.500038999597425, 1.9523941186556926, 0.9080885769281828, 0.0), # 85
(12.164099695831096, 9.942515080313289, 9.745970764746229, 10.477833001207731, 8.886220447026545, 4.284880948026216, 4.139090753997072, 3.391999085505258, 4.578393164151806, 1.9812744549342376, 1.5540919664481068, 0.8902127162900394, 0.0, 11.976586291152262, 9.792339879190433, 7.770459832240534, 5.943823364802712, 9.156786328303612, 4.748798719707362, 4.139090753997072, 3.0606292485901543, 4.443110223513273, 3.4926110004025777, 1.9491941529492458, 0.9038650073012082, 0.0), # 86
(12.135839613526569, 9.895728136200717, 9.729738425925925, 10.455114945652172, 8.874814814814815, 4.276173251028807, 4.122216931216931, 3.3771049382716045, 4.570296913580247, 1.9746607407407408, 1.5486835725677832, 0.8879850552306694, 0.0, 11.959288194444444, 9.76783560753736, 7.743417862838915, 5.923982222222222, 9.140593827160494, 4.727946913580246, 4.122216931216931, 3.054409465020576, 4.437407407407408, 3.4850383152173916, 1.9459476851851853, 0.8996116487455198, 0.0), # 87
(12.106641689032028, 9.84863629364131, 9.713277692043896, 10.431981672705316, 8.863002501412087, 4.2672120560890106, 4.105241023158234, 3.3623589391860995, 4.562096959304984, 1.9680279706285808, 1.5431726800165397, 0.8857296705412365, 0.0, 11.941388245884776, 9.743026375953601, 7.715863400082698, 5.904083911885741, 9.124193918609969, 4.707302514860539, 4.105241023158234, 3.0480086114921505, 4.431501250706043, 3.477327224235106, 1.9426555384087794, 0.8953305721492102, 0.0), # 88
(12.076560887457505, 9.801262332404088, 9.696592678326475, 10.40845202294686, 8.850802872589364, 4.258017847889041, 4.088169392860024, 3.3477665752171926, 4.553800983081847, 1.9613762995239252, 1.537567936676709, 0.8834477173729935, 0.0, 11.922917309670781, 9.717924891102928, 7.687839683383544, 5.884128898571774, 9.107601966163694, 4.68687320530407, 4.088169392860024, 3.041441319920744, 4.425401436294682, 3.469484007648954, 1.9393185356652953, 0.8910238484003719, 0.0), # 89
(12.045652173913043, 9.753629032258065, 9.6796875, 10.384544836956522, 8.838235294117647, 4.248611111111111, 4.071008403361344, 3.333333333333333, 4.545416666666667, 1.9547058823529415, 1.5318779904306221, 0.881140350877193, 0.0, 11.90390625, 9.692543859649122, 7.65938995215311, 5.864117647058823, 9.090833333333334, 4.666666666666666, 4.071008403361344, 3.0347222222222223, 4.419117647058823, 3.461514945652175, 1.9359375, 0.8866935483870969, 0.0), # 90
(12.013970513508676, 9.705759172972254, 9.662566272290809, 10.360278955314012, 8.825319131767932, 4.239012330437433, 4.053764417701236, 3.319064700502972, 4.536951691815272, 1.948016874041798, 1.526111489160612, 0.8788087262050875, 0.0, 11.884385931069957, 9.66689598825596, 7.630557445803059, 5.844050622125392, 9.073903383630544, 4.646690580704161, 4.053764417701236, 3.027865950312452, 4.412659565883966, 3.4534263184380047, 1.9325132544581618, 0.8823417429974777, 0.0), # 91
(11.981570871354446, 9.657675534315677, 9.64523311042524, 10.335673218599032, 8.812073751311223, 4.2292419905502205, 4.036443798918745, 3.304966163694559, 4.528413740283494, 1.941309429516663, 1.5202770807490107, 0.8764539985079298, 0.0, 11.864387217078187, 9.640993983587226, 7.601385403745053, 5.823928288549988, 9.056827480566987, 4.626952629172383, 4.036443798918745, 3.0208871361073006, 4.406036875655611, 3.4452244061996784, 1.9290466220850482, 0.8779705031196072, 0.0), # 92
(11.948508212560386, 9.609400896057348, 9.62769212962963, 10.310746467391306, 8.798518518518518, 4.219320576131687, 4.01905291005291, 3.2910432098765434, 4.51981049382716, 1.9345837037037037, 1.5143834130781502, 0.8740773229369722, 0.0, 11.84394097222222, 9.614850552306692, 7.57191706539075, 5.80375111111111, 9.03962098765432, 4.607460493827161, 4.01905291005291, 3.0138004115226336, 4.399259259259259, 3.436915489130436, 1.925538425925926, 0.8735818996415772, 0.0), # 93
(11.914837502236535, 9.56095803796628, 9.609947445130317, 10.285517542270531, 8.784672799160816, 4.209268571864045, 4.0015981141427766, 3.277301326017376, 4.511149634202103, 1.9278398515290893, 1.5084391340303622, 0.8716798546434675, 0.0, 11.823078060699588, 9.588478401078142, 7.54219567015181, 5.783519554587267, 9.022299268404206, 4.588221856424326, 4.0015981141427766, 3.0066204084743178, 4.392336399580408, 3.4285058474235113, 1.9219894890260634, 0.8691780034514802, 0.0), # 94
(11.880613705492932, 9.512369739811495, 9.592003172153635, 10.260005283816424, 8.770555959009117, 4.199106462429508, 3.984085774227386, 3.2637459990855056, 4.5024388431641515, 1.9210780279189867, 1.5024528914879791, 0.869262748778668, 0.0, 11.801829346707818, 9.561890236565347, 7.512264457439896, 5.763234083756959, 9.004877686328303, 4.569244398719708, 3.984085774227386, 2.9993617588782198, 4.385277979504559, 3.4200017612721423, 1.9184006344307272, 0.8647608854374088, 0.0), # 95
(11.845891787439614, 9.463658781362009, 9.573863425925927, 10.234228532608697, 8.756187363834421, 4.188854732510288, 3.966522253345782, 3.250382716049383, 4.493685802469135, 1.9142983877995645, 1.4964333333333335, 0.8668271604938274, 0.0, 11.780225694444445, 9.5350987654321, 7.482166666666667, 5.742895163398693, 8.98737160493827, 4.5505358024691365, 3.966522253345782, 2.9920390946502056, 4.3780936819172105, 3.411409510869566, 1.9147726851851854, 0.8603326164874555, 0.0), # 96
(11.810726713186616, 9.414847942386832, 9.555532321673525, 10.208206129227051, 8.74158637940773, 4.178533866788599, 3.948913914537008, 3.237216963877458, 4.484898193872885, 1.9075010860969905, 1.4903891074487565, 0.864374244940197, 0.0, 11.758297968106996, 9.508116694342165, 7.451945537243782, 5.7225032582909705, 8.96979638774577, 4.532103749428441, 3.948913914537008, 2.984667047706142, 4.370793189703865, 3.402735376409018, 1.911106464334705, 0.8558952674897121, 0.0), # 97
(11.775173447843981, 9.365960002654985, 9.53701397462277, 10.181956914251208, 8.72677237150004, 4.168164349946655, 3.931267120840105, 3.22425422953818, 4.476083699131229, 1.9006862777374327, 1.484328861716581, 0.8619051572690299, 0.0, 11.736077031893004, 9.480956729959328, 7.421644308582906, 5.702058833212297, 8.952167398262459, 4.513955921353452, 3.931267120840105, 2.9772602499618963, 4.36338618575002, 3.3939856380837368, 1.9074027949245542, 0.8514509093322715, 0.0), # 98
(11.739286956521738, 9.317017741935484, 9.5183125, 10.15549972826087, 8.711764705882352, 4.157766666666667, 3.913588235294118, 3.2115, 4.46725, 1.893854117647059, 1.4782612440191387, 0.859421052631579, 0.0, 11.71359375, 9.453631578947368, 7.391306220095694, 5.681562352941175, 8.9345, 4.4961, 3.913588235294118, 2.9698333333333333, 4.355882352941176, 3.385166576086957, 1.9036625000000003, 0.8470016129032258, 0.0), # 99
(11.703122204329933, 9.268043939997343, 9.49943201303155, 10.128853411835749, 8.696582748325667, 4.147361301630848, 3.895883620938087, 3.1989597622313672, 4.458404778235025, 1.8870047607520377, 1.4721949022387621, 0.8569230861790968, 0.0, 11.690878986625515, 9.426153947970063, 7.36097451119381, 5.661014282256112, 8.91680955647005, 4.4785436671239145, 3.895883620938087, 2.9624009297363205, 4.348291374162834, 3.376284470611917, 1.89988640260631, 0.8425494490906678, 0.0), # 100
(11.6667341563786, 9.219061376609584, 9.480376628943759, 10.102036805555556, 8.681245864600983, 4.136968739521414, 3.878159640811057, 3.1866390032007312, 4.449555715592135, 1.8801383619785366, 1.4661384842577825, 0.8544124130628354, 0.0, 11.667963605967076, 9.398536543691188, 7.330692421288911, 5.640415085935608, 8.89911143118427, 4.461294604481024, 3.878159640811057, 2.9549776710867244, 4.340622932300492, 3.367345601851853, 1.8960753257887522, 0.8380964887826896, 0.0), # 101
(11.630177777777778, 9.170092831541218, 9.461150462962962, 10.07506875, 8.665773420479303, 4.126609465020577, 3.8604226579520695, 3.174543209876543, 4.44071049382716, 1.8732550762527238, 1.4601006379585326, 0.8518901884340482, 0.0, 11.644878472222222, 9.37079207277453, 7.300503189792663, 5.61976522875817, 8.88142098765432, 4.44436049382716, 3.8604226579520695, 2.947578189300412, 4.332886710239651, 3.358356250000001, 1.8922300925925928, 0.8336448028673837, 0.0), # 102
(11.593508033637502, 9.121161084561264, 9.4417576303155, 10.047968085748792, 8.650184781731623, 4.116303962810547, 3.842679035400168, 3.162677869227252, 4.43187679469593, 1.8663550585007669, 1.4540900112233446, 0.8493575674439874, 0.0, 11.621654449588474, 9.342933241883859, 7.270450056116723, 5.599065175502299, 8.86375358939186, 4.427749016918153, 3.842679035400168, 2.940217116293248, 4.325092390865811, 3.3493226952495982, 1.8883515260631, 0.8291964622328422, 0.0), # 103
(11.556779889067812, 9.072288915438735, 9.422202246227709, 10.020753653381641, 8.634499314128943, 4.10607271757354, 3.8249351361943953, 3.151048468221308, 4.423062299954275, 1.8594384636488344, 1.44811525193455, 0.8468157052439055, 0.0, 11.598322402263374, 9.314972757682959, 7.24057625967275, 5.578315390946502, 8.84612459990855, 4.411467855509831, 3.8249351361943953, 2.9329090839811003, 4.317249657064472, 3.3402512177938815, 1.884440449245542, 0.8247535377671579, 0.0), # 104
(11.520048309178742, 9.023499103942651, 9.402488425925926, 9.99344429347826, 8.618736383442265, 4.09593621399177, 3.8071973233737944, 3.1396604938271606, 4.414274691358024, 1.8525054466230941, 1.4421850079744816, 0.8442657569850553, 0.0, 11.574913194444443, 9.286923326835607, 7.210925039872408, 5.557516339869281, 8.828549382716048, 4.395524691358025, 3.8071973233737944, 2.9256687242798356, 4.309368191721132, 3.331148097826088, 1.8804976851851853, 0.8203181003584229, 0.0), # 105
(11.483368259080336, 8.974814429842029, 9.382620284636488, 9.966058846618358, 8.602915355442589, 4.0859149367474465, 3.7894719599774067, 3.12851943301326, 4.405521650663008, 1.8455561623497139, 1.436307927225471, 0.8417088778186895, 0.0, 11.551457690329217, 9.258797656005584, 7.181539636127354, 5.53666848704914, 8.811043301326016, 4.379927206218564, 3.7894719599774067, 2.918510669105319, 4.301457677721294, 3.3220196155394537, 1.8765240569272976, 0.81589222089473, 0.0), # 106
(11.446794703882626, 8.926257672905882, 9.362601937585735, 9.938616153381641, 8.58705559590091, 4.076029370522787, 3.7717654090442765, 3.117630772748057, 4.396810859625057, 1.838590765754862, 1.4304926575698504, 0.8391462228960604, 0.0, 11.527986754115226, 9.230608451856664, 7.152463287849251, 5.515772297264585, 8.793621719250114, 4.36468308184728, 3.7717654090442765, 2.911449550373419, 4.293527797950455, 3.312872051127215, 1.8725203875171472, 0.8114779702641711, 0.0), # 107
(11.410382608695652, 8.877851612903227, 9.3424375, 9.911135054347826, 8.571176470588235, 4.0663, 3.7540840336134447, 3.107, 4.3881499999999996, 1.8316094117647064, 1.4247478468899522, 0.8365789473684213, 0.0, 11.504531250000001, 9.202368421052633, 7.12373923444976, 5.494828235294118, 8.776299999999999, 4.3498, 3.7540840336134447, 2.9045, 4.285588235294117, 3.3037116847826096, 1.8684875000000005, 0.8070774193548388, 0.0), # 108
(11.374186938629451, 8.82961902960308, 9.322131087105625, 9.883634390096615, 8.555297345275559, 4.056747309861302, 3.7364341967239567, 3.0966326017375403, 4.379546753543667, 1.8246122553054145, 1.4190821430681082, 0.8340082063870239, 0.0, 11.48112204218107, 9.174090270257262, 7.09541071534054, 5.473836765916242, 8.759093507087334, 4.335285642432557, 3.7364341967239567, 2.8976766499009297, 4.277648672637779, 3.294544796698873, 1.864426217421125, 0.8026926390548256, 0.0), # 109
(11.338262658794058, 8.78158270277446, 9.301686814128946, 9.85613300120773, 8.539437585733882, 4.047391784788904, 3.7188222614148536, 3.0865340649291264, 4.371008802011888, 1.8175994513031553, 1.4135041939866502, 0.8314351551031215, 0.0, 11.457789994855966, 9.145786706134334, 7.067520969933251, 5.452798353909465, 8.742017604023776, 4.321147690900777, 3.7188222614148536, 2.8909941319920742, 4.269718792866941, 3.2853776670692443, 1.8603373628257893, 0.7983257002522237, 0.0), # 110
(11.302664734299517, 8.733765412186381, 9.281108796296298, 9.82864972826087, 8.523616557734204, 4.038253909465022, 3.7012545907251786, 3.0767098765432097, 4.3625438271604935, 1.8105711546840961, 1.4080226475279107, 0.8288609486679663, 0.0, 11.434565972222222, 9.117470435347629, 7.040113237639553, 5.431713464052287, 8.725087654320987, 4.307393827160493, 3.7012545907251786, 2.8844670781893007, 4.261808278867102, 3.2762165760869575, 1.8562217592592598, 0.7939786738351257, 0.0), # 111
(11.26744813025586, 8.686189937607857, 9.26040114883402, 9.801203411835749, 8.507853627047526, 4.029354168571865, 3.6837375476939744, 3.0671655235482396, 4.354159510745312, 1.803527520374405, 1.402646151574222, 0.8262867422328111, 0.0, 11.411480838477365, 9.08915416456092, 7.013230757871109, 5.4105825611232135, 8.708319021490624, 4.294031732967535, 3.6837375476939744, 2.8781101204084747, 4.253926813523763, 3.2670678039452503, 1.8520802297668042, 0.7896536306916234, 0.0), # 112
(11.232605068443652, 8.638958480664547, 9.239617828252069, 9.773850494242836, 8.492140544138962, 4.02070883845016, 3.6663155781940615, 3.057926284390303, 4.3458851245034475, 1.7964914209838192, 1.3973847812305735, 0.8237192936504428, 0.0, 11.388532681011865, 9.06091223015487, 6.9869239061528665, 5.389474262951456, 8.691770249006895, 4.281096798146424, 3.6663155781940615, 2.8719348846072568, 4.246070272069481, 3.257950164747613, 1.8479235656504138, 0.7853598618785952, 0.0), # 113
(11.197777077480078, 8.592536901878088, 9.219045675021619, 9.746810479149604, 8.47631468365306, 4.012298225970931, 3.649210925046347, 3.04910562975256, 4.337847614285224, 1.7895945503738353, 1.3922488674226394, 0.8211912172112975, 0.0, 11.365530496992042, 9.033103389324271, 6.961244337113197, 5.368783651121505, 8.675695228570447, 4.268747881653584, 3.649210925046347, 2.8659273042649507, 4.23815734182653, 3.248936826383202, 1.8438091350043238, 0.7811397183525536, 0.0), # 114
(11.162861883604794, 8.546941918551349, 9.198696932707318, 9.7200760546636, 8.46032614231088, 4.004100458749136, 3.6324357901149367, 3.0407013271393546, 4.330049991467515, 1.7828475983964234, 1.3872309022854188, 0.8187037582558852, 0.0, 11.342407957992451, 9.005741340814735, 6.936154511427093, 5.348542795189269, 8.66009998293503, 4.256981857995097, 3.6324357901149367, 2.8600717562493823, 4.23016307115544, 3.2400253515545345, 1.8397393865414637, 0.7769947198683046, 0.0), # 115
(11.127815847885161, 8.502107109420871, 9.178532189983873, 9.693599535239764, 8.444150821107023, 3.9960962141009686, 3.6159628905167356, 3.0326901564494966, 4.322472535691132, 1.7762380075348645, 1.3823211862542963, 0.8162523197487347, 0.0, 11.319128711707068, 8.97877551723608, 6.911605931271482, 5.328714022604592, 8.644945071382264, 4.245766219029295, 3.6159628905167356, 2.854354438643549, 4.222075410553511, 3.231199845079922, 1.835706437996775, 0.7729188281291702, 0.0), # 116
(11.092595331388527, 8.457966053223192, 9.158512035525986, 9.66733323533302, 8.427764621036088, 3.988266169342624, 3.5997649433686516, 3.0250488975817924, 4.315095526596881, 1.769753220272439, 1.3775100197646568, 0.8138323046543751, 0.0, 11.295656405829869, 8.952155351198124, 6.887550098823283, 5.309259660817316, 8.630191053193762, 4.23506845661451, 3.5997649433686516, 2.8487615495304452, 4.213882310518044, 3.222444411777674, 1.8317024071051975, 0.768906004838472, 0.0), # 117
(11.057156695182252, 8.414452328694855, 9.138597058008367, 9.6412294693983, 8.411143443092673, 3.980591001790297, 3.583814665787589, 3.0177543304350483, 4.307899243825574, 1.7633806790924282, 1.3727877032518847, 0.811439115937335, 0.0, 11.271954688054828, 8.925830275310684, 6.863938516259424, 5.290142037277283, 8.615798487651148, 4.224856062609067, 3.583814665787589, 2.843279286993069, 4.205571721546336, 3.213743156466101, 1.8277194116016737, 0.7649502116995325, 0.0), # 118
(11.02145630033369, 8.3714995145724, 9.118747846105723, 9.615240551890535, 8.394263188271376, 3.973051388760183, 3.5680847748904534, 3.0107832349080725, 4.300863967018017, 1.757107826478112, 1.3681445371513656, 0.8090681565621435, 0.0, 11.247987206075917, 8.899749722183577, 6.840722685756828, 5.271323479434335, 8.601727934036035, 4.215096528871301, 3.5680847748904534, 2.8378938491144163, 4.197131594135688, 3.2050801839635126, 1.8237495692211447, 0.761045410415673, 0.0), # 119
(10.985450507910194, 8.329041189592374, 9.098924988492762, 9.589318797264655, 8.377099757566796, 3.965628007568476, 3.5525479877941515, 3.0041123908996714, 4.293969975815023, 1.7509221049127721, 1.3635708218984832, 0.8067148294933297, 0.0, 11.223717607587115, 8.873863124426626, 6.817854109492416, 5.252766314738315, 8.587939951630046, 4.20575734725954, 3.5525479877941515, 2.8325914339774827, 4.188549878783398, 3.1964395990882193, 1.8197849976985525, 0.7571855626902159, 0.0), # 120
(10.949095678979122, 8.287010932491311, 9.079089073844187, 9.56341651997559, 8.359629051973535, 3.9583015355313718, 3.5371770216155882, 2.9977185783086533, 4.2871975498573995, 1.7448109568796892, 1.3590568579286233, 0.8043745376954222, 0.0, 11.199109540282393, 8.848119914649644, 6.795284289643115, 5.234432870639067, 8.574395099714799, 4.196806009632114, 3.5371770216155882, 2.8273582396652652, 4.179814525986767, 3.1878055066585307, 1.8158178147688375, 0.753364630226483, 0.0), # 121
(10.912348174607825, 8.245342322005756, 9.059200690834711, 9.537486034478269, 8.341826972486187, 3.951052649965064, 3.5219445934716704, 2.9915785770338243, 4.2805269687859555, 1.7387618248621435, 1.3545929456771704, 0.8020426841329501, 0.0, 11.174126651855724, 8.82246952546245, 6.772964728385852, 5.216285474586429, 8.561053937571911, 4.1882100078473545, 3.5219445934716704, 2.8221804642607595, 4.170913486243093, 3.1791620114927572, 1.8118401381669422, 0.7495765747277962, 0.0), # 122
(10.875164355863662, 8.20396893687225, 9.039220428139036, 9.511479655227625, 8.323669420099352, 3.9438620281857477, 3.506823420479303, 2.9856691669739917, 4.273938512241501, 1.7327621513434166, 1.3501693855795087, 0.7997146717704421, 0.0, 11.148732590001085, 8.796861389474863, 6.750846927897544, 5.1982864540302485, 8.547877024483002, 4.1799368337635885, 3.506823420479303, 2.8170443058469625, 4.161834710049676, 3.170493218409209, 1.8078440856278073, 0.7458153578974774, 0.0), # 123
(10.837500583813984, 8.162824355827334, 9.01910887443187, 9.485349696678588, 8.30513229580763, 3.9367103475096172, 3.4917862197553915, 2.979967128027963, 4.267412459864846, 1.7267993788067886, 1.345776478071024, 0.7973859035724276, 0.0, 11.122891002412453, 8.771244939296702, 6.728882390355119, 5.180398136420364, 8.534824919729692, 4.171953979239149, 3.4917862197553915, 2.8119359625068694, 4.152566147903815, 3.1617832322261967, 1.803821774886374, 0.7420749414388487, 0.0), # 124
(10.79931321952615, 8.121842157607551, 8.998826618387923, 9.459048473286083, 8.286191500605618, 3.9295782852528696, 3.4768057084168436, 2.9744492400945455, 4.260929091296797, 1.7208609497355405, 1.3414045235871004, 0.7950517825034348, 0.0, 11.096565536783794, 8.745569607537782, 6.707022617935502, 5.16258284920662, 8.521858182593594, 4.164228936132364, 3.4768057084168436, 2.806841632323478, 4.143095750302809, 3.153016157762029, 1.799765323677585, 0.7383492870552321, 0.0), # 125
(10.760558624067514, 8.080955920949442, 8.978334248681898, 9.432528299505048, 8.266822935487914, 3.9224465187316975, 3.461854603580562, 2.969092283072546, 4.254468686178167, 1.7149343066129532, 1.3370438225631227, 0.7927077115279934, 0.0, 11.069719840809094, 8.719784826807926, 6.685219112815614, 5.144802919838858, 8.508937372356334, 4.156729196301565, 3.461854603580562, 2.801747513379784, 4.133411467743957, 3.144176099835017, 1.79566684973638, 0.7346323564499494, 0.0), # 126
(10.721193158505432, 8.040099224589545, 8.957592353988504, 9.405741489790408, 8.247002501449117, 3.915295725262296, 3.4469056223634564, 2.9638730368607726, 4.248011524149763, 1.7090068919223076, 1.3326846754344757, 0.7903490936106315, 0.0, 11.042317562182317, 8.693840029716947, 6.6634233771723785, 5.127020675766921, 8.496023048299525, 4.149422251605082, 3.4469056223634564, 2.7966398037587825, 4.1235012507245585, 3.1352471632634704, 1.7915184707977012, 0.7309181113263225, 0.0), # 127
(10.681173183907255, 7.999205647264407, 8.93656152298245, 9.3786403585971, 8.226706099483831, 3.908106582160861, 3.431931481882429, 2.958768281358031, 4.241537884852393, 1.703066148146884, 1.328317382636545, 0.7879713317158789, 0.0, 11.014322348597444, 8.667684648874667, 6.641586913182724, 5.109198444440651, 8.483075769704786, 4.1422755939012434, 3.431931481882429, 2.791504701543472, 4.1133530497419155, 3.1262134528657004, 1.7873123045964903, 0.7272005133876734, 0.0), # 128
(10.640455061340337, 7.958208767710564, 8.91520234433844, 9.351177220380043, 8.205909630586648, 3.9008597667435865, 3.4169048992543876, 2.95375479646313, 4.235028047926869, 1.697099517769964, 1.3239322446047141, 0.7855698288082636, 0.0, 10.985697847748446, 8.641268116890899, 6.619661223023571, 5.0912985533098905, 8.470056095853739, 4.135256715048382, 3.4169048992543876, 2.7863284048168473, 4.102954815293324, 3.117059073460015, 1.783040468867688, 0.7234735243373241, 0.0), # 129
(10.598995151872039, 7.917042164664562, 8.893475406731179, 9.323304389594178, 8.18458899575217, 3.893535956326666, 3.4017985915962377, 2.948809362074875, 4.228462293014, 1.6910944432748274, 1.3195195617743691, 0.7831399878523152, 0.0, 10.956407707329298, 8.614539866375466, 6.5975978088718445, 5.073283329824481, 8.456924586028, 4.128333106904826, 3.4017985915962377, 2.781097111661904, 4.092294497876085, 3.1077681298647266, 1.7786950813462359, 0.7197311058785967, 0.0), # 130
(10.556749816569713, 7.8756394168629384, 8.87134129883538, 9.294974180694428, 8.162720095974995, 3.886115828226296, 3.3865852760248853, 2.943908758092075, 4.221820899754594, 1.685038367144756, 1.3150696345808937, 0.7806772118125626, 0.0, 10.926415575033973, 8.587449329938186, 6.575348172904468, 5.055115101434266, 8.443641799509187, 4.121472261328905, 3.3865852760248853, 2.77579702016164, 4.081360047987498, 3.0983247268981433, 1.7742682597670765, 0.7159672197148127, 0.0), # 131
(10.51367541650071, 7.833934103042237, 8.848760609325746, 9.266138908135728, 8.140278832249722, 3.878580059758672, 3.3712376696572353, 2.9390297644135366, 4.215084147789462, 1.6789187318630299, 1.310572763459673, 0.7781769036535342, 0.0, 10.89568509855645, 8.559945940188875, 6.552863817298364, 5.0367561955890885, 8.430168295578923, 4.114641670178951, 3.3712376696572353, 2.770414328399051, 4.070139416124861, 3.088712969378577, 1.7697521218651495, 0.7121758275492944, 0.0), # 132
(10.469728312732395, 7.791859801938998, 8.825693926876983, 9.236750886373006, 8.117241105570947, 3.870909328239987, 3.3557284896101933, 2.934149160938066, 4.2082323167594105, 1.67272297991293, 1.306019248846092, 0.7756344663397593, 0.0, 10.864179925590703, 8.531979129737351, 6.53009624423046, 5.018168939738788, 8.416464633518821, 4.107808825313293, 3.3557284896101933, 2.764935234457133, 4.058620552785474, 3.078916962124336, 1.765138785375397, 0.7083508910853636, 0.0), # 133
(10.424864866332113, 7.749350092289764, 8.802101840163804, 9.206762429861191, 8.093582816933273, 3.863084310986436, 3.3400304530006673, 2.929243727564472, 4.201245686305251, 1.6664385537777375, 1.3013993911755357, 0.7730453028357667, 0.0, 10.831863703830699, 8.503498331193432, 6.506996955877678, 4.9993156613332115, 8.402491372610502, 4.100941218590261, 3.3400304530006673, 2.7593459364188826, 4.046791408466636, 3.0689208099537315, 1.7604203680327608, 0.7044863720263422, 0.0), # 134
(10.379041438367224, 7.706338552831077, 8.777944937860909, 9.17612585305522, 8.069279867331296, 3.8550856853142146, 3.3241162769455603, 2.92429024419156, 4.194104536067791, 1.6600528959407332, 1.2967034908833885, 0.7704048161060852, 0.0, 10.798700080970423, 8.474452977166937, 6.483517454416942, 4.980158687822199, 8.388209072135583, 4.094006341868184, 3.3241162769455603, 2.753632632367296, 4.034639933665648, 3.0587086176850744, 1.755588987572182, 0.7005762320755525, 0.0), # 135
(10.332214389905081, 7.6627587622994735, 8.753183808643008, 9.144793470410015, 8.044308157759612, 3.8468941285395175, 3.3079586785617807, 2.9192654907181383, 4.186789145687842, 1.653553448885197, 1.2919218484050357, 0.7677084091152441, 0.0, 10.764652704703844, 8.444792500267685, 6.459609242025177, 4.96066034665559, 8.373578291375685, 4.086971687005394, 3.3079586785617807, 2.7477815203853697, 4.022154078879806, 3.0482644901366727, 1.750636761728602, 0.6966144329363159, 0.0), # 136
(10.28434008201304, 7.618544299431501, 8.72777904118481, 9.112717596380511, 8.018643589212827, 3.838490317978539, 3.291530374966233, 2.9141462470430146, 4.179279794806213, 1.6469276550944107, 1.2870447641758613, 0.764951484827772, 0.0, 10.729685222724932, 8.41446633310549, 6.435223820879306, 4.940782965283231, 8.358559589612426, 4.079804745860221, 3.291530374966233, 2.741778798556099, 4.0093217946064135, 3.037572532126838, 1.7455558082369622, 0.6925949363119547, 0.0), # 137
(10.235374875758456, 7.573628742963698, 8.701691224161017, 9.079850545421637, 7.992262062685534, 3.8298549309474748, 3.2748040832758227, 2.908909293064995, 4.1715567630637125, 1.6401629570516543, 1.2820625386312503, 0.7621294462081979, 0.0, 10.693761282727667, 8.383423908290176, 6.410312693156252, 4.920488871154961, 8.343113526127425, 4.0724730102909925, 3.2748040832758227, 2.735610664962482, 3.996131031342767, 3.02661684847388, 1.7403382448322038, 0.6885117039057909, 0.0), # 138
(10.185275132208682, 7.527945671632606, 8.67488094624634, 9.046144631988323, 7.965139479172331, 3.8209686447625186, 3.2577525206074553, 2.903531408682887, 4.163600330101148, 1.6332467972402094, 1.276965472206588, 0.7592376962210506, 0.0, 10.656844532406023, 8.351614658431556, 6.38482736103294, 4.899740391720627, 8.327200660202296, 4.064943972156042, 3.2577525206074553, 2.729263317687513, 3.9825697395861654, 3.0153815439961082, 1.7349761892492683, 0.6843586974211461, 0.0), # 139
(10.133997212431076, 7.481428664174767, 8.647308796115487, 9.011552170535499, 7.937251739667823, 3.811812136739866, 3.240348404078038, 2.897989373795498, 4.155390775559333, 1.626166618143356, 1.2717438653372588, 0.7562716378308593, 0.0, 10.618898619453978, 8.31898801613945, 6.358719326686294, 4.878499854430067, 8.310781551118666, 4.0571851233136975, 3.240348404078038, 2.7227229548141896, 3.9686258698339114, 3.003850723511834, 1.7294617592230976, 0.6801298785613425, 0.0), # 140
(10.081497477492995, 7.4340112993267216, 8.61893536244316, 8.976025475518098, 7.908574745166602, 3.802366084195711, 3.222564450804477, 2.892259968301635, 4.146908379079072, 1.6189098622443758, 1.2663880184586478, 0.7532266740021526, 0.0, 10.579887191565495, 8.285493414023676, 6.331940092293238, 4.856729586733126, 8.293816758158144, 4.049163955622289, 3.222564450804477, 2.7159757744255075, 3.954287372583301, 2.9920084918393663, 1.7237870724886322, 0.675819209029702, 0.0), # 141
(10.027732288461786, 7.385627155825012, 8.58972123390407, 8.939516861391049, 7.879084396663268, 3.792611164446249, 3.2043733779036754, 2.8863199721001056, 4.138133420301177, 1.6114639720265487, 1.2608882320061394, 0.7500982076994595, 0.0, 10.539773896434559, 8.251080284694053, 6.304441160030697, 4.834391916079644, 8.276266840602354, 4.040847960940148, 3.2043733779036754, 2.7090079746044635, 3.939542198331634, 2.9798389537970165, 1.7179442467808141, 0.6714206505295467, 0.0), # 142
(9.972658006404808, 7.336209812406179, 8.559626999172925, 8.901978642609278, 7.848756595152423, 3.7825280548076745, 3.185747902492541, 2.880146165089716, 4.129046178866458, 1.6038163899731561, 1.2552348064151186, 0.746881641887309, 0.0, 10.49852238175514, 8.215698060760397, 6.276174032075593, 4.811449169919467, 8.258092357732917, 4.032204631125603, 3.185747902492541, 2.701805753434053, 3.9243782975762116, 2.967326214203093, 1.7119253998345851, 0.6669281647641981, 0.0), # 143
(9.916230992389421, 7.285692847806764, 8.528613246924428, 8.86336313362772, 7.817567241628662, 3.772097432596183, 3.1666607416879793, 2.8737153271692746, 4.119626934415724, 1.5959545585674784, 1.2494180421209704, 0.7435723795302299, 0.0, 10.456096295221217, 8.179296174832528, 6.247090210604851, 4.787863675702434, 8.239253868831447, 4.023201458036985, 3.1666607416879793, 2.6943553089972734, 3.908783620814331, 2.954454377875907, 1.7057226493848856, 0.6623357134369786, 0.0), # 144
(9.858407607482972, 7.234009840763308, 8.496640565833289, 8.823622648901305, 7.785492237086586, 3.7612999751279688, 3.147084612606896, 2.867004238237588, 4.109855966589781, 1.5878659202927967, 1.2434282395590792, 0.7401658235927514, 0.0, 10.41245928452676, 8.141824059520264, 6.217141197795395, 4.763597760878389, 8.219711933179562, 4.013805933532623, 3.147084612606896, 2.6866428393771202, 3.892746118543293, 2.9412075496337686, 1.699328113166658, 0.6576372582512099, 0.0), # 145
(9.79914421275282, 7.181094370012356, 8.463669544574216, 8.782709502884963, 7.752507482520793, 3.750116359719226, 3.126992232366198, 2.8599896781934633, 4.099713555029442, 1.5795379176323916, 1.2372556991648298, 0.7366573770394019, 0.0, 10.367574997365741, 8.103231147433421, 6.186278495824149, 4.738613752897173, 8.199427110058885, 4.0039855494708485, 3.126992232366198, 2.67865454265659, 3.8762537412603963, 2.927569834294988, 1.6927339089148434, 0.6528267609102142, 0.0), # 146
(9.73839716926632, 7.126880014290443, 8.42966077182191, 8.740576010033621, 7.71858887892588, 3.7385272636861506, 3.1063563180827884, 2.8526484269357075, 4.0891799793755155, 1.570957993069544, 1.2308907213736073, 0.7330424428347111, 0.0, 10.321407081432142, 8.06346687118182, 6.154453606868036, 4.712873979208631, 8.178359958751031, 3.9937077977099906, 3.1063563180827884, 2.670376616918679, 3.85929443946294, 2.9135253366778744, 1.6859321543643822, 0.6478981831173131, 0.0), # 147
(9.676122838090825, 7.071300352334116, 8.394574836251083, 8.697174484802217, 7.6837123272964485, 3.726513364344937, 3.085149586873576, 2.8449572643631287, 4.078235519268811, 1.5621135890875346, 1.2243236066207965, 0.729316423943207, 0.0, 10.27391918441993, 8.022480663375276, 6.1216180331039824, 4.686340767262602, 8.156471038537623, 3.9829401701083804, 3.085149586873576, 2.6617952602463837, 3.8418561636482242, 2.899058161600739, 1.6789149672502168, 0.6428454865758287, 0.0), # 148
(9.612277580293695, 7.014288962879912, 8.358372326536443, 8.652457241645672, 7.647853728627096, 3.71405533901178, 3.0633447558554643, 2.8368929703745334, 4.0668604543501345, 1.5529921481696445, 1.2175446553417821, 0.7254747233294191, 0.0, 10.225074954023084, 7.980221956623609, 6.08772327670891, 4.658976444508932, 8.133720908700269, 3.971650158524347, 3.0633447558554643, 2.6528966707226997, 3.823926864313548, 2.8841524138818913, 1.671674465307289, 0.637662632989083, 0.0), # 149
(9.546817756942277, 6.955779424664377, 8.321013831352694, 8.606376595018924, 7.610988983912421, 3.7011338650028747, 3.04091454214536, 2.828432324868728, 4.0550350642603, 1.5435811127991534, 1.2105441679719486, 0.7215127439578762, 0.0, 10.174838037935576, 7.936640183536638, 6.0527208398597425, 4.630743338397459, 8.1100701285206, 3.95980525481622, 3.04091454214536, 2.6436670464306244, 3.8054944919562104, 2.8687921983396416, 1.6642027662705388, 0.632343584060398, 0.0), # 150
(9.47969972910393, 6.895705316424048, 8.282459939374542, 8.558884859376896, 7.573093994147021, 3.6877296196344136, 3.01783166286017, 2.8195521077445216, 4.042739628640115, 1.5338679254593437, 1.203312444946681, 0.7174258887931072, 0.0, 10.123172083851381, 7.891684776724178, 6.016562224733405, 4.601603776378029, 8.08547925728023, 3.9473729508423303, 3.01783166286017, 2.6340925854531525, 3.7865469970735104, 2.8529616197922993, 1.6564919878749085, 0.6268823014930954, 0.0), # 151
(9.41087985784601, 6.83400021689547, 8.242671239276701, 8.509934349174525, 7.534144660325495, 3.6738232802225945, 2.9940688351167988, 2.8102290989007206, 4.029954427130388, 1.5238400286334952, 1.1958397867013644, 0.713209560799641, 0.0, 10.070040739464476, 7.84530516879605, 5.979198933506821, 4.5715200859004845, 8.059908854260776, 3.9343207384610093, 2.9940688351167988, 2.6241594858732817, 3.7670723301627476, 2.836644783058176, 1.6485342478553402, 0.6212727469904974, 0.0), # 152
(9.340314504235872, 6.770597704815181, 8.201608319733868, 8.459477378866739, 7.4941168834424445, 3.659395524083611, 2.9695987760321514, 2.800440078236131, 4.016659739371929, 1.513484864804889, 1.1881164936713833, 0.7088591629420063, 0.0, 10.015407652468832, 7.797450792362069, 5.940582468356916, 4.5404545944146655, 8.033319478743858, 3.9206161095305836, 2.9695987760321514, 2.6138539457740078, 3.7470584417212223, 2.81982579295558, 1.6403216639467737, 0.6155088822559257, 0.0), # 153
(9.267960029340873, 6.705431358919725, 8.159231769420758, 8.407466262908468, 7.4529865644924636, 3.644427028533658, 2.944394202723137, 2.7901618256495615, 4.002835845005546, 1.5027898764568062, 1.1801328662921224, 0.7043700981847325, 0.0, 9.959236470558428, 7.748071080032056, 5.900664331460612, 4.508369629370417, 8.005671690011091, 3.9062265559093863, 2.944394202723137, 2.603162163238327, 3.7264932822462318, 2.802488754302823, 1.631846353884152, 0.6095846689927024, 0.0), # 154
(9.193772794228362, 6.638434757945644, 8.115502177012075, 8.35385331575464, 7.4107296044701565, 3.62889847088893, 2.9184278323066564, 2.779371121039818, 3.988463023672051, 1.4917425060725265, 1.1718792049989668, 0.6997377694923482, 0.0, 9.901490841427231, 7.6971154644158295, 5.859396024994833, 4.4752275182175785, 7.976926047344102, 3.8911195694557454, 2.9184278323066564, 2.5920703363492357, 3.7053648022350782, 2.7846177719182137, 1.6231004354024152, 0.6034940689041496, 0.0), # 155
(9.117709159965697, 6.569541480629476, 8.070380131182526, 8.298590851860187, 7.367321904370117, 3.612790528465623, 2.8916723818996197, 2.7680447443057092, 3.9735215550122502, 1.480330196135332, 1.163345810227301, 0.6949575798293822, 0.0, 9.842134412769221, 7.644533378123204, 5.816729051136504, 4.440990588405995, 7.9470431100245005, 3.875262642027993, 2.8916723818996197, 2.5805646631897305, 3.6836609521850585, 2.766196950620063, 1.6140760262365055, 0.5972310436935888, 0.0), # 156
(9.039725487620235, 6.498685105707764, 8.023826220606818, 8.241631185680044, 7.322739365186948, 3.59608387857993, 2.864100568618931, 2.756159475346041, 3.957991718666955, 1.4685403891285025, 1.1545229824125098, 0.6900249321603636, 0.0, 9.781130832278372, 7.590274253763999, 5.772614912062549, 4.405621167385506, 7.91598343733391, 3.8586232654844577, 2.864100568618931, 2.568631341842807, 3.661369682593474, 2.7472103952266815, 1.6047652441213638, 0.5907895550643424, 0.0), # 157
(8.957617135686286, 6.424498432849483, 7.973591953902356, 8.180792623486118, 7.274944884696797, 3.5777171334219773, 2.8350640325567142, 2.742898476174686, 3.9406648366396384, 1.4560097748873433, 1.1451191505077887, 0.6847599564194339, 0.0, 9.715783031298415, 7.532359520613772, 5.7255957525389425, 4.368029324662029, 7.881329673279277, 3.840057866644561, 2.8350640325567142, 2.555512238158555, 3.6374724423483986, 2.7269308744953733, 1.5947183907804712, 0.5840453120772259, 0.0), # 158
(8.858744120374082, 6.3393718515594255, 7.906737818402987, 8.103579442909608, 7.212153047825302, 3.551582753604972, 2.8009276580314295, 2.7236067663821912, 3.9145709044888575, 1.4406842982296237, 1.133483387123799, 0.6781362523683109, 0.0, 9.630513176304232, 7.459498776051419, 5.667416935618994, 4.322052894688871, 7.829141808977715, 3.813049472935068, 2.8009276580314295, 2.5368448240035515, 3.606076523912651, 2.7011931476365363, 1.5813475636805976, 0.5763065319599479, 0.0), # 159
(8.741846513885172, 6.242606401394785, 7.821920957955889, 8.008719759367974, 7.133136105077435, 3.517038907233379, 2.7613462490302703, 2.6977995947636733, 3.8789700908914604, 1.4223616955588683, 1.119451901721908, 0.6700501948887847, 0.0, 9.523704730672296, 7.370552143776631, 5.59725950860954, 4.267085086676604, 7.757940181782921, 3.7769194326691427, 2.7613462490302703, 2.512170648023842, 3.5665680525387176, 2.669573253122658, 1.5643841915911778, 0.5675096728540715, 0.0), # 160
(8.607866465503152, 6.134832954888515, 7.7200469719103095, 7.897115253381055, 7.038714499425689, 3.4745040690992197, 2.716608867604126, 2.66580026655489, 3.8343319067996067, 1.4011974579512814, 1.1031483309199415, 0.6605767468907572, 0.0, 9.396448853782916, 7.266344215798328, 5.515741654599707, 4.203592373853843, 7.668663813599213, 3.7321203731768464, 2.716608867604126, 2.481788620785157, 3.5193572497128445, 2.632371751127019, 1.5440093943820619, 0.557712086808047, 0.0), # 161
(8.457746124511628, 6.016682384573562, 7.602021459615496, 7.769667605468694, 6.929708673842563, 3.424396713994519, 2.6670045758038854, 2.627932086991601, 3.781125863165454, 1.3773470764830695, 1.0846963113357242, 0.6497908712841294, 0.0, 9.2498367050164, 7.147699584125422, 5.42348155667862, 4.132041229449208, 7.562251726330908, 3.6791049217882414, 2.6670045758038854, 2.4459976528532277, 3.4648543369212814, 2.5898892018228983, 1.5204042919230993, 0.5469711258703239, 0.0), # 162
(8.292427640194196, 5.888785562982875, 7.468750020420702, 7.6272784961507405, 6.806939071300549, 3.367135316711301, 2.61282243568044, 2.5845183613095624, 3.719821470941162, 1.3509660422304377, 1.0642194795870819, 0.6377675309788032, 0.0, 9.084959443753055, 7.015442840766835, 5.321097397935408, 4.052898126691312, 7.439642941882324, 3.6183257058333878, 2.61282243568044, 2.405096654793786, 3.4034695356502747, 2.5424261653835805, 1.4937500040841403, 0.5353441420893524, 0.0), # 163
(8.11285316183446, 5.751773362649402, 7.321138253675176, 7.470849605947036, 6.67122613477215, 3.3031383520415907, 2.5543515092846794, 2.5358823947445344, 3.650888241078889, 1.3222098462695906, 1.0418414722918394, 0.6245816888846804, 0.0, 8.902908229373192, 6.870398577731482, 5.209207361459196, 3.966629538808771, 7.301776482157778, 3.550235352642348, 2.5543515092846794, 2.3593845371725646, 3.335613067386075, 2.4902832019823458, 1.4642276507350354, 0.5228884875135821, 0.0), # 164
(7.9199648387160195, 5.606276656106095, 7.160091758728169, 7.301282615377426, 6.5233903072298585, 3.2328242947774104, 2.491880858667493, 2.482347492532273, 3.5747956845307916, 1.2912339796767343, 1.0176859260678224, 0.610308307911662, 0.0, 8.704774221257123, 6.713391387028281, 5.088429630339111, 3.873701939030202, 7.149591369061583, 3.4752864895451823, 2.491880858667493, 2.309160210555293, 3.2616951536149292, 2.433760871792476, 1.432018351745634, 0.5096615141914632, 0.0), # 165
(7.714704820122476, 5.452926315885899, 6.9865161349289275, 7.119479204961751, 6.364252031646171, 3.156611619710786, 2.4256995458797714, 2.4242369599085385, 3.492013312249029, 1.2581939335280738, 0.9918764775328559, 0.5950223509696502, 0.0, 8.491648578785155, 6.545245860666151, 4.959382387664279, 3.7745818005842207, 6.984026624498058, 3.393931743871954, 2.4256995458797714, 2.254722585507704, 3.1821260158230853, 2.373159734987251, 1.3973032269857855, 0.4957205741714455, 0.0), # 166
(7.498015255337426, 5.292353214521765, 6.801316981626705, 6.926341055219858, 6.194631750993583, 3.074918801633741, 2.3560966329724047, 2.361874102109088, 3.403010635185759, 1.2232451988998143, 0.9645367633047655, 0.5787987809685459, 0.0, 8.264622461337595, 6.366786590654004, 4.822683816523827, 3.669735596699442, 6.806021270371518, 3.3066237429527234, 2.3560966329724047, 2.196370572595529, 3.0973158754967915, 2.308780351739953, 1.360263396325341, 0.4811230195019787, 0.0), # 167
(7.2708382936444735, 5.125188224546641, 6.605399898170748, 6.722769846671591, 6.015349908244593, 2.9881643153382993, 2.2833611819962822, 2.2955822243696797, 3.308257164293142, 1.1865432668681617, 0.9357904200013762, 0.5617125608182512, 0.0, 8.024787028294753, 6.178838169000762, 4.678952100006881, 3.559629800604484, 6.616514328586284, 3.2138151141175517, 2.2833611819962822, 2.1344030823844995, 3.0076749541222965, 2.2409232822238643, 1.3210799796341497, 0.46592620223151293, 0.0), # 168
(7.034116084327218, 4.952062218493477, 6.399670483910309, 6.509667259836794, 5.827226946371695, 2.8967666356164865, 2.2077822550022947, 2.2256846319260726, 3.2082224105233346, 1.1482436285093212, 0.9057610842405137, 0.5438386534286673, 0.0, 7.773233439036942, 5.982225187715339, 4.528805421202568, 3.444730885527963, 6.416444821046669, 3.1159584846965016, 2.2077822550022947, 2.0691190254403473, 2.9136134731858476, 2.1698890866122653, 1.2799340967820618, 0.450187474408498, 0.0), # 169
(6.78879077666926, 4.773606068895221, 6.185034338194635, 6.2879349752353075, 5.631083308347386, 2.8011442372603246, 2.1296489140413315, 2.1525046300140236, 3.103375884828495, 1.1085017748994974, 0.8745723926400033, 0.525252021709696, 0.0, 7.5110528529444665, 5.777772238806654, 4.372861963200016, 3.325505324698492, 6.20675176965699, 3.013506482019633, 2.1296489140413315, 2.0008173123288033, 2.815541654173693, 2.0959783250784363, 1.2370068676389272, 0.4339641880813838, 0.0), # 170
(6.5358045199542, 4.59045064828482, 5.962397060372978, 6.058474673386982, 5.427739437144163, 2.701715595061839, 2.049250221164283, 2.0763655238692915, 2.994187098160782, 1.0674731971148967, 0.8423479818176697, 0.5060276285712387, 0.0, 7.239336429397638, 5.566303914283624, 4.211739909088348, 3.2024195913446896, 5.988374196321564, 2.906911733417008, 2.049250221164283, 1.9297968536155994, 2.7138697185720817, 2.019491557795661, 1.1924794120745956, 0.4173136952986201, 0.0), # 171
(6.276099463465638, 4.403226829195226, 5.7326642497945866, 5.822188034811656, 5.218015775734522, 2.5988991838130535, 1.9668752384220392, 1.9975906187276353, 2.881125561472354, 1.025313386231724, 0.8092114883913387, 0.4862404369231972, 0.0, 6.959175327776763, 5.348644806155168, 4.046057441956694, 3.075940158695172, 5.762251122944708, 2.7966268662186895, 1.9668752384220392, 1.8563565598664666, 2.609007887867261, 1.9407293449372194, 1.1465328499589174, 0.40029334810865697, 0.0), # 172
(6.010617756487176, 4.212565484159386, 5.4967415058087115, 5.579976740029178, 5.002732767090961, 2.4931134783059927, 1.8828130278654898, 1.916503219824812, 2.7646607857153684, 0.9821778333261846, 0.7752865489788355, 0.4659654096754725, 0.0, 6.671660707462155, 5.125619506430197, 3.8764327448941778, 2.9465334999785533, 5.529321571430737, 2.6831045077547366, 1.8828130278654898, 1.7807953416471376, 2.5013663835454807, 1.859992246676393, 1.0993483011617424, 0.38296049855994424, 0.0), # 173
(5.740301548302412, 4.019097485710249, 5.2555344277646014, 5.332742469559387, 4.782710854185972, 2.3847769533326795, 1.7973526515455251, 1.8334266323965802, 2.645262281841985, 0.9382220294744842, 0.7406968001979856, 0.44527750973796687, 0.0, 6.37788372783412, 4.898052607117634, 3.7034840009899272, 2.814666088423452, 5.29052456368397, 2.5667972853552126, 1.7973526515455251, 1.7034121095233423, 2.391355427092986, 1.7775808231864625, 1.0511068855529204, 0.3653724987009318, 0.0), # 174
(5.466092988194946, 3.823453706380764, 5.009948615011508, 5.08138690392213, 4.558770479992055, 2.2743080836851397, 1.7107831715130346, 1.748684161678698, 2.5233995608043616, 0.8936014657528275, 0.7055658786666139, 0.4242517000205815, 0.0, 6.078935548272969, 4.666768700226395, 3.5278293933330693, 2.680804397258482, 5.046799121608723, 2.4481578263501773, 1.7107831715130346, 1.6245057740608142, 2.2793852399960275, 1.6937956346407106, 1.0019897230023018, 0.3475867005800695, 0.0), # 175
(5.188934225448382, 3.62626501870388, 4.760889666898678, 4.8268117236372525, 4.331732087481704, 2.1621253441553967, 1.6233936498189088, 1.6625991129069244, 2.3995421335546565, 0.8484716332374204, 0.670017421002546, 0.4029629434332179, 0.0, 5.7759073281590085, 4.432592377765396, 3.35008710501273, 2.5454148997122603, 4.799084267109313, 2.327638758069694, 1.6233936498189088, 1.5443752458252833, 2.165866043740852, 1.6089372412124179, 0.9521779333797357, 0.3296604562458073, 0.0), # 176
(4.909767409346319, 3.4281622952125463, 4.5092631827753635, 4.569918609224595, 4.102416119627418, 2.0486472095354746, 1.5354731485140374, 1.5754947913170163, 2.2741595110450277, 0.8029880230044676, 0.6341750638236071, 0.3814862028857779, 0.0, 5.4698902268725496, 4.196348231743556, 3.1708753191180357, 2.408964069013402, 4.548319022090055, 2.2056927078438227, 1.5354731485140374, 1.4633194353824817, 2.051208059813709, 1.5233062030748654, 0.9018526365550728, 0.31165111774659515, 0.0), # 177
(4.629534689172356, 3.2297764084397107, 4.255974761990814, 4.311609241204004, 3.8716430194016906, 1.9342921546173981, 1.4473107296493104, 1.4876945021447328, 2.147721204227634, 0.7573061261301752, 0.5981624437476226, 0.3598964412881627, 0.0, 5.161975403793902, 3.958860854169789, 2.9908122187381125, 2.271918378390525, 4.295442408455268, 2.082772303002626, 1.4473107296493104, 1.3816372532981414, 1.9358215097008453, 1.437203080401335, 0.8511949523981628, 0.29361603713088286, 0.0), # 178
(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, 0.0, 0.0), # 179
)
passenger_allighting_rate = (
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 0
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 1
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 2
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 3
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 4
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 5
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 6
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 7
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 8
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 9
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 10
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 11
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 12
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 13
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 14
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 15
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 16
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 17
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 18
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 19
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 20
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 21
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 22
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 23
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 24
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 25
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 26
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 27
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 28
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 29
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 30
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 31
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 32
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 33
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 34
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 35
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 36
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 37
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 38
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 39
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 40
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 41
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 42
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 43
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 44
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 45
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 46
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 47
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 48
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 49
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 50
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 51
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 52
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 53
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 54
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 55
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 56
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 57
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 58
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 59
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 60
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 61
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 62
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 63
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 64
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 65
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 66
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 67
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 68
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 69
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 70
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 71
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 72
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 73
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 74
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 75
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 76
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 77
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 78
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 79
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 80
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 81
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 82
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 83
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 84
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 85
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 86
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 87
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 88
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 89
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 90
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 91
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 92
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 93
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 94
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 95
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 96
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 97
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 98
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 99
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 100
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 101
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 102
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 103
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 104
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 105
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 106
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 107
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 108
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 109
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 110
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 111
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 112
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 113
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 114
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 115
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 116
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 117
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 118
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 119
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 120
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 121
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 122
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 123
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 124
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 125
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 126
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 127
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 128
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 129
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 130
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 131
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(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 162
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 163
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 164
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 165
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 166
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 167
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 168
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 169
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 170
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 171
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 172
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 173
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 174
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 175
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 176
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 177
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 178
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 179
)
"""
parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html
"""
#initial entropy
entropy = 8991598675325360468762009371570610170
#index for seed sequence child
child_seed_index = (
1, # 0
74, # 1
)
| 275.528342
| 493
| 0.768946
| 32,987
| 257,619
| 6.004911
| 0.222512
| 0.359847
| 0.345308
| 0.654268
| 0.374745
| 0.366996
| 0.36533
| 0.36533
| 0.36533
| 0.36533
| 0
| 0.849368
| 0.09601
| 257,619
| 934
| 494
| 275.82334
| 0.001198
| 0.01557
| 0
| 0.200873
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.005459
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
eae1360b95d3d3a5b7fca3ffe90f7355a2269033
| 3,101
|
py
|
Python
|
network/coarse_network.py
|
sveatlo/inpainting
|
6870ee56beea7401aa97194f76487c391af9dd5d
|
[
"Unlicense"
] | 1
|
2021-08-08T03:17:17.000Z
|
2021-08-08T03:17:17.000Z
|
network/coarse_network.py
|
sveatlo/inpainting
|
6870ee56beea7401aa97194f76487c391af9dd5d
|
[
"Unlicense"
] | 6
|
2021-08-08T13:12:55.000Z
|
2022-03-13T15:26:02.000Z
|
network/coarse_network.py
|
sveatlo/unmasked
|
6870ee56beea7401aa97194f76487c391af9dd5d
|
[
"Unlicense"
] | null | null | null |
import torch
import torch.nn as nn
from network.gated_conv import GatedConv2d, GatedDeConv2d
class CoarseNetwork(nn.Module):
def __init__(self, in_channels: int = 4, out_channels: int = 3, latent_channels: int = 48, padding_type: str = 'zero', activation: str = 'lrelu', norm: str = 'none'):
super().__init__()
self.coarse = nn.Sequential(
# encoder
GatedConv2d(in_channels, latent_channels, 5, 1, 2, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels, latent_channels*2, 3, 2, 1, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels*2, latent_channels*2, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels*2, latent_channels*4, 3, 2, 1, padding_type = padding_type, activation = activation, norm = norm),
# Bottleneck
GatedConv2d(latent_channels*4, latent_channels*4, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels*4, latent_channels*4, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
## dilated
GatedConv2d(latent_channels*4, latent_channels*4, 3, 1, 2, dilation = 2, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels*4, latent_channels*4, 3, 1, 4, dilation = 4, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels*4, latent_channels*4, 3, 1, 8, dilation = 8, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels*4, latent_channels*4, 3, 1, 16, dilation = 16, padding_type = padding_type, activation = activation, norm = norm),
## end dilated
GatedConv2d(latent_channels*4, latent_channels*4, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels*4, latent_channels*4, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
# decoder
GatedDeConv2d(latent_channels*4, latent_channels*2, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels*2, latent_channels*2, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
GatedDeConv2d(latent_channels*2, latent_channels, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels, latent_channels//2, 3, 1, 1, padding_type = padding_type, activation = activation, norm = norm),
GatedConv2d(latent_channels//2, out_channels, 3, 1, 1, padding_type = padding_type, activation = 'none', norm = norm),
nn.Tanh()
)
def forward(self, img, mask):
img_masked = img*(1 - mask) + mask
x = torch.cat((img_masked, mask), dim=1) # in: [B, 4, H, W]
return self.coarse(x)
| 75.634146
| 170
| 0.671719
| 393
| 3,101
| 5.089059
| 0.147583
| 0.1925
| 0.135
| 0.187
| 0.7575
| 0.7395
| 0.7395
| 0.7395
| 0.7145
| 0.689
| 0
| 0.045717
| 0.217027
| 3,101
| 40
| 171
| 77.525
| 0.778007
| 0.020316
| 0
| 0.2
| 0
| 0
| 0.005612
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.066667
| false
| 0
| 0.1
| 0
| 0.233333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
dc1be0e4603b11cd7c1a9ffba59a6aab834e2e36
| 3,376
|
py
|
Python
|
ripiu/djangocms_aoxomoxoa/models/options/constants.py
|
ripiu/djangocms_aoxomoxoa
|
e801e49259fba739308daa37bc9bbd28ba0a8e27
|
[
"BSD-3-Clause"
] | null | null | null |
ripiu/djangocms_aoxomoxoa/models/options/constants.py
|
ripiu/djangocms_aoxomoxoa
|
e801e49259fba739308daa37bc9bbd28ba0a8e27
|
[
"BSD-3-Clause"
] | null | null | null |
ripiu/djangocms_aoxomoxoa/models/options/constants.py
|
ripiu/djangocms_aoxomoxoa
|
e801e49259fba739308daa37bc9bbd28ba0a8e27
|
[
"BSD-3-Clause"
] | null | null | null |
from django.db import models # NOQA
from django.utils.translation import ugettext_lazy as _
ALIGN_LEFT = 'left'
ALIGN_CENTER = 'center'
ALIGN_RIGHT = 'right'
ALIGN_CHOICES = (
(ALIGN_LEFT, _('Left')),
(ALIGN_CENTER, _('Center')),
(ALIGN_RIGHT, _('Right')),
)
VALIGN_TOP = 'top'
VALIGN_MIDDLE = 'middle'
VALIGN_BOTTOM = 'bottom'
VALIGN_CHOICES = (
(VALIGN_TOP, _('Top')),
(VALIGN_MIDDLE, _('Middle')),
(VALIGN_BOTTOM, _('Bottom')),
)
POSITION_TOP = 'top'
POSITION_BOTTOM = 'bottom'
POSITION_LEFT = 'left'
POSITION_RIGHT = 'right'
POSITION_CHOICES = (
(POSITION_TOP, _('Top')),
(POSITION_BOTTOM, _('Bottom')),
(POSITION_LEFT, _('Left')),
(POSITION_RIGHT, _('Right')),
)
EASE_INOUT_BACK = 'easeInOutBack'
EASE_INOUT_BOUNCE = 'easeInOutBounce'
EASE_INOUT_CIRC = 'easeInOutCirc'
EASE_INOUT_CUBIC = 'easeInOutCubic'
EASE_INOUT_ELASTIC = 'easeInOutElastic'
EASE_INOUT_EXPO = 'easeInOutExpo'
EASE_INOUT_QUAD = 'easeInOutQuad'
EASE_INOUT_QUART = 'easeInOutQuart'
EASE_INOUT_QUINT = 'easeInOutQuint'
EASE_INOUT_SINE = 'easeInOutSine'
EASE_IN_BACK = 'easeInBack'
EASE_IN_BOUNCE = 'easeInBounce'
EASE_IN_CIRC = 'easeInCirc'
EASE_IN_CUBIC = 'easeInCubic'
EASE_IN_ELASTIC = 'easeInElastic'
EASE_IN_EXPO = 'easeInExpo'
EASE_IN_QUAD = 'easeInQuad'
EASE_IN_QUART = 'easeInQuart'
EASE_IN_QUINT = 'easeInQuint'
EASE_IN_SINE = 'easeInSine'
EASE_OUT_BACK = 'easeOutBack'
EASE_OUT_BOUNCE = 'easeOutBounce'
EASE_OUT_CIRC = 'easeOutCirc'
EASE_OUT_CUBIC = 'easeOutCubic'
EASE_OUT_ELASTIC = 'easeOutElastic'
EASE_OUT_EXPO = 'easeOutExpo'
EASE_OUT_QUAD = 'easeOutQuad'
EASE_OUT_QUART = 'easeOutQuart'
EASE_OUT_QUINT = 'easeOutQuint'
EASE_OUT_SINE = 'easeOutSine'
EASE_SWING = 'swing'
EASING_CHOICES = (
(EASE_INOUT_BACK, _('easeInOutBack')),
(EASE_INOUT_BOUNCE, _('easeInOutBounce')),
(EASE_INOUT_CIRC, _('easeInOutCirc')),
(EASE_INOUT_CUBIC, _('easeInOutCubic')),
(EASE_INOUT_ELASTIC, _('easeInOutElastic')),
(EASE_INOUT_EXPO, _('easeInOutExpo')),
(EASE_INOUT_QUAD, _('easeInOutQuad')),
(EASE_INOUT_QUART, _('easeInOutQuart')),
(EASE_INOUT_QUINT, _('easeInOutQuint')),
(EASE_INOUT_SINE, _('easeInOutSine')),
(EASE_IN_BACK, _('easeInBack')),
(EASE_IN_BOUNCE, _('easeInBounce')),
(EASE_IN_CIRC, _('easeInCirc')),
(EASE_IN_CUBIC, _('easeInCubic')),
(EASE_IN_ELASTIC, _('easeInElastic')),
(EASE_IN_EXPO, _('easeInExpo')),
(EASE_IN_QUAD, _('easeInQuad')),
(EASE_IN_QUART, _('easeInQuart')),
(EASE_IN_QUINT, _('easeInQuint')),
(EASE_IN_SINE, _('easeInSine')),
(EASE_OUT_BACK, _('easeOutBack')),
(EASE_OUT_BOUNCE, _('easeOutBounce')),
(EASE_OUT_CIRC, _('easeOutCirc')),
(EASE_OUT_CUBIC, _('easeOutCubic')),
(EASE_OUT_ELASTIC, _('easeOutElastic')),
(EASE_OUT_EXPO, _('easeOutExpo')),
(EASE_OUT_QUAD, _('easeOutQuad')),
(EASE_OUT_QUART, _('easeOutQuart')),
(EASE_OUT_QUINT, _('easeOutQuint')),
(EASE_OUT_SINE, _('easeOutSine')),
(EASE_SWING, _('swing')),
)
APPEAR_SLIDE = 'slide'
APPEAR_FADE = 'fade'
APPEAR_CHOICES = (
(APPEAR_SLIDE, _('Slide')),
(APPEAR_FADE, _('Fade')),
)
IMAGE_EFFECT_BW = 'bw'
IMAGE_EFFECT_BLUR = 'blur'
IMAGE_EFFECT_SEPIA = 'sepia'
IMAGE_EFFECT_CHOICES = (
(IMAGE_EFFECT_BW, _('Black and white')),
(IMAGE_EFFECT_BLUR, _('Blur')),
(IMAGE_EFFECT_SEPIA, _('Sepia')),
)
| 29.876106
| 55
| 0.69846
| 371
| 3,376
| 5.781671
| 0.210243
| 0.083916
| 0.027972
| 0.016783
| 0.907226
| 0.907226
| 0.879254
| 0.879254
| 0.841958
| 0.755245
| 0
| 0
| 0.145142
| 3,376
| 112
| 56
| 30.142857
| 0.743243
| 0.001185
| 0
| 0
| 0
| 0
| 0.263205
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.018868
| 0
| 0.018868
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
dc3f364ba0ad05f9813c36780d003449640d6fa5
| 25,167
|
py
|
Python
|
tests/test_configure.py
|
EricGhildyal/RootCoachRecommendation
|
09ba197b63aa8bf4714331b39a59289ae8c66dbc
|
[
"MIT"
] | 51
|
2015-02-09T02:09:31.000Z
|
2022-03-14T19:30:35.000Z
|
tests/test_configure.py
|
EricGhildyal/RootCoachRecommendation
|
09ba197b63aa8bf4714331b39a59289ae8c66dbc
|
[
"MIT"
] | 1
|
2019-11-02T09:40:18.000Z
|
2019-11-02T09:40:18.000Z
|
tests/test_configure.py
|
EricGhildyal/RootCoachRecommendation
|
09ba197b63aa8bf4714331b39a59289ae8c66dbc
|
[
"MIT"
] | 47
|
2015-01-17T08:20:44.000Z
|
2022-03-04T18:43:33.000Z
|
import unittest
from mock import Mock
from mock import patch
import subprocess
import logging
from twilio.rest import TwilioRestClient
from twilio.exceptions import TwilioException
from .context import configure
class ConfigureTest(unittest.TestCase):
def setUp(self):
self.configure = configure.Configure(account_sid="ACxxxxx",
auth_token="yyyyyyyy",
phone_number="+15555555555",
app_sid="APzzzzzzzzz")
self.configure.client = TwilioRestClient(self.configure.account_sid,
self.configure.auth_token)
class TwilioTest(ConfigureTest):
@patch('twilio.rest.resources.Applications')
@patch('twilio.rest.resources.Application')
def test_createNewTwiMLApp(self, MockApp, MockApps):
# Mock the Applications resource and its create method.
self.configure.client.applications = MockApps.return_value
self.configure.client.applications.create.return_value = \
MockApp.return_value
# Mock our input.
configure.raw_input = lambda _: 'y'
# Test
self.configure.createNewTwiMLApp(self.configure.voice_url,
self.configure.sms_url)
# Assert
app_create = self.configure.client.applications.create
app_create.assert_called_once_with(voice_url=self.configure.voice_url,
sms_url=self.configure.sms_url,
friendly_name="Hackpack for Heroku "
"and Flask")
@patch('twilio.rest.resources.Applications')
@patch('twilio.rest.resources.Application')
def test_createNewTwiMLAppNegativeInput(self, MockApp, MockApps):
# Mock the Applications resource and its create method.
self.configure.client.applications = MockApps.return_value
self.configure.client.applications.create.return_value = \
MockApp.return_value
# Mock our input .
configure.raw_input = lambda _: 'n'
# Test / Assert
self.assertRaises(configure.ConfigurationError,
self.configure.createNewTwiMLApp,
self.configure.voice_url,
self.configure.sms_url)
@patch('twilio.rest.resources.Applications')
def test_createNewTwiMLAppException(self, MockApps):
# Mock the Applications resource and its create method.
self.configure.client.applications = MockApps.return_value
def raiseException(*args, **kwargs):
raise TwilioException("Test error.")
self.configure.client.applications.create.side_effect = raiseException
# Mock our input .
configure.raw_input = lambda _: 'y'
# Test / Assert
self.assertRaises(configure.ConfigurationError,
self.configure.createNewTwiMLApp,
self.configure.voice_url,
self.configure.sms_url)
@patch('twilio.rest.resources.Applications')
@patch('twilio.rest.resources.Application')
def test_setAppSidRequestUrls(self, MockApp, MockApps):
# Mock the Applications resource and its update method.
self.configure.client.applications = MockApps.return_value
self.configure.client.applications.update.return_value = \
MockApp.return_value
# Test
self.configure.setAppRequestUrls(self.configure.app_sid,
self.configure.voice_url,
self.configure.sms_url)
# Assert
app_create = self.configure.client.applications.update
app_create.assert_called_once_with(self.configure.app_sid,
voice_url=self.configure.voice_url,
sms_url=self.configure.sms_url,
friendly_name='Hackpack for Heroku '
'and Flask')
@patch('twilio.rest.resources.Applications')
def test_setAppSidRequestUrls404Error(self, MockApps):
# Mock the Applications resource and its update method.
self.configure.client.applications.update = MockApps()
def raiseException(*args, **kwargs):
raise TwilioException("HTTP ERROR 404.")
self.configure.client.applications.update.side_effect = raiseException
# Test
self.assertRaises(configure.ConfigurationError,
self.configure.setAppRequestUrls,
self.configure.app_sid,
self.configure.voice_url,
self.configure.sms_url)
@patch('twilio.rest.resources.Applications')
def test_setAppSidRequestUrls500Error(self, MockApps):
# Mock the Applications resource and its update method.
self.configure.client.applications.update = MockApps()
def raiseException(*args, **kwargs):
raise TwilioException("HTTP ERROR 500.")
self.configure.client.applications.update.side_effect = raiseException
# Test
self.assertRaises(configure.ConfigurationError,
self.configure.setAppRequestUrls,
self.configure.app_sid,
self.configure.voice_url,
self.configure.sms_url)
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_retrievePhoneNumber(self, MockPhoneNumber, MockPhoneNumbers):
# Mock the PhoneNumbers resource and its list method.
mock_num = MockPhoneNumber.return_value
mock_num.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
self.configure.client.phone_numbers.list.return_value = [mock_num]
# Test
self.configure.retrievePhoneNumber(self.configure.phone_number)
# Assert
num_l = self.configure.client.phone_numbers.list
num_l.assert_called_once_with(phone_number=self.configure.phone_number)
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_purchasePhoneNumber(self, MockPhoneNumber, MockPhoneNumbers):
# Mock the PhoneNumbers resource and its search and purchase methods
mock_phone_number = MockPhoneNumber.return_value
mock_phone_number.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
self.configure.client.phone_numbers.purchase = mock_phone_number
# Mock our input.
configure.raw_input = lambda _: 'y'
# Test
self.configure.purchasePhoneNumber()
# Assert
purchase = self.configure.client.phone_numbers.purchase
purchase.assert_called_once_with(area_code="646")
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_purchasePhoneNumberNegativeInput(self, MockPhoneNumbers,
MockPhoneNumber):
# Mock the PhoneNumbers resource and its search and purchase methods
mock_phone_number = MockPhoneNumber.return_value
mock_phone_number.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
self.configure.client.phone_numbers.purchase = mock_phone_number
# Mock our input.
configure.raw_input = lambda _: 'n'
# Test / Assert
self.assertRaises(configure.ConfigurationError,
self.configure.purchasePhoneNumber)
@patch('twilio.rest.resources.PhoneNumbers')
def test_purchasePhoneNumberExceptionOnPurchase(self, MockPhoneNumbers):
# Mock the PhoneNumbers resource and its search and purchase methods
self.configure.client.phone_numbers.purchase = MockPhoneNumbers()
def raiseException(*args, **kwargs):
raise TwilioException("Test error.")
self.configure.client.phone_numbers.purchase.side_effect = \
raiseException
# Mock our input.
configure.raw_input = lambda _: 'y'
# Test / Assert
self.assertRaises(configure.ConfigurationError,
self.configure.purchasePhoneNumber)
@patch('twilio.rest.resources.Applications')
@patch('twilio.rest.resources.Application')
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_configure(self, MockPhoneNumber, MockPhoneNumbers, MockApp,
MockApps):
# Mock the Applications resource and its update method.
mock_app = MockApp.return_value
mock_app.sid = self.configure.app_sid
self.configure.client.applications = MockApps.return_value
self.configure.client.applications.update.return_value = \
mock_app
# Mock the PhoneNumbers resource and its list method.
mock_phone_number = MockPhoneNumber.return_value
mock_phone_number.sid = "PN123"
mock_phone_number.friendly_name = "(555) 555-5555"
mock_phone_number.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
self.configure.client.phone_numbers.list.return_value = \
[mock_phone_number]
# Test
self.configure.configureHackpack(self.configure.voice_url,
self.configure.sms_url,
self.configure.app_sid,
self.configure.phone_number)
# Assert
apps = self.configure.client.applications.update
apps.assert_called_once_with(self.configure.app_sid,
voice_url=self.configure.voice_url,
sms_url=self.configure.sms_url,
friendly_name='Hackpack for Heroku '
'and Flask')
update = self.configure.client.phone_numbers.update
app_sid = self.configure.app_sid
update.assert_called_once_with("PN123",
voice_application_sid=app_sid,
sms_application_sid=app_sid)
@patch('twilio.rest.resources.Applications')
@patch('twilio.rest.resources.Application')
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_configureNoApp(self, MockPhoneNumber, MockPhoneNumbers, MockApp,
MockApps):
# Mock the Applications resource and its update method.
mock_app = MockApp.return_value
mock_app.sid = self.configure.app_sid
self.configure.client.applications = MockApps.return_value
self.configure.client.applications.create.return_value = \
mock_app
# Mock the PhoneNumbers resource and its list method.
mock_phone_number = MockPhoneNumber.return_value
mock_phone_number.sid = "PN123"
mock_phone_number.friendly_name = "(555) 555-5555"
mock_phone_number.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
self.configure.client.phone_numbers.list.return_value = \
[mock_phone_number]
# Set AppSid to None
self.configure.app_sid = None
# Mock our input.
configure.raw_input = lambda _: 'y'
# Test
self.configure.configureHackpack(self.configure.voice_url,
self.configure.sms_url,
self.configure.app_sid,
self.configure.phone_number)
# Assert
create = self.configure.client.applications.create
create.assert_called_once_with(voice_url=self.configure.voice_url,
sms_url=self.configure.sms_url,
friendly_name="Hackpack for Heroku "
"and Flask")
update = self.configure.client.phone_numbers.update
update.assert_called_once_with("PN123",
voice_application_sid=mock_app.sid,
sms_application_sid=mock_app.sid)
@patch('twilio.rest.resources.Applications')
@patch('twilio.rest.resources.Application')
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_configureNoPhoneNumber(self, MockPhoneNumber, MockPhoneNumbers,
MockApp, MockApps):
# Mock the Applications resource and its update method.
mock_app = MockApp.return_value
mock_app.sid = self.configure.app_sid
self.configure.client.applications = MockApps.return_value
self.configure.client.applications.update.return_value = \
mock_app
# Mock the PhoneNumbers resource and its list method.
mock_phone_number = MockPhoneNumber.return_value
mock_phone_number.sid = "PN123"
mock_phone_number.friendly_name = "(555) 555-5555"
mock_phone_number.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
self.configure.client.phone_numbers.purchase.return_value = \
mock_phone_number
# Set AppSid to None
self.configure.phone_number = None
# Mock our input.
configure.raw_input = lambda _: 'y'
# Test
self.configure.configureHackpack(self.configure.voice_url,
self.configure.sms_url,
self.configure.app_sid,
self.configure.phone_number)
# Assert
update = self.configure.client.applications.update
update.assert_called_once_with(self.configure.app_sid,
voice_url=self.configure.voice_url,
sms_url=self.configure.sms_url,
friendly_name='Hackpack for Heroku '
'and Flask')
update = self.configure.client.phone_numbers.update
app_sid = self.configure.app_sid
update.assert_called_once_with("PN123",
voice_application_sid=app_sid,
sms_application_sid=app_sid)
@patch('twilio.rest.resources.Applications')
@patch('twilio.rest.resources.Application')
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_configureNoPhoneNumberTwilioError(self, MockPhoneNumber,
MockPhoneNumbers, MockApp,
MockApps):
# Mock the Applications resource and its update method.
mock_app = MockApp.return_value
mock_app.sid = self.configure.app_sid
self.configure.client.applications = MockApps.return_value
self.configure.client.applications.update.return_value = \
mock_app
# Mock the PhoneNumbers resource and its list method.
mock_phone_number = MockPhoneNumber.return_value
mock_phone_number.sid = "PN123"
mock_phone_number.friendly_name = "(555) 555-5555"
mock_phone_number.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
def raiseException(*args, **kwargs):
raise TwilioException("Test error.")
self.configure.client.phone_numbers.update.side_effect = \
raiseException
# Mock our input.
configure.raw_input = lambda _: 'y'
# Test
self.assertRaises(configure.ConfigurationError,
self.configure.configureHackpack,
self.configure.voice_url,
self.configure.sms_url,
self.configure.app_sid,
self.configure.phone_number)
@patch.object(subprocess, 'call')
@patch.object(configure.Configure, 'configureHackpack')
def test_start(self, mock_configureHackpack, mock_call):
mock_call.return_value = None
self.configure.host = 'http://look-here-snacky-11211.herokuapp.com'
self.configure.start()
m = mock_configureHackpack
m.assert_called_once_with('http://look-here-snacky-11211.herokuapp.com'
'/voice',
'http://look-here-snacky-11211.herokuapp.com'
'/sms',
self.configure.app_sid,
self.configure.phone_number)
@patch.object(subprocess, 'call')
@patch.object(configure.Configure, 'configureHackpack')
@patch.object(configure.Configure, 'getHerokuHostname')
def test_startWithoutHostname(self, mock_getHerokuHostname,
mock_configureHackpack, mock_call):
mock_call.return_value = None
mock_getHerokuHostname.return_value = 'http://look-here-snacky-11211' \
'.herokuapp.com'
self.configure.start()
m = mock_configureHackpack
m.assert_called_once_with('http://look-here-snacky-11211.herokuapp.com'
'/voice',
'http://look-here-snacky-11211.herokuapp.com'
'/sms',
self.configure.app_sid,
self.configure.phone_number)
class HerokuTest(ConfigureTest):
def test_getHerokuHostname(self):
test = self.configure.getHerokuHostname(git_config_path='./tests'
'/test_assets'
'/good_git_'
'config')
self.assertEquals(test, 'http://look-here-snacky-11211.herokuapp.com')
def test_getHerokuHostnameNoSuchFile(self):
self.assertRaises(configure.ConfigurationError,
self.configure.getHerokuHostname,
git_config_path='/tmp')
def test_getHerokuHostnameNoHerokuRemote(self):
self.assertRaises(configure.ConfigurationError,
self.configure.getHerokuHostname,
git_config_path='./tests/test_assets/bad_git_config')
@patch.object(subprocess, 'call')
def test_setHerokuEnvironmentVariables(self, mock_call):
mock_call.return_value = None
configuration = {'TWILIO_ACCOUNT_SID': self.configure.account_sid,
'TWILIO_AUTH_TOKEN': self.configure.auth_token,
'TWILIO_APP_SID': self.configure.app_sid,
'TWILIO_CALLER_ID': self.configure.phone_number}
self.configure.setHerokuEnvironmentVariables(**configuration)
args, kwargs = mock_call.call_args
self.assertTrue("heroku" in args[0],
"Heroku toolbelt not present in call: "
"{0}".format(args[0]))
self.assertTrue("config:add" in args[0],
"Config:add not present in call: "
"{0}".format(args[0]))
config = ["{0}={1}".format(k, v) for k, v in configuration.items()]
for item in config:
self.assertTrue(item in args[0],
"Missing config from call_args: {0} Instead got: "
"{0}".format(item, args[0]))
class MiscellaneousTest(unittest.TestCase):
def test_configureWithoutAccountSid(self):
test = configure.Configure(account_sid=None, auth_token=None,
phone_number=None, app_sid=None)
self.assertRaises(configure.ConfigurationError,
test.start)
def test_configureWithoutAuthToken(self):
test = configure.Configure(account_sid='ACxxxxxxx', auth_token=None,
phone_number=None, app_sid=None)
self.assertRaises(configure.ConfigurationError,
test.start)
class InputTest(ConfigureTest):
@patch('twilio.rest.resources.Applications')
@patch('twilio.rest.resources.Application')
def test_createNewTwiMLAppWtfInput(self, MockApp, MockApps):
# Mock the Applications resource and its create method.
self.configure.client.applications = MockApps.return_value
self.configure.client.applications.create.return_value = \
MockApp.return_value
# Mock our input
configure.raw_input = Mock()
configure.raw_input.return_value = 'wtf'
# Test / Assert
self.assertRaises(configure.ConfigurationError,
self.configure.createNewTwiMLApp,
self.configure.voice_url,
self.configure.sms_url)
count = configure.raw_input.call_count
self.assertTrue(configure.raw_input.call_count == 3, "Prompt did "
"not appear three times, instead: %i".format(count))
self.assertFalse(self.configure.client.applications.create.called,
"Unexpected request to create AppSid made.")
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_purchasePhoneNumberWtfInput(self, MockPhoneNumbers,
MockPhoneNumber):
# Mock the PhoneNumbers resource and its search and purchase methods
mock_phone_number = MockPhoneNumber.return_value
mock_phone_number.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
self.configure.client.phone_numbers.purchase = mock_phone_number
# Mock our input.
configure.raw_input = Mock()
configure.raw_input.return_value = 'wtf'
# Test / Assert
self.assertRaises(configure.ConfigurationError,
self.configure.purchasePhoneNumber)
self.assertTrue(configure.raw_input.call_count == 3, "Prompt did "
"not appear three times, instead: %i" %
configure.raw_input.call_count)
self.assertFalse(self.configure.client.phone_numbers.purchase.called,
"Unexpected request to create AppSid made.")
@patch('twilio.rest.resources.PhoneNumbers')
@patch('twilio.rest.resources.PhoneNumber')
def test_purchasePhoneNumberWtfInputConfirm(self,
MockPhoneNumbers,
MockPhoneNumber):
# Mock the PhoneNumbers resource and its search and purchase methods
mock_phone_number = MockPhoneNumber.return_value
mock_phone_number.phone_number = self.configure.phone_number
self.configure.client.phone_numbers = MockPhoneNumbers.return_value
self.configure.client.phone_numbers.purchase = mock_phone_number
# Mock our input.
configure.raw_input = Mock()
configure.raw_input.side_effect = ['y', 'wtf', 'wtf', 'wtf']
# Test / Assert
self.assertRaises(configure.ConfigurationError,
self.configure.purchasePhoneNumber)
self.assertTrue(configure.raw_input.call_count == 4, "Prompt did "
"not appear three times, instead: %i" %
configure.raw_input.call_count)
self.assertFalse(self.configure.client.phone_numbers.purchase.called,
"Unexpectedly requested phone number purchase.")
class CommandLineTest(unittest.TestCase):
def test_account_sid(self):
parser = configure.parse_args(['-SACxxx'])
self.assertEquals(parser.account_sid, 'ACxxx')
def test_new_phone_number(self):
parser = configure.parse_args(['--new'])
self.assertEquals(parser.phone_number, None)
def test_custom_domain(self):
parser = configure.parse_args(['-dtwilio.com'])
self.assertEquals(parser.host, "twilio.com")
def test_debug(self):
parser = configure.parse_args(['-D'])
self.assertTrue(parser.logger.level, logging.DEBUG)
| 45.183124
| 79
| 0.611118
| 2,405
| 25,167
| 6.207069
| 0.082328
| 0.135852
| 0.071275
| 0.061093
| 0.841506
| 0.820539
| 0.791466
| 0.783963
| 0.779944
| 0.757704
| 0
| 0.007871
| 0.30842
| 25,167
| 556
| 80
| 45.264388
| 0.849813
| 0.064211
| 0
| 0.676617
| 0
| 0
| 0.111787
| 0.055723
| 0
| 0
| 0
| 0
| 0.099502
| 1
| 0.087065
| false
| 0
| 0.019901
| 0
| 0.121891
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| null | 0
| 0
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| 1
| 1
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
dc522fec90f01435b7342e9dfc4d373e63b132b8
| 523
|
py
|
Python
|
gpudb/packages/avro/__init__.py
|
kineticadb/kinetica-api-python
|
530dd3fb73a10a035fe5ec25e4260be6f0514017
|
[
"MIT"
] | 12
|
2017-05-17T05:55:26.000Z
|
2022-03-02T15:53:44.000Z
|
gpudb/packages/avro/__init__.py
|
kineticadb/kinetica-api-python
|
530dd3fb73a10a035fe5ec25e4260be6f0514017
|
[
"MIT"
] | 11
|
2017-03-11T18:21:26.000Z
|
2022-02-09T05:08:40.000Z
|
gpudb/packages/avro/__init__.py
|
kineticadb/kinetica-api-python
|
530dd3fb73a10a035fe5ec25e4260be6f0514017
|
[
"MIT"
] | 9
|
2017-03-10T01:20:12.000Z
|
2020-08-26T13:27:38.000Z
|
#! /usr/bin/env python
import sys
if sys.version_info[0] == 2:
from .avro_py2 import schema
from .avro_py2 import io
from .avro_py2 import protocol
from .avro_py2 import ipc
from .avro_py2 import datafile
from .avro_py2 import tool
#from .avro_py2 import txipc
else:
from .avro_py3 import schema
from .avro_py3 import io
from .avro_py3 import protocol
from .avro_py3 import ipc
from .avro_py3 import datafile
from .avro_py3 import tool
#from .avro_py3 import txipc
| 24.904762
| 34
| 0.709369
| 83
| 523
| 4.289157
| 0.277108
| 0.314607
| 0.216292
| 0.33427
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.0401
| 0.237094
| 523
| 20
| 35
| 26.15
| 0.85213
| 0.143403
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.866667
| 0
| 0.866667
| 0
| 0
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
dc5feac40c2aeea326c31268bb58a80f2cd69032
| 123
|
py
|
Python
|
pysts/gui/__init__.py
|
sdswart/pysts
|
f140072e064b59a7d8732e73d71fd812b6d292c5
|
[
"MIT"
] | null | null | null |
pysts/gui/__init__.py
|
sdswart/pysts
|
f140072e064b59a7d8732e73d71fd812b6d292c5
|
[
"MIT"
] | null | null | null |
pysts/gui/__init__.py
|
sdswart/pysts
|
f140072e064b59a7d8732e73d71fd812b6d292c5
|
[
"MIT"
] | null | null | null |
# Dash for simple web-based apps
# pyqt for larger platform independant apps
# tkinter for small platform independant apps
| 30.75
| 45
| 0.804878
| 18
| 123
| 5.5
| 0.666667
| 0.383838
| 0.464646
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.162602
| 123
| 3
| 46
| 41
| 0.961165
| 0.943089
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
dc6e0f19609fa1848809be4bb3360a82cb975f2f
| 28
|
py
|
Python
|
reldi_tokeniser/__init__.py
|
clarinsi/reldi-tokeniser
|
7d519ca3799ec5cc702652ab0ac66f0bc93faffb
|
[
"Apache-2.0"
] | 4
|
2016-07-20T09:28:06.000Z
|
2021-12-27T20:53:38.000Z
|
reldi_tokeniser/__init__.py
|
clarinsi/reldi-tokeniser
|
7d519ca3799ec5cc702652ab0ac66f0bc93faffb
|
[
"Apache-2.0"
] | 3
|
2017-07-10T18:14:37.000Z
|
2020-02-03T12:01:57.000Z
|
reldi_tokeniser/__init__.py
|
clarinsi/reldi-tokeniser
|
7d519ca3799ec5cc702652ab0ac66f0bc93faffb
|
[
"Apache-2.0"
] | 7
|
2018-01-29T14:33:25.000Z
|
2021-07-05T09:44:15.000Z
|
from . tokeniser import run
| 14
| 27
| 0.785714
| 4
| 28
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.178571
| 28
| 1
| 28
| 28
| 0.956522
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
dcabc339fe746f114822f488614e91e8feb83bdc
| 25
|
py
|
Python
|
tokenization.py
|
letitiayhho/beb
|
48e400e0be0ea895bb4f403194eaf5f4493a3d89
|
[
"MIT"
] | 2
|
2019-11-29T22:07:44.000Z
|
2021-09-21T20:46:36.000Z
|
tokenization.py
|
letitiayhho/beb
|
48e400e0be0ea895bb4f403194eaf5f4493a3d89
|
[
"MIT"
] | 6
|
2021-03-31T19:25:19.000Z
|
2022-03-12T00:07:39.000Z
|
tokenization.py
|
letitiayhho/beb
|
48e400e0be0ea895bb4f403194eaf5f4493a3d89
|
[
"MIT"
] | null | null | null |
def tokenize():
pass
| 8.333333
| 15
| 0.6
| 3
| 25
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.28
| 25
| 2
| 16
| 12.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 1
| 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
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
f4d08e5aa2f8b25229f75db1c4216847bf3022c1
| 38
|
py
|
Python
|
Mapping spatial patterns of LST distribution in urban areas using satellite times series/demo.py
|
icharalamp/UrbanClimateSummerSchool2018
|
421585c44c6e6f3cb1fbc077073da218fa9d51d9
|
[
"MIT"
] | 1
|
2020-07-11T06:58:33.000Z
|
2020-07-11T06:58:33.000Z
|
Remote sensing in urban areas/demo.py
|
icharalamp/UrbanClimateSummerSchool2018
|
421585c44c6e6f3cb1fbc077073da218fa9d51d9
|
[
"MIT"
] | null | null | null |
Remote sensing in urban areas/demo.py
|
icharalamp/UrbanClimateSummerSchool2018
|
421585c44c6e6f3cb1fbc077073da218fa9d51d9
|
[
"MIT"
] | null | null | null |
import os
import sys
import tempfile
| 7.6
| 15
| 0.815789
| 6
| 38
| 5.166667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.184211
| 38
| 5
| 15
| 7.6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
5207f37c30743b2f5794e680f5c1c5d8d44a8056
| 108
|
py
|
Python
|
opy/_regtest/src/build/testdata/future_import.py
|
Schweinepriester/oil
|
8b0e5c58a825223341896064d63a95c8b57a9c05
|
[
"Apache-2.0"
] | 2,209
|
2016-11-20T10:32:58.000Z
|
2022-03-31T20:51:27.000Z
|
opy/_regtest/src/build/testdata/future_import.py
|
Schweinepriester/oil
|
8b0e5c58a825223341896064d63a95c8b57a9c05
|
[
"Apache-2.0"
] | 1,074
|
2016-12-07T05:02:48.000Z
|
2022-03-22T02:09:11.000Z
|
opy/_regtest/src/build/testdata/future_import.py
|
Schweinepriester/oil
|
8b0e5c58a825223341896064d63a95c8b57a9c05
|
[
"Apache-2.0"
] | 147
|
2016-12-11T04:13:28.000Z
|
2022-03-27T14:50:00.000Z
|
#!/usr/bin/env python
"""
future_import.py
"""
from __future__ import print_function
print('future print')
| 13.5
| 37
| 0.740741
| 15
| 108
| 4.933333
| 0.666667
| 0.324324
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 108
| 7
| 38
| 15.428571
| 0.770833
| 0.342593
| 0
| 0
| 0
| 0
| 0.190476
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 1
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 6
|
521c8bc04df1cf2dcbac38020749dbcda910a3fc
| 195
|
py
|
Python
|
providers/users.py
|
LauraForde/FitKit-API
|
05faf0a738b410c01b02999e47a465c58864c426
|
[
"MIT"
] | null | null | null |
providers/users.py
|
LauraForde/FitKit-API
|
05faf0a738b410c01b02999e47a465c58864c426
|
[
"MIT"
] | null | null | null |
providers/users.py
|
LauraForde/FitKit-API
|
05faf0a738b410c01b02999e47a465c58864c426
|
[
"MIT"
] | null | null | null |
from providers.couchProvider import CouchProvider
import flask
from flask import request, Response
data_provider=CouchProvider
def read_user(data_provider):
return data_provider.read_user()
| 24.375
| 49
| 0.846154
| 25
| 195
| 6.4
| 0.52
| 0.225
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107692
| 195
| 8
| 50
| 24.375
| 0.91954
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.5
| 0.166667
| 0.833333
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 1
| 0
|
0
| 6
|
525dd83de67cfdb568999126ec91e5153f3e71d8
| 47
|
py
|
Python
|
demo2.py
|
KulvinderSingh26/hello-world
|
758bb890db565c699b29a1a05e601d06a0f001cc
|
[
"MIT"
] | null | null | null |
demo2.py
|
KulvinderSingh26/hello-world
|
758bb890db565c699b29a1a05e601d06a0f001cc
|
[
"MIT"
] | null | null | null |
demo2.py
|
KulvinderSingh26/hello-world
|
758bb890db565c699b29a1a05e601d06a0f001cc
|
[
"MIT"
] | null | null | null |
print("This file is created in master branch")
| 23.5
| 46
| 0.765957
| 8
| 47
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148936
| 47
| 1
| 47
| 47
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0.787234
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
526e370dd0d792cfffbbea4d78179e4de478aa06
| 65
|
py
|
Python
|
Inheritance/Exercises/02. zoo/project/gorilla.py
|
geodimitrov/PythonOOP_SoftUni
|
f1c6718c878b618b3ab3f174cd4d187bd178940b
|
[
"MIT"
] | 1
|
2021-06-30T11:53:44.000Z
|
2021-06-30T11:53:44.000Z
|
Inheritance/Exercises/02. zoo/project/gorilla.py
|
geodimitrov/PythonOOP_SoftUni
|
f1c6718c878b618b3ab3f174cd4d187bd178940b
|
[
"MIT"
] | null | null | null |
Inheritance/Exercises/02. zoo/project/gorilla.py
|
geodimitrov/PythonOOP_SoftUni
|
f1c6718c878b618b3ab3f174cd4d187bd178940b
|
[
"MIT"
] | null | null | null |
from project.mammal import Mammal
class Gorilla(Mammal):
pass
| 21.666667
| 33
| 0.784615
| 9
| 65
| 5.666667
| 0.777778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 65
| 3
| 34
| 21.666667
| 0.927273
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 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
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
bfe6189a532ff69e293d786a550f4d6c2a0aca86
| 25
|
py
|
Python
|
OledDisplay/__init__.py
|
jcksnvllxr80/MidiController
|
de6d3c983cd27408e88a744a0a4d3c887efa3d54
|
[
"MIT"
] | null | null | null |
OledDisplay/__init__.py
|
jcksnvllxr80/MidiController
|
de6d3c983cd27408e88a744a0a4d3c887efa3d54
|
[
"MIT"
] | null | null | null |
OledDisplay/__init__.py
|
jcksnvllxr80/MidiController
|
de6d3c983cd27408e88a744a0a4d3c887efa3d54
|
[
"MIT"
] | null | null | null |
from OledDisplay import *
| 25
| 25
| 0.84
| 3
| 25
| 7
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12
| 25
| 1
| 25
| 25
| 0.954545
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
bfed4ee5ed33293e273b78e5bc02c54a903f05cd
| 25
|
py
|
Python
|
main.py
|
marcoshr/Insulin-Dosage-Calculator
|
759a4d0ba4324b728cfef5255bf7190ce0237cd0
|
[
"MIT"
] | 1
|
2021-09-04T22:22:03.000Z
|
2021-09-04T22:22:03.000Z
|
main.py
|
marcoshr/Insulin-Dosage-Calculator
|
759a4d0ba4324b728cfef5255bf7190ce0237cd0
|
[
"MIT"
] | 5
|
2021-09-05T00:14:28.000Z
|
2021-09-05T00:54:11.000Z
|
main.py
|
marcoshr/Insulin-Dosage-Calculator
|
759a4d0ba4324b728cfef5255bf7190ce0237cd0
|
[
"MIT"
] | null | null | null |
print("Holaaaaa maaaaaa")
| 25
| 25
| 0.8
| 3
| 25
| 6.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04
| 25
| 1
| 25
| 25
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0.615385
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
5e7f26862d2fc99cc83eb57271ee782cace4ffa6
| 9,042
|
py
|
Python
|
.openshift-ci/tests/test_runners.py
|
stackrox/stackrox
|
3b2929fd5f2bc68d5742bd958a22e03202ae6be4
|
[
"Apache-2.0"
] | 22
|
2022-03-31T14:32:18.000Z
|
2022-03-31T22:11:30.000Z
|
.openshift-ci/tests/test_runners.py
|
stackrox/stackrox
|
3b2929fd5f2bc68d5742bd958a22e03202ae6be4
|
[
"Apache-2.0"
] | 5
|
2022-03-31T14:35:28.000Z
|
2022-03-31T22:40:13.000Z
|
.openshift-ci/tests/test_runners.py
|
stackrox/stackrox
|
3b2929fd5f2bc68d5742bd958a22e03202ae6be4
|
[
"Apache-2.0"
] | 4
|
2022-03-31T16:33:58.000Z
|
2022-03-31T22:19:26.000Z
|
import unittest
from unittest.mock import Mock
from runners import ClusterTestRunner, ClusterTestSetsRunner
class TestClusterTestRunner(unittest.TestCase):
def test_provisions(self):
cluster = Mock()
ClusterTestRunner(cluster=cluster).run()
cluster.provision.assert_called_once()
def test_runs_pre_test(self):
pre_test = Mock()
ClusterTestRunner(pre_test=pre_test).run()
pre_test.run.assert_called_once()
def test_runs_test(self):
test = Mock()
ClusterTestRunner(test=test).run()
test.run.assert_called_once()
def test_runs_post_test(self):
post_test = Mock()
ClusterTestRunner(post_test=post_test).run()
post_test.run.assert_called_once()
def test_runs_final_post(self):
post_test = Mock()
ClusterTestRunner(final_post=post_test).run()
post_test.run.assert_called_once()
def test_tearsdown(self):
cluster = Mock()
ClusterTestRunner(cluster=cluster).run()
cluster.teardown.assert_called_once()
def test_post_gets_output_from_test(self):
test = Mock()
test.test_output_dirs = ["a", "b"]
post_test = Mock()
ClusterTestRunner(test=test, post_test=post_test).run()
post_test.run.assert_called_with(test_output_dirs=["a", "b"])
def test_provision_failure(self):
cluster = Mock()
test = Mock()
post_test = Mock()
final_post = Mock()
cluster.provision.side_effect = Exception("oops")
with self.assertRaisesRegex(Exception, "oops"):
ClusterTestRunner(
cluster=cluster, test=test, post_test=post_test, final_post=final_post
).run()
test.run.assert_not_called() # skips test
post_test.run.assert_not_called() # skips post test
cluster.teardown.assert_called_once() # still tearsdown
final_post.run.assert_called_once() # still runs the final post
def test_pre_test_failure(self):
cluster = Mock()
pre_test = Mock()
test = Mock()
post_test = Mock()
pre_test.run.side_effect = Exception("oops")
with self.assertRaisesRegex(Exception, "oops"):
ClusterTestRunner(
cluster=cluster, pre_test=pre_test, test=test, post_test=post_test
).run()
test.run.assert_not_called() # skips test
post_test.run.assert_not_called() # skips post test
cluster.teardown.assert_called_once() # still tearsdown
def test_run_failure(self):
cluster = Mock()
test = Mock()
post_test = Mock()
test.run.side_effect = Exception("oops")
with self.assertRaisesRegex(Exception, "oops"):
ClusterTestRunner(cluster=cluster, test=test, post_test=post_test).run()
test.run.assert_called_once() # skips test
post_test.run.assert_called_once() # still post tests
cluster.teardown.assert_called_once() # still tearsdown
def test_post_failure(self):
cluster = Mock()
test = Mock()
post_test = Mock()
post_test.run.side_effect = Exception("oops")
with self.assertRaisesRegex(Exception, "oops"):
ClusterTestRunner(cluster=cluster, test=test, post_test=post_test).run()
cluster.teardown.assert_called_once() # still tearsdown
def test_run_and_post_test_failure(self):
cluster = Mock()
test = Mock()
post_test = Mock()
test.run.side_effect = Exception("run oops")
post_test.run.side_effect = Exception("post test oops")
with self.assertRaisesRegex(Exception, "run oops"): # the run error is #1
ClusterTestRunner(cluster=cluster, test=test, post_test=post_test).run()
cluster.teardown.assert_called_once() # still tearsdown
def test_run_and_post_test_and_teardown_failure(self):
cluster = Mock()
test = Mock()
post_test = Mock()
test.run.side_effect = Exception("run oops")
post_test.run.side_effect = Exception("post test oops")
cluster.teardown.side_effect = Exception("teardown oops")
with self.assertRaisesRegex(Exception, "run oops"): # the run error is #1
ClusterTestRunner(cluster=cluster, test=test, post_test=post_test).run()
def test_post_test_and_teardown_failure(self):
cluster = Mock()
test = Mock()
post_test = Mock()
post_test.run.side_effect = Exception("post test oops")
cluster.teardown.side_effect = Exception("teardown oops")
with self.assertRaisesRegex(
Exception, "post test oops"
): # the post_test error is #1
ClusterTestRunner(cluster=cluster, test=test, post_test=post_test).run()
def test_provision_and_teardown_failure(self):
cluster = Mock()
test = Mock()
post_test = Mock()
cluster.provision.side_effect = Exception("provision oops")
cluster.teardown.side_effect = Exception("teardown oops")
with self.assertRaisesRegex(
Exception, "provision oops"
): # the provision error is #1
ClusterTestRunner(cluster=cluster, test=test, post_test=post_test).run()
def test_pre_test_and_teardown_failure(self):
cluster = Mock()
pre_test = Mock()
test = Mock()
post_test = Mock()
pre_test.run.side_effect = Exception("pre test oops")
cluster.teardown.side_effect = Exception("teardown oops")
with self.assertRaisesRegex(
Exception, "pre test oops"
): # the pre test error is #1
ClusterTestRunner(
cluster=cluster, pre_test=pre_test, test=test, post_test=post_test
).run()
def test_teardown_and_final_post_failure(self):
cluster = Mock()
cluster.teardown.side_effect = Exception("teardown oops")
final_post = Mock()
final_post.run.side_effect = Exception("final post oops")
with self.assertRaisesRegex(
Exception, "teardown oops"
): # the teardown error is #1
ClusterTestRunner(cluster=cluster, final_post=final_post).run()
class TestClusterTestSetsRunner(unittest.TestCase):
def test_provisions(self):
cluster = Mock()
ClusterTestSetsRunner(cluster=cluster).run()
cluster.provision.assert_called_once()
def test_tearsdown(self):
cluster = Mock()
ClusterTestSetsRunner(cluster=cluster).run()
cluster.teardown.assert_called_once()
def test_runs_pre_test(self):
pre_test = Mock()
ClusterTestSetsRunner(sets=[{"pre_test": pre_test}]).run()
pre_test.run.assert_called_once()
def test_runs_test(self):
test = Mock()
ClusterTestSetsRunner(sets=[{"test": test}]).run()
test.run.assert_called_once()
def test_runs_post_test(self):
post_test = Mock()
ClusterTestSetsRunner(sets=[{"post_test": post_test}]).run()
post_test.run.assert_called_once()
def test_runs_nth_pre_test(self):
pre_test = Mock()
ClusterTestSetsRunner(sets=[{}, {"pre_test": pre_test}]).run()
pre_test.run.assert_called_once()
def test_runs_nth_test(self):
test = Mock()
ClusterTestSetsRunner(sets=[{"test": test}, {}]).run()
test.run.assert_called_once()
def test_runs_nth_post_test(self):
post_test = Mock()
ClusterTestSetsRunner(sets=[{}, {"post_test": post_test}, {}]).run()
post_test.run.assert_called_once()
# Failure semantics
def test_initial_failure_does_not_halt_the_set(self):
test1 = Mock()
test1.run.side_effect = Exception("test1 oops")
test2 = Mock()
with self.assertRaisesRegex(Exception, "test1 oops"):
ClusterTestSetsRunner(sets=[{"test": test1}, {"test": test2}]).run()
test2.run.assert_called_once()
def test_first_failure_is_reported(self):
test1 = Mock()
test1.run.side_effect = Exception("test1 oops")
test2 = Mock()
test2.run.side_effect = Exception("test2 oops")
with self.assertRaisesRegex(Exception, "test1 oops"):
ClusterTestSetsRunner(sets=[{"test": test1}, {"test": test2}]).run()
def test_can_always_run(self):
test1 = Mock()
test1.run.side_effect = Exception("test1 oops")
test2 = Mock()
post_test2 = Mock()
test3 = Mock()
post_test3 = Mock()
with self.assertRaisesRegex(Exception, "test1 oops"):
ClusterTestSetsRunner(
sets=[
{"test": test1},
{"test": test2, "post_test": post_test2, "always_run": False},
{"test": test3, "post_test": post_test3},
]
).run()
test2.run.assert_not_called()
post_test2.run.assert_not_called()
test3.run.assert_called_once()
post_test3.run.assert_called_once()
| 37.991597
| 86
| 0.635921
| 1,042
| 9,042
| 5.255278
| 0.060461
| 0.099343
| 0.059167
| 0.055515
| 0.870526
| 0.804419
| 0.775931
| 0.758583
| 0.727173
| 0.69832
| 0
| 0.005927
| 0.253594
| 9,042
| 237
| 87
| 38.151899
| 0.805453
| 0.037713
| 0
| 0.682927
| 0
| 0
| 0.050605
| 0
| 0
| 0
| 0
| 0
| 0.219512
| 1
| 0.136585
| false
| 0
| 0.014634
| 0
| 0.160976
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
5ed356682c134a07a78eb89908376ed0ba09c688
| 44
|
py
|
Python
|
pypi_packages/adabelief_tf0.0.1/adabelief_tf/__init__.py
|
wes-chen/Adabelief-Optimizer
|
2e4e57cb75e79fe3f72051041b6aec09549b2d85
|
[
"BSD-2-Clause"
] | 1,005
|
2020-10-16T02:40:57.000Z
|
2022-03-21T19:51:27.000Z
|
pypi_packages/adabelief_tf0.0.1/adabelief_tf/__init__.py
|
wes-chen/Adabelief-Optimizer
|
2e4e57cb75e79fe3f72051041b6aec09549b2d85
|
[
"BSD-2-Clause"
] | 56
|
2020-10-16T16:27:18.000Z
|
2022-03-31T18:35:56.000Z
|
pypi_packages/adabelief_tf0.0.1/adabelief_tf/__init__.py
|
wes-chen/Adabelief-Optimizer
|
2e4e57cb75e79fe3f72051041b6aec09549b2d85
|
[
"BSD-2-Clause"
] | 118
|
2020-10-16T06:40:24.000Z
|
2022-03-25T05:29:48.000Z
|
from .AdaBelief_tf import AdaBeliefOptimizer
| 44
| 44
| 0.909091
| 5
| 44
| 7.8
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.068182
| 44
| 1
| 44
| 44
| 0.95122
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
0dea2f7501151e6dd57d2396a2b0c6d20f882203
| 132
|
py
|
Python
|
MarioGame/abs_filepath.py
|
LuterGS/OSSP1_RL
|
f3e1054cd7d0b7f41f376697f2de005d55a42e64
|
[
"MIT"
] | 2
|
2021-06-12T14:17:08.000Z
|
2021-06-12T15:05:53.000Z
|
MarioGame/abs_filepath.py
|
LuterGS/OSSP1_RL
|
f3e1054cd7d0b7f41f376697f2de005d55a42e64
|
[
"MIT"
] | null | null | null |
MarioGame/abs_filepath.py
|
LuterGS/OSSP1_RL
|
f3e1054cd7d0b7f41f376697f2de005d55a42e64
|
[
"MIT"
] | 2
|
2021-06-06T07:52:03.000Z
|
2021-06-20T19:10:51.000Z
|
import os
REAL_PATH = os.path.dirname(os.path.realpath(__file__)) + "/"
ABS_PATH = os.path.dirname(os.path.abspath(__file__)) + "/"
| 33
| 61
| 0.712121
| 20
| 132
| 4.2
| 0.45
| 0.285714
| 0.238095
| 0.404762
| 0.547619
| 0.547619
| 0
| 0
| 0
| 0
| 0
| 0
| 0.090909
| 132
| 4
| 62
| 33
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0.015038
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 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
| 1
| 0
| 0
| 0
|
0
| 6
|
0dee6a4e235df6fc12f811731d257711bbaa5677
| 38
|
py
|
Python
|
dbq/__init__.py
|
mattbriancon/django-dbq
|
68e4088259ef677bd8014096eb93a62cbef8fb6d
|
[
"Apache-2.0"
] | 1
|
2021-03-11T21:45:12.000Z
|
2021-03-11T21:45:12.000Z
|
dbq/__init__.py
|
mattbriancon/django-dbq
|
68e4088259ef677bd8014096eb93a62cbef8fb6d
|
[
"Apache-2.0"
] | null | null | null |
dbq/__init__.py
|
mattbriancon/django-dbq
|
68e4088259ef677bd8014096eb93a62cbef8fb6d
|
[
"Apache-2.0"
] | null | null | null |
from .tasks import task # noqa: F401
| 19
| 37
| 0.710526
| 6
| 38
| 4.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 0.210526
| 38
| 1
| 38
| 38
| 0.8
| 0.263158
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
df237d326aae878cb5dc2d061e0fd88d9bb9ab42
| 93
|
py
|
Python
|
src/modules/__init__.py
|
yunyuyuan/news
|
605b2bc79ed7092c693d06fc1da82f58c3665170
|
[
"MIT"
] | null | null | null |
src/modules/__init__.py
|
yunyuyuan/news
|
605b2bc79ed7092c693d06fc1da82f58c3665170
|
[
"MIT"
] | null | null | null |
src/modules/__init__.py
|
yunyuyuan/news
|
605b2bc79ed7092c693d06fc1da82f58c3665170
|
[
"MIT"
] | null | null | null |
class NewsModule:
def __init__(self):
pass
def update(self):
pass
| 10.333333
| 23
| 0.548387
| 10
| 93
| 4.7
| 0.7
| 0.340426
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.376344
| 93
| 8
| 24
| 11.625
| 0.810345
| 0
| 0
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0.4
| 0
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 6
|
df332f25934255ec6b784ad51272a4e53e678bc6
| 173
|
py
|
Python
|
rotkehlchen/chain/ethereum/utils.py
|
coblee/rotki
|
d675f5c2d0df5176337b7b10038524ee74923482
|
[
"BSD-3-Clause"
] | null | null | null |
rotkehlchen/chain/ethereum/utils.py
|
coblee/rotki
|
d675f5c2d0df5176337b7b10038524ee74923482
|
[
"BSD-3-Clause"
] | 10
|
2020-10-06T18:57:17.000Z
|
2022-03-27T06:33:54.000Z
|
rotkehlchen/chain/ethereum/utils.py
|
coblee/rotki
|
d675f5c2d0df5176337b7b10038524ee74923482
|
[
"BSD-3-Clause"
] | null | null | null |
from rotkehlchen.fval import FVal
def token_normalized_value(token_amount: int, token_decimals: int) -> FVal:
return token_amount / (FVal(10) ** FVal(token_decimals))
| 28.833333
| 75
| 0.763006
| 24
| 173
| 5.25
| 0.541667
| 0.174603
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.013333
| 0.132948
| 173
| 5
| 76
| 34.6
| 0.826667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 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
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
df3564b8ca5ab9c86e58323c02c610209455887c
| 320
|
py
|
Python
|
ensemble/__init__.py
|
adityajn105/MLfromScratch
|
ea0758d4039051268d7f3af8799e2b005dbc2ebe
|
[
"MIT"
] | 16
|
2019-12-17T04:24:51.000Z
|
2021-12-15T18:31:41.000Z
|
ensemble/__init__.py
|
adityajn105/MLfromScratch
|
ea0758d4039051268d7f3af8799e2b005dbc2ebe
|
[
"MIT"
] | null | null | null |
ensemble/__init__.py
|
adityajn105/MLfromScratch
|
ea0758d4039051268d7f3af8799e2b005dbc2ebe
|
[
"MIT"
] | 5
|
2019-12-17T04:24:55.000Z
|
2022-01-23T15:18:24.000Z
|
from .forest import RandomForestClassifier, RandomForestRegressor
from .boosting import GradientBoostingRegressor, GradientBoostingClassifier
from .voting import VotingClassifier
__all__ = ['RandomForestClassifier','RandomForestRegressor','VotingClassifier',
'GradientBoostingRegressor','GradientBoostingClassifier']
| 45.714286
| 79
| 0.865625
| 20
| 320
| 13.65
| 0.55
| 0.315018
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.065625
| 320
| 7
| 80
| 45.714286
| 0.913043
| 0
| 0
| 0
| 0
| 0
| 0.34375
| 0.29375
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.6
| 0
| 0.6
| 0
| 1
| 0
| 1
| null | 1
| 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
| 1
| 0
|
0
| 6
|
10e5913b1b1627837f99fe9dc8933daf467049c7
| 162
|
py
|
Python
|
morepath/tests/fixtures/self_scan/__init__.py
|
hugovk/morepath
|
5596f9ce43ee4e5cd73eaa2ab9ef37825f88ae28
|
[
"BSD-3-Clause"
] | 314
|
2015-01-01T01:42:52.000Z
|
2022-01-07T21:46:15.000Z
|
morepath/tests/fixtures/self_scan/__init__.py
|
hugovk/morepath
|
5596f9ce43ee4e5cd73eaa2ab9ef37825f88ae28
|
[
"BSD-3-Clause"
] | 369
|
2015-01-02T19:10:40.000Z
|
2021-07-03T04:37:27.000Z
|
morepath/tests/fixtures/self_scan/__init__.py
|
hugovk/morepath
|
5596f9ce43ee4e5cd73eaa2ab9ef37825f88ae28
|
[
"BSD-3-Clause"
] | 37
|
2015-01-11T09:22:02.000Z
|
2021-07-02T20:48:20.000Z
|
def get_this_package():
from morepath.autosetup import caller_package
return caller_package(1)
def do_scan():
import morepath
morepath.scan()
| 14.727273
| 49
| 0.722222
| 21
| 162
| 5.333333
| 0.619048
| 0.232143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007752
| 0.203704
| 162
| 10
| 50
| 16.2
| 0.860465
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| 0
| 1
| 0.333333
| true
| 0
| 0.333333
| 0
| 0.833333
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| null | 1
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| null | 0
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| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
802030c28439bd7f4295b6d405690f741ade7255
| 77
|
py
|
Python
|
flow_py_sdk/utils/__init__.py
|
janezpodhostnik/flow-py-sdk
|
8b10f4ca2290f5d31920b86fd93a68a643cb1c75
|
[
"MIT"
] | 21
|
2020-11-25T16:30:53.000Z
|
2022-03-08T06:24:02.000Z
|
flow_py_sdk/utils/__init__.py
|
janezpodhostnik/flow-py-sdk
|
8b10f4ca2290f5d31920b86fd93a68a643cb1c75
|
[
"MIT"
] | 29
|
2021-03-06T19:04:33.000Z
|
2022-03-18T15:16:44.000Z
|
flow_py_sdk/utils/__init__.py
|
janezpodhostnik/flow-py-sdk
|
8b10f4ca2290f5d31920b86fd93a68a643cb1c75
|
[
"MIT"
] | 15
|
2021-03-06T18:36:40.000Z
|
2022-02-09T15:14:01.000Z
|
from .verify_user_signature import verify_user_signature, CompositeSignature
| 38.5
| 76
| 0.909091
| 9
| 77
| 7.333333
| 0.666667
| 0.30303
| 0.575758
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.064935
| 77
| 1
| 77
| 77
| 0.916667
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| true
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| null | 0
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| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
8024c0db49ec55bdc014198dabc14543f43ef03d
| 77
|
py
|
Python
|
lendingblock/orders.py
|
lendingblock/lb-py
|
56466d1e45013e2817cc0c1db7a20b911a1ac0e4
|
[
"BSD-3-Clause"
] | 1
|
2018-05-13T18:37:06.000Z
|
2018-05-13T18:37:06.000Z
|
lendingblock/orders.py
|
lendingblock/lb-py
|
56466d1e45013e2817cc0c1db7a20b911a1ac0e4
|
[
"BSD-3-Clause"
] | 2
|
2018-05-14T08:46:33.000Z
|
2018-05-14T08:52:48.000Z
|
lendingblock/orders.py
|
lendingblock/lb-py
|
56466d1e45013e2817cc0c1db7a20b911a1ac0e4
|
[
"BSD-3-Clause"
] | null | null | null |
from .component import CrudComponent
class Orders(CrudComponent):
pass
| 12.833333
| 36
| 0.779221
| 8
| 77
| 7.5
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.168831
| 77
| 5
| 37
| 15.4
| 0.9375
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
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| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
802f0d000c53848e7d0c8f3d26a4267eadbf91e2
| 83
|
py
|
Python
|
lib/eventio/__init__.py
|
bboser/eventio
|
cdad47772d94e87a8ca8927e8d578fc7aba78266
|
[
"MIT"
] | 6
|
2018-12-04T02:53:20.000Z
|
2020-03-08T15:42:16.000Z
|
lib/eventio/__init__.py
|
bboser/eventio
|
cdad47772d94e87a8ca8927e8d578fc7aba78266
|
[
"MIT"
] | null | null | null |
lib/eventio/__init__.py
|
bboser/eventio
|
cdad47772d94e87a8ca8927e8d578fc7aba78266
|
[
"MIT"
] | null | null | null |
from .kernel import *
from .traps import *
from .task import *
from .sync import *
| 16.6
| 21
| 0.710843
| 12
| 83
| 4.916667
| 0.5
| 0.508475
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.192771
| 83
| 4
| 22
| 20.75
| 0.880597
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| 1
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| 0
| null | 1
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
805534a76918bf1e4315bb490a00e22febdd3419
| 24
|
py
|
Python
|
FireBase/__init__.py
|
c17r/tsace
|
59c6e0388429943dc3de879745119f9c94cd9ccc
|
[
"MIT"
] | null | null | null |
FireBase/__init__.py
|
c17r/tsace
|
59c6e0388429943dc3de879745119f9c94cd9ccc
|
[
"MIT"
] | null | null | null |
FireBase/__init__.py
|
c17r/tsace
|
59c6e0388429943dc3de879745119f9c94cd9ccc
|
[
"MIT"
] | null | null | null |
from .firebase import *
| 12
| 23
| 0.75
| 3
| 24
| 6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 24
| 1
| 24
| 24
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| 1
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| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
33fcd9016710bc006cefc7321848b71b5bd068c0
| 95
|
py
|
Python
|
stonehenge/components/ui/base.py
|
RobertTownley/stonehenge
|
376b8e1501dd12ac1bcec5de680a5b521b0d949c
|
[
"MIT"
] | 1
|
2018-09-07T14:15:31.000Z
|
2018-09-07T14:15:31.000Z
|
stonehenge/components/ui/base.py
|
RobertTownley/stonehenge
|
376b8e1501dd12ac1bcec5de680a5b521b0d949c
|
[
"MIT"
] | 5
|
2018-09-06T01:48:12.000Z
|
2021-05-08T10:47:00.000Z
|
stonehenge/components/ui/base.py
|
RobertTownley/stonehenge
|
376b8e1501dd12ac1bcec5de680a5b521b0d949c
|
[
"MIT"
] | null | null | null |
from stonehenge.components.component import Component
class UIComponent(Component):
pass
| 15.833333
| 53
| 0.810526
| 10
| 95
| 7.7
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136842
| 95
| 5
| 54
| 19
| 0.939024
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
| 0
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
1d55be6d4f53554987cf56a5cf4ba28671ef506d
| 73
|
py
|
Python
|
lib/renderer/gl/__init__.py
|
caxapexac/PIFu
|
4e5112d91cf9808a5c01fc43809344c2c7aae746
|
[
"MIT"
] | null | null | null |
lib/renderer/gl/__init__.py
|
caxapexac/PIFu
|
4e5112d91cf9808a5c01fc43809344c2c7aae746
|
[
"MIT"
] | null | null | null |
lib/renderer/gl/__init__.py
|
caxapexac/PIFu
|
4e5112d91cf9808a5c01fc43809344c2c7aae746
|
[
"MIT"
] | null | null | null |
from .framework import *
from .render import *
from .cam_render import *
| 18.25
| 25
| 0.753425
| 10
| 73
| 5.4
| 0.5
| 0.37037
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164384
| 73
| 3
| 26
| 24.333333
| 0.885246
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
1d804a4163a7b8810278901b3a029d2186de7d6f
| 113
|
py
|
Python
|
office365/sharepoint/search/query/queryAutoCompletionResults.py
|
wreiner/Office365-REST-Python-Client
|
476bbce4f5928a140b4f5d33475d0ac9b0783530
|
[
"MIT"
] | 544
|
2016-08-04T17:10:16.000Z
|
2022-03-31T07:17:20.000Z
|
office365/sharepoint/search/query/queryAutoCompletionResults.py
|
wreiner/Office365-REST-Python-Client
|
476bbce4f5928a140b4f5d33475d0ac9b0783530
|
[
"MIT"
] | 438
|
2016-10-11T12:24:22.000Z
|
2022-03-31T19:30:35.000Z
|
office365/sharepoint/search/query/queryAutoCompletionResults.py
|
wreiner/Office365-REST-Python-Client
|
476bbce4f5928a140b4f5d33475d0ac9b0783530
|
[
"MIT"
] | 202
|
2016-08-22T19:29:40.000Z
|
2022-03-30T20:26:15.000Z
|
from office365.runtime.client_value import ClientValue
class QueryAutoCompletionResults(ClientValue):
pass
| 18.833333
| 54
| 0.840708
| 11
| 113
| 8.545455
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.03
| 0.115044
| 113
| 5
| 55
| 22.6
| 0.91
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
1d9d4ff8a6dc6d812b54d97a970af731236cfea6
| 401
|
py
|
Python
|
model/criterions/__init__.py
|
UESTC-Liuxin/CVMI_Sementic_Segmentation
|
dc5bf6e940cf6961ef65abb6e7ec372f29d55249
|
[
"Apache-2.0"
] | null | null | null |
model/criterions/__init__.py
|
UESTC-Liuxin/CVMI_Sementic_Segmentation
|
dc5bf6e940cf6961ef65abb6e7ec372f29d55249
|
[
"Apache-2.0"
] | null | null | null |
model/criterions/__init__.py
|
UESTC-Liuxin/CVMI_Sementic_Segmentation
|
dc5bf6e940cf6961ef65abb6e7ec372f29d55249
|
[
"Apache-2.0"
] | null | null | null |
'''
Author: Liu Xin
Date: 2021-11-18 09:58:40
LastEditors: Liu Xin
LastEditTime: 2021-11-29 22:50:42
Description: file content
FilePath: /CVMI_Sementic_Segmentation/model/criterions/__init__.py
'''
from model.criterions.ce_loss import *
from model.criterions.dice_loss import *
from model.criterions.ce_loss import *
from model.criterions.se_loss import *
from model.criterions.encnet_loss import *
| 25.0625
| 66
| 0.798005
| 61
| 401
| 5.065574
| 0.557377
| 0.291262
| 0.307443
| 0.245955
| 0.449838
| 0.323625
| 0.323625
| 0.323625
| 0.323625
| 0
| 0
| 0.077778
| 0.102244
| 401
| 15
| 67
| 26.733333
| 0.780556
| 0.471322
| 0
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
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| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
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| 0
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| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
d534eff5e8a631a59a813b67b41c8ec8d378d2dc
| 4,696
|
py
|
Python
|
python/tests/test_kmeans.py
|
Duconnor/Pudding
|
4565f2ad9a933e83e9eacbc5ebe848599ea9cec1
|
[
"MIT"
] | 3
|
2022-01-08T05:05:30.000Z
|
2022-01-09T10:09:57.000Z
|
python/tests/test_kmeans.py
|
Duconnor/Pudding
|
4565f2ad9a933e83e9eacbc5ebe848599ea9cec1
|
[
"MIT"
] | null | null | null |
python/tests/test_kmeans.py
|
Duconnor/Pudding
|
4565f2ad9a933e83e9eacbc5ebe848599ea9cec1
|
[
"MIT"
] | null | null | null |
from pudding.clustering import kmeans
import pytest
import numpy as np
from sklearn.datasets import make_blobs
import pudding
def testKmeansToyData():
'''
Test KMeans uisng a toy dataset
'''
X = [[0.0, 0.0], [0.5, 0.0], [0.5, 1.0], [1.0, 1.0]]
initial_centers = [[0.0, 0.0], [1.0, 1.0]]
expected_membership = [0, 0, 1, 1]
expected_centers = [[0.25, 0.0], [0.75, 1.0]]
expected_iterations = 2
pudding_kmeans = pudding.clustering.KMeans(n_clusters=len(initial_centers), cuda_enabled=False)
pudding_kmeans.fit(np.array(X), initial_centers=initial_centers)
assert pudding_kmeans.membership.tolist() == expected_membership
for center, expected_center in zip(pudding_kmeans.centers, expected_centers):
assert center == pytest.approx(expected_center)
assert expected_iterations == pudding_kmeans.n_iter
pudding_kmeans = pudding.clustering.KMeans(n_clusters=len(initial_centers), cuda_enabled=True)
pudding_kmeans.fit(np.array(X), initial_centers=initial_centers)
assert pudding_kmeans.membership.tolist() == expected_membership
for center, expected_center in zip(pudding_kmeans.centers, expected_centers):
assert center == pytest.approx(expected_center)
assert expected_iterations == pudding_kmeans.n_iter
def testKmeansCPUGPU():
'''
Test our implementation with some randomly generated data between the CPU and GPU version
'''
# Generate random data
seed = 0
np.random.seed(seed)
n_examples = 3000
truth_centers = [[1, 1], [-1, -1], [1, -1]]
X, _ = make_blobs(n_samples=n_examples, centers=truth_centers, cluster_std=0.7)
# Our implementation CPU
cpu_kmeans = pudding.clustering.KMeans(n_clusters=3, cuda_enabled=False, rand_seed=seed)
cpu_kmeans.fit(X)
our_cpu_centers, our_cpu_membership, our_cpu_n_iter = cpu_kmeans.centers, cpu_kmeans.membership, cpu_kmeans.n_iter
# Our implementation GPU
gpu_kmeans = pudding.clustering.KMeans(n_clusters=3, cuda_enabled=True, rand_seed=seed)
gpu_kmeans.fit(X)
our_gpu_centers, our_gpu_membership, our_gpu_n_iter = gpu_kmeans.centers, gpu_kmeans.membership, gpu_kmeans.n_iter
# Assertions
assert our_cpu_membership.tolist() == our_gpu_membership.tolist()
for our_cpu_center, our_gpu_center in zip(our_cpu_centers, our_gpu_centers):
assert our_cpu_center == pytest.approx(our_gpu_center)
assert our_cpu_n_iter == our_gpu_n_iter
def testKmeansCPUGPULarge():
'''
Test our implementation with some randomly generated data between the CPU and GPU version using a larger number of data pooints
'''
# Generate random data
seed = 0
np.random.seed(seed)
n_examples = 1000000
truth_centers = [[1, 1], [-1, -1], [1, -1]]
X, _ = make_blobs(n_samples=n_examples, centers=truth_centers, cluster_std=0.7)
# Our implementation CPU
cpu_kmeans = pudding.clustering.KMeans(n_clusters=3, cuda_enabled=False, rand_seed=seed)
cpu_kmeans.fit(X)
our_cpu_centers = cpu_kmeans.centers
# Our implementation GPU
gpu_kmeans = pudding.clustering.KMeans(n_clusters=3, cuda_enabled=True, rand_seed=seed)
gpu_kmeans.fit(X)
our_gpu_centers = gpu_kmeans.centers
# Assertions
for our_cpu_center, our_gpu_center in zip(our_cpu_centers, our_gpu_centers):
assert our_cpu_center == pytest.approx(our_gpu_center, rel=1e-1)
def testKmeansEmptyCluster():
'''
Test KMeans when there is empty cluster
'''
X = [[0.0, 0.0], [0.5, 0.0], [0.5, 1.0], [1.0, 1.0]]
initial_centers = [[0.0, 0.0], [10.0, 10.0]]
expected_membership = [0, 0, 0, 0]
expected_centers = [[0.5, 0.5], [10.0, 10.0]]
expected_iterations = 2
cpu_kmeans = pudding.clustering.KMeans(n_clusters=len(initial_centers), cuda_enabled=False)
cpu_kmeans.fit(np.array(X), initial_centers=initial_centers)
centers, membership, n_iterations = cpu_kmeans.centers, cpu_kmeans.membership, cpu_kmeans.n_iter
assert membership.tolist() == expected_membership
for center, expected_center in zip(centers, expected_centers):
assert center == pytest.approx(expected_center)
assert expected_iterations == n_iterations
gpu_kmeans = pudding.clustering.KMeans(n_clusters=len(initial_centers), cuda_enabled=True)
gpu_kmeans.fit(np.array(X), initial_centers=initial_centers)
centers, membership, n_iterations = gpu_kmeans.centers, gpu_kmeans.membership, gpu_kmeans.n_iter
assert membership.tolist() == expected_membership
for center, expected_center in zip(centers, expected_centers):
assert center == pytest.approx(expected_center)
assert expected_iterations == n_iterations
| 39.462185
| 131
| 0.725511
| 674
| 4,696
| 4.795252
| 0.135015
| 0.014851
| 0.013923
| 0.071782
| 0.823639
| 0.803837
| 0.803837
| 0.80198
| 0.80198
| 0.80198
| 0
| 0.029427
| 0.167802
| 4,696
| 119
| 132
| 39.462185
| 0.797595
| 0.094974
| 0
| 0.547945
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.219178
| 1
| 0.054795
| false
| 0
| 0.068493
| 0
| 0.123288
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
d53a97105ca56e88a30463e43e3f5cf35a232fb2
| 79
|
py
|
Python
|
pc/__init__.py
|
zy6p/adjust
|
ddcde0a99c6d01038de1f4675ad9409759c03ef0
|
[
"Apache-2.0"
] | 1
|
2020-12-25T13:39:16.000Z
|
2020-12-25T13:39:16.000Z
|
pc/__init__.py
|
zy6p/adjust
|
ddcde0a99c6d01038de1f4675ad9409759c03ef0
|
[
"Apache-2.0"
] | null | null | null |
pc/__init__.py
|
zy6p/adjust
|
ddcde0a99c6d01038de1f4675ad9409759c03ef0
|
[
"Apache-2.0"
] | null | null | null |
from . import daoxian
from . import adjustfather
from . import inverseadjust
| 13.166667
| 27
| 0.78481
| 9
| 79
| 6.888889
| 0.555556
| 0.483871
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177215
| 79
| 5
| 28
| 15.8
| 0.953846
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
d54646bca6d0ddcd68d7bfa3afb6e7ef750a525f
| 4,927
|
py
|
Python
|
tests/test_data.py
|
Gaskell-1206/fastMRI
|
1b6d1f9020bc9209afa65ef9b9f2f3fa3348901c
|
[
"MIT"
] | 1
|
2020-09-29T22:31:03.000Z
|
2020-09-29T22:31:03.000Z
|
tests/test_data.py
|
Gaskell-1206/fastMRI
|
1b6d1f9020bc9209afa65ef9b9f2f3fa3348901c
|
[
"MIT"
] | null | null | null |
tests/test_data.py
|
Gaskell-1206/fastMRI
|
1b6d1f9020bc9209afa65ef9b9f2f3fa3348901c
|
[
"MIT"
] | null | null | null |
"""
Copyright (c) Facebook, Inc. and its affiliates.
This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""
from fastmri.data.mri_data import (
SliceDataset,
CombinedSliceDataset,
AnnotatedSliceDataset,
)
def test_slice_datasets(fastmri_mock_dataset, monkeypatch):
knee_path, brain_path, metadata = fastmri_mock_dataset
def retrieve_metadata_mock(a, fname):
return metadata[str(fname)]
monkeypatch.setattr(SliceDataset, "_retrieve_metadata", retrieve_metadata_mock)
for challenge in ("multicoil", "singlecoil"):
for split in ("train", "val", "test", "challenge"):
dataset = SliceDataset(
knee_path / f"{challenge}_{split}", transform=None, challenge=challenge
)
assert len(dataset) > 0
assert dataset[0] is not None
assert dataset[-1] is not None
for challenge in ("multicoil",):
for split in ("train", "val", "test", "challenge"):
dataset = SliceDataset(
brain_path / f"{challenge}_{split}", transform=None, challenge=challenge
)
assert len(dataset) > 0
assert dataset[0] is not None
assert dataset[-1] is not None
def test_combined_slice_dataset(fastmri_mock_dataset, monkeypatch):
knee_path, brain_path, metadata = fastmri_mock_dataset
def retrieve_metadata_mock(a, fname):
return metadata[str(fname)]
monkeypatch.setattr(SliceDataset, "_retrieve_metadata", retrieve_metadata_mock)
roots = [knee_path / "multicoil_train", knee_path / "multicoil_val"]
challenges = ["multicoil", "multicoil"]
transforms = [None, None]
dataset1 = SliceDataset(
root=roots[0], challenge=challenges[0], transform=transforms[0]
)
dataset2 = SliceDataset(
root=roots[1], challenge=challenges[1], transform=transforms[1]
)
comb_dataset = CombinedSliceDataset(
roots=roots, challenges=challenges, transforms=transforms
)
assert len(comb_dataset) == len(dataset1) + len(dataset2)
assert comb_dataset[0] is not None
assert comb_dataset[-1] is not None
roots = [brain_path / "multicoil_train", brain_path / "multicoil_val"]
challenges = ["multicoil", "multicoil"]
transforms = [None, None]
dataset1 = SliceDataset(
root=roots[0], challenge=challenges[0], transform=transforms[0]
)
dataset2 = SliceDataset(
root=roots[1], challenge=challenges[1], transform=transforms[1]
)
comb_dataset = CombinedSliceDataset(
roots=roots, challenges=challenges, transforms=transforms
)
assert len(comb_dataset) == len(dataset1) + len(dataset2)
assert comb_dataset[0] is not None
assert comb_dataset[-1] is not None
def test_annotated_slice_dataset(
fastmri_mock_dataset, fastmri_mock_annotation, monkeypatch
):
knee_path, brain_path, metadata = fastmri_mock_dataset
annotation_knee_csv, annotation_brain_csv = fastmri_mock_annotation
def download_csv_mock(a, version, subsplit, path):
if subsplit == "knee":
return annotation_knee_csv
else:
return annotation_brain_csv
def retrieve_metadata_mock(a, fname):
return metadata[str(fname)]
monkeypatch.setattr(AnnotatedSliceDataset, "download_csv", download_csv_mock)
monkeypatch.setattr(SliceDataset, "_retrieve_metadata", retrieve_metadata_mock)
for challenge in ("multicoil", "singlecoil"):
for split in ("train", "val", "test", "challenge"):
for multiple_annotation_policy in ("first", "random", "all"):
dataset = AnnotatedSliceDataset(
knee_path / f"{challenge}_{split}",
challenge=challenge,
subsplit="knee",
multiple_annotation_policy=multiple_annotation_policy,
)
assert len(dataset) > 0
assert dataset[0] is not None
assert dataset[-1] is not None
assert dataset[0][3]["annotation"] is not None
assert dataset[-1][3]["annotation"] is not None
for challenge in ("multicoil",):
for split in ("train", "val", "test", "challenge"):
for multiple_annotation_policy in ("first", "random", "all"):
dataset = AnnotatedSliceDataset(
brain_path / f"{challenge}_{split}",
challenge=challenge,
subsplit="brain",
multiple_annotation_policy=multiple_annotation_policy,
)
assert len(dataset) > 0
assert dataset[0] is not None
assert dataset[-1] is not None
assert dataset[0][3]["annotation"] is not None
assert dataset[-1][3]["annotation"] is not None
| 35.446043
| 88
| 0.637102
| 532
| 4,927
| 5.716165
| 0.157895
| 0.026307
| 0.047353
| 0.049326
| 0.818481
| 0.79875
| 0.79875
| 0.764551
| 0.764551
| 0.734298
| 0
| 0.012128
| 0.263649
| 4,927
| 138
| 89
| 35.702899
| 0.826075
| 0.034301
| 0
| 0.660194
| 0
| 0
| 0.095789
| 0
| 0
| 0
| 0
| 0
| 0.213592
| 1
| 0.067961
| false
| 0
| 0.009709
| 0.029126
| 0.126214
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
d58da70d3488289cfda8cd564bf7436e81e3e357
| 12,400
|
py
|
Python
|
openstack/tests/unit/cdn/v1/test_statistic.py
|
IamFive/sdk-python
|
223b04f90477f7de0f00b3e652d8672ba73271c8
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
openstack/tests/unit/cdn/v1/test_statistic.py
|
IamFive/sdk-python
|
223b04f90477f7de0f00b3e652d8672ba73271c8
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
openstack/tests/unit/cdn/v1/test_statistic.py
|
IamFive/sdk-python
|
223b04f90477f7de0f00b3e652d8672ba73271c8
|
[
"ECL-2.0",
"Apache-2.0"
] | null | null | null |
# 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 mock
import testtools
from openstack.cdn.v1 import statistic
class TestStatistic(testtools.TestCase):
def setUp(self):
super(TestStatistic, self).setUp()
class Test(statistic.Statistic):
base_path = '/cdn/statistics/test'
resource_key = 'resource'
self.sot = Test()
def _verify(self, test_method, mock_method,
mock_json=None,
method_args=[], method_kwargs={},
expected_args=[], expected_kwargs={}):
resp = mock.Mock()
resp.json.return_value = mock_json
resp.headers = {}
sess = mock.Mock()
mocked = getattr(sess, mock_method)
mocked.return_value = resp
method_args = [sess] + method_args
actual_result = test_method(*method_args, **method_kwargs)
mocked.assert_called_once_with(*expected_args, **expected_kwargs)
return actual_result
def test_query(self):
url = '/cdn/statistics/test'
body = {
"resource": {
"start_time": 1498838400000,
"end_time": 1502380500000,
"value": 835038583
}
}
kwargs = {
'start_time': 1,
'end_time': 2,
'domain_name': 'domain'
}
expected_kwargs = {
'endpoint_filter': self.sot.service,
'endpoint_override': None,
'params': kwargs
}
self._verify(self.sot.query, 'get',
mock_json=body,
method_kwargs=kwargs,
expected_args=[url],
expected_kwargs=expected_kwargs)
class TestStatisticDetail(testtools.TestCase):
def setUp(self):
super(TestStatisticDetail, self).setUp()
class Test(statistic.StatisticDetail):
base_path = '/cdn/statistics/test-detail'
resource_key = 'resource'
self.sot = Test()
def _verify(self, test_method, mock_method,
mock_json=None,
method_args=[], method_kwargs={},
expected_args=[], expected_kwargs={}):
resp = mock.Mock()
resp.json.return_value = mock_json
resp.headers = {}
sess = mock.Mock()
mocked = getattr(sess, mock_method)
mocked.return_value = resp
method_args = [sess] + method_args
actual_result = test_method(*method_args, **method_kwargs)
mocked.assert_called_once_with(*expected_args, **expected_kwargs)
return actual_result
def test_query(self):
url = '/cdn/statistics/test-detail'
body = {
"resource": {
"start_time": 1498838400000,
"end_time": 1502380500000,
"interval": 300,
"values": [1, 2, 3]
}
}
kwargs = {
'start_time': 1,
'end_time': 2,
'domain_name': 'domain'
}
expected_kwargs = {
'endpoint_filter': self.sot.service,
'endpoint_override': None,
'params': kwargs
}
self._verify(self.sot.query, 'get',
mock_json=body,
method_kwargs=kwargs,
expected_args=[url],
expected_kwargs=expected_kwargs)
class TestNetworkTraffic(testtools.TestCase):
def test_basic(self):
sot = statistic.NetworkTraffic()
self.assertEqual('/cdn/statistics/flux', sot.base_path)
self.assertEqual('flux', sot.resource_key)
self.assertIsNone(sot.resources_key)
self.assertEqual('cdn', sot.service.service_type)
self.assertFalse(sot.allow_create)
self.assertFalse(sot.allow_get)
self.assertFalse(sot.allow_update)
self.assertFalse(sot.allow_delete)
self.assertFalse(sot.allow_list)
self.assertDictEqual({'start_time': 'start_time',
'end_time': 'end_time',
'domain_name': 'domain_name'},
sot._query_mapping._mapping)
def test_make_it(self):
EXAMPLE = {
"start_time": 1498838400000,
"end_time": 1502380500000,
"value": 835038583
}
sot = statistic.NetworkTraffic(**EXAMPLE)
self.assertEqual(EXAMPLE['start_time'], sot.start_time)
self.assertEqual(EXAMPLE['end_time'], sot.end_time)
self.assertEqual(EXAMPLE['value'], sot.value)
class TestNetworkTrafficDetail(testtools.TestCase):
def test_basic(self):
sot = statistic.NetworkTrafficDetail()
self.assertEqual('/cdn/statistics/flux-detail', sot.base_path)
self.assertEqual('flux_detail', sot.resource_key)
self.assertIsNone(sot.resources_key)
self.assertEqual('cdn', sot.service.service_type)
self.assertFalse(sot.allow_create)
self.assertFalse(sot.allow_get)
self.assertFalse(sot.allow_update)
self.assertFalse(sot.allow_delete)
self.assertFalse(sot.allow_list)
self.assertDictEqual({'start_time': 'start_time',
'end_time': 'end_time',
'domain_name': 'domain_name',
'interval': 'interval'},
sot._query_mapping._mapping)
def test_make_it(self):
EXAMPLE = {
"start_time": 1498838400000,
"end_time": 1502380500000,
"interval": 300,
"values": [835038583, 835038584]
}
sot = statistic.NetworkTrafficDetail(**EXAMPLE)
self.assertEqual(EXAMPLE['start_time'], sot.start_time)
self.assertEqual(EXAMPLE['end_time'], sot.end_time)
self.assertEqual(EXAMPLE['interval'], sot.interval)
self.assertItemsEqual(EXAMPLE['values'], sot.values)
class TestBandwidthPeak(testtools.TestCase):
def test_basic(self):
sot = statistic.BandwidthPeak()
self.assertEqual('/cdn/statistics/bandwidth', sot.base_path)
self.assertEqual('bandwidth', sot.resource_key)
self.assertIsNone(sot.resources_key)
self.assertEqual('cdn', sot.service.service_type)
self.assertFalse(sot.allow_create)
self.assertFalse(sot.allow_get)
self.assertFalse(sot.allow_update)
self.assertFalse(sot.allow_delete)
self.assertFalse(sot.allow_list)
self.assertDictEqual({'start_time': 'start_time',
'end_time': 'end_time',
'domain_name': 'domain_name'},
sot._query_mapping._mapping)
def test_make_it(self):
EXAMPLE = {
"start_time": 1498838400000,
"end_time": 1502380500000,
"peak_time": 1502380400000,
"value": 835038583
}
sot = statistic.BandwidthPeak(**EXAMPLE)
self.assertEqual(EXAMPLE['start_time'], sot.start_time)
self.assertEqual(EXAMPLE['end_time'], sot.end_time)
self.assertEqual(EXAMPLE['peak_time'], sot.peaked_at)
self.assertEqual(EXAMPLE['value'], sot.value)
class TestBandWidthDetail(testtools.TestCase):
def test_basic(self):
sot = statistic.BandwidthDetail()
self.assertEqual('/cdn/statistics/bandwidth-detail', sot.base_path)
self.assertEqual('bandwidth_detail', sot.resource_key)
self.assertIsNone(sot.resources_key)
self.assertEqual('cdn', sot.service.service_type)
self.assertFalse(sot.allow_create)
self.assertFalse(sot.allow_get)
self.assertFalse(sot.allow_update)
self.assertFalse(sot.allow_delete)
self.assertFalse(sot.allow_list)
self.assertDictEqual({'start_time': 'start_time',
'end_time': 'end_time',
'domain_name': 'domain_name',
'interval': 'interval'},
sot._query_mapping._mapping)
def test_make_it(self):
EXAMPLE = {
"start_time": 1498838400000,
"end_time": 1502380500000,
"interval": 300,
"values": [835038583, 835038584]
}
sot = statistic.BandwidthDetail(**EXAMPLE)
self.assertEqual(EXAMPLE['start_time'], sot.start_time)
self.assertEqual(EXAMPLE['end_time'], sot.end_time)
self.assertEqual(EXAMPLE['interval'], sot.interval)
self.assertItemsEqual(EXAMPLE['values'], sot.values)
class TestConsumptionSummary(testtools.TestCase):
def test_basic(self):
sot = statistic.ConsumptionSummary()
self.assertEqual('/cdn/statistics/domain-summary', sot.base_path)
self.assertEqual('domain_summary', sot.resource_key)
self.assertIsNone(sot.resources_key)
self.assertEqual('cdn', sot.service.service_type)
self.assertFalse(sot.allow_create)
self.assertFalse(sot.allow_get)
self.assertFalse(sot.allow_update)
self.assertFalse(sot.allow_delete)
self.assertFalse(sot.allow_list)
self.assertDictEqual({'start_time': 'start_time',
'end_time': 'end_time',
'domain_name': 'domain_name',
'stat_type': 'stat_type',
'service_area': 'service_area'},
sot._query_mapping._mapping)
def test_make_it(self):
EXAMPLE = {
"start_time": 1513094400000,
"end_time": 1513180799346,
"value": 835038583,
"stat_type": "flux_hit_rate",
"service_area": "mainland_china"
}
sot = statistic.ConsumptionSummary(**EXAMPLE)
self.assertEqual(EXAMPLE['start_time'], sot.start_time)
self.assertEqual(EXAMPLE['end_time'], sot.end_time)
self.assertEqual(EXAMPLE['value'], sot.value)
self.assertEqual(EXAMPLE['stat_type'], sot.stat_type)
self.assertEqual(EXAMPLE['service_area'], sot.service_area)
class TestConsumptionSummaryDetail(testtools.TestCase):
def test_basic(self):
sot = statistic.ConsumptionSummaryDetail()
self.assertEqual('/cdn/statistics/domain-summary-detail',
sot.base_path)
self.assertEqual('domain_summary_detail', sot.resource_key)
self.assertIsNone(sot.resources_key)
self.assertEqual('cdn', sot.service.service_type)
self.assertFalse(sot.allow_create)
self.assertFalse(sot.allow_get)
self.assertFalse(sot.allow_update)
self.assertFalse(sot.allow_delete)
self.assertFalse(sot.allow_list)
self.assertDictEqual({'start_time': 'start_time',
'end_time': 'end_time',
'domain_name': 'domain_name',
'interval': 'interval',
'stat_type': 'stat_type',
'service_area': 'service_area'},
sot._query_mapping._mapping)
def test_make_it(self):
EXAMPLE = {
"start_time": 1498838400000,
"end_time": 1502380500000,
"interval": 300,
"stat_type": "bs_flux",
"values": [835038583, 835038584],
"service_area": "outside_mainland_china"
}
sot = statistic.ConsumptionSummaryDetail(**EXAMPLE)
self.assertEqual(EXAMPLE['start_time'], sot.start_time)
self.assertEqual(EXAMPLE['end_time'], sot.end_time)
self.assertEqual(EXAMPLE['interval'], sot.interval)
self.assertEqual(EXAMPLE['stat_type'], sot.stat_type)
self.assertEqual(EXAMPLE['service_area'], sot.service_area)
self.assertItemsEqual(EXAMPLE['values'], sot.values)
| 38.03681
| 75
| 0.594274
| 1,244
| 12,400
| 5.700161
| 0.13746
| 0.08673
| 0.076153
| 0.097306
| 0.833028
| 0.7989
| 0.750952
| 0.733606
| 0.682273
| 0.673953
| 0
| 0.038356
| 0.295645
| 12,400
| 325
| 76
| 38.153846
| 0.773529
| 0.042097
| 0
| 0.744526
| 0
| 0
| 0.131889
| 0.0209
| 0
| 0
| 0
| 0
| 0.321168
| 1
| 0.065693
| false
| 0
| 0.010949
| 0
| 0.120438
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
63864135ceea8fa9256de0254acd643fe8eded17
| 32
|
py
|
Python
|
fastai/vision/imports.py
|
bearpelican/fastai_pytorch
|
3e8751d2fc5acdc880eef22d6849e156ce84778b
|
[
"Apache-2.0"
] | 1
|
2018-10-23T20:45:41.000Z
|
2018-10-23T20:45:41.000Z
|
fastai/vision/imports.py
|
bearpelican/fastai_pytorch
|
3e8751d2fc5acdc880eef22d6849e156ce84778b
|
[
"Apache-2.0"
] | null | null | null |
fastai/vision/imports.py
|
bearpelican/fastai_pytorch
|
3e8751d2fc5acdc880eef22d6849e156ce84778b
|
[
"Apache-2.0"
] | null | null | null |
import PIL
from PIL import Image
| 16
| 21
| 0.84375
| 6
| 32
| 4.5
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15625
| 32
| 2
| 21
| 16
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
8977cd25aabff8a80ba260b162b7c4ced969e8f4
| 31
|
py
|
Python
|
code/sample_5-4-3.py
|
KoyanagiHitoshi/AtCoder-Python-Introduction
|
6d014e333a873f545b4d32d438e57cf428b10b96
|
[
"MIT"
] | 1
|
2022-03-29T13:50:12.000Z
|
2022-03-29T13:50:12.000Z
|
code/sample_5-4-3.py
|
KoyanagiHitoshi/AtCoder-Python-Introduction
|
6d014e333a873f545b4d32d438e57cf428b10b96
|
[
"MIT"
] | null | null | null |
code/sample_5-4-3.py
|
KoyanagiHitoshi/AtCoder-Python-Introduction
|
6d014e333a873f545b4d32d438e57cf428b10b96
|
[
"MIT"
] | null | null | null |
x = [2, 4, 6, 8]
print(min(x))
| 10.333333
| 16
| 0.451613
| 8
| 31
| 1.75
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 0.225806
| 31
| 2
| 17
| 15.5
| 0.416667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.5
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
898e8409fee369c8926849f7b7616f3074980112
| 10,766
|
py
|
Python
|
gru/models.py
|
LCE-UMD/GRU
|
e4512e779b83413dbd7547896a05a4f83cbf3d4f
|
[
"MIT"
] | 4
|
2021-04-20T09:24:22.000Z
|
2022-03-14T07:47:32.000Z
|
gru/models.py
|
LCE-UMD/GRU
|
e4512e779b83413dbd7547896a05a4f83cbf3d4f
|
[
"MIT"
] | null | null | null |
gru/models.py
|
LCE-UMD/GRU
|
e4512e779b83413dbd7547896a05a4f83cbf3d4f
|
[
"MIT"
] | 1
|
2021-10-20T15:21:33.000Z
|
2021-10-20T15:21:33.000Z
|
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
import tensorflow_addons as tfa
from sklearn.metrics import r2_score
from functools import partial
'''
classification
'''
# GRU clip classifier
def GRUClassifier(X, k_layers=1, k_hidden=32, k_class=15,
l2=0.001, dropout=1e-6, lr=0.006, seed=42):
"""
Parameters
---------
X: tensor (batch x time x feat)
k_layers: int, number of hidden layers
k_hidden: int, number of units
k_class: int, number of classes
Returns
-------
model: complied model
"""
tf.random.set_seed(seed)
regularizer = keras.regularizers.l2(l2)
CustomGRU = partial(keras.layers.GRU,
kernel_regularizer=regularizer,
dropout=dropout,
recurrent_dropout=dropout
)
'''
For masking, refer:
https://www.tensorflow.org/guide/keras/masking_and_padding
https://gist.github.com/ragulpr/601486471549cfa26fe4af36a1fade21
'''
input_layers = [layers.Masking(mask_value=0.0,
input_shape = [None, X.shape[-1]])]
hidden_layers = []
for ii in range(k_layers):
hidden_layers.append(CustomGRU(k_hidden,return_sequences=True))
output_layer = [layers.TimeDistributed(layers.Dense(k_class,activation='softmax'))]
optimizer = keras.optimizers.Adam(lr=lr)
model = keras.models.Sequential(input_layers+hidden_layers+output_layer)
model.compile(loss='sparse_categorical_crossentropy',
optimizer=optimizer,metrics=['sparse_categorical_accuracy'])
return model
# GRU encoder
def GRUEncoder(X, gru_model_path, k_layers=1, k_hidden=32, k_dim = 3,
k_class = 15,
l2=0.001, dropout=1e-6, lr=0.006, seed=42):
'''
GRU Encoder: classification after supervised dim reduction
Parameters
----------
X: tensor (batch x time x feat)
k_layers: int, number of hidden layers
k_hidden: int, number of units
k_dim: int, reduce to k_dim
k_class: int, number of classes
Returns
-------
model: complied model
'''
tf.random.set_seed(seed)
regularizer = keras.regularizers.l2(l2)
'''
Transfer Learning
-----------------
Using pretrained gru model for finetuning DR_layer
'''
gru_model = keras.models.load_model(gru_model_path)
gru_model.trainable = False
'''
For masking, refer:
https://www.tensorflow.org/guide/keras/masking_and_padding
https://gist.github.com/ragulpr/601486471549cfa26fe4af36a1fade21
'''
input_layers = [layers.Masking(mask_value=0.0,
input_shape = [None, X.shape[-1]])]
hidden_layers = [gru_model.layers[1]]
DR_layer = [layers.TimeDistributed(layers.Dense(k_dim,activation='linear'))]
output_layer = [layers.TimeDistributed(layers.Dense(k_class,activation='softmax'))]
optimizer = keras.optimizers.Adam(lr=lr)
model = keras.models.Sequential(input_layers +
hidden_layers +
DR_layer +
output_layer)
model.compile(loss='sparse_categorical_crossentropy',
optimizer=optimizer,metrics=['sparse_categorical_accuracy'])
return model
# GRU Decoder
def GRUDecoder(X, Y, k_layers=1,
l2=0, dropout=0, lr=0.001,seed=42):
"""
Parameters
---------
X: tensor (batch x time x feat)
k_layers: int, number of hidden layers
k_hidden: int, number of units
k_class: int, number of classes
Returns
-------
model: complied model
"""
tf.random.set_seed(seed)
regularizer = keras.regularizers.l2(l2)
CustomGRU = partial(keras.layers.GRU,
kernel_regularizer=regularizer,
dropout=dropout,
recurrent_dropout=dropout
)
input_layers = [layers.Masking(mask_value=0.0,
input_shape = [None, X.shape[-1]])]
hidden_layers = []
for ii in range(k_layers):
hidden_layers.append(CustomGRU(Y.shape[-1],return_sequences=True))
optimizer = keras.optimizers.Adam(lr=lr)
model = keras.models.Sequential(input_layers+hidden_layers)
model.compile(loss='mse', optimizer=optimizer)
return model
'''
classifier (FeedForward)
k_feat: (k_hidden:)*k_layers: k_class
'''
def FFClassifier(X,k_hidden,k_layers,k_class,seed=42):
'''
Feed-forward network classifier
Parameters
----------
X: tensor (batch x time x feat)
k_layers: int, number of hidden layers
k_hidden: int, number of units
k_class: int, number of classes
Returns
-------
model: complied model
'''
tf.random.set_seed(seed)
input_layers = [layers.Masking(mask_value=0.0, input_shape = [X.shape[-2], X.shape[-1]])]
hidden_layers = []
for ii in range(k_layers):
hidden_layers.append(layers.Dense(k_hidden,activation='relu'))
output_layer = [layers.Dense(k_class,activation='softmax')]
model = keras.models.Sequential(input_layers+hidden_layers+output_layer)
optimizer = keras.optimizers.Adam()
model.compile(loss=keras.losses.SparseCategoricalCrossentropy(from_logits=False),
optimizer=optimizer,metrics=['sparse_categorical_accuracy'])
return model
'''
classifier (TCN)
k_hidden: filters, k_wind: kernel_size
'''
def TCNClassifier (X, k_hidden, k_wind, k_class,seed=42):
'''
TCN classifier
Parameters
----------
X: tensor (batch x time x feat)
k_hidden: int, number of filters
k_wind: int, kernel size
k_class: int, number of classes
Returns
-------
model: complied model
'''
tf.random.set_seed(seed)
input_layers = [layers.Masking(mask_value=0.0,
input_shape = [None, X.shape[-1]])]
hidden_layers = [layers.Conv1D(filters=k_hidden,kernel_size=k_wind,
strides=1,padding='same',activation="relu")]
output_layer = [layers.TimeDistributed(layers.Dense(k_class,activation='softmax'))]
model = keras.models.Sequential(input_layers+hidden_layers+output_layer)
optimizer = keras.optimizers.Adam()
model.compile(loss='sparse_categorical_crossentropy',
optimizer=optimizer,metrics=['sparse_categorical_accuracy'])
return model
'''
classifier (LogReg)
k_feat: k_class
'''
def LogReg(k_dim=3,k_class=15,seed=42):
'''
Logistic regression classifier
Parameters
----------
k_dim: int, number of input features
k_class: int, number of classes
Returns
-------
model: complied model
'''
tf.random.set_seed(seed)
masking_layer = [
layers.Masking(mask_value=0.0, input_shape=[None,k_dim])
]
output_layer = [
layers.Dense(k_class,activation='softmax')
]
model = keras.models.Sequential(
masking_layer + output_layer
)
optimizer = keras.optimizers.Adam()
model.compile(loss=keras.losses.SparseCategoricalCrossentropy(from_logits=False),
optimizer=optimizer,metrics=['sparse_categorical_accuracy'])
return model
'''
regression: GRU
'''
def GRURegressor(X,k_layers=1, k_hidden=32,
l2=0, dropout=0, lr=0.001,seed=42):
"""
GRU regressor for individual difference
Parameters
---------
X: tensor (batch x time x feat)
k_layers: int, number of hidden layers
k_hidden: int, number of units
Returns
-------
model: complied model
"""
tf.random.set_seed(seed)
regularizer = keras.regularizers.l2(l2)
CustomGRU = partial(keras.layers.GRU,
kernel_regularizer=regularizer,
dropout=dropout,
recurrent_dropout=dropout
)
'''
For masking, refer:
https://www.tensorflow.org/guide/keras/masking_and_padding
https://gist.github.com/ragulpr/601486471549cfa26fe4af36a1fade21
'''
input_layers = [layers.Masking(mask_value=0.0,
input_shape = [None, X.shape[-1]])]
hidden_layers = []
for ii in range(k_layers):
hidden_layers.append(CustomGRU(k_hidden,return_sequences=True))
output_layer = [layers.TimeDistributed(layers.Dense(1,activation='linear'))]
optimizer = keras.optimizers.Adam(lr=lr)
model = keras.models.Sequential(input_layers+hidden_layers+output_layer)
model.compile(loss='mse',
optimizer=optimizer)
return model
'''
regression: FF
'''
def FFRegressor (X,k_hidden,k_layers,seed=42):
"""
FF regressor for individual difference
Parameters
---------
X: tensor (batch x time x feat)
k_layers: int, number of hidden layers
k_hidden: int, number of units
Returns
-------
model: complied model
"""
tf.random.set_seed(seed)
input_layers = [layers.Masking(mask_value=0.0, input_shape = [X.shape[-2], X.shape[-1]])]
hidden_layers = []
for ii in range(k_layers):
hidden_layers.append(layers.Dense(k_hidden,activation='relu'))
output_layer = [layers.Dense(1,activation='linear')]
model = keras.models.Sequential(input_layers+hidden_layers+output_layer)
optimizer = keras.optimizers.Adam()
model.compile(loss='mse', optimizer=optimizer)
return model
def TCNRegressor (X, k_hidden, k_wind, seed=42):
'''
TCN classifier
Parameters
----------
X: tensor (batch x time x feat)
k_hidden: int, number of filters
k_wind: int, kernel size
Returns
-------
model: complied model
'''
tf.random.set_seed(seed)
input_layers = [layers.Masking(mask_value=0.0,
input_shape = [None, X.shape[-1]])]
hidden_layers = [layers.Conv1D(filters=k_hidden,kernel_size=k_wind,
strides=1,padding='same',activation='relu')]
output_layer = [layers.TimeDistributed(layers.Dense(1,activation='linear'))]
model = keras.models.Sequential(input_layers+hidden_layers+output_layer)
optimizer = keras.optimizers.Adam()
model.compile(loss='mse',optimizer=optimizer)
return model
| 28.632979
| 93
| 0.607468
| 1,237
| 10,766
| 5.120453
| 0.124495
| 0.051153
| 0.03647
| 0.035523
| 0.865172
| 0.858541
| 0.843543
| 0.835017
| 0.822387
| 0.804231
| 0
| 0.022856
| 0.276612
| 10,766
| 376
| 94
| 28.632979
| 0.790447
| 0.174345
| 0
| 0.696552
| 0
| 0
| 0.043038
| 0.03038
| 0
| 0
| 0
| 0
| 0
| 1
| 0.062069
| false
| 0
| 0.041379
| 0
| 0.165517
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
98716258a8fb14fac4ba549a7b7b36128f15d546
| 44
|
py
|
Python
|
rlutils/tf/exploration/__init__.py
|
vermouth1992/rl-util
|
4c06ab8f5c96a44e58f88cf30146bcb837057112
|
[
"Apache-2.0"
] | null | null | null |
rlutils/tf/exploration/__init__.py
|
vermouth1992/rl-util
|
4c06ab8f5c96a44e58f88cf30146bcb837057112
|
[
"Apache-2.0"
] | null | null | null |
rlutils/tf/exploration/__init__.py
|
vermouth1992/rl-util
|
4c06ab8f5c96a44e58f88cf30146bcb837057112
|
[
"Apache-2.0"
] | null | null | null |
from .ou import OrnsteinUhlenbeckActionNoise
| 44
| 44
| 0.909091
| 4
| 44
| 10
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.068182
| 44
| 1
| 44
| 44
| 0.97561
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
9875048339bf29db3ecb35980cebc2f9d7cfa873
| 7,036
|
py
|
Python
|
tests/summarycode/test_tallies.py
|
sthagen/nexB-scancode-toolkit
|
12cc1286df78af898fae76fa339da2bb50ad51b9
|
[
"Apache-2.0",
"CC-BY-4.0"
] | null | null | null |
tests/summarycode/test_tallies.py
|
sthagen/nexB-scancode-toolkit
|
12cc1286df78af898fae76fa339da2bb50ad51b9
|
[
"Apache-2.0",
"CC-BY-4.0"
] | null | null | null |
tests/summarycode/test_tallies.py
|
sthagen/nexB-scancode-toolkit
|
12cc1286df78af898fae76fa339da2bb50ad51b9
|
[
"Apache-2.0",
"CC-BY-4.0"
] | null | null | null |
#
# Copyright (c) nexB Inc. and others. All rights reserved.
# ScanCode is a trademark of nexB Inc.
# SPDX-License-Identifier: Apache-2.0
# See http://www.apache.org/licenses/LICENSE-2.0 for the license text.
# See https://github.com/nexB/scancode-toolkit for support or download.
# See https://aboutcode.org for more information about nexB OSS projects.
#
from os import path
import pytest
from commoncode.testcase import FileDrivenTesting
from scancode.cli_test_utils import check_json_scan
from scancode.cli_test_utils import check_jsonlines_scan
from scancode.cli_test_utils import run_scan_click
from scancode_config import REGEN_TEST_FIXTURES
pytestmark = pytest.mark.scanslow
class TestTallies(FileDrivenTesting):
test_data_dir = path.join(path.dirname(__file__), 'data')
def test_copyright_summary_base(self):
test_dir = self.get_test_loc('tallies/copyright_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/copyright_tallies/tallies.expected.json')
run_scan_click(['-c', '--tallies', '--json-pp', result_file, test_dir])
check_json_scan(expected_file, result_file, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_copyright_summary_with_details(self):
test_dir = self.get_test_loc('tallies/copyright_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/copyright_tallies/tallies_details.expected.json')
run_scan_click(['-c', '--tallies-with-details', '--json-pp', result_file, test_dir])
check_json_scan(expected_file, result_file, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_copyright_summary_with_details_plain_json(self):
test_dir = self.get_test_loc('tallies/copyright_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/copyright_tallies/tallies_details.expected2.json')
run_scan_click(['-c', '--tallies-with-details', '--json', result_file, test_dir])
check_json_scan(expected_file, result_file, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_copyright_summary_does_not_crash(self):
test_dir = self.get_test_loc('tallies/copyright_tallies/scan2')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/copyright_tallies/tallies2.expected.json')
run_scan_click(['-c', '--tallies', '--json-pp', result_file, test_dir])
check_json_scan(expected_file, result_file, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_full_summary_base(self):
test_dir = self.get_test_loc('tallies/full_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/full_tallies/tallies.expected.json')
run_scan_click(['-clip', '--tallies', '--json-pp', result_file, test_dir])
check_json_scan(expected_file, result_file, remove_uuid=True, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_full_summary_with_details(self):
test_dir = self.get_test_loc('tallies/full_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/full_tallies/tallies_details.expected.json')
run_scan_click(['-clip', '--tallies-with-details', '--json-pp', result_file, test_dir])
check_json_scan(expected_file, result_file, remove_uuid=True, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_copyright_summary_key_files(self):
test_dir = self.get_test_loc('tallies/copyright_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/copyright_tallies/tallies_key_files.expected.json')
run_scan_click(
['-c', '-i', '--classify', '--tallies', '--tallies-key-files',
'--json-pp', result_file, test_dir])
check_json_scan(expected_file, result_file, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_full_summary_key_files(self):
test_dir = self.get_test_loc('tallies/full_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/full_tallies/tallies_key_files.expected.json')
run_scan_click(
['-cli', '--classify', '--tallies', '--tallies-key-files',
'--json-pp', result_file, test_dir])
check_json_scan(expected_file, result_file, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_full_summary_key_files_json_lines(self):
test_dir = self.get_test_loc('tallies/full_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/full_tallies/tallies_key_files-details.expected.json-lines')
run_scan_click(
['-cli', '--classify', '--tallies', '--tallies-key-files',
'--json-lines', result_file, test_dir])
check_jsonlines_scan(expected_file, result_file, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_full_summary_by_facet(self):
test_dir = self.get_test_loc('tallies/full_tallies/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/full_tallies/tallies_by_facet.expected.json')
run_scan_click([
'-clpieu',
'--facet', 'dev=*.java',
'--facet', 'dev=*.cs',
'--facet', 'dev=*ada*',
'--facet', 'data=*.S',
'--facet', 'tests=*infback9*',
'--facet', 'docs=*README',
'--tallies',
'--tallies-by-facet',
'--json-pp', result_file, test_dir
])
check_json_scan(expected_file, result_file, remove_uuid=True, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_end2end_summary_and_classify_works_with_empty_dir_and_empty_values(self):
test_dir = self.extract_test_tar('tallies/end-2-end/bug-1141.tar.gz')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/end-2-end/bug-1141.expected.json')
run_scan_click([
'-clip',
'--classify',
'--facet', 'dev=*.java',
'--tallies',
'--tallies-key-files',
'--json-pp', result_file, test_dir
])
check_json_scan(expected_file, result_file, remove_uuid=True, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
def test_summary_with_packages_reports_packages_with_files(self):
test_dir = self.get_test_loc('tallies/packages/scan')
result_file = self.get_temp_file('json')
expected_file = self.get_test_loc('tallies/packages/expected.json')
run_scan_click([
'--package',
'--tallies',
'--json-pp', result_file, test_dir
])
check_json_scan(expected_file, result_file, remove_uuid=True, remove_file_date=True, regen=REGEN_TEST_FIXTURES)
| 49.549296
| 119
| 0.699829
| 952
| 7,036
| 4.783613
| 0.133403
| 0.079051
| 0.057971
| 0.070707
| 0.805665
| 0.790294
| 0.772727
| 0.741985
| 0.733421
| 0.703338
| 0
| 0.003279
| 0.176521
| 7,036
| 141
| 120
| 49.900709
| 0.782706
| 0.048323
| 0
| 0.5
| 0
| 0
| 0.229999
| 0.148048
| 0
| 0
| 0
| 0
| 0
| 1
| 0.109091
| false
| 0
| 0.063636
| 0
| 0.190909
| 0
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| null | 0
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| 1
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| null | 0
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| 0
| 0
|
0
| 6
|
7f309c84687b26207f427d5278befd726a3f871f
| 9,958
|
py
|
Python
|
api/tests/test_api_topic_modeling.py
|
eoglethorpe/DEEPL
|
fb6403ceb63197ecd314905f060a2e5f1e790f66
|
[
"MIT"
] | 1
|
2020-07-02T15:39:37.000Z
|
2020-07-02T15:39:37.000Z
|
api/tests/test_api_topic_modeling.py
|
eoglethorpe/DEEPL
|
fb6403ceb63197ecd314905f060a2e5f1e790f66
|
[
"MIT"
] | 11
|
2017-10-28T10:50:09.000Z
|
2021-06-10T20:07:44.000Z
|
api/tests/test_api_topic_modeling.py
|
eoglethorpe/DEEPL
|
fb6403ceb63197ecd314905f060a2e5f1e790f66
|
[
"MIT"
] | null | null | null |
from rest_framework.test import APITestCase
from classifier.models import ClassifiedDocument
from topic_modeling.models import TopicModelingModel
class TestTopicModelingAPI(APITestCase):
"""
Tests for Topic Modeling API
"""
def setUp(self):
self.url = '/api/topic-modeling/'
def test_no_params(self):
params = {}
response = self.client.post(self.url, params)
assert response.status_code == 400, "No params should be a bad request"
data = response.json()
assert 'number_of_topics' in data
assert 'keywords_per_topic' in data
assert 'depth' in data
def test_no_documents(self):
params = {'number_of_topics': 2, 'keywords_per_topic': 2, 'depth': 1}
response = self.client.post(self.url, params)
assert response.status_code == 400, "Should be a bad request"
data = response.json()
assert 'documents' in data
assert 'number_of_topics' not in data
assert 'keywords_per_topic' not in data
assert 'depth' not in data
def test_no_depth(self):
params = {
'documents': [
'This is to be classified',
'This is to be classified',
'This is to be classified',
],
# 'depth': 1,
'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 400, "Should be a bad request"
data = response.json()
assert 'depth' in data
assert 'documents' not in data
assert 'keywords_per_topic' not in data
assert 'number_of_topics' not in data
def test_no_number_of_topics(self):
params = {
'documents': [
'This is to be classified',
'This is to be classified',
'This is to be classified',
],
'depth': 1,
# 'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 400, "Should be a bad request"
data = response.json()
assert 'number_of_topics' in data
assert 'documents' not in data
assert 'keywords_per_topic' not in data
assert 'depth' not in data
def test_no_keywords_per_topic(self):
params = {
'documents': [
'This is to be classified',
'This is to be classified',
'This is to be classified',
],
'depth': 1,
'number_of_topics': 3,
# 'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 400, "Should be a bad request"
data = response.json()
assert 'keywords_per_topic' in data
assert 'documents' not in data
assert 'number_of_topics' not in data
assert 'depth' not in data
def test_api_with_documents_depth1(self):
params = {
'documents': [
'This is to be classified',
'This is to be classified',
'This is to be classified',
],
'depth': 1,
'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 200
data = response.json()
# Check data structure for depth 1
assert isinstance(data, dict)
assert len(data.keys()) == params['number_of_topics']
for name, topic in data.items():
assert 'keywords' in topic
assert isinstance(topic['keywords'], list)
for kw in topic['keywords']:
assert isinstance(kw, list)
assert len(kw) == 2
assert isinstance(kw[0], str)
assert isinstance(kw[1], int) or isinstance(kw[1], float)
assert 'subtopics' in topic
assert not topic['subtopics'], "Subtopics should be empty"
def test_api_with_documents_depth2(self):
params = {
'documents': [
'This is to be classified',
'This is to be classified',
'This is to be classified',
],
'depth': 2,
'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 200
data = response.json()
# Check data structure for depth 2
depth2 = False # topic with depth 2 found
assert isinstance(data, dict)
assert len(data.keys()) == params['number_of_topics']
for name, topic in data.items():
assert 'keywords' in topic
assert isinstance(topic['keywords'], list)
for kw in topic['keywords']:
assert isinstance(kw, list)
assert len(kw) == 2
assert isinstance(kw[0], str)
assert isinstance(kw[1], int) or isinstance(kw[1], float)
assert 'subtopics' in topic
sdata = topic['subtopics']
assert isinstance(sdata, dict)
if len(sdata.keys()) == params['number_of_topics']:
depth2 = True
for name, topic in sdata.items():
assert 'keywords' in topic
assert isinstance(topic['keywords'], list)
for kw in topic['keywords']:
assert isinstance(kw, list)
assert len(kw) == 2
assert isinstance(kw[0], str)
assert isinstance(kw[1], int) or\
isinstance(kw[1], float)
assert 'subtopics' in topic
assert depth2, "At least one topic should have depth 2"
class TestTopicModelingAPIV2(APITestCase):
"""Test cases for v2 topic modeling api"""
fixtures = [
'fixtures/test_base_models.json',
'fixtures/classifier.json',
'fixtures/test_classified_docs.json',
]
def setUp(self):
self.url = '/api/v2/topic-modeling/'
self.group_id = ClassifiedDocument.objects.last().group_id
def test_invalid_version(self):
url = self.url.replace('2', '3')
params = {} # does not matter as params validation does not take place
response = self.client.post(url, params)
assert response.status_code == 400
data = response.json()
assert 'error' in data
assert 'version' in data['error']
def test_no_group_id(self):
params = {
'depth': 1,
'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 400
data = response.json()
assert 'group_id' in data
def test_non_existent_group_id(self):
params = {
'group_id': 'This does not exist',
'depth': 1,
'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 404
data = response.json()
assert 'message' in data
def test_no_depth(self):
params = {
'group_id': self.group_id,
'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 400, "Should be a bad request"
data = response.json()
assert 'depth' in data
assert 'keywords_per_topic' not in data
assert 'number_of_topics' not in data
def test_no_number_of_topics(self):
params = {
'depth': 1,
'group_id': self.group_id,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 400, "Should be a bad request"
data = response.json()
assert 'number_of_topics' in data
assert 'keywords_per_topic' not in data
assert 'depth' not in data
def test_no_keywords_per_topic(self):
params = {
'depth': 1,
'number_of_topics': 3,
'group_id': self.group_id
}
response = self.client.post(self.url, params)
assert response.status_code == 400, "Should be a bad request"
data = response.json()
assert 'keywords_per_topic' in data
assert 'number_of_topics' not in data
assert 'depth' not in data
def test_topic_modeling_post_new(self):
params = {
'group_id': self.group_id,
'depth': 1,
'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.post(self.url, params)
assert response.status_code == 202, "Model will be created in bg"
# get topic model and check status is not ready
model = TopicModelingModel.objects.get(group_id=self.group_id)
assert not model.ready
def test_topic_modeling_get_no_model_exists(self):
params = {
'group_id': self.group_id,
}
response = self.client.get(self.url, params)
assert response.status_code == 404, "Model is not yet created"
data = response.json()
assert 'message' in data # Message is about initiating model creation
def test_topic_modeling_get_not_ready(self):
params = {
'group_id': self.group_id,
'depth': 1,
'number_of_topics': 3,
'keywords_per_topic': 2
}
response = self.client.get(self.url, params)
assert response.status_code == 202, "Model is still not ready"
| 36.07971
| 79
| 0.561157
| 1,168
| 9,958
| 4.628425
| 0.105308
| 0.038846
| 0.064743
| 0.068073
| 0.779319
| 0.749723
| 0.741583
| 0.722346
| 0.700703
| 0.697743
| 0
| 0.016845
| 0.344246
| 9,958
| 275
| 80
| 36.210909
| 0.811026
| 0.036353
| 0
| 0.740741
| 0
| 0
| 0.201317
| 0.011602
| 0
| 0
| 0
| 0
| 0.320988
| 1
| 0.074074
| false
| 0
| 0.012346
| 0
| 0.098765
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
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| null | 0
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| 0
| 0
|
0
| 6
|
7f5b8e13fe696170002f245cee3180381247e5f7
| 29
|
py
|
Python
|
molsysmt/basic/compare/__init__.py
|
dprada/molsysmt
|
83f150bfe3cfa7603566a0ed4aed79d9b0c97f5d
|
[
"MIT"
] | null | null | null |
molsysmt/basic/compare/__init__.py
|
dprada/molsysmt
|
83f150bfe3cfa7603566a0ed4aed79d9b0c97f5d
|
[
"MIT"
] | null | null | null |
molsysmt/basic/compare/__init__.py
|
dprada/molsysmt
|
83f150bfe3cfa7603566a0ed4aed79d9b0c97f5d
|
[
"MIT"
] | null | null | null |
from .compare import compare
| 14.5
| 28
| 0.827586
| 4
| 29
| 6
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137931
| 29
| 1
| 29
| 29
| 0.96
| 0
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| true
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| null | 0
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| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
7f6ebd827ba8c582246f89c6796d8b2c7ff80d52
| 11,354
|
py
|
Python
|
fast_bitrix24/bitrix.py
|
halsbox/fast_bitrix24
|
95a527a1b1e5e92107c4cfd3f8a0f03c87ead976
|
[
"MIT"
] | 62
|
2020-08-07T12:27:25.000Z
|
2022-03-10T09:11:41.000Z
|
fast_bitrix24/bitrix.py
|
halsbox/fast_bitrix24
|
95a527a1b1e5e92107c4cfd3f8a0f03c87ead976
|
[
"MIT"
] | 115
|
2020-07-31T17:46:45.000Z
|
2022-02-17T07:44:12.000Z
|
fast_bitrix24/bitrix.py
|
halsbox/fast_bitrix24
|
95a527a1b1e5e92107c4cfd3f8a0f03c87ead976
|
[
"MIT"
] | 19
|
2020-10-18T18:32:36.000Z
|
2022-02-09T11:02:12.000Z
|
'''Высокоуровневый API для доступа к Битрикс24'''
import aiohttp
from contextlib import asynccontextmanager, contextmanager
from typing import Iterable, Union
from . import correct_asyncio
from .srh import ServerRequestHandler
from .user_request import (BatchUserRequest, CallUserRequest,
GetAllUserRequest, GetByIDUserRequest,
ListAndGetUserRequest)
class BitrixAbstract(object):
def __init__(self, webhook: str, verbose: bool = True,
respect_velocity_policy: bool = False,
client: aiohttp.ClientSession = None):
'''
Создает объект класса Bitrix.
Параметры:
- `webhook: str` - URL вебхука, полученного от сервера Битрикс
- `verbose: bool = True` - показывать ли прогрессбар при выполнении
запроса
- `respect_velocity_policy: bool = False` - соблюдать ли политику
Битрикса о скорости запросов
- `client: aiohttp.ClientSession = None` - использовать для HTTP-вызовов
объект aiohttp.ClientSession, инициализированнный и настроенный
пользователем.
'''
self.srh = ServerRequestHandler(webhook, respect_velocity_policy, client)
self.verbose = verbose
class Bitrix(BitrixAbstract):
'''Клиент для запросов к серверу Битрикс24.'''
def get_all(self, method: str, params: dict = None) -> Union[list, dict]:
'''
Получить полный список сущностей по запросу `method`.
Под капотом использует параллельные запросы и автоматическое построение
батчей, чтобы ускорить получение данных. Также самостоятельно
обратывает постраничные ответы сервера, чтобы вернуть полный список.
Параметры:
- `method` - метод REST API для запроса к серверу
- `params` - параметры для передачи методу. Используется именно тот
формат, который указан в документации к REST API Битрикс24.
`get_all()` не поддерживает параметры `start`, `limit` и `order`.
Возвращает полный список сущностей, имеющихся на сервере,
согласно заданным методу и параметрам.
'''
return self.srh.run(GetAllUserRequest(self, method, params).run())
def get_by_ID(self, method: str, ID_list: Iterable,
ID_field_name: str = 'ID', params: dict = None) -> dict:
'''
Получить список сущностей по запросу method и списку ID.
Используется для случаев, когда нужны не все сущности,
имеющиеся в базе, а конкретный список поименованных ID.
Например, все контакты, привязанные к сделкам.
Параметры:
- `method` - метод REST API для запроса к серверу
- `ID_list` - список ID
- `ID_field_name` - название поля, которое будет подаваться в запрос
для каждого элемента ID_list
- `params` - параметры для передачи методу. Используется именно тот
формат, который указан в документации к REST API Битрикс24
Возвращает словарь вида:
```
{
ID_1: <результат запроса 1>,
ID_2: <результат запроса 2>,
...
}
```
Значением элемента словаря будет результат выполнения запроса
относительно этого ID. Это может быть, например, список связанных
сущностей или пустой список, если не найдено ни одной привязанной
сущности.
'''
return self.srh.run(GetByIDUserRequest(
self, method, params, ID_list, ID_field_name).run())
def list_and_get(self, method_branch: str, ID_field_name='ID') -> dict:
'''
Скачать список всех ID при помощи метода *.list,
а затем все элементы при помощи метода *.get.
Подобный подход показывает на порядок большую скорость
получения данных, чем `get_all()`
с параметром `'select': ['*', 'UF_*']`.
Параметры:
* `method_branch: str` - группа методов к использованию, например,
`crm.lead` или `tasks.task`
* `ID_field_name='ID'` - имя поля, в котором метод *.get принимает
идентификаторы элементов (например, `'ID'` для метода `crm.lead.get`)
Возвращает полное содержимое всех элементов в виде, используемом
функцией `get_by_ID()` - словарь следующего вида:
```
{
ID_1: <словарь полей сущности с ID_1>,
ID_2: <словарь полей сущности с ID_2>,
...
}
```
'''
return self.srh.run(ListAndGetUserRequest(
self, method_branch, ID_field_name).run())
def call(self, method: str, items: Union[dict, Iterable]):
'''
Вызвать метод REST API по списку элементов.
Параметры:
- `method` - метод REST API
- `items` - список параметров вызываемого метода
либо dict с параметрами для единичного вызова
Возвращает список ответов сервера для каждого из элементов `items`
либо просто результат для единичного вызова.
'''
return self.srh.run(CallUserRequest(self, method, items).run())
def call_batch(self, params: dict) -> dict:
'''
Вызвать метод `batch`.
Параметры:
- `params` - список параметров вызываемого метода
Возвращает ответы сервера в формате словаря, где ключ - название
команды, а значение - ответ сервера по этой команде.
'''
return self.srh.run(BatchUserRequest(self, params).run())
@contextmanager
def slow(self, max_concurrent_requests: int = 1):
'''Временно ограничивает количество одновременно выполняемых запросов
к Битрикс24.'''
if not isinstance(max_concurrent_requests, int):
raise 'slow() argument should be only int'
if max_concurrent_requests < 1:
raise 'slow() argument should be >= 1'
mcr_max_backup, self.srh.mcr_max = \
self.srh.mcr_max, max_concurrent_requests
self.srh.mcr_cur_limit = min(self.srh.mcr_max, self.srh.mcr_cur_limit)
yield True
self.srh.mcr_max = mcr_max_backup
self.srh.mcr_cur_limit = min(self.srh.mcr_max, self.srh.mcr_cur_limit)
class BitrixAsync(BitrixAbstract):
'''Класс, повторяющий интерфейс класса `Bitrix`,
но с асинхронными методами.'''
async def get_all(self, method: str, params: dict = None) -> \
Union[list, dict]:
'''
Получить полный список сущностей по запросу `method`.
Под капотом использует параллельные запросы и автоматическое построение
батчей, чтобы ускорить получение данных. Также самостоятельно
обратывает постраничные ответы сервера, чтобы вернуть полный список.
Параметры:
- `method` - метод REST API для запроса к серверу
- `params` - параметры для передачи методу. Используется
именно тот формат, который указан в документации к REST API
Битрикс24. `get_all()` не поддерживает параметры
`start`, `limit` и `order`.
Возвращает полный список сущностей, имеющихся на сервере,
согласно заданным методу и параметрам.
'''
return await self.srh.run_async(
GetAllUserRequest(self, method, params).run())
async def get_by_ID(self, method: str, ID_list: Iterable,
ID_field_name: str = 'ID',
params: dict = None) -> list:
'''
Получить список сущностей по запросу `method` и списку ID.
Используется для случаев, когда нужны не все сущности,
имеющиеся в базе, а конкретный список поименованных ID.
Например, все контакты, привязанные к сделкам.
Параметры:
- `method` - метод REST API для запроса к серверу
- `ID_list` - список ID
- `ID_field_name` - название поля, которое будет подаваться в запрос
для каждого элемента ID_list
- `params` - параметры для передачи методу. Используется именно тот
формат, который указан в документации к REST API Битрикс24
Возвращает словарь вида:
```
{
ID_1: <результат запроса 1>,
ID_2: <результат запроса 2>,
...
}
```
Значением элемента словаря будет результат выполнения запроса
относительно этого ID. Это может быть, например, список связанных
сущностей или пустой список, если не найдено ни одной привязанной
сущности.
'''
return await self.srh.run_async(GetByIDUserRequest(
self, method, params, ID_list, ID_field_name).run())
async def list_and_get(self, method_branch: str,
ID_field_name='ID') -> dict:
'''
Скачать список всех ID при помощи метода *.list,
а затем все элементы при помощи метода *.get.
Подобный подход показывает на порядок большую скорость
получения данных, чем `get_all()`
с параметром `'select': ['*', 'UF_*']`.
Параметры:
* `method_branch: str` - группа методов к использованию, например,
`crm.lead` или `tasks.task`
* `ID_field_name='ID'` - имя поля, в котором метод *.get принимает
идентификаторы элементов (например, `'ID'` для метода `crm.lead.get`)
Возвращает полное содержимое всех элементов в виде, используемом
функцией `get_by_ID()` - словарь следующего вида:
```
{
ID_1: <словарь полей сущности с ID_1>,
ID_2: <словарь полей сущности с ID_2>,
...
}
```
'''
return await ListAndGetUserRequest(
self, method_branch, ID_field_name=ID_field_name).run()
async def call(self, method: str, items: Union[dict, Iterable]):
'''
Вызвать метод REST API по списку элементов.
Параметры:
- `method` - метод REST API
- `items` - список параметров вызываемого метода
либо dict с параметрами для единичного вызова
Возвращает список ответов сервера для каждого из элементов `items`
либо просто результат для единичного вызова.
'''
return await self.srh.run_async(
CallUserRequest(self, method, items).run())
async def call_batch(self, params: dict) -> dict:
'''
Вызвать метод `batch`.
Параметры:
- `params` - список параметров вызываемого метода
Возвращает ответы сервера в формате словаря, где ключ - название
команды, а значение - ответ сервера по этой команде.
'''
return await self.srh.run_async(
BatchUserRequest(self, params).run())
@asynccontextmanager
async def slow(self, max_concurrent_requests: int = 1):
'''Временно ограничивает количество одновременно выполняемых запросов
к Битрикс24.'''
if not isinstance(max_concurrent_requests, int):
raise 'slow() argument should be only int'
if max_concurrent_requests < 1:
raise 'slow() argument should be >= 1'
mcr_max_backup, self.srh.mcr_max = \
self.srh.mcr_max, max_concurrent_requests
self.srh.mcr_cur_limit = min(self.srh.mcr_max, self.srh.mcr_cur_limit)
yield True
self.srh.mcr_max = mcr_max_backup
self.srh.mcr_cur_limit = min(self.srh.mcr_max, self.srh.mcr_cur_limit)
| 36.27476
| 81
| 0.631407
| 1,275
| 11,354
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| 0.213333
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| 0.025608
| 0.018495
| 0.843505
| 0.81491
| 0.800114
| 0.786456
| 0.786456
| 0.786456
| 0
| 0.004701
| 0.288092
| 11,354
| 312
| 82
| 36.391026
| 0.864902
| 0.292496
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| 0
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| 0
| 0
| 0
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| 0
| 0
| 1
| 0.097222
| false
| 0
| 0.083333
| 0
| 0.361111
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| 0
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| null | 0
| 0
| 0
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| 1
| 1
| 1
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0
| 6
|
7f73091cad9b940608edf775fff03047a2031c55
| 15,452
|
py
|
Python
|
tests/cli_test.py
|
gcxtx/zap-cli
|
93c34189b498596dd0d64d95dde7b08bef2de13a
|
[
"MIT"
] | 1
|
2021-05-06T06:25:09.000Z
|
2021-05-06T06:25:09.000Z
|
tests/cli_test.py
|
gcxtx/zap-cli
|
93c34189b498596dd0d64d95dde7b08bef2de13a
|
[
"MIT"
] | null | null | null |
tests/cli_test.py
|
gcxtx/zap-cli
|
93c34189b498596dd0d64d95dde7b08bef2de13a
|
[
"MIT"
] | null | null | null |
"""
Tests for the ZAP CLI.
.. moduleauthor:: Daniel Grunwell (grunny)
"""
import unittest
from click.testing import CliRunner
from ddt import ddt, data, unpack
from mock import Mock, MagicMock, patch
import zapv2
from zapcli import zap_helper, cli
from zapcli.exceptions import ZAPError
@ddt
class ZAPCliTestCase(unittest.TestCase):
"""Test ZAP CLI methods."""
def setUp(self):
self.runner = CliRunner()
cli.console = Mock()
@patch('zapcli.zap_helper.ZAPHelper.start')
def test_start_zap_daemon(self, helper_mock):
"""Test command to start ZAP daemon."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'start'])
helper_mock.assert_called_with(options=None)
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.start')
def test_start_zap_daemon_with_options(self, helper_mock):
"""Test command to start ZAP daemon."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'start',
'--start-options', '-config api.key=12345'])
helper_mock.assert_called_with(options='-config api.key=12345')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.start')
def test_start_zap_daemon_exception(self, helper_mock):
"""Test command to start ZAP daemon has an exit code of 1 when an exception is raised."""
helper_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'start'])
helper_mock.assert_called_with(options=None)
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.shutdown')
def test_shutdown_zap_daemon(self, helper_mock):
"""Test command to shutdown ZAP daemon."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'shutdown'])
helper_mock.assert_called_with()
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.shutdown')
def test_shutdown_zap_daemon_exception(self, helper_mock):
"""Test command to shutdown ZAP daemon has an exit code of 1 when an exception is raised."""
helper_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'shutdown'])
helper_mock.assert_called_with()
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.is_running')
def test_check_status_running(self, helper_mock):
"""Test the status command."""
helper_mock.return_value = True
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'status'])
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.is_running')
def test_check_status_not_running(self, helper_mock):
"""Test the status command when ZAP is not running."""
helper_mock.return_value = False
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'status'])
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.wait_for_zap')
@patch('zapcli.zap_helper.ZAPHelper.is_running')
def test_check_status_timeout(self, running_mock, wait_mock):
"""Test the status command with a timeout."""
running_mock.return_value = False
wait_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'status', '-t', '0'])
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.wait_for_zap')
@patch('zapcli.zap_helper.ZAPHelper.is_running')
def test_check_status_timeout_success(self, running_mock, wait_mock):
"""Test the status command with a successful wait for ZAP to start."""
running_mock.return_value = False
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'status', '-t', '0'])
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.open_url')
def test_open_url(self, helper_mock):
"""Test open URL method."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'open-url', 'http://localhost/'])
helper_mock.assert_called_with('http://localhost/')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.open_url')
def test_open_url_no_url(self, helper_mock):
"""Test open URL method isn't called and an error status raised when no URL provided."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'open-url'])
self.assertFalse(helper_mock.called)
self.assertEqual(result.exit_code, 2)
@patch('zapcli.zap_helper.ZAPHelper.run_spider')
def test_spider_url(self, helper_mock):
"""Test spider URL method."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'spider', 'http://localhost/'])
helper_mock.assert_called_with('http://localhost/')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.run_spider')
def test_spider_url_no_url(self, helper_mock):
"""Test spider URL method isn't called and an error status raised when no URL provided."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'spider'])
self.assertFalse(helper_mock.called)
self.assertEqual(result.exit_code, 2)
@patch('zapcli.zap_helper.ZAPHelper.run_ajax_spider')
def test_ajax_spider_url(self, helper_mock):
"""Test AJAX Spider URL method."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'ajax-spider', 'http://localhost/'])
helper_mock.assert_called_with('http://localhost/')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.run_ajax_spider')
def test_ajax_spider_url_no_url(self, helper_mock):
"""Test AJAX Spider URL method isn't called and an error status raised when no URL provided."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'ajax-spider'])
self.assertFalse(helper_mock.called)
self.assertEqual(result.exit_code, 2)
@patch('zapcli.cli.ZAPHelper')
def test_quick_scan(self, helper_mock):
"""Testing quick scan."""
instance = helper_mock.return_value
instance.scanner_groups = ['xss']
instance.scanner_group_map = {'xss': ['40012', '40014', '40016', '40017']}
instance.alerts.return_value = []
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', '--verbose', 'quick-scan',
'http://localhost/', '--self-contained', '--scanners', 'xss',
'--spider', '--exclude', 'pattern'])
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.start')
def test_quick_scan_start_error(self, helper_mock):
"""Testing quick scan."""
helper_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', '--verbose', 'quick-scan',
'http://localhost/', '--self-contained'])
self.assertEqual(result.exit_code, 1)
@patch('zapcli.cli.ZAPHelper')
def test_quick_scan_shutdown_error(self, helper_mock):
"""Testing quick scan."""
instance = helper_mock.return_value
instance.alerts.return_value = []
instance.shutdown.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', '--verbose', 'quick-scan',
'http://localhost/', '--self-contained'])
self.assertEqual(result.exit_code, 1)
@patch('zapcli.cli.ZAPHelper')
def test_quick_scan_enable_scanners_error(self, helper_mock):
"""Testing quick scan."""
instance = helper_mock.return_value
instance.alerts.return_value = []
instance.scanner_groups = ['xss']
instance.scanner_group_map = {'xss': ['40012', '40014', '40016', '40017']}
instance.set_enabled_scanners.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', '--verbose', 'quick-scan',
'http://localhost/', '--scanners', 'xss'])
self.assertEqual(result.exit_code, 1)
@patch('zapcli.cli.ZAPHelper')
def test_quick_scan_exclude_from_all_error(self, helper_mock):
"""Testing quick scan."""
instance = helper_mock.return_value
instance.alerts.return_value = []
instance.exclude_from_all.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', '--verbose', 'quick-scan',
'http://localhost/', '--exclude', 'pattern'])
self.assertEqual(result.exit_code, 1)
@patch('zapv2.ascan')
def test_active_scanners_enable(self, ascan_mock):
"""Test enabling active scanners."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', '--verbose', 'scanners', 'enable',
'--scanners', '1,2,3'])
ascan_mock.return_value.enable_scanners.assert_called_with('1,2,3', apikey='')
@patch('zapv2.ascan')
def test_active_scanners_disable(self, ascan_mock):
"""Test enabling active scanners."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', '--verbose', 'scanners', 'disable',
'--scanners', '1,2,3'])
ascan_mock.return_value.disable_scanners.assert_called_with('1,2,3', apikey='')
@patch('zapv2.ascan')
def test_active_scan_policies_enable(self, ascan_mock):
"""Test enabling active scan policies method."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', '--verbose', 'policies', 'enable',
'--policy-ids', '1,2,3'])
ascan_mock.return_value.set_enabled_policies.assert_called_with('1,2,3', apikey='')
@patch('zapcli.zap_helper.ZAPHelper.exclude_from_all')
def test_exclude_from_scanners(self, helper_mock):
"""Test exclude from scanners command."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'exclude', 'pattern'])
helper_mock.assert_called_with('pattern')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.exclude_from_all')
def test_exclude_from_scanners_error(self, helper_mock):
"""Test exclude from scanners command with error raised."""
helper_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'exclude', '['])
helper_mock.assert_called_with('[')
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.enable_script')
def test_enable_script(self, helper_mock):
"""Test command to enable a script."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'scripts', 'enable', 'Foo.js'])
helper_mock.assert_called_with('Foo.js')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.enable_script')
def test_enable_script_error(self, helper_mock):
"""Test command to enable a script with error raised."""
helper_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'scripts', 'enable', 'Foo.js'])
helper_mock.assert_called_with('Foo.js')
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.disable_script')
def test_disable_script(self, helper_mock):
"""Test command to disable a script."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'scripts', 'disable', 'Foo.js'])
helper_mock.assert_called_with('Foo.js')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.disable_script')
def test_disable_script_error(self, helper_mock):
"""Test command to disable a script with error raised."""
helper_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'scripts', 'disable', 'Foo.js'])
helper_mock.assert_called_with('Foo.js')
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.remove_script')
def test_remove_script(self, helper_mock):
"""Test command to remove a script."""
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'scripts', 'remove', 'Foo.js'])
helper_mock.assert_called_with('Foo.js')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.remove_script')
def test_remove_script_error(self, helper_mock):
"""Test command to remove a script with error raised."""
helper_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'scripts', 'remove', 'Foo.js'])
helper_mock.assert_called_with('Foo.js')
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.load_script')
def test_load_script(self, helper_mock):
"""Test command to load a script."""
script_name = 'Foo.js'
script_type = 'proxy'
engine = 'Oracle Nashorn'
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'scripts', 'load',
'--name', script_name, '--script-type', script_type,
'--engine', engine, '--file-path', script_name])
helper_mock.assert_called_with(name=script_name, script_type=script_type, engine=engine,
file_path=script_name, description='')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.load_script')
def test_load_script_error(self, helper_mock):
"""Test command to load a script with error raised."""
helper_mock.side_effect = ZAPError('error')
result = self.runner.invoke(cli.cli, ['--boring', '--api-key', '', 'scripts', 'load',
'--name', 'Foo.js', '--script-type', 'proxy',
'--engine', 'Oracle Nashorn', '--file-path', 'Foo.js'])
self.assertEqual(result.exit_code, 1)
@patch('zapcli.zap_helper.ZAPHelper.xml_report')
def test_xml_report(self, report_mock):
"""Testing XML report."""
result = self.runner.invoke(cli.cli,
['report', '-o', 'foo.xml', '-f', 'xml'])
report_mock.assert_called_with('foo.xml')
self.assertEqual(result.exit_code, 0)
@patch('zapcli.zap_helper.ZAPHelper.html_report')
def test_html_report(self, report_mock):
"""Testing HTML report."""
result = self.runner.invoke(cli.cli,
['report', '-o', 'foo.html', '-f', 'html'])
report_mock.assert_called_with('foo.html')
self.assertEqual(result.exit_code, 0)
if __name__ == '__main__':
unittest.main()
| 48.744479
| 111
| 0.623479
| 1,878
| 15,452
| 4.922258
| 0.079872
| 0.067071
| 0.06058
| 0.083297
| 0.914756
| 0.893769
| 0.880679
| 0.85926
| 0.81653
| 0.760493
| 0
| 0.008934
| 0.217706
| 15,452
| 316
| 112
| 48.898734
| 0.755791
| 0.100052
| 0
| 0.584071
| 0
| 0
| 0.221898
| 0.084633
| 0
| 0
| 0
| 0
| 0.252212
| 1
| 0.159292
| false
| 0
| 0.030973
| 0
| 0.19469
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
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| 0
| 0
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| 0
| 0
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| 0
| 0
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| null | 0
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| 0
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| 0
| 0
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| 0
| 0
| 0
|
0
| 6
|
7f763d77fe668a86253b5ab52260756d9ee696ea
| 97
|
py
|
Python
|
leaker/main.py
|
lgvaz/leaker
|
3500a8bded1910c27414935ec9e74b7fe5f4c7e0
|
[
"MIT"
] | null | null | null |
leaker/main.py
|
lgvaz/leaker
|
3500a8bded1910c27414935ec9e74b7fe5f4c7e0
|
[
"MIT"
] | null | null | null |
leaker/main.py
|
lgvaz/leaker
|
3500a8bded1910c27414935ec9e74b7fe5f4c7e0
|
[
"MIT"
] | null | null | null |
import gc
def count_type(obj):
return sum([type(obj) == type(o) for o in gc.get_objects()])
| 19.4
| 64
| 0.659794
| 18
| 97
| 3.444444
| 0.722222
| 0.225806
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.175258
| 97
| 5
| 64
| 19.4
| 0.775
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 0
| 1
| 1
| 0
| 0
|
0
| 6
|
7f82a9421cc6317678f51a82965829da49fb13ad
| 4,844
|
py
|
Python
|
geometry_utils/pytests/two_d/test_point2.py
|
django-advance-utils/geometry-utils
|
b749cfdab67d8462cc5d02d566c2b526f7d0b418
|
[
"MIT"
] | null | null | null |
geometry_utils/pytests/two_d/test_point2.py
|
django-advance-utils/geometry-utils
|
b749cfdab67d8462cc5d02d566c2b526f7d0b418
|
[
"MIT"
] | null | null | null |
geometry_utils/pytests/two_d/test_point2.py
|
django-advance-utils/geometry-utils
|
b749cfdab67d8462cc5d02d566c2b526f7d0b418
|
[
"MIT"
] | null | null | null |
import pytest
from geometry_utils.three_d.point3 import Point3
from geometry_utils.two_d.point2 import Point2
from geometry_utils.two_d.vector2 import Vector2
'''
Point2 Initialisation
'''
def test_point2_with_string_inputs():
with pytest.raises(TypeError):
return Point2("0", "0", "0")
def test_point2_print_string(test_point2_1):
assert test_point2_1.__str__() == "Point2(x:1.00, y:1.00)"
'''
Point2 Addition Tests
'''
def test_point2_point2_addition_return_type(test_point2_1, test_point2_2):
with pytest.raises(TypeError):
return test_point2_1 + test_point2_2
def test_point2_vector2_addition_return_type(test_point2_1, test_vector2_1):
assert isinstance(test_point2_1 + test_vector2_1, Point2)
def test_point2_vector2_addition_arithmetic(test_point2_1, test_vector2_1):
assert test_point2_1 + test_vector2_1 == Point2(2.0, 2.0)
def test_point2_float_addition(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1 + 9.0
'''
Point2 Subtraction Tests
'''
def test_point2_point2_subtraction_return_type(test_point2_1, test_point2_2):
assert isinstance(test_point2_1 - test_point2_2, Vector2)
def test_point2_point2_subtraction_arithmetic(test_point2_1, test_point2_2):
assert test_point2_1 - test_point2_2 == Vector2(0.0, 1.0)
def test_point2_vector2_subtraction_solution_type(test_point2_1, test_vector2_1):
assert isinstance(test_point2_1 - test_vector2_1, Point2)
def test_point2_vector2_subtraction_arithmetic(test_point2_1, test_vector2_1):
assert test_point2_1 - test_vector2_1 == Point2(0.0, 0.0)
def test_point2_float_subtraction(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1 - 9.0
'''
Point2 Equality and Inequality Tests
'''
def test_point2_to_point2_equality(test_point2_1, test_point2_3):
assert test_point2_1 == test_point2_1
assert test_point2_1 == test_point2_3
def test_point2_to_float_equality(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1 == 9.0
def test_point2_to_point2_inequality(test_point2_1, test_point2_2):
assert test_point2_1 != test_point2_2
assert not (test_point2_1 == test_point2_2)
def test_point2_to_float_inequality(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1 != 9.0
'''
Less Than or Equal To Tests
'''
def test_point2_less_than_or_equal_to_point2(test_point2_1, test_point2_2):
assert test_point2_2 <= test_point2_1
def test_point2_less_than_or_equal_to_float(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1 <= 9.0
'''
Greater Than or Equal To Tests
'''
def test_point2_greater_than_or_equal_to_point2(test_point2_1, test_point2_2):
assert test_point2_1 >= test_point2_2
def test_point2_greater_than_or_equal_to_float(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1 >= 9.0
'''
Less Than Tests
'''
def test_point2_less_than_point2(test_point2_1, test_point2_4):
assert test_point2_4 < test_point2_1
def test_point2_less_than_float(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1 < 9.0
'''
Greater Than Tests
'''
def test_point2_greater_than_point2(test_point2_1, test_point2_4):
assert test_point2_1 > test_point2_4
def test_point2_greater_than_float(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1 > 9.0
'''
To_Vector Tests
'''
def test_point2_to_vector_return_type(test_point2_1):
assert isinstance(test_point2_1.to_vector2(), Vector2)
def test_point2_to_vector_arithmetic(test_point2_1):
assert test_point2_1.to_vector2() == Vector2(1.0, 1.0)
'''
Distance_To Tests
'''
def test_point2_distance_to_point2_return_type(test_point2_1, test_point2_2):
assert isinstance(test_point2_1.distance_to(test_point2_2), float)
def test_point2_distance_to_point2_arithmetic(test_point2_1, test_point2_2):
assert test_point2_1.distance_to(test_point2_2) == 1.0
def test_point2_distance_to_float(test_point2_1):
with pytest.raises(TypeError):
return test_point2_1.distance_to(9.0)
def test_point2_mirror_x():
assert Point2(1.0, 1.0).mirror_x() == Point2(1.0, -1.0)
def test_point2_mirror_y():
assert Point2(1.0, 1.0).mirror_y() == Point2(-1.0, 1.0)
def test_point2_point2_equal(test_point2_1, test_point2_3):
assert test_point2_1.equal(test_point2_3)
def test_point2_from_comma_string(test_2d_string):
assert Point2.from_comma_string(test_2d_string) == Point2(1.0, 2.0)
def test_point2_to_point3(test_point2_2):
assert test_point2_2.to_point3() == Point3(1.0, 0.0, 0.0)
def test_point2_accuracy_fix():
low_accuracy_point = Point2(0.0000003, 0.0000005)
low_accuracy_point.accuracy_fix()
assert low_accuracy_point == Point2(0.0, 0.0)
| 23.514563
| 81
| 0.773121
| 784
| 4,844
| 4.306122
| 0.077806
| 0.35545
| 0.192239
| 0.128851
| 0.870261
| 0.734005
| 0.643661
| 0.551836
| 0.469194
| 0.444609
| 0
| 0.087186
| 0.138109
| 4,844
| 205
| 82
| 23.629268
| 0.721437
| 0
| 0
| 0.126437
| 0
| 0
| 0.005507
| 0
| 0
| 0
| 0
| 0
| 0.287356
| 1
| 0.390805
| false
| 0
| 0.045977
| 0
| 0.563218
| 0.011494
| 0
| 0
| 0
| null | 1
| 1
| 0
| 1
| 1
| 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
| 6
|
7f8a5b50d33fc3b8b24d017809971b873579ba8c
| 3,700
|
py
|
Python
|
backup/pluginManager.py
|
uzairAK/serverom-panel
|
3dcde05ad618e6bef280db7d3180f926fe2ab1db
|
[
"MIT"
] | null | null | null |
backup/pluginManager.py
|
uzairAK/serverom-panel
|
3dcde05ad618e6bef280db7d3180f926fe2ab1db
|
[
"MIT"
] | null | null | null |
backup/pluginManager.py
|
uzairAK/serverom-panel
|
3dcde05ad618e6bef280db7d3180f926fe2ab1db
|
[
"MIT"
] | null | null | null |
from .signals import *
from plogical.pluginManagerGlobal import pluginManagerGlobal
class pluginManager:
@staticmethod
def preBackupSite(request):
return pluginManagerGlobal.globalPlug(request, preBackupSite)
@staticmethod
def postBackupSite(request, response):
return pluginManagerGlobal.globalPlug(request, postBackupSite, response)
@staticmethod
def preRestoreSite(request):
return pluginManagerGlobal.globalPlug(request, preRestoreSite)
@staticmethod
def postRestoreSite(request, response):
return pluginManagerGlobal.globalPlug(request, postRestoreSite, response)
@staticmethod
def preSubmitBackupCreation(request):
return pluginManagerGlobal.globalPlug(request, preSubmitBackupCreation)
@staticmethod
def preBackupStatus(request):
return pluginManagerGlobal.globalPlug(request, preBackupStatus)
@staticmethod
def postBackupStatus(request, response):
return pluginManagerGlobal.globalPlug(request, postBackupStatus, response)
@staticmethod
def preDeleteBackup(request):
return pluginManagerGlobal.globalPlug(request, preDeleteBackup)
@staticmethod
def postDeleteBackup(request, response):
return pluginManagerGlobal.globalPlug(request, postDeleteBackup, response)
@staticmethod
def preSubmitRestore(request):
return pluginManagerGlobal.globalPlug(request, preSubmitRestore)
@staticmethod
def preSubmitDestinationCreation(request):
return pluginManagerGlobal.globalPlug(request, preSubmitDestinationCreation)
@staticmethod
def postSubmitDestinationCreation(request, response):
return pluginManagerGlobal.globalPlug(request, postSubmitDestinationCreation, response)
@staticmethod
def preDeleteDestination(request):
return pluginManagerGlobal.globalPlug(request, preDeleteDestination)
@staticmethod
def postDeleteDestination(request, response):
return pluginManagerGlobal.globalPlug(request, postDeleteDestination, response)
@staticmethod
def preSubmitBackupSchedule(request):
return pluginManagerGlobal.globalPlug(request, preSubmitBackupSchedule)
@staticmethod
def postSubmitBackupSchedule(request, response):
return pluginManagerGlobal.globalPlug(request, postSubmitBackupSchedule, response)
@staticmethod
def preScheduleDelete(request):
return pluginManagerGlobal.globalPlug(request, preScheduleDelete)
@staticmethod
def postScheduleDelete(request, response):
return pluginManagerGlobal.globalPlug(request, postScheduleDelete, response)
@staticmethod
def preSubmitRemoteBackups(request):
return pluginManagerGlobal.globalPlug(request, preSubmitRemoteBackups)
@staticmethod
def postSubmitRemoteBackups(request, response):
return pluginManagerGlobal.globalPlug(request, postSubmitRemoteBackups, response)
@staticmethod
def preStarRemoteTransfer(request):
return pluginManagerGlobal.globalPlug(request, preStarRemoteTransfer)
@staticmethod
def postStarRemoteTransfer(request, response):
return pluginManagerGlobal.globalPlug(request, postStarRemoteTransfer, response)
@staticmethod
def preRemoteBackupRestore(request):
return pluginManagerGlobal.globalPlug(request, preRemoteBackupRestore)
@staticmethod
def postRemoteBackupRestore(request, response):
return pluginManagerGlobal.globalPlug(request, postRemoteBackupRestore, response)
@staticmethod
def postDeleteBackup(request, response):
return pluginManagerGlobal.globalPlug(request, postRemoteBackupRestore, response)
| 35.238095
| 95
| 0.773514
| 259
| 3,700
| 11.050193
| 0.142857
| 0.131027
| 0.30573
| 0.366876
| 0.504892
| 0.28232
| 0.103075
| 0.103075
| 0.061495
| 0
| 0
| 0
| 0.164865
| 3,700
| 104
| 96
| 35.576923
| 0.926214
| 0
| 0
| 0.371795
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.320513
| false
| 0
| 0.025641
| 0.320513
| 0.679487
| 0
| 0
| 0
| 1
| 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
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
7f8c79b56ca448f21d26fedc902f36a604923904
| 38
|
py
|
Python
|
lg_pointer/src/lg_pointer/__init__.py
|
carlosvquezada/lg_ros_nodes
|
7560e99272d06ef5c80a5444131dad72c078a718
|
[
"Apache-2.0"
] | null | null | null |
lg_pointer/src/lg_pointer/__init__.py
|
carlosvquezada/lg_ros_nodes
|
7560e99272d06ef5c80a5444131dad72c078a718
|
[
"Apache-2.0"
] | null | null | null |
lg_pointer/src/lg_pointer/__init__.py
|
carlosvquezada/lg_ros_nodes
|
7560e99272d06ef5c80a5444131dad72c078a718
|
[
"Apache-2.0"
] | null | null | null |
from megaviewport import MegaViewport
| 19
| 37
| 0.894737
| 4
| 38
| 8.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 38
| 1
| 38
| 38
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
7f8f5aae9f7cedd2884c8d1c873365134650fb8a
| 36
|
py
|
Python
|
src/__init__.py
|
dombraccia/gff3_parser
|
a01ba73a7feeca0d50034d6de549196c63564e5b
|
[
"MIT"
] | 1
|
2021-09-17T03:21:30.000Z
|
2021-09-17T03:21:30.000Z
|
src/__init__.py
|
dombraccia/gff3_parser
|
a01ba73a7feeca0d50034d6de549196c63564e5b
|
[
"MIT"
] | null | null | null |
src/__init__.py
|
dombraccia/gff3_parser
|
a01ba73a7feeca0d50034d6de549196c63564e5b
|
[
"MIT"
] | 1
|
2021-09-17T03:23:15.000Z
|
2021-09-17T03:23:15.000Z
|
from src.gff3_parser.parser import *
| 36
| 36
| 0.833333
| 6
| 36
| 4.833333
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.030303
| 0.083333
| 36
| 1
| 36
| 36
| 0.848485
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
7fad7e6b3d9ac773fa16261180173f3e20e02fe3
| 6,555
|
py
|
Python
|
Test_Menu_Basket.py
|
Shemlenie/Autotest_python
|
d7b37dc52e4260d9aa3cae05bd7d68cd3c506b53
|
[
"Apache-2.0"
] | null | null | null |
Test_Menu_Basket.py
|
Shemlenie/Autotest_python
|
d7b37dc52e4260d9aa3cae05bd7d68cd3c506b53
|
[
"Apache-2.0"
] | null | null | null |
Test_Menu_Basket.py
|
Shemlenie/Autotest_python
|
d7b37dc52e4260d9aa3cae05bd7d68cd3c506b53
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
from selenium import webdriver
from selenium.common.exceptions import NoSuchElementException
from selenium.common.exceptions import NoAlertPresentException
import unittest, time, re
url="C:\\Users\\Glebo\\OneDrive\\Рабочий стол\\UIR\\chromedriver.exe"
class Test_Menu_Basket(unittest.TestCase):
def setUp(self):
self.driver = webdriver.Chrome(url)
self.driver.implicitly_wait(30)
self.base_url = "https://www.google.com/"
self.verificationErrors = []
self.accept_next_alert = True
def test_menu_basket_all(self):
driver = self.driver
self.open_menu_page(driver, "http://localhost:8080/menu")
self.auth(driver, "test1@mail.ru", "12345678")
self.menu_click_all(driver, "Holywood")
def test_menu_basket_limit(self):
driver = self.driver
self.open_menu_page(driver, "http://localhost:8080/menu")
self.auth(driver, "test1@mail.ru", "12345678")
self.menu_click_limit(driver, "Fedora Litkina")
def open_menu_page(self, driver, url):
driver.get(url)
def auth(self, driver, mail, password):
# Почта
driver.find_element_by_xpath("//div[@id='app']/section/header/div/div/button").click()
driver.find_element_by_xpath("//input[@type='text']").click()
driver.find_element_by_xpath("//input[@type='text']").clear()
driver.find_element_by_xpath("//input[@type='text']").send_keys(mail)
# Пароль
# time.sleep(5)
driver.find_element_by_xpath("//input[@type='password']").clear()
driver.find_element_by_xpath("//input[@type='password']").send_keys(password)
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[2]/div/div[4]/button").click()
def menu_click_limit(self, driver, address):
# Выбор блюд из меню
for i in range(100):
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[2]/div/div[3]/i").click()
# Перейти в корзину
driver.find_element_by_xpath("//div[@id='app']/section/header/div/div/i").click()
# Указать адрес доставки
driver.find_element_by_xpath("//input[@type='text']").click()
driver.find_element_by_xpath("//input[@type='text']").clear()
driver.find_element_by_xpath("//input[@type='text']").send_keys(address)
# Оформить заказ
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[4]/button").click()
# ОК
driver.find_element_by_xpath("//button/div").click()
def menu_click_all(self, driver, address):
# Выбор блюд из меню
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[2]/div/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[2]/div[2]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[2]/div[3]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[2]/div[4]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[2]/div[5]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[2]/div[6]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[2]/div[2]/div/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[2]/div[2]/div[2]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[2]/div[2]/div[3]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[2]/div[2]/div[4]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[3]/div[2]/div/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[3]/div[2]/div[2]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[3]/div[2]/div[3]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[4]/div[2]/div/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[4]/div[2]/div[2]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[4]/div[2]/div[3]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[5]/div[2]/div/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[5]/div[2]/div[2]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[5]/div[2]/div[3]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[5]/div[2]/div[4]/div[3]/i").click()
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div[5]/div[2]/div[5]/div[3]/i").click()
# Перейти в корзину
driver.find_element_by_xpath("//div[@id='app']/section/header/div/div/i").click()
# Указать адрес доставки
driver.find_element_by_xpath("//input[@type='text']").click()
driver.find_element_by_xpath("//input[@type='text']").clear()
driver.find_element_by_xpath("//input[@type='text']").send_keys(address)
# Оформить заказ
driver.find_element_by_xpath("//div[@id='app']/section/section/section/div/div[4]/button").click()
# ОК
driver.find_element_by_xpath("//button/div").click()
def is_element_present(self, how, what):
try: self.driver.find_element(by=how, value=what)
except NoSuchElementException as e: return False
return True
def is_alert_present(self):
try: self.driver.switch_to.alert()
except NoAlertPresentException as e: return False
return True
def close_alert_and_get_its_text(self):
try:
alert = self.driver.switch_to.alert()
alert_text = alert.text
if self.accept_next_alert:
alert.accept()
else:
alert.dismiss()
return alert_text
finally: self.accept_next_alert = True
def tearDown(self):
self.driver.quit()
self.assertEqual([], self.verificationErrors)
if __name__ == "__main__":
unittest.main()
| 54.173554
| 118
| 0.651259
| 955
| 6,555
| 4.282723
| 0.139267
| 0.171149
| 0.174572
| 0.19511
| 0.781174
| 0.749633
| 0.736919
| 0.708068
| 0.686308
| 0.685086
| 0
| 0.020268
| 0.156979
| 6,555
| 120
| 119
| 54.625
| 0.71987
| 0.031121
| 0
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| 0
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| 0.360322
| 0.333176
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| 1
| 0.119565
| false
| 0.032609
| 0.043478
| 0
| 0.206522
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| null | 0
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0
| 6
|
f6beb6f1e4f2426087898c28ecc7c0898e84fed9
| 9,121
|
py
|
Python
|
musicData1.py
|
Maier007/Rhapsography
|
05044efee036430b7f8eab891a7bbe1bf49b6e94
|
[
"MIT"
] | null | null | null |
musicData1.py
|
Maier007/Rhapsography
|
05044efee036430b7f8eab891a7bbe1bf49b6e94
|
[
"MIT"
] | null | null | null |
musicData1.py
|
Maier007/Rhapsography
|
05044efee036430b7f8eab891a7bbe1bf49b6e94
|
[
"MIT"
] | null | null | null |
XMajor = [[15, 13.333333333333334, 26.666666666666668, 46.666666666666664, 13.333333333333334, 0.0, 0.0, 0.0],[13, 15.384615384615385, 38.46153846153846, 7.6923076923076925, 15.384615384615385, 15.384615384615385, 0.0, 7.6923076923076925],[4, 25.0, 0.0, 25.0, 50.0, 0.0, 0.0, 0.0],[10, 20.0, 30.0, 0.0, 0.0, 0.0, 20.0, 30.0],[6, 0.0, 33.333333333333336, 33.333333333333336, 0.0, 33.333333333333336, 0.0, 0.0],[8, 12.5, 37.5, 12.5, 12.5, 25.0, 0.0, 0.0],[12, 0.0, 41.666666666666664, 0.0, 16.666666666666668, 8.333333333333334, 16.666666666666668, 16.666666666666668],[4, 0.0, 0.0, 0.0, 50.0, 0.0, 50.0, 0.0],[11, 36.36363636363637, 36.36363636363637, 18.181818181818183, 9.090909090909092, 0.0, 0.0, 0.0],[9, 22.22222222222222, 22.22222222222222, 33.333333333333336, 0.0, 0.0, 22.22222222222222, 0.0],[11, 18.181818181818183, 9.090909090909092, 18.181818181818183, 9.090909090909092, 18.181818181818183, 27.272727272727273, 0.0],[9, 22.22222222222222, 44.44444444444444, 33.333333333333336, 0.0, 0.0, 0.0, 0.0],[12, 16.666666666666668, 8.333333333333334, 25.0, 41.666666666666664, 8.333333333333334, 0.0, 0.0],[7, 28.571428571428573, 28.571428571428573, 0.0, 0.0, 14.285714285714286, 28.571428571428573, 0.0],[10, 30.0, 10.0, 10.0, 20.0, 10.0, 10.0, 10.0],[7, 14.285714285714286, 14.285714285714286, 28.571428571428573, 14.285714285714286, 28.571428571428573, 0.0, 0.0],[6, 16.666666666666668, 33.333333333333336, 0.0, 16.666666666666668, 0.0, 33.333333333333336, 0.0],[12, 8.333333333333334, 50.0, 16.666666666666668, 8.333333333333334, 16.666666666666668, 0.0, 0.0],[12, 25.0, 41.666666666666664, 16.666666666666668, 16.666666666666668, 0.0, 0.0, 0.0],[7, 28.571428571428573, 0.0, 14.285714285714286, 14.285714285714286, 14.285714285714286, 14.285714285714286, 14.285714285714286],[13, 23.076923076923077, 7.6923076923076925, 30.76923076923077, 0.0, 15.384615384615385, 23.076923076923077, 0.0],[10, 20.0, 30.0, 20.0, 20.0, 10.0, 0.0, 0.0],[10, 10.0, 30.0, 20.0, 30.0, 0.0, 10.0, 0.0],[15, 20.0, 13.333333333333334, 26.666666666666668, 13.333333333333334, 20.0, 6.666666666666667, 0.0],[7, 28.571428571428573, 42.857142857142854, 0.0, 14.285714285714286, 14.285714285714286, 0.0, 0.0],[6, 33.333333333333336, 0.0, 0.0, 33.333333333333336, 0.0, 16.666666666666668, 16.666666666666668],[7, 14.285714285714286, 28.571428571428573, 14.285714285714286, 28.571428571428573, 0.0, 14.285714285714286, 0.0],[6, 16.666666666666668, 33.333333333333336, 16.666666666666668, 16.666666666666668, 0.0, 16.666666666666668, 0.0],[5, 20.0, 20.0, 0.0, 60.0, 0.0, 0.0, 0.0],[13, 0.0, 15.384615384615385, 15.384615384615385, 38.46153846153846, 15.384615384615385, 7.6923076923076925, 7.6923076923076925],[6, 16.666666666666668, 33.333333333333336, 0.0, 0.0, 33.333333333333336, 16.666666666666668, 0.0],[8, 25.0, 25.0, 25.0, 12.5, 0.0, 12.5, 0.0],[7, 28.571428571428573, 28.571428571428573, 14.285714285714286, 14.285714285714286, 0.0, 14.285714285714286, 0.0],[7, 28.571428571428573, 0.0, 42.857142857142854, 28.571428571428573, 0.0, 0.0, 0.0],[9, 33.333333333333336, 11.11111111111111, 11.11111111111111, 11.11111111111111, 22.22222222222222, 11.11111111111111, 0.0],[8, 12.5, 12.5, 50.0, 0.0, 12.5, 12.5, 0.0],[7, 28.571428571428573, 0.0, 0.0, 57.142857142857146, 14.285714285714286, 0.0, 0.0],[10, 0.0, 20.0, 20.0, 10.0, 10.0, 30.0, 10.0],[7, 28.571428571428573, 28.571428571428573, 0.0, 0.0, 14.285714285714286, 28.571428571428573, 0.0],[14, 7.142857142857143, 21.428571428571427, 14.285714285714286, 14.285714285714286, 42.857142857142854, 0.0, 0.0],[8, 12.5, 37.5, 37.5, 0.0, 12.5, 0.0, 0.0],[7, 0.0, 0.0, 28.571428571428573, 0.0, 28.571428571428573, 42.857142857142854, 0.0],[8, 12.5, 12.5, 12.5, 12.5, 25.0, 25.0, 0.0],[7, 14.285714285714286, 14.285714285714286, 14.285714285714286, 42.857142857142854, 14.285714285714286, 0.0, 0.0],[8, 25.0, 25.0, 12.5, 0.0, 12.5, 0.0, 25.0],[13, 30.76923076923077, 15.384615384615385, 15.384615384615385, 15.384615384615385, 15.384615384615385, 7.6923076923076925, 0.0],[7, 28.571428571428573, 14.285714285714286, 14.285714285714286, 0.0, 0.0, 28.571428571428573, 14.285714285714286],[6, 16.666666666666668, 50.0, 16.666666666666668, 0.0, 0.0, 16.666666666666668, 0.0],[8, 25.0, 37.5, 12.5, 0.0, 0.0, 12.5, 12.5],[9, 22.22222222222222, 0.0, 33.333333333333336, 22.22222222222222, 0.0, 0.0, 22.22222222222222],[6, 50.0, 0.0, 33.333333333333336, 0.0, 0.0, 16.666666666666668, 0.0],[9, 0.0, 22.22222222222222, 22.22222222222222, 22.22222222222222, 22.22222222222222, 11.11111111111111, 0.0],[7, 0.0, 28.571428571428573, 14.285714285714286, 28.571428571428573, 0.0, 0.0, 28.571428571428573],[11, 0.0, 27.272727272727273, 9.090909090909092, 18.181818181818183, 27.272727272727273, 9.090909090909092, 9.090909090909092],[13, 15.384615384615385, 23.076923076923077, 15.384615384615385, 7.6923076923076925, 23.076923076923077, 15.384615384615385, 0.0],[9, 22.22222222222222, 44.44444444444444, 11.11111111111111, 22.22222222222222, 0.0, 0.0, 0.0]]
YMajor = [0, 0, 1, 0, 3, 0, 0, 3, 0, 3, 0, 0, 0, 3, 1, 3, 3, 0, 0, 0, 2, 3, 3, 0, 3, 0, 3, 3, 3, 3, 0, 0, 0, 3, 0, 3, 0, 0, 3, 3, 0, 3, 3, 3, 0, 0, 3, 3, 0, 0, 1, 3, 3, 1, 0, 3]
XMinor = [[11, 9.090909090909092, 36.36363636363637, 18.181818181818183, 9.090909090909092, 9.090909090909092, 9.090909090909092, 9.090909090909092],[7, 28.571428571428573, 14.285714285714286, 28.571428571428573, 14.285714285714286, 0.0, 0.0, 14.285714285714286],[5, 20.0, 40.0, 20.0, 20.0, 0.0, 0.0, 0.0],[8, 12.5, 0.0, 25.0, 37.5, 12.5, 12.5, 0.0],[13, 7.6923076923076925, 30.76923076923077, 15.384615384615385, 30.76923076923077, 7.6923076923076925, 7.6923076923076925, 0.0],[4, 0.0, 50.0, 50.0, 0.0, 0.0, 0.0, 0.0],[3, 0.0, 0.0, 0.0, 33.333333333333336, 33.333333333333336, 33.333333333333336, 0.0],[8, 12.5, 37.5, 25.0, 0.0, 0.0, 25.0, 0.0],[13, 0.0, 7.6923076923076925, 7.6923076923076925, 23.076923076923077, 23.076923076923077, 38.46153846153846, 0.0],[8, 12.5, 50.0, 0.0, 0.0, 25.0, 12.5, 0.0],[7, 14.285714285714286, 42.857142857142854, 28.571428571428573, 14.285714285714286, 0.0, 0.0, 0.0],[14, 35.714285714285715, 14.285714285714286, 14.285714285714286, 0.0, 35.714285714285715, 0.0, 0.0],[12, 50.0, 8.333333333333334, 16.666666666666668, 16.666666666666668, 8.333333333333334, 0.0, 0.0],[10, 10.0, 10.0, 40.0, 30.0, 0.0, 10.0, 0.0],[11, 9.090909090909092, 18.181818181818183, 0.0, 18.181818181818183, 18.181818181818183, 9.090909090909092, 27.272727272727273],[10, 0.0, 40.0, 10.0, 20.0, 20.0, 0.0, 10.0],[8, 37.5, 37.5, 0.0, 0.0, 25.0, 0.0, 0.0],[12, 16.666666666666668, 16.666666666666668, 16.666666666666668, 33.333333333333336, 0.0, 16.666666666666668, 0.0],[9, 11.11111111111111, 33.333333333333336, 22.22222222222222, 0.0, 22.22222222222222, 11.11111111111111, 0.0],[6, 16.666666666666668, 16.666666666666668, 33.333333333333336, 16.666666666666668, 0.0, 16.666666666666668, 0.0],[7, 0.0, 14.285714285714286, 42.857142857142854, 14.285714285714286, 0.0, 0.0, 28.571428571428573],[10, 20.0, 30.0, 30.0, 10.0, 0.0, 10.0, 0.0],[8, 0.0, 37.5, 25.0, 0.0, 25.0, 12.5, 0.0],[11, 9.090909090909092, 0.0, 54.54545454545455, 18.181818181818183, 18.181818181818183, 0.0, 0.0],[6, 0.0, 33.333333333333336, 66.66666666666667, 0.0, 0.0, 0.0, 0.0],[6, 0.0, 33.333333333333336, 33.333333333333336, 16.666666666666668, 16.666666666666668, 0.0, 0.0],[10, 20.0, 20.0, 30.0, 20.0, 0.0, 0.0, 10.0],[10, 20.0, 20.0, 30.0, 20.0, 10.0, 0.0, 0.0],[9, 22.22222222222222, 0.0, 0.0, 55.55555555555556, 22.22222222222222, 0.0, 0.0],[11, 27.272727272727273, 9.090909090909092, 18.181818181818183, 0.0, 18.181818181818183, 9.090909090909092, 18.181818181818183],[10, 40.0, 10.0, 0.0, 10.0, 20.0, 20.0, 0.0],[10, 10.0, 30.0, 10.0, 20.0, 30.0, 0.0, 0.0],[12, 0.0, 8.333333333333334, 16.666666666666668, 41.666666666666664, 16.666666666666668, 16.666666666666668, 0.0],[7, 0.0, 57.142857142857146, 42.857142857142854, 0.0, 0.0, 0.0, 0.0],[11, 0.0, 27.272727272727273, 9.090909090909092, 27.272727272727273, 9.090909090909092, 27.272727272727273, 0.0],[8, 25.0, 37.5, 0.0, 25.0, 0.0, 12.5, 0.0],[9, 0.0, 44.44444444444444, 0.0, 0.0, 22.22222222222222, 11.11111111111111, 22.22222222222222],[11, 18.181818181818183, 27.272727272727273, 9.090909090909092, 18.181818181818183, 9.090909090909092, 9.090909090909092, 9.090909090909092],[11, 0.0, 54.54545454545455, 9.090909090909092, 27.272727272727273, 0.0, 9.090909090909092, 0.0],[4, 25.0, 25.0, 25.0, 25.0, 0.0, 0.0, 0.0],[3, 33.333333333333336, 33.333333333333336, 0.0, 0.0, 0.0, 33.333333333333336, 0.0],[12, 33.333333333333336, 16.666666666666668, 16.666666666666668, 16.666666666666668, 16.666666666666668, 0.0, 0.0],[10, 20.0, 30.0, 40.0, 10.0, 0.0, 0.0, 0.0],[12, 16.666666666666668, 16.666666666666668, 16.666666666666668, 0.0, 33.333333333333336, 16.666666666666668, 0.0],[5, 40.0, 20.0, 20.0, 20.0, 0.0, 0.0, 0.0],[3, 33.333333333333336, 0.0, 0.0, 66.66666666666667, 0.0, 0.0, 0.0],[9, 0.0, 33.333333333333336, 44.44444444444444, 0.0, 11.11111111111111, 11.11111111111111, 0.0]]
YMinor = [2, 1, 2, 1, 1, 1, 3, 2, 1, 1, 2, 2, 2, 3, 1, 1, 2, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 3, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 1, 1, 2, 2, 1]
| 1,824.2
| 4,966
| 0.70398
| 1,652
| 9,121
| 3.886804
| 0.044794
| 0.121788
| 0.099984
| 0.080361
| 0.769974
| 0.731506
| 0.474848
| 0.375798
| 0.171001
| 0.145616
| 0
| 0.772305
| 0.091876
| 9,121
| 4
| 4,967
| 2,280.25
| 0.002898
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| 1
| 1
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| 0
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| null | 0
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| 0
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| 0
|
0
| 6
|
63e40f47e46b06271a470ddf6fb3be20271c72b3
| 4,515
|
py
|
Python
|
idl2py/star/helio_jd.py
|
RapidLzj/idl2py
|
193051cd8d01db0d125b8975713b885ad521a992
|
[
"MIT"
] | null | null | null |
idl2py/star/helio_jd.py
|
RapidLzj/idl2py
|
193051cd8d01db0d125b8975713b885ad521a992
|
[
"MIT"
] | null | null | null |
idl2py/star/helio_jd.py
|
RapidLzj/idl2py
|
193051cd8d01db0d125b8975713b885ad521a992
|
[
"MIT"
] | null | null | null |
"""
By Dr Jie Zheng -Q, NAOC
v1 2019-04-27
"""
import numpy as np
from..util import *
def helio_jd():
pass
#function helio_jd,date,ra,dec, B1950 = B1950, TIME_DIFF = time_diff
#;+
#; NAME:
#; HELIO_JD
#; PURPOSE:
#; Convert geocentric (reduced) Julian date to heliocentric Julian date
#; EXPLANATION:
#; This procedure correct for the extra light travel time between the Earth
#; and the Sun.
#;
#; An online calculator for this quantity is available at
#; http://www.physics.sfasu.edu/astro/javascript/hjd.html
#;
#; Users requiring more precise calculations and documentation should
#; look at the IDL code available at
#; http://astroutils.astronomy.ohio-state.edu/time/
#; CALLING SEQUENCE:
#; jdhelio = HELIO_JD( date, ra, dec, /B1950, /TIME_DIFF)
#;
#; INPUTS
#; date - reduced Julian date (= JD - 2400000), scalar or vector, MUST
#; be double precision
#; ra,dec - scalars giving right ascension and declination in DEGREES
#; Equinox is J2000 unless the /B1950 keyword is set
#;
#; OUTPUTS:
#; jdhelio - heliocentric reduced Julian date. If /TIME_DIFF is set, then
#; HELIO_JD() instead returns the time difference in seconds
#; between the geocentric and heliocentric Julian date.
#;
#; OPTIONAL INPUT KEYWORDS
#; /B1950 - if set, then input coordinates are assumed to be in equinox
#; B1950 coordinates.
#; /TIME_DIFF - if set, then HELIO_JD() returns the time difference
#; (heliocentric JD - geocentric JD ) in seconds
#;
#; EXAMPLE:
#; What is the heliocentric Julian date of an observation of V402 Cygni
#; (J2000: RA = 20 9 7.8, Dec = 37 09 07) taken June 15, 1973 at 11:40 UT?
#;
#; IDL> juldate, [1973,6,15,11,40], jd ;Get geocentric Julian date
#; IDL> hjd = helio_jd( jd, ten(20,9,7.8)*15., ten(37,9,7) )
#;
#; ==> hjd = 41848.9881
#;
#; Wayne Warren (Raytheon ITSS) has compared the results of HELIO_JD with the
#; FORTRAN subroutines in the STARLINK SLALIB library (see
#; http://star-www.rl.ac.uk/).
#; Time Diff (sec)
#; Date RA(2000) Dec(2000) STARLINK IDL
#;
#; 1999-10-29T00:00:00.0 21 08 25. -67 22 00. -59.0 -59.0
#; 1999-10-29T00:00:00.0 02 56 33.4 +00 26 55. 474.1 474.1
#; 1940-12-11T06:55:00.0 07 34 41.9 -00 30 42. 366.3 370.2
#; 1992-02-29T03:15:56.2 12 56 27.4 +42 10 17. 350.8 350.9
#; 2000-03-01T10:26:31.8 14 28 36.7 -20 42 11. 243.7 243.7
#; 2100-02-26T09:18:24.2 08 26 51.7 +85 47 28. 104.0 108.8
#; PROCEDURES CALLED:
#; bprecess, xyz, zparcheck
#;
#; REVISION HISTORY:
#; Algorithm from the book Astronomical Photometry by Henden, p. 114
#; Written, W. Landsman STX June, 1989
#; Make J2000 default equinox, add B1950, /TIME_DIFF keywords, compute
#; variation of the obliquity W. Landsman November 1999
#;-
# On_error,2
# If N_params() LT 3 then begin
# print,'Syntax - jdhelio = HELIO_JD( date, ra, dec, /B1950, /TIME_DIFF)'
# print,' date - reduced Julian date (= JD - 2400000)'
# print,' Ra and Dec must be in degrees'
# endif
#
#;Because XYZ uses default B1950 coordinates, we'll convert everything to B1950
#
# if not keyword_set(B1950) then bprecess,ra,dec,ra1,dec1 else begin
# ra1 = ra
# dec1 = dec
# endelse
#
# radeg = 180.0d/!DPI
# zparcheck,'HELIO_JD',date,1,[3,4,5],[0,1],'Reduced Julian Date'
#
# delta_t = (double(date) - 33282.42345905d)/36525.0d
# epsilon_sec = poly( delta_t, [44.836d, -46.8495, -0.00429, 0.00181])
# epsilon = (23.433333d0 + epsilon_sec/3600.0d)/radeg
# ra1 = ra1/radeg
# dec1 = dec1/radeg
#
# xyz, date, x, y, z
#
#;Find extra distance light must travel in AU, multiply by 1.49598e13 cm/AU,
#;and divide by the speed of light, and multiply by 86400 second/year
#
# time = -499.00522d*( cos(dec1)*cos(ra1)*x + $
# (tan(epsilon)*sin(dec1) + cos(dec1)*sin(ra1))*y)
#
# if keyword_set(TIME_DIFF) then return, time else $
#
# return, double(date) + time/86400.0d
#
# end
| 38.589744
| 83
| 0.57608
| 632
| 4,515
| 4.074367
| 0.471519
| 0.027184
| 0.03301
| 0.015146
| 0.071845
| 0.071845
| 0.027961
| 0.027961
| 0.027961
| 0
| 0
| 0.150907
| 0.304319
| 4,515
| 116
| 84
| 38.922414
| 0.668895
| 0.892359
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0.25
| 0.5
| 0
| 0.75
| 0
| 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
| 1
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
63e74e0083c8d7921de1b84cd074e087c1f3d2ea
| 123
|
py
|
Python
|
games/admin.py
|
phildini/tintg
|
ad82d94f37b301b5ef8062e472bac52bcfe7ad8f
|
[
"Apache-2.0"
] | null | null | null |
games/admin.py
|
phildini/tintg
|
ad82d94f37b301b5ef8062e472bac52bcfe7ad8f
|
[
"Apache-2.0"
] | null | null | null |
games/admin.py
|
phildini/tintg
|
ad82d94f37b301b5ef8062e472bac52bcfe7ad8f
|
[
"Apache-2.0"
] | null | null | null |
from django.contrib import admin
from . import models
admin.site.register(models.Game)
admin.site.register(models.Player)
| 20.5
| 34
| 0.813008
| 18
| 123
| 5.555556
| 0.555556
| 0.18
| 0.34
| 0.46
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.089431
| 123
| 5
| 35
| 24.6
| 0.892857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
1231fe97f70f17edfbd4fb5102026282cd84d9c9
| 20
|
py
|
Python
|
pydp/__init__.py
|
leclair-7/PyDP
|
0f9b354066218010243f93a9a12d01b9fd9b4d7b
|
[
"Apache-2.0"
] | null | null | null |
pydp/__init__.py
|
leclair-7/PyDP
|
0f9b354066218010243f93a9a12d01b9fd9b4d7b
|
[
"Apache-2.0"
] | null | null | null |
pydp/__init__.py
|
leclair-7/PyDP
|
0f9b354066218010243f93a9a12d01b9fd9b4d7b
|
[
"Apache-2.0"
] | null | null | null |
from .pydp import *
| 10
| 19
| 0.7
| 3
| 20
| 4.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 20
| 1
| 20
| 20
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
12334b8f0bd00fcf944263febe21f1440a22ef95
| 2,422
|
py
|
Python
|
task2_final.py
|
inwk6312winter2019/model-openbook2-lipi0035
|
acbf0427719c26e47f219a51788ea15b95906882
|
[
"MIT"
] | null | null | null |
task2_final.py
|
inwk6312winter2019/model-openbook2-lipi0035
|
acbf0427719c26e47f219a51788ea15b95906882
|
[
"MIT"
] | null | null | null |
task2_final.py
|
inwk6312winter2019/model-openbook2-lipi0035
|
acbf0427719c26e47f219a51788ea15b95906882
|
[
"MIT"
] | null | null | null |
#Part 1
import csv
def count_accessible_busstops(csv1,csv2):
count = 0
street_csv = open(csv1)
bus_csv = open(csv2)
reader1 = csv.DictReader(street_csv)
reader2 = csv.DictReader(bus_csv)
street_fdmid = []
bus_fdmid = []
for row1 in reader1:
if(row1["ST_CLASS"].upper() == "ARTERIAL".upper()):
street_fdmid.append(row1["FDMID"])
for row2 in reader2:
if(row2["ACCESSIBLE"].upper() == "Accessible".upper()):
bus_fdmid.append(row2["FDMID"])
for i in range(len(street_fdmid)):
for j in range(len(bus_fdmid)):
if(street_fdmid[i] == bus_fdmid[j]):
count = count+1
return count
cnt1 = count_accessible_busstops("Street_Centrelines.csv","Bus_Stops.csv")
print ("Number of bus Stops on ARTERIAL road which are Accessible are : {}".format(cnt1))
#Part 2
def count_nonstandard_busstops(csv1,csv2):
count = 0
street_csv = open(csv1)
bus_csv = open(csv2)
reader1 = csv.DictReader(street_csv)
reader2 = csv.DictReader(bus_csv)
street_fdmid = []
bus_fdmid = []
for row1 in reader1:
if(row1["ST_CLASS"].upper() == "LOCAL STREET".upper()):
street_fdmid.append(row1["FDMID"])
for row2 in reader2:
if(row2["ACCESSIBLE"].upper() == "Non-Standard".upper()):
bus_fdmid.append(row2["FDMID"])
for i in range(len(street_fdmid)):
for j in range(len(bus_fdmid)):
if(street_fdmid[i] == bus_fdmid[j]):
count = count+1
return count
cnt2 = count_nonstandard_busstops("Street_Centrelines.csv","Bus_Stops.csv")
print ("Number of bus Stops on LOCAL STREET road which are Non-Standard are : {}".format(cnt2))
#Part 3
def count_inaccessible_busstops(csv1,csv2):
count = 0
street_csv = open(csv1)
bus_csv = open(csv2)
reader1 = csv.DictReader(street_csv)
reader2 = csv.DictReader(bus_csv)
street_fdmid = []
bus_fdmid = []
for row1 in reader1:
if(row1["ST_CLASS"].upper() == "MINOR COLLECTOR".upper()):
street_fdmid.append(row1["FDMID"])
for row2 in reader2:
if(row2["ACCESSIBLE"].upper() == "Inaccessible".upper()):
bus_fdmid.append(row2["FDMID"])
for i in range(len(street_fdmid)):
for j in range(len(bus_fdmid)):
if(street_fdmid[i] == bus_fdmid[j]):
count = count+1
return count
cnt3 = count_inaccessible_busstops("Street_Centrelines.csv","Bus_Stops.csv")
print ("Number of bus Stops on MINOR COLLECTOR road which are Inaccessible are : {}".format(cnt3))
| 31.051282
| 98
| 0.676301
| 347
| 2,422
| 4.556196
| 0.158501
| 0.083491
| 0.037951
| 0.039848
| 0.779886
| 0.779886
| 0.779886
| 0.779886
| 0.779886
| 0.779886
| 0
| 0.028629
| 0.177952
| 2,422
| 77
| 99
| 31.454545
| 0.765445
| 0.007432
| 0
| 0.75
| 0
| 0
| 0.196168
| 0.027489
| 0
| 0
| 0
| 0
| 0
| 1
| 0.046875
| false
| 0
| 0.015625
| 0
| 0.109375
| 0.046875
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
12385d82c6be497560a15f0feb0782177cbff699
| 177
|
py
|
Python
|
opps/contrib/multisite/models.py
|
jeanmask/opps
|
031c6136c38d43aa6d1ccb25a94f7bcd65ccbf87
|
[
"MIT"
] | 159
|
2015-01-03T16:36:35.000Z
|
2022-03-29T20:50:13.000Z
|
opps/contrib/multisite/models.py
|
jeanmask/opps
|
031c6136c38d43aa6d1ccb25a94f7bcd65ccbf87
|
[
"MIT"
] | 81
|
2015-01-02T21:26:16.000Z
|
2021-05-29T12:24:52.000Z
|
opps/contrib/multisite/models.py
|
jeanmask/opps
|
031c6136c38d43aa6d1ccb25a94f7bcd65ccbf87
|
[
"MIT"
] | 75
|
2015-01-23T13:41:03.000Z
|
2021-09-24T03:45:23.000Z
|
# -*- coding: utf-8 -*-
from django.utils.translation import ugettext_lazy as _
from opps.core.permissions.models import Permission
class SitePermission(Permission):
pass
| 22.125
| 55
| 0.768362
| 22
| 177
| 6.090909
| 0.863636
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006536
| 0.135593
| 177
| 7
| 56
| 25.285714
| 0.869281
| 0.118644
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.25
| 0.5
| 0
| 0.75
| 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
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
125ca4d5a30b6a19febbad1936ed876cd9cd4428
| 70
|
py
|
Python
|
testing/test_homework_01/conftest.py
|
Akuzmicheva2021python/Python_2021_homeworks
|
910b9b5f9be30b9cc384ff3ef2e6d238eb4e2383
|
[
"Apache-2.0"
] | null | null | null |
testing/test_homework_01/conftest.py
|
Akuzmicheva2021python/Python_2021_homeworks
|
910b9b5f9be30b9cc384ff3ef2e6d238eb4e2383
|
[
"Apache-2.0"
] | null | null | null |
testing/test_homework_01/conftest.py
|
Akuzmicheva2021python/Python_2021_homeworks
|
910b9b5f9be30b9cc384ff3ef2e6d238eb4e2383
|
[
"Apache-2.0"
] | null | null | null |
# from utils import add_homework_path
#
# add_homework_path(__file__)
| 17.5
| 37
| 0.814286
| 10
| 70
| 4.9
| 0.7
| 0.44898
| 0.612245
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114286
| 70
| 3
| 38
| 23.333333
| 0.790323
| 0.9
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
89d46c1e242b479b0d9aba7198ec54484dae559a
| 11,364
|
py
|
Python
|
tests/test_results.py
|
ndarvishev/projects
|
6a9855c5f8af8fad2799ef7a203e126b834c5056
|
[
"Apache-2.0"
] | 1
|
2021-06-26T19:13:49.000Z
|
2021-06-26T19:13:49.000Z
|
tests/test_results.py
|
ndarvishev/projects
|
6a9855c5f8af8fad2799ef7a203e126b834c5056
|
[
"Apache-2.0"
] | null | null | null |
tests/test_results.py
|
ndarvishev/projects
|
6a9855c5f8af8fad2799ef7a203e126b834c5056
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
from io import BytesIO
from json import dumps
from re import S
from tests.test_datasets import TASK_ID
from unittest import TestCase
from fastapi.testclient import TestClient
from minio.error import BucketAlreadyOwnedByYou
from projects.api.main import app
from projects.controllers.utils import uuid_alpha
from projects.database import engine
from projects.kfp import kfp_client
from projects.object_storage import BUCKET_NAME, MINIO_CLIENT
TEST_CLIENT = TestClient(app)
PROJECT_ID = str(uuid_alpha())
EXPERIMENT_ID = str(uuid_alpha())
EXPERIMENT_ID_2 = str(uuid_alpha())
OPERATOR_ID = str(uuid_alpha())
OPERATOR_ID_2 = str(uuid_alpha())
LATEST_RUN = "latest"
TASK_ID = str(uuid_alpha())
NAME = "foo"
IMAGE = "platiagro/platiagro-experiment-image-test:0.2.0"
CATEGORY = "DEFAULT"
CREATED_AT = "2000-01-01 00:00:00"
UPDATED_AT = "2000-01-01 00:00:00"
CONTENT_DISPOSITION = "attachment; filename=results.zip"
CONTENT_TYPE = "application/x-zip-compressed"
MOCK_EXPERIMENT_PATH = "tests/resources/mocked_experiment.yaml"
MOCK_DESTINATION_PATH = "tests/resources/mocked.yaml"
class TestResults(TestCase):
def setUp(self):
conn = engine.connect()
text = (
f"INSERT INTO projects (uuid, name, created_at, updated_at) "
f"VALUES (%s, %s, %s, %s)"
)
conn.execute(text, (PROJECT_ID, NAME, CREATED_AT, UPDATED_AT,))
text = (
f"INSERT INTO experiments (uuid, name, project_id, position, is_active, created_at, updated_at) "
f"VALUES (%s, %s, %s, %s, %s, %s, %s)"
)
conn.execute(text, (EXPERIMENT_ID, NAME, PROJECT_ID, 1, 1, CREATED_AT, UPDATED_AT))
text = (
f"INSERT INTO experiments (uuid, name, project_id, position, is_active, created_at, updated_at) "
f"VALUES (%s, %s, %s, %s, %s, %s, %s)"
)
conn.execute(text, (EXPERIMENT_ID_2, NAME, PROJECT_ID, 1, 1, CREATED_AT, UPDATED_AT))
text = (
f"INSERT INTO tasks (uuid, name, image, category, parameters, "
f"experiment_notebook_path, cpu_limit, cpu_request, memory_limit, memory_request, "
f"readiness_probe_initial_delay_seconds, is_default, created_at, updated_at) "
f"VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"
)
conn.execute(text, (TASK_ID, NAME, IMAGE, CATEGORY, dumps([]),
"Experiment.ipynb", "100m", "100m", "1Gi", "1Gi", 300, 0, CREATED_AT, UPDATED_AT,))
text = (
f"INSERT INTO operators (uuid, status, experiment_id, task_id, parameters, created_at, updated_at) "
f"VALUES (%s, %s, %s, %s, %s, %s, %s)"
)
conn.execute(text, (OPERATOR_ID, "Unset", EXPERIMENT_ID, TASK_ID, dumps([]), CREATED_AT, UPDATED_AT,))
text = (
f"INSERT INTO operators (uuid, status, experiment_id, task_id, parameters, created_at, updated_at) "
f"VALUES (%s, %s, %s, %s, %s, %s, %s)"
)
conn.execute(text, (OPERATOR_ID_2, "Unset", EXPERIMENT_ID, TASK_ID, dumps([]), CREATED_AT, UPDATED_AT,))
with open(MOCK_EXPERIMENT_PATH, "r") as file:
content = file.read()
content = content.replace("$experimentId", EXPERIMENT_ID)
content = content.replace("$taskName", NAME)
content = content.replace("$operatorId", OPERATOR_ID)
content = content.replace("$image", IMAGE)
with open(MOCK_DESTINATION_PATH, "w") as file:
file.write(content)
kfp_experiment = kfp_client().create_experiment(name=EXPERIMENT_ID)
run = kfp_client().run_pipeline(
experiment_id=kfp_experiment.id,
job_name=f"experiment-{EXPERIMENT_ID}",
pipeline_package_path=MOCK_DESTINATION_PATH,
)
self.run_id = run.id
with open(MOCK_EXPERIMENT_PATH, "r") as file:
content = file.read()
content = content.replace("$experimentId", EXPERIMENT_ID_2)
content = content.replace("$taskName", NAME)
content = content.replace("$operatorId", OPERATOR_ID)
content = content.replace("$image", IMAGE)
with open(MOCK_DESTINATION_PATH, "w") as file:
file.write(content)
kfp_experiment = kfp_client().create_experiment(name=EXPERIMENT_ID_2)
run = kfp_client().run_pipeline(
experiment_id=kfp_experiment.id,
job_name=f"experiment-{EXPERIMENT_ID_2}",
pipeline_package_path=MOCK_DESTINATION_PATH,
)
self.run_id_empty = run.id
try:
MINIO_CLIENT.make_bucket(BUCKET_NAME)
except BucketAlreadyOwnedByYou:
pass
buffer = BytesIO()
MINIO_CLIENT.put_object(
bucket_name=BUCKET_NAME,
object_name=f"experiments/{EXPERIMENT_ID}/operators/{OPERATOR_ID}/{self.run_id}/figure-000101000000000000.png",
data=buffer,
length=buffer.getbuffer().nbytes,
)
MINIO_CLIENT.put_object(
bucket_name=BUCKET_NAME,
object_name=f"experiments/{EXPERIMENT_ID}/operators/{OPERATOR_ID}/{self.run_id}/.metadata",
data=buffer,
length=buffer.getbuffer().nbytes,
)
MINIO_CLIENT.put_object(
bucket_name=BUCKET_NAME,
object_name=f"experiments/{EXPERIMENT_ID}/operators/{OPERATOR_ID}/foo/.metadata",
data=buffer,
length=buffer.getbuffer().nbytes,
)
def tearDown(self):
kfp_experiment = kfp_client().get_experiment(experiment_name=EXPERIMENT_ID)
kfp_client().experiments.delete_experiment(id=kfp_experiment.id)
kfp_experiment = kfp_client().get_experiment(experiment_name=EXPERIMENT_ID_2)
kfp_client().experiments.delete_experiment(id=kfp_experiment.id)
MINIO_CLIENT.remove_object(
bucket_name=BUCKET_NAME,
object_name=f"experiments/{EXPERIMENT_ID}/operators/{OPERATOR_ID}/{self.run_id}/figure-000101000000000000.png",
)
MINIO_CLIENT.remove_object(
bucket_name=BUCKET_NAME,
object_name=f"experiments/{EXPERIMENT_ID}/operators/{OPERATOR_ID}/foo/.metadata",
)
MINIO_CLIENT.remove_object(
bucket_name=BUCKET_NAME,
object_name=f"experiments/{EXPERIMENT_ID}/operators/{OPERATOR_ID}/{self.run_id}/.metadata",
)
conn = engine.connect()
text = f"DELETE FROM operators WHERE experiment_id = '{EXPERIMENT_ID}'"
conn.execute(text)
text = f"DELETE FROM tasks WHERE uuid = '{TASK_ID}'"
conn.execute(text)
text = f"DELETE FROM experiments WHERE project_id = '{PROJECT_ID}'"
conn.execute(text)
text = f"DELETE FROM projects WHERE uuid = '{PROJECT_ID}'"
conn.execute(text)
conn.close()
def test_get_results(self):
rv = TEST_CLIENT.get(f"/projects/unk/experiments/{EXPERIMENT_ID}/runs/{LATEST_RUN}/results")
result = rv.json()
expected = {"message": "The specified project does not exist"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/unk/runs/{LATEST_RUN}/results")
result = rv.json()
expected = {"message": "The specified experiment does not exist"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID}/runs/unk/results")
result = rv.json()
expected = {"message": "The specified run does not exist"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID_2}/runs/{self.run_id_empty}/results")
result = rv.json()
expected = {"message": "The specified run has no results"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID}/runs/{self.run_id}/results")
self.assertEqual(rv.status_code, 200)
self.assertEqual(
rv.headers.get("Content-Disposition"),
CONTENT_DISPOSITION
)
self.assertEqual(
rv.headers.get("Content-Type"),
CONTENT_TYPE
)
# test `run_id=latest`
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID}/runs/{LATEST_RUN}/results")
self.assertEqual(rv.status_code, 200)
self.assertEqual(
rv.headers.get("Content-Disposition"),
CONTENT_DISPOSITION
)
self.assertEqual(
rv.headers.get("Content-Type"),
CONTENT_TYPE
)
def test_get_operators_results(self):
rv = TEST_CLIENT.get(f"/projects/unk/experiments/{EXPERIMENT_ID}/runs/{LATEST_RUN}/operators/{OPERATOR_ID}/results")
result = rv.json()
expected = {"message": "The specified project does not exist"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/unk/runs/{LATEST_RUN}/operators/{OPERATOR_ID}/results")
result = rv.json()
expected = {"message": "The specified experiment does not exist"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID}/runs/unk/operators/{OPERATOR_ID}/results")
result = rv.json()
expected = {"message": "The specified run does not exist"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID}/runs/{LATEST_RUN}/operators/unk/results")
result = rv.json()
expected = {"message": "The specified operator does not exist"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID}/runs/{LATEST_RUN}/operators/{OPERATOR_ID_2}/results")
result = rv.json()
expected = {"message": "The specified operator has no results"}
self.assertDictEqual(expected, result)
self.assertEqual(rv.status_code, 404)
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID}/runs/{self.run_id}/operators/{OPERATOR_ID}/results")
self.assertEqual(rv.status_code, 200)
self.assertEqual(
rv.headers.get("Content-Disposition"),
CONTENT_DISPOSITION
)
self.assertEqual(
rv.headers.get("Content-Type"),
CONTENT_TYPE
)
# test `run_id=latest`
rv = TEST_CLIENT.get(f"/projects/{PROJECT_ID}/experiments/{EXPERIMENT_ID}/runs/{LATEST_RUN}/operators/{OPERATOR_ID}/results")
self.assertEqual(rv.status_code, 200)
self.assertEqual(
rv.headers.get("Content-Disposition"),
CONTENT_DISPOSITION
)
self.assertEqual(
rv.headers.get("Content-Type"),
CONTENT_TYPE
)
| 40.877698
| 135
| 0.642731
| 1,367
| 11,364
| 5.130944
| 0.122165
| 0.073567
| 0.014542
| 0.015968
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| 1
| 0.017241
| false
| 0.00431
| 0.051724
| 0
| 0.073276
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
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| 1
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| 0
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| null | 0
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| 0
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|
0
| 6
|
d61febff1d18afe2fd216c369599a0f2b80698f7
| 47,133
|
py
|
Python
|
src/java/JavaLexer.py
|
sloboegen98/BasePlag
|
65ea0f56401ec9689c7bf55247fc46a96d9340ae
|
[
"MIT"
] | null | null | null |
src/java/JavaLexer.py
|
sloboegen98/BasePlag
|
65ea0f56401ec9689c7bf55247fc46a96d9340ae
|
[
"MIT"
] | null | null | null |
src/java/JavaLexer.py
|
sloboegen98/BasePlag
|
65ea0f56401ec9689c7bf55247fc46a96d9340ae
|
[
"MIT"
] | null | null | null |
# Generated from JavaLexer.g4 by ANTLR 4.9.3
from antlr4 import *
from io import StringIO
import sys
if sys.version_info[1] > 5:
from typing import TextIO
else:
from typing.io import TextIO
def serializedATN():
with StringIO() as buf:
buf.write("\3\u608b\ua72a\u8133\ub9ed\u417c\u3be7\u7786\u5964\2\u0082")
buf.write("\u045a\b\1\4\2\t\2\4\3\t\3\4\4\t\4\4\5\t\5\4\6\t\6\4\7")
buf.write("\t\7\4\b\t\b\4\t\t\t\4\n\t\n\4\13\t\13\4\f\t\f\4\r\t\r")
buf.write("\4\16\t\16\4\17\t\17\4\20\t\20\4\21\t\21\4\22\t\22\4\23")
buf.write("\t\23\4\24\t\24\4\25\t\25\4\26\t\26\4\27\t\27\4\30\t\30")
buf.write("\4\31\t\31\4\32\t\32\4\33\t\33\4\34\t\34\4\35\t\35\4\36")
buf.write("\t\36\4\37\t\37\4 \t \4!\t!\4\"\t\"\4#\t#\4$\t$\4%\t%")
buf.write("\4&\t&\4\'\t\'\4(\t(\4)\t)\4*\t*\4+\t+\4,\t,\4-\t-\4.")
buf.write("\t.\4/\t/\4\60\t\60\4\61\t\61\4\62\t\62\4\63\t\63\4\64")
buf.write("\t\64\4\65\t\65\4\66\t\66\4\67\t\67\48\t8\49\t9\4:\t:")
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buf.write("\u0429\u0430\u0437\u043c\u043e\u0442\u044a\u044e\u0452")
buf.write("\u0458\3\2\3\2")
return buf.getvalue()
class JavaLexer(Lexer):
atn = ATNDeserializer().deserialize(serializedATN())
decisionsToDFA = [ DFA(ds, i) for i, ds in enumerate(atn.decisionToState) ]
ABSTRACT = 1
ASSERT = 2
BOOLEAN = 3
BREAK = 4
BYTE = 5
CASE = 6
CATCH = 7
CHAR = 8
CLASS = 9
CONST = 10
CONTINUE = 11
DEFAULT = 12
DO = 13
DOUBLE = 14
ELSE = 15
ENUM = 16
EXTENDS = 17
FINAL = 18
FINALLY = 19
FLOAT = 20
FOR = 21
IF = 22
GOTO = 23
IMPLEMENTS = 24
IMPORT = 25
INSTANCEOF = 26
INT = 27
INTERFACE = 28
LONG = 29
NATIVE = 30
NEW = 31
PACKAGE = 32
PRIVATE = 33
PROTECTED = 34
PUBLIC = 35
RETURN = 36
SHORT = 37
STATIC = 38
STRICTFP = 39
SUPER = 40
SWITCH = 41
SYNCHRONIZED = 42
THIS = 43
THROW = 44
THROWS = 45
TRANSIENT = 46
TRY = 47
VOID = 48
VOLATILE = 49
WHILE = 50
MODULE = 51
OPEN = 52
REQUIRES = 53
EXPORTS = 54
OPENS = 55
TO = 56
USES = 57
PROVIDES = 58
WITH = 59
TRANSITIVE = 60
VAR = 61
YIELD = 62
RECORD = 63
SEALED = 64
PERMITS = 65
NON_SEALED = 66
DECIMAL_LITERAL = 67
HEX_LITERAL = 68
OCT_LITERAL = 69
BINARY_LITERAL = 70
FLOAT_LITERAL = 71
HEX_FLOAT_LITERAL = 72
BOOL_LITERAL = 73
CHAR_LITERAL = 74
STRING_LITERAL = 75
TEXT_BLOCK = 76
NULL_LITERAL = 77
LPAREN = 78
RPAREN = 79
LBRACE = 80
RBRACE = 81
LBRACK = 82
RBRACK = 83
SEMI = 84
COMMA = 85
DOT = 86
ASSIGN = 87
GT = 88
LT = 89
BANG = 90
TILDE = 91
QUESTION = 92
COLON = 93
EQUAL = 94
LE = 95
GE = 96
NOTEQUAL = 97
AND = 98
OR = 99
INC = 100
DEC = 101
ADD = 102
SUB = 103
MUL = 104
DIV = 105
BITAND = 106
BITOR = 107
CARET = 108
MOD = 109
ADD_ASSIGN = 110
SUB_ASSIGN = 111
MUL_ASSIGN = 112
DIV_ASSIGN = 113
AND_ASSIGN = 114
OR_ASSIGN = 115
XOR_ASSIGN = 116
MOD_ASSIGN = 117
LSHIFT_ASSIGN = 118
RSHIFT_ASSIGN = 119
URSHIFT_ASSIGN = 120
ARROW = 121
COLONCOLON = 122
AT = 123
ELLIPSIS = 124
WS = 125
COMMENT = 126
LINE_COMMENT = 127
IDENTIFIER = 128
channelNames = [ u"DEFAULT_TOKEN_CHANNEL", u"HIDDEN" ]
modeNames = [ "DEFAULT_MODE" ]
literalNames = [ "<INVALID>",
"'abstract'", "'assert'", "'boolean'", "'break'", "'byte'",
"'case'", "'catch'", "'char'", "'class'", "'const'", "'continue'",
"'default'", "'do'", "'double'", "'else'", "'enum'", "'extends'",
"'final'", "'finally'", "'float'", "'for'", "'if'", "'goto'",
"'implements'", "'import'", "'instanceof'", "'int'", "'interface'",
"'long'", "'native'", "'new'", "'package'", "'private'", "'protected'",
"'public'", "'return'", "'short'", "'static'", "'strictfp'",
"'super'", "'switch'", "'synchronized'", "'this'", "'throw'",
"'throws'", "'transient'", "'try'", "'void'", "'volatile'",
"'while'", "'module'", "'open'", "'requires'", "'exports'",
"'opens'", "'to'", "'uses'", "'provides'", "'with'", "'transitive'",
"'var'", "'yield'", "'record'", "'sealed'", "'permits'", "'non-sealed'",
"'null'", "'('", "')'", "'{'", "'}'", "'['", "']'", "';'", "','",
"'.'", "'='", "'>'", "'<'", "'!'", "'~'", "'?'", "':'", "'=='",
"'<='", "'>='", "'!='", "'&&'", "'||'", "'++'", "'--'", "'+'",
"'-'", "'*'", "'/'", "'&'", "'|'", "'^'", "'%'", "'+='", "'-='",
"'*='", "'/='", "'&='", "'|='", "'^='", "'%='", "'<<='", "'>>='",
"'>>>='", "'->'", "'::'", "'@'", "'...'" ]
symbolicNames = [ "<INVALID>",
"ABSTRACT", "ASSERT", "BOOLEAN", "BREAK", "BYTE", "CASE", "CATCH",
"CHAR", "CLASS", "CONST", "CONTINUE", "DEFAULT", "DO", "DOUBLE",
"ELSE", "ENUM", "EXTENDS", "FINAL", "FINALLY", "FLOAT", "FOR",
"IF", "GOTO", "IMPLEMENTS", "IMPORT", "INSTANCEOF", "INT", "INTERFACE",
"LONG", "NATIVE", "NEW", "PACKAGE", "PRIVATE", "PROTECTED",
"PUBLIC", "RETURN", "SHORT", "STATIC", "STRICTFP", "SUPER",
"SWITCH", "SYNCHRONIZED", "THIS", "THROW", "THROWS", "TRANSIENT",
"TRY", "VOID", "VOLATILE", "WHILE", "MODULE", "OPEN", "REQUIRES",
"EXPORTS", "OPENS", "TO", "USES", "PROVIDES", "WITH", "TRANSITIVE",
"VAR", "YIELD", "RECORD", "SEALED", "PERMITS", "NON_SEALED",
"DECIMAL_LITERAL", "HEX_LITERAL", "OCT_LITERAL", "BINARY_LITERAL",
"FLOAT_LITERAL", "HEX_FLOAT_LITERAL", "BOOL_LITERAL", "CHAR_LITERAL",
"STRING_LITERAL", "TEXT_BLOCK", "NULL_LITERAL", "LPAREN", "RPAREN",
"LBRACE", "RBRACE", "LBRACK", "RBRACK", "SEMI", "COMMA", "DOT",
"ASSIGN", "GT", "LT", "BANG", "TILDE", "QUESTION", "COLON",
"EQUAL", "LE", "GE", "NOTEQUAL", "AND", "OR", "INC", "DEC",
"ADD", "SUB", "MUL", "DIV", "BITAND", "BITOR", "CARET", "MOD",
"ADD_ASSIGN", "SUB_ASSIGN", "MUL_ASSIGN", "DIV_ASSIGN", "AND_ASSIGN",
"OR_ASSIGN", "XOR_ASSIGN", "MOD_ASSIGN", "LSHIFT_ASSIGN", "RSHIFT_ASSIGN",
"URSHIFT_ASSIGN", "ARROW", "COLONCOLON", "AT", "ELLIPSIS", "WS",
"COMMENT", "LINE_COMMENT", "IDENTIFIER" ]
ruleNames = [ "ABSTRACT", "ASSERT", "BOOLEAN", "BREAK", "BYTE", "CASE",
"CATCH", "CHAR", "CLASS", "CONST", "CONTINUE", "DEFAULT",
"DO", "DOUBLE", "ELSE", "ENUM", "EXTENDS", "FINAL", "FINALLY",
"FLOAT", "FOR", "IF", "GOTO", "IMPLEMENTS", "IMPORT",
"INSTANCEOF", "INT", "INTERFACE", "LONG", "NATIVE", "NEW",
"PACKAGE", "PRIVATE", "PROTECTED", "PUBLIC", "RETURN",
"SHORT", "STATIC", "STRICTFP", "SUPER", "SWITCH", "SYNCHRONIZED",
"THIS", "THROW", "THROWS", "TRANSIENT", "TRY", "VOID",
"VOLATILE", "WHILE", "MODULE", "OPEN", "REQUIRES", "EXPORTS",
"OPENS", "TO", "USES", "PROVIDES", "WITH", "TRANSITIVE",
"VAR", "YIELD", "RECORD", "SEALED", "PERMITS", "NON_SEALED",
"DECIMAL_LITERAL", "HEX_LITERAL", "OCT_LITERAL", "BINARY_LITERAL",
"FLOAT_LITERAL", "HEX_FLOAT_LITERAL", "BOOL_LITERAL",
"CHAR_LITERAL", "STRING_LITERAL", "TEXT_BLOCK", "NULL_LITERAL",
"LPAREN", "RPAREN", "LBRACE", "RBRACE", "LBRACK", "RBRACK",
"SEMI", "COMMA", "DOT", "ASSIGN", "GT", "LT", "BANG",
"TILDE", "QUESTION", "COLON", "EQUAL", "LE", "GE", "NOTEQUAL",
"AND", "OR", "INC", "DEC", "ADD", "SUB", "MUL", "DIV",
"BITAND", "BITOR", "CARET", "MOD", "ADD_ASSIGN", "SUB_ASSIGN",
"MUL_ASSIGN", "DIV_ASSIGN", "AND_ASSIGN", "OR_ASSIGN",
"XOR_ASSIGN", "MOD_ASSIGN", "LSHIFT_ASSIGN", "RSHIFT_ASSIGN",
"URSHIFT_ASSIGN", "ARROW", "COLONCOLON", "AT", "ELLIPSIS",
"WS", "COMMENT", "LINE_COMMENT", "IDENTIFIER", "ExponentPart",
"EscapeSequence", "HexDigits", "HexDigit", "Digits", "LetterOrDigit",
"Letter" ]
grammarFileName = "JavaLexer.g4"
def __init__(self, input=None, output:TextIO = sys.stdout):
super().__init__(input, output)
self.checkVersion("4.9.3")
self._interp = LexerATNSimulator(self, self.atn, self.decisionsToDFA, PredictionContextCache())
self._actions = None
self._predicates = None
| 63.350806
| 103
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| 47,133
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| 63.43607
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| 0.644021
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| 0
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| null | 0
| 0
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0
| 6
|
7f05baed48c1d11946edde0cfa37feda33a2fed5
| 7,084
|
py
|
Python
|
test-runner/rest_wrappers/generated/e2erestapi/operations/wrapper_operations.py
|
v-greach/iot-sdks-e2e-fx
|
2ceb178c886ced2a639dcd61bf11206a58685509
|
[
"MIT"
] | null | null | null |
test-runner/rest_wrappers/generated/e2erestapi/operations/wrapper_operations.py
|
v-greach/iot-sdks-e2e-fx
|
2ceb178c886ced2a639dcd61bf11206a58685509
|
[
"MIT"
] | null | null | null |
test-runner/rest_wrappers/generated/e2erestapi/operations/wrapper_operations.py
|
v-greach/iot-sdks-e2e-fx
|
2ceb178c886ced2a639dcd61bf11206a58685509
|
[
"MIT"
] | null | null | null |
# coding=utf-8
# --------------------------------------------------------------------------
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is
# regenerated.
# --------------------------------------------------------------------------
from msrest.pipeline import ClientRawResponse
from msrest.exceptions import HttpOperationError
from .. import models
class WrapperOperations(object):
"""WrapperOperations operations.
:param client: Client for service requests.
:param config: Configuration of service client.
:param serializer: An object model serializer.
:param deserializer: An object model deserializer.
"""
models = models
def __init__(self, client, config, serializer, deserializer):
self._client = client
self._serialize = serializer
self._deserialize = deserializer
self.config = config
def cleanup(
self, custom_headers=None, raw=False, **operation_config):
"""verify that the clients have cleaned themselves up completely.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.cleanup.metadata['url']
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
cleanup.metadata = {'url': '/wrapper/cleanup'}
def start_session(
self, custom_headers=None, raw=False, **operation_config):
"""Launch a wrapper, getting ready to test.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.start_session.metadata['url']
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
start_session.metadata = {'url': '/wrapper/session'}
def end_session(
self, custom_headers=None, raw=False, **operation_config):
"""Terminate a wrapper, optionally returning the log.
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.end_session.metadata['url']
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct and send request
request = self._client.get(url, query_parameters)
response = self._client.send(request, header_parameters, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
end_session.metadata = {'url': '/wrapper/session'}
def log_message(
self, msg, custom_headers=None, raw=False, **operation_config):
"""log a message to output.
:param msg:
:type msg: object
:param dict custom_headers: headers that will be added to the request
:param bool raw: returns the direct response alongside the
deserialized response
:param operation_config: :ref:`Operation configuration
overrides<msrest:optionsforoperations>`.
:return: None or ClientRawResponse if raw=true
:rtype: None or ~msrest.pipeline.ClientRawResponse
:raises:
:class:`HttpOperationError<msrest.exceptions.HttpOperationError>`
"""
# Construct URL
url = self.log_message.metadata['url']
# Construct parameters
query_parameters = {}
# Construct headers
header_parameters = {}
header_parameters['Content-Type'] = 'application/json; charset=utf-8'
if custom_headers:
header_parameters.update(custom_headers)
# Construct body
body_content = self._serialize.body(msg, 'object')
# Construct and send request
request = self._client.put(url, query_parameters)
response = self._client.send(
request, header_parameters, body_content, stream=False, **operation_config)
if response.status_code not in [200]:
raise HttpOperationError(self._deserialize, response)
if raw:
client_raw_response = ClientRawResponse(None, response)
return client_raw_response
log_message.metadata = {'url': '/wrapper/message'}
| 37.284211
| 98
| 0.651468
| 718
| 7,084
| 6.284123
| 0.171309
| 0.046099
| 0.035461
| 0.017731
| 0.79344
| 0.79344
| 0.777926
| 0.76906
| 0.759309
| 0.736702
| 0
| 0.003192
| 0.248165
| 7,084
| 189
| 99
| 37.481481
| 0.843973
| 0.390175
| 0
| 0.644737
| 1
| 0
| 0.068013
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.065789
| false
| 0
| 0.039474
| 0
| 0.184211
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
| null | 0
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
|
0
| 6
|
61398f6c3160a02c381cd821efc8cfe2cfbcd28f
| 8,579
|
py
|
Python
|
tests/pybaseball/cache/test_cache.py
|
reddigari/pybaseball
|
2d878cf3505ce0a5e657694ae967d6275dc3c211
|
[
"MIT"
] | 650
|
2017-06-29T20:05:19.000Z
|
2022-03-31T03:27:25.000Z
|
tests/pybaseball/cache/test_cache.py
|
reddigari/pybaseball
|
2d878cf3505ce0a5e657694ae967d6275dc3c211
|
[
"MIT"
] | 216
|
2017-10-21T05:05:08.000Z
|
2022-03-31T04:04:53.000Z
|
tests/pybaseball/cache/test_cache.py
|
reddigari/pybaseball
|
2d878cf3505ce0a5e657694ae967d6275dc3c211
|
[
"MIT"
] | 214
|
2017-07-18T21:40:01.000Z
|
2022-03-29T03:19:55.000Z
|
from datetime import datetime, timedelta
from typing import Callable
from unittest.mock import MagicMock, patch
import pandas as pd
import pytest
from _pytest.monkeypatch import MonkeyPatch
from pybaseball import cache
@pytest.fixture(name="mock_data_1")
def _mock_data_1() -> pd.DataFrame:
return pd.DataFrame([1, 2], columns=['a'])
@pytest.fixture(name='empty_load_mock')
def _empty_load_mock(monkeypatch: MonkeyPatch) -> MagicMock:
load_mock = MagicMock(return_value=None)
monkeypatch.setattr(cache.dataframe_utils, 'load_df', load_mock)
return load_mock
@pytest.fixture(name='load_mock')
def _load_mock(monkeypatch: MonkeyPatch, mock_data_1: pd.DataFrame) -> MagicMock:
load_mock = MagicMock(return_value=mock_data_1)
monkeypatch.setattr(cache.dataframe_utils, 'load_df', load_mock)
return load_mock
@pytest.fixture(name='save_json_mock')
def _save_json_mock(monkeypatch: MonkeyPatch) -> MagicMock:
save_mock = MagicMock()
monkeypatch.setattr(cache.file_utils, 'safe_jsonify', save_mock)
return save_mock
@pytest.fixture(name='save_mock')
def _save_mock(monkeypatch: MonkeyPatch) -> MagicMock:
save_mock = MagicMock()
monkeypatch.setattr(cache.dataframe_utils, 'save_df', save_mock)
return save_mock
def test_cache_enable() -> None:
enable_mock = MagicMock()
with patch('pybaseball.cache.config.enable', enable_mock):
cache.enable()
enable_mock.assert_called_once_with(True)
def test_cache_disable() -> None:
enable_mock = MagicMock()
with patch('pybaseball.cache.config.enable', enable_mock):
cache.disable()
enable_mock.assert_called_once_with(False)
@patch('pybaseball.cache.config.enabled', False)
def test_call_cache_disabled(load_mock: MagicMock, save_mock: MagicMock) -> None:
df_func = MagicMock(return_value=pd.DataFrame([1, 2], columns=['a']))
df_func.__name__ = "df_func"
df_cache = cache.df_cache()
assert not df_cache.cache_config.enabled
wrapper = df_cache.__call__(df_func)
wrapper(*(1, 2), **{'val1': 'a'})
df_func.assert_called_once_with(1, 2, val1='a')
load_mock.assert_not_called()
save_mock.assert_not_called()
@patch('pybaseball.cache.config.enabled', True)
@patch('glob.glob', MagicMock(return_value=['1.cache_record.json']))
@patch('pybaseball.cache.file_utils.load_json', MagicMock(
return_value={
'expires': '3000-01-01',
'func': 'df_func',
'args': [1, 2],
'kwargs': {'val1': 'a'},
'dataframe': 'cachefile.csv'
}
))
def test_call_cache_enabled_loads_cache(
mock_data_1: pd.DataFrame,
load_mock: MagicMock, save_mock: MagicMock, save_json_mock: MagicMock) -> None:
df_func = MagicMock()
df_func.__name__ = "df_func"
df_cache = cache.df_cache()
assert df_cache.cache_config.enabled
wrapper = df_cache.__call__(df_func)
result = wrapper(*(1, 2), **{'val1': 'a'})
load_mock.assert_called_once()
df_func.assert_not_called()
save_mock.assert_not_called()
assert isinstance(result, pd.DataFrame)
pd.testing.assert_frame_equal(result, mock_data_1)
@patch('pybaseball.cache.config.enabled', True)
@patch('glob.glob', MagicMock(return_value=['1.cache_record.json']))
@patch('pybaseball.cache.file_utils.load_json', MagicMock(
return_value={'expires': '2020-01-01', 'filename': 'old_file.csv'}
))
def test_call_cache_ignores_expired(
mock_data_1: pd.DataFrame, load_mock: MagicMock,
save_mock: MagicMock, save_json_mock: MagicMock) -> None:
df_func = MagicMock(return_value=mock_data_1)
df_func.__name__ = "df_func"
df_cache = cache.df_cache()
assert df_cache.cache_config.enabled
wrapper = df_cache.__call__(df_func)
wrapper(*(1, 2), **{'val1': 'a'})
df_func.assert_called_once_with(1, 2, val1='a')
load_mock.assert_not_called()
save_mock.assert_called_once()
pd.testing.assert_frame_equal(mock_data_1, save_mock.call_args[0][0])
@patch('pybaseball.cache.config.enabled', True)
@patch('glob.glob', MagicMock(return_value=[]))
@patch('os.path.exists', MagicMock(return_value=False))
def test_call_cache_gets_uncached_data(
mock_data_1: pd.DataFrame, load_mock: MagicMock,
save_mock: MagicMock, save_json_mock: MagicMock) -> None:
df_func = MagicMock(return_value=mock_data_1)
df_func.__name__ = "df_func" # type: ignore
df_cache = cache.df_cache()
assert df_cache.cache_config.enabled
wrapper = df_cache.__call__(df_func)
wrapper(*(1, 2), **{'val1': 'a'})
df_func.assert_called_once_with(1, 2, val1='a')
load_mock.assert_not_called()
save_mock.assert_called_once()
pd.testing.assert_frame_equal(mock_data_1, save_mock.call_args[0][0])
@patch('pybaseball.cache.config.enabled', True)
def test_call_cache_get_func_data_fails_silently(
mock_data_1: pd.DataFrame, thrower: Callable,
load_mock: MagicMock, save_mock: MagicMock, save_json_mock: MagicMock) -> None:
assert cache.config.enabled
df_func = MagicMock(return_value=mock_data_1)
df_func.__name__ = "df_func"
df_cache = cache.cache.df_cache()
assert df_cache.cache_config.enabled
with patch('pybaseball.cache.func_utils.get_func_name', thrower):
wrapper = df_cache.__call__(df_func)
result = wrapper(*(1, 2), **{'val1': 'a'})
assert isinstance(result, pd.DataFrame)
pd.testing.assert_frame_equal(result, mock_data_1)
load_mock.assert_not_called()
save_mock.assert_not_called()
@patch('pybaseball.cache.config.enabled', True)
def test_call_cache_load_fails_silently(
mock_data_1: pd.DataFrame, thrower: Callable,
load_mock: MagicMock, save_mock: MagicMock, save_json_mock: MagicMock) -> None:
assert cache.config.enabled
df_func = MagicMock(return_value=mock_data_1)
df_func.__name__ = "df_func"
df_cache = cache.cache.df_cache()
assert df_cache.cache_config.enabled
with patch('glob.glob', thrower):
wrapper = df_cache.__call__(df_func)
result = wrapper(*(1, 2), **{'val1': 'a'})
assert isinstance(result, pd.DataFrame)
pd.testing.assert_frame_equal(result, mock_data_1)
load_mock.assert_not_called()
save_mock.assert_called_once()
@patch('pybaseball.cache.config.enabled', True)
@patch('glob.glob', MagicMock(return_value=['1.cache_record.json']))
@patch('pybaseball.cache.file_utils.load_json', MagicMock(
return_value={
'expires': '3000-01-01',
'func': 'df_func',
'args': [1, 2],
'kwargs': {'val1': 'a'},
'dataframe': 'cachefile.csv'
}
))
def test_call_cache_save_fails_silently(
mock_data_1: pd.DataFrame, thrower: Callable,
empty_load_mock: MagicMock, save_mock: MagicMock) -> None:
assert cache.config.enabled
df_func = MagicMock(return_value=mock_data_1)
df_func.__name__ = "df_func"
df_cache = cache.cache.df_cache()
assert df_cache.cache_config.enabled
with patch.object(cache.cache_record.CacheRecord, 'save', thrower):
wrapper = df_cache.__call__(df_func)
result = wrapper(*(1, 2), **{'val1': 'a'})
assert isinstance(result, pd.DataFrame)
pd.testing.assert_frame_equal(result, mock_data_1)
empty_load_mock.assert_called_once()
save_mock.assert_not_called()
def test_purge(remove: MagicMock) -> None:
glob_result = ['1.cache_record.json', '2.cache_record.json']
glob_mock = MagicMock(return_value=glob_result)
mock_cache_record = {'expires': '3000-01-01', 'filename': 'df_cache.parquet'}
mock_load_json = MagicMock(return_value=mock_cache_record)
with patch('glob.glob', glob_mock):
with patch('pybaseball.cache.file_utils.load_json', mock_load_json):
cache.purge()
assert glob_mock.called_once()
assert mock_load_json.call_count == len(glob_result)
assert remove.call_count == len(glob_result)
def test_flush(remove: MagicMock) -> None:
glob_result = ['1.cache_record.json', '2.cache_record.json']
glob_mock = MagicMock(return_value=glob_result)
mock_cache_records = [
{'expires': '2000-01-01', 'filename': 'df_cache.parquet'},
{'expires': '3000-01-01', 'filename': 'df_cache2.parquet'},
]
mock_load_json = MagicMock(side_effect=mock_cache_records)
with patch('glob.glob', glob_mock):
with patch('pybaseball.cache.file_utils.load_json', mock_load_json):
cache.flush()
assert glob_mock.called_once()
assert mock_load_json.call_count == len(glob_result)
remove.assert_called_once()
| 32.744275
| 87
| 0.710689
| 1,180
| 8,579
| 4.79661
| 0.085593
| 0.036042
| 0.033392
| 0.012367
| 0.85318
| 0.790283
| 0.742049
| 0.732155
| 0.717845
| 0.709364
| 0
| 0.016778
| 0.159343
| 8,579
| 261
| 88
| 32.869732
| 0.768026
| 0.001399
| 0
| 0.663212
| 0
| 0
| 0.138704
| 0.058727
| 0
| 0
| 0
| 0
| 0.238342
| 1
| 0.082902
| false
| 0
| 0.036269
| 0.005181
| 0.145078
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
6165e4d41993124cf9265ef76b700400508f5ce3
| 98
|
py
|
Python
|
office365/directory/applications/app_identity.py
|
rikeshtailor/Office365-REST-Python-Client
|
ca7bfa1b22212137bb4e984c0457632163e89a43
|
[
"MIT"
] | 544
|
2016-08-04T17:10:16.000Z
|
2022-03-31T07:17:20.000Z
|
office365/directory/applications/app_identity.py
|
rikeshtailor/Office365-REST-Python-Client
|
ca7bfa1b22212137bb4e984c0457632163e89a43
|
[
"MIT"
] | 438
|
2016-10-11T12:24:22.000Z
|
2022-03-31T19:30:35.000Z
|
office365/directory/applications/app_identity.py
|
rikeshtailor/Office365-REST-Python-Client
|
ca7bfa1b22212137bb4e984c0457632163e89a43
|
[
"MIT"
] | 202
|
2016-08-22T19:29:40.000Z
|
2022-03-30T20:26:15.000Z
|
from office365.runtime.client_value import ClientValue
class AppIdentity(ClientValue):
pass
| 16.333333
| 54
| 0.816327
| 11
| 98
| 7.181818
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.035294
| 0.132653
| 98
| 5
| 55
| 19.6
| 0.894118
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 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
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
61bca8b4fdaa6905a8fdd564488a30200204e734
| 85
|
py
|
Python
|
exercises/strain/strain.py
|
kishankj/python
|
82042de746128127502e109111e6c4e8ab002af6
|
[
"MIT"
] | 1,177
|
2017-06-21T20:24:06.000Z
|
2022-03-29T02:30:55.000Z
|
exercises/strain/strain.py
|
kishankj/python
|
82042de746128127502e109111e6c4e8ab002af6
|
[
"MIT"
] | 1,890
|
2017-06-18T20:06:10.000Z
|
2022-03-31T18:35:51.000Z
|
exercises/strain/strain.py
|
kishankj/python
|
82042de746128127502e109111e6c4e8ab002af6
|
[
"MIT"
] | 1,095
|
2017-06-26T23:06:19.000Z
|
2022-03-29T03:25:38.000Z
|
def keep(sequence, predicate):
pass
def discard(sequence, predicate):
pass
| 12.142857
| 33
| 0.694118
| 10
| 85
| 5.9
| 0.6
| 0.576271
| 0.711864
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.211765
| 85
| 6
| 34
| 14.166667
| 0.880597
| 0
| 0
| 0.5
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0.5
| 0
| 0
| 0.5
| 0
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| 0
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| null | 1
| 1
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| null | 0
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| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
4efc3ffa7d0a18d3700829d9d18f21f1ed609cd7
| 6
|
py
|
Python
|
Random-Programs/dev/games/terminal/ratX.py
|
naumoff0/Archive
|
d4ad2da89abb1576dd5a7c72ded6bf9b45c3f610
|
[
"MIT"
] | null | null | null |
Random-Programs/dev/games/terminal/ratX.py
|
naumoff0/Archive
|
d4ad2da89abb1576dd5a7c72ded6bf9b45c3f610
|
[
"MIT"
] | null | null | null |
Random-Programs/dev/games/terminal/ratX.py
|
naumoff0/Archive
|
d4ad2da89abb1576dd5a7c72ded6bf9b45c3f610
|
[
"MIT"
] | null | null | null |
M`!j
| 6
| 6
| 0.333333
| 4
| 6
| 1
| 1
| 0
| 0
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| 0
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| 6
| 1
| 6
| 6
| 0.333333
| 0
| 0
| 0
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| null | null | 0
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| null | null | 0
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| 1
| null | 0
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| null | 0
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|
0
| 6
|
f62743e15982298d97e720a606fb0dff455038c5
| 8,607
|
py
|
Python
|
test/test_rigctl.py
|
Marzona/rig-remote
|
05957aae40e80e5250fd6c10a514283a35ff56a9
|
[
"MIT"
] | 19
|
2016-01-29T20:16:18.000Z
|
2022-01-13T07:01:30.000Z
|
test/test_rigctl.py
|
Marzona/rig-remote
|
05957aae40e80e5250fd6c10a514283a35ff56a9
|
[
"MIT"
] | 93
|
2016-01-17T18:01:33.000Z
|
2022-01-12T16:46:04.000Z
|
test/test_rigctl.py
|
Marzona/rig-remote
|
05957aae40e80e5250fd6c10a514283a35ff56a9
|
[
"MIT"
] | 6
|
2016-02-15T21:04:47.000Z
|
2022-01-12T16:46:23.000Z
|
#!/usr/bin/env python
# import modules
import pytest
import socket
import telnetlib
from mock import patch, MagicMock
from rig_remote.rigctl import RigCtl
from rig_remote.constants import (
DEFAULT_CONFIG,
ALLOWED_VFO_COMMANDS,
ALLOWED_SPLIT_MODES,
RESET_CMD_DICT,
)
testdata = [("127.0.0.1", "80"),
("test", "80"),
("127.0.0.1","test"),
("test", "test")]
@pytest.fixture
def fake_target():
fake_target= {}
fake_target["hostname"] = "127.0.0.1"
fake_target["port"] = 80
fake_target["rig_number"] = 1
return fake_target
def test_rig_control():
with pytest.raises(TypeError):
rigctl = RigCtl("test")
@pytest.mark.parametrize("hostname, port", testdata)
def test_set_frequency(hostname, port, fake_target):
DEFAULT_CONFIG["hostname"] = "127.0.0.1"
DEFAULT_CONFIG["port"] = "80"
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl.set_frequency("1000000")
rigctl._request.assert_called_once_with('F 1000000', None)
def test_request_timeout(fake_target):
telnetlib.Telnet = MagicMock(side_effect=socket.timeout)
rigctl = RigCtl(fake_target)
with pytest.raises(socket.timeout):
rigctl.get_frequency()
def test_request_socket_error(fake_target):
telnetlib.Telnet = MagicMock(side_effect=socket.error)
rigctl = RigCtl(fake_target)
with pytest.raises(socket.error):
rigctl.get_frequency()
def test_get_frequency(fake_target):
DEFAULT_CONFIG["hostname"] = "127.0.0.1"
DEFAULT_CONFIG["port"] = "80"
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "f"
rigctl.get_frequency()
rigctl._request == "f"
def test_get_frequency_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_frequency()
def test_get_level(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "22"
assert(rigctl.get_level() == "22")
def test_get_level_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_level()
def test_set_bad_frequency(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_frequency("test")
def test_set_bad_mode(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_mode(5)
def test_get_mode(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "m"
assert(rigctl.get_mode() == "m")
def test_get_mode_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_mode()
def test_get_split_mode(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "m"
assert(rigctl.get_split_mode() == "m")
def test_get_split_mode_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_split_mode()
def test_get_vfo_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_vfo()
def test_get_vfo(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "22"
assert(rigctl.get_vfo() == "22")
def test_get_rit_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_rit()
def test_get_rit(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "22"
assert(rigctl.get_rit() == "22")
def test_get_xit_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_xit()
def test_get_xit(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "22"
assert(rigctl.get_xit() == "22")
def test_get_split_freq_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "22"
with pytest.raises(ValueError):
rigctl.get_split_freq()
def test_get_split_freq(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
assert(rigctl.get_split_freq() == 22)
def test_get_func_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_func()
def test_get_func(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "22"
assert(rigctl.get_func() == "22")
def test_get_parm_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
with pytest.raises(ValueError):
rigctl.get_parm()
def test_get_parm(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "22"
assert(rigctl.get_parm() == "22")
def test_get_antenna_error(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = "22"
with pytest.raises(ValueError):
rigctl.get_antenna()
def test_get_antenna(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl._request.return_value = 22
assert(rigctl.get_antenna() == 22)
def test_set_mode(fake_target):
rigctl = RigCtl(fake_target)
rigctl._request = MagicMock()
rigctl.set_mode("AM")
rigctl._request.assert_called_once_with('M AM', None)
def test_rig_reset(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.rig_reset("testreset")
def test_set_antenna(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_antenna("testreset")
def test_xit(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_xit(22)
def test_vfo_1(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_vfo(22)
def test_vfo_2(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_vfo("testvfo")
def test_split_mode_1(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_split_mode(22)
def test_split_mode_2(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_split_mode("testvfo")
def test_split_freq(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_split_freq("testvfo")
def test_rit(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_rit("testrit")
def test_parm_1(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_parm(22)
def test_parm_2(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_parm("testparm")
def test_mode_1(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_mode(22)
def test_mode_2(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_mode("testmode")
def test_func_1(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_func(22)
def test_func_2(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_func("testvfo")
def test_antenna(fake_target):
rigctl = RigCtl(fake_target)
with pytest.raises(ValueError):
rigctl.set_antenna("testparm")
| 29.176271
| 62
| 0.693157
| 1,100
| 8,607
| 5.11
| 0.075455
| 0.16723
| 0.182174
| 0.172211
| 0.777086
| 0.756093
| 0.73599
| 0.731898
| 0.69525
| 0.694183
| 0
| 0.019061
| 0.195422
| 8,607
| 294
| 63
| 29.27551
| 0.792635
| 0.004066
| 0
| 0.516393
| 0
| 0
| 0.031505
| 0
| 0
| 0
| 0
| 0
| 0.04918
| 1
| 0.188525
| false
| 0
| 0.02459
| 0
| 0.217213
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 1
| 1
| 0
| 1
| 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
| 6
|
f672ab6ea27110ccbfc5826e036db42205f67f7c
| 29
|
py
|
Python
|
utils/models/other/deeplab/__init__.py
|
bhklab/ptl-oar-segmentation
|
354c3ee7f042a025f74e210a7b8462beac9b727d
|
[
"Apache-2.0"
] | 3
|
2022-01-18T19:25:46.000Z
|
2022-02-05T18:53:24.000Z
|
utils/models/other/deeplab/__init__.py
|
bhklab/ptl-oar-segmentation
|
354c3ee7f042a025f74e210a7b8462beac9b727d
|
[
"Apache-2.0"
] | null | null | null |
utils/models/other/deeplab/__init__.py
|
bhklab/ptl-oar-segmentation
|
354c3ee7f042a025f74e210a7b8462beac9b727d
|
[
"Apache-2.0"
] | null | null | null |
from .model import Deeplabv3
| 14.5
| 28
| 0.827586
| 4
| 29
| 6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.04
| 0.137931
| 29
| 1
| 29
| 29
| 0.92
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
9cd06829cbb81ccaade6a8d9b4f6a12f94bb7adf
| 75
|
py
|
Python
|
ppq/api/__init__.py
|
xiguadong/ppq
|
6c71adb3c2a8ca95967f101724b5e4b3e6f761ff
|
[
"Apache-2.0"
] | 100
|
2021-12-31T09:34:06.000Z
|
2022-03-25T02:54:51.000Z
|
ppq/api/__init__.py
|
xiguadong/ppq
|
6c71adb3c2a8ca95967f101724b5e4b3e6f761ff
|
[
"Apache-2.0"
] | 12
|
2021-12-31T10:28:15.000Z
|
2022-03-31T07:08:44.000Z
|
ppq/api/__init__.py
|
xiguadong/ppq
|
6c71adb3c2a8ca95967f101724b5e4b3e6f761ff
|
[
"Apache-2.0"
] | 21
|
2021-12-31T09:51:02.000Z
|
2022-03-30T12:21:55.000Z
|
from .setting import *
from .fsys import *
from .interface import *
| 18.75
| 24
| 0.666667
| 9
| 75
| 5.555556
| 0.555556
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.253333
| 75
| 3
| 25
| 25
| 0.892857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
1445240ba7f99d3345820b1ba9963e8dc4f358e1
| 9,011
|
py
|
Python
|
cogs/error.py
|
Kumarozh/Modration_bot
|
1d99ed22a2952aa0ec2f4dee2238928bad3fdc96
|
[
"MIT"
] | null | null | null |
cogs/error.py
|
Kumarozh/Modration_bot
|
1d99ed22a2952aa0ec2f4dee2238928bad3fdc96
|
[
"MIT"
] | null | null | null |
cogs/error.py
|
Kumarozh/Modration_bot
|
1d99ed22a2952aa0ec2f4dee2238928bad3fdc96
|
[
"MIT"
] | null | null | null |
import discord
from discord.ext import commands
from discord import Member,Embed
class error(commands.Cog):
def __init__(self,client):
self.client=client
self._last_member = None
@commands.Cog.listener()
async def on_command_error(self, ctx, error):
async with ctx.typing():
if isinstance(error, commands.NoPrivateMessage):
error3_embed=Embed(title="ERROR", description=f"THIS IS A **DM** {ctx.author.mention} TRY THIS COMMAND ON A **SERVER**!", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.CommandOnCooldown):
error3_embed=Embed(title="ERROR", description=f"TRY AGAIN IN **{error.retry_after:.2f}**s", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.MissingPermissions):
error3_embed=Embed(title="ERROR", description="**YOU** DONT HAVE PERMISSION", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.BotMissingPermissions):
error3_embed=Embed(title="ERROR", description="**I** DONT HAVE PERMISSION", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.MissingRequiredArgument):
error3_embed=Embed(title="ERROR", description="YOU ARE MISSIONG **REQUIRED ARGUMENT** USE **HELP** COMMAND!", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.MemberNotFound):
error3_embed=Embed(title="ERROR", description=f"PLS ENTER A TRUE **MEMBER**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.ChannelNotFound):
error3_embed=Embed(title="ERROR", description=f"PLS ENTER A TRUE **CHANNEL**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.EmojiNotFound):
error3_embed=Embed(title="ERROR", description=f"PLS ENTER A TRUE **EMOJI**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.ChannelNotReadable):
error3_embed=Embed(title="ERROR", description=f"I DON'T HAVE PERMISSIONS TO **READ THIS CHANNEL**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.GuildNotFound):
error3_embed=Embed(title="ERROR", description=f"I CAN'T FIND THIS **GUILD**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.BadColourArgument):
error3_embed=Embed(title="ERROR", description=f"I CAN'T FIND THIS **COLOR**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.UserNotFound):
error3_embed=Embed(title="ERROR", description="ENTER TRUE **USER**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.RoleNotFound):
error3_embed=Embed(title="ERROR", description="ENTER TRUE **ROLE**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.MessageNotFound):
error3_embed=Embed(title="ERROR", description="ENTER TRUE **MESSAGE**", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
elif isinstance(error, commands.BadArgument):
error3_embed=Embed(title="ERROR", description="ENTER **TRUE** ARGUMENT", colour=0xff0000)
error3_embed.set_thumbnail(url='https://images.emojiterra.com/google/android-11/512px/274c.png')
error3_embed.set_footer(text=ctx.author.name, icon_url=ctx.author.avatar_url)
error3_embed.set_author(name=self.client.user.name, icon_url=self.client.user.avatar_url)
await ctx.channel.send(embed=error3_embed, delete_after=10)
def setup(client):
client.add_cog(error(client))
| 88.343137
| 154
| 0.676839
| 1,163
| 9,011
| 5.067928
| 0.097163
| 0.139973
| 0.106888
| 0.053444
| 0.881235
| 0.881235
| 0.874958
| 0.84849
| 0.810655
| 0.810655
| 0
| 0.042027
| 0.205194
| 9,011
| 102
| 155
| 88.343137
| 0.780927
| 0
| 0
| 0.588235
| 0
| 0.009804
| 0.166223
| 0.003107
| 0
| 0
| 0.013316
| 0
| 0
| 1
| 0.019608
| false
| 0
| 0.029412
| 0
| 0.058824
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
144712eeed35ecaba7662db6d5f36fa1bb5358e7
| 89
|
py
|
Python
|
test.py
|
andrscyv/fast_youtube_search
|
7d1cfc51dee9b716c2e76a9b9fcc806661b89cba
|
[
"MIT"
] | 7
|
2020-06-28T21:09:57.000Z
|
2021-09-01T04:51:12.000Z
|
test.py
|
andrscyv/fast_youtube_search
|
7d1cfc51dee9b716c2e76a9b9fcc806661b89cba
|
[
"MIT"
] | null | null | null |
test.py
|
andrscyv/fast_youtube_search
|
7d1cfc51dee9b716c2e76a9b9fcc806661b89cba
|
[
"MIT"
] | 2
|
2020-10-07T17:43:21.000Z
|
2021-12-22T03:35:09.000Z
|
from fast_youtube_search import search_youtube
print(search_youtube(['jorja', 'smith']))
| 29.666667
| 46
| 0.808989
| 12
| 89
| 5.666667
| 0.666667
| 0.382353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.067416
| 89
| 3
| 47
| 29.666667
| 0.819277
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 6
|
145da4b1765a08ced445b8f9431552112809cc5f
| 37,799
|
py
|
Python
|
scale/data/test/test_views.py
|
kaydoh/scale
|
1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee
|
[
"Apache-2.0"
] | 121
|
2015-11-18T18:15:33.000Z
|
2022-03-10T01:55:00.000Z
|
scale/data/test/test_views.py
|
kaydoh/scale
|
1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee
|
[
"Apache-2.0"
] | 1,415
|
2015-12-23T23:36:04.000Z
|
2022-01-07T14:10:09.000Z
|
scale/data/test/test_views.py
|
kaydoh/scale
|
1b6a3b879ffe83e10d3b9d9074835a4c3bf476ee
|
[
"Apache-2.0"
] | 66
|
2015-12-03T20:38:56.000Z
|
2020-07-27T15:28:11.000Z
|
""" Tests dataset views methods """
from __future__ import unicode_literals
from __future__ import absolute_import
import copy
import datetime
import json
import django
from django.utils.timezone import now
from rest_framework import status
from rest_framework.test import APITestCase
from data.data.json.data_v6 import DataV6
from data.dataset.json.dataset_v6 import DataSetDefinitionV6
from util import rest
from data.models import DataSet
import data.test.utils as dataset_test_utils
import storage.test.utils as storage_utils
from storage.models import Workspace
"""Tests the v6/datasets/ endpoint"""
class TestDatasetViews(APITestCase):
api = 'v6'
def setUp(self):
django.setup()
rest.login_client(self.client, is_staff=True)
# create a workspace and files
self.workspace = storage_utils.create_workspace(name='Test Workspace', is_active=True)
self.file1 = storage_utils.create_file(file_name='input_e.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.file2 = storage_utils.create_file(file_name='input_f.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.file3 = storage_utils.create_file(file_name='input_f2.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.file4 = storage_utils.create_file(file_name='input_eb.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.file5 = storage_utils.create_file(file_name='input_fb.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.file6 = storage_utils.create_file(file_name='input_fb2.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
today = now()
yesterday = today - datetime.timedelta(days=1)
tomorrow = today + datetime.timedelta(days=1)
self.dataset = dataset_test_utils.create_dataset(definition=copy.deepcopy(dataset_test_utils.DATASET_DEFINITION),
title="Test Dataset 1", description="Key Test Dataset Number one")
DataSet.objects.filter(pk=self.dataset.pk).update(created=yesterday)
self.dataset2 = dataset_test_utils.create_dataset(title="Test Dataset 2", description="Test Dataset Number two")
DataSet.objects.filter(pk=self.dataset2.pk).update(created=tomorrow)
# create dataset members
data1 = copy.deepcopy(dataset_test_utils.DATA_DEFINITION)
data1['files']['input_e'] = [self.file1.id]
data1['files']['input_f'] = [self.file2.id, self.file3.id]
self.member1_1 = dataset_test_utils.create_dataset_members(dataset=self.dataset, data_list=[data1])[0]
data2 = copy.deepcopy(dataset_test_utils.DATA_DEFINITION)
data2['files']['input_e'] = [self.file4.id]
data2['files']['input_f'] = [self.file5.id, self.file6.id]
self.member1_1_2 = dataset_test_utils.create_dataset_members(dataset=self.dataset, data_list=[data2])
self.member2_1 = dataset_test_utils.create_dataset_members(dataset=self.dataset2)[0]
self.member2_2 = dataset_test_utils.create_dataset_members(dataset=self.dataset2)[0]
def test_successful(self):
"""Tests successfully calling the v6/datasets/ view.
"""
url = '/%s/datasets/' % self.api
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Test response contains specific dataset
result = json.loads(response.content)
self.assertEqual(len(result['results']), 2)
for entry in result['results']:
expected = None
expectedFiles = 0
if entry['id'] == self.dataset.id:
expected = self.dataset
expectedFiles = 6
elif entry['id'] == self.dataset2.id:
expected = self.dataset2
expectedFiles = 0
else:
self.fail('Found unexpected result: %s' % entry['id'])
self.assertEqual(entry['title'], expected.title)
self.assertEqual(entry['files'], expectedFiles)
def test_dataset_time_successful(self):
"""Tests successfully calling the v6/datasets api with time filters
"""
yesterday = now().date() - datetime.timedelta(days=1)
yesterday = yesterday.isoformat() + 'T00:00:00Z'
today = now().date()
today = today.isoformat() + 'T00:00:00Z'
tomorrow = now().date() + datetime.timedelta(days=1)
tomorrow = tomorrow.isoformat() + 'T00:00:00Z'
url = '/%s/datasets/?started=%s' % (self.api, today)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Verify one result
result = json.loads(response.content)
self.assertEqual(len(result['results']), 1)
url = '/%s/datasets/?ended=%s' % (self.api, today)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Verify one result
result = json.loads(response.content)
self.assertEqual(len(result['results']), 1)
def test_dataset_id_successful(self):
"""Tests successfully calling the v6/datasets/?id= api call
"""
url = '/%s/datasets/?id=%s' % (self.api, self.dataset.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Verify one result
result = json.loads(response.content)
self.assertEqual(len(result['results']), 1)
url = '/%s/datasets/?id=%s&id=%s' % (self.api, self.dataset.id, self.dataset2.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Verify two results
result = json.loads(response.content)
self.assertEqual(len(result['results']), 2)
def test_dataset_keyword_successful(self):
"""Tests successfully calling the v6/datasets/?keyword= api call
"""
url = '/%s/datasets/?keyword=%s' % (self.api, 'key')
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Verify one result
result = json.loads(response.content)
self.assertEqual(len(result['results']), 1)
url = '/%s/datasets/?keyword=%s&keyword=%s' % (self.api, 'one', 'two')
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Verify 2 results
result = json.loads(response.content)
self.assertEqual(len(result['results']), 2)
def test_order_by(self):
"""Tests successfully calling the datasets view with sorting."""
url = '/%s/datasets/?order=-id' % self.api
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Verify 2 results
result = json.loads(response.content)
self.assertEqual(len(result['results']), 2)
self.assertEqual(result['results'][0]['id'], self.dataset2.id)
"""Tests the v6/datasets POST calls """
class TestDataSetPostView(APITestCase):
"""Tests the v6/dataset/ POST API call"""
api = 'v6'
def setUp(self):
django.setup()
rest.login_client(self.client, is_staff=True)
def test_invalid_definition(self):
"""Tests successfully calling POST with an invalid definition."""
json_data = {}
url = '/%s/datasets/' % self.api
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST, response.content)
definition = copy.deepcopy(dataset_test_utils.DATASET_DEFINITION)
del definition['global_data']['json']['input_c']
json_data = {
'title': 'My Dataset',
'description': 'A test dataset',
'definition': definition,
}
url = '/%s/datasets/' % self.api
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST, response.content)
def test_add_dataset(self):
"""Tests adding a new dataset"""
url = '/%s/datasets/' % self.api
json_data = {
'title': 'My Dataset',
'description': 'A test dataset',
'definition': copy.deepcopy(dataset_test_utils.DATASET_DEFINITION),
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_201_CREATED, response.content)
result = json.loads(response.content)
new_dataset_id = result['id']
self.assertTrue('/%s/datasets/%d/' % (self.api, new_dataset_id) in response['location'])
self.assertEqual(result['title'], json_data['title'])
self.assertEqual(result['description'], json_data['description'])
# create another dataset
json_data_2 = {
'title': 'My Dataset 2',
'description': 'Another test dataset',
'definition': copy.deepcopy(dataset_test_utils.DATASET_DEFINITION),
}
response = self.client.generic('POST', url, json.dumps(json_data_2), 'application/json')
self.assertEqual(response.status_code, status.HTTP_201_CREATED, response.content)
result = json.loads(response.content)
new_dataset_id = result['id']
self.assertTrue('/%s/datasets/%d/' % (self.api, new_dataset_id) in response['location'])
self.assertEqual(result['title'], json_data_2['title'])
self.assertEqual(result['description'], json_data_2['description'])
def test_create_dataset_with_members(self):
"""Tests creating a dataset along with a bunch of members"""
title = 'Test Dataset'
description = 'Test DataSet description'
file1 = storage_utils.create_file()
file2 = storage_utils.create_file()
file3 = storage_utils.create_file()
file4 = storage_utils.create_file()
# call test
parameters = {'version': '6',
'files': [
{'name': 'input_a',
'media_types': ['application/json'],
'required': True},
{'name': 'input_b',
'media_types': ['application/json'],
'multiple': True,
'required': True},
{'name': 'input_c',
'media_types': ['application/json'],
'required': True}
],
'json': []}
definition = {'version': '6', 'parameters': parameters}
json_data = {
'title': title,
'description': description,
'definition': definition,
'data': {
'version': '7',
'files': {
'input_a': [file1.id],
'input_b': [file2.id, file3.id],
'input_c': [file4.id],
},
'json': {}
},
}
url = '/%s/datasets/' % self.api
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_201_CREATED, response.content)
result = json.loads(response.content)
new_dataset_id = result['id']
self.assertTrue('/%s/datasets/%d/' % (self.api, new_dataset_id) in response['location'])
self.assertTrue(len(result['definition']['parameters']['files']), 3)
self.assertTrue(len(result['files']), 4)
"""Tests the v6/datasets/<dataset_id> endpoint"""
class TestDatasetDetailsView(APITestCase):
api = 'v6'
def setUp(self):
django.setup()
rest.login_client(self.client, is_staff=True)
# Create workspace
self.workspace = Workspace.objects.create(name='Test Workspace', is_active=True, created=now(),
last_modified=now())
# Create files
self.country = storage_utils.create_country()
self.src_file_a = storage_utils.create_file(file_name='input_a.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path', countries=[self.country],
workspace=self.workspace)
self.src_file_b = storage_utils.create_file(file_name='input_b.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_c = storage_utils.create_file(file_name='input_c.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_b2 = storage_utils.create_file(file_name='input_b2.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_e = storage_utils.create_file(file_name='input_e.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_f = storage_utils.create_file(file_name='input_f.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
for i in range(0,500):
storage_utils.create_file(source_collection='12345')
for i in range(0,500):
storage_utils.create_file(source_collection='123456')
# Create datasets
parameters = {'version': '6',
'files': [
{'name': 'input_a',
'media_types': ['application/json'],
'required': True}
],
'json': []}
definition = {'version': '6', 'parameters': parameters}
self.dataset = dataset_test_utils.create_dataset( title="Test Dataset 1",
description="Test Dataset Number 1",
definition=definition)
parameters2 = {'version': '6',
'files': [
{'name': 'input_b',
'media_types': ['application/json'],
'required': True,
'multiple': True},
{'name': 'input_c',
'media_types': ['application/json'],
'required': False}
],
'json': []}
definition2 = {'version': '6', 'parameters': parameters2}
self.dataset2 = dataset_test_utils.create_dataset(title="Test Dataset 2",
description="Test Dataset Number 2",
definition=definition2)
# Create members
data_dict = {
'version': '6',
'files': {'input_a': [self.src_file_a.id]},
'json': {}
}
data = DataV6(data=data_dict).get_dict()
self.member_a = dataset_test_utils.create_dataset_members(dataset=self.dataset,
data_list=[data])[0]
data_dict = {
'version': '6',
'files': {'input_b': [self.src_file_b.id, self.src_file_b2.id]},
'json': {}
}
data2 = DataV6(data=data_dict).get_dict()
self.member_b = dataset_test_utils.create_dataset_members(dataset=self.dataset2,
data_list=[data2])[0]
data_dict = {
'version': '6',
'files': {'input_b': [self.src_file_b.id, self.src_file_b2.id], 'input_c': [self.src_file_c.id]},
'json': {}
}
data3 = DataV6(data=data_dict).get_dict()
self.member_bc = dataset_test_utils.create_dataset_members(dataset=self.dataset2,
data_list=[data3])[0]
def test_dataset_details_successful(self):
"""Tests successfully calling the v6/datasets/<dataset_id>/ view.
"""
url = '/%s/datasets/%d/' % (self.api, self.dataset.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Check response for dataset details
result = json.loads(response.content)
self.assertEqual(result['id'], self.dataset.id)
self.assertEqual(result['title'], self.dataset.title)
self.assertEqual(result['description'], self.dataset.description)
dsdict = DataSetDefinitionV6(definition=self.dataset.definition).get_dict()
del dsdict['version']
self.assertDictEqual(result['definition'], dsdict)
self.assertEqual(len(result['files']), 1)
self.assertIsNotNone(result['files'][0]['scale_file']["countries"])
url = '/%s/datasets/%d/' % (self.api, self.dataset2.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Check response for dataset details
result = json.loads(response.content)
self.assertEqual(result['id'], self.dataset2.id)
self.assertEqual(result['title'], self.dataset2.title)
self.assertEqual(result['description'], self.dataset2.description)
self.maxDiff = None
dsdict = DataSetDefinitionV6(definition=self.dataset2.definition).get_dict()
del dsdict['version']
self.assertDictEqual(result['definition'], self.dataset2.definition)
self.assertEqual(len(result['files']), 3)
def test_add_dataset_member(self):
"""Tests adding a new dataset member"""
url = '/%s/datasets/%d/' % (self.api, self.dataset.id)
data_dict = {
'version': '6',
'files': {'input_a': [self.src_file_a.id]},
'json': {}
}
json_data = {
'data': [data_dict],
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_201_CREATED, response.content)
result = json.loads(response.content)
self.assertEqual(len(result), 1)
def test_add_filter_dataset_members(self):
"""Tests adding new dataset members based on a filter"""
url = '/%s/datasets/%d/' % (self.api, self.dataset.id)
template = {
'version': '6',
'files': {'input_a': 'FILE_VALUE'},
'json': {}
}
json_data = {
'data_template': template,
'source_collection': '12345'
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_201_CREATED, response.content)
result = json.loads(response.content)
self.assertEqual(len(result), 500)
json_data = {
'data_template': template,
'source_collection': ['12345', '123456']
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_201_CREATED, response.content)
result = json.loads(response.content)
self.assertEqual(len(result), 1000)
def test_add_filter_dataset_members_dry_run(self):
"""Tests adding new dataset members based on a filter"""
url = '/%s/datasets/%d/' % (self.api, self.dataset.id)
template = {
'version': '6',
'files': {'input_a': 'FILE_VALUE'},
'json': {}
}
json_data = {
'data_template': template,
'source_collection': '12345',
'dry_run': True
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
result = json.loads(response.content)
self.assertEqual(len(result), 500)
def test_add_invalid_dataset_member(self):
"""Tests adding an invalid new dataset member"""
url = '/%s/datasets/%d/' % (self.api, self.dataset.id)
data_dict = {
'version': '6',
'files': {'input_b': [self.src_file_a.id]},
'json': {}
}
json_data = {
'data': [data_dict],
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST, response.content)
class TestDataSetValidationView(APITestCase):
api = 'v6'
def setUp(self):
django.setup()
rest.login_client(self.client, is_staff=True)
def test_validate_successful(self):
"""Tests successfully validating a new dataset using the v6/datasets/validation API
"""
url = '/%s/datasets/validation/' % self.api
json_data = {
'title': 'Test Dataset',
'description': 'My Test Dataset',
'definition': dataset_test_utils.DATASET_DEFINITION,
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
results = json.loads(response.content)
self.assertTrue(results['is_valid'])
self.assertEqual(len(results['warnings']), 0)
self.assertEqual(len(results['errors']), 0)
def test_validate_missing_definition(self):
url = '/%s/datasets/validation/' % self.api
json_data = {
'title': 'Test Dataset',
'description': 'My Test Dataset',
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST, response.content)
results = json.loads(response.content)
self.assertEqual(results['detail'], "Missing required parameter: \"definition\"")
def test_invalid_definition(self):
"""Validates an invalid dataset definition
"""
url = '/%s/datasets/validation/' % self.api
json_data = {
'title': 'Test Dataset',
'description': 'My Test Dataset',
'definition': {
'version': '6',
'parameters': [
{
'name': 'global-param',
},
{
'name': 'member-param',
},
],
},
}
response = self.client.generic('POST', url, json.dumps(json_data), 'application/json')
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
results = json.loads(response.content)
self.assertFalse(results['is_valid'])
self.assertEqual(len(results['errors']), 1)
self.assertEqual(results['errors'][0]['name'], 'INVALID_DATASET_DEFINITION')
"""Tests the v6/datasets/%d/members/ endpoint"""
class TestDatasetMembersView(APITestCase):
api = 'v6'
def setUp(self):
django.setup()
rest.login_client(self.client, is_staff=True)
# Create workspace
self.workspace = Workspace.objects.create(name='Test Workspace', is_active=True, created=now(),
last_modified=now())
# Create files
self.src_file_a = storage_utils.create_file(file_name='input_a.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_b = storage_utils.create_file(file_name='input_b.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_c = storage_utils.create_file(file_name='input_c.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_b2 = storage_utils.create_file(file_name='input_b2.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_e = storage_utils.create_file(file_name='input_e.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_f = storage_utils.create_file(file_name='input_f.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
# Create datasets
parameters = {'version': '6',
'files': [
{'name': 'input_a',
'media_types': ['application/json'],
'required': True}
],
'json': []}
definition = {'version': '6', 'parameters': parameters}
self.dataset = dataset_test_utils.create_dataset( title="Test Dataset 1",
description="Test Dataset Number 1",
definition=definition)
parameters2 = {'version': '6',
'files': [
{'name': 'input_b',
'media_types': ['application/json'],
'required': True,
'multiple': True},
{'name': 'input_c',
'media_types': ['application/json'],
'required': False}
],
'json': []}
definition2 = {'version': '6', 'parameters': parameters2}
self.dataset2 = dataset_test_utils.create_dataset(title="Test Dataset 2",
description="Test Dataset Number 2",
definition=definition2)
# Create members
data_dict = {
'version': '6',
'files': {'input_a': [self.src_file_a.id]},
'json': {}
}
data = DataV6(data=data_dict).get_dict()
self.member_a = dataset_test_utils.create_dataset_members(dataset=self.dataset,
data_list=[data])[0]
data_dict = {
'version': '6',
'files': {'input_b': [self.src_file_b.id, self.src_file_b2.id]},
'json': {}
}
data2 = DataV6(data=data_dict).get_dict()
self.member_b = dataset_test_utils.create_dataset_members(dataset=self.dataset2,
data_list=[data2])[0]
data_dict = {
'version': '6',
'files': {'input_b': [self.src_file_b.id, self.src_file_b2.id], 'input_c': [self.src_file_c.id]},
'json': {}
}
data3 = DataV6(data=data_dict).get_dict()
self.member_bc = dataset_test_utils.create_dataset_members(dataset=self.dataset2,
data_list=[data3])[0]
def test_dataset_members_successful(self):
"""Tests successfully calling the v6/datasets/members/<id>/ view.
"""
url = '/%s/datasets/%d/members/' % (self.api, self.dataset.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Check response for dataset members
result = json.loads(response.content)
self.assertEqual(len(result['results']), 1)
url = '/%s/datasets/%d/members/' % (self.api, self.dataset2.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Check response for dataset members
result = json.loads(response.content)
self.assertEqual(len(result['results']), 2)
"""Tests the v6/datasets/members/<datasetmember_id> endpoint"""
class TestDatasetMemberDetailsView(APITestCase):
api = 'v6'
def setUp(self):
django.setup()
rest.login_client(self.client, is_staff=True)
# Create workspace
self.workspace = Workspace.objects.create(name='Test Workspace', is_active=True, created=now(),
last_modified=now())
# Create files
self.src_file_a = storage_utils.create_file(file_name='input_a.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_b = storage_utils.create_file(file_name='input_b.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_c = storage_utils.create_file(file_name='input_c.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_b2 = storage_utils.create_file(file_name='input_b2.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_e = storage_utils.create_file(file_name='input_e.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
self.src_file_f = storage_utils.create_file(file_name='input_f.json', file_type='SOURCE', media_type='application/json',
file_size=10, data_type_tags=['type'], file_path='the_path',
workspace=self.workspace)
# Create datasets
parameters = {'version': '6',
'files': [
{'name': 'input_a',
'media_types': ['application/json'],
'required': True}
],
'json': []}
definition = {'version': '6', 'parameters': parameters}
self.dataset = dataset_test_utils.create_dataset( title="Test Dataset 1",
description="Test Dataset Number 1",
definition=definition)
parameters2 = {'version': '6',
'files': [
{'name': 'input_b',
'media_types': ['application/json'],
'required': True,
'multiple': True},
{'name': 'input_c',
'media_types': ['application/json'],
'required': False}
],
'json': []}
definition2 = {'version': '6', 'parameters': parameters2}
self.dataset2 = dataset_test_utils.create_dataset(title="Test Dataset 2",
description="Test Dataset Number 2",
definition=definition2)
# Create members
data_dict = {
'version': '6',
'files': {'input_a': [self.src_file_a.id]},
'json': {}
}
data = DataV6(data=data_dict).get_dict()
self.member_a = dataset_test_utils.create_dataset_members(dataset=self.dataset,
data_list=[data])[0]
data_dict = {
'version': '6',
'files': {'input_b': [self.src_file_b.id, self.src_file_b2.id]},
'json': {}
}
data2 = DataV6(data=data_dict).get_dict()
self.member_b = dataset_test_utils.create_dataset_members(dataset=self.dataset2,
data_list=[data2])[0]
data_dict = {
'version': '6',
'files': {'input_b': [self.src_file_b.id, self.src_file_b2.id], 'input_c': [self.src_file_c.id]},
'json': {}
}
data3 = DataV6(data=data_dict).get_dict()
self.member_bc = dataset_test_utils.create_dataset_members(dataset=self.dataset2,
data_list=[data3])[0]
def test_dataset_member_details_successful(self):
"""Tests successfully calling the v6/datasets/members/<id>/ view.
"""
url = '/%s/datasets/members/%d/' % (self.api, self.member_a.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Check response for dataset details
result = json.loads(response.content)
self.assertEqual(result['id'], self.member_a.id)
self.assertEqual(result['dataset']['id'], self.dataset.id)
versionless = copy.deepcopy(self.member_a.data)
del versionless['version']
self.assertDictEqual(result['data'], versionless)
url = '/%s/datasets/members/%d/' % (self.api, self.member_b.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Check response for dataset details
result = json.loads(response.content)
self.assertEqual(result['id'], self.member_b.id)
self.assertEqual(result['dataset']['id'], self.dataset2.id)
versionless = copy.deepcopy(self.member_b.data)
del versionless['version']
self.assertDictEqual(result['data'], versionless)
url = '/%s/datasets/members/%d/' % (self.api, self.member_bc.id)
response = self.client.generic('GET', url)
self.assertEqual(response.status_code, status.HTTP_200_OK, response.content)
# Check response for dataset details
result = json.loads(response.content)
self.assertEqual(result['id'], self.member_bc.id)
self.assertEqual(result['dataset']['id'], self.dataset2.id)
versionless = copy.deepcopy(self.member_bc.data)
del versionless['version']
self.assertDictEqual(result['data'], versionless)
| 45.595899
| 132
| 0.562105
| 3,984
| 37,799
| 5.129267
| 0.059739
| 0.049914
| 0.020455
| 0.032298
| 0.842966
| 0.813653
| 0.794715
| 0.768534
| 0.750966
| 0.738243
| 0
| 0.016395
| 0.312601
| 37,799
| 829
| 133
| 45.595899
| 0.77008
| 0.046245
| 0
| 0.682183
| 0
| 0
| 0.133515
| 0.010395
| 0
| 0
| 0
| 0
| 0.130016
| 1
| 0.038523
| false
| 0
| 0.025682
| 0
| 0.083467
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
14825fbd4a59980dd9c389a5f3f7c488b012e1ef
| 6,627
|
py
|
Python
|
bert_pytorch/model/associated_learning.py
|
Hibb-bb/ALLM
|
8eabed5175cb0f91850b367367abbecdded91568
|
[
"Apache-2.0"
] | 1
|
2022-01-27T09:39:31.000Z
|
2022-01-27T09:39:31.000Z
|
bert_pytorch/model/associated_learning.py
|
Hibb-bb/ALLM
|
8eabed5175cb0f91850b367367abbecdded91568
|
[
"Apache-2.0"
] | null | null | null |
bert_pytorch/model/associated_learning.py
|
Hibb-bb/ALLM
|
8eabed5175cb0f91850b367367abbecdded91568
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
from typing import Optional, Tuple
import torch
import torch.nn as nn
from torch import Tensor
from torch.nn.modules import dropout
class ALComponent(nn.Module):
x: Tensor
y: Tensor
loss_b: Tensor
loss_d: Tensor
_s: Tensor
_t: Tensor
_s_prime: Tensor
_t_prime: Tensor
def __init__(
self,
f: nn.Module,
g: nn.Module,
bx: nn.Module,
dy: nn.Module,
cb: nn.Module,
ca: nn.Module,
dropout: float = 0.1
) -> None:
super(ALComponent, self).__init__()
self.f = f
self.g = g
# birdge function
self.bx = bx
# h function
self.dy = dy
# loss function
self.criterion_br = cb
self.criterion_ae = ca
self.dropout = nn.Dropout(dropout)
def forward(self, x, y):
self.x = x
self.y = y
if self.training:
self._s = self.f(x)
self._t = self.g(y)
self._t_prime = self.dy(self._t)
return self._s.detach(), self._t.detach()
else:
self._s = self.f(x)
return self._s.detach(), self._t_prime.detach()
def loss(self):
self.loss_b = self.criterion_br(self.bx(self._s), self._t)
self.loss_d = self.criterion_ae(self._t_prime, self.y)
return self.loss_b + self.loss_d
class TransformerEncoderAL(ALComponent):
'''x: encoder, y: linear'''
def __init__(
self,
d_model: Tuple[int, int],
nhead: int,
y_hidden: int,
dim_feedforward: int = 2048,
dropout: float = 0.1,
activation: str = "relu",
layer_norm_eps: float = 1e-5,
batch_first: bool = True,
act: nn.Module = None,
) -> None:
if act == None:
act = nn.ELU()
encoder_layer = nn.TransformerEncoderLayer(
d_model[0], nhead, dim_feedforward=dim_feedforward, dropout=dropout, activation=activation, layer_norm_eps=layer_norm_eps, batch_first=batch_first
)
# num layer = 1
f = nn.TransformerEncoder(encoder_layer, 1)
g = nn.Sequential(
nn.Linear(d_model[1], y_hidden, bias=False),
act
)
# bridge function
bx = nn.Sequential(
nn.Linear(d_model[0], y_hidden, bias=False),
act
)
# h function
dy = nn.Sequential(
nn.Linear(y_hidden, d_model[1], bias=False),
act
)
# loss function
cb = nn.MSELoss(reduction='mean')
ca = nn.MSELoss(reduction='mean')
super().__init__(f, g, bx, dy, cb, ca)
def forward(self, x, y, src_mask=None, src_key_padding_mask=None):
self.x = x
self.y = y
if self.training:
self._s = self.f(x, src_mask, src_key_padding_mask)
self._s_prime = self.bx(self._s)
self._t = self.g(y)
self._t_prime = self.dy(self._t)
return self._s.detach(), self._t.detach()
else:
self._s = self.f(x, src_mask, src_key_padding_mask)
output = self.dy(y)
return self._s.detach(), output.detach()
def loss(self):
p = self._s_prime
q = self._t
# mean
p_nonzero = (p != 0.).sum(dim=1)
p = p.sum(dim=1) / p_nonzero
self.loss_b = self.criterion_br(p, q)
self.loss_d = self.criterion_ae(self._t_prime, self.y)
return self.loss_b + self.loss_d
def _generate_square_subsequent_mask(self, sz: int):
"""
Generate a square mask for the sequence. The masked positions are filled with float('-inf'). Unmasked positions are filled with float(0.0).
Shape: (sz, sz).
"""
mask = (torch.triu(torch.ones(sz, sz)) == 1).transpose(0, 1)
mask = mask.float().masked_fill(mask == 0, float(
'-inf')).masked_fill(mask == 1, float(0.0))
return mask
"""
class TransformerEncoderAL(ALComponent):
'''x: encoder, y: encoder'''
def __init__(
self,
d_model: Tuple[int, int],
nhead: int,
y_hidden: int,
dim_feedforward: int = 2048,
dropout: float = 0.1,
activation: str = "relu",
layer_norm_eps: float = 1e-5,
batch_first: bool = True,
act: nn.Module = None,
) -> None:
if act == None:
act = nn.ELU()
encoder_layer = nn.TransformerEncoderLayer(
d_model[0], nhead, dim_feedforward=dim_feedforward, dropout=dropout, activation=activation, layer_norm_eps=layer_norm_eps, batch_first=batch_first
)
# num layer = 1
f = nn.TransformerEncoder(encoder_layer, 1)
g = nn.Sequential(
nn.Linear(d_model[1], y_hidden, bias=False),
act
)
# bridge function
bx = nn.Sequential(
nn.Linear(d_model[0], y_hidden, bias=False),
act
)
# h function
dy = nn.Sequential(
nn.Linear(y_hidden, d_model[1], bias=False),
act
)
# loss function
cb = nn.MSELoss(reduction='mean')
ca = nn.MSELoss(reduction='mean')
super().__init__(f, g, bx, dy, cb, ca)
def forward(self, x, y, src_mask=None, src_key_padding_mask=None):
self.x = x
self.y = y
if self.training:
self._s = self.f(x, src_mask, src_key_padding_mask)
self._s_prime = self.bx(self._s)
self._t = self.g(y)
self._t_prime = self.dy(self._t)
return self._s.detach(), self._t.detach()
else:
self._s = self.f(x, src_mask, src_key_padding_mask)
output = self.dy(y)
return self._s.detach(), output.detach()
def loss(self):
p = self._s_prime
q = self._t
# mean
p_nonzero = (p != 0.).sum(dim=1)
p = p.sum(dim=1) / p_nonzero
self.loss_b = self.criterion_br(p, q)
self.loss_d = self.criterion_ae(self._t_prime, self.y)
return self.loss_b + self.loss_d
def _generate_square_subsequent_mask(self, sz: int):
'''
Generate a square mask for the sequence. The masked positions are filled with float('-inf'). Unmasked positions are filled with float(0.0).
Shape: (sz, sz).
'''
mask = (torch.triu(torch.ones(sz, sz)) == 1).transpose(0, 1)
mask = mask.float().masked_fill(mask == 0, float(
'-inf')).masked_fill(mask == 1, float(0.0))
return mask
"""
| 26.614458
| 158
| 0.547306
| 885
| 6,627
| 3.887006
| 0.128814
| 0.027616
| 0.023547
| 0.017442
| 0.85843
| 0.853779
| 0.814244
| 0.809593
| 0.809593
| 0.809593
| 0
| 0.012407
| 0.33107
| 6,627
| 249
| 159
| 26.614458
| 0.763591
| 0.045571
| 0
| 0.308411
| 0
| 0
| 0.004362
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.065421
| false
| 0
| 0.046729
| 0
| 0.271028
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
148699c4bbf0080627e05668e44f90e461ed01ca
| 4,234
|
py
|
Python
|
notebooks/tracking/create_dataset.py
|
jeffhernandez1995/jeffhernandez1995.github.io
|
214c9dcaa0d37b505870e1f5d51793ab7319c1e7
|
[
"MIT"
] | null | null | null |
notebooks/tracking/create_dataset.py
|
jeffhernandez1995/jeffhernandez1995.github.io
|
214c9dcaa0d37b505870e1f5d51793ab7319c1e7
|
[
"MIT"
] | null | null | null |
notebooks/tracking/create_dataset.py
|
jeffhernandez1995/jeffhernandez1995.github.io
|
214c9dcaa0d37b505870e1f5d51793ab7319c1e7
|
[
"MIT"
] | null | null | null |
import numpy as np
import cv2
import matplotlib.pyplot as plt
# vids = np.load('data/mnist_training_fast_videos.npy')
# bbox = np.load('data/mnist_training_fast_trajectories.npy')
# bbox[:, :, :, 3] = vids.shape[2] - bbox[:, :, :, 3]
# bbox[:, :, :, 1] = vids.shape[2] - bbox[:, :, :, 1]
# bbox = bbox.swapaxes(1, 2)
# length = 20000
# X_train = np.zeros((length, 5, 2, 28, 28))
# y_train = np.zeros((length, 5, 5))
# i = 0
# count = 0
# while count < length:
# print(f'{i/length}: There are {count} examples so far')
# num_t = vids.shape[1]
# indexes = np.triu(np.ones((num_t, num_t)) - np.eye(num_t))
# indexes = np.array([np.where(indexes)[0], np.where(indexes)[1]]).T
# inds = np.random.choice(indexes.shape[0], 250)
# indexes = indexes[inds]
# for idx in indexes:
# seq1 = vids[i, idx[0], :, :]
# seq2 = vids[i, idx[1], :, :]
# bbox1 = bbox[i, idx[0], :, :].astype(int)
# bbox2 = bbox[i, idx[1], :, :].astype(int)
# for j in range(5):
# # print(bbox1[j])
# y1 = min(127, max(0, bbox1[j, 1]))
# y2 = min(127, max(0, bbox1[j, 3]))
# x1 = min(127, max(0, bbox1[j, 0]))
# x2 = min(127, max(0, bbox1[j, 2]))
# img = seq1[y1:y2, x1:x2]
# # print(x1, x2, y1, y2)
# img = cv2.resize(img, (28, 28))
# X_train[count, j, 0, :, :] = img / 255.
# permidx = np.random.permutation(5)
# for j, index in enumerate(permidx):
# # print(bbox2[j])
# y1 = min(127, max(0, bbox2[j, 1]))
# y2 = min(127, max(0, bbox2[j, 3]))
# x1 = min(127, max(0, bbox2[j, 0]))
# x2 = min(127, max(0, bbox2[j, 2]))
# # print(x1, x2, y1, y2)
# img = seq2[y1:y2, x1:x2]
# img = cv2.resize(img, (28, 28))
# X_train[count, index, 1, :, :] = img / 255.
# y_train[count, j, index] = 1
# # assert 2 == 1
# count += 1
# i += 1
# permidx = np.random.permutation(X_train.shape[0])
# X_train = X_train[permidx]
# y_train = y_train[permidx]
# np.save('datasets/X_train.npy', X_train)
# np.save('datasets/y_train.npy', y_train)
vids = np.load('data/icons8_testing_fast_videos.npy')
bbox = np.load('data/icons8_testing_fast_trajectories.npy')
bbox[:, :, :, 3] = vids.shape[2] - bbox[:, :, :, 3]
bbox[:, :, :, 1] = vids.shape[2] - bbox[:, :, :, 1]
bbox = bbox.swapaxes(1, 2)
length = 20000
X_test = np.zeros((length, 5, 2, 28, 28))
y_test = np.zeros((length, 5, 5))
i = 0
count = 0
while count < length:
print(f'{i/length}: There are {count} examples so far')
num_t = vids.shape[1]
indexes = np.triu(np.ones((num_t, num_t)) - np.eye(num_t))
indexes = np.array([np.where(indexes)[0], np.where(indexes)[1]]).T
inds = np.random.choice(indexes.shape[0], 250)
indexes = indexes[inds]
for idx in indexes:
seq1 = vids[i, idx[0], :, :]
seq2 = vids[i, idx[1], :, :]
bbox1 = bbox[i, idx[0], :, :].astype(int)
bbox2 = bbox[i, idx[1], :, :].astype(int)
for j in range(5):
# print(bbox1[j])
y1 = min(127, max(0, bbox1[j, 1]))
y2 = min(127, max(0, bbox1[j, 3]))
x1 = min(127, max(0, bbox1[j, 0]))
x2 = min(127, max(0, bbox1[j, 2]))
img = seq1[y1:y2, x1:x2]
# print(x1, x2, y1, y2)
img = cv2.resize(img, (28, 28))
X_test[count, j, 0, :, :] = img / 255.
permidx = np.random.permutation(5)
for j, index in enumerate(permidx):
# print(bbox2[j])
y1 = min(127, max(0, bbox2[j, 1]))
y2 = min(127, max(0, bbox2[j, 3]))
x1 = min(127, max(0, bbox2[j, 0]))
x2 = min(127, max(0, bbox2[j, 2]))
# print(x1, x2, y1, y2)
img = seq2[y1:y2, x1:x2]
img = cv2.resize(img, (28, 28))
X_test[count, index, 1, :, :] = img / 255.
y_test[count, j, index] = 1
count += 1
i += 1
permidx = np.random.permutation(X_test.shape[0])
X_test = X_test[permidx]
y_test = y_test[permidx]
np.save('datasets/X_test.npy', X_test)
np.save('datasets/y_test.npy', y_test)
| 34.991736
| 72
| 0.510392
| 652
| 4,234
| 3.240798
| 0.130368
| 0.045433
| 0.06815
| 0.075722
| 0.877425
| 0.848083
| 0.801704
| 0.776148
| 0.757217
| 0.743966
| 0
| 0.093511
| 0.290269
| 4,234
| 120
| 73
| 35.283333
| 0.609651
| 0.499764
| 0
| 0.04
| 0
| 0
| 0.077335
| 0.036965
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.06
| 0
| 0.06
| 0.02
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
148a29d6ca890168d8417f3932b07db9f5717080
| 40
|
py
|
Python
|
prodcon_ipc/__init__.py
|
CodeFinder2/shared-memory-pycpp-example
|
dd82cdc3a0cb4a986ddc3237e2d1e367d39031ff
|
[
"BSD-3-Clause"
] | 3
|
2020-08-02T14:06:06.000Z
|
2021-09-21T21:22:04.000Z
|
prodcon_ipc/__init__.py
|
CodeFinder2/shared-memory-cpp-example
|
dd82cdc3a0cb4a986ddc3237e2d1e367d39031ff
|
[
"BSD-3-Clause"
] | 1
|
2020-05-07T16:23:27.000Z
|
2020-05-07T16:23:27.000Z
|
prodcon_ipc/__init__.py
|
CodeFinder2/shared-memory-cpp-example
|
dd82cdc3a0cb4a986ddc3237e2d1e367d39031ff
|
[
"BSD-3-Clause"
] | null | null | null |
import producer_ipc
import consumer_ipc
| 13.333333
| 19
| 0.9
| 6
| 40
| 5.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 40
| 2
| 20
| 20
| 0.944444
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
1494a72b6d31a02f8e1a01eea17d33b9d02b1ee5
| 10,757
|
py
|
Python
|
tests/unit/test_paths.py
|
p1c2u/pathable
|
ba9f30ead908e9d579e290977b8f2221d32751b6
|
[
"Apache-2.0"
] | 1
|
2022-02-01T01:53:59.000Z
|
2022-02-01T01:53:59.000Z
|
tests/unit/test_paths.py
|
p1c2u/pathable
|
ba9f30ead908e9d579e290977b8f2221d32751b6
|
[
"Apache-2.0"
] | 2
|
2022-02-01T03:37:04.000Z
|
2022-02-01T03:53:16.000Z
|
tests/unit/test_paths.py
|
p1c2u/pathable
|
ba9f30ead908e9d579e290977b8f2221d32751b6
|
[
"Apache-2.0"
] | null | null | null |
from types import GeneratorType
import pytest
from pathable.paths import SEPARATOR
from pathable.paths import BasePath
from pathable.paths import LookupPath
class TestBasePathInit:
def test_default(self):
p = BasePath()
assert p.parts == []
assert p.separator == SEPARATOR
def test_part_text(self):
part = "part"
p = BasePath(part)
assert p.parts == [
part,
]
assert p.separator == SEPARATOR
def test_part_binary(self):
part = b"part"
p = BasePath(part)
assert p.parts == [
"part",
]
assert p.separator == SEPARATOR
def test_part_binary_many(self):
part1 = b"part1"
part2 = b"part2"
p = BasePath(part1, part2)
assert p.parts == ["part1", "part2"]
assert p.separator == SEPARATOR
def test_part_text_many(self):
part1 = "part1"
part2 = "part2"
p = BasePath(part1, part2)
assert p.parts == [part1, part2]
assert p.separator == SEPARATOR
def test_part_path(self):
part = "part"
p1 = BasePath(part)
p = BasePath(p1)
assert p.parts == [
part,
]
assert p.separator == SEPARATOR
def test_part_path_many(self):
part1 = "part1"
part2 = "part2"
p1 = BasePath(part1)
p2 = BasePath(part2)
p = BasePath(p1, p2)
assert p.parts == [part1, part2]
assert p.separator == SEPARATOR
def test_separator(self):
separator = "."
p = BasePath(separator=separator)
assert p.parts == []
assert p.separator == separator
class TestBasePathFromParts:
def test_default(self):
parts = []
p = BasePath._from_parts(parts)
assert p.parts == parts
assert p.separator == SEPARATOR
def test_parts(self):
parts = ["part1"]
p = BasePath._from_parts(parts)
assert p.parts == parts
assert p.separator == SEPARATOR
def test_parts_unparsed(self):
parts = ["part1", "part2"]
part = SEPARATOR.join(parts)
p = BasePath._from_parts([part])
assert p.parts == parts
assert p.separator == SEPARATOR
def test_parts_many(self):
parts = ["part1", "part2"]
p = BasePath._from_parts(parts)
assert p.parts == parts
assert p.separator == SEPARATOR
def test_separator(self):
parts = []
separator = "."
p = BasePath._from_parts(parts, separator=separator)
assert p.parts == parts
assert p.separator == separator
class TestBasePathFromParsedParts:
def test_default(self):
parts = []
p = BasePath._from_parsed_parts(parts)
assert p.parts == parts
assert p.separator == SEPARATOR
def test_parts(self):
parts = ["part1"]
p = BasePath._from_parsed_parts(parts)
assert p.parts == parts
assert p.separator == SEPARATOR
def test_parts_unparsed(self):
part = SEPARATOR.join(["part1", "part2"])
parts = [part]
p = BasePath._from_parsed_parts(parts)
assert p.parts == parts
assert p.separator == SEPARATOR
def test_parts_many(self):
parts = ["part1", "part2"]
p = BasePath._from_parsed_parts(parts)
assert p.parts == parts
assert p.separator == SEPARATOR
def test_separator(self):
parts = []
separator = "."
p = BasePath._from_parsed_parts(parts, separator=separator)
assert p.parts == parts
assert p.separator == separator
class TestBasePathTruediv:
def test_default_empty(self):
p = BasePath() / ""
assert p.parts == []
assert p.separator == SEPARATOR
@pytest.mark.parametrize(
"part1,part2,parts,separator",
(
[
"",
"",
[],
SEPARATOR,
],
[
"",
"part1",
["part1"],
SEPARATOR,
],
[
"part1",
"",
["part1"],
SEPARATOR,
],
[
"part1",
"part2",
["part1", "part2"],
SEPARATOR,
],
[
b"",
"",
[],
SEPARATOR,
],
[
b"",
"part1",
["part1"],
SEPARATOR,
],
[
b"part1",
"",
["part1"],
SEPARATOR,
],
[
b"part1",
"part2",
["part1", "part2"],
SEPARATOR,
],
[
"part1",
BasePath("part2"),
["part1", "part2"],
SEPARATOR,
],
[
BasePath("part1"),
"part2",
["part1", "part2"],
SEPARATOR,
],
[
BasePath("part1"),
BasePath("part2"),
["part1", "part2"],
SEPARATOR,
],
),
)
def test_parts(self, part1, part2, parts, separator):
p = BasePath(part1) / part2
assert p.parts == parts
assert p.separator == separator
def test_combined(self):
part11 = "part11"
part12 = "part12"
part21 = "part21"
part22 = "part22"
part1 = SEPARATOR.join([part11, part12])
part2 = SEPARATOR.join([part21, part22])
p = BasePath(part1) / part2
assert p.parts == [part11, part12, part21, part22]
assert p.separator == SEPARATOR
def test_combined_different_separators(self):
part11 = "part11"
part12 = "part12"
part21 = "part21"
part22 = "part22"
separator1 = "."
part1 = SEPARATOR.join([part11, part12])
part2 = SEPARATOR.join([part21, part22])
p1 = BasePath(part2)
p = BasePath(part1, separator=separator1) / p1
assert p.parts == [part11, part12, part21, part22]
assert p.separator == separator1
class TestBasePathRtruediv:
def test_default_empty(self):
p = "" / BasePath()
assert p.parts == []
assert p.separator == SEPARATOR
@pytest.mark.parametrize(
"part1,part2,parts,separator",
(
[
"",
"",
[],
SEPARATOR,
],
[
"",
"part1",
["part1"],
SEPARATOR,
],
[
"part1",
"",
["part1"],
SEPARATOR,
],
[
"part1",
"part2",
["part1", "part2"],
SEPARATOR,
],
[
b"",
"",
[],
SEPARATOR,
],
[
b"",
"part1",
["part1"],
SEPARATOR,
],
[
b"part1",
"",
["part1"],
SEPARATOR,
],
[
b"part1",
"part2",
["part1", "part2"],
SEPARATOR,
],
[
"part1",
BasePath("part2"),
["part1", "part2"],
SEPARATOR,
],
[
BasePath("part1"),
"part2",
["part1", "part2"],
SEPARATOR,
],
[
BasePath("part1"),
BasePath("part2"),
["part1", "part2"],
SEPARATOR,
],
),
)
def test_parts(self, part1, part2, parts, separator):
p = part1 / BasePath(part2)
assert p.parts == parts
assert p.separator == separator
def test_combined(self):
part11 = "part11"
part12 = "part12"
part21 = "part21"
part22 = "part22"
part1 = SEPARATOR.join([part11, part12])
part2 = SEPARATOR.join([part21, part22])
p = part1 / BasePath(part2)
assert p.parts == [part11, part12, part21, part22]
assert p.separator == SEPARATOR
class TestBasePathEq:
@pytest.mark.parametrize(
"part1,part2,expected",
(
["", "", True],
["", "part", False],
["part", "", False],
["part", "part", True],
["part", BasePath("part"), True],
[BasePath("part"), "part", True],
[BasePath("part"), BasePath("part"), True],
),
)
def test_parts(self, part1, part2, expected):
result = BasePath(part1) == BasePath(part2)
assert result is expected
class TestLookupPathPathGetItem:
def test_valid(self):
value = "testvalue"
resource = {"test1": {"test2": {"test3": value}}}
p = LookupPath(resource, "test1/test2")
result = p["test3"]
assert result == value
def test_invalid(self):
value = "testvalue"
resource = {"test1": {"test2": {"test3": value}}}
p = LookupPath(resource, "test1/test2")
with pytest.raises(KeyError):
p["test4"]
class TestLookupPathPathContains:
def test_valid(self):
value = "testvalue"
resource = {"test1": {"test2": {"test3": value}}}
p = LookupPath(resource, "test1/test2")
result = "test3" in p
assert result is True
def test_invalid(self):
value = "testvalue"
resource = {"test1": {"test2": {"test3": value}}}
p = LookupPath(resource, "test1/test2")
result = "test4" in p
assert result is False
class TestLookupPathPathItems:
def test_empty(self):
resource = {}
p = LookupPath(resource)
result = p.items()
assert type(result) is GeneratorType
assert dict(result) == {}
def test_keys(self):
resource = {
"test1": 1,
"test2": 2,
}
p = LookupPath(resource)
result = p.items()
assert type(result) is GeneratorType
assert dict(result) == {
"test1": p / "test1",
"test2": p / "test2",
}
| 24.064877
| 67
| 0.454774
| 894
| 10,757
| 5.389262
| 0.083893
| 0.072644
| 0.062267
| 0.124533
| 0.794105
| 0.771067
| 0.752802
| 0.731216
| 0.713367
| 0.702574
| 0
| 0.041889
| 0.425211
| 10,757
| 446
| 68
| 24.118834
| 0.737344
| 0
| 0
| 0.70765
| 0
| 0
| 0.071209
| 0.00502
| 0
| 0
| 0
| 0
| 0.15847
| 1
| 0.087432
| false
| 0
| 0.013661
| 0
| 0.125683
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
14ab8cc35bfc1aa451bcb71d355f11d50e2a1322
| 4,586
|
py
|
Python
|
tests/utils/test_utils.py
|
run-x/opta
|
64606498334f2b1aa79f5a431465eafdf5ca5ed7
|
[
"Apache-2.0"
] | 595
|
2021-05-21T22:30:48.000Z
|
2022-03-31T15:40:25.000Z
|
tests/utils/test_utils.py
|
run-x/opta
|
64606498334f2b1aa79f5a431465eafdf5ca5ed7
|
[
"Apache-2.0"
] | 463
|
2021-05-24T21:32:59.000Z
|
2022-03-31T17:12:33.000Z
|
tests/utils/test_utils.py
|
run-x/opta
|
64606498334f2b1aa79f5a431465eafdf5ca5ed7
|
[
"Apache-2.0"
] | 29
|
2021-05-21T22:27:52.000Z
|
2022-03-28T16:43:45.000Z
|
import click
import pytest
from pytest_mock import MockFixture
from opta.exceptions import UserErrors
from opta.utils import alternate_yaml_extension, check_opta_file_exists, exp_backoff
def test_exp_backoff(mocker: MockFixture) -> None:
# Sleep should be exponential for each iteration
mocked_sleep = mocker.patch("opta.utils.sleep")
retries = 3
for _ in exp_backoff(num_tries=retries):
pass
raw_call_args = mocked_sleep.call_args_list
sleep_param_history = [arg[0][0] for arg in raw_call_args]
assert sleep_param_history == [2, 4, 16]
# Sleep should not be called if body succeeded and exited.
mocked_sleep = mocker.patch("opta.utils.sleep")
for _ in exp_backoff(num_tries=retries):
break
assert mocked_sleep.call_count == 0
def test_check_opta_file_exists_file_exists(mocker: MockFixture) -> None:
mock_config_path = "mock_config_path"
mock_os_path_exists = mocker.patch("opta.utils.os.path.exists", return_value=True)
mock_click_prompt = mocker.patch("opta.utils.click.prompt")
mock_system_exit = mocker.patch("opta.utils.sys.exit")
config_path = check_opta_file_exists(mock_config_path)
assert config_path == mock_config_path
mock_os_path_exists.assert_called_once_with(mock_config_path)
mock_click_prompt.assert_not_called()
mock_system_exit.assert_not_called()
def test_check_opta_file_exists_file_does_not_exists_user_input(
mocker: MockFixture,
) -> None:
mock_config_path = "mock_config_path"
mock_user_config_path = "mock_user_config_path"
mock_os_path_exists = mocker.patch(
"opta.utils.os.path.exists", side_effect=[False, True]
)
mock_click_prompt = mocker.patch(
"opta.utils.click.prompt", return_value=mock_user_config_path
)
mock_system_exit = mocker.patch("opta.utils.sys.exit")
config_path = check_opta_file_exists(mock_config_path)
assert config_path == mock_user_config_path
mock_os_path_exists.assert_has_calls(
[mocker.call(mock_config_path), mocker.call(mock_user_config_path)]
)
mock_click_prompt.assert_called_once_with(
"Enter a Configuration Path (Empty String will exit)",
default="",
type=click.STRING,
show_default=False,
)
mock_system_exit.assert_not_called()
def test_check_opta_file_exists_file_does_not_exists_no_user_input(
mocker: MockFixture,
) -> None:
mock_config_path = "mock_config_path"
mock_no_user_config_path = ""
mock_os_path_exists = mocker.patch(
"opta.utils.os.path.exists", side_effect=[False, False]
)
mock_click_prompt = mocker.patch(
"opta.utils.click.prompt", return_value=mock_no_user_config_path
)
mock_system_exit = mocker.patch("opta.utils.sys.exit")
config_path = check_opta_file_exists(mock_config_path)
assert config_path == mock_no_user_config_path
mock_os_path_exists.assert_called_once_with(mock_config_path)
mock_click_prompt.assert_called_once_with(
"Enter a Configuration Path (Empty String will exit)",
default="",
type=click.STRING,
show_default=False,
)
mock_system_exit.assert_called_once_with(0)
def test_check_opta_file_exists_file_does_not_exists_invalid_user_input(
mocker: MockFixture,
) -> None:
mock_config_path = "mock_config_path"
mock_invalid_user_config_path = "mock_invalid_user_config_path"
mock_os_path_exists = mocker.patch(
"opta.utils.os.path.exists", side_effect=[False, False]
)
mock_click_prompt = mocker.patch(
"opta.utils.click.prompt", return_value=mock_invalid_user_config_path
)
mock_system_exit = mocker.patch("opta.utils.sys.exit")
with pytest.raises(UserErrors):
_ = check_opta_file_exists(mock_config_path)
mock_os_path_exists.assert_has_calls(
[mocker.call(mock_config_path), mocker.call(mock_invalid_user_config_path)]
)
mock_click_prompt.assert_called_once_with(
"Enter a Configuration Path (Empty String will exit)",
default="",
type=click.STRING,
show_default=False,
)
mock_system_exit.assert_not_called()
def test_alternate_yaml_extension() -> None:
assert alternate_yaml_extension("opta.yaml") == ("opta.yml", True)
assert alternate_yaml_extension("opta.yml") == ("opta.yaml", True)
assert alternate_yaml_extension("opta.YML") == ("opta.yaml", True)
assert alternate_yaml_extension("path/opta.yml") == ("path/opta.yaml", True)
assert alternate_yaml_extension("path/config") == ("path/config", False)
| 35.828125
| 86
| 0.737898
| 641
| 4,586
| 4.853354
| 0.141966
| 0.115718
| 0.121504
| 0.090003
| 0.816458
| 0.806172
| 0.801029
| 0.751205
| 0.713918
| 0.713918
| 0
| 0.00236
| 0.168556
| 4,586
| 127
| 87
| 36.110236
| 0.813533
| 0.02246
| 0
| 0.495146
| 0
| 0
| 0.148884
| 0.054018
| 0
| 0
| 0
| 0
| 0.213592
| 1
| 0.058252
| false
| 0.009709
| 0.048544
| 0
| 0.106796
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 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
| 6
|
1add2285b18cc4f6eb09b39b65ad3527acb1c2e0
| 122
|
py
|
Python
|
tests/test_dice.py
|
juanescendales/ci-me-dice-on-demand
|
05a5ce27f7e613291bd037425c01c8476549d95f
|
[
"MIT"
] | null | null | null |
tests/test_dice.py
|
juanescendales/ci-me-dice-on-demand
|
05a5ce27f7e613291bd037425c01c8476549d95f
|
[
"MIT"
] | null | null | null |
tests/test_dice.py
|
juanescendales/ci-me-dice-on-demand
|
05a5ce27f7e613291bd037425c01c8476549d95f
|
[
"MIT"
] | null | null | null |
import unittest
import app
def test_test():
assert app.test() == "Works!"
assert app.hello() == "Goodbye World"
| 15.25
| 41
| 0.647541
| 16
| 122
| 4.875
| 0.625
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.204918
| 122
| 7
| 42
| 17.428571
| 0.804124
| 0
| 0
| 0
| 0
| 0
| 0.155738
| 0
| 0
| 0
| 0
| 0
| 0.4
| 1
| 0.2
| true
| 0
| 0.4
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
1ae7b7f44d529e712e61af49f433ef51076599ae
| 147
|
py
|
Python
|
product/models/__init__.py
|
sharif-42/Style-Icon
|
26cd93cdd991588ce41f0032b033551f9f1a1bce
|
[
"MIT"
] | 1
|
2022-01-01T11:51:30.000Z
|
2022-01-01T11:51:30.000Z
|
product/models/__init__.py
|
sharif-42/Style-Icon
|
26cd93cdd991588ce41f0032b033551f9f1a1bce
|
[
"MIT"
] | null | null | null |
product/models/__init__.py
|
sharif-42/Style-Icon
|
26cd93cdd991588ce41f0032b033551f9f1a1bce
|
[
"MIT"
] | null | null | null |
from .product import Product
from .product_type import ProductType
from .product_group import ProductGroup
from .product_brand import ProductBrand
| 29.4
| 39
| 0.863946
| 19
| 147
| 6.526316
| 0.473684
| 0.354839
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108844
| 147
| 4
| 40
| 36.75
| 0.946565
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
210143c9902f90df6edef4406a514b630d74e2c8
| 254
|
py
|
Python
|
tests/fixtures/sampler/__init__.py
|
fangqyi/garage
|
ddafba385ef005f46f913ab352f9638760e5b412
|
[
"MIT"
] | 1
|
2021-03-02T08:43:20.000Z
|
2021-03-02T08:43:20.000Z
|
tests/fixtures/sampler/__init__.py
|
fangqyi/garage
|
ddafba385ef005f46f913ab352f9638760e5b412
|
[
"MIT"
] | null | null | null |
tests/fixtures/sampler/__init__.py
|
fangqyi/garage
|
ddafba385ef005f46f913ab352f9638760e5b412
|
[
"MIT"
] | null | null | null |
"""Fixtures for testing samplers."""
from tests.fixtures.sampler.ray_fixtures import (ray_local_session_fixture,
ray_session_fixture)
__all__ = ['ray_local_session_fixture', 'ray_session_fixture']
| 36.285714
| 76
| 0.641732
| 26
| 254
| 5.692308
| 0.5
| 0.378378
| 0.202703
| 0.297297
| 0.527027
| 0.527027
| 0.527027
| 0
| 0
| 0
| 0
| 0
| 0.275591
| 254
| 6
| 77
| 42.333333
| 0.804348
| 0.11811
| 0
| 0
| 0
| 0
| 0.207547
| 0.117925
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 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
| 1
| 0
| 0
| 0
|
0
| 6
|
2133aee6a5b85b9b7855fa72d1c24e8d321f9d7c
| 156
|
py
|
Python
|
dash/admin.py
|
ravshansk/ajans
|
84e0d23609b0af98ba390cc8736bfae66d0b883e
|
[
"MIT"
] | null | null | null |
dash/admin.py
|
ravshansk/ajans
|
84e0d23609b0af98ba390cc8736bfae66d0b883e
|
[
"MIT"
] | null | null | null |
dash/admin.py
|
ravshansk/ajans
|
84e0d23609b0af98ba390cc8736bfae66d0b883e
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from .models import Actor
# Register your models here.
@admin.register(Actor)
class ActorAdmin(admin.ModelAdmin):
pass
| 15.6
| 35
| 0.788462
| 21
| 156
| 5.857143
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.134615
| 156
| 9
| 36
| 17.333333
| 0.911111
| 0.166667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.2
| 0.4
| 0
| 0.6
| 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
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
216818220f93141584620c00849be8301514f246
| 265
|
py
|
Python
|
Artifact.py
|
drherobrine/Chigsaw
|
1e8a2832deb61fa0bb7377a83540c6ae04c20eec
|
[
"BSD-2-Clause"
] | null | null | null |
Artifact.py
|
drherobrine/Chigsaw
|
1e8a2832deb61fa0bb7377a83540c6ae04c20eec
|
[
"BSD-2-Clause"
] | 5
|
2016-02-15T17:06:53.000Z
|
2016-02-15T20:34:02.000Z
|
Artifact.py
|
drherobrine/Chigsaw
|
1e8a2832deb61fa0bb7377a83540c6ae04c20eec
|
[
"BSD-2-Clause"
] | null | null | null |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
class Artifact:
def __init__(self, name):
self.name = name
def getName():
return self.name
| 24.090909
| 39
| 0.758491
| 33
| 265
| 5.393939
| 0.515152
| 0.224719
| 0.359551
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 265
| 10
| 40
| 26.5
| 0.839623
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.222222
| false
| 0
| 0.444444
| 0.111111
| 0.888889
| 0.111111
| 0
| 0
| 0
| null | 1
| 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
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
dce8864b2fb92d7397d63cb9f28a1d2d4e5fa008
| 125
|
py
|
Python
|
dgcnn/__init__.py
|
Temigo/dynamic-gcnn
|
baed5b637b6dc7a7d984db580213a35622f1471d
|
[
"MIT"
] | 49
|
2018-10-19T22:51:31.000Z
|
2022-02-10T17:11:06.000Z
|
dgcnn/__init__.py
|
Temigo/dynamic-gcnn
|
baed5b637b6dc7a7d984db580213a35622f1471d
|
[
"MIT"
] | 2
|
2018-11-06T23:41:28.000Z
|
2019-06-03T05:47:43.000Z
|
dgcnn/__init__.py
|
Temigo/dynamic-gcnn
|
baed5b637b6dc7a7d984db580213a35622f1471d
|
[
"MIT"
] | 11
|
2018-10-12T23:35:07.000Z
|
2020-12-01T12:29:32.000Z
|
from iotool import io_factory
from model import build
from trainval import trainval
import ops
from flags import DGCNN_FLAGS
| 20.833333
| 29
| 0.856
| 20
| 125
| 5.25
| 0.55
| 0.266667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.144
| 125
| 5
| 30
| 25
| 0.981308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
dcfe2cef6ccba9ed1fca41f906d74565f0470594
| 1,913
|
py
|
Python
|
event/veldt_helpers.py
|
HansGR/WorldsCollide
|
af227be553e120ee004b130598360c61daf7df59
|
[
"MIT"
] | 7
|
2022-01-15T02:53:53.000Z
|
2022-02-17T00:51:32.000Z
|
event/veldt_helpers.py
|
HansGR/WorldsCollide
|
af227be553e120ee004b130598360c61daf7df59
|
[
"MIT"
] | 8
|
2022-01-16T02:45:24.000Z
|
2022-03-21T02:08:27.000Z
|
event/veldt_helpers.py
|
HansGR/WorldsCollide
|
af227be553e120ee004b130598360c61daf7df59
|
[
"MIT"
] | 5
|
2022-01-15T02:53:38.000Z
|
2022-01-19T17:42:10.000Z
|
import data.event_bit as event_bit
import instruction.asm as asm
def ram_event_byte(event):
return 0x1e80 + event_bit.byte(event)
def ram_event_bit(event):
return 1 << event_bit.bit(event)
def char_recruited_event_byte(char):
return ram_event_byte(event_bit.character_recruited(char))
def char_recruited_event_bit(char):
return ram_event_bit(event_bit.character_recruited(char))
def char_available_event_byte(char):
return ram_event_byte(event_bit.character_available(char))
def char_available_event_bit(char):
return ram_event_bit(event_bit.character_available(char))
def esper_available_byte(esper):
return 0x1a69 + esper // 8
def esper_available_bit(esper):
return 1 << (esper % 8)
def branch_if_char_recruited(char, dest):
return [
asm.LDA(char_recruited_event_byte(char), asm.ABS),
asm.BIT(char_recruited_event_bit(char), asm.IMM8),
asm.BNE(dest),
]
def branch_if_char_not_recruited(char, dest):
return [
asm.LDA(char_recruited_event_byte(char), asm.ABS),
asm.BIT(char_recruited_event_bit(char), asm.IMM8),
asm.BEQ(dest),
]
def branch_if_char_available(char, dest):
return [
asm.LDA(char_available_event_byte(char), asm.ABS),
asm.BIT(char_available_event_bit(char), asm.IMM8),
asm.BNE(dest),
]
def branch_if_char_not_available(char, dest):
return [
asm.LDA(char_available_event_byte(char), asm.ABS),
asm.BIT(char_available_event_bit(char), asm.IMM8),
asm.BEQ(dest),
]
def branch_if_event_bit_set(event, dest):
return [
asm.LDA(ram_event_byte(event), asm.ABS),
asm.BIT(ram_event_bit(event), asm.IMM8),
asm.BNE(dest),
]
def branch_if_event_bit_clear(event, dest):
return [
asm.LDA(ram_event_byte(event), asm.ABS),
asm.BIT(ram_event_bit(event), asm.IMM8),
asm.BEQ(dest),
]
| 27.724638
| 62
| 0.699425
| 286
| 1,913
| 4.34965
| 0.108392
| 0.135048
| 0.086817
| 0.07717
| 0.799839
| 0.755627
| 0.717042
| 0.684887
| 0.670418
| 0.670418
| 0
| 0.011561
| 0.186095
| 1,913
| 68
| 63
| 28.132353
| 0.787412
| 0
| 0
| 0.444444
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006273
| 0
| 0
| 1
| 0.259259
| false
| 0
| 0.037037
| 0.259259
| 0.555556
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 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
| 1
| 0
|
0
| 6
|
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