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TheAlgorithms/Python

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TheAlgorithms/Python

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## Audio Filters * [Butterworth Filter](audio_filters/butterworth_filter.py) * [Iir Filter](audio_filters/iir_filter.py) * [Show Response](audio_filters/show_response.py) ## Backtracking * [All Combinations](backtracking/all_combinations.py) * [All Permutations](backtracking/all_permutations.py) * [All Subsequences](backtracking/all_subsequences.py) * [Coloring](backtracking/coloring.py) * [Combination Sum](backtracking/combination_sum.py) * [Crossword Puzzle Solver](backtracking/crossword_puzzle_solver.py) * [Generate Parentheses](backtracking/generate_parentheses.py) * [Hamiltonian Cycle](backtracking/hamiltonian_cycle.py) * [Knight Tour](backtracking/knight_tour.py) * [Match Word Pattern](backtracking/match_word_pattern.py) * [Minimax](backtracking/minimax.py) * [N Queens](backtracking/n_queens.py) * [N Queens Math](backtracking/n_queens_math.py) * [Power Sum](backtracking/power_sum.py) * [Rat In Maze](backtracking/rat_in_maze.py) * [Sudoku](backtracking/sudoku.py) * [Sum Of Subsets](backtracking/sum_of_subsets.py) * [Word Search](backtracking/word_search.py) ## Bit Manipulation * [Binary And Operator](bit_manipulation/binary_and_operator.py) * [Binary Coded Decimal](bit_manipulation/binary_coded_decimal.py) * [Binary Count Setbits](bit_manipulation/binary_count_setbits.py) * [Binary Count Trailing Zeros](bit_manipulation/binary_count_trailing_zeros.py) * [Binary Or Operator](bit_manipulation/binary_or_operator.py) * [Binary Shifts](bit_manipulation/binary_shifts.py) * [Binary Twos Complement](bit_manipulation/binary_twos_complement.py) * [Binary Xor Operator](bit_manipulation/binary_xor_operator.py) * [Bitwise Addition Recursive](bit_manipulation/bitwise_addition_recursive.py) * [Count 1S Brian Kernighan Method](bit_manipulation/count_1s_brian_kernighan_method.py) * [Count Number Of One Bits](bit_manipulation/count_number_of_one_bits.py) * [Excess 3 Code](bit_manipulation/excess_3_code.py) * [Find Previous Power Of Two](bit_manipulation/find_previous_power_of_two.py) * [Gray Code Sequence](bit_manipulation/gray_code_sequence.py) * [Highest Set Bit](bit_manipulation/highest_set_bit.py) * [Index Of Rightmost Set Bit](bit_manipulation/index_of_rightmost_set_bit.py) * [Is Even](bit_manipulation/is_even.py) * [Is Power Of Two](bit_manipulation/is_power_of_two.py) * [Largest Pow Of Two Le Num](bit_manipulation/largest_pow_of_two_le_num.py) * [Missing Number](bit_manipulation/missing_number.py) * [Numbers Different Signs](bit_manipulation/numbers_different_signs.py) * [Power Of 4](bit_manipulation/power_of_4.py) * [Reverse Bits](bit_manipulation/reverse_bits.py) * [Single Bit Manipulation Operations](bit_manipulation/single_bit_manipulation_operations.py) * [Swap All Odd And Even Bits](bit_manipulation/swap_all_odd_and_even_bits.py) ## Blockchain * [Diophantine Equation](blockchain/diophantine_equation.py) ## Boolean Algebra * [And Gate](boolean_algebra/and_gate.py) * [Imply Gate](boolean_algebra/imply_gate.py) * [Karnaugh Map Simplification](boolean_algebra/karnaugh_map_simplification.py) * [Multiplexer](boolean_algebra/multiplexer.py) * [Nand Gate](boolean_algebra/nand_gate.py) * [Nimply Gate](boolean_algebra/nimply_gate.py) * [Nor Gate](boolean_algebra/nor_gate.py) * [Not Gate](boolean_algebra/not_gate.py) * [Or Gate](boolean_algebra/or_gate.py) * [Quine Mc Cluskey](boolean_algebra/quine_mc_cluskey.py) * [Xnor Gate](boolean_algebra/xnor_gate.py) * [Xor Gate](boolean_algebra/xor_gate.py) ## Cellular Automata * [Conways Game Of Life](cellular_automata/conways_game_of_life.py) * [Game Of Life](cellular_automata/game_of_life.py) * [Langtons Ant](cellular_automata/langtons_ant.py) * [Nagel Schrekenberg](cellular_automata/nagel_schrekenberg.py) * [One Dimensional](cellular_automata/one_dimensional.py) * [Wa Tor](cellular_automata/wa_tor.py) ## Ciphers * [A1Z26](ciphers/a1z26.py) * [Affine Cipher](ciphers/affine_cipher.py) * [Atbash](ciphers/atbash.py) * [Autokey](ciphers/autokey.py) * [Baconian Cipher](ciphers/baconian_cipher.py) * [Base16](ciphers/base16.py) * [Base32](ciphers/base32.py) * [Base64](ciphers/base64.py) * [Base85](ciphers/base85.py) * [Beaufort Cipher](ciphers/beaufort_cipher.py) * [Bifid](ciphers/bifid.py) * [Brute Force Caesar Cipher](ciphers/brute_force_caesar_cipher.py) * [Caesar Cipher](ciphers/caesar_cipher.py) * [Cryptomath Module](ciphers/cryptomath_module.py) * [Decrypt Caesar With Chi Squared](ciphers/decrypt_caesar_with_chi_squared.py) * [Deterministic Miller Rabin](ciphers/deterministic_miller_rabin.py) * [Diffie](ciphers/diffie.py) * [Diffie Hellman](ciphers/diffie_hellman.py) * [Elgamal Key Generator](ciphers/elgamal_key_generator.py) * [Enigma Machine2](ciphers/enigma_machine2.py) * [Fractionated Morse Cipher](ciphers/fractionated_morse_cipher.py) * [Hill Cipher](ciphers/hill_cipher.py) * [Mixed Keyword Cypher](ciphers/mixed_keyword_cypher.py) * [Mono Alphabetic Ciphers](ciphers/mono_alphabetic_ciphers.py) * [Morse Code](ciphers/morse_code.py) * [Onepad Cipher](ciphers/onepad_cipher.py) * [Permutation Cipher](ciphers/permutation_cipher.py) * [Playfair Cipher](ciphers/playfair_cipher.py) * [Polybius](ciphers/polybius.py) * [Porta Cipher](ciphers/porta_cipher.py) * [Rabin Miller](ciphers/rabin_miller.py) * [Rail Fence Cipher](ciphers/rail_fence_cipher.py) * [Rot13](ciphers/rot13.py) * [Rsa Cipher](ciphers/rsa_cipher.py) * [Rsa Factorization](ciphers/rsa_factorization.py) * [Rsa Key Generator](ciphers/rsa_key_generator.py) * [Running Key Cipher](ciphers/running_key_cipher.py) * [Shuffled Shift Cipher](ciphers/shuffled_shift_cipher.py) * [Simple Keyword Cypher](ciphers/simple_keyword_cypher.py) * [Simple Substitution Cipher](ciphers/simple_substitution_cipher.py) * [Transposition Cipher](ciphers/transposition_cipher.py) * [Transposition Cipher Encrypt Decrypt File](ciphers/transposition_cipher_encrypt_decrypt_file.py) * [Trifid Cipher](ciphers/trifid_cipher.py) * [Vernam Cipher](ciphers/vernam_cipher.py) * [Vigenere Cipher](ciphers/vigenere_cipher.py) * [Xor Cipher](ciphers/xor_cipher.py) ## Compression * [Burrows Wheeler](compression/burrows_wheeler.py) * [Huffman](compression/huffman.py) * [Lempel Ziv](compression/lempel_ziv.py) * [Lempel Ziv Decompress](compression/lempel_ziv_decompress.py) * [Lz77](compression/lz77.py) * [Peak Signal To Noise Ratio](compression/peak_signal_to_noise_ratio.py) * [Run Length Encoding](compression/run_length_encoding.py) ## Computer Vision * [Flip Augmentation](computer_vision/flip_augmentation.py) * [Haralick Descriptors](computer_vision/haralick_descriptors.py) * [Harris Corner](computer_vision/harris_corner.py) * [Horn Schunck](computer_vision/horn_schunck.py) * [Mean Threshold](computer_vision/mean_threshold.py) * [Mosaic Augmentation](computer_vision/mosaic_augmentation.py) * [Pooling Functions](computer_vision/pooling_functions.py) ## Conversions * [Astronomical Length Scale Conversion](conversions/astronomical_length_scale_conversion.py) * [Binary To Decimal](conversions/binary_to_decimal.py) * [Binary To Hexadecimal](conversions/binary_to_hexadecimal.py) * [Binary To Octal](conversions/binary_to_octal.py) * [Convert Number To Words](conversions/convert_number_to_words.py) * [Decimal To Any](conversions/decimal_to_any.py) * [Decimal To Binary](conversions/decimal_to_binary.py) * [Decimal To Hexadecimal](conversions/decimal_to_hexadecimal.py) * [Decimal To Octal](conversions/decimal_to_octal.py) * [Energy Conversions](conversions/energy_conversions.py) * [Excel Title To Column](conversions/excel_title_to_column.py) * [Hex To Bin](conversions/hex_to_bin.py) * [Hexadecimal To Decimal](conversions/hexadecimal_to_decimal.py) * [Ipv4 Conversion](conversions/ipv4_conversion.py) * [Length Conversion](conversions/length_conversion.py) * [Molecular Chemistry](conversions/molecular_chemistry.py) * [Octal To Binary](conversions/octal_to_binary.py) * [Octal To Decimal](conversions/octal_to_decimal.py) * [Octal To Hexadecimal](conversions/octal_to_hexadecimal.py) * [Prefix Conversions](conversions/prefix_conversions.py) * [Prefix Conversions String](conversions/prefix_conversions_string.py) * [Pressure Conversions](conversions/pressure_conversions.py) * [Rgb Cmyk Conversion](conversions/rgb_cmyk_conversion.py) * [Rgb Hsv Conversion](conversions/rgb_hsv_conversion.py) * [Roman Numerals](conversions/roman_numerals.py) * [Speed Conversions](conversions/speed_conversions.py) * [Temperature Conversions](conversions/temperature_conversions.py) * [Time Conversions](conversions/time_conversions.py) * [Volume Conversions](conversions/volume_conversions.py) * [Weight Conversion](conversions/weight_conversion.py) ## Data Structures * Arrays * [Equilibrium Index In Array](data_structures/arrays/equilibrium_index_in_array.py) * [Find Triplets With 0 Sum](data_structures/arrays/find_triplets_with_0_sum.py) * [Index 2D Array In 1D](data_structures/arrays/index_2d_array_in_1d.py) * [Kth Largest Element](data_structures/arrays/kth_largest_element.py) * [Median Two Array](data_structures/arrays/median_two_array.py) * [Monotonic Array](data_structures/arrays/monotonic_array.py) * [Pairs With Given Sum](data_structures/arrays/pairs_with_given_sum.py) * [Permutations](data_structures/arrays/permutations.py) * [Prefix Sum](data_structures/arrays/prefix_sum.py) * [Product Sum](data_structures/arrays/product_sum.py) * [Sparse Table](data_structures/arrays/sparse_table.py) * [Sudoku Solver](data_structures/arrays/sudoku_solver.py) * Binary Tree * [Avl Tree](data_structures/binary_tree/avl_tree.py) * [Basic Binary Tree](data_structures/binary_tree/basic_binary_tree.py) * [Binary Search Tree](data_structures/binary_tree/binary_search_tree.py) * [Binary Search Tree Recursive](data_structures/binary_tree/binary_search_tree_recursive.py) * [Binary Tree Mirror](data_structures/binary_tree/binary_tree_mirror.py) * [Binary Tree Node Sum](data_structures/binary_tree/binary_tree_node_sum.py) * [Binary Tree Path Sum](data_structures/binary_tree/binary_tree_path_sum.py) * [Binary Tree Traversals](data_structures/binary_tree/binary_tree_traversals.py) * [Diameter Of Binary Tree](data_structures/binary_tree/diameter_of_binary_tree.py) * [Diff Views Of Binary Tree](data_structures/binary_tree/diff_views_of_binary_tree.py) * [Distribute Coins](data_structures/binary_tree/distribute_coins.py) * [Fenwick Tree](data_structures/binary_tree/fenwick_tree.py) * [Flatten Binarytree To Linkedlist](data_structures/binary_tree/flatten_binarytree_to_linkedlist.py) * [Floor And Ceiling](data_structures/binary_tree/floor_and_ceiling.py) * [Inorder Tree Traversal 2022](data_structures/binary_tree/inorder_tree_traversal_2022.py) * [Is Sorted](data_structures/binary_tree/is_sorted.py) * [Is Sum Tree](data_structures/binary_tree/is_sum_tree.py) * [Lazy Segment Tree](data_structures/binary_tree/lazy_segment_tree.py) * [Lowest Common Ancestor](data_structures/binary_tree/lowest_common_ancestor.py) * [Maximum Fenwick Tree](data_structures/binary_tree/maximum_fenwick_tree.py) * [Merge Two Binary Trees](data_structures/binary_tree/merge_two_binary_trees.py) * [Mirror Binary Tree](data_structures/binary_tree/mirror_binary_tree.py) * [Non Recursive Segment Tree](data_structures/binary_tree/non_recursive_segment_tree.py) * [Number Of Possible Binary Trees](data_structures/binary_tree/number_of_possible_binary_trees.py) * [Red Black Tree](data_structures/binary_tree/red_black_tree.py) * [Segment Tree](data_structures/binary_tree/segment_tree.py) * [Segment Tree Other](data_structures/binary_tree/segment_tree_other.py) * [Serialize Deserialize Binary Tree](data_structures/binary_tree/serialize_deserialize_binary_tree.py) * [Symmetric Tree](data_structures/binary_tree/symmetric_tree.py) * [Treap](data_structures/binary_tree/treap.py) * [Wavelet Tree](data_structures/binary_tree/wavelet_tree.py) * Disjoint Set * [Alternate Disjoint Set](data_structures/disjoint_set/alternate_disjoint_set.py) * [Disjoint Set](data_structures/disjoint_set/disjoint_set.py) * Hashing * [Bloom Filter](data_structures/hashing/bloom_filter.py) * [Double Hash](data_structures/hashing/double_hash.py) * [Hash Map](data_structures/hashing/hash_map.py) * [Hash Table](data_structures/hashing/hash_table.py) * [Hash Table With Linked List](data_structures/hashing/hash_table_with_linked_list.py) * Number Theory * [Prime Numbers](data_structures/hashing/number_theory/prime_numbers.py) * [Quadratic Probing](data_structures/hashing/quadratic_probing.py) * Tests * [Test Hash Map](data_structures/hashing/tests/test_hash_map.py) * Heap * [Binomial Heap](data_structures/heap/binomial_heap.py) * [Heap](data_structures/heap/heap.py) * [Heap Generic](data_structures/heap/heap_generic.py) * [Max Heap](data_structures/heap/max_heap.py) * [Min Heap](data_structures/heap/min_heap.py) * [Randomized Heap](data_structures/heap/randomized_heap.py) * [Skew Heap](data_structures/heap/skew_heap.py) * Linked List * [Circular Linked List](data_structures/linked_list/circular_linked_list.py) * [Deque Doubly](data_structures/linked_list/deque_doubly.py) * [Doubly Linked List](data_structures/linked_list/doubly_linked_list.py) * [Doubly Linked List Two](data_structures/linked_list/doubly_linked_list_two.py) * [Floyds Cycle Detection](data_structures/linked_list/floyds_cycle_detection.py) * [From Sequence](data_structures/linked_list/from_sequence.py) * [Has Loop](data_structures/linked_list/has_loop.py) * [Is Palindrome](data_structures/linked_list/is_palindrome.py) * [Merge Two Lists](data_structures/linked_list/merge_two_lists.py) * [Middle Element Of Linked List](data_structures/linked_list/middle_element_of_linked_list.py) * [Print Reverse](data_structures/linked_list/print_reverse.py) * [Reverse K Group](data_structures/linked_list/reverse_k_group.py) * [Rotate To The Right](data_structures/linked_list/rotate_to_the_right.py) * [Singly Linked List](data_structures/linked_list/singly_linked_list.py) * [Skip List](data_structures/linked_list/skip_list.py) * [Swap Nodes](data_structures/linked_list/swap_nodes.py) * Queue * [Circular Queue](data_structures/queue/circular_queue.py) * [Circular Queue Linked List](data_structures/queue/circular_queue_linked_list.py) * [Double Ended Queue](data_structures/queue/double_ended_queue.py) * [Linked Queue](data_structures/queue/linked_queue.py) * [Priority Queue Using List](data_structures/queue/priority_queue_using_list.py) * [Queue By List](data_structures/queue/queue_by_list.py) * [Queue By Two Stacks](data_structures/queue/queue_by_two_stacks.py) * [Queue On Pseudo Stack](data_structures/queue/queue_on_pseudo_stack.py) * Stacks * [Balanced Parentheses](data_structures/stacks/balanced_parentheses.py) * [Dijkstras Two Stack Algorithm](data_structures/stacks/dijkstras_two_stack_algorithm.py) * [Infix To Postfix Conversion](data_structures/stacks/infix_to_postfix_conversion.py) * [Infix To Prefix Conversion](data_structures/stacks/infix_to_prefix_conversion.py) * [Next Greater Element](data_structures/stacks/next_greater_element.py) * [Postfix Evaluation](data_structures/stacks/postfix_evaluation.py) * [Prefix Evaluation](data_structures/stacks/prefix_evaluation.py) * [Stack](data_structures/stacks/stack.py) * [Stack Using Two Queues](data_structures/stacks/stack_using_two_queues.py) * [Stack With Doubly Linked List](data_structures/stacks/stack_with_doubly_linked_list.py) * [Stack With Singly Linked List](data_structures/stacks/stack_with_singly_linked_list.py) * [Stock Span Problem](data_structures/stacks/stock_span_problem.py) * Trie * [Radix Tree](data_structures/trie/radix_tree.py) * [Trie](data_structures/trie/trie.py) ## Digital Image Processing * [Change Brightness](digital_image_processing/change_brightness.py) * [Change Contrast](digital_image_processing/change_contrast.py) * [Convert To Negative](digital_image_processing/convert_to_negative.py) * Dithering * [Burkes](digital_image_processing/dithering/burkes.py) * Edge Detection * [Canny](digital_image_processing/edge_detection/canny.py) * Filters * [Bilateral Filter](digital_image_processing/filters/bilateral_filter.py) * [Convolve](digital_image_processing/filters/convolve.py) * [Gabor Filter](digital_image_processing/filters/gabor_filter.py) * [Gaussian Filter](digital_image_processing/filters/gaussian_filter.py) * [Laplacian Filter](digital_image_processing/filters/laplacian_filter.py) * [Local Binary Pattern](digital_image_processing/filters/local_binary_pattern.py) * [Median Filter](digital_image_processing/filters/median_filter.py) * [Sobel Filter](digital_image_processing/filters/sobel_filter.py) * Histogram Equalization * [Histogram Stretch](digital_image_processing/histogram_equalization/histogram_stretch.py) * [Index Calculation](digital_image_processing/index_calculation.py) * Morphological Operations * [Dilation Operation](digital_image_processing/morphological_operations/dilation_operation.py) * [Erosion Operation](digital_image_processing/morphological_operations/erosion_operation.py) * Resize * [Resize](digital_image_processing/resize/resize.py) * Rotation * [Rotation](digital_image_processing/rotation/rotation.py) * [Sepia](digital_image_processing/sepia.py) * [Test Digital Image Processing](digital_image_processing/test_digital_image_processing.py) ## Divide And Conquer * [Closest Pair Of Points](divide_and_conquer/closest_pair_of_points.py) * [Convex Hull](divide_and_conquer/convex_hull.py) * [Heaps Algorithm](divide_and_conquer/heaps_algorithm.py) * [Heaps Algorithm Iterative](divide_and_conquer/heaps_algorithm_iterative.py) * [Inversions](divide_and_conquer/inversions.py) * [Kth Order Statistic](divide_and_conquer/kth_order_statistic.py) * [Max Difference Pair](divide_and_conquer/max_difference_pair.py) * [Max Subarray](divide_and_conquer/max_subarray.py) * [Mergesort](divide_and_conquer/mergesort.py) * [Peak](divide_and_conquer/peak.py) * [Power](divide_and_conquer/power.py) * [Strassen Matrix Multiplication](divide_and_conquer/strassen_matrix_multiplication.py) ## Dynamic Programming * [Abbreviation](dynamic_programming/abbreviation.py) * [All Construct](dynamic_programming/all_construct.py) * [Bitmask](dynamic_programming/bitmask.py) * [Catalan Numbers](dynamic_programming/catalan_numbers.py) * [Climbing Stairs](dynamic_programming/climbing_stairs.py) * [Combination Sum Iv](dynamic_programming/combination_sum_iv.py) * [Edit Distance](dynamic_programming/edit_distance.py) * [Factorial](dynamic_programming/factorial.py) * [Fast Fibonacci](dynamic_programming/fast_fibonacci.py) * [Fibonacci](dynamic_programming/fibonacci.py) * [Fizz Buzz](dynamic_programming/fizz_buzz.py) * [Floyd Warshall](dynamic_programming/floyd_warshall.py) * [Integer Partition](dynamic_programming/integer_partition.py) * [Iterating Through Submasks](dynamic_programming/iterating_through_submasks.py) * [Knapsack](dynamic_programming/knapsack.py) * [Largest Divisible Subset](dynamic_programming/largest_divisible_subset.py) * [Longest Common Subsequence](dynamic_programming/longest_common_subsequence.py) * [Longest Common Substring](dynamic_programming/longest_common_substring.py) * [Longest Increasing Subsequence](dynamic_programming/longest_increasing_subsequence.py) * [Longest Increasing Subsequence O(Nlogn)](dynamic_programming/longest_increasing_subsequence_o(nlogn).py) * [Longest Palindromic Subsequence](dynamic_programming/longest_palindromic_subsequence.py) * [Matrix Chain Multiplication](dynamic_programming/matrix_chain_multiplication.py) * [Matrix Chain Order](dynamic_programming/matrix_chain_order.py) * [Max Non Adjacent Sum](dynamic_programming/max_non_adjacent_sum.py) * [Max Product Subarray](dynamic_programming/max_product_subarray.py) * [Max Subarray Sum](dynamic_programming/max_subarray_sum.py) * [Min Distance Up Bottom](dynamic_programming/min_distance_up_bottom.py) * [Minimum Coin Change](dynamic_programming/minimum_coin_change.py) * [Minimum Cost Path](dynamic_programming/minimum_cost_path.py) * [Minimum Partition](dynamic_programming/minimum_partition.py) * [Minimum Size Subarray Sum](dynamic_programming/minimum_size_subarray_sum.py) * [Minimum Squares To Represent A Number](dynamic_programming/minimum_squares_to_represent_a_number.py) * [Minimum Steps To One](dynamic_programming/minimum_steps_to_one.py) * [Minimum Tickets Cost](dynamic_programming/minimum_tickets_cost.py) * [Optimal Binary Search Tree](dynamic_programming/optimal_binary_search_tree.py) * [Palindrome Partitioning](dynamic_programming/palindrome_partitioning.py) * [Regex Match](dynamic_programming/regex_match.py) * [Rod Cutting](dynamic_programming/rod_cutting.py) * [Smith Waterman](dynamic_programming/smith_waterman.py) * [Subset Generation](dynamic_programming/subset_generation.py) * [Sum Of Subset](dynamic_programming/sum_of_subset.py) * [Trapped Water](dynamic_programming/trapped_water.py) * [Tribonacci](dynamic_programming/tribonacci.py) * [Viterbi](dynamic_programming/viterbi.py) * [Wildcard Matching](dynamic_programming/wildcard_matching.py) * [Word Break](dynamic_programming/word_break.py) ## Electronics * [Apparent Power](electronics/apparent_power.py) * [Builtin Voltage](electronics/builtin_voltage.py) * [Capacitor Equivalence](electronics/capacitor_equivalence.py) * [Carrier Concentration](electronics/carrier_concentration.py) * [Charging Capacitor](electronics/charging_capacitor.py) * [Charging Inductor](electronics/charging_inductor.py) * [Circular Convolution](electronics/circular_convolution.py) * [Coulombs Law](electronics/coulombs_law.py) * [Electric Conductivity](electronics/electric_conductivity.py) * [Electric Power](electronics/electric_power.py) * [Electrical Impedance](electronics/electrical_impedance.py) * [Ic 555 Timer](electronics/ic_555_timer.py) * [Ind Reactance](electronics/ind_reactance.py) * [Ohms Law](electronics/ohms_law.py) * [Real And Reactive Power](electronics/real_and_reactive_power.py) * [Resistor Color Code](electronics/resistor_color_code.py) * [Resistor Equivalence](electronics/resistor_equivalence.py) * [Resonant Frequency](electronics/resonant_frequency.py) * [Wheatstone Bridge](electronics/wheatstone_bridge.py) ## File Transfer * [Receive File](file_transfer/receive_file.py) * [Send File](file_transfer/send_file.py) * Tests * [Test Send File](file_transfer/tests/test_send_file.py) ## Financial * [Equated Monthly Installments](financial/equated_monthly_installments.py) * [Exponential Moving Average](financial/exponential_moving_average.py) * [Interest](financial/interest.py) * [Present Value](financial/present_value.py) * [Price Plus Tax](financial/price_plus_tax.py) * [Simple Moving Average](financial/simple_moving_average.py) ## Fractals * [Julia Sets](fractals/julia_sets.py) * [Koch Snowflake](fractals/koch_snowflake.py) * [Mandelbrot](fractals/mandelbrot.py) * [Sierpinski Triangle](fractals/sierpinski_triangle.py) ## Fuzzy Logic * [Fuzzy Operations](fuzzy_logic/fuzzy_operations.py) ## Genetic Algorithm * [Basic String](genetic_algorithm/basic_string.py) ## Geodesy * [Haversine Distance](geodesy/haversine_distance.py) * [Lamberts Ellipsoidal Distance](geodesy/lamberts_ellipsoidal_distance.py) ## Graphics * [Bezier Curve](graphics/bezier_curve.py) * [Vector3 For 2D Rendering](graphics/vector3_for_2d_rendering.py) ## Graphs * [A Star](graphs/a_star.py) * [Articulation Points](graphs/articulation_points.py) * [Basic Graphs](graphs/basic_graphs.py) * [Bellman Ford](graphs/bellman_ford.py) * [Bi Directional Dijkstra](graphs/bi_directional_dijkstra.py) * [Bidirectional A Star](graphs/bidirectional_a_star.py) * [Bidirectional Breadth First Search](graphs/bidirectional_breadth_first_search.py) * [Boruvka](graphs/boruvka.py) * [Breadth First Search](graphs/breadth_first_search.py) * [Breadth First Search 2](graphs/breadth_first_search_2.py) * [Breadth First Search Shortest Path](graphs/breadth_first_search_shortest_path.py) * [Breadth First Search Shortest Path 2](graphs/breadth_first_search_shortest_path_2.py) * [Breadth First Search Zero One Shortest Path](graphs/breadth_first_search_zero_one_shortest_path.py) * [Check Bipatrite](graphs/check_bipatrite.py) * [Check Cycle](graphs/check_cycle.py) * [Connected Components](graphs/connected_components.py) * [Deep Clone Graph](graphs/deep_clone_graph.py) * [Depth First Search](graphs/depth_first_search.py) * [Depth First Search 2](graphs/depth_first_search_2.py) * [Dijkstra](graphs/dijkstra.py) * [Dijkstra 2](graphs/dijkstra_2.py) * [Dijkstra Algorithm](graphs/dijkstra_algorithm.py) * [Dijkstra Alternate](graphs/dijkstra_alternate.py) * [Dijkstra Binary Grid](graphs/dijkstra_binary_grid.py) * [Dinic](graphs/dinic.py) * [Directed And Undirected (Weighted) Graph](graphs/directed_and_undirected_(weighted)_graph.py) * [Edmonds Karp Multiple Source And Sink](graphs/edmonds_karp_multiple_source_and_sink.py) * [Eulerian Path And Circuit For Undirected Graph](graphs/eulerian_path_and_circuit_for_undirected_graph.py) * [Even Tree](graphs/even_tree.py) * [Finding Bridges](graphs/finding_bridges.py) * [Frequent Pattern Graph Miner](graphs/frequent_pattern_graph_miner.py) * [G Topological Sort](graphs/g_topological_sort.py) * [Gale Shapley Bigraph](graphs/gale_shapley_bigraph.py) * [Graph Adjacency List](graphs/graph_adjacency_list.py) * [Graph Adjacency Matrix](graphs/graph_adjacency_matrix.py) * [Graph List](graphs/graph_list.py) * [Graphs Floyd Warshall](graphs/graphs_floyd_warshall.py) * [Greedy Best First](graphs/greedy_best_first.py) * [Greedy Min Vertex Cover](graphs/greedy_min_vertex_cover.py) * [Kahns Algorithm Long](graphs/kahns_algorithm_long.py) * [Kahns Algorithm Topo](graphs/kahns_algorithm_topo.py) * [Karger](graphs/karger.py) * [Markov Chain](graphs/markov_chain.py) * [Matching Min Vertex Cover](graphs/matching_min_vertex_cover.py) * [Minimum Path Sum](graphs/minimum_path_sum.py) * [Minimum Spanning Tree Boruvka](graphs/minimum_spanning_tree_boruvka.py) * [Minimum Spanning Tree Kruskal](graphs/minimum_spanning_tree_kruskal.py) * [Minimum Spanning Tree Kruskal2](graphs/minimum_spanning_tree_kruskal2.py) * [Minimum Spanning Tree Prims](graphs/minimum_spanning_tree_prims.py) * [Minimum Spanning Tree Prims2](graphs/minimum_spanning_tree_prims2.py) * [Multi Heuristic Astar](graphs/multi_heuristic_astar.py) * [Page Rank](graphs/page_rank.py) * [Prim](graphs/prim.py) * [Random Graph Generator](graphs/random_graph_generator.py) * [Scc Kosaraju](graphs/scc_kosaraju.py) * [Strongly Connected Components](graphs/strongly_connected_components.py) * [Tarjans Scc](graphs/tarjans_scc.py) * Tests * [Test Min Spanning Tree Kruskal](graphs/tests/test_min_spanning_tree_kruskal.py) * [Test Min Spanning Tree Prim](graphs/tests/test_min_spanning_tree_prim.py) ## Greedy Methods * [Best Time To Buy And Sell Stock](greedy_methods/best_time_to_buy_and_sell_stock.py) * [Fractional Cover Problem](greedy_methods/fractional_cover_problem.py) * [Fractional Knapsack](greedy_methods/fractional_knapsack.py) * [Fractional Knapsack 2](greedy_methods/fractional_knapsack_2.py) * [Gas Station](greedy_methods/gas_station.py) * [Minimum Coin Change](greedy_methods/minimum_coin_change.py) * [Minimum Waiting Time](greedy_methods/minimum_waiting_time.py) * [Optimal Merge Pattern](greedy_methods/optimal_merge_pattern.py) ## Hashes * [Adler32](hashes/adler32.py) * [Chaos Machine](hashes/chaos_machine.py) * [Djb2](hashes/djb2.py) * [Elf](hashes/elf.py) * [Enigma Machine](hashes/enigma_machine.py) * [Fletcher16](hashes/fletcher16.py) * [Hamming Code](hashes/hamming_code.py) * [Luhn](hashes/luhn.py) * [Md5](hashes/md5.py) * [Sdbm](hashes/sdbm.py) * [Sha1](hashes/sha1.py) * [Sha256](hashes/sha256.py) ## Knapsack * [Greedy Knapsack](knapsack/greedy_knapsack.py) * [Knapsack](knapsack/knapsack.py) * [Recursive Approach Knapsack](knapsack/recursive_approach_knapsack.py) * Tests * [Test Greedy Knapsack](knapsack/tests/test_greedy_knapsack.py) * [Test Knapsack](knapsack/tests/test_knapsack.py) ## Linear Algebra * [Gaussian Elimination](linear_algebra/gaussian_elimination.py) * [Jacobi Iteration Method](linear_algebra/jacobi_iteration_method.py) * [Lu Decomposition](linear_algebra/lu_decomposition.py) * Src * [Conjugate Gradient](linear_algebra/src/conjugate_gradient.py) * Gaussian Elimination Pivoting * [Gaussian Elimination Pivoting](linear_algebra/src/gaussian_elimination_pivoting/gaussian_elimination_pivoting.py) * [Lib](linear_algebra/src/lib.py) * [Polynom For Points](linear_algebra/src/polynom_for_points.py) * [Power Iteration](linear_algebra/src/power_iteration.py) * [Rank Of Matrix](linear_algebra/src/rank_of_matrix.py) * [Rayleigh Quotient](linear_algebra/src/rayleigh_quotient.py) * [Schur Complement](linear_algebra/src/schur_complement.py) * [Test Linear Algebra](linear_algebra/src/test_linear_algebra.py) * [Transformations 2D](linear_algebra/src/transformations_2d.py) ## Linear Programming * [Simplex](linear_programming/simplex.py) ## Machine Learning * [Apriori Algorithm](machine_learning/apriori_algorithm.py) * [Astar](machine_learning/astar.py) * [Automatic Differentiation](machine_learning/automatic_differentiation.py) * [Data Transformations](machine_learning/data_transformations.py) * [Decision Tree](machine_learning/decision_tree.py) * [Dimensionality Reduction](machine_learning/dimensionality_reduction.py) * Forecasting * [Run](machine_learning/forecasting/run.py) * [Frequent Pattern Growth](machine_learning/frequent_pattern_growth.py) * [Gradient Boosting Classifier](machine_learning/gradient_boosting_classifier.py) * [Gradient Descent](machine_learning/gradient_descent.py) * [K Means Clust](machine_learning/k_means_clust.py) * [K Nearest Neighbours](machine_learning/k_nearest_neighbours.py) * [Linear Discriminant Analysis](machine_learning/linear_discriminant_analysis.py) * [Linear Regression](machine_learning/linear_regression.py) * Local Weighted Learning * [Local Weighted Learning](machine_learning/local_weighted_learning/local_weighted_learning.py) * [Logistic Regression](machine_learning/logistic_regression.py) * [Loss Functions](machine_learning/loss_functions.py) * [Mfcc](machine_learning/mfcc.py) * [Multilayer Perceptron Classifier](machine_learning/multilayer_perceptron_classifier.py) * [Polynomial Regression](machine_learning/polynomial_regression.py) * [Scoring Functions](machine_learning/scoring_functions.py) * [Self Organizing Map](machine_learning/self_organizing_map.py) * [Sequential Minimum Optimization](machine_learning/sequential_minimum_optimization.py) * [Similarity Search](machine_learning/similarity_search.py) * [Support Vector Machines](machine_learning/support_vector_machines.py) * [Word Frequency Functions](machine_learning/word_frequency_functions.py) * [Xgboost Classifier](machine_learning/xgboost_classifier.py) * [Xgboost Regressor](machine_learning/xgboost_regressor.py) ## Maths * [Abs](maths/abs.py) * [Addition Without Arithmetic](maths/addition_without_arithmetic.py) * [Aliquot Sum](maths/aliquot_sum.py) * [Allocation Number](maths/allocation_number.py) * [Arc Length](maths/arc_length.py) * [Area](maths/area.py) * [Area Under Curve](maths/area_under_curve.py) * [Average Absolute Deviation](maths/average_absolute_deviation.py) * [Average Mean](maths/average_mean.py) * [Average Median](maths/average_median.py) * [Average Mode](maths/average_mode.py) * [Bailey Borwein Plouffe](maths/bailey_borwein_plouffe.py) * [Base Neg2 Conversion](maths/base_neg2_conversion.py) * [Basic Maths](maths/basic_maths.py) * [Binary Exponentiation](maths/binary_exponentiation.py) * [Binary Multiplication](maths/binary_multiplication.py) * [Binomial Coefficient](maths/binomial_coefficient.py) * [Binomial Distribution](maths/binomial_distribution.py) * [Ceil](maths/ceil.py) * [Chebyshev Distance](maths/chebyshev_distance.py) * [Check Polygon](maths/check_polygon.py) * [Chinese Remainder Theorem](maths/chinese_remainder_theorem.py) * [Chudnovsky Algorithm](maths/chudnovsky_algorithm.py) * [Collatz Sequence](maths/collatz_sequence.py) * [Combinations](maths/combinations.py) * [Continued Fraction](maths/continued_fraction.py) * [Decimal Isolate](maths/decimal_isolate.py) * [Decimal To Fraction](maths/decimal_to_fraction.py) * [Dodecahedron](maths/dodecahedron.py) * [Double Factorial](maths/double_factorial.py) * [Dual Number Automatic Differentiation](maths/dual_number_automatic_differentiation.py) * [Entropy](maths/entropy.py) * [Euclidean Distance](maths/euclidean_distance.py) * [Euler Method](maths/euler_method.py) * [Euler Modified](maths/euler_modified.py) * [Eulers Totient](maths/eulers_totient.py) * [Extended Euclidean Algorithm](maths/extended_euclidean_algorithm.py) * [Factorial](maths/factorial.py) * [Factors](maths/factors.py) * [Fast Inverse Sqrt](maths/fast_inverse_sqrt.py) * [Fermat Little Theorem](maths/fermat_little_theorem.py) * [Fibonacci](maths/fibonacci.py) * [Find Max](maths/find_max.py) * [Find Min](maths/find_min.py) * [Floor](maths/floor.py) * [Gamma](maths/gamma.py) * [Gaussian](maths/gaussian.py) * [Gaussian Error Linear Unit](maths/gaussian_error_linear_unit.py) * [Gcd Of N Numbers](maths/gcd_of_n_numbers.py) * [Germain Primes](maths/germain_primes.py) * [Greatest Common Divisor](maths/greatest_common_divisor.py) * [Hardy Ramanujanalgo](maths/hardy_ramanujanalgo.py) * [Integer Square Root](maths/integer_square_root.py) * [Interquartile Range](maths/interquartile_range.py) * [Is Int Palindrome](maths/is_int_palindrome.py) * [Is Ip V4 Address Valid](maths/is_ip_v4_address_valid.py) * [Is Square Free](maths/is_square_free.py) * [Jaccard Similarity](maths/jaccard_similarity.py) * [Joint Probability Distribution](maths/joint_probability_distribution.py) * [Josephus Problem](maths/josephus_problem.py) * [Juggler Sequence](maths/juggler_sequence.py) * [Karatsuba](maths/karatsuba.py) * [Kth Lexicographic Permutation](maths/kth_lexicographic_permutation.py) * [Largest Of Very Large Numbers](maths/largest_of_very_large_numbers.py) * [Least Common Multiple](maths/least_common_multiple.py) * [Line Length](maths/line_length.py) * [Liouville Lambda](maths/liouville_lambda.py) * [Lucas Lehmer Primality Test](maths/lucas_lehmer_primality_test.py) * [Lucas Series](maths/lucas_series.py) * [Maclaurin Series](maths/maclaurin_series.py) * [Manhattan Distance](maths/manhattan_distance.py) * [Matrix Exponentiation](maths/matrix_exponentiation.py) * [Max Sum Sliding Window](maths/max_sum_sliding_window.py) * [Median Of Two Arrays](maths/median_of_two_arrays.py) * [Minkowski Distance](maths/minkowski_distance.py) * [Mobius Function](maths/mobius_function.py) * [Modular Division](maths/modular_division.py) * [Modular Exponential](maths/modular_exponential.py) * [Monte Carlo](maths/monte_carlo.py) * [Monte Carlo Dice](maths/monte_carlo_dice.py) * [Number Of Digits](maths/number_of_digits.py) * Numerical Analysis * [Adams Bashforth](maths/numerical_analysis/adams_bashforth.py) * [Bisection](maths/numerical_analysis/bisection.py) * [Bisection 2](maths/numerical_analysis/bisection_2.py) * [Integration By Simpson Approx](maths/numerical_analysis/integration_by_simpson_approx.py) * [Intersection](maths/numerical_analysis/intersection.py) * [Nevilles Method](maths/numerical_analysis/nevilles_method.py) * [Newton Forward Interpolation](maths/numerical_analysis/newton_forward_interpolation.py) * [Newton Raphson](maths/numerical_analysis/newton_raphson.py) * [Numerical Integration](maths/numerical_analysis/numerical_integration.py) * [Runge Kutta](maths/numerical_analysis/runge_kutta.py) * [Runge Kutta Fehlberg 45](maths/numerical_analysis/runge_kutta_fehlberg_45.py) * [Runge Kutta Gills](maths/numerical_analysis/runge_kutta_gills.py) * [Secant Method](maths/numerical_analysis/secant_method.py) * [Simpson Rule](maths/numerical_analysis/simpson_rule.py) * [Square Root](maths/numerical_analysis/square_root.py) * [Odd Sieve](maths/odd_sieve.py) * [Perfect Cube](maths/perfect_cube.py) * [Perfect Number](maths/perfect_number.py) * [Perfect Square](maths/perfect_square.py) * [Persistence](maths/persistence.py) * [Pi Generator](maths/pi_generator.py) * [Pi Monte Carlo Estimation](maths/pi_monte_carlo_estimation.py) * [Points Are Collinear 3D](maths/points_are_collinear_3d.py) * [Pollard Rho](maths/pollard_rho.py) * [Polynomial Evaluation](maths/polynomial_evaluation.py) * Polynomials * [Single Indeterminate Operations](maths/polynomials/single_indeterminate_operations.py) * [Power Using Recursion](maths/power_using_recursion.py) * [Prime Check](maths/prime_check.py) * [Prime Factors](maths/prime_factors.py) * [Prime Numbers](maths/prime_numbers.py) * [Prime Sieve Eratosthenes](maths/prime_sieve_eratosthenes.py) * [Primelib](maths/primelib.py) * [Print Multiplication Table](maths/print_multiplication_table.py) * [Pythagoras](maths/pythagoras.py) * [Qr Decomposition](maths/qr_decomposition.py) * [Quadratic Equations Complex Numbers](maths/quadratic_equations_complex_numbers.py) * [Radians](maths/radians.py) * [Radix2 Fft](maths/radix2_fft.py) * [Remove Digit](maths/remove_digit.py) * [Segmented Sieve](maths/segmented_sieve.py) * Series * [Arithmetic](maths/series/arithmetic.py) * [Geometric](maths/series/geometric.py) * [Geometric Series](maths/series/geometric_series.py) * [Harmonic](maths/series/harmonic.py) * [Harmonic Series](maths/series/harmonic_series.py) * [Hexagonal Numbers](maths/series/hexagonal_numbers.py) * [P Series](maths/series/p_series.py) * [Sieve Of Eratosthenes](maths/sieve_of_eratosthenes.py) * [Sigmoid](maths/sigmoid.py) * [Signum](maths/signum.py) * [Simultaneous Linear Equation Solver](maths/simultaneous_linear_equation_solver.py) * [Sin](maths/sin.py) * [Sock Merchant](maths/sock_merchant.py) * [Softmax](maths/softmax.py) * [Solovay Strassen Primality Test](maths/solovay_strassen_primality_test.py) * Special Numbers * [Armstrong Numbers](maths/special_numbers/armstrong_numbers.py) * [Automorphic Number](maths/special_numbers/automorphic_number.py) * [Bell Numbers](maths/special_numbers/bell_numbers.py) * [Carmichael Number](maths/special_numbers/carmichael_number.py) * [Catalan Number](maths/special_numbers/catalan_number.py) * [Hamming Numbers](maths/special_numbers/hamming_numbers.py) * [Happy Number](maths/special_numbers/happy_number.py) * [Harshad Numbers](maths/special_numbers/harshad_numbers.py) * [Hexagonal Number](maths/special_numbers/hexagonal_number.py) * [Krishnamurthy Number](maths/special_numbers/krishnamurthy_number.py) * [Perfect Number](maths/special_numbers/perfect_number.py) * [Polygonal Numbers](maths/special_numbers/polygonal_numbers.py) * [Pronic Number](maths/special_numbers/pronic_number.py) * [Proth Number](maths/special_numbers/proth_number.py) * [Triangular Numbers](maths/special_numbers/triangular_numbers.py) * [Ugly Numbers](maths/special_numbers/ugly_numbers.py) * [Weird Number](maths/special_numbers/weird_number.py) * [Sum Of Arithmetic Series](maths/sum_of_arithmetic_series.py) * [Sum Of Digits](maths/sum_of_digits.py) * [Sum Of Geometric Progression](maths/sum_of_geometric_progression.py) * [Sum Of Harmonic Series](maths/sum_of_harmonic_series.py) * [Sumset](maths/sumset.py) * [Sylvester Sequence](maths/sylvester_sequence.py) * [Tanh](maths/tanh.py) * [Test Prime Check](maths/test_prime_check.py) * [Three Sum](maths/three_sum.py) * [Trapezoidal Rule](maths/trapezoidal_rule.py) * [Triplet Sum](maths/triplet_sum.py) * [Twin Prime](maths/twin_prime.py) * [Two Pointer](maths/two_pointer.py) * [Two Sum](maths/two_sum.py) * [Volume](maths/volume.py) * [Zellers Congruence](maths/zellers_congruence.py) ## Matrix * [Binary Search Matrix](matrix/binary_search_matrix.py) * [Count Islands In Matrix](matrix/count_islands_in_matrix.py) * [Count Negative Numbers In Sorted Matrix](matrix/count_negative_numbers_in_sorted_matrix.py) * [Count Paths](matrix/count_paths.py) * [Cramers Rule 2X2](matrix/cramers_rule_2x2.py) * [Inverse Of Matrix](matrix/inverse_of_matrix.py) * [Largest Square Area In Matrix](matrix/largest_square_area_in_matrix.py) * [Matrix Class](matrix/matrix_class.py) * [Matrix Multiplication Recursion](matrix/matrix_multiplication_recursion.py) * [Matrix Operation](matrix/matrix_operation.py) * [Max Area Of Island](matrix/max_area_of_island.py) * [Median Matrix](matrix/median_matrix.py) * [Nth Fibonacci Using Matrix Exponentiation](matrix/nth_fibonacci_using_matrix_exponentiation.py) * [Pascal Triangle](matrix/pascal_triangle.py) * [Rotate Matrix](matrix/rotate_matrix.py) * [Searching In Sorted Matrix](matrix/searching_in_sorted_matrix.py) * [Sherman Morrison](matrix/sherman_morrison.py) * [Spiral Print](matrix/spiral_print.py) * Tests * [Test Matrix Operation](matrix/tests/test_matrix_operation.py) * [Validate Sudoku Board](matrix/validate_sudoku_board.py) ## Networking Flow * [Ford Fulkerson](networking_flow/ford_fulkerson.py) * [Minimum Cut](networking_flow/minimum_cut.py) ## Neural Network * [2 Hidden Layers Neural Network](neural_network/2_hidden_layers_neural_network.py) * Activation Functions * [Binary Step](neural_network/activation_functions/binary_step.py) * [Exponential Linear Unit](neural_network/activation_functions/exponential_linear_unit.py) * [Leaky Rectified Linear Unit](neural_network/activation_functions/leaky_rectified_linear_unit.py) * [Mish](neural_network/activation_functions/mish.py) * [Rectified Linear Unit](neural_network/activation_functions/rectified_linear_unit.py) * [Scaled Exponential Linear Unit](neural_network/activation_functions/scaled_exponential_linear_unit.py) * [Soboleva Modified Hyperbolic Tangent](neural_network/activation_functions/soboleva_modified_hyperbolic_tangent.py) * [Softplus](neural_network/activation_functions/softplus.py) * [Squareplus](neural_network/activation_functions/squareplus.py) * [Swish](neural_network/activation_functions/swish.py) * [Back Propagation Neural Network](neural_network/back_propagation_neural_network.py) * [Convolution Neural Network](neural_network/convolution_neural_network.py) * [Simple Neural Network](neural_network/simple_neural_network.py) ## Other * [Activity Selection](other/activity_selection.py) * [Alternative List Arrange](other/alternative_list_arrange.py) * [Bankers Algorithm](other/bankers_algorithm.py) * [Davis Putnam Logemann Loveland](other/davis_putnam_logemann_loveland.py) * [Doomsday](other/doomsday.py) * [Fischer Yates Shuffle](other/fischer_yates_shuffle.py) * [Gauss Easter](other/gauss_easter.py) * [Graham Scan](other/graham_scan.py) * [Greedy](other/greedy.py) * [Guess The Number Search](other/guess_the_number_search.py) * [H Index](other/h_index.py) * [Least Recently Used](other/least_recently_used.py) * [Lfu Cache](other/lfu_cache.py) * [Linear Congruential Generator](other/linear_congruential_generator.py) * [Lru Cache](other/lru_cache.py) * [Magicdiamondpattern](other/magicdiamondpattern.py) * [Majority Vote Algorithm](other/majority_vote_algorithm.py) * [Maximum Subsequence](other/maximum_subsequence.py) * [Nested Brackets](other/nested_brackets.py) * [Number Container System](other/number_container_system.py) * [Password](other/password.py) * [Quine](other/quine.py) * [Scoring Algorithm](other/scoring_algorithm.py) * [Sdes](other/sdes.py) * [Tower Of Hanoi](other/tower_of_hanoi.py) * [Word Search](other/word_search.py) ## Physics * [Altitude Pressure](physics/altitude_pressure.py) * [Archimedes Principle Of Buoyant Force](physics/archimedes_principle_of_buoyant_force.py) * [Basic Orbital Capture](physics/basic_orbital_capture.py) * [Casimir Effect](physics/casimir_effect.py) * [Center Of Mass](physics/center_of_mass.py) * [Centripetal Force](physics/centripetal_force.py) * [Coulombs Law](physics/coulombs_law.py) * [Doppler Frequency](physics/doppler_frequency.py) * [Grahams Law](physics/grahams_law.py) * [Horizontal Projectile Motion](physics/horizontal_projectile_motion.py) * [Hubble Parameter](physics/hubble_parameter.py) * [Ideal Gas Law](physics/ideal_gas_law.py) * [In Static Equilibrium](physics/in_static_equilibrium.py) * [Kinetic Energy](physics/kinetic_energy.py) * [Lens Formulae](physics/lens_formulae.py) * [Lorentz Transformation Four Vector](physics/lorentz_transformation_four_vector.py) * [Malus Law](physics/malus_law.py) * [Mass Energy Equivalence](physics/mass_energy_equivalence.py) * [Mirror Formulae](physics/mirror_formulae.py) * [N Body Simulation](physics/n_body_simulation.py) * [Newtons Law Of Gravitation](physics/newtons_law_of_gravitation.py) * [Newtons Second Law Of Motion](physics/newtons_second_law_of_motion.py) * [Photoelectric Effect](physics/photoelectric_effect.py) * [Potential Energy](physics/potential_energy.py) * [Reynolds Number](physics/reynolds_number.py) * [Rms Speed Of Molecule](physics/rms_speed_of_molecule.py) * [Shear Stress](physics/shear_stress.py) * [Speed Of Sound](physics/speed_of_sound.py) * [Speeds Of Gas Molecules](physics/speeds_of_gas_molecules.py) * [Terminal Velocity](physics/terminal_velocity.py) ## Project Euler * Problem 001 * [Sol1](project_euler/problem_001/sol1.py) * [Sol2](project_euler/problem_001/sol2.py) * [Sol3](project_euler/problem_001/sol3.py) * [Sol4](project_euler/problem_001/sol4.py) * [Sol5](project_euler/problem_001/sol5.py) * [Sol6](project_euler/problem_001/sol6.py) * [Sol7](project_euler/problem_001/sol7.py) * Problem 002 * [Sol1](project_euler/problem_002/sol1.py) * [Sol2](project_euler/problem_002/sol2.py) * [Sol3](project_euler/problem_002/sol3.py) * [Sol4](project_euler/problem_002/sol4.py) * [Sol5](project_euler/problem_002/sol5.py) * Problem 003 * [Sol1](project_euler/problem_003/sol1.py) * [Sol2](project_euler/problem_003/sol2.py) * [Sol3](project_euler/problem_003/sol3.py) * Problem 004 * [Sol1](project_euler/problem_004/sol1.py) * [Sol2](project_euler/problem_004/sol2.py) * Problem 005 * [Sol1](project_euler/problem_005/sol1.py) * [Sol2](project_euler/problem_005/sol2.py) * Problem 006 * [Sol1](project_euler/problem_006/sol1.py) * [Sol2](project_euler/problem_006/sol2.py) * [Sol3](project_euler/problem_006/sol3.py) * [Sol4](project_euler/problem_006/sol4.py) * Problem 007 * [Sol1](project_euler/problem_007/sol1.py) * [Sol2](project_euler/problem_007/sol2.py) * [Sol3](project_euler/problem_007/sol3.py) * Problem 008 * [Sol1](project_euler/problem_008/sol1.py) * [Sol2](project_euler/problem_008/sol2.py) * [Sol3](project_euler/problem_008/sol3.py) * Problem 009 * [Sol1](project_euler/problem_009/sol1.py) * [Sol2](project_euler/problem_009/sol2.py) * [Sol3](project_euler/problem_009/sol3.py) * Problem 010 * [Sol1](project_euler/problem_010/sol1.py) * [Sol2](project_euler/problem_010/sol2.py) * [Sol3](project_euler/problem_010/sol3.py) * Problem 011 * [Sol1](project_euler/problem_011/sol1.py) * [Sol2](project_euler/problem_011/sol2.py) * Problem 012 * [Sol1](project_euler/problem_012/sol1.py) * [Sol2](project_euler/problem_012/sol2.py) * Problem 013 * [Sol1](project_euler/problem_013/sol1.py) * Problem 014 * [Sol1](project_euler/problem_014/sol1.py) * [Sol2](project_euler/problem_014/sol2.py) * Problem 015 * [Sol1](project_euler/problem_015/sol1.py) * Problem 016 * [Sol1](project_euler/problem_016/sol1.py) * [Sol2](project_euler/problem_016/sol2.py) * Problem 017 * [Sol1](project_euler/problem_017/sol1.py) * Problem 018 * [Solution](project_euler/problem_018/solution.py) * Problem 019 * [Sol1](project_euler/problem_019/sol1.py) * Problem 020 * [Sol1](project_euler/problem_020/sol1.py) * [Sol2](project_euler/problem_020/sol2.py) * [Sol3](project_euler/problem_020/sol3.py) * [Sol4](project_euler/problem_020/sol4.py) * Problem 021 * [Sol1](project_euler/problem_021/sol1.py) * Problem 022 * [Sol1](project_euler/problem_022/sol1.py) * [Sol2](project_euler/problem_022/sol2.py) * Problem 023 * [Sol1](project_euler/problem_023/sol1.py) * Problem 024 * [Sol1](project_euler/problem_024/sol1.py) * Problem 025 * [Sol1](project_euler/problem_025/sol1.py) * [Sol2](project_euler/problem_025/sol2.py) * [Sol3](project_euler/problem_025/sol3.py) * Problem 026 * [Sol1](project_euler/problem_026/sol1.py) * Problem 027 * [Sol1](project_euler/problem_027/sol1.py) * Problem 028 * [Sol1](project_euler/problem_028/sol1.py) * Problem 029 * [Sol1](project_euler/problem_029/sol1.py) * Problem 030 * [Sol1](project_euler/problem_030/sol1.py) * Problem 031 * [Sol1](project_euler/problem_031/sol1.py) * [Sol2](project_euler/problem_031/sol2.py) * Problem 032 * [Sol32](project_euler/problem_032/sol32.py) * Problem 033 * [Sol1](project_euler/problem_033/sol1.py) * Problem 034 * [Sol1](project_euler/problem_034/sol1.py) * Problem 035 * [Sol1](project_euler/problem_035/sol1.py) * Problem 036 * [Sol1](project_euler/problem_036/sol1.py) * Problem 037 * [Sol1](project_euler/problem_037/sol1.py) * Problem 038 * [Sol1](project_euler/problem_038/sol1.py) * Problem 039 * [Sol1](project_euler/problem_039/sol1.py) * Problem 040 * [Sol1](project_euler/problem_040/sol1.py) * Problem 041 * [Sol1](project_euler/problem_041/sol1.py) * Problem 042 * [Solution42](project_euler/problem_042/solution42.py) * Problem 043 * [Sol1](project_euler/problem_043/sol1.py) * Problem 044 * [Sol1](project_euler/problem_044/sol1.py) * Problem 045 * [Sol1](project_euler/problem_045/sol1.py) * Problem 046 * [Sol1](project_euler/problem_046/sol1.py) * Problem 047 * [Sol1](project_euler/problem_047/sol1.py) * Problem 048 * [Sol1](project_euler/problem_048/sol1.py) * Problem 049 * [Sol1](project_euler/problem_049/sol1.py) * Problem 050 * [Sol1](project_euler/problem_050/sol1.py) * Problem 051 * [Sol1](project_euler/problem_051/sol1.py) * Problem 052 * [Sol1](project_euler/problem_052/sol1.py) * Problem 053 * [Sol1](project_euler/problem_053/sol1.py) * Problem 054 * [Sol1](project_euler/problem_054/sol1.py) * [Test Poker Hand](project_euler/problem_054/test_poker_hand.py) * Problem 055 * [Sol1](project_euler/problem_055/sol1.py) * Problem 056 * [Sol1](project_euler/problem_056/sol1.py) * Problem 057 * [Sol1](project_euler/problem_057/sol1.py) * Problem 058 * [Sol1](project_euler/problem_058/sol1.py) * Problem 059 * [Sol1](project_euler/problem_059/sol1.py) * Problem 062 * [Sol1](project_euler/problem_062/sol1.py) * Problem 063 * [Sol1](project_euler/problem_063/sol1.py) * Problem 064 * [Sol1](project_euler/problem_064/sol1.py) * Problem 065 * [Sol1](project_euler/problem_065/sol1.py) * Problem 067 * [Sol1](project_euler/problem_067/sol1.py) * [Sol2](project_euler/problem_067/sol2.py) * Problem 068 * [Sol1](project_euler/problem_068/sol1.py) * Problem 069 * [Sol1](project_euler/problem_069/sol1.py) * Problem 070 * [Sol1](project_euler/problem_070/sol1.py) * Problem 071 * [Sol1](project_euler/problem_071/sol1.py) * Problem 072 * [Sol1](project_euler/problem_072/sol1.py) * [Sol2](project_euler/problem_072/sol2.py) * Problem 073 * [Sol1](project_euler/problem_073/sol1.py) * Problem 074 * [Sol1](project_euler/problem_074/sol1.py) * [Sol2](project_euler/problem_074/sol2.py) * Problem 075 * [Sol1](project_euler/problem_075/sol1.py) * Problem 076 * [Sol1](project_euler/problem_076/sol1.py) * Problem 077 * [Sol1](project_euler/problem_077/sol1.py) * Problem 078 * [Sol1](project_euler/problem_078/sol1.py) * Problem 079 * [Sol1](project_euler/problem_079/sol1.py) * Problem 080 * [Sol1](project_euler/problem_080/sol1.py) * Problem 081 * [Sol1](project_euler/problem_081/sol1.py) * Problem 082 * [Sol1](project_euler/problem_082/sol1.py) * Problem 085 * [Sol1](project_euler/problem_085/sol1.py) * Problem 086 * [Sol1](project_euler/problem_086/sol1.py) * Problem 087 * [Sol1](project_euler/problem_087/sol1.py) * Problem 089 * [Sol1](project_euler/problem_089/sol1.py) * Problem 091 * [Sol1](project_euler/problem_091/sol1.py) * Problem 092 * [Sol1](project_euler/problem_092/sol1.py) * Problem 094 * [Sol1](project_euler/problem_094/sol1.py) * Problem 097 * [Sol1](project_euler/problem_097/sol1.py) * Problem 099 * [Sol1](project_euler/problem_099/sol1.py) * Problem 100 * [Sol1](project_euler/problem_100/sol1.py) * Problem 101 * [Sol1](project_euler/problem_101/sol1.py) * Problem 102 * [Sol1](project_euler/problem_102/sol1.py) * Problem 104 * [Sol1](project_euler/problem_104/sol1.py) * Problem 107 * [Sol1](project_euler/problem_107/sol1.py) * Problem 109 * [Sol1](project_euler/problem_109/sol1.py) * Problem 112 * [Sol1](project_euler/problem_112/sol1.py) * Problem 113 * [Sol1](project_euler/problem_113/sol1.py) * Problem 114 * [Sol1](project_euler/problem_114/sol1.py) * Problem 115 * [Sol1](project_euler/problem_115/sol1.py) * Problem 116 * [Sol1](project_euler/problem_116/sol1.py) * Problem 117 * [Sol1](project_euler/problem_117/sol1.py) * Problem 119 * [Sol1](project_euler/problem_119/sol1.py) * Problem 120 * [Sol1](project_euler/problem_120/sol1.py) * Problem 121 * [Sol1](project_euler/problem_121/sol1.py) * Problem 123 * [Sol1](project_euler/problem_123/sol1.py) * Problem 125 * [Sol1](project_euler/problem_125/sol1.py) * Problem 129 * [Sol1](project_euler/problem_129/sol1.py) * Problem 131 * [Sol1](project_euler/problem_131/sol1.py) * Problem 135 * [Sol1](project_euler/problem_135/sol1.py) * Problem 144 * [Sol1](project_euler/problem_144/sol1.py) * Problem 145 * [Sol1](project_euler/problem_145/sol1.py) * Problem 173 * [Sol1](project_euler/problem_173/sol1.py) * Problem 174 * [Sol1](project_euler/problem_174/sol1.py) * Problem 180 * [Sol1](project_euler/problem_180/sol1.py) * Problem 187 * [Sol1](project_euler/problem_187/sol1.py) * Problem 188 * [Sol1](project_euler/problem_188/sol1.py) * Problem 191 * [Sol1](project_euler/problem_191/sol1.py) * Problem 203 * [Sol1](project_euler/problem_203/sol1.py) * Problem 205 * [Sol1](project_euler/problem_205/sol1.py) * Problem 206 * [Sol1](project_euler/problem_206/sol1.py) * Problem 207 * [Sol1](project_euler/problem_207/sol1.py) * Problem 234 * [Sol1](project_euler/problem_234/sol1.py) * Problem 301 * [Sol1](project_euler/problem_301/sol1.py) * Problem 493 * [Sol1](project_euler/problem_493/sol1.py) * Problem 551 * [Sol1](project_euler/problem_551/sol1.py) * Problem 587 * [Sol1](project_euler/problem_587/sol1.py) * Problem 686 * [Sol1](project_euler/problem_686/sol1.py) * Problem 800 * [Sol1](project_euler/problem_800/sol1.py) ## Quantum * [Q Fourier Transform](quantum/q_fourier_transform.py) ## Scheduling * [First Come First Served](scheduling/first_come_first_served.py) * [Highest Response Ratio Next](scheduling/highest_response_ratio_next.py) * [Job Sequence With Deadline](scheduling/job_sequence_with_deadline.py) * [Job Sequencing With Deadline](scheduling/job_sequencing_with_deadline.py) * [Multi Level Feedback Queue](scheduling/multi_level_feedback_queue.py) * [Non Preemptive Shortest Job First](scheduling/non_preemptive_shortest_job_first.py) * [Round Robin](scheduling/round_robin.py) * [Shortest Job First](scheduling/shortest_job_first.py) ## Searches * [Binary Search](searches/binary_search.py) * [Binary Tree Traversal](searches/binary_tree_traversal.py) * [Double Linear Search](searches/double_linear_search.py) * [Double Linear Search Recursion](searches/double_linear_search_recursion.py) * [Fibonacci Search](searches/fibonacci_search.py) * [Hill Climbing](searches/hill_climbing.py) * [Interpolation Search](searches/interpolation_search.py) * [Jump Search](searches/jump_search.py) * [Linear Search](searches/linear_search.py) * [Median Of Medians](searches/median_of_medians.py) * [Quick Select](searches/quick_select.py) * [Sentinel Linear Search](searches/sentinel_linear_search.py) * [Simple Binary Search](searches/simple_binary_search.py) * [Simulated Annealing](searches/simulated_annealing.py) * [Tabu Search](searches/tabu_search.py) * [Ternary Search](searches/ternary_search.py) ## Sorts * [Bead Sort](sorts/bead_sort.py) * [Binary Insertion Sort](sorts/binary_insertion_sort.py) * [Bitonic Sort](sorts/bitonic_sort.py) * [Bogo Sort](sorts/bogo_sort.py) * [Bubble Sort](sorts/bubble_sort.py) * [Bucket Sort](sorts/bucket_sort.py) * [Circle Sort](sorts/circle_sort.py) * [Cocktail Shaker Sort](sorts/cocktail_shaker_sort.py) * [Comb Sort](sorts/comb_sort.py) * [Counting Sort](sorts/counting_sort.py) * [Cycle Sort](sorts/cycle_sort.py) * [Double Sort](sorts/double_sort.py) * [Dutch National Flag Sort](sorts/dutch_national_flag_sort.py) * [Exchange Sort](sorts/exchange_sort.py) * [External Sort](sorts/external_sort.py) * [Gnome Sort](sorts/gnome_sort.py) * [Heap Sort](sorts/heap_sort.py) * [Insertion Sort](sorts/insertion_sort.py) * [Intro Sort](sorts/intro_sort.py) * [Iterative Merge Sort](sorts/iterative_merge_sort.py) * [Merge Insertion Sort](sorts/merge_insertion_sort.py) * [Merge Sort](sorts/merge_sort.py) * [Msd Radix Sort](sorts/msd_radix_sort.py) * [Natural Sort](sorts/natural_sort.py) * [Odd Even Sort](sorts/odd_even_sort.py) * [Odd Even Transposition Parallel](sorts/odd_even_transposition_parallel.py) * [Odd Even Transposition Single Threaded](sorts/odd_even_transposition_single_threaded.py) * [Pancake Sort](sorts/pancake_sort.py) * [Patience Sort](sorts/patience_sort.py) * [Pigeon Sort](sorts/pigeon_sort.py) * [Pigeonhole Sort](sorts/pigeonhole_sort.py) * [Quick Sort](sorts/quick_sort.py) * [Quick Sort 3 Partition](sorts/quick_sort_3_partition.py) * [Radix Sort](sorts/radix_sort.py) * [Recursive Insertion Sort](sorts/recursive_insertion_sort.py) * [Recursive Mergesort Array](sorts/recursive_mergesort_array.py) * [Recursive Quick Sort](sorts/recursive_quick_sort.py) * [Selection Sort](sorts/selection_sort.py) * [Shell Sort](sorts/shell_sort.py) * [Shrink Shell Sort](sorts/shrink_shell_sort.py) * [Slowsort](sorts/slowsort.py) * [Stooge Sort](sorts/stooge_sort.py) * [Strand Sort](sorts/strand_sort.py) * [Tim Sort](sorts/tim_sort.py) * [Topological Sort](sorts/topological_sort.py) * [Tree Sort](sorts/tree_sort.py) * [Unknown Sort](sorts/unknown_sort.py) * [Wiggle Sort](sorts/wiggle_sort.py) ## Strings * [Aho Corasick](strings/aho_corasick.py) * [Alternative String Arrange](strings/alternative_string_arrange.py) * [Anagrams](strings/anagrams.py) * [Autocomplete Using Trie](strings/autocomplete_using_trie.py) * [Barcode Validator](strings/barcode_validator.py) * [Bitap String Match](strings/bitap_string_match.py) * [Boyer Moore Search](strings/boyer_moore_search.py) * [Camel Case To Snake Case](strings/camel_case_to_snake_case.py) * [Can String Be Rearranged As Palindrome](strings/can_string_be_rearranged_as_palindrome.py) * [Capitalize](strings/capitalize.py) * [Check Anagrams](strings/check_anagrams.py) * [Credit Card Validator](strings/credit_card_validator.py) * [Damerau Levenshtein Distance](strings/damerau_levenshtein_distance.py) * [Detecting English Programmatically](strings/detecting_english_programmatically.py) * [Dna](strings/dna.py) * [Edit Distance](strings/edit_distance.py) * [Frequency Finder](strings/frequency_finder.py) * [Hamming Distance](strings/hamming_distance.py) * [Indian Phone Validator](strings/indian_phone_validator.py) * [Is Contains Unique Chars](strings/is_contains_unique_chars.py) * [Is Isogram](strings/is_isogram.py) * [Is Pangram](strings/is_pangram.py) * [Is Polish National Id](strings/is_polish_national_id.py) * [Is Spain National Id](strings/is_spain_national_id.py) * [Is Srilankan Phone Number](strings/is_srilankan_phone_number.py) * [Is Valid Email Address](strings/is_valid_email_address.py) * [Jaro Winkler](strings/jaro_winkler.py) * [Join](strings/join.py) * [Knuth Morris Pratt](strings/knuth_morris_pratt.py) * [Levenshtein Distance](strings/levenshtein_distance.py) * [Lower](strings/lower.py) * [Manacher](strings/manacher.py) * [Min Cost String Conversion](strings/min_cost_string_conversion.py) * [Naive String Search](strings/naive_string_search.py) * [Ngram](strings/ngram.py) * [Palindrome](strings/palindrome.py) * [Pig Latin](strings/pig_latin.py) * [Prefix Function](strings/prefix_function.py) * [Rabin Karp](strings/rabin_karp.py) * [Remove Duplicate](strings/remove_duplicate.py) * [Reverse Letters](strings/reverse_letters.py) * [Reverse Words](strings/reverse_words.py) * [Snake Case To Camel Pascal Case](strings/snake_case_to_camel_pascal_case.py) * [Split](strings/split.py) * [String Switch Case](strings/string_switch_case.py) * [Strip](strings/strip.py) * [Text Justification](strings/text_justification.py) * [Title](strings/title.py) * [Top K Frequent Words](strings/top_k_frequent_words.py) * [Upper](strings/upper.py) * [Wave](strings/wave.py) * [Wildcard Pattern Matching](strings/wildcard_pattern_matching.py) * [Word Occurrence](strings/word_occurrence.py) * [Word Patterns](strings/word_patterns.py) * [Z Function](strings/z_function.py) ## Web Programming * [Co2 Emission](web_programming/co2_emission.py) * [Covid Stats Via Xpath](web_programming/covid_stats_via_xpath.py) * [Crawl Google Results](web_programming/crawl_google_results.py) * [Crawl Google Scholar Citation](web_programming/crawl_google_scholar_citation.py) * [Currency Converter](web_programming/currency_converter.py) * [Current Stock Price](web_programming/current_stock_price.py) * [Current Weather](web_programming/current_weather.py) * [Daily Horoscope](web_programming/daily_horoscope.py) * [Download Images From Google Query](web_programming/download_images_from_google_query.py) * [Emails From Url](web_programming/emails_from_url.py) * [Fetch Anime And Play](web_programming/fetch_anime_and_play.py) * [Fetch Bbc News](web_programming/fetch_bbc_news.py) * [Fetch Github Info](web_programming/fetch_github_info.py) * [Fetch Jobs](web_programming/fetch_jobs.py) * [Fetch Quotes](web_programming/fetch_quotes.py) * [Fetch Well Rx Price](web_programming/fetch_well_rx_price.py) * [Get Amazon Product Data](web_programming/get_amazon_product_data.py) * [Get Imdb Top 250 Movies Csv](web_programming/get_imdb_top_250_movies_csv.py) * [Get Imdbtop](web_programming/get_imdbtop.py) * [Get Ip Geolocation](web_programming/get_ip_geolocation.py) * [Get Top Billionaires](web_programming/get_top_billionaires.py) * [Get Top Hn Posts](web_programming/get_top_hn_posts.py) * [Get User Tweets](web_programming/get_user_tweets.py) * [Giphy](web_programming/giphy.py) * [Instagram Crawler](web_programming/instagram_crawler.py) * [Instagram Pic](web_programming/instagram_pic.py) * [Instagram Video](web_programming/instagram_video.py) * [Nasa Data](web_programming/nasa_data.py) * [Open Google Results](web_programming/open_google_results.py) * [Random Anime Character](web_programming/random_anime_character.py) * [Recaptcha Verification](web_programming/recaptcha_verification.py) * [Reddit](web_programming/reddit.py) * [Search Books By Isbn](web_programming/search_books_by_isbn.py) * [Slack Message](web_programming/slack_message.py) * [Test Fetch Github Info](web_programming/test_fetch_github_info.py) * [World Covid19 Stats](web_programming/world_covid19_stats.py)

## Audio Filters * [Butterworth Filter](audio_filters/butterworth_filter.py) * [Iir Filter](audio_filters/iir_filter.py) * [Show Response](audio_filters/show_response.py) ## Backtracking * [All Combinations](backtracking/all_combinations.py) * [All Permutations](backtracking/all_permutations.py) * [All Subsequences](backtracking/all_subsequences.py) * [Coloring](backtracking/coloring.py) * [Combination Sum](backtracking/combination_sum.py) * [Crossword Puzzle Solver](backtracking/crossword_puzzle_solver.py) * [Generate Parentheses](backtracking/generate_parentheses.py) * [Hamiltonian Cycle](backtracking/hamiltonian_cycle.py) * [Knight Tour](backtracking/knight_tour.py) * [Match Word Pattern](backtracking/match_word_pattern.py) * [Minimax](backtracking/minimax.py) * [N Queens](backtracking/n_queens.py) * [N Queens Math](backtracking/n_queens_math.py) * [Power Sum](backtracking/power_sum.py) * [Rat In Maze](backtracking/rat_in_maze.py) * [Sudoku](backtracking/sudoku.py) * [Sum Of Subsets](backtracking/sum_of_subsets.py) * [Word Search](backtracking/word_search.py) ## Bit Manipulation * [Binary And Operator](bit_manipulation/binary_and_operator.py) * [Binary Coded Decimal](bit_manipulation/binary_coded_decimal.py) * [Binary Count Setbits](bit_manipulation/binary_count_setbits.py) * [Binary Count Trailing Zeros](bit_manipulation/binary_count_trailing_zeros.py) * [Binary Or Operator](bit_manipulation/binary_or_operator.py) * [Binary Shifts](bit_manipulation/binary_shifts.py) * [Binary Twos Complement](bit_manipulation/binary_twos_complement.py) * [Binary Xor Operator](bit_manipulation/binary_xor_operator.py) * [Bitwise Addition Recursive](bit_manipulation/bitwise_addition_recursive.py) * [Count 1S Brian Kernighan Method](bit_manipulation/count_1s_brian_kernighan_method.py) * [Count Number Of One Bits](bit_manipulation/count_number_of_one_bits.py) * [Excess 3 Code](bit_manipulation/excess_3_code.py) * [Find Previous Power Of Two](bit_manipulation/find_previous_power_of_two.py) * [Gray Code Sequence](bit_manipulation/gray_code_sequence.py) * [Highest Set Bit](bit_manipulation/highest_set_bit.py) * [Index Of Rightmost Set Bit](bit_manipulation/index_of_rightmost_set_bit.py) * [Is Even](bit_manipulation/is_even.py) * [Is Power Of Two](bit_manipulation/is_power_of_two.py) * [Largest Pow Of Two Le Num](bit_manipulation/largest_pow_of_two_le_num.py) * [Missing Number](bit_manipulation/missing_number.py) * [Numbers Different Signs](bit_manipulation/numbers_different_signs.py) * [Power Of 4](bit_manipulation/power_of_4.py) * [Reverse Bits](bit_manipulation/reverse_bits.py) * [Single Bit Manipulation Operations](bit_manipulation/single_bit_manipulation_operations.py) * [Swap All Odd And Even Bits](bit_manipulation/swap_all_odd_and_even_bits.py) ## Blockchain * [Diophantine Equation](blockchain/diophantine_equation.py) ## Boolean Algebra * [And Gate](boolean_algebra/and_gate.py) * [Imply Gate](boolean_algebra/imply_gate.py) * [Karnaugh Map Simplification](boolean_algebra/karnaugh_map_simplification.py) * [Multiplexer](boolean_algebra/multiplexer.py) * [Nand Gate](boolean_algebra/nand_gate.py) * [Nimply Gate](boolean_algebra/nimply_gate.py) * [Nor Gate](boolean_algebra/nor_gate.py) * [Not Gate](boolean_algebra/not_gate.py) * [Or Gate](boolean_algebra/or_gate.py) * [Quine Mc Cluskey](boolean_algebra/quine_mc_cluskey.py) * [Xnor Gate](boolean_algebra/xnor_gate.py) * [Xor Gate](boolean_algebra/xor_gate.py) ## Cellular Automata * [Conways Game Of Life](cellular_automata/conways_game_of_life.py) * [Game Of Life](cellular_automata/game_of_life.py) * [Langtons Ant](cellular_automata/langtons_ant.py) * [Nagel Schrekenberg](cellular_automata/nagel_schrekenberg.py) * [One Dimensional](cellular_automata/one_dimensional.py) * [Wa Tor](cellular_automata/wa_tor.py) ## Ciphers * [A1Z26](ciphers/a1z26.py) * [Affine Cipher](ciphers/affine_cipher.py) * [Atbash](ciphers/atbash.py) * [Autokey](ciphers/autokey.py) * [Baconian Cipher](ciphers/baconian_cipher.py) * [Base16](ciphers/base16.py) * [Base32](ciphers/base32.py) * [Base64](ciphers/base64.py) * [Base85](ciphers/base85.py) * [Beaufort Cipher](ciphers/beaufort_cipher.py) * [Bifid](ciphers/bifid.py) * [Brute Force Caesar Cipher](ciphers/brute_force_caesar_cipher.py) * [Caesar Cipher](ciphers/caesar_cipher.py) * [Cryptomath Module](ciphers/cryptomath_module.py) * [Decrypt Caesar With Chi Squared](ciphers/decrypt_caesar_with_chi_squared.py) * [Deterministic Miller Rabin](ciphers/deterministic_miller_rabin.py) * [Diffie](ciphers/diffie.py) * [Diffie Hellman](ciphers/diffie_hellman.py) * [Elgamal Key Generator](ciphers/elgamal_key_generator.py) * [Enigma Machine2](ciphers/enigma_machine2.py) * [Fractionated Morse Cipher](ciphers/fractionated_morse_cipher.py) * [Hill Cipher](ciphers/hill_cipher.py) * [Mixed Keyword Cypher](ciphers/mixed_keyword_cypher.py) * [Mono Alphabetic Ciphers](ciphers/mono_alphabetic_ciphers.py) * [Morse Code](ciphers/morse_code.py) * [Onepad Cipher](ciphers/onepad_cipher.py) * [Permutation Cipher](ciphers/permutation_cipher.py) * [Playfair Cipher](ciphers/playfair_cipher.py) * [Polybius](ciphers/polybius.py) * [Porta Cipher](ciphers/porta_cipher.py) * [Rabin Miller](ciphers/rabin_miller.py) * [Rail Fence Cipher](ciphers/rail_fence_cipher.py) * [Rot13](ciphers/rot13.py) * [Rsa Cipher](ciphers/rsa_cipher.py) * [Rsa Factorization](ciphers/rsa_factorization.py) * [Rsa Key Generator](ciphers/rsa_key_generator.py) * [Running Key Cipher](ciphers/running_key_cipher.py) * [Shuffled Shift Cipher](ciphers/shuffled_shift_cipher.py) * [Simple Keyword Cypher](ciphers/simple_keyword_cypher.py) * [Simple Substitution Cipher](ciphers/simple_substitution_cipher.py) * [Transposition Cipher](ciphers/transposition_cipher.py) * [Transposition Cipher Encrypt Decrypt File](ciphers/transposition_cipher_encrypt_decrypt_file.py) * [Trifid Cipher](ciphers/trifid_cipher.py) * [Vernam Cipher](ciphers/vernam_cipher.py) * [Vigenere Cipher](ciphers/vigenere_cipher.py) * [Xor Cipher](ciphers/xor_cipher.py) ## Compression * [Burrows Wheeler](compression/burrows_wheeler.py) * [Huffman](compression/huffman.py) * [Lempel Ziv](compression/lempel_ziv.py) * [Lempel Ziv Decompress](compression/lempel_ziv_decompress.py) * [Lz77](compression/lz77.py) * [Peak Signal To Noise Ratio](compression/peak_signal_to_noise_ratio.py) * [Run Length Encoding](compression/run_length_encoding.py) ## Computer Vision * [Flip Augmentation](computer_vision/flip_augmentation.py) * [Haralick Descriptors](computer_vision/haralick_descriptors.py) * [Harris Corner](computer_vision/harris_corner.py) * [Horn Schunck](computer_vision/horn_schunck.py) * [Mean Threshold](computer_vision/mean_threshold.py) * [Mosaic Augmentation](computer_vision/mosaic_augmentation.py) * [Pooling Functions](computer_vision/pooling_functions.py) ## Conversions * [Astronomical Length Scale Conversion](conversions/astronomical_length_scale_conversion.py) * [Binary To Decimal](conversions/binary_to_decimal.py) * [Binary To Hexadecimal](conversions/binary_to_hexadecimal.py) * [Binary To Octal](conversions/binary_to_octal.py) * [Convert Number To Words](conversions/convert_number_to_words.py) * [Decimal To Any](conversions/decimal_to_any.py) * [Decimal To Binary](conversions/decimal_to_binary.py) * [Decimal To Hexadecimal](conversions/decimal_to_hexadecimal.py) * [Decimal To Octal](conversions/decimal_to_octal.py) * [Energy Conversions](conversions/energy_conversions.py) * [Excel Title To Column](conversions/excel_title_to_column.py) * [Hex To Bin](conversions/hex_to_bin.py) * [Hexadecimal To Decimal](conversions/hexadecimal_to_decimal.py) * [Ipv4 Conversion](conversions/ipv4_conversion.py) * [Length Conversion](conversions/length_conversion.py) * [Molecular Chemistry](conversions/molecular_chemistry.py) * [Octal To Binary](conversions/octal_to_binary.py) * [Octal To Decimal](conversions/octal_to_decimal.py) * [Octal To Hexadecimal](conversions/octal_to_hexadecimal.py) * [Prefix Conversions](conversions/prefix_conversions.py) * [Prefix Conversions String](conversions/prefix_conversions_string.py) * [Pressure Conversions](conversions/pressure_conversions.py) * [Rgb Cmyk Conversion](conversions/rgb_cmyk_conversion.py) * [Rgb Hsv Conversion](conversions/rgb_hsv_conversion.py) * [Roman Numerals](conversions/roman_numerals.py) * [Speed Conversions](conversions/speed_conversions.py) * [Temperature Conversions](conversions/temperature_conversions.py) * [Time Conversions](conversions/time_conversions.py) * [Volume Conversions](conversions/volume_conversions.py) * [Weight Conversion](conversions/weight_conversion.py) ## Data Structures * Arrays * [Equilibrium Index In Array](data_structures/arrays/equilibrium_index_in_array.py) * [Find Triplets With 0 Sum](data_structures/arrays/find_triplets_with_0_sum.py) * [Index 2D Array In 1D](data_structures/arrays/index_2d_array_in_1d.py) * [Kth Largest Element](data_structures/arrays/kth_largest_element.py) * [Median Two Array](data_structures/arrays/median_two_array.py) * [Monotonic Array](data_structures/arrays/monotonic_array.py) * [Pairs With Given Sum](data_structures/arrays/pairs_with_given_sum.py) * [Permutations](data_structures/arrays/permutations.py) * [Prefix Sum](data_structures/arrays/prefix_sum.py) * [Product Sum](data_structures/arrays/product_sum.py) * [Sparse Table](data_structures/arrays/sparse_table.py) * [Sudoku Solver](data_structures/arrays/sudoku_solver.py) * Binary Tree * [Avl Tree](data_structures/binary_tree/avl_tree.py) * [Basic Binary Tree](data_structures/binary_tree/basic_binary_tree.py) * [Binary Search Tree](data_structures/binary_tree/binary_search_tree.py) * [Binary Search Tree Recursive](data_structures/binary_tree/binary_search_tree_recursive.py) * [Binary Tree Mirror](data_structures/binary_tree/binary_tree_mirror.py) * [Binary Tree Node Sum](data_structures/binary_tree/binary_tree_node_sum.py) * [Binary Tree Path Sum](data_structures/binary_tree/binary_tree_path_sum.py) * [Binary Tree Traversals](data_structures/binary_tree/binary_tree_traversals.py) * [Diameter Of Binary Tree](data_structures/binary_tree/diameter_of_binary_tree.py) * [Diff Views Of Binary Tree](data_structures/binary_tree/diff_views_of_binary_tree.py) * [Distribute Coins](data_structures/binary_tree/distribute_coins.py) * [Fenwick Tree](data_structures/binary_tree/fenwick_tree.py) * [Flatten Binarytree To Linkedlist](data_structures/binary_tree/flatten_binarytree_to_linkedlist.py) * [Floor And Ceiling](data_structures/binary_tree/floor_and_ceiling.py) * [Inorder Tree Traversal 2022](data_structures/binary_tree/inorder_tree_traversal_2022.py) * [Is Sorted](data_structures/binary_tree/is_sorted.py) * [Is Sum Tree](data_structures/binary_tree/is_sum_tree.py) * [Lazy Segment Tree](data_structures/binary_tree/lazy_segment_tree.py) * [Lowest Common Ancestor](data_structures/binary_tree/lowest_common_ancestor.py) * [Maximum Fenwick Tree](data_structures/binary_tree/maximum_fenwick_tree.py) * [Merge Two Binary Trees](data_structures/binary_tree/merge_two_binary_trees.py) * [Mirror Binary Tree](data_structures/binary_tree/mirror_binary_tree.py) * [Non Recursive Segment Tree](data_structures/binary_tree/non_recursive_segment_tree.py) * [Number Of Possible Binary Trees](data_structures/binary_tree/number_of_possible_binary_trees.py) * [Red Black Tree](data_structures/binary_tree/red_black_tree.py) * [Segment Tree](data_structures/binary_tree/segment_tree.py) * [Segment Tree Other](data_structures/binary_tree/segment_tree_other.py) * [Serialize Deserialize Binary Tree](data_structures/binary_tree/serialize_deserialize_binary_tree.py) * [Symmetric Tree](data_structures/binary_tree/symmetric_tree.py) * [Treap](data_structures/binary_tree/treap.py) * [Wavelet Tree](data_structures/binary_tree/wavelet_tree.py) * Disjoint Set * [Alternate Disjoint Set](data_structures/disjoint_set/alternate_disjoint_set.py) * [Disjoint Set](data_structures/disjoint_set/disjoint_set.py) * Hashing * [Bloom Filter](data_structures/hashing/bloom_filter.py) * [Double Hash](data_structures/hashing/double_hash.py) * [Hash Map](data_structures/hashing/hash_map.py) * [Hash Table](data_structures/hashing/hash_table.py) * [Hash Table With Linked List](data_structures/hashing/hash_table_with_linked_list.py) * Number Theory * [Prime Numbers](data_structures/hashing/number_theory/prime_numbers.py) * [Quadratic Probing](data_structures/hashing/quadratic_probing.py) * Tests * [Test Hash Map](data_structures/hashing/tests/test_hash_map.py) * Heap * [Binomial Heap](data_structures/heap/binomial_heap.py) * [Heap](data_structures/heap/heap.py) * [Heap Generic](data_structures/heap/heap_generic.py) * [Max Heap](data_structures/heap/max_heap.py) * [Min Heap](data_structures/heap/min_heap.py) * [Randomized Heap](data_structures/heap/randomized_heap.py) * [Skew Heap](data_structures/heap/skew_heap.py) * Linked List * [Circular Linked List](data_structures/linked_list/circular_linked_list.py) * [Deque Doubly](data_structures/linked_list/deque_doubly.py) * [Doubly Linked List](data_structures/linked_list/doubly_linked_list.py) * [Doubly Linked List Two](data_structures/linked_list/doubly_linked_list_two.py) * [Floyds Cycle Detection](data_structures/linked_list/floyds_cycle_detection.py) * [From Sequence](data_structures/linked_list/from_sequence.py) * [Has Loop](data_structures/linked_list/has_loop.py) * [Is Palindrome](data_structures/linked_list/is_palindrome.py) * [Merge Two Lists](data_structures/linked_list/merge_two_lists.py) * [Middle Element Of Linked List](data_structures/linked_list/middle_element_of_linked_list.py) * [Print Reverse](data_structures/linked_list/print_reverse.py) * [Reverse K Group](data_structures/linked_list/reverse_k_group.py) * [Rotate To The Right](data_structures/linked_list/rotate_to_the_right.py) * [Singly Linked List](data_structures/linked_list/singly_linked_list.py) * [Skip List](data_structures/linked_list/skip_list.py) * [Swap Nodes](data_structures/linked_list/swap_nodes.py) * Queue * [Circular Queue](data_structures/queue/circular_queue.py) * [Circular Queue Linked List](data_structures/queue/circular_queue_linked_list.py) * [Double Ended Queue](data_structures/queue/double_ended_queue.py) * [Linked Queue](data_structures/queue/linked_queue.py) * [Priority Queue Using List](data_structures/queue/priority_queue_using_list.py) * [Queue By List](data_structures/queue/queue_by_list.py) * [Queue By Two Stacks](data_structures/queue/queue_by_two_stacks.py) * [Queue On Pseudo Stack](data_structures/queue/queue_on_pseudo_stack.py) * Stacks * [Balanced Parentheses](data_structures/stacks/balanced_parentheses.py) * [Dijkstras Two Stack Algorithm](data_structures/stacks/dijkstras_two_stack_algorithm.py) * [Infix To Postfix Conversion](data_structures/stacks/infix_to_postfix_conversion.py) * [Infix To Prefix Conversion](data_structures/stacks/infix_to_prefix_conversion.py) * [Next Greater Element](data_structures/stacks/next_greater_element.py) * [Postfix Evaluation](data_structures/stacks/postfix_evaluation.py) * [Prefix Evaluation](data_structures/stacks/prefix_evaluation.py) * [Stack](data_structures/stacks/stack.py) * [Stack Using Two Queues](data_structures/stacks/stack_using_two_queues.py) * [Stack With Doubly Linked List](data_structures/stacks/stack_with_doubly_linked_list.py) * [Stack With Singly Linked List](data_structures/stacks/stack_with_singly_linked_list.py) * [Stock Span Problem](data_structures/stacks/stock_span_problem.py) * Trie * [Radix Tree](data_structures/trie/radix_tree.py) * [Trie](data_structures/trie/trie.py) ## Digital Image Processing * [Change Brightness](digital_image_processing/change_brightness.py) * [Change Contrast](digital_image_processing/change_contrast.py) * [Convert To Negative](digital_image_processing/convert_to_negative.py) * Dithering * [Burkes](digital_image_processing/dithering/burkes.py) * Edge Detection * [Canny](digital_image_processing/edge_detection/canny.py) * Filters * [Bilateral Filter](digital_image_processing/filters/bilateral_filter.py) * [Convolve](digital_image_processing/filters/convolve.py) * [Gabor Filter](digital_image_processing/filters/gabor_filter.py) * [Gaussian Filter](digital_image_processing/filters/gaussian_filter.py) * [Laplacian Filter](digital_image_processing/filters/laplacian_filter.py) * [Local Binary Pattern](digital_image_processing/filters/local_binary_pattern.py) * [Median Filter](digital_image_processing/filters/median_filter.py) * [Sobel Filter](digital_image_processing/filters/sobel_filter.py) * Histogram Equalization * [Histogram Stretch](digital_image_processing/histogram_equalization/histogram_stretch.py) * [Index Calculation](digital_image_processing/index_calculation.py) * Morphological Operations * [Dilation Operation](digital_image_processing/morphological_operations/dilation_operation.py) * [Erosion Operation](digital_image_processing/morphological_operations/erosion_operation.py) * Resize * [Resize](digital_image_processing/resize/resize.py) * Rotation * [Rotation](digital_image_processing/rotation/rotation.py) * [Sepia](digital_image_processing/sepia.py) * [Test Digital Image Processing](digital_image_processing/test_digital_image_processing.py) ## Divide And Conquer * [Closest Pair Of Points](divide_and_conquer/closest_pair_of_points.py) * [Convex Hull](divide_and_conquer/convex_hull.py) * [Heaps Algorithm](divide_and_conquer/heaps_algorithm.py) * [Heaps Algorithm Iterative](divide_and_conquer/heaps_algorithm_iterative.py) * [Inversions](divide_and_conquer/inversions.py) * [Kth Order Statistic](divide_and_conquer/kth_order_statistic.py) * [Max Difference Pair](divide_and_conquer/max_difference_pair.py) * [Max Subarray](divide_and_conquer/max_subarray.py) * [Mergesort](divide_and_conquer/mergesort.py) * [Peak](divide_and_conquer/peak.py) * [Power](divide_and_conquer/power.py) * [Strassen Matrix Multiplication](divide_and_conquer/strassen_matrix_multiplication.py) ## Dynamic Programming * [Abbreviation](dynamic_programming/abbreviation.py) * [All Construct](dynamic_programming/all_construct.py) * [Bitmask](dynamic_programming/bitmask.py) * [Catalan Numbers](dynamic_programming/catalan_numbers.py) * [Climbing Stairs](dynamic_programming/climbing_stairs.py) * [Combination Sum Iv](dynamic_programming/combination_sum_iv.py) * [Edit Distance](dynamic_programming/edit_distance.py) * [Factorial](dynamic_programming/factorial.py) * [Fast Fibonacci](dynamic_programming/fast_fibonacci.py) * [Fibonacci](dynamic_programming/fibonacci.py) * [Fizz Buzz](dynamic_programming/fizz_buzz.py) * [Floyd Warshall](dynamic_programming/floyd_warshall.py) * [Integer Partition](dynamic_programming/integer_partition.py) * [Iterating Through Submasks](dynamic_programming/iterating_through_submasks.py) * [Knapsack](dynamic_programming/knapsack.py) * [Largest Divisible Subset](dynamic_programming/largest_divisible_subset.py) * [Longest Common Subsequence](dynamic_programming/longest_common_subsequence.py) * [Longest Common Substring](dynamic_programming/longest_common_substring.py) * [Longest Increasing Subsequence](dynamic_programming/longest_increasing_subsequence.py) * [Longest Increasing Subsequence O(Nlogn)](dynamic_programming/longest_increasing_subsequence_o(nlogn).py) * [Longest Palindromic Subsequence](dynamic_programming/longest_palindromic_subsequence.py) * [Matrix Chain Multiplication](dynamic_programming/matrix_chain_multiplication.py) * [Matrix Chain Order](dynamic_programming/matrix_chain_order.py) * [Max Non Adjacent Sum](dynamic_programming/max_non_adjacent_sum.py) * [Max Product Subarray](dynamic_programming/max_product_subarray.py) * [Max Subarray Sum](dynamic_programming/max_subarray_sum.py) * [Min Distance Up Bottom](dynamic_programming/min_distance_up_bottom.py) * [Minimum Coin Change](dynamic_programming/minimum_coin_change.py) * [Minimum Cost Path](dynamic_programming/minimum_cost_path.py) * [Minimum Partition](dynamic_programming/minimum_partition.py) * [Minimum Size Subarray Sum](dynamic_programming/minimum_size_subarray_sum.py) * [Minimum Squares To Represent A Number](dynamic_programming/minimum_squares_to_represent_a_number.py) * [Minimum Steps To One](dynamic_programming/minimum_steps_to_one.py) * [Minimum Tickets Cost](dynamic_programming/minimum_tickets_cost.py) * [Optimal Binary Search Tree](dynamic_programming/optimal_binary_search_tree.py) * [Palindrome Partitioning](dynamic_programming/palindrome_partitioning.py) * [Regex Match](dynamic_programming/regex_match.py) * [Rod Cutting](dynamic_programming/rod_cutting.py) * [Smith Waterman](dynamic_programming/smith_waterman.py) * [Subset Generation](dynamic_programming/subset_generation.py) * [Sum Of Subset](dynamic_programming/sum_of_subset.py) * [Trapped Water](dynamic_programming/trapped_water.py) * [Tribonacci](dynamic_programming/tribonacci.py) * [Viterbi](dynamic_programming/viterbi.py) * [Wildcard Matching](dynamic_programming/wildcard_matching.py) * [Word Break](dynamic_programming/word_break.py) ## Electronics * [Apparent Power](electronics/apparent_power.py) * [Builtin Voltage](electronics/builtin_voltage.py) * [Capacitor Equivalence](electronics/capacitor_equivalence.py) * [Carrier Concentration](electronics/carrier_concentration.py) * [Charging Capacitor](electronics/charging_capacitor.py) * [Charging Inductor](electronics/charging_inductor.py) * [Circular Convolution](electronics/circular_convolution.py) * [Coulombs Law](electronics/coulombs_law.py) * [Electric Conductivity](electronics/electric_conductivity.py) * [Electric Power](electronics/electric_power.py) * [Electrical Impedance](electronics/electrical_impedance.py) * [Ic 555 Timer](electronics/ic_555_timer.py) * [Ind Reactance](electronics/ind_reactance.py) * [Ohms Law](electronics/ohms_law.py) * [Real And Reactive Power](electronics/real_and_reactive_power.py) * [Resistor Color Code](electronics/resistor_color_code.py) * [Resistor Equivalence](electronics/resistor_equivalence.py) * [Resonant Frequency](electronics/resonant_frequency.py) * [Wheatstone Bridge](electronics/wheatstone_bridge.py) ## File Transfer * [Receive File](file_transfer/receive_file.py) * [Send File](file_transfer/send_file.py) * Tests * [Test Send File](file_transfer/tests/test_send_file.py) ## Financial * [Equated Monthly Installments](financial/equated_monthly_installments.py) * [Exponential Moving Average](financial/exponential_moving_average.py) * [Interest](financial/interest.py) * [Present Value](financial/present_value.py) * [Price Plus Tax](financial/price_plus_tax.py) * [Simple Moving Average](financial/simple_moving_average.py) ## Fractals * [Julia Sets](fractals/julia_sets.py) * [Koch Snowflake](fractals/koch_snowflake.py) * [Mandelbrot](fractals/mandelbrot.py) * [Sierpinski Triangle](fractals/sierpinski_triangle.py) ## Fuzzy Logic * [Fuzzy Operations](fuzzy_logic/fuzzy_operations.py) ## Genetic Algorithm * [Basic String](genetic_algorithm/basic_string.py) ## Geodesy * [Haversine Distance](geodesy/haversine_distance.py) * [Lamberts Ellipsoidal Distance](geodesy/lamberts_ellipsoidal_distance.py) ## Graphics * [Bezier Curve](graphics/bezier_curve.py) * [Vector3 For 2D Rendering](graphics/vector3_for_2d_rendering.py) ## Graphs * [A Star](graphs/a_star.py) * [Articulation Points](graphs/articulation_points.py) * [Basic Graphs](graphs/basic_graphs.py) * [Bellman Ford](graphs/bellman_ford.py) * [Bi Directional Dijkstra](graphs/bi_directional_dijkstra.py) * [Bidirectional A Star](graphs/bidirectional_a_star.py) * [Bidirectional Breadth First Search](graphs/bidirectional_breadth_first_search.py) * [Boruvka](graphs/boruvka.py) * [Breadth First Search](graphs/breadth_first_search.py) * [Breadth First Search 2](graphs/breadth_first_search_2.py) * [Breadth First Search Shortest Path](graphs/breadth_first_search_shortest_path.py) * [Breadth First Search Shortest Path 2](graphs/breadth_first_search_shortest_path_2.py) * [Breadth First Search Zero One Shortest Path](graphs/breadth_first_search_zero_one_shortest_path.py) * [Check Bipatrite](graphs/check_bipatrite.py) * [Check Cycle](graphs/check_cycle.py) * [Connected Components](graphs/connected_components.py) * [Deep Clone Graph](graphs/deep_clone_graph.py) * [Depth First Search](graphs/depth_first_search.py) * [Depth First Search 2](graphs/depth_first_search_2.py) * [Dijkstra](graphs/dijkstra.py) * [Dijkstra 2](graphs/dijkstra_2.py) * [Dijkstra Algorithm](graphs/dijkstra_algorithm.py) * [Dijkstra Alternate](graphs/dijkstra_alternate.py) * [Dijkstra Binary Grid](graphs/dijkstra_binary_grid.py) * [Dinic](graphs/dinic.py) * [Directed And Undirected (Weighted) Graph](graphs/directed_and_undirected_(weighted)_graph.py) * [Edmonds Karp Multiple Source And Sink](graphs/edmonds_karp_multiple_source_and_sink.py) * [Eulerian Path And Circuit For Undirected Graph](graphs/eulerian_path_and_circuit_for_undirected_graph.py) * [Even Tree](graphs/even_tree.py) * [Finding Bridges](graphs/finding_bridges.py) * [Frequent Pattern Graph Miner](graphs/frequent_pattern_graph_miner.py) * [G Topological Sort](graphs/g_topological_sort.py) * [Gale Shapley Bigraph](graphs/gale_shapley_bigraph.py) * [Graph Adjacency List](graphs/graph_adjacency_list.py) * [Graph Adjacency Matrix](graphs/graph_adjacency_matrix.py) * [Graph List](graphs/graph_list.py) * [Graphs Floyd Warshall](graphs/graphs_floyd_warshall.py) * [Greedy Best First](graphs/greedy_best_first.py) * [Greedy Min Vertex Cover](graphs/greedy_min_vertex_cover.py) * [Kahns Algorithm Long](graphs/kahns_algorithm_long.py) * [Kahns Algorithm Topo](graphs/kahns_algorithm_topo.py) * [Karger](graphs/karger.py) * [Markov Chain](graphs/markov_chain.py) * [Matching Min Vertex Cover](graphs/matching_min_vertex_cover.py) * [Minimum Path Sum](graphs/minimum_path_sum.py) * [Minimum Spanning Tree Boruvka](graphs/minimum_spanning_tree_boruvka.py) * [Minimum Spanning Tree Kruskal](graphs/minimum_spanning_tree_kruskal.py) * [Minimum Spanning Tree Kruskal2](graphs/minimum_spanning_tree_kruskal2.py) * [Minimum Spanning Tree Prims](graphs/minimum_spanning_tree_prims.py) * [Minimum Spanning Tree Prims2](graphs/minimum_spanning_tree_prims2.py) * [Multi Heuristic Astar](graphs/multi_heuristic_astar.py) * [Page Rank](graphs/page_rank.py) * [Prim](graphs/prim.py) * [Random Graph Generator](graphs/random_graph_generator.py) * [Scc Kosaraju](graphs/scc_kosaraju.py) * [Strongly Connected Components](graphs/strongly_connected_components.py) * [Tarjans Scc](graphs/tarjans_scc.py) * Tests * [Test Min Spanning Tree Kruskal](graphs/tests/test_min_spanning_tree_kruskal.py) * [Test Min Spanning Tree Prim](graphs/tests/test_min_spanning_tree_prim.py) ## Greedy Methods * [Best Time To Buy And Sell Stock](greedy_methods/best_time_to_buy_and_sell_stock.py) * [Fractional Cover Problem](greedy_methods/fractional_cover_problem.py) * [Fractional Knapsack](greedy_methods/fractional_knapsack.py) * [Fractional Knapsack 2](greedy_methods/fractional_knapsack_2.py) * [Gas Station](greedy_methods/gas_station.py) * [Minimum Coin Change](greedy_methods/minimum_coin_change.py) * [Minimum Waiting Time](greedy_methods/minimum_waiting_time.py) * [Optimal Merge Pattern](greedy_methods/optimal_merge_pattern.py) ## Hashes * [Adler32](hashes/adler32.py) * [Chaos Machine](hashes/chaos_machine.py) * [Djb2](hashes/djb2.py) * [Elf](hashes/elf.py) * [Enigma Machine](hashes/enigma_machine.py) * [Fletcher16](hashes/fletcher16.py) * [Hamming Code](hashes/hamming_code.py) * [Luhn](hashes/luhn.py) * [Md5](hashes/md5.py) * [Sdbm](hashes/sdbm.py) * [Sha1](hashes/sha1.py) * [Sha256](hashes/sha256.py) ## Knapsack * [Greedy Knapsack](knapsack/greedy_knapsack.py) * [Knapsack](knapsack/knapsack.py) * [Recursive Approach Knapsack](knapsack/recursive_approach_knapsack.py) * Tests * [Test Greedy Knapsack](knapsack/tests/test_greedy_knapsack.py) * [Test Knapsack](knapsack/tests/test_knapsack.py) ## Linear Algebra * [Gaussian Elimination](linear_algebra/gaussian_elimination.py) * [Jacobi Iteration Method](linear_algebra/jacobi_iteration_method.py) * [Lu Decomposition](linear_algebra/lu_decomposition.py) * Src * [Conjugate Gradient](linear_algebra/src/conjugate_gradient.py) * Gaussian Elimination Pivoting * [Gaussian Elimination Pivoting](linear_algebra/src/gaussian_elimination_pivoting/gaussian_elimination_pivoting.py) * [Lib](linear_algebra/src/lib.py) * [Polynom For Points](linear_algebra/src/polynom_for_points.py) * [Power Iteration](linear_algebra/src/power_iteration.py) * [Rank Of Matrix](linear_algebra/src/rank_of_matrix.py) * [Rayleigh Quotient](linear_algebra/src/rayleigh_quotient.py) * [Schur Complement](linear_algebra/src/schur_complement.py) * [Test Linear Algebra](linear_algebra/src/test_linear_algebra.py) * [Transformations 2D](linear_algebra/src/transformations_2d.py) ## Linear Programming * [Simplex](linear_programming/simplex.py) ## Machine Learning * [Apriori Algorithm](machine_learning/apriori_algorithm.py) * [Astar](machine_learning/astar.py) * [Automatic Differentiation](machine_learning/automatic_differentiation.py) * [Data Transformations](machine_learning/data_transformations.py) * [Decision Tree](machine_learning/decision_tree.py) * [Dimensionality Reduction](machine_learning/dimensionality_reduction.py) * Forecasting * [Run](machine_learning/forecasting/run.py) * [Frequent Pattern Growth](machine_learning/frequent_pattern_growth.py) * [Gradient Boosting Classifier](machine_learning/gradient_boosting_classifier.py) * [Gradient Descent](machine_learning/gradient_descent.py) * [K Means Clust](machine_learning/k_means_clust.py) * [K Nearest Neighbours](machine_learning/k_nearest_neighbours.py) * [Linear Discriminant Analysis](machine_learning/linear_discriminant_analysis.py) * [Linear Regression](machine_learning/linear_regression.py) * Local Weighted Learning * [Local Weighted Learning](machine_learning/local_weighted_learning/local_weighted_learning.py) * [Logistic Regression](machine_learning/logistic_regression.py) * [Loss Functions](machine_learning/loss_functions.py) * [Mfcc](machine_learning/mfcc.py) * [Multilayer Perceptron Classifier](machine_learning/multilayer_perceptron_classifier.py) * [Polynomial Regression](machine_learning/polynomial_regression.py) * [Scoring Functions](machine_learning/scoring_functions.py) * [Self Organizing Map](machine_learning/self_organizing_map.py) * [Sequential Minimum Optimization](machine_learning/sequential_minimum_optimization.py) * [Similarity Search](machine_learning/similarity_search.py) * [Support Vector Machines](machine_learning/support_vector_machines.py) * [Word Frequency Functions](machine_learning/word_frequency_functions.py) * [Xgboost Classifier](machine_learning/xgboost_classifier.py) * [Xgboost Regressor](machine_learning/xgboost_regressor.py) ## Maths * [Abs](maths/abs.py) * [Addition Without Arithmetic](maths/addition_without_arithmetic.py) * [Aliquot Sum](maths/aliquot_sum.py) * [Allocation Number](maths/allocation_number.py) * [Arc Length](maths/arc_length.py) * [Area](maths/area.py) * [Area Under Curve](maths/area_under_curve.py) * [Average Absolute Deviation](maths/average_absolute_deviation.py) * [Average Mean](maths/average_mean.py) * [Average Median](maths/average_median.py) * [Average Mode](maths/average_mode.py) * [Bailey Borwein Plouffe](maths/bailey_borwein_plouffe.py) * [Base Neg2 Conversion](maths/base_neg2_conversion.py) * [Basic Maths](maths/basic_maths.py) * [Binary Exponentiation](maths/binary_exponentiation.py) * [Binary Multiplication](maths/binary_multiplication.py) * [Binomial Coefficient](maths/binomial_coefficient.py) * [Binomial Distribution](maths/binomial_distribution.py) * [Ceil](maths/ceil.py) * [Chebyshev Distance](maths/chebyshev_distance.py) * [Check Polygon](maths/check_polygon.py) * [Chinese Remainder Theorem](maths/chinese_remainder_theorem.py) * [Chudnovsky Algorithm](maths/chudnovsky_algorithm.py) * [Collatz Sequence](maths/collatz_sequence.py) * [Combinations](maths/combinations.py) * [Continued Fraction](maths/continued_fraction.py) * [Decimal Isolate](maths/decimal_isolate.py) * [Decimal To Fraction](maths/decimal_to_fraction.py) * [Dodecahedron](maths/dodecahedron.py) * [Double Factorial](maths/double_factorial.py) * [Dual Number Automatic Differentiation](maths/dual_number_automatic_differentiation.py) * [Entropy](maths/entropy.py) * [Euclidean Distance](maths/euclidean_distance.py) * [Euler Method](maths/euler_method.py) * [Euler Modified](maths/euler_modified.py) * [Eulers Totient](maths/eulers_totient.py) * [Extended Euclidean Algorithm](maths/extended_euclidean_algorithm.py) * [Factorial](maths/factorial.py) * [Factors](maths/factors.py) * [Fast Inverse Sqrt](maths/fast_inverse_sqrt.py) * [Fermat Little Theorem](maths/fermat_little_theorem.py) * [Fibonacci](maths/fibonacci.py) * [Find Max](maths/find_max.py) * [Find Min](maths/find_min.py) * [Floor](maths/floor.py) * [Gamma](maths/gamma.py) * [Gaussian](maths/gaussian.py) * [Gaussian Error Linear Unit](maths/gaussian_error_linear_unit.py) * [Gcd Of N Numbers](maths/gcd_of_n_numbers.py) * [Germain Primes](maths/germain_primes.py) * [Greatest Common Divisor](maths/greatest_common_divisor.py) * [Hardy Ramanujanalgo](maths/hardy_ramanujanalgo.py) * [Integer Square Root](maths/integer_square_root.py) * [Interquartile Range](maths/interquartile_range.py) * [Is Int Palindrome](maths/is_int_palindrome.py) * [Is Ip V4 Address Valid](maths/is_ip_v4_address_valid.py) * [Is Square Free](maths/is_square_free.py) * [Jaccard Similarity](maths/jaccard_similarity.py) * [Joint Probability Distribution](maths/joint_probability_distribution.py) * [Josephus Problem](maths/josephus_problem.py) * [Juggler Sequence](maths/juggler_sequence.py) * [Karatsuba](maths/karatsuba.py) * [Kth Lexicographic Permutation](maths/kth_lexicographic_permutation.py) * [Largest Of Very Large Numbers](maths/largest_of_very_large_numbers.py) * [Least Common Multiple](maths/least_common_multiple.py) * [Line Length](maths/line_length.py) * [Liouville Lambda](maths/liouville_lambda.py) * [Lucas Lehmer Primality Test](maths/lucas_lehmer_primality_test.py) * [Lucas Series](maths/lucas_series.py) * [Maclaurin Series](maths/maclaurin_series.py) * [Manhattan Distance](maths/manhattan_distance.py) * [Matrix Exponentiation](maths/matrix_exponentiation.py) * [Max Sum Sliding Window](maths/max_sum_sliding_window.py) * [Median Of Two Arrays](maths/median_of_two_arrays.py) * [Minkowski Distance](maths/minkowski_distance.py) * [Mobius Function](maths/mobius_function.py) * [Modular Division](maths/modular_division.py) * [Modular Exponential](maths/modular_exponential.py) * [Monte Carlo](maths/monte_carlo.py) * [Monte Carlo Dice](maths/monte_carlo_dice.py) * [Number Of Digits](maths/number_of_digits.py) * Numerical Analysis * [Adams Bashforth](maths/numerical_analysis/adams_bashforth.py) * [Bisection](maths/numerical_analysis/bisection.py) * [Bisection 2](maths/numerical_analysis/bisection_2.py) * [Integration By Simpson Approx](maths/numerical_analysis/integration_by_simpson_approx.py) * [Intersection](maths/numerical_analysis/intersection.py) * [Nevilles Method](maths/numerical_analysis/nevilles_method.py) * [Newton Forward Interpolation](maths/numerical_analysis/newton_forward_interpolation.py) * [Newton Raphson](maths/numerical_analysis/newton_raphson.py) * [Numerical Integration](maths/numerical_analysis/numerical_integration.py) * [Runge Kutta](maths/numerical_analysis/runge_kutta.py) * [Runge Kutta Fehlberg 45](maths/numerical_analysis/runge_kutta_fehlberg_45.py) * [Runge Kutta Gills](maths/numerical_analysis/runge_kutta_gills.py) * [Secant Method](maths/numerical_analysis/secant_method.py) * [Simpson Rule](maths/numerical_analysis/simpson_rule.py) * [Square Root](maths/numerical_analysis/square_root.py) * [Odd Sieve](maths/odd_sieve.py) * [Perfect Cube](maths/perfect_cube.py) * [Perfect Number](maths/perfect_number.py) * [Perfect Square](maths/perfect_square.py) * [Persistence](maths/persistence.py) * [Pi Generator](maths/pi_generator.py) * [Pi Monte Carlo Estimation](maths/pi_monte_carlo_estimation.py) * [Points Are Collinear 3D](maths/points_are_collinear_3d.py) * [Pollard Rho](maths/pollard_rho.py) * [Polynomial Evaluation](maths/polynomial_evaluation.py) * Polynomials * [Single Indeterminate Operations](maths/polynomials/single_indeterminate_operations.py) * [Power Using Recursion](maths/power_using_recursion.py) * [Prime Check](maths/prime_check.py) * [Prime Factors](maths/prime_factors.py) * [Prime Numbers](maths/prime_numbers.py) * [Prime Sieve Eratosthenes](maths/prime_sieve_eratosthenes.py) * [Primelib](maths/primelib.py) * [Print Multiplication Table](maths/print_multiplication_table.py) * [Pythagoras](maths/pythagoras.py) * [Qr Decomposition](maths/qr_decomposition.py) * [Quadratic Equations Complex Numbers](maths/quadratic_equations_complex_numbers.py) * [Radians](maths/radians.py) * [Radix2 Fft](maths/radix2_fft.py) * [Remove Digit](maths/remove_digit.py) * [Segmented Sieve](maths/segmented_sieve.py) * Series * [Arithmetic](maths/series/arithmetic.py) * [Geometric](maths/series/geometric.py) * [Geometric Series](maths/series/geometric_series.py) * [Harmonic](maths/series/harmonic.py) * [Harmonic Series](maths/series/harmonic_series.py) * [Hexagonal Numbers](maths/series/hexagonal_numbers.py) * [P Series](maths/series/p_series.py) * [Sieve Of Eratosthenes](maths/sieve_of_eratosthenes.py) * [Sigmoid](maths/sigmoid.py) * [Signum](maths/signum.py) * [Simultaneous Linear Equation Solver](maths/simultaneous_linear_equation_solver.py) * [Sin](maths/sin.py) * [Sock Merchant](maths/sock_merchant.py) * [Softmax](maths/softmax.py) * [Solovay Strassen Primality Test](maths/solovay_strassen_primality_test.py) * Special Numbers * [Armstrong Numbers](maths/special_numbers/armstrong_numbers.py) * [Automorphic Number](maths/special_numbers/automorphic_number.py) * [Bell Numbers](maths/special_numbers/bell_numbers.py) * [Carmichael Number](maths/special_numbers/carmichael_number.py) * [Catalan Number](maths/special_numbers/catalan_number.py) * [Hamming Numbers](maths/special_numbers/hamming_numbers.py) * [Happy Number](maths/special_numbers/happy_number.py) * [Harshad Numbers](maths/special_numbers/harshad_numbers.py) * [Hexagonal Number](maths/special_numbers/hexagonal_number.py) * [Krishnamurthy Number](maths/special_numbers/krishnamurthy_number.py) * [Perfect Number](maths/special_numbers/perfect_number.py) * [Polygonal Numbers](maths/special_numbers/polygonal_numbers.py) * [Pronic Number](maths/special_numbers/pronic_number.py) * [Proth Number](maths/special_numbers/proth_number.py) * [Triangular Numbers](maths/special_numbers/triangular_numbers.py) * [Ugly Numbers](maths/special_numbers/ugly_numbers.py) * [Weird Number](maths/special_numbers/weird_number.py) * [Sum Of Arithmetic Series](maths/sum_of_arithmetic_series.py) * [Sum Of Digits](maths/sum_of_digits.py) * [Sum Of Geometric Progression](maths/sum_of_geometric_progression.py) * [Sum Of Harmonic Series](maths/sum_of_harmonic_series.py) * [Sumset](maths/sumset.py) * [Sylvester Sequence](maths/sylvester_sequence.py) * [Tanh](maths/tanh.py) * [Test Prime Check](maths/test_prime_check.py) * [Three Sum](maths/three_sum.py) * [Trapezoidal Rule](maths/trapezoidal_rule.py) * [Triplet Sum](maths/triplet_sum.py) * [Twin Prime](maths/twin_prime.py) * [Two Pointer](maths/two_pointer.py) * [Two Sum](maths/two_sum.py) * [Volume](maths/volume.py) * [Zellers Congruence](maths/zellers_congruence.py) ## Matrix * [Binary Search Matrix](matrix/binary_search_matrix.py) * [Count Islands In Matrix](matrix/count_islands_in_matrix.py) * [Count Negative Numbers In Sorted Matrix](matrix/count_negative_numbers_in_sorted_matrix.py) * [Count Paths](matrix/count_paths.py) * [Cramers Rule 2X2](matrix/cramers_rule_2x2.py) * [Inverse Of Matrix](matrix/inverse_of_matrix.py) * [Largest Square Area In Matrix](matrix/largest_square_area_in_matrix.py) * [Matrix Class](matrix/matrix_class.py) * [Matrix Multiplication Recursion](matrix/matrix_multiplication_recursion.py) * [Matrix Operation](matrix/matrix_operation.py) * [Max Area Of Island](matrix/max_area_of_island.py) * [Median Matrix](matrix/median_matrix.py) * [Nth Fibonacci Using Matrix Exponentiation](matrix/nth_fibonacci_using_matrix_exponentiation.py) * [Pascal Triangle](matrix/pascal_triangle.py) * [Rotate Matrix](matrix/rotate_matrix.py) * [Searching In Sorted Matrix](matrix/searching_in_sorted_matrix.py) * [Sherman Morrison](matrix/sherman_morrison.py) * [Spiral Print](matrix/spiral_print.py) * Tests * [Test Matrix Operation](matrix/tests/test_matrix_operation.py) * [Validate Sudoku Board](matrix/validate_sudoku_board.py) ## Networking Flow * [Ford Fulkerson](networking_flow/ford_fulkerson.py) * [Minimum Cut](networking_flow/minimum_cut.py) ## Neural Network * [2 Hidden Layers Neural Network](neural_network/2_hidden_layers_neural_network.py) * Activation Functions * [Binary Step](neural_network/activation_functions/binary_step.py) * [Exponential Linear Unit](neural_network/activation_functions/exponential_linear_unit.py) * [Leaky Rectified Linear Unit](neural_network/activation_functions/leaky_rectified_linear_unit.py) * [Mish](neural_network/activation_functions/mish.py) * [Rectified Linear Unit](neural_network/activation_functions/rectified_linear_unit.py) * [Scaled Exponential Linear Unit](neural_network/activation_functions/scaled_exponential_linear_unit.py) * [Soboleva Modified Hyperbolic Tangent](neural_network/activation_functions/soboleva_modified_hyperbolic_tangent.py) * [Softplus](neural_network/activation_functions/softplus.py) * [Squareplus](neural_network/activation_functions/squareplus.py) * [Swish](neural_network/activation_functions/swish.py) * [Back Propagation Neural Network](neural_network/back_propagation_neural_network.py) * [Convolution Neural Network](neural_network/convolution_neural_network.py) * [Simple Neural Network](neural_network/simple_neural_network.py) ## Other * [Activity Selection](other/activity_selection.py) * [Alternative List Arrange](other/alternative_list_arrange.py) * [Bankers Algorithm](other/bankers_algorithm.py) * [Davis Putnam Logemann Loveland](other/davis_putnam_logemann_loveland.py) * [Doomsday](other/doomsday.py) * [Fischer Yates Shuffle](other/fischer_yates_shuffle.py) * [Gauss Easter](other/gauss_easter.py) * [Graham Scan](other/graham_scan.py) * [Greedy](other/greedy.py) * [Guess The Number Search](other/guess_the_number_search.py) * [H Index](other/h_index.py) * [Least Recently Used](other/least_recently_used.py) * [Lfu Cache](other/lfu_cache.py) * [Linear Congruential Generator](other/linear_congruential_generator.py) * [Lru Cache](other/lru_cache.py) * [Magicdiamondpattern](other/magicdiamondpattern.py) * [Majority Vote Algorithm](other/majority_vote_algorithm.py) * [Maximum Subsequence](other/maximum_subsequence.py) * [Nested Brackets](other/nested_brackets.py) * [Number Container System](other/number_container_system.py) * [Password](other/password.py) * [Quine](other/quine.py) * [Scoring Algorithm](other/scoring_algorithm.py) * [Sdes](other/sdes.py) * [Tower Of Hanoi](other/tower_of_hanoi.py) * [Word Search](other/word_search.py) ## Physics * [Altitude Pressure](physics/altitude_pressure.py) * [Archimedes Principle Of Buoyant Force](physics/archimedes_principle_of_buoyant_force.py) * [Basic Orbital Capture](physics/basic_orbital_capture.py) * [Casimir Effect](physics/casimir_effect.py) * [Center Of Mass](physics/center_of_mass.py) * [Centripetal Force](physics/centripetal_force.py) * [Coulombs Law](physics/coulombs_law.py) * [Doppler Frequency](physics/doppler_frequency.py) * [Grahams Law](physics/grahams_law.py) * [Horizontal Projectile Motion](physics/horizontal_projectile_motion.py) * [Hubble Parameter](physics/hubble_parameter.py) * [Ideal Gas Law](physics/ideal_gas_law.py) * [In Static Equilibrium](physics/in_static_equilibrium.py) * [Kinetic Energy](physics/kinetic_energy.py) * [Lens Formulae](physics/lens_formulae.py) * [Lorentz Transformation Four Vector](physics/lorentz_transformation_four_vector.py) * [Malus Law](physics/malus_law.py) * [Mass Energy Equivalence](physics/mass_energy_equivalence.py) * [Mirror Formulae](physics/mirror_formulae.py) * [N Body Simulation](physics/n_body_simulation.py) * [Newtons Law Of Gravitation](physics/newtons_law_of_gravitation.py) * [Newtons Second Law Of Motion](physics/newtons_second_law_of_motion.py) * [Photoelectric Effect](physics/photoelectric_effect.py) * [Potential Energy](physics/potential_energy.py) * [Reynolds Number](physics/reynolds_number.py) * [Rms Speed Of Molecule](physics/rms_speed_of_molecule.py) * [Shear Stress](physics/shear_stress.py) * [Speed Of Sound](physics/speed_of_sound.py) * [Speeds Of Gas Molecules](physics/speeds_of_gas_molecules.py) * [Terminal Velocity](physics/terminal_velocity.py) ## Project Euler * Problem 001 * [Sol1](project_euler/problem_001/sol1.py) * [Sol2](project_euler/problem_001/sol2.py) * [Sol3](project_euler/problem_001/sol3.py) * [Sol4](project_euler/problem_001/sol4.py) * [Sol5](project_euler/problem_001/sol5.py) * [Sol6](project_euler/problem_001/sol6.py) * [Sol7](project_euler/problem_001/sol7.py) * Problem 002 * [Sol1](project_euler/problem_002/sol1.py) * [Sol2](project_euler/problem_002/sol2.py) * [Sol3](project_euler/problem_002/sol3.py) * [Sol4](project_euler/problem_002/sol4.py) * [Sol5](project_euler/problem_002/sol5.py) * Problem 003 * [Sol1](project_euler/problem_003/sol1.py) * [Sol2](project_euler/problem_003/sol2.py) * [Sol3](project_euler/problem_003/sol3.py) * Problem 004 * [Sol1](project_euler/problem_004/sol1.py) * [Sol2](project_euler/problem_004/sol2.py) * Problem 005 * [Sol1](project_euler/problem_005/sol1.py) * [Sol2](project_euler/problem_005/sol2.py) * Problem 006 * [Sol1](project_euler/problem_006/sol1.py) * [Sol2](project_euler/problem_006/sol2.py) * [Sol3](project_euler/problem_006/sol3.py) * [Sol4](project_euler/problem_006/sol4.py) * Problem 007 * [Sol1](project_euler/problem_007/sol1.py) * [Sol2](project_euler/problem_007/sol2.py) * [Sol3](project_euler/problem_007/sol3.py) * Problem 008 * [Sol1](project_euler/problem_008/sol1.py) * [Sol2](project_euler/problem_008/sol2.py) * [Sol3](project_euler/problem_008/sol3.py) * Problem 009 * [Sol1](project_euler/problem_009/sol1.py) * [Sol2](project_euler/problem_009/sol2.py) * [Sol3](project_euler/problem_009/sol3.py) * Problem 010 * [Sol1](project_euler/problem_010/sol1.py) * [Sol2](project_euler/problem_010/sol2.py) * [Sol3](project_euler/problem_010/sol3.py) * Problem 011 * [Sol1](project_euler/problem_011/sol1.py) * [Sol2](project_euler/problem_011/sol2.py) * Problem 012 * [Sol1](project_euler/problem_012/sol1.py) * [Sol2](project_euler/problem_012/sol2.py) * Problem 013 * [Sol1](project_euler/problem_013/sol1.py) * Problem 014 * [Sol1](project_euler/problem_014/sol1.py) * [Sol2](project_euler/problem_014/sol2.py) * Problem 015 * [Sol1](project_euler/problem_015/sol1.py) * Problem 016 * [Sol1](project_euler/problem_016/sol1.py) * [Sol2](project_euler/problem_016/sol2.py) * Problem 017 * [Sol1](project_euler/problem_017/sol1.py) * Problem 018 * [Solution](project_euler/problem_018/solution.py) * Problem 019 * [Sol1](project_euler/problem_019/sol1.py) * Problem 020 * [Sol1](project_euler/problem_020/sol1.py) * [Sol2](project_euler/problem_020/sol2.py) * [Sol3](project_euler/problem_020/sol3.py) * [Sol4](project_euler/problem_020/sol4.py) * Problem 021 * [Sol1](project_euler/problem_021/sol1.py) * Problem 022 * [Sol1](project_euler/problem_022/sol1.py) * [Sol2](project_euler/problem_022/sol2.py) * Problem 023 * [Sol1](project_euler/problem_023/sol1.py) * Problem 024 * [Sol1](project_euler/problem_024/sol1.py) * Problem 025 * [Sol1](project_euler/problem_025/sol1.py) * [Sol2](project_euler/problem_025/sol2.py) * [Sol3](project_euler/problem_025/sol3.py) * Problem 026 * [Sol1](project_euler/problem_026/sol1.py) * Problem 027 * [Sol1](project_euler/problem_027/sol1.py) * Problem 028 * [Sol1](project_euler/problem_028/sol1.py) * Problem 029 * [Sol1](project_euler/problem_029/sol1.py) * Problem 030 * [Sol1](project_euler/problem_030/sol1.py) * Problem 031 * [Sol1](project_euler/problem_031/sol1.py) * [Sol2](project_euler/problem_031/sol2.py) * Problem 032 * [Sol32](project_euler/problem_032/sol32.py) * Problem 033 * [Sol1](project_euler/problem_033/sol1.py) * Problem 034 * [Sol1](project_euler/problem_034/sol1.py) * Problem 035 * [Sol1](project_euler/problem_035/sol1.py) * Problem 036 * [Sol1](project_euler/problem_036/sol1.py) * Problem 037 * [Sol1](project_euler/problem_037/sol1.py) * Problem 038 * [Sol1](project_euler/problem_038/sol1.py) * Problem 039 * [Sol1](project_euler/problem_039/sol1.py) * Problem 040 * [Sol1](project_euler/problem_040/sol1.py) * Problem 041 * [Sol1](project_euler/problem_041/sol1.py) * Problem 042 * [Solution42](project_euler/problem_042/solution42.py) * Problem 043 * [Sol1](project_euler/problem_043/sol1.py) * Problem 044 * [Sol1](project_euler/problem_044/sol1.py) * Problem 045 * [Sol1](project_euler/problem_045/sol1.py) * Problem 046 * [Sol1](project_euler/problem_046/sol1.py) * Problem 047 * [Sol1](project_euler/problem_047/sol1.py) * Problem 048 * [Sol1](project_euler/problem_048/sol1.py) * Problem 049 * [Sol1](project_euler/problem_049/sol1.py) * Problem 050 * [Sol1](project_euler/problem_050/sol1.py) * Problem 051 * [Sol1](project_euler/problem_051/sol1.py) * Problem 052 * [Sol1](project_euler/problem_052/sol1.py) * Problem 053 * [Sol1](project_euler/problem_053/sol1.py) * Problem 054 * [Sol1](project_euler/problem_054/sol1.py) * [Test Poker Hand](project_euler/problem_054/test_poker_hand.py) * Problem 055 * [Sol1](project_euler/problem_055/sol1.py) * Problem 056 * [Sol1](project_euler/problem_056/sol1.py) * Problem 057 * [Sol1](project_euler/problem_057/sol1.py) * Problem 058 * [Sol1](project_euler/problem_058/sol1.py) * Problem 059 * [Sol1](project_euler/problem_059/sol1.py) * Problem 062 * [Sol1](project_euler/problem_062/sol1.py) * Problem 063 * [Sol1](project_euler/problem_063/sol1.py) * Problem 064 * [Sol1](project_euler/problem_064/sol1.py) * Problem 065 * [Sol1](project_euler/problem_065/sol1.py) * Problem 067 * [Sol1](project_euler/problem_067/sol1.py) * [Sol2](project_euler/problem_067/sol2.py) * Problem 068 * [Sol1](project_euler/problem_068/sol1.py) * Problem 069 * [Sol1](project_euler/problem_069/sol1.py) * Problem 070 * [Sol1](project_euler/problem_070/sol1.py) * Problem 071 * [Sol1](project_euler/problem_071/sol1.py) * Problem 072 * [Sol1](project_euler/problem_072/sol1.py) * [Sol2](project_euler/problem_072/sol2.py) * Problem 073 * [Sol1](project_euler/problem_073/sol1.py) * Problem 074 * [Sol1](project_euler/problem_074/sol1.py) * [Sol2](project_euler/problem_074/sol2.py) * Problem 075 * [Sol1](project_euler/problem_075/sol1.py) * Problem 076 * [Sol1](project_euler/problem_076/sol1.py) * Problem 077 * [Sol1](project_euler/problem_077/sol1.py) * Problem 078 * [Sol1](project_euler/problem_078/sol1.py) * Problem 079 * [Sol1](project_euler/problem_079/sol1.py) * Problem 080 * [Sol1](project_euler/problem_080/sol1.py) * Problem 081 * [Sol1](project_euler/problem_081/sol1.py) * Problem 082 * [Sol1](project_euler/problem_082/sol1.py) * Problem 085 * [Sol1](project_euler/problem_085/sol1.py) * Problem 086 * [Sol1](project_euler/problem_086/sol1.py) * Problem 087 * [Sol1](project_euler/problem_087/sol1.py) * Problem 089 * [Sol1](project_euler/problem_089/sol1.py) * Problem 091 * [Sol1](project_euler/problem_091/sol1.py) * Problem 092 * [Sol1](project_euler/problem_092/sol1.py) * Problem 094 * [Sol1](project_euler/problem_094/sol1.py) * Problem 097 * [Sol1](project_euler/problem_097/sol1.py) * Problem 099 * [Sol1](project_euler/problem_099/sol1.py) * Problem 100 * [Sol1](project_euler/problem_100/sol1.py) * Problem 101 * [Sol1](project_euler/problem_101/sol1.py) * Problem 102 * [Sol1](project_euler/problem_102/sol1.py) * Problem 104 * [Sol1](project_euler/problem_104/sol1.py) * Problem 107 * [Sol1](project_euler/problem_107/sol1.py) * Problem 109 * [Sol1](project_euler/problem_109/sol1.py) * Problem 112 * [Sol1](project_euler/problem_112/sol1.py) * Problem 113 * [Sol1](project_euler/problem_113/sol1.py) * Problem 114 * [Sol1](project_euler/problem_114/sol1.py) * Problem 115 * [Sol1](project_euler/problem_115/sol1.py) * Problem 116 * [Sol1](project_euler/problem_116/sol1.py) * Problem 117 * [Sol1](project_euler/problem_117/sol1.py) * Problem 119 * [Sol1](project_euler/problem_119/sol1.py) * Problem 120 * [Sol1](project_euler/problem_120/sol1.py) * Problem 121 * [Sol1](project_euler/problem_121/sol1.py) * Problem 123 * [Sol1](project_euler/problem_123/sol1.py) * Problem 125 * [Sol1](project_euler/problem_125/sol1.py) * Problem 129 * [Sol1](project_euler/problem_129/sol1.py) * Problem 131 * [Sol1](project_euler/problem_131/sol1.py) * Problem 135 * [Sol1](project_euler/problem_135/sol1.py) * Problem 144 * [Sol1](project_euler/problem_144/sol1.py) * Problem 145 * [Sol1](project_euler/problem_145/sol1.py) * Problem 173 * [Sol1](project_euler/problem_173/sol1.py) * Problem 174 * [Sol1](project_euler/problem_174/sol1.py) * Problem 180 * [Sol1](project_euler/problem_180/sol1.py) * Problem 187 * [Sol1](project_euler/problem_187/sol1.py) * Problem 188 * [Sol1](project_euler/problem_188/sol1.py) * Problem 191 * [Sol1](project_euler/problem_191/sol1.py) * Problem 203 * [Sol1](project_euler/problem_203/sol1.py) * Problem 205 * [Sol1](project_euler/problem_205/sol1.py) * Problem 206 * [Sol1](project_euler/problem_206/sol1.py) * Problem 207 * [Sol1](project_euler/problem_207/sol1.py) * Problem 234 * [Sol1](project_euler/problem_234/sol1.py) * Problem 301 * [Sol1](project_euler/problem_301/sol1.py) * Problem 493 * [Sol1](project_euler/problem_493/sol1.py) * Problem 551 * [Sol1](project_euler/problem_551/sol1.py) * Problem 587 * [Sol1](project_euler/problem_587/sol1.py) * Problem 686 * [Sol1](project_euler/problem_686/sol1.py) * Problem 800 * [Sol1](project_euler/problem_800/sol1.py) ## Quantum * [Q Fourier Transform](quantum/q_fourier_transform.py) ## Scheduling * [First Come First Served](scheduling/first_come_first_served.py) * [Highest Response Ratio Next](scheduling/highest_response_ratio_next.py) * [Job Sequence With Deadline](scheduling/job_sequence_with_deadline.py) * [Job Sequencing With Deadline](scheduling/job_sequencing_with_deadline.py) * [Multi Level Feedback Queue](scheduling/multi_level_feedback_queue.py) * [Non Preemptive Shortest Job First](scheduling/non_preemptive_shortest_job_first.py) * [Round Robin](scheduling/round_robin.py) * [Shortest Job First](scheduling/shortest_job_first.py) ## Searches * [Binary Search](searches/binary_search.py) * [Binary Tree Traversal](searches/binary_tree_traversal.py) * [Double Linear Search](searches/double_linear_search.py) * [Double Linear Search Recursion](searches/double_linear_search_recursion.py) * [Fibonacci Search](searches/fibonacci_search.py) * [Hill Climbing](searches/hill_climbing.py) * [Interpolation Search](searches/interpolation_search.py) * [Jump Search](searches/jump_search.py) * [Linear Search](searches/linear_search.py) * [Median Of Medians](searches/median_of_medians.py) * [Quick Select](searches/quick_select.py) * [Sentinel Linear Search](searches/sentinel_linear_search.py) * [Simple Binary Search](searches/simple_binary_search.py) * [Simulated Annealing](searches/simulated_annealing.py) * [Tabu Search](searches/tabu_search.py) * [Ternary Search](searches/ternary_search.py) ## Sorts * [Bead Sort](sorts/bead_sort.py) * [Binary Insertion Sort](sorts/binary_insertion_sort.py) * [Bitonic Sort](sorts/bitonic_sort.py) * [Bogo Sort](sorts/bogo_sort.py) * [Bubble Sort](sorts/bubble_sort.py) * [Bucket Sort](sorts/bucket_sort.py) * [Circle Sort](sorts/circle_sort.py) * [Cocktail Shaker Sort](sorts/cocktail_shaker_sort.py) * [Comb Sort](sorts/comb_sort.py) * [Counting Sort](sorts/counting_sort.py) * [Cycle Sort](sorts/cycle_sort.py) * [Double Sort](sorts/double_sort.py) * [Dutch National Flag Sort](sorts/dutch_national_flag_sort.py) * [Exchange Sort](sorts/exchange_sort.py) * [External Sort](sorts/external_sort.py) * [Gnome Sort](sorts/gnome_sort.py) * [Heap Sort](sorts/heap_sort.py) * [Insertion Sort](sorts/insertion_sort.py) * [Intro Sort](sorts/intro_sort.py) * [Iterative Merge Sort](sorts/iterative_merge_sort.py) * [Merge Insertion Sort](sorts/merge_insertion_sort.py) * [Merge Sort](sorts/merge_sort.py) * [Msd Radix Sort](sorts/msd_radix_sort.py) * [Natural Sort](sorts/natural_sort.py) * [Odd Even Sort](sorts/odd_even_sort.py) * [Odd Even Transposition Parallel](sorts/odd_even_transposition_parallel.py) * [Odd Even Transposition Single Threaded](sorts/odd_even_transposition_single_threaded.py) * [Pancake Sort](sorts/pancake_sort.py) * [Patience Sort](sorts/patience_sort.py) * [Pigeon Sort](sorts/pigeon_sort.py) * [Pigeonhole Sort](sorts/pigeonhole_sort.py) * [Quick Sort](sorts/quick_sort.py) * [Quick Sort 3 Partition](sorts/quick_sort_3_partition.py) * [Radix Sort](sorts/radix_sort.py) * [Recursive Insertion Sort](sorts/recursive_insertion_sort.py) * [Recursive Mergesort Array](sorts/recursive_mergesort_array.py) * [Recursive Quick Sort](sorts/recursive_quick_sort.py) * [Selection Sort](sorts/selection_sort.py) * [Shell Sort](sorts/shell_sort.py) * [Shrink Shell Sort](sorts/shrink_shell_sort.py) * [Slowsort](sorts/slowsort.py) * [Stooge Sort](sorts/stooge_sort.py) * [Strand Sort](sorts/strand_sort.py) * [Tim Sort](sorts/tim_sort.py) * [Topological Sort](sorts/topological_sort.py) * [Tree Sort](sorts/tree_sort.py) * [Unknown Sort](sorts/unknown_sort.py) * [Wiggle Sort](sorts/wiggle_sort.py) ## Strings * [Aho Corasick](strings/aho_corasick.py) * [Alternative String Arrange](strings/alternative_string_arrange.py) * [Anagrams](strings/anagrams.py) * [Autocomplete Using Trie](strings/autocomplete_using_trie.py) * [Barcode Validator](strings/barcode_validator.py) * [Bitap String Match](strings/bitap_string_match.py) * [Boyer Moore Search](strings/boyer_moore_search.py) * [Camel Case To Snake Case](strings/camel_case_to_snake_case.py) * [Can String Be Rearranged As Palindrome](strings/can_string_be_rearranged_as_palindrome.py) * [Capitalize](strings/capitalize.py) * [Check Anagrams](strings/check_anagrams.py) * [Credit Card Validator](strings/credit_card_validator.py) * [Damerau Levenshtein Distance](strings/damerau_levenshtein_distance.py) * [Detecting English Programmatically](strings/detecting_english_programmatically.py) * [Dna](strings/dna.py) * [Edit Distance](strings/edit_distance.py) * [Frequency Finder](strings/frequency_finder.py) * [Hamming Distance](strings/hamming_distance.py) * [Indian Phone Validator](strings/indian_phone_validator.py) * [Is Contains Unique Chars](strings/is_contains_unique_chars.py) * [Is Isogram](strings/is_isogram.py) * [Is Pangram](strings/is_pangram.py) * [Is Polish National Id](strings/is_polish_national_id.py) * [Is Spain National Id](strings/is_spain_national_id.py) * [Is Srilankan Phone Number](strings/is_srilankan_phone_number.py) * [Is Valid Email Address](strings/is_valid_email_address.py) * [Jaro Winkler](strings/jaro_winkler.py) * [Join](strings/join.py) * [Knuth Morris Pratt](strings/knuth_morris_pratt.py) * [Levenshtein Distance](strings/levenshtein_distance.py) * [Lower](strings/lower.py) * [Manacher](strings/manacher.py) * [Min Cost String Conversion](strings/min_cost_string_conversion.py) * [Naive String Search](strings/naive_string_search.py) * [Ngram](strings/ngram.py) * [Palindrome](strings/palindrome.py) * [Pig Latin](strings/pig_latin.py) * [Prefix Function](strings/prefix_function.py) * [Rabin Karp](strings/rabin_karp.py) * [Remove Duplicate](strings/remove_duplicate.py) * [Reverse Letters](strings/reverse_letters.py) * [Reverse Words](strings/reverse_words.py) * [Snake Case To Camel Pascal Case](strings/snake_case_to_camel_pascal_case.py) * [Split](strings/split.py) * [String Switch Case](strings/string_switch_case.py) * [Strip](strings/strip.py) * [Text Justification](strings/text_justification.py) * [Title](strings/title.py) * [Top K Frequent Words](strings/top_k_frequent_words.py) * [Upper](strings/upper.py) * [Wave](strings/wave.py) * [Wildcard Pattern Matching](strings/wildcard_pattern_matching.py) * [Word Occurrence](strings/word_occurrence.py) * [Word Patterns](strings/word_patterns.py) * [Z Function](strings/z_function.py) ## Web Programming * [Co2 Emission](web_programming/co2_emission.py) * [Covid Stats Via Xpath](web_programming/covid_stats_via_xpath.py) * [Crawl Google Results](web_programming/crawl_google_results.py) * [Crawl Google Scholar Citation](web_programming/crawl_google_scholar_citation.py) * [Currency Converter](web_programming/currency_converter.py) * [Current Stock Price](web_programming/current_stock_price.py) * [Current Weather](web_programming/current_weather.py) * [Daily Horoscope](web_programming/daily_horoscope.py) * [Download Images From Google Query](web_programming/download_images_from_google_query.py) * [Emails From Url](web_programming/emails_from_url.py) * [Fetch Anime And Play](web_programming/fetch_anime_and_play.py) * [Fetch Bbc News](web_programming/fetch_bbc_news.py) * [Fetch Github Info](web_programming/fetch_github_info.py) * [Fetch Jobs](web_programming/fetch_jobs.py) * [Fetch Quotes](web_programming/fetch_quotes.py) * [Fetch Well Rx Price](web_programming/fetch_well_rx_price.py) * [Get Amazon Product Data](web_programming/get_amazon_product_data.py) * [Get Imdb Top 250 Movies Csv](web_programming/get_imdb_top_250_movies_csv.py) * [Get Ip Geolocation](web_programming/get_ip_geolocation.py) * [Get Top Billionaires](web_programming/get_top_billionaires.py) * [Get Top Hn Posts](web_programming/get_top_hn_posts.py) * [Get User Tweets](web_programming/get_user_tweets.py) * [Giphy](web_programming/giphy.py) * [Instagram Crawler](web_programming/instagram_crawler.py) * [Instagram Pic](web_programming/instagram_pic.py) * [Instagram Video](web_programming/instagram_video.py) * [Nasa Data](web_programming/nasa_data.py) * [Open Google Results](web_programming/open_google_results.py) * [Random Anime Character](web_programming/random_anime_character.py) * [Recaptcha Verification](web_programming/recaptcha_verification.py) * [Reddit](web_programming/reddit.py) * [Search Books By Isbn](web_programming/search_books_by_isbn.py) * [Slack Message](web_programming/slack_message.py) * [Test Fetch Github Info](web_programming/test_fetch_github_info.py) * [World Covid19 Stats](web_programming/world_covid19_stats.py)

TheAlgorithms/Python

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""" This program print the matrix in spiral form. This problem has been solved through recursive way. Matrix must satisfy below conditions i) matrix should be only one or two dimensional ii) number of column of all rows should be equal """ def check_matrix(matrix: list[list[int]]) -> bool: # must be matrix = [list(row) for row in matrix] if matrix and isinstance(matrix, list): if isinstance(matrix[0], list): prev_len = 0 for row in matrix: if prev_len == 0: prev_len = len(row) result = True else: result = prev_len == len(row) else: result = True else: result = False return result def spiral_print_clockwise(a: list[list[int]]) -> None: """ >>> spiral_print_clockwise([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]) 1 2 3 4 8 12 11 10 9 5 6 7 """ if check_matrix(a) and len(a) > 0: a = [list(row) for row in a] mat_row = len(a) if isinstance(a[0], list): mat_col = len(a[0]) else: for dat in a: print(dat) return # horizotal printing increasing for i in range(mat_col): print(a[0][i]) # vertical printing down for i in range(1, mat_row): print(a[i][mat_col - 1]) # horizotal printing decreasing if mat_row > 1: for i in range(mat_col - 2, -1, -1): print(a[mat_row - 1][i]) # vertical printing up for i in range(mat_row - 2, 0, -1): print(a[i][0]) remain_mat = [row[1 : mat_col - 1] for row in a[1 : mat_row - 1]] if len(remain_mat) > 0: spiral_print_clockwise(remain_mat) else: return else: print("Not a valid matrix") return # Other Easy to understand Approach def spiral_traversal(matrix: list[list]) -> list[int]: """ >>> spiral_traversal([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]) [1, 2, 3, 4, 8, 12, 11, 10, 9, 5, 6, 7] Example: matrix = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] Algorithm: Step 1. first pop the 0 index list. (which is [1,2,3,4] and concatenate the output of [step 2]) Step 2. Now perform matrix’s Transpose operation (Change rows to column and vice versa) and reverse the resultant matrix. Step 3. Pass the output of [2nd step], to same recursive function till base case hits. Dry Run: Stage 1. [1, 2, 3, 4] + spiral_traversal([ [8, 12], [7, 11], [6, 10], [5, 9]] ]) Stage 2. [1, 2, 3, 4, 8, 12] + spiral_traversal([ [11, 10, 9], [7, 6, 5] ]) Stage 3. [1, 2, 3, 4, 8, 12, 11, 10, 9] + spiral_traversal([ [5], [6], [7] ]) Stage 4. [1, 2, 3, 4, 8, 12, 11, 10, 9, 5] + spiral_traversal([ [5], [6], [7] ]) Stage 5. [1, 2, 3, 4, 8, 12, 11, 10, 9, 5] + spiral_traversal([[6, 7]]) Stage 6. [1, 2, 3, 4, 8, 12, 11, 10, 9, 5, 6, 7] + spiral_traversal([]) """ if matrix: return list(matrix.pop(0)) + spiral_traversal(list(zip(*matrix))[::-1]) else: return [] # driver code if __name__ == "__main__": import doctest doctest.testmod() a = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] spiral_print_clockwise(a)

""" This program print the matrix in spiral form. This problem has been solved through recursive way. Matrix must satisfy below conditions i) matrix should be only one or two dimensional ii) number of column of all rows should be equal """ def check_matrix(matrix: list[list[int]]) -> bool: # must be matrix = [list(row) for row in matrix] if matrix and isinstance(matrix, list): if isinstance(matrix[0], list): prev_len = 0 for row in matrix: if prev_len == 0: prev_len = len(row) result = True else: result = prev_len == len(row) else: result = True else: result = False return result def spiral_print_clockwise(a: list[list[int]]) -> None: """ >>> spiral_print_clockwise([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]) 1 2 3 4 8 12 11 10 9 5 6 7 """ if check_matrix(a) and len(a) > 0: a = [list(row) for row in a] mat_row = len(a) if isinstance(a[0], list): mat_col = len(a[0]) else: for dat in a: print(dat) return # horizotal printing increasing for i in range(mat_col): print(a[0][i]) # vertical printing down for i in range(1, mat_row): print(a[i][mat_col - 1]) # horizotal printing decreasing if mat_row > 1: for i in range(mat_col - 2, -1, -1): print(a[mat_row - 1][i]) # vertical printing up for i in range(mat_row - 2, 0, -1): print(a[i][0]) remain_mat = [row[1 : mat_col - 1] for row in a[1 : mat_row - 1]] if len(remain_mat) > 0: spiral_print_clockwise(remain_mat) else: return else: print("Not a valid matrix") return # Other Easy to understand Approach def spiral_traversal(matrix: list[list]) -> list[int]: """ >>> spiral_traversal([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]) [1, 2, 3, 4, 8, 12, 11, 10, 9, 5, 6, 7] Example: matrix = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] Algorithm: Step 1. first pop the 0 index list. (which is [1,2,3,4] and concatenate the output of [step 2]) Step 2. Now perform matrix’s Transpose operation (Change rows to column and vice versa) and reverse the resultant matrix. Step 3. Pass the output of [2nd step], to same recursive function till base case hits. Dry Run: Stage 1. [1, 2, 3, 4] + spiral_traversal([ [8, 12], [7, 11], [6, 10], [5, 9]] ]) Stage 2. [1, 2, 3, 4, 8, 12] + spiral_traversal([ [11, 10, 9], [7, 6, 5] ]) Stage 3. [1, 2, 3, 4, 8, 12, 11, 10, 9] + spiral_traversal([ [5], [6], [7] ]) Stage 4. [1, 2, 3, 4, 8, 12, 11, 10, 9, 5] + spiral_traversal([ [5], [6], [7] ]) Stage 5. [1, 2, 3, 4, 8, 12, 11, 10, 9, 5] + spiral_traversal([[6, 7]]) Stage 6. [1, 2, 3, 4, 8, 12, 11, 10, 9, 5, 6, 7] + spiral_traversal([]) """ if matrix: return list(matrix.pop(0)) + spiral_traversal(list(zip(*matrix))[::-1]) # type: ignore else: return [] # driver code if __name__ == "__main__": import doctest doctest.testmod() a = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] spiral_print_clockwise(a)

TheAlgorithms/Python

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# https://farside.ph.utexas.edu/teaching/316/lectures/node46.html from __future__ import annotations def capacitor_parallel(capacitors: list[float]) -> float: """ Ceq = C1 + C2 + ... + Cn Calculate the equivalent resistance for any number of capacitors in parallel. >>> capacitor_parallel([5.71389, 12, 3]) 20.71389 >>> capacitor_parallel([5.71389, 12, -3]) Traceback (most recent call last): ... ValueError: Capacitor at index 2 has a negative value! """ sum_c = 0.0 for index, capacitor in enumerate(capacitors): if capacitor < 0: msg = f"Capacitor at index {index} has a negative value!" raise ValueError(msg) sum_c += capacitor return sum_c def capacitor_series(capacitors: list[float]) -> float: """ Ceq = 1/ (1/C1 + 1/C2 + ... + 1/Cn) >>> capacitor_series([5.71389, 12, 3]) 1.6901062252507735 >>> capacitor_series([5.71389, 12, -3]) Traceback (most recent call last): ... ValueError: Capacitor at index 2 has a negative or zero value! >>> capacitor_series([5.71389, 12, 0.000]) Traceback (most recent call last): ... ValueError: Capacitor at index 2 has a negative or zero value! """ first_sum = 0.0 for index, capacitor in enumerate(capacitors): if capacitor <= 0: msg = f"Capacitor at index {index} has a negative or zero value!" raise ValueError(msg) first_sum += 1 / capacitor return 1 / first_sum if __name__ == "__main__": import doctest doctest.testmod()

# https://farside.ph.utexas.edu/teaching/316/lectures/node46.html from __future__ import annotations def capacitor_parallel(capacitors: list[float]) -> float: """ Ceq = C1 + C2 + ... + Cn Calculate the equivalent resistance for any number of capacitors in parallel. >>> capacitor_parallel([5.71389, 12, 3]) 20.71389 >>> capacitor_parallel([5.71389, 12, -3]) Traceback (most recent call last): ... ValueError: Capacitor at index 2 has a negative value! """ sum_c = 0.0 for index, capacitor in enumerate(capacitors): if capacitor < 0: msg = f"Capacitor at index {index} has a negative value!" raise ValueError(msg) sum_c += capacitor return sum_c def capacitor_series(capacitors: list[float]) -> float: """ Ceq = 1/ (1/C1 + 1/C2 + ... + 1/Cn) >>> capacitor_series([5.71389, 12, 3]) 1.6901062252507735 >>> capacitor_series([5.71389, 12, -3]) Traceback (most recent call last): ... ValueError: Capacitor at index 2 has a negative or zero value! >>> capacitor_series([5.71389, 12, 0.000]) Traceback (most recent call last): ... ValueError: Capacitor at index 2 has a negative or zero value! """ first_sum = 0.0 for index, capacitor in enumerate(capacitors): if capacitor <= 0: msg = f"Capacitor at index {index} has a negative or zero value!" raise ValueError(msg) first_sum += 1 / capacitor return 1 / first_sum if __name__ == "__main__": import doctest doctest.testmod()

TheAlgorithms/Python

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"""Breath First Search (BFS) can be used when finding the shortest path from a given source node to a target node in an unweighted graph. """ from __future__ import annotations graph = { "A": ["B", "C", "E"], "B": ["A", "D", "E"], "C": ["A", "F", "G"], "D": ["B"], "E": ["A", "B", "D"], "F": ["C"], "G": ["C"], } class Graph: def __init__(self, graph: dict[str, list[str]], source_vertex: str) -> None: """ Graph is implemented as dictionary of adjacency lists. Also, Source vertex have to be defined upon initialization. """ self.graph = graph # mapping node to its parent in resulting breadth first tree self.parent: dict[str, str | None] = {} self.source_vertex = source_vertex def breath_first_search(self) -> None: """ This function is a helper for running breath first search on this graph. >>> g = Graph(graph, "G") >>> g.breath_first_search() >>> g.parent {'G': None, 'C': 'G', 'A': 'C', 'F': 'C', 'B': 'A', 'E': 'A', 'D': 'B'} """ visited = {self.source_vertex} self.parent[self.source_vertex] = None queue = [self.source_vertex] # first in first out queue while queue: vertex = queue.pop(0) for adjacent_vertex in self.graph[vertex]: if adjacent_vertex not in visited: visited.add(adjacent_vertex) self.parent[adjacent_vertex] = vertex queue.append(adjacent_vertex) def shortest_path(self, target_vertex: str) -> str: """ This shortest path function returns a string, describing the result: 1.) No path is found. The string is a human readable message to indicate this. 2.) The shortest path is found. The string is in the form `v1(->v2->v3->...->vn)`, where v1 is the source vertex and vn is the target vertex, if it exists separately. >>> g = Graph(graph, "G") >>> g.breath_first_search() Case 1 - No path is found. >>> g.shortest_path("Foo") Traceback (most recent call last): ... ValueError: No path from vertex: G to vertex: Foo Case 2 - The path is found. >>> g.shortest_path("D") 'G->C->A->B->D' >>> g.shortest_path("G") 'G' """ if target_vertex == self.source_vertex: return self.source_vertex target_vertex_parent = self.parent.get(target_vertex) if target_vertex_parent is None: msg = ( f"No path from vertex: {self.source_vertex} to vertex: {target_vertex}" ) raise ValueError(msg) return self.shortest_path(target_vertex_parent) + f"->{target_vertex}" if __name__ == "__main__": g = Graph(graph, "G") g.breath_first_search() print(g.shortest_path("D")) print(g.shortest_path("G")) print(g.shortest_path("Foo"))

"""Breath First Search (BFS) can be used when finding the shortest path from a given source node to a target node in an unweighted graph. """ from __future__ import annotations graph = { "A": ["B", "C", "E"], "B": ["A", "D", "E"], "C": ["A", "F", "G"], "D": ["B"], "E": ["A", "B", "D"], "F": ["C"], "G": ["C"], } class Graph: def __init__(self, graph: dict[str, list[str]], source_vertex: str) -> None: """ Graph is implemented as dictionary of adjacency lists. Also, Source vertex have to be defined upon initialization. """ self.graph = graph # mapping node to its parent in resulting breadth first tree self.parent: dict[str, str | None] = {} self.source_vertex = source_vertex def breath_first_search(self) -> None: """ This function is a helper for running breath first search on this graph. >>> g = Graph(graph, "G") >>> g.breath_first_search() >>> g.parent {'G': None, 'C': 'G', 'A': 'C', 'F': 'C', 'B': 'A', 'E': 'A', 'D': 'B'} """ visited = {self.source_vertex} self.parent[self.source_vertex] = None queue = [self.source_vertex] # first in first out queue while queue: vertex = queue.pop(0) for adjacent_vertex in self.graph[vertex]: if adjacent_vertex not in visited: visited.add(adjacent_vertex) self.parent[adjacent_vertex] = vertex queue.append(adjacent_vertex) def shortest_path(self, target_vertex: str) -> str: """ This shortest path function returns a string, describing the result: 1.) No path is found. The string is a human readable message to indicate this. 2.) The shortest path is found. The string is in the form `v1(->v2->v3->...->vn)`, where v1 is the source vertex and vn is the target vertex, if it exists separately. >>> g = Graph(graph, "G") >>> g.breath_first_search() Case 1 - No path is found. >>> g.shortest_path("Foo") Traceback (most recent call last): ... ValueError: No path from vertex: G to vertex: Foo Case 2 - The path is found. >>> g.shortest_path("D") 'G->C->A->B->D' >>> g.shortest_path("G") 'G' """ if target_vertex == self.source_vertex: return self.source_vertex target_vertex_parent = self.parent.get(target_vertex) if target_vertex_parent is None: msg = ( f"No path from vertex: {self.source_vertex} to vertex: {target_vertex}" ) raise ValueError(msg) return self.shortest_path(target_vertex_parent) + f"->{target_vertex}" if __name__ == "__main__": g = Graph(graph, "G") g.breath_first_search() print(g.shortest_path("D")) print(g.shortest_path("G")) print(g.shortest_path("Foo"))

TheAlgorithms/Python

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""" Fast inverse square root (1/sqrt(x)) using the Quake III algorithm. Reference: https://en.wikipedia.org/wiki/Fast_inverse_square_root Accuracy: https://en.wikipedia.org/wiki/Fast_inverse_square_root#Accuracy """ import struct def fast_inverse_sqrt(number: float) -> float: """ Compute the fast inverse square root of a floating-point number using the famous Quake III algorithm. :param float number: Input number for which to calculate the inverse square root. :return float: The fast inverse square root of the input number. Example: >>> fast_inverse_sqrt(10) 0.3156857923527257 >>> fast_inverse_sqrt(4) 0.49915357479239103 >>> fast_inverse_sqrt(4.1) 0.4932849504615651 >>> fast_inverse_sqrt(0) Traceback (most recent call last): ... ValueError: Input must be a positive number. >>> fast_inverse_sqrt(-1) Traceback (most recent call last): ... ValueError: Input must be a positive number. >>> from math import isclose, sqrt >>> all(isclose(fast_inverse_sqrt(i), 1 / sqrt(i), rel_tol=0.00132) ... for i in range(50, 60)) True """ if number <= 0: raise ValueError("Input must be a positive number.") i = struct.unpack(">i", struct.pack(">f", number))[0] i = 0x5F3759DF - (i >> 1) y = struct.unpack(">f", struct.pack(">i", i))[0] return y * (1.5 - 0.5 * number * y * y) if __name__ == "__main__": from doctest import testmod testmod() # https://en.wikipedia.org/wiki/Fast_inverse_square_root#Accuracy from math import sqrt for i in range(5, 101, 5): print(f"{i:>3}: {(1 / sqrt(i)) - fast_inverse_sqrt(i):.5f}")

""" Fast inverse square root (1/sqrt(x)) using the Quake III algorithm. Reference: https://en.wikipedia.org/wiki/Fast_inverse_square_root Accuracy: https://en.wikipedia.org/wiki/Fast_inverse_square_root#Accuracy """ import struct def fast_inverse_sqrt(number: float) -> float: """ Compute the fast inverse square root of a floating-point number using the famous Quake III algorithm. :param float number: Input number for which to calculate the inverse square root. :return float: The fast inverse square root of the input number. Example: >>> fast_inverse_sqrt(10) 0.3156857923527257 >>> fast_inverse_sqrt(4) 0.49915357479239103 >>> fast_inverse_sqrt(4.1) 0.4932849504615651 >>> fast_inverse_sqrt(0) Traceback (most recent call last): ... ValueError: Input must be a positive number. >>> fast_inverse_sqrt(-1) Traceback (most recent call last): ... ValueError: Input must be a positive number. >>> from math import isclose, sqrt >>> all(isclose(fast_inverse_sqrt(i), 1 / sqrt(i), rel_tol=0.00132) ... for i in range(50, 60)) True """ if number <= 0: raise ValueError("Input must be a positive number.") i = struct.unpack(">i", struct.pack(">f", number))[0] i = 0x5F3759DF - (i >> 1) y = struct.unpack(">f", struct.pack(">i", i))[0] return y * (1.5 - 0.5 * number * y * y) if __name__ == "__main__": from doctest import testmod testmod() # https://en.wikipedia.org/wiki/Fast_inverse_square_root#Accuracy from math import sqrt for i in range(5, 101, 5): print(f"{i:>3}: {(1 / sqrt(i)) - fast_inverse_sqrt(i):.5f}")

TheAlgorithms/Python

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import math """ In cryptography, the TRANSPOSITION cipher is a method of encryption where the positions of plaintext are shifted a certain number(determined by the key) that follows a regular system that results in the permuted text, known as the encrypted text. The type of transposition cipher demonstrated under is the ROUTE cipher. """ def main() -> None: message = input("Enter message: ") key = int(input(f"Enter key [2-{len(message) - 1}]: ")) mode = input("Encryption/Decryption [e/d]: ") if mode.lower().startswith("e"): text = encrypt_message(key, message) elif mode.lower().startswith("d"): text = decrypt_message(key, message) # Append pipe symbol (vertical bar) to identify spaces at the end. print(f"Output:\n{text + '|'}") def encrypt_message(key: int, message: str) -> str: """ >>> encrypt_message(6, 'Harshil Darji') 'Hlia rDsahrij' """ cipher_text = [""] * key for col in range(key): pointer = col while pointer < len(message): cipher_text[col] += message[pointer] pointer += key return "".join(cipher_text) def decrypt_message(key: int, message: str) -> str: """ >>> decrypt_message(6, 'Hlia rDsahrij') 'Harshil Darji' """ num_cols = math.ceil(len(message) / key) num_rows = key num_shaded_boxes = (num_cols * num_rows) - len(message) plain_text = [""] * num_cols col = 0 row = 0 for symbol in message: plain_text[col] += symbol col += 1 if ( (col == num_cols) or (col == num_cols - 1) and (row >= num_rows - num_shaded_boxes) ): col = 0 row += 1 return "".join(plain_text) if __name__ == "__main__": import doctest doctest.testmod() main()

import math """ In cryptography, the TRANSPOSITION cipher is a method of encryption where the positions of plaintext are shifted a certain number(determined by the key) that follows a regular system that results in the permuted text, known as the encrypted text. The type of transposition cipher demonstrated under is the ROUTE cipher. """ def main() -> None: message = input("Enter message: ") key = int(input(f"Enter key [2-{len(message) - 1}]: ")) mode = input("Encryption/Decryption [e/d]: ") if mode.lower().startswith("e"): text = encrypt_message(key, message) elif mode.lower().startswith("d"): text = decrypt_message(key, message) # Append pipe symbol (vertical bar) to identify spaces at the end. print(f"Output:\n{text + '|'}") def encrypt_message(key: int, message: str) -> str: """ >>> encrypt_message(6, 'Harshil Darji') 'Hlia rDsahrij' """ cipher_text = [""] * key for col in range(key): pointer = col while pointer < len(message): cipher_text[col] += message[pointer] pointer += key return "".join(cipher_text) def decrypt_message(key: int, message: str) -> str: """ >>> decrypt_message(6, 'Hlia rDsahrij') 'Harshil Darji' """ num_cols = math.ceil(len(message) / key) num_rows = key num_shaded_boxes = (num_cols * num_rows) - len(message) plain_text = [""] * num_cols col = 0 row = 0 for symbol in message: plain_text[col] += symbol col += 1 if ( (col == num_cols) or (col == num_cols - 1) and (row >= num_rows - num_shaded_boxes) ): col = 0 row += 1 return "".join(plain_text) if __name__ == "__main__": import doctest doctest.testmod() main()

TheAlgorithms/Python

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""" PyTest's for Digital Image Processing """ import numpy as np from cv2 import COLOR_BGR2GRAY, cvtColor, imread from numpy import array, uint8 from PIL import Image from digital_image_processing import change_contrast as cc from digital_image_processing import convert_to_negative as cn from digital_image_processing import sepia as sp from digital_image_processing.dithering import burkes as bs from digital_image_processing.edge_detection import canny from digital_image_processing.filters import convolve as conv from digital_image_processing.filters import gaussian_filter as gg from digital_image_processing.filters import local_binary_pattern as lbp from digital_image_processing.filters import median_filter as med from digital_image_processing.filters import sobel_filter as sob from digital_image_processing.resize import resize as rs img = imread(r"digital_image_processing/image_data/lena_small.jpg") gray = cvtColor(img, COLOR_BGR2GRAY) # Test: convert_to_negative() def test_convert_to_negative(): negative_img = cn.convert_to_negative(img) # assert negative_img array for at least one True assert negative_img.any() # Test: change_contrast() def test_change_contrast(): with Image.open("digital_image_processing/image_data/lena_small.jpg") as img: # Work around assertion for response assert str(cc.change_contrast(img, 110)).startswith( "<PIL.Image.Image image mode=RGB size=100x100 at" ) # canny.gen_gaussian_kernel() def test_gen_gaussian_kernel(): resp = canny.gen_gaussian_kernel(9, sigma=1.4) # Assert ambiguous array assert resp.all() # canny.py def test_canny(): canny_img = imread("digital_image_processing/image_data/lena_small.jpg", 0) # assert ambiguous array for all == True assert canny_img.all() canny_array = canny.canny(canny_img) # assert canny array for at least one True assert canny_array.any() # filters/gaussian_filter.py def test_gen_gaussian_kernel_filter(): assert gg.gaussian_filter(gray, 5, sigma=0.9).all() def test_convolve_filter(): # laplace diagonals laplace = array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]) res = conv.img_convolve(gray, laplace).astype(uint8) assert res.any() def test_median_filter(): assert med.median_filter(gray, 3).any() def test_sobel_filter(): grad, theta = sob.sobel_filter(gray) assert grad.any() assert theta.any() def test_sepia(): sepia = sp.make_sepia(img, 20) assert sepia.all() def test_burkes(file_path: str = "digital_image_processing/image_data/lena_small.jpg"): burkes = bs.Burkes(imread(file_path, 1), 120) burkes.process() assert burkes.output_img.any() def test_nearest_neighbour( file_path: str = "digital_image_processing/image_data/lena_small.jpg", ): nn = rs.NearestNeighbour(imread(file_path, 1), 400, 200) nn.process() assert nn.output.any() def test_local_binary_pattern(): # pull request 10161 before: # "digital_image_processing/image_data/lena.jpg" # after: "digital_image_processing/image_data/lena_small.jpg" from os import getenv # Speed up our Continuous Integration tests file_name = "lena_small.jpg" if getenv("CI") else "lena.jpg" file_path = f"digital_image_processing/image_data/{file_name}" # Reading the image and converting it to grayscale image = imread(file_path, 0) # Test for get_neighbors_pixel function() return not None x_coordinate = 0 y_coordinate = 0 center = image[x_coordinate][y_coordinate] neighbors_pixels = lbp.get_neighbors_pixel( image, x_coordinate, y_coordinate, center ) assert neighbors_pixels is not None # Test for local_binary_pattern function() # Create a numpy array as the same height and width of read image lbp_image = np.zeros((image.shape[0], image.shape[1])) # Iterating through the image and calculating the local binary pattern value # for each pixel. for i in range(image.shape[0]): for j in range(image.shape[1]): lbp_image[i][j] = lbp.local_binary_value(image, i, j) assert lbp_image.any()

""" PyTest's for Digital Image Processing """ import numpy as np from cv2 import COLOR_BGR2GRAY, cvtColor, imread from numpy import array, uint8 from PIL import Image from digital_image_processing import change_contrast as cc from digital_image_processing import convert_to_negative as cn from digital_image_processing import sepia as sp from digital_image_processing.dithering import burkes as bs from digital_image_processing.edge_detection import canny from digital_image_processing.filters import convolve as conv from digital_image_processing.filters import gaussian_filter as gg from digital_image_processing.filters import local_binary_pattern as lbp from digital_image_processing.filters import median_filter as med from digital_image_processing.filters import sobel_filter as sob from digital_image_processing.resize import resize as rs img = imread(r"digital_image_processing/image_data/lena_small.jpg") gray = cvtColor(img, COLOR_BGR2GRAY) # Test: convert_to_negative() def test_convert_to_negative(): negative_img = cn.convert_to_negative(img) # assert negative_img array for at least one True assert negative_img.any() # Test: change_contrast() def test_change_contrast(): with Image.open("digital_image_processing/image_data/lena_small.jpg") as img: # Work around assertion for response assert str(cc.change_contrast(img, 110)).startswith( "<PIL.Image.Image image mode=RGB size=100x100 at" ) # canny.gen_gaussian_kernel() def test_gen_gaussian_kernel(): resp = canny.gen_gaussian_kernel(9, sigma=1.4) # Assert ambiguous array assert resp.all() # canny.py def test_canny(): canny_img = imread("digital_image_processing/image_data/lena_small.jpg", 0) # assert ambiguous array for all == True assert canny_img.all() canny_array = canny.canny(canny_img) # assert canny array for at least one True assert canny_array.any() # filters/gaussian_filter.py def test_gen_gaussian_kernel_filter(): assert gg.gaussian_filter(gray, 5, sigma=0.9).all() def test_convolve_filter(): # laplace diagonals laplace = array([[0.25, 0.5, 0.25], [0.5, -3, 0.5], [0.25, 0.5, 0.25]]) res = conv.img_convolve(gray, laplace).astype(uint8) assert res.any() def test_median_filter(): assert med.median_filter(gray, 3).any() def test_sobel_filter(): grad, theta = sob.sobel_filter(gray) assert grad.any() assert theta.any() def test_sepia(): sepia = sp.make_sepia(img, 20) assert sepia.all() def test_burkes(file_path: str = "digital_image_processing/image_data/lena_small.jpg"): burkes = bs.Burkes(imread(file_path, 1), 120) burkes.process() assert burkes.output_img.any() def test_nearest_neighbour( file_path: str = "digital_image_processing/image_data/lena_small.jpg", ): nn = rs.NearestNeighbour(imread(file_path, 1), 400, 200) nn.process() assert nn.output.any() def test_local_binary_pattern(): # pull request 10161 before: # "digital_image_processing/image_data/lena.jpg" # after: "digital_image_processing/image_data/lena_small.jpg" from os import getenv # Speed up our Continuous Integration tests file_name = "lena_small.jpg" if getenv("CI") else "lena.jpg" file_path = f"digital_image_processing/image_data/{file_name}" # Reading the image and converting it to grayscale image = imread(file_path, 0) # Test for get_neighbors_pixel function() return not None x_coordinate = 0 y_coordinate = 0 center = image[x_coordinate][y_coordinate] neighbors_pixels = lbp.get_neighbors_pixel( image, x_coordinate, y_coordinate, center ) assert neighbors_pixels is not None # Test for local_binary_pattern function() # Create a numpy array as the same height and width of read image lbp_image = np.zeros((image.shape[0], image.shape[1])) # Iterating through the image and calculating the local binary pattern value # for each pixel. for i in range(image.shape[0]): for j in range(image.shape[1]): lbp_image[i][j] = lbp.local_binary_value(image, i, j) assert lbp_image.any()

TheAlgorithms/Python

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def rgb_to_cmyk(r_input: int, g_input: int, b_input: int) -> tuple[int, int, int, int]: """ Simple RGB to CMYK conversion. Returns percentages of CMYK paint. https://www.programmingalgorithms.com/algorithm/rgb-to-cmyk/ Note: this is a very popular algorithm that converts colors linearly and gives only approximate results. Actual preparation for printing requires advanced color conversion considering the color profiles and parameters of the target device. >>> rgb_to_cmyk(255, 200, "a") Traceback (most recent call last): ... ValueError: Expected int, found (<class 'int'>, <class 'int'>, <class 'str'>) >>> rgb_to_cmyk(255, 255, 999) Traceback (most recent call last): ... ValueError: Expected int of the range 0..255 >>> rgb_to_cmyk(255, 255, 255) # white (0, 0, 0, 0) >>> rgb_to_cmyk(128, 128, 128) # gray (0, 0, 0, 50) >>> rgb_to_cmyk(0, 0, 0) # black (0, 0, 0, 100) >>> rgb_to_cmyk(255, 0, 0) # red (0, 100, 100, 0) >>> rgb_to_cmyk(0, 255, 0) # green (100, 0, 100, 0) >>> rgb_to_cmyk(0, 0, 255) # blue (100, 100, 0, 0) """ if ( not isinstance(r_input, int) or not isinstance(g_input, int) or not isinstance(b_input, int) ): msg = f"Expected int, found {type(r_input), type(g_input), type(b_input)}" raise ValueError(msg) if not 0 <= r_input < 256 or not 0 <= g_input < 256 or not 0 <= b_input < 256: raise ValueError("Expected int of the range 0..255") # changing range from 0..255 to 0..1 r = r_input / 255 g = g_input / 255 b = b_input / 255 k = 1 - max(r, g, b) if k == 1: # pure black return 0, 0, 0, 100 c = round(100 * (1 - r - k) / (1 - k)) m = round(100 * (1 - g - k) / (1 - k)) y = round(100 * (1 - b - k) / (1 - k)) k = round(100 * k) return c, m, y, k if __name__ == "__main__": from doctest import testmod testmod()

def rgb_to_cmyk(r_input: int, g_input: int, b_input: int) -> tuple[int, int, int, int]: """ Simple RGB to CMYK conversion. Returns percentages of CMYK paint. https://www.programmingalgorithms.com/algorithm/rgb-to-cmyk/ Note: this is a very popular algorithm that converts colors linearly and gives only approximate results. Actual preparation for printing requires advanced color conversion considering the color profiles and parameters of the target device. >>> rgb_to_cmyk(255, 200, "a") Traceback (most recent call last): ... ValueError: Expected int, found (<class 'int'>, <class 'int'>, <class 'str'>) >>> rgb_to_cmyk(255, 255, 999) Traceback (most recent call last): ... ValueError: Expected int of the range 0..255 >>> rgb_to_cmyk(255, 255, 255) # white (0, 0, 0, 0) >>> rgb_to_cmyk(128, 128, 128) # gray (0, 0, 0, 50) >>> rgb_to_cmyk(0, 0, 0) # black (0, 0, 0, 100) >>> rgb_to_cmyk(255, 0, 0) # red (0, 100, 100, 0) >>> rgb_to_cmyk(0, 255, 0) # green (100, 0, 100, 0) >>> rgb_to_cmyk(0, 0, 255) # blue (100, 100, 0, 0) """ if ( not isinstance(r_input, int) or not isinstance(g_input, int) or not isinstance(b_input, int) ): msg = f"Expected int, found {type(r_input), type(g_input), type(b_input)}" raise ValueError(msg) if not 0 <= r_input < 256 or not 0 <= g_input < 256 or not 0 <= b_input < 256: raise ValueError("Expected int of the range 0..255") # changing range from 0..255 to 0..1 r = r_input / 255 g = g_input / 255 b = b_input / 255 k = 1 - max(r, g, b) if k == 1: # pure black return 0, 0, 0, 100 c = round(100 * (1 - r - k) / (1 - k)) m = round(100 * (1 - g - k) / (1 - k)) y = round(100 * (1 - b - k) / (1 - k)) k = round(100 * k) return c, m, y, k if __name__ == "__main__": from doctest import testmod testmod()

TheAlgorithms/Python

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# Minimum cut on Ford_Fulkerson algorithm. test_graph = [ [0, 16, 13, 0, 0, 0], [0, 0, 10, 12, 0, 0], [0, 4, 0, 0, 14, 0], [0, 0, 9, 0, 0, 20], [0, 0, 0, 7, 0, 4], [0, 0, 0, 0, 0, 0], ] def bfs(graph, s, t, parent): # Return True if there is node that has not iterated. visited = [False] * len(graph) queue = [s] visited[s] = True while queue: u = queue.pop(0) for ind in range(len(graph[u])): if visited[ind] is False and graph[u][ind] > 0: queue.append(ind) visited[ind] = True parent[ind] = u return visited[t] def mincut(graph, source, sink): """This array is filled by BFS and to store path >>> mincut(test_graph, source=0, sink=5) [(1, 3), (4, 3), (4, 5)] """ parent = [-1] * (len(graph)) max_flow = 0 res = [] temp = [i[:] for i in graph] # Record original cut, copy. while bfs(graph, source, sink, parent): path_flow = float("Inf") s = sink while s != source: # Find the minimum value in select path path_flow = min(path_flow, graph[parent[s]][s]) s = parent[s] max_flow += path_flow v = sink while v != source: u = parent[v] graph[u][v] -= path_flow graph[v][u] += path_flow v = parent[v] for i in range(len(graph)): for j in range(len(graph[0])): if graph[i][j] == 0 and temp[i][j] > 0: res.append((i, j)) return res if __name__ == "__main__": print(mincut(test_graph, source=0, sink=5))

# Minimum cut on Ford_Fulkerson algorithm. test_graph = [ [0, 16, 13, 0, 0, 0], [0, 0, 10, 12, 0, 0], [0, 4, 0, 0, 14, 0], [0, 0, 9, 0, 0, 20], [0, 0, 0, 7, 0, 4], [0, 0, 0, 0, 0, 0], ] def bfs(graph, s, t, parent): # Return True if there is node that has not iterated. visited = [False] * len(graph) queue = [s] visited[s] = True while queue: u = queue.pop(0) for ind in range(len(graph[u])): if visited[ind] is False and graph[u][ind] > 0: queue.append(ind) visited[ind] = True parent[ind] = u return visited[t] def mincut(graph, source, sink): """This array is filled by BFS and to store path >>> mincut(test_graph, source=0, sink=5) [(1, 3), (4, 3), (4, 5)] """ parent = [-1] * (len(graph)) max_flow = 0 res = [] temp = [i[:] for i in graph] # Record original cut, copy. while bfs(graph, source, sink, parent): path_flow = float("Inf") s = sink while s != source: # Find the minimum value in select path path_flow = min(path_flow, graph[parent[s]][s]) s = parent[s] max_flow += path_flow v = sink while v != source: u = parent[v] graph[u][v] -= path_flow graph[v][u] += path_flow v = parent[v] for i in range(len(graph)): for j in range(len(graph[0])): if graph[i][j] == 0 and temp[i][j] > 0: res.append((i, j)) return res if __name__ == "__main__": print(mincut(test_graph, source=0, sink=5))