diff --git a/DIRECTORY.md b/DIRECTORY.md
index b1a23a239b01..015efb3c796d 100644
--- a/DIRECTORY.md
+++ b/DIRECTORY.md
@@ -54,13 +54,12 @@
* [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)
## Blockchain
- * [Chinese Remainder Theorem](blockchain/chinese_remainder_theorem.py)
* [Diophantine Equation](blockchain/diophantine_equation.py)
- * [Modular Division](blockchain/modular_division.py)
## Boolean Algebra
* [And Gate](boolean_algebra/and_gate.py)
@@ -101,11 +100,13 @@
* [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)
@@ -172,6 +173,7 @@
## Data Structures
* Arrays
+ * [Equilibrium Index In Array](data_structures/arrays/equilibrium_index_in_array.py)
* [Median Two Array](data_structures/arrays/median_two_array.py)
* [Permutations](data_structures/arrays/permutations.py)
* [Prefix Sum](data_structures/arrays/prefix_sum.py)
@@ -352,6 +354,7 @@
* [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)
* [Word Break](dynamic_programming/word_break.py)
@@ -360,6 +363,7 @@
* [Apparent Power](electronics/apparent_power.py)
* [Builtin Voltage](electronics/builtin_voltage.py)
* [Carrier Concentration](electronics/carrier_concentration.py)
+ * [Charging Capacitor](electronics/charging_capacitor.py)
* [Circular Convolution](electronics/circular_convolution.py)
* [Coulombs Law](electronics/coulombs_law.py)
* [Electric Conductivity](electronics/electric_conductivity.py)
@@ -466,6 +470,8 @@
* [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)
@@ -524,6 +530,10 @@
* Local Weighted Learning
* [Local Weighted Learning](machine_learning/local_weighted_learning/local_weighted_learning.py)
* [Logistic Regression](machine_learning/logistic_regression.py)
+ * Loss Functions
+ * [Binary Cross Entropy](machine_learning/loss_functions/binary_cross_entropy.py)
+ * [Huber Loss](machine_learning/loss_functions/huber_loss.py)
+ * [Mean Squared Error](machine_learning/loss_functions/mean_squared_error.py)
* [Mfcc](machine_learning/mfcc.py)
* [Multilayer Perceptron Classifier](machine_learning/multilayer_perceptron_classifier.py)
* [Polynomial Regression](machine_learning/polynomial_regression.py)
@@ -564,7 +574,9 @@
* [Carmichael Number](maths/carmichael_number.py)
* [Catalan Number](maths/catalan_number.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)
@@ -591,6 +603,7 @@
* [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)
* [Greedy Coin Change](maths/greedy_coin_change.py)
* [Hamming Numbers](maths/hamming_numbers.py)
@@ -618,7 +631,9 @@
* [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)
@@ -720,12 +735,16 @@
## 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)
* [Sigmoid Linear Unit](neural_network/activation_functions/sigmoid_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)
* [Back Propagation Neural Network](neural_network/back_propagation_neural_network.py)
* [Convolution Neural Network](neural_network/convolution_neural_network.py)
* [Perceptron](neural_network/perceptron.py)
@@ -779,6 +798,7 @@
* [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)
@@ -1101,6 +1121,7 @@
* [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)
@@ -1201,6 +1222,7 @@
* [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)
* [Top K Frequent Words](strings/top_k_frequent_words.py)
* [Upper](strings/upper.py)
diff --git a/maths/binary_exponentiation_2.py b/maths/binary_exponentiation_2.py
index 9cd143e09207..edb6b66b2594 100644
--- a/maths/binary_exponentiation_2.py
+++ b/maths/binary_exponentiation_2.py
@@ -1,17 +1,33 @@
"""
-* Binary Exponentiation for Powers
-* This is a method to find a^b in a time complexity of O(log b)
-* This is one of the most commonly used methods of finding powers.
-* Also useful in cases where solution to (a^b)%c is required,
-* where a,b,c can be numbers over the computers calculation limits.
-* Done using iteration, can also be done using recursion
-
-* @author chinmoy159
-* @version 1.0 dated 10/08/2017
+Binary Exponentiation
+This is a method to find a^b in O(log b) time complexity
+This is one of the most commonly used methods of exponentiation
+It's also useful when the solution to (a^b) % c is required because a, b, c may be
+over the computer's calculation limits
+
+Let's say you need to calculate a ^ b
+- RULE 1 : a ^ b = (a*a) ^ (b/2) ---- example : 4 ^ 4 = (4*4) ^ (4/2) = 16 ^ 2
+- RULE 2 : IF b is odd, then a ^ b = a * (a ^ (b - 1)), where b - 1 is even
+Once b is even, repeat the process until b = 1 or b = 0, because a^1 = a and a^0 = 1
+
+For modular exponentiation, we use the fact that (a*b) % c = ((a%c) * (b%c)) % c
+Now apply RULE 1 or 2 as required
+
+@author chinmoy159
"""
def b_expo(a: int, b: int) -> int:
+ """
+ >>> b_expo(2, 10)
+ 1024
+ >>> b_expo(9, 0)
+ 1
+ >>> b_expo(0, 12)
+ 0
+ >>> b_expo(4, 12)
+ 16777216
+ """
res = 1
while b > 0:
if b & 1:
@@ -24,6 +40,16 @@ def b_expo(a: int, b: int) -> int:
def b_expo_mod(a: int, b: int, c: int) -> int:
+ """
+ >>> b_expo_mod(2, 10, 1000000007)
+ 1024
+ >>> b_expo_mod(11, 13, 19)
+ 11
+ >>> b_expo_mod(0, 19, 20)
+ 0
+ >>> b_expo_mod(15, 5, 4)
+ 3
+ """
res = 1
while b > 0:
if b & 1:
@@ -33,18 +59,3 @@ def b_expo_mod(a: int, b: int, c: int) -> int:
b >>= 1
return res
-
-
-"""
-* Wondering how this method works !
-* It's pretty simple.
-* Let's say you need to calculate a ^ b
-* RULE 1 : a ^ b = (a*a) ^ (b/2) ---- example : 4 ^ 4 = (4*4) ^ (4/2) = 16 ^ 2
-* RULE 2 : IF b is ODD, then ---- a ^ b = a * (a ^ (b - 1)) :: where (b - 1) is even.
-* Once b is even, repeat the process to get a ^ b
-* Repeat the process till b = 1 OR b = 0, because a^1 = a AND a^0 = 1
-*
-* As far as the modulo is concerned,
-* the fact : (a*b) % c = ((a%c) * (b%c)) % c
-* Now apply RULE 1 OR 2 whichever is required.
-"""