Added a downloads badge to the README

.pre-commit-config.yaml

@@ -1,10 +1,10 @@
 repos:
 - repo: https://github.com/ambv/black
-  rev: 19.3b0
+  rev: 22.6.0
   hooks:
-  - id:  black
+  - id: black
 - repo: https://github.com/pre-commit/pre-commit-hooks
-  rev: v4.0.1
+  rev: v4.3.0
   hooks:
   - id: check-yaml
   - id: check-toml
@@ -16,7 +16,7 @@ repos:
     args:
     - --maxkb=1000
 - repo: https://github.com/Lucas-C/pre-commit-hooks
-  rev: v1.1.10
+  rev: v1.3.0
   hooks:
     -   id: remove-crlf
     -   id: remove-tabs

README.md

@@ -8,7 +8,7 @@
 [![Deploy](https://github.com/hasnainroopawalla/ShowML/actions/workflows/deploy.yml/badge.svg)](https://github.com/hasnainroopawalla/ShowML/actions/workflows/deploy.yml)
 [![PyPi version](https://img.shields.io/pypi/v/showml.svg)](https://pypi.python.org/pypi/showml/)
 [![Python versions](https://img.shields.io/pypi/pyversions/showml.svg?style=plastic)](https://img.shields.io/pypi/pyversions/showml.svg?style=plastic)
-![Status](https://img.shields.io/badge/status-stable-green.svg)
+![Downloads](https://img.shields.io/pypi/dm/showml.svg)
 
 
 A Python package of Machine Learning Algorithms implemented from scratch.
@@ -23,6 +23,7 @@ The aim of this package is to present the working behind fundamental Machine Lea
 - [Getting Started](#getting_started)
 - [Contents](#contents)
 - [Contributing](#contributing)
+- [License](#license)
 
 
 ## 🏁 Getting Started <a name = "getting_started"></a>
@@ -104,3 +105,7 @@ _ShowML_ currently includes the following content, however, this repository will
    $ pytest
    ```
 5. Open a Pull Request and I'll review it.
+
+
+## 📄 License <a name = "license"></a>
+This project is licensed under the MIT License - see the [LICENSE](https://github.com/hasnainroopawalla/ShowML/blob/bbaacc81779437ea2ef09d7869b1f8a824f80353/LICENSE) file for details.

setup.py

@@ -8,7 +8,7 @@
 
 setup(
     name="showml",
-    version="1.5.11",
+    version="1.5.12",
     packages=find_packages(exclude="tests"),
     description="A Python package of Machine Learning Algorithms implemented from scratch",
     long_description=long_description,

showml/deep_learning/activations.py

@@ -3,8 +3,7 @@
 
 
 class Sigmoid(Activation):
-    """A layer which applies the Sigmoid operation to an input.
-    """
+    """A layer which applies the Sigmoid operation to an input."""
 
     def forward(self, X: np.ndarray) -> np.ndarray:
         return 1 / (1 + np.exp(-X))
@@ -14,8 +13,7 @@ def backward(self, X: np.ndarray) -> np.ndarray:
 
 
 class Relu(Activation):
-    """A layer which applies the ReLU operation to an input.
-    """
+    """A layer which applies the ReLU operation to an input."""
 
     def forward(self, X: np.ndarray) -> np.ndarray:
         return abs(X) * (X > 0)
@@ -25,8 +23,7 @@ def backward(self, X: np.ndarray) -> np.ndarray:
 
 
 class Softmax(Activation):
-    """A layer which applies the Softmax operation to an input.
-    """
+    """A layer which applies the Softmax operation to an input."""
 
     def forward(self, X: np.ndarray) -> np.ndarray:
         e_x = np.exp(X - np.max(X, axis=-1, keepdims=True))

showml/deep_learning/base_layer.py

@@ -5,8 +5,7 @@
 
 
 class Layer(ABC):
-    """A layer class.
-    """
+    """A layer class."""
 
     def __init__(
         self, input_shape: Tuple[int] = (0,), has_weights: bool = True

showml/deep_learning/layers.py

@@ -5,8 +5,7 @@
 
 
 class Dense(Layer):
-    """A Dense Layer.
-    """
+    """A Dense Layer."""
 
     def __init__(self, num_nodes: int, input_shape: Tuple[int] = (0,)):
         """Constructor for the Dense Layer.
@@ -27,7 +26,7 @@ def initialize_params(self, optimizer: Optimizer) -> None:
         self.bias = np.zeros((1, self.num_nodes))
 
     def get_params_count(self) -> int:
-        return np.prod(self.weights.shape) + np.prod(self.bias.shape)
+        return int(np.prod(self.weights.shape) + np.prod(self.bias.shape))
 
     def get_output_shape(self) -> Tuple[int]:
         return (self.num_nodes,)

showml/deep_learning/model.py

@@ -10,12 +10,10 @@
 
 
 class Sequential:
-    """A Sequential model (deep neural network) with various types of layers and activation functions.
-    """
+    """A Sequential model (deep neural network) with various types of layers and activation functions."""
 
     def __init__(self) -> None:
-        """Constructor for the Sequential model class.
-        """
+        """Constructor for the Sequential model class."""
         self.layers: List[Layer] = []
 
     def compile(
@@ -39,8 +37,7 @@ def compile(
         self.initialize_layers()
 
     def initialize_layers(self) -> None:
-        """Initializes all the layers with the specified optimizer and parameters.
-        """
+        """Initializes all the layers with the specified optimizer and parameters."""
         for layer_idx, layer in enumerate(self.layers):
             if layer_idx > 0:
                 # If this layer is NOT the first layer of the network, then input shape = output shape of previous layer
@@ -132,8 +129,7 @@ def predict(self, X: np.ndarray) -> np.ndarray:
         return self.forward_pass(X)
 
     def summary(self) -> None:
-        """Summarizes the model by displaying all layers, their parameters and total number of trainable parameters.
-        """
+        """Summarizes the model by displaying all layers, their parameters and total number of trainable parameters."""
         total_params = 0
         print(AsciiTable([[self.__class__.__name__]]).table)
         summary_data = [["Layer", "Params", "Output Shape"]]

showml/linear_model/regression.py

@@ -11,8 +11,7 @@
 
 
 class Regression(ABC):
-    """Base Regression class.
-    """
+    """Base Regression class."""
 
     def compile(
         self, optimizer: Optimizer, loss: Loss, metrics: List[Callable] = []
@@ -62,8 +61,7 @@ def evaluate(self, X: np.ndarray, y: np.ndarray) -> None:
         print(text_to_display)
 
     def plot_metrics(self) -> None:
-        """Display the plot after training for the specified metrics
-        """
+        """Display the plot after training for the specified metrics"""
         for metric in self.history:
             generic_metric_plot(metric, self.history[metric])
 

showml/losses/loss_functions.py

@@ -23,8 +23,7 @@ def parameter_gradient(
 
 class BinaryCrossEntropy(Loss):
     def objective(self, y: np.ndarray, z: np.ndarray) -> float:
-        """Also known as Log Loss
-        """
+        """Also known as Log Loss"""
         num_samples = len(y)
         # Avoid division by zero
         z = np.clip(z, 1e-15, 1 - 1e-15)
@@ -46,8 +45,7 @@ def parameter_gradient(
 
 class CrossEntropy(Loss):
     def objective(self, y: np.ndarray, z: np.ndarray) -> float:
-        """param y: one hot encoded values
-        """
+        """param y: one hot encoded values"""
         num_samples = len(z)
         z = np.clip(z, 1e-15, 1.0 - 1e-15)
         return -np.sum(y * np.log(z)) / num_samples

showml/optimizers/base_optimizer.py

@@ -4,8 +4,7 @@
 
 
 class Optimizer(ABC):
-    """The Base Optimizer Class.
-    """
+    """The Base Optimizer Class."""
 
     def __init__(self, learning_rate: float):
         """Constructor for the Base Optimzer class.

showml/simulations/conways_game_of_life/event.py

@@ -3,8 +3,7 @@
 
 
 class Action(Enum):
-    """This class defines the different Actions in the game.
-    """
+    """This class defines the different Actions in the game."""
 
     START = auto()
     STOP = auto()
@@ -15,8 +14,7 @@ class Action(Enum):
 
 @dataclass
 class Event:
-    """This class defines an Event (and also the row, column if a cell is toggled)
-    """
+    """This class defines an Event (and also the row, column if a cell is toggled)"""
 
     action: Action
     row: int = 0

showml/simulations/conways_game_of_life/event_handler.py

@@ -4,8 +4,7 @@
 
 
 class EventHandler:
-    """The EventHandler class responsible for observing events taking place in the window as well as initializing and managing the Grid.
-    """
+    """The EventHandler class responsible for observing events taking place in the window as well as initializing and managing the Grid."""
 
     def __init__(self, window: GameWindow) -> None:
         """Constructor for the EventHandler class.

showml/simulations/conways_game_of_life/game_of_life.py

@@ -5,8 +5,7 @@
 
 
 class GameOfLife:
-    """A simulation of Conway's Game of Life (Cellular Automaton): https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life
-    """
+    """A simulation of Conway's Game of Life (Cellular Automaton): https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life"""
 
     def __init__(self, num_rows: int = 50, num_columns: int = 100) -> None:
         """Constructor for the GameOfLife class.
@@ -28,20 +27,17 @@ def __init__(self, num_rows: int = 50, num_columns: int = 100) -> None:
         }
 
     def start_event(self, row: int, column: int) -> None:
-        """This method runs when the game starts.
-        """
+        """This method runs when the game starts."""
         self.game_running = True
         self.delay = 150
 
     def stop_event(self, row: int, column: int) -> None:
-        """This method runs when the game is stopped.
-        """
+        """This method runs when the game is stopped."""
         self.game_running = False
         self.delay = 0
 
     def reset_event(self, row: int, column: int) -> None:
-        """This method runs when the RESET button is pressed.
-        """
+        """This method runs when the RESET button is pressed."""
         self.game_running = False
         self.window.grid.reset_grid()
         self.delay = 0
@@ -59,8 +55,7 @@ def no_event(self, row: int, column: int) -> None:
         pass
 
     def run(self) -> None:
-        """This method runs the game loop by communicating with the EventHandler to receive event information.
-        """
+        """This method runs the game loop by communicating with the EventHandler to receive event information."""
         while True:
             if self.game_running:
                 self.window.grid.update_grid()

showml/simulations/conways_game_of_life/game_window.py

@@ -11,8 +11,7 @@
 
 
 class GameWindow:
-    """The GameWindow class responsible for observing events taking place in the window as well as initializing and managing the Grid.
-    """
+    """The GameWindow class responsible for observing events taking place in the window as well as initializing and managing the Grid."""
 
     def __init__(self, grid: Grid) -> None:
         """Constructor for the GameWindow class.
@@ -55,8 +54,7 @@ def display_window_and_grid(self, delay: int) -> None:
         self.clock.tick(60)
 
     def _display_buttons_and_text(self) -> None:
-        """This private method displays the buttons and the text objects in the window.
-        """
+        """This private method displays the buttons and the text objects in the window."""
         self.SCREEN.fill(Color.BLACK)
         for button in self.buttons:
             # Button
@@ -75,8 +73,7 @@ def _display_buttons_and_text(self) -> None:
             )
 
     def _display_grid(self) -> None:
-        """This private method displays the entire grid in the window.
-        """
+        """This private method displays the entire grid in the window."""
         for row in range(self.grid.num_rows):
             for column in range(self.grid.num_columns):
                 if self.grid.grid[row][column] == 1:

showml/simulations/conways_game_of_life/grid.py

@@ -2,8 +2,7 @@
 
 
 class Grid:
-    """A 2D Grid class to display the cells.
-    """
+    """A 2D Grid class to display the cells."""
 
     def __init__(self, num_rows: int, num_columns: int) -> None:
         """[summary]
@@ -60,8 +59,7 @@ def update_grid(self) -> None:
         self.grid = new_grid
 
     def reset_grid(self) -> None:
-        """This method resets the grid i.e., kills all the cells.
-        """
+        """This method resets the grid i.e., kills all the cells."""
         self.grid = np.zeros((self.num_rows, self.num_columns))
 
     def toggle_cell_value(self, row: int, column: int) -> None:

showml/utils/dataset.py

@@ -23,14 +23,12 @@ def __init__(self, X: np.ndarray, y: np.ndarray) -> None:
         self.valid_dataset_length()
 
     def validate_data_types(self) -> None:
-        """Validates if X and y are NumPy arrays (np.ndarray).
-        """
+        """Validates if X and y are NumPy arrays (np.ndarray)."""
         if not (isinstance(self.X, np.ndarray) and isinstance(self.y, np.ndarray)):
             raise DataTypeError("X and y must be NumPy arrays (np.ndarray)")
 
     def valid_dataset_length(self) -> None:
-        """Validates if X and y have the same number of samples.
-        """
+        """Validates if X and y have the same number of samples."""
         if self.X.shape[0] != self.y.shape[0]:
             raise DatasetSizeMismatchError(
                 "Dimension 1 (number of samples) of X and y must the same"

showml/utils/exceptions.py

@@ -1,18 +1,14 @@
 class DatasetSizeMismatchError(Exception):
-    """Raised when X and y have different lengths.
-    """
+    """Raised when X and y have different lengths."""
 
 
 class DataTypeError(Exception):
-    """Raised when a variable has an unexpected datatype.
-    """
+    """Raised when a variable has an unexpected datatype."""
 
 
 class InvalidShapeError(Exception):
-    """Raised when an unexpected array shape is encountered.
-    """
+    """Raised when an unexpected array shape is encountered."""
 
 
 class InvalidValueError(Exception):
-    """Raised when an unexpected value is encountered.
-    """
+    """Raised when an unexpected value is encountered."""