Updated line 694 and 700 with: p[0] = x and p[1] = y

Updated lines 686-702 with: LaTeX formulation and standalone mathematical notation obverse proper delimiters ‘$$’. Also, swapped p[0] with ‘x’ and p[1] with ‘y'

Updated with debug plot_positions method validating the shape of all_positions [iterations=0,3,7,11] populates three to four visualizations honing in on optimization

Updated line 640 with: gr.components.Textbox(label="Delta, Beta, & Alpha wolves jostling for hierarchy (all other wolves are Omega).")

Updated line 640 with: gr.components.Textbox(label="Delta, Beta, & Alpha wolves jostling for hierarchy\n(all other wolves are Omega). Each number represents a Grey Wolf in the pack of grey wolves.")

Declaring identical iterations=[0,3,7,11] in both the plot_positions constructor and optimize function calling the plot_positions method

Updated the plot_positions constructor with: iterations=[0, 2, 4, 12] and the optimize function calling the plot_positions method positions_plot = gwo.positions(iterations=[0, 2, 4, 12])

Updated the entire plot_positions method with a revised version leveraging a variable producing the correct amount of subplots in the visualization.

Updated with plot_positions method modification iterations=[0, 5, 10, 15] and optimize function gwo.plot_positions call with iterations=[0,5,10,15]

Updating lines 292, 549, and 603 with: allow_pickle = True, (a second one) allow_pickle = True, and gwo.plot_positions(iterations=[0, 25, 50, 120]

Updated lines 546-583 with: plot_positions method leveraging the data capture obverse wolves positions oscillations deriving from all_positions.npy

Updated line 292 with: np.save('all_positions.npy', np.array(self.all_positions))

Updated line 521 with: positions = self.all_positions[i]

Updated line 521 with: positions = self.gpos[i]

Updated line 521 with: positions = self.gpos[ax]

Updated the [optimize function lines 578, 579, 582] with: results = gwo.Results(), pos_text = f"Grey Wolf Positions: {results['pos']}" if results else "No results available.”, return positions_plot, best_fitness_text, best_positions_text, best_fitness_npy, best_positions_npy, gidx_text, pos_text #,vpos_text, Updated line 601 with: gr.components.Textbox(label="Grey Wolves Positions Capture")

Updated lines [optimize functionn 574, 575, 578], and [gr.Interface components 597] with: results = gwo.Results() , vpos_text = f"Grey Wolf Index: {results['vpos']}" if results else "No results available.”, return positions_plot, best_fitness_text, best_positions_text, best_fitness_npy, best_positions_npy, gidx_text, vpos_text, gr.components.Textbox(label="Vpos data capture”)

Updated plot_positions method leveraging functionality deriving from Results method, specifically, pos data

Updated the entire plot_positions method with: Performing a built-in check if vpos is empty or if the first element is not a 2D numpy array.

Updated line 344 with: if not any(vpos): (deriving from the plot_positions method)

Updated lines 335-384 with: a new plot_positions method that plots the positions of the wolves over iterations, deriving from the Results method data capture, specifically vpos

Updated line 350 with: iterations_to_plot = [0, 25, 45, 65]

Updated lines 347-386 with: indentation modifications throughout the method

Updated plot_positions method with: a check you can add to ensure that the self.all_positions list has enough elements before trying to access them

Updated line 342 with: iterations_to_plot = [0, 50, 150, 199] (utilizing iteration 199) Updated lines 362-373 with: indentation now matches indentation found on line 349 for i, iteration in enumerate(iterations_to_plot):

Updated line 342 with: iterations_to_plot = [0, 50, 150, 175] (utilizing iteration 175) instead of 200.

Updated plot_positions with: indentation initializing from for i, iteration in enumerate(iterations_to_plot):

Updated plot_positions method with: Stratagem (logic) that reflects positions of a set of particles (wolves) over SPECIFIC iterations. Here the data visualization captures wolves positions at iterations: 0, 50, 150 and 200. Producing a 2 x 2 grid validating the optimization accurately for the GWO algorithm.

Updated the plot_positions method: def plot_positions(self): """Plot the positions of the particles over the iterations""" fig, axs = plt.subplots(len(self.all_positions), 1, figsize=(10, 5*len(self.all_positions))) for i, positions in enumerate(self.all_positions): # Plot the particles' positions at the current iteration axs[i].scatter(positions[:, 0], positions[:, 1], c='b', alpha=0.5) # Plot the goal position axs[i].scatter([-2.2], [4.3], c='g', marker='s', s=100, label='Goal') # Set plot title and labels axs[i].set_title(f'Iteration {i}') axs[i].set_xlabel('X') axs[i].set_ylabel('Y') axs[i].legend() plt.tight_layout() plt.show() # Save the plot to a BytesIO object buf = BytesIO() plt.savefig(buf, format='png') buf.seek(0) image = Image.open(buf) plt.close() return image

Updated line 413 with: gr.components.Textbox(label="Grey Wolves (each # represents a wolf in the pack) Delta, Beta, & Alpha jostling for hierarchy (all other wolves are Omega)")

Updated line 413: gr.components.Textbox(label="Grey Wolves (each # represents a wolf in the pack) Delta, Beta, & Alpha jostling for hierarcy (all other wolves are Omega)")

Update README.md

Updated with the removal of line 409: gr.components.Image(Additional Plot not necessary)

Updated line 3 with: as plt

Updated swapping of all dimensions into equaling 2 (Example ndim=2)

Create app.py

init!

initial commit