DebasishDhal99's picture
Converting float to int
a35a874
raw
history blame
2.58 kB
import matplotlib.pyplot as plt
import random
import gradio as gr
import io
def generate_random_walk(iters):
iters = int(iters)
directions = ['east', 'north', 'north', 'south']
start_point = [0, 0]
def distance_from_start(final_coord, start_coord, round_to=2):
return round(np.sqrt((final_coord[0] - start_coord[0])**2 + (final_coord[1] - start_coord[1])**2), round_to)
def step_addition(old_coord, step):
return [sum(x) for x in zip(old_coord, step)]
def step_determination():
direction = random.choice(directions)
if direction == 'east':
return [1, 0]
elif direction == 'west':
return [-1, 0]
elif direction == 'north':
return [0, 1]
elif direction == 'south':
return [0, -1]
coordinate_list = [start_point]
for i in range(iters):
new_step = step_determination()
new_coordinate = step_addition(coordinate_list[-1], new_step)
coordinate_list.append(new_coordinate)
x = [i[0] for i in coordinate_list]
y = [i[1] for i in coordinate_list]
fig, ax = plt.subplots(1)
base_marker_size = 10
markersize = base_marker_size / np.sqrt(iters)
ax.plot(x, y, marker='o', markersize=markersize, linestyle='None')
ax.plot(x[0], y[0], marker='o', markersize=5, color="red")
ax.plot(x[-1], y[-1], marker='o', markersize=5, color="orange")
ax.text(start_point[0], start_point[1], 'Start', color='red')
ax.text(x[-1], y[-1], 'End', color='orange')
x_max_index = x.index(max(x))
x_min_index = x.index(min(x))
y_max_index = y.index(max(y))
y_min_index = y.index(min(y))
info_text = 'Start point=' + str(start_point) + '\n' +'End point=' + str([x[-1],y[-1]]) + '\n' +'Displacement =' + str(distance_from_start([x[-1], y[-1]], start_point)) + '\n' +'Max x = ' + str(max(x)) + '\n' + 'Min x = ' + str(min(x)) + '\n' + 'Max y = ' + str(max(y)) + '\n' + 'Min y = ' + str(min(y))
ax.legend([info_text], loc='best', handlelength=0, handletextpad=0, fancybox=True, fontsize=8)
plt.title('2D Random Walk, iterations = ' + str(iters))
plt.grid()
# Save the plot to an in-memory buffer and return it
buf = io.BytesIO()
plt.savefig(buf, format='png')
buf.seek(0)
return buf.read()
# Create a Gradio interface
iface = gr.Interface(fn=generate_random_walk, inputs=gr.inputs.Number(label="How many random steps"), outputs="image", title="Random Walk Plot")
iface.launch()