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Update app.py
Browse files
app.py
CHANGED
@@ -62,6 +62,29 @@ if sidebar_option == "Introductory Tutorial":
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# Display a logo or icon
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image = Image.open("1.png") # Path to your image file
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st.image(image, width=200) # You can adjust the width as needed
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# Add content descriptions
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descriptions = [
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@@ -101,29 +124,6 @@ if sidebar_option == "Introductory Tutorial":
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st.write(desc)
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st.write("---")
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# Add the Bubble Sort Simulator button
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if st.button("Bubble Sort Simulator"):
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st.title("Bubble Sort with Animation")
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# Get input array from user
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user_input = st.text_input("Enter the array elements separated by spaces:")
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if user_input:
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arr = list(map(int, user_input.split()))
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# Ask the user if they want an animation
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animate_option = st.radio("Do you want to see the animation?", ("Yes", "No"))
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animate = animate_option == 'Yes'
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# Perform bubble sort and get the steps for animation
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sorted_array, steps = bubble_sort(arr, animate)
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# Display the sorted array
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st.write("Sorted Array:", sorted_array)
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# Show animation if required
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if animate:
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animate_sorting(arr, steps)
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def plot_greedy_coloring(graph):
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# Apply greedy coloring
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graph_coloring = nx.greedy_color(graph)
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# Display a logo or icon
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image = Image.open("1.png") # Path to your image file
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st.image(image, width=200) # You can adjust the width as needed
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# Add the Bubble Sort Simulator button
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if st.button("Bubble Sort Simulator"):
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st.title("Bubble Sort with Animation")
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# Get input array from user
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user_input = st.text_input("Enter the array elements separated by spaces:")
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if user_input:
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arr = list(map(int, user_input.split()))
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# Ask the user if they want an animation
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animate_option = st.radio("Do you want to see the animation?", ("Yes", "No"))
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animate = animate_option == 'Yes'
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# Perform bubble sort and get the steps for animation
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sorted_array, steps = bubble_sort(arr, animate)
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# Display the sorted array
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st.write("Sorted Array:", sorted_array)
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# Show animation if required
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if animate:
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animate_sorting(arr, steps)
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# Add content descriptions
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descriptions = [
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st.write(desc)
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st.write("---")
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def plot_greedy_coloring(graph):
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# Apply greedy coloring
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graph_coloring = nx.greedy_color(graph)
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