EdwardXu commited on
Commit
eea13ab
1 Parent(s): 75b01e7

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +18 -70
app.py CHANGED
@@ -182,96 +182,42 @@ class Search:
182
 
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  import matplotlib.pyplot as plt
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- def plot_pie_chart(category_similarity_scores):
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- """Plot a pie chart of category similarity scores."""
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- categories = list(category_similarity_scores.keys())
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- similarities = list(category_similarity_scores.values())
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- normalized_similarities = [sim / sum(similarities) for sim in similarities]
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-
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- fig, ax = plt.subplots()
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- ax.pie(normalized_similarities, labels=categories, autopct="%1.11f%%", startangle=90)
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- ax.axis('equal') # Equal aspect ratio ensures the pie chart is circular.
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- plt.show()
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-
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-
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-
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- def plot_piechart(sorted_cosine_scores_items):
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- sorted_cosine_scores = np.array([
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- sorted_cosine_scores_items[index][1]
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- for index in range(len(sorted_cosine_scores_items))
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- ]
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- )
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- categories = st.session_state.categories.split(" ")
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- categories_sorted = [
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- categories[sorted_cosine_scores_items[index][0]]
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- for index in range(len(sorted_cosine_scores_items))
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- ]
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  fig, ax = plt.subplots()
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- ax.pie(sorted_cosine_scores, labels=categories_sorted, autopct="%1.1f%%")
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- st.pyplot(fig) # Figure
 
 
 
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  def plot_piechart_helper(sorted_cosine_scores_items):
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- sorted_cosine_scores = np.array(
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- [
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- sorted_cosine_scores_items[index][1]
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- for index in range(len(sorted_cosine_scores_items))
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- ]
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- )
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- categories = st.session_state.categories.split(" ")
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- categories_sorted = [
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- categories[sorted_cosine_scores_items[index][0]]
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- for index in range(len(sorted_cosine_scores_items))
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- ]
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  fig, ax = plt.subplots(figsize=(3, 3))
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  my_explode = np.zeros(len(categories_sorted))
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  my_explode[0] = 0.2
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  if len(categories_sorted) == 3:
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- my_explode[1] = 0.1 # explode this by 0.2
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  elif len(categories_sorted) > 3:
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  my_explode[2] = 0.05
 
235
  ax.pie(
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  sorted_cosine_scores,
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  labels=categories_sorted,
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- autopct="%1.1f%%",
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  explode=my_explode,
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  )
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  return fig
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244
 
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- def plot_piecharts(sorted_cosine_scores_models):
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- scores_list = []
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- categories = st.session_state.categories.split(" ")
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- index = 0
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- for model in sorted_cosine_scores_models:
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- scores_list.append(sorted_cosine_scores_models[model])
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- # scores_list[index] = np.array([scores_list[index][ind2][1] for ind2 in range(len(scores_list[index]))])
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- index += 1
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-
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- if len(sorted_cosine_scores_models) == 2:
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- fig, (ax1, ax2) = plt.subplots(2)
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-
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- categories_sorted = [
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- categories[scores_list[0][index][0]] for index in range(len(scores_list[0]))
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- ]
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- sorted_scores = np.array(
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- [scores_list[0][index][1] for index in range(len(scores_list[0]))]
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- )
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- ax1.pie(sorted_scores, labels=categories_sorted, autopct="%1.1f%%")
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-
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- categories_sorted = [
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- categories[scores_list[1][index][0]] for index in range(len(scores_list[1]))
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- ]
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- sorted_scores = np.array(
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- [scores_list[1][index][1] for index in range(len(scores_list[1]))]
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- )
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- ax2.pie(sorted_scores, labels=categories_sorted, autopct="%1.1f%%")
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-
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- st.pyplot(fig)
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-
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  def plot_alatirchart(sorted_cosine_scores_models):
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  models = list(sorted_cosine_scores_models.keys())
@@ -296,7 +242,9 @@ if 'text_search' not in st.session_state:
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  embeddings_model = Embeddings()
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- model_type = st.sidebar.selectbox("Choose the model", ("50d"), index=1)
 
 
300
 
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  st.title("in in-class coding practice1 Demo")
 
182
 
183
  import matplotlib.pyplot as plt
184
 
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+ def plot_pie_chart(category_simiarity_scores):
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+ categories = list(category_simiarity_scores.keys())
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+ cur_similarities = list(category_simiarity_scores.values())
 
 
 
 
 
 
 
 
 
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+ similarities = [similar / sum(cur_similarities) for similar in cur_similarities]
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  fig, ax = plt.subplots()
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+ ax.pie(similarities, labels=categories,
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+ autopct="%1.11f%%",
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+ startangle=90)
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+ ax.axis('equal')
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+ plt.show()
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198
 
199
  def plot_piechart_helper(sorted_cosine_scores_items):
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+ sorted_cosine_scores = np.array(list(sorted_cosine_scores_items.values()))
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+ categories_sorted = list(sorted_cosine_scores_items.keys())
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+
 
 
 
 
 
 
 
 
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  fig, ax = plt.subplots(figsize=(3, 3))
204
  my_explode = np.zeros(len(categories_sorted))
205
  my_explode[0] = 0.2
206
  if len(categories_sorted) == 3:
207
+ my_explode[1] = 0.1
208
  elif len(categories_sorted) > 3:
209
  my_explode[2] = 0.05
210
+
211
  ax.pie(
212
  sorted_cosine_scores,
213
  labels=categories_sorted,
214
+ autopct="%1.11f%%",
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  explode=my_explode,
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  )
217
 
218
  return fig
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222
  def plot_alatirchart(sorted_cosine_scores_models):
223
  models = list(sorted_cosine_scores_models.keys())
 
242
 
243
  embeddings_model = Embeddings()
244
 
245
+ model_type = "50d"
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+ st.sidebar.write("Model Type: 50d")
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+
248
 
249
 
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  st.title("in in-class coding practice1 Demo")