logo in word cloud
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@@ -194,13 +194,13 @@ def _():
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# Start with loading all necessary libraries
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import numpy as np
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from os import path
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from PIL import Image
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from PIL import Image, ImageDraw
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from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator
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import matplotlib.pyplot as plt
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import warnings
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warnings.filterwarnings("ignore")
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return Image, WordCloud, np, plt
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return Image, ImageDraw, WordCloud, np, plt
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@app.cell
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@@ -222,11 +222,23 @@ def _(df):
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# create list of keywords sorted by their frequencies. only store the keyword
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sorted_keywords = sorted(keyword_freq_filtered.items(), key=lambda x: x[1], reverse=True)
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sorted_keywords_list = [kw for kw, freq in sorted_keywords]
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sorted_keywords_list = [f"{kw}:{freq}" for kw, freq in sorted_keywords]
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sorted_keywords_list
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return (keyword_freq_filtered,)
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@app.cell
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def _():
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IGNORE_WORDS = {
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'chase as a brand': [
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"brand"
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]
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}
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return (IGNORE_WORDS,)
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@app.cell
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def _(plt):
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import random
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@@ -248,37 +260,137 @@ def _(plt):
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@app.cell
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def _(Image, np):
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chase_mask = np.array(Image.open("./data/assets/Chase-National-Bank-Logo.png"))
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def _():
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# chase_mask = np.array(Image.open("./data/assets/Chase-National-Bank-Logo.png"))
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def transform_format(val):
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if val == 0:
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return 255
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else:
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return 1
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# def transform_format(val):
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# if val == 0:
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# return 255
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# else:
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# return 1
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transformed_chase_mask = np.ndarray((chase_mask.shape[0], chase_mask.shape[1]), np.int32)
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for i in range(len(chase_mask)):
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transformed_chase_mask[i] = list(map(transform_format, chase_mask[i]))
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# transformed_chase_mask = np.ndarray((chase_mask.shape[0], chase_mask.shape[1]), np.int32)
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# for i in range(len(chase_mask)):
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# transformed_chase_mask[i] = list(map(transform_format, chase_mask[i]))
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return
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@app.cell
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def _(WordCloud, blue_color_func, keyword_freq_filtered, mo, plt):
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wordcloud = WordCloud(
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background_color='white',
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width=800,
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max_font_size=60,
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max_words=20,
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# colormap='Blues',
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# relative_scaling=0.5, # Use rank in sorted frequency list instead of pure frequency
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color_func=blue_color_func,
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# mask=chase_mask
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# random_state=42
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).generate_from_frequencies(keyword_freq_filtered)
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def _(mo):
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buffer = -100 # Adjust this to increase/decrease space between logo and words
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canvas_size = (1200, 800)
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logo_switch = mo.ui.switch(label="Include Chase Logo", value=False)
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logo_switch
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return buffer, canvas_size, logo_switch
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@app.cell(hide_code=True)
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def _(
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IGNORE_WORDS,
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Image,
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ImageDraw,
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WordCloud,
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blue_color_func,
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buffer,
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canvas_size,
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keyword_freq_filtered,
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logo_switch,
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mo,
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np,
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plt,
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tag_select,
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):
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# remove specific keywords depending on selected tag
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if IGNORE_WORDS.get(tag_select.value.lower()):
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for word in IGNORE_WORDS[tag_select.value.lower()]:
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if word in keyword_freq_filtered:
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del keyword_freq_filtered[word]
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if logo_switch.value:
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# 1. Load the logo
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# Make sure this path points to your uploaded file
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logo_path = "./data/assets/JP-Morgan-Chase-Symbol.png"
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logo = Image.open(logo_path).convert("RGBA")
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# Optional: Resize logo if it's too large or small for the canvas
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# target_width = 600
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# ratio = target_width / logo.width
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# logo = logo.resize((target_width, int(logo.height * ratio)), Image.Resampling.LANCZOS)
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target_width = 600 # Set a reasonable size for the logo
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if logo.width > target_width:
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ratio = target_width / logo.width
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new_height = int(logo.height * ratio)
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# Use Image.Resampling.LANCZOS for high-quality downsampling
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# If you get an error, try Image.LANCZOS or Image.ANTIALIAS
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logo = logo.resize((target_width, new_height), Image.Resampling.LANCZOS)
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# 3. Create the mask (0 = draw here, 255 = don't draw here)
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# Initialize with 0 (black/draw everywhere)
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mask_image = Image.new("L", canvas_size, 0)
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draw = ImageDraw.Draw(mask_image)
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# 4. Draw a protected circular area in the center
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center = (canvas_size[0] // 2, canvas_size[1] // 2)
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# Calculate radius: half of logo max dimension + buffer
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radius = (max(logo.size) // 2) + buffer
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# Draw the white circle (255) which the WordCloud will avoid
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draw.ellipse(
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(center[0] - radius, center[1] - radius, center[0] + radius, center[1] + radius),
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fill=255
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)
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chase_mask = np.array(mask_image)
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# Generate the WordCloud
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wordcloud = WordCloud(
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background_color='white',
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width=canvas_size[0],
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height=canvas_size[1],
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max_font_size=100, # Increased font size for larger canvas
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max_words=20, # Increased word count to fill space
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color_func=blue_color_func,
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mask=chase_mask, # Apply the circular mask
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contour_width=0,
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contour_color='steelblue'
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).generate_from_frequencies(keyword_freq_filtered)
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else:
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# Generate the WordCloud
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wordcloud = WordCloud(
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background_color='white',
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width=canvas_size[0],
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height=canvas_size[1],
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max_font_size=100, # Increased font size for larger canvas
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max_words=20, # Increased word count to fill space
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color_func=blue_color_func,
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# mask=chase_mask, # Apply the circular mask
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# contour_width=0,
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# contour_color='steelblue'
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).generate_from_frequencies(keyword_freq_filtered)
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# Convert WordCloud to Image to composite the logo
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wc_image = wordcloud.to_image()
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if logo_switch.value:
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# Calculate position to center the logo
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logo_pos = (
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(canvas_size[0] - logo.width) // 2,
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(canvas_size[1] - logo.height) // 2
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)
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# Paste logo (using alpha channel as mask to keep transparency)
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wc_image.paste(logo, logo_pos, logo)
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# Display the generated image
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fig = plt.figure(figsize=(7,7))
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# Display the generated image:
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plt.imshow(wordcloud, interpolation='bilinear')
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plt.imshow(wc_image, interpolation='bilinear')
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plt.axis("off")
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plt.show()
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@@ -289,11 +401,11 @@ def _(WordCloud, blue_color_func, keyword_freq_filtered, mo, plt):
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on_click=lambda val: True
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)
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save_wordcloud_btn
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return save_wordcloud_btn, wordcloud
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return save_wordcloud_btn, wc_image
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@app.cell
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def _(WORKING_DIR, mo, save_wordcloud_btn, tag_select, wordcloud):
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def _(WORKING_DIR, mo, save_wordcloud_btn, tag_select, wc_image):
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# Wait for start processing button
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mo.stop(not save_wordcloud_btn.value, "Click button above to save wordcloud image")
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@@ -315,7 +427,7 @@ def _(WORKING_DIR, mo, save_wordcloud_btn, tag_select, wordcloud):
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next_number = 1
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fpath = WORKING_DIR / f'wordcloud_{tag_select.value.replace(" ", "-")}_{next_number}.png'
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wordcloud.to_file(fpath)
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wc_image.save(fpath)
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mo.md(f"Wordcloud saved to: {fpath}")
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return
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