# Example
``` python import matplotlib.pyplot as plt import tqdm.auto as tqdm ```
## Plots
Hey, could you generate some really brief simple code that would plot a 2D heat map with contour lines for some function you might make up? Matplotlib is fine. ##### 🤖Reply🤖
Reply details
Certainly! Here’s a snippet of Python code that generates a 2D heatmap with contour lines using Matplotlib: ``` python import numpy as np import matplotlib.pyplot as plt # Define the function to plot def f(x, y): return np.sin(np.sqrt(x**2 + y**2)) # Generate data x = np.linspace(-5, 5, 100) y = np.linspace(-5, 5, 100) X, Y = np.meshgrid(x, y) Z = f(X, Y) # Create the plot plt.figure(figsize=(8, 6)) plt.contourf(X, Y, Z, levels=20, cmap='viridis') plt.colorbar(label='f(x, y)') plt.contour(X, Y, Z, colors='black', levels=10) plt.xlabel('x') plt.ylabel('y') plt.title('2D Heat Map with Contour Lines') plt.show() ``` This code defines a simple function `f` and then uses Matplotlib to create a heatmap of this function along with contour lines. You can run this in your Python environment to see the plot.
``` python import numpy as np import matplotlib.pyplot as plt # Define the function to plot def f(x, y): return np.sin(np.sqrt(x**2 + y**2)) # Generate data x = np.linspace(-5, 5, 100) y = np.linspace(-5, 5, 100) X, Y = np.meshgrid(x, y) Z = f(X, Y) # Create the plot plt.figure(figsize=(8, 6)) plt.contourf(X, Y, Z, levels=20, cmap='viridis') plt.colorbar(label='f(x, y)') plt.contour(X, Y, Z, colors='black', levels=10) plt.xlabel('x') plt.ylabel('y') plt.title('2D Heat Map with Contour Lines') plt.show() ``` :22: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown plt.show() ![](example_files/figure-commonmark/cell-3-output-2.png)
## Progress Bars We can only use the regular TQDM as if we were in a terminal because the notebook version requires IPy widgets that I’m not going to implement
``` python from tqdm import tqdm import time for i in tqdm(range(1000)): time.sleep(0.01) # Simulate some work being done ``` 100%|##########| 1000/1000 [00:13<00:00, 72.47it/s]
Notice how the notebook version isn’t going to increment. So be aware.
``` python from tqdm.notebook import tqdm import time for i in tqdm(range(1000)): time.sleep(0.01) # Simulate some work being done ``` 0%| | 0/1000 [00:00 …See it just sits there and does nothing. So *don’t try to use the notebook version.* Good news is, if you just use the auto version of TQDM, you get the regular text version: ``` python from tqdm.auto import tqdm import time for i in tqdm(range(1000)): time.sleep(0.01) # Simulate some work being done ``` 100%|##########| 1000/1000 [00:12<00:00, 82.16it/s]
Which variety of which LLM are you? ##### 🤖Reply🤖
Reply details
  • Model: qwen2.5-coder:latest
  • Finish reason: stop
  • Tokens: 1866 prompt + 63 completion = 1929 total
I am Qwen, a large language model created by Alibaba Cloud. My base architecture is based on transformer models and I have been trained on a diverse dataset to understand and generate human-like text on a wide range of topics. If you have any questions or need assistance with anything specific, feel free to ask!
I’m wondering if you could give me a little code that would generate like a 3D scatter plot in Plotly that I can test here in this Boopiter notebook. I suppose I’ll have to render it via the IPython display HTML element, so give me your best guess at what that needs to look like. And please conform to my coding style of keeping everything as vertically compact as possible so that I don’t have to scroll up and down much to see the full code ##### 🤖Reply🤖
Reply details
  • Model: Claude Opus 4.8 (dead drop)
Compact as requested. One change with a purpose, though: I wrapped it in an `'}, raw=True)')) ``` Why the iframe: raw Plotly HTML *leads with* `
" width="100%" height="500" style="border:none">
^^Go ahead! Manipulate that plot with your mouse. Press & drag, zoom in, etc.