Jupyter Notebook Context

The Jupyter notebook context handles interactive code execution and display. It’s particularly useful for teaching programming concepts and creating interactive demonstrations.

Key Macros

Code Execution

\setupcode{block}
    Initializes the environment with imports and setup code
    Args:
        block: Setup code to run first

\code{block}
    Creates a code cell
    Args:
        block: Code to execute

\pythonblockstart
\pythonblockend
    Delimits a Python code block

Code Loading

\loadcode{object}{module}
    Imports specific objects from modules
    Args:
        object: Name of object to load
        module: Module to load from

\loadplotcode{object}{filename}
    Loads plotting code from file
    Args:
        object: Name of plotting function
        filename: Source file

Display Control

\displaycode{block}
    Shows code without executing
    Args:
        block: Code to display

\plotcode{block}
    Executes plotting code
    Args:
        block: Code that generates plots

Extended Code Controls

\setuphelpercode{block}
    Sets up helper code that runs first
    Args:
        block: Setup code

\loadhelpercode{block}
    Loads helper code from file
    Args:
        block: File to load

\helpercode{block}
    Defines helper code
    Args:
        block: Helper code definition

\setupdisplaycode{block}
    Sets up display code
    Args:
        block: Display setup code

\loaddisplaycode{block}
    Loads display code
    Args:
        block: Code to load

\displaycode{block}
    Defines display code
    Args:
        block: Code to display

\setupplotcode{block}
    Sets up plotting code
    Args:
        block: Plot setup code

\loadplotcode{object}{filename}
    Loads plotting code
    Args:
        object: Object to load
        filename: Source file

\plotcode{block}
    Defines plotting code
    Args:
        block: Plot generation code

\setuptestcode{block}
    Sets up test code that runs first
    Args:
        block: Setup code

\loadtestcode{object}{filename}
    Loads test code from file
    Args:
        object: Object to load
        filename: Source file

\testcode{block}
    Defines test code for execution/testing
    Args:
        block: Test code to execute

\matlabcode{block}
    Defines MATLAB code
    Args:
        block: MATLAB code

Example usage:

\setuphelpercode{
import numpy as np
import matplotlib.pyplot as plt
}

\helpercode{
def process_data(data):
    return np.mean(data, axis=0)
}

\plotcode{
x = np.linspace(0, 10, 100)
plt.plot(x, np.sin(x))
}

\testcode{
# Test the data processing function
test_data = np.random.randn(100, 3)
result = process_data(test_data)
assert result.shape == (3,)
print("Test passed!")
}

Example Usage

\ifndef{gaussianPlot}
\define{gaussianPlot}

\setuphelpercode{
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
}

\helpercode{
def plot_gaussian(mu=0, sigma=1):
    x = np.linspace(mu - 4*sigma, mu + 4*sigma, 100)
    y = 1/(sigma * np.sqrt(2*np.pi)) * np.exp(-(x-mu)**2/(2*sigma**2))
    plt.plot(x, y)
    plt.title(f'Gaussian (μ={mu}, σ={sigma})')
}

\plotcode{
plot_gaussian()
}

\endif

Output Formats

• Jupyter notebooks (.ipynb)

• Google Colab notebooks

• Interactive HTML

Best Practices

1. Always include necessary imports in \setupcode

2. Use meaningful variable names

3. Add comments for complex operations

4. Consider notebook execution order

5. Handle dependencies explicitly

6. Use \testcode for code that should be executed during testing

7. Use --code test to include all code blocks for extraction and execution