STREAMPLOT

Excel Usage

=STREAMPLOT(data, title, xlabel, ylabel, color_map, density)

• data (list[list], required): Input data (X, Y, U, V).
• title (str, optional, default: null): Chart title.
• xlabel (str, optional, default: null): Label for X-axis.
• ylabel (str, optional, default: null): Label for Y-axis.
• color_map (str, optional, default: “viridis”): Color map for streamlines.
• density (float, optional, default: 1): Density of streamlines.

Returns (object): Matplotlib Figure object (standard Python) or base64 encoded PNG string (Pyodide).

Examples

Example 1: Basic streamplot

Inputs:

data
0	0	1	0
1	0	1	0
0	1	1	1
1	1	1	1

Excel formula:

=STREAMPLOT({0,0,1,0;1,0,1,0;0,1,1,1;1,1,1,1})

Expected output:

"chart"

Example 2: Streamplot with plasma colormap

Inputs:

data				color_map
0	0	1	0	plasma
1	0	0	1
2	0	-1	0
0	1	1	1
1	1	0	0
2	1	-1	1

Excel formula:

=STREAMPLOT({0,0,1,0;1,0,0,1;2,0,-1,0;0,1,1,1;1,1,0,0;2,1,-1,1}, "plasma")

Expected output:

"chart"

Example 3: Streamplot with labels and title

Inputs:

data				title	xlabel	ylabel
0	0	1	1	Flow Field	X	Y
1	0	-1	1
0	1	1	-1
1	1	-1	-1

Excel formula:

=STREAMPLOT({0,0,1,1;1,0,-1,1;0,1,1,-1;1,1,-1,-1}, "Flow Field", "X", "Y")

Expected output:

"chart"

Example 4: Streamplot with higher density

Inputs:

data				density
0	0	1	0	2
1	0	0	1
0	1	-1	0
1	1	0	-1

Excel formula:

=STREAMPLOT({0,0,1,0;1,0,0,1;0,1,-1,0;1,1,0,-1}, 2)

Expected output:

"chart"

Python Code

import sys
import matplotlib
IS_PYODIDE = sys.platform == "emscripten"
if IS_PYODIDE:
    matplotlib.use('Agg')
import matplotlib.pyplot as plt
import io
import base64
import numpy as np

def streamplot(data, title=None, xlabel=None, ylabel=None, color_map='viridis', density=1):
    """
    Create a streamplot (vector field streamlines).

    See: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.streamplot.html

    This example function is provided as-is without any representation of accuracy.

    Args:
        data (list[list]): Input data (X, Y, U, V).
        title (str, optional): Chart title. Default is None.
        xlabel (str, optional): Label for X-axis. Default is None.
        ylabel (str, optional): Label for Y-axis. Default is None.
        color_map (str, optional): Color map for streamlines. Valid options: Viridis, Plasma, Inferno, Magma, Cividis. Default is 'viridis'.
        density (float, optional): Density of streamlines. Default is 1.

    Returns:
        object: Matplotlib Figure object (standard Python) or base64 encoded PNG string (Pyodide).
    """
    def to2d(x):
        return [[x]] if not isinstance(x, list) else x

    try:
        data = to2d(data)

        if not isinstance(data, list) or not all(isinstance(row, list) for row in data):
            return "Error: Invalid input - data must be a 2D list"

        # Extract X, Y, U, V columns
        if len(data) < 1 or len(data[0]) < 4:
            return "Error: Data must have at least 4 columns (X, Y, U, V)"

        X = []
        Y = []
        U = []
        V = []
        for row in data:
            if len(row) >= 4:
                try:
                    X.append(float(row[0]))
                    Y.append(float(row[1]))
                    U.append(float(row[2]))
                    V.append(float(row[3]))
                except (TypeError, ValueError):
                    continue

        if len(X) == 0:
            return "Error: No valid numeric data found"

        # Convert to unique grid points
        X_unique = sorted(list(set(X)))
        Y_unique = sorted(list(set(Y)))

        if len(X_unique) < 2 or len(Y_unique) < 2:
            return "Error: Need at least 2 unique X and Y values for streamplot"

        # Create meshgrid
        X_grid, Y_grid = np.meshgrid(X_unique, Y_unique)

        # Interpolate U and V onto grid
        U_grid = np.zeros_like(X_grid)
        V_grid = np.zeros_like(Y_grid)

        for i in range(len(X)):
            xi = X_unique.index(X[i])
            yi = Y_unique.index(Y[i])
            U_grid[yi, xi] = U[i]
            V_grid[yi, xi] = V[i]

        # Create streamplot
        fig, ax = plt.subplots(figsize=(8, 6))

        strm = ax.streamplot(X_grid, Y_grid, U_grid, V_grid, color=np.sqrt(U_grid**2 + V_grid**2), 
                             cmap=color_map, density=density)

        if title:
            ax.set_title(title)
        if xlabel:
            ax.set_xlabel(xlabel)
        if ylabel:
            ax.set_ylabel(ylabel)

        if IS_PYODIDE:
            buf = io.BytesIO()
            plt.savefig(buf, format='png', bbox_inches='tight')
            plt.close(fig)
            buf.seek(0)
            img_base64 = base64.b64encode(buf.read()).decode('utf-8')
            return f"data:image/png;base64,{img_base64}"
        else:
            return fig
    except Exception as e:
        return f"Error: {str(e)}"

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