CONTOUR_FILLED

Excel Usage

=CONTOUR_FILLED(data, title, xlabel, ylabel, color_map, levels, colorbar)
  • data (list[list], required): Input Z-data.
  • 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 contours.
  • levels (int, optional, default: 10): Number of contour levels.
  • colorbar (str, optional, default: “true”): Show colorbar.

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

Examples

Example 1: Basic filled contour plot

Inputs:

data
1 2 3 4
2 4 6 8
3 6 9 12
4 8 12 16

Excel formula:

=CONTOUR_FILLED({1,2,3,4;2,4,6,8;3,6,9,12;4,8,12,16})

Expected output:

"chart"

Example 2: Filled contour with inferno colormap

Inputs:

data color_map
0 1 2 inferno
1 2 3
2 3 4

Excel formula:

=CONTOUR_FILLED({0,1,2;1,2,3;2,3,4}, "inferno")

Expected output:

"chart"

Example 3: Filled contour with labels and title

Inputs:

data title xlabel ylabel
1 2 3 Filled Contour X-axis Y-axis
2 4 6
3 6 9

Excel formula:

=CONTOUR_FILLED({1,2,3;2,4,6;3,6,9}, "Filled Contour", "X-axis", "Y-axis")

Expected output:

"chart"

Example 4: Filled contour without colorbar

Inputs:

data colorbar
1 2 3 4 5 false
2 3 4 5 6
3 4 5 6 7

Excel formula:

=CONTOUR_FILLED({1,2,3,4,5;2,3,4,5,6;3,4,5,6,7}, "false")

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 contour_filled(data, title=None, xlabel=None, ylabel=None, color_map='viridis', levels=10, colorbar='true'):
    """
    Create a filled contour plot.

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

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

    Args:
        data (list[list]): Input Z-data.
        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 contours. Valid options: Viridis, Plasma, Inferno, Magma, Cividis. Default is 'viridis'.
        levels (int, optional): Number of contour levels. Default is 10.
        colorbar (str, optional): Show colorbar. Valid options: True, False. Default is 'true'.

    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"

        # Convert to numpy array
        Z = []
        for row in data:
            z_row = []
            for val in row:
                try:
                    z_row.append(float(val))
                except (TypeError, ValueError):
                    z_row.append(0)
            Z.append(z_row)

        Z = np.array(Z)

        if Z.size == 0:
            return "Error: No valid data found"

        # Create X and Y coordinates
        rows, cols = Z.shape
        X = np.arange(cols)
        Y = np.arange(rows)
        X, Y = np.meshgrid(X, Y)

        # Create filled contour plot
        fig, ax = plt.subplots(figsize=(8, 6))

        CS = ax.contourf(X, Y, Z, levels=levels, cmap=color_map)

        if colorbar == "true":
            plt.colorbar(CS, ax=ax)

        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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