EVENTPLOT
Excel Usage
=EVENTPLOT(data, title, xlabel, ylabel, stat_color, event_orientation, legend)
data(list[list], required): Input 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.stat_color(str, optional, default: null): Event color.event_orientation(str, optional, default: “horizontal”): Orientation (‘horizontal’ or ‘vertical’).legend(str, optional, default: “false”): Show legend.
Returns (object): Matplotlib Figure object (standard Python) or base64 encoded PNG string (Pyodide).
Examples
Example 1: Event plot with single sequence
Inputs:
| data |
|---|
| 1 |
| 2 |
| 3 |
| 4 |
| 5 |
Excel formula:
=EVENTPLOT({1;2;3;4;5})
Expected output:
"chart"
Example 2: Event plot with multiple sequences
Inputs:
| data | ||
|---|---|---|
| 1 | 1.5 | 2 |
| 2 | 2.5 | 3 |
| 3 | 3.5 | 4 |
| 4 | 4.5 | 5 |
Excel formula:
=EVENTPLOT({1,1.5,2;2,2.5,3;3,3.5,4;4,4.5,5})
Expected output:
"chart"
Example 3: Vertical event plot with labels
Inputs:
| data | event_orientation | title | xlabel | ylabel |
|---|---|---|---|---|
| 1 | vertical | Test Event Plot | Time | Events |
| 2 | ||||
| 3 | ||||
| 4 | ||||
| 5 |
Excel formula:
=EVENTPLOT({1;2;3;4;5}, "vertical", "Test Event Plot", "Time", "Events")
Expected output:
"chart"
Example 4: Event plot with custom color
Inputs:
| data | stat_color | |
|---|---|---|
| 1 | 1.5 | red |
| 2 | 2.5 | |
| 3 | 3.5 |
Excel formula:
=EVENTPLOT({1,1.5;2,2.5;3,3.5}, "red")
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 eventplot(data, title=None, xlabel=None, ylabel=None, stat_color=None, event_orientation='horizontal', legend='false'):
"""
Create a spike raster or event plot from data.
See: https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.eventplot.html
This example function is provided as-is without any representation of accuracy.
Args:
data (list[list]): Input 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.
stat_color (str, optional): Event color. Valid options: Blue, Green, Red, Cyan, Magenta, Yellow, Black, White. Default is None.
event_orientation (str, optional): Orientation ('horizontal' or 'vertical'). Valid options: Horizontal, Vertical. Default is 'horizontal'.
legend (str, optional): Show legend. Valid options: True, False. Default is 'false'.
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
def str_to_bool(s):
return s.lower() == "true" if isinstance(s, str) else bool(s)
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 numeric columns
cols = []
max_rows = max(len(row) for row in data) if data else 0
for col_idx in range(max_rows):
col_data = []
for row in data:
if col_idx < len(row):
val = row[col_idx]
try:
col_data.append(float(val))
except (TypeError, ValueError):
continue
if col_data:
cols.append(col_data)
if not cols:
return "Error: No valid numeric data found"
# Create plot
fig, ax = plt.subplots(figsize=(8, 6))
# Plot eventplot
color = stat_color if stat_color else None
colors = [color] * len(cols) if color else None
# Map orientation values
orient_map = {'horizontal': 'horizontal', 'vertical': 'vertical'}
plot_orientation = orient_map.get(event_orientation, 'horizontal')
ax.eventplot(cols, orientation=plot_orientation, colors=colors,
lineoffsets=np.arange(1, len(cols) + 1),
linelengths=0.5)
if title:
ax.set_title(title)
if xlabel:
ax.set_xlabel(xlabel)
if ylabel:
ax.set_ylabel(ylabel)
if str_to_bool(legend) and len(cols) > 1:
ax.legend([f'Sequence {i+1}' for i in range(len(cols))])
plt.tight_layout()
# Return based on platform
if IS_PYODIDE:
buf = io.BytesIO()
plt.savefig(buf, format='png', dpi=100, bbox_inches='tight')
buf.seek(0)
img_base64 = base64.b64encode(buf.read()).decode('utf-8')
plt.close(fig)
return f"data:image/png;base64,{img_base64}"
else:
return fig
except Exception as e:
return f"Error: {str(e)}"