plot

eempy.plot.plot

Functions for plotting EEM-related data Author: Yongmin Hu (yongminhu@outlook.com) Last update: 2026-01

plot_abs

plot_abs(absorbance, ex_range, xmax=0.1, ex_range_display=(200, 800), plot_tool='matplotlib', display=True, figure_size=(6.5, 2))

Plot the UV absorbance data

Parameters:

Name	Type	Description	Default
absorbance	np.ndarray	The absorbance spectrum (1D array).	required
ex_range	np.ndarray	The excitation wavelengths (1D array).	required
xmax	float (0~1)	The maximum absorbance displayed.	0.1
ex_range_display	tuple with two elements	The range of excitation wavelengths displayed.	(200, 800)
plot_tool	str, {'matplotlib', 'plotly'}	Which python package to use for plotting.	'matplotlib'
display	bool	Whether to display the figure when calling the function.	True
figure_size	tuple (width, height)	The size of the plot.	(6.5, 2)

Returns:

Name	Type	Description
fig	Figure
ax	Axes	Axes object when plot_tool="matplotlib".

plot_dendrogram

plot_dendrogram(linkage_matrix, threshold, index: Optional[list] = None)

Plot a dendrogram from a linkage matrix.

Parameters:

Name	Type	Description	Default
linkage_matrix	np.ndarray	Linkage matrix from hierarchical clustering.	required
threshold	float	Distance threshold for coloring clusters.	required
index	list or None	Optional labels for samples.	None

Returns:

Name	Type	Description
fig	Figure

plot_eem

plot_eem(intensity: ndarray, ex_range, em_range, auto_intensity_range=True, scale_type='linear', vmin=0, vmax=10000, n_cbar_ticks=5, cbar=True, cmap='jet', figure_size=(10, 7), axis_label_font_size=18, axis_ticks_font_size=16, cbar_label='Intensity (a.u.)', cbar_font_size=16, cbar_fraction=0.02, fix_aspect_ratio=True, rotate=False, plot_tool='matplotlib', display=True, title=None, title_font_size=20)

Plot EEM or EEM-like data.

Parameters:

Name	Type	Description	Default
intensity	np.ndarray	The EEM.	required
ex_range	np.ndarray	The excitation wavelengths.	required
em_range	np.ndarray	The emission wavelengths.	required
auto_intensity_range	bool	Whether to use the colorbar range generated automatically by matplotlib for plotting fluorescence intensity.	True
scale_type	str, {'linear', 'log'}	The type of colorbar scale used for plotting fluorescence intensity.	'linear'
vmin	int or float	The minimum intensity displayed, if you wish to adjust the intensity scale yourself (autoscale=False).	0
vmax	int or float	The maximum intensity displayed, if you wish to adjust the intensity scale yourself (autoscale=False).	10000
n_cbar_ticks	int	The number of ticks in colorbar.	5
cmap	str	The colormap, see https://matplotlib.org/stable/users/explain/colors/colormaps.html.	'jet'
figure_size	tuple or list with two elements	The figure size.	(10, 7)
axis_label_font_size	int	The fontsize of the x and y axes labels.	18
axis_ticks_font_size	int	The fontsize of the x and y ticks labels.	16
cbar	bool	Whether to plot the colorscale bar.	True
cbar_label	str	The label of the colorbar scale.	'Intensity (a.u.)'
cbar_font_size	int	The label size of the colorbar scale.	16
cbar_fraction	float	The size fraction of the colorbar scale.	0.02
fix_aspect_ratio	bool	Whether to fix the aspect ratio to be one.	True
rotate	bool	Whether to rotate the EEM, so that the x-axis is excitation and y-axis is emission.	False
plot_tool	str, {'matplotlib', 'plotly'}	Which python package to use for plotting.	'matplotlib'
display	bool	Whether to display the figure when calling the function	True
title	str	Plot title.	None
title_font_size	int	Font size for the plot title.	20

Returns:

Name	Type	Description
fig	Figure
ax	Axes	Axes object when plot_tool="matplotlib".
im	AxesImage	Image handle when plot_tool="matplotlib".

plot_eem_stack

plot_eem_stack(eem_stack: ndarray, ex_range: ndarray, em_range: ndarray, titles: Optional[list] = None, n_cols: int = 2, auto_intensity_range: bool = True, scale_type: str = 'linear', vmin: Optional[float] = None, vmax: Optional[float] = None, cmap: str = 'jet', figure_size: tuple = (12, 12), axis_label_font_size: int = 12, axis_ticks_font_size: int = 10, cbar: bool = True, cbar_fraction: float = 0.02, fix_aspect_ratio: bool = True, rotate: bool = False, suptitle: Optional[str] = None, suptitle_font_size: int = 16, plot_x_axis_label: bool = True, plot_y_axis_label: bool = True) -> tuple

Plot a stack of EEMs in a grid of subplots.

Parameters:

Name	Type	Description	Default
eem_stack	np.ndarray	Stack of EEMs, shape (n_samples, n_ex, n_em).	required
ex_range	np.ndarray	Excitation wavelengths (1D array).	required
em_range	np.ndarray	Emission wavelengths (1D array).	required
titles	list of str	List of subplot titles, length must equal number of EEMs.	None
n_cols	int	Number of columns in the subplot grid.	2
auto_intensity_range	bool	If True, use matplotlib's autoscale for intensities.	True
scale_type	str	'linear' or 'log' scale for color mapping.	'linear'
vmin	float	Minimum intensity if auto_intensity_range is False.	None
vmax	float	Maximum intensity if auto_intensity_range is False.	None
cmap	str	Matplotlib colormap.	'jet'
figure_size	tuple	Size of the entire figure.	(12, 12)
axis_label_font_size	int	Font size for axis labels.	12
axis_ticks_font_size	int	Font size for axis ticks.	10
cbar	bool	Whether to show a colorbar for each subplot.	True
cbar_fraction	float	Fraction size of colorbar.	0.02
fix_aspect_ratio	bool	If True, force aspect ratio to 1.	True
rotate	bool	If True, swap axes so x=excitation and y=emission.	False
suptitle	str	Overall figure title.	None
suptitle_font_size	int	Font size for overall title.	16
plot_x_axis_label	bool	Whether to show the x-axis label on each subplot.	True
plot_y_axis_label	bool	Whether to show the y-axis label on each subplot.	True

Returns:

Name	Type	Description
fig	Figure
axes	np.ndarray of Axes
ims	list of AxesImage

plot_error

plot_error(error, bins='auto', display=True)

Plot a histogram of error values with sample indices on hover.

Parameters:

Name	Type	Description	Default
error	pd.DataFrame	Error table with a single column.	required
bins	int, str, or sequence	Bin specification passed to NumPy histogram.	'auto'
display	bool	Whether to display the figure when calling the function.	True

Returns:

Name	Type	Description
fig	Figure

plot_fi

plot_fi(fi: DataFrame, q: float = 0.05)

Plot the fluorescence intensities of samples at a specific pair of ex/em.

Parameters:

Name	Type	Description	Default
fi	pd.DataFrame	A DataFrame of shape (n,1), where n is the number of samples. The output of EEMDataset.peak_picking() can be passed to this parameter.	required
q	float	Where to plot the reference lines. By default, this is set to be 0.05 - two horizontal lines will be plotted at 95% and 105% of the average fluorescence intensity.	0.05

Returns:

Name	Type	Description
fig	Figure
ax	Axes

plot_fi_correlation

plot_fi_correlation(fi: DataFrame, ref)

Plot fluorescence intensity versus the reference value.

Parameters:

Name	Type	Description	Default
fi	pd.DataFrame	A DataFrame of shape (n,1), where n is the number of samples. The output of EEMDataset.peak_picking() can be passed to this parameter.	required
ref	np.ndarray	The reference values. It should be a 1D numpy array of shape (n,), where n is the number of samples.	required

Returns:

Name	Type	Description
fig	Figure
ax	Axes

plot_fmax

plot_fmax(table, component_labels=None, display=True, yaxis_title='Fmax', labels=None)

Plot Fmax (or similar score) tables.

Parameters:

Name	Type	Description	Default
table	pd.DataFrame	Table of component scores (samples x components).	required
component_labels	list or None	Optional labels for components shown in the legend.	None
display	bool	Whether to display the figure when calling the function.	True
yaxis_title	str	Y-axis title for the score axis.	'Fmax'
labels	array-like or None	Optional cluster labels used to overlay cluster-colored markers.	None

Returns:

Name	Type	Description
fig	Figure

plot_loadings

plot_loadings(parafac_models_dict: dict, colors=list(TABLEAU_COLORS.values()), component_labels_dict=None, n_cols=None, plot_tool='matplotlib', display=True, legend_pad=0)

Plot the excitation and emission loadings for PARAFAC models.

Parameters:

Name	Type	Description	Default
parafac_models_dict	dict	A dictionary of PARAFAC objects. Each PARAFAC model is labelled with a dictionary key.	required
colors	list	A list of matplotlib-compatible colors used for plotting.	list(values())
component_labels_dict	dict or None	A dictionary of component names for each PARAFAC model. The keys of the dict should be identical to those of the parafac_models_dict. The value of each key is a list of component names.	None
n_cols	int or None	Maximum number of subplots at each row. if None, subplots will be shown in-line.	None
plot_tool	(str, {matplotlib, plotly})	Which python package to use for plotting.	'matplotlib'
display	bool	Whether to display the figure when calling the function.	True
legend_pad	float	Extra padding below the legend in the plotly layout.	0

Returns:

Name	Type	Description
fig	Figure
ax	Axes	Axes object when plot_tool="matplotlib".

plot_reconstruction_error

plot_reconstruction_error(table, bar_col_name, display=True, yaxis_scatter_title='Reconstruction error', yaxis_bar_title='Reconstruction error reduction', labels=None)

Plot reconstruction errors and per-sample error reductions.

Parameters:

Name	Type	Description	Default
table	pd.DataFrame	Table containing error series. One column is used as bars (bar_col_name), the rest are plotted as lines.	required
bar_col_name	str	Column name used for the bar series.	required
display	bool	Whether to display the figure when calling the function.	True
yaxis_scatter_title	str	Y-axis title for the line series.	'Reconstruction error'
yaxis_bar_title	str	Y-axis title for the bar series.	'Reconstruction error reduction'
labels	array-like or None	Optional cluster labels used to overlay cluster-colored markers and bars.	None

Returns:

Name	Type	Description
fig	Figure