This is development documentation. Some features are not available in the stable release. View stable documentation.

Advanced Matplotlib Integration

SpectroChemPy plots return Matplotlib Axes objects, giving you full access to Matplotlib’s capabilities.

Modifying the Axes

After plotting, customize using Matplotlib methods:

import spectrochempy as scp

ds = scp.read("irdata/nh4y-activation.spg")
ds1 = ds[0]

ax = ds1.plot()
_ = ax.set_title(r"NH$_4$Y Activation - $\nu_{NH}$ Region")
_ = ax.set_xlabel(r"Wavenumber (cm$^{-1}$)")
_ = ax.set_ylabel("Absorbance (a.u.)")
_ = ax.set_xlim(3500, 2800)
_ = ax.annotate(
    "NH stretch",
    xy=(3250, 0.6),
    xytext=(3400, 0.7),
    arrowprops={"arrowstyle": "->", "color": "gray"},
)

Multiple Plots

Create separate plots with different settings:

import matplotlib.pyplot as plt

fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 3))

# Plot 1: full spectrum
_ = ds.plot(ax=ax1)
ax1.set_title("Full Spectrum")

# Plot 2: subset
_ = ds[:, 1800.0:1500.0].plot(ax=ax2)
ax2.set_title("Water bending Region")

plt.tight_layout()

Colormap Normalization

Advanced colormap normalization for special data scenarios:

import matplotlib as mpl

# CenteredNorm - centers the colormap around a specific value
norm = mpl.colors.CenteredNorm(vcenter=1.0)
_ = ds.plot_image(cmap="RdBu_r", norm=norm, colorbar=True)

LaTeX-like Math in Labels

SpectroChemPy supports LaTeX math notation in labels:

ax = ds1.plot()
_ = ax.set_xlabel(r"$ \tilde{\nu}$ (cm$^{-1}$)")
_ = ax.set_ylabel(r"$ \epsilon$ (mol$^{-1}$·L·cm$^{-1}$)")
_ = ax.set_title(r"Beer-Lambert: $A = \epsilon c l$")

Reproducibility

Avoid modifying global Matplotlib state. Instead:

• Use kwargs for per-plot settings

• Use preferences for session defaults

• Use styles for theme changes

Example of clean, reproducible plotting:

def plot_spectrum(dataset, title=None, output_path=None):
    """Plot a spectrum with consistent styling."""
    ax = dataset.plot(
        linewidth=1.5,
        color="navy",
        grid=True,
    )
    if title:
        ax.set_title(title)
    ax.set_xlabel(r"Wavenumber (cm$^{-1}$)")
    ax.set_ylabel("Absorbance")
    return ax


# Each call produces consistent results
ax1 = plot_spectrum(ds1, title="Sample 1")
ax2 = plot_spectrum(ds1 * 1.5, title="Sample 2 (amplified)")

Where to Go Further

SpectroChemPy is built on Matplotlib. For advanced customization:

• Matplotlib Axes documentation

• Matplotlib customization guide

• SpectroChemPy API reference for plot method options

The combination of SpectroChemPy’s convenience with Matplotlib’s power gives you full control over your visualizations.