The same plot in 14 other libraries — Python: Altair, Bokeh, lets-plot, Plotly, plotnine, Pygal, Seaborn; R: ggplot2; Julia: Makie.jl; JavaScript: Chart.js, D3.js, Apache ECharts, Highcharts, MUI X Charts. Compare all 15 side by side: NMR Spectrum (Nuclear Magnetic Resonance) in Python, R, Julia and JavaScript.
An NMR spectrum plots signal intensity versus chemical shift (in ppm) to reveal the electronic environment of atomic nuclei in a molecule. It is the primary analytical tool in organic chemistry for determining molecular structure, with peak positions indicating functional groups and splitting patterns (multiplets) revealing connectivity between neighboring atoms. The x-axis is conventionally reversed (high ppm on the left) and peaks appear as sharp signals rising from a baseline.
""" anyplot.ai
spectrum-nmr: NMR Spectrum (Nuclear Magnetic Resonance)
Library: matplotlib 3.10.9 | Python 3.13.13
Quality: 91/100 | Updated: 2026-06-03
"""
import os
import matplotlib.patheffects as pe
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
import numpy as np
# Theme-adaptive chrome (Imprint palette)
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
# Imprint palette — first categorical series always brand green
BRAND = "#009E73"
# Data: synthetic 1H NMR spectrum of ethanol (CH3CH2OH)
np.random.seed(42)
ppm = np.linspace(-0.5, 5.0, 6000)
spectrum = np.zeros_like(ppm)
w = 0.025 # Lorentzian half-width
j = 0.078 # J-coupling constant — wider than minimal so multiplet splitting is visually striking
# Lorentzian peaks: A / (1 + ((x - x0) / w)^2)
# TMS reference singlet at 0.00 ppm
spectrum += 0.30 / (1 + ((ppm - 0.00) / 0.015) ** 2)
# CH3 triplet ~1.18 ppm (1 : 2 : 1 ratio)
spectrum += 0.50 / (1 + ((ppm - (1.18 - j)) / w) ** 2)
spectrum += 1.00 / (1 + ((ppm - 1.18) / w) ** 2)
spectrum += 0.50 / (1 + ((ppm - (1.18 + j)) / w) ** 2)
# CH2 quartet ~3.69 ppm (1 : 3 : 3 : 1 ratio)
spectrum += 0.25 / (1 + ((ppm - (3.69 - 1.5 * j)) / w) ** 2)
spectrum += 0.75 / (1 + ((ppm - (3.69 - 0.5 * j)) / w) ** 2)
spectrum += 0.75 / (1 + ((ppm - (3.69 + 0.5 * j)) / w) ** 2)
spectrum += 0.25 / (1 + ((ppm - (3.69 + 1.5 * j)) / w) ** 2)
# OH singlet ~2.61 ppm
spectrum += 0.40 / (1 + ((ppm - 2.61) / w) ** 2)
# Subtle baseline noise
spectrum += np.random.normal(0, 0.003, len(ppm))
spectrum = np.clip(spectrum, 0, None)
# Canvas — landscape 3200 × 1800 px (16:9)
fig, ax = plt.subplots(figsize=(8, 4.5), dpi=400, facecolor=PAGE_BG)
ax.set_facecolor(PAGE_BG)
# Spectrum trace + area fill
ax.plot(ppm, spectrum, linewidth=2.5, color=BRAND, zorder=3)
ax.fill_between(ppm, spectrum, alpha=0.12, color=BRAND, zorder=2)
# Subtle peak-region highlight bands
for lo, hi in [(-0.15, 0.15), (1.00, 1.42), (2.45, 2.75), (3.50, 3.92)]:
ax.axvspan(lo, hi, alpha=0.06, color=BRAND, zorder=1)
# Peak annotations with theme-matched path-effect outline
text_outline = [pe.withStroke(linewidth=3, foreground=ELEVATED_BG)]
annotations = [
(0.00, "TMS\n0.00 ppm", (42, 28)),
(1.18, "CH₃ (triplet)\n1.18 ppm", (82, -48)),
(2.61, "OH (singlet)\n2.61 ppm", (-55, 34)),
(3.69, "CH₂ (quartet)\n3.69 ppm", (-60, 38)),
]
for peak_ppm, label, offset in annotations:
peak_idx = np.argmin(np.abs(ppm - peak_ppm))
ax.annotate(
label,
xy=(peak_ppm, spectrum[peak_idx]),
xytext=offset,
textcoords="offset points",
fontsize=9,
fontweight="semibold",
ha="center",
va="bottom",
arrowprops={"arrowstyle": "-|>", "color": INK_MUTED, "lw": 1.5, "mutation_scale": 12},
color=INK,
path_effects=text_outline,
zorder=5,
)
# Integration bars — prominent thick lines below baseline
bar_y = -0.07
for center, ratio, rlabel in [(1.18, 3, "3H"), (2.61, 1, "1H"), (3.69, 2, "2H")]:
hw = 0.28 * ratio / 3
ax.plot(
[center - hw, center + hw],
[bar_y, bar_y],
linewidth=7,
color=BRAND,
alpha=0.75,
solid_capstyle="round",
zorder=4,
)
ax.text(
center,
bar_y - 0.028,
rlabel,
ha="center",
va="top",
fontsize=8,
color=BRAND,
fontweight="bold",
path_effects=text_outline,
)
# Minor x-axis ticks at 0.2 ppm intervals (standard NMR scale)
ax.xaxis.set_major_locator(mticker.MultipleLocator(1.0))
ax.xaxis.set_minor_locator(mticker.MultipleLocator(0.2))
ax.tick_params(axis="x", which="minor", length=3, width=0.8, color=INK_SOFT)
ax.tick_params(axis="x", which="major", length=6, width=1.2)
ax.tick_params(axis="both", labelsize=8, colors=INK_SOFT, labelcolor=INK_SOFT)
# Title — length-aware fontsize scaling
title = "Ethanol ¹H NMR · spectrum-nmr · matplotlib · anyplot.ai"
title_fs = max(8, round(12 * 67 / len(title))) if len(title) > 67 else 12
ax.set_title(title, fontsize=title_fs, fontweight="medium", pad=14, color=INK)
ax.set_xlabel("Chemical Shift (ppm)", fontsize=10, labelpad=10, color=INK)
ax.set_ylabel("Intensity", fontsize=10, color=INK)
# NMR conventions: reversed x-axis, no y-ticks
ax.set_xlim(5.0, -0.5)
ax.set_ylim(-0.12, 1.30)
ax.set_yticks([])
# Spine styling — remove top, right, left (NMR convention); keep bottom
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.spines["left"].set_visible(False)
ax.spines["bottom"].set_color(INK_SOFT)
# Molecule formula watermark
ax.text(
0.98,
0.95,
"CH₃CH₂OH",
transform=ax.transAxes,
fontsize=11,
fontweight="bold",
ha="right",
va="top",
color=BRAND,
alpha=0.30,
fontstyle="italic",
)
fig.subplots_adjust(left=0.06, right=0.97, top=0.91, bottom=0.15)
plt.savefig(f"plot-{THEME}.png", dpi=400, facecolor=PAGE_BG)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/spectrum-nmr/matplotlib/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.
{
"spec_id": "spectrum-nmr",
"language": "python",
"library": "matplotlib",
"page": "https://anyplot.ai/spectrum-nmr/python/matplotlib",
"hub": "https://anyplot.ai/spectrum-nmr",
"code_json": "https://api.anyplot.ai/specs/spectrum-nmr/matplotlib/code",
"spec_json": "https://api.anyplot.ai/specs/spectrum-nmr",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/spectrum-nmr/python/matplotlib/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/spectrum-nmr/python/matplotlib/plot-dark.png",
"quality_score": 91.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of NMR Spectrum (Nuclear Magnetic Resonance) on anyplot.ai.