Show HN: Ultraplot – A succint wrapper for matplotlib
1–10 of 15 posts
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#2For those unfamiliar, ProPlot was widely loved for enabling publication-quality graphics with minimal effort. UltraPlot continues that mission with active development, updated compatibility, and a focus on simplicity.
Why UltraPlot?
Key improvements over vanilla matplotlib:
- Effortless subplot management: build complex multi-panel layouts in one line
- GeoAxes support included out of the box
- Smarter aesthetics: beautiful colormaps, fonts, and styles without extra code
- Intuitive syntax: less boilerplate, more plotting
- Seamless compatibility: everything you know from matplotlib still applies
``` import ultraplot as uplt
layout = [[0, 1, 2], [3, 3, 4]]
fig, axs = uplt.subplots(layout)
axs[0].plot(x, y1, label="Data 1")
axs[1].plot(x, y2, label="Data 2")
axs.format(xlabel="Hello", ylabel="Hacker news", abc="[A]") # format applies to all axes fig.legend()
```
...and get a clean, professional-looking plot in seconds.
Get Started:
- GitHub: https://github.com/Ultraplot/ultraplot
- Docs: https://ultraplot.readthedocs.io/en/latest/
Try it out and let us know what you think — contributions and feedback are very welcome!
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#3For those unfamiliar, ProPlot was widely loved for enabling publication-quality graphics with minimal effort. UltraPlot continues that mission with active development, updated compatibility, and a focus on simplicity. Why UltraPlot? Key improvements over vanilla matplotlib: - Effortless subplot management: build complex multi-panel layouts in one line - GeoAxes support included out of the box - Smarter aesthetics: be…
> Instead of wrestling with subplot positioning and styling, you can write:
This would be more convincing if you showed the equivalent Matplotlib code and demonstrated that any improvements are not just a result of default settings being a closer match for what the example tries to do. The code shown here looks more or less like what I'd expect a Matplotlib hello-world to look like.
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#4I was hoping to see more support towards Python typings, which is my biggest annoyance with Matplotlib.
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#5For those unfamiliar, ProPlot was widely loved for enabling publication-quality graphics with minimal effort. UltraPlot continues that mission with active development, updated compatibility, and a focus on simplicity. Why UltraPlot? Key improvements over vanilla matplotlib: - Effortless subplot management: build complex multi-panel layouts in one line - GeoAxes support included out of the box - Smarter aesthetics: be…
> Instead of wrestling with subplot positioning and styling, you can write: This would be more convincing if you showed the equivalent Matplotlib code and demonstrated that any improvements are not just a result of default settings being a closer match for what the example tries to do. The code shown here looks more or less like what I'd expect a Matplotlib hello-world to look like.
You are right. I was doubting whether to make a more complicated example -- but formatting is poor in text boxes. Let me give you a more complex one.
Let's say we want a 3-column plot: colormesh, polar, and geo plot.
UltraPlot:
import ultraplot as uplt, numpy as np
fig, ax = uplt.subplots(
ncols=3, share=0, proj="cart polar merc".split(), journal="nat2"
)
ax[0].pcolormesh(
np.random.rand(10, 10), cmap="viko", colorbar="r",
colorbar_kw=dict(title="some interesting colors")
)
angles, radii = np.random.rand(100) * 360, np.random.rand(100)
ax[1].scatter(angles, radii, c=radii, cmap="spectral_r")
x, y = np.meshgrid(np.linspace(-30, 30, 100), np.linspace(-60, 60, 100))
z = np.exp(-(x*2 + y*2) / 100)
ax[2].pcolormesh(x, y, z, cmap="Fire")
ax[2].format(landcolor="green", land=True, grid=True, lonlabels=True, latlabels=True)
ax.format(abc="[A]")
fig.show()
import matplotlib.pyplot as plt, numpy as np, cartopy.crs as ccrs
fig = plt.figure(figsize=(15, 5))
ax0 = fig.add_subplot(1, 3, 1)
pcm = ax0.pcolormesh(np.random.rand(10, 10), cmap="viridis")
cbar = plt.colorbar(pcm, ax=ax0)
cbar.set_label("some interesting colors")
cbar.ax.yaxis.label.set_color("r")
ax1 = fig.add_subplot(1, 3, 2, projection="polar")
angles = np.random.rand(100) * 2 * np.pi
radii = np.random.rand(100)
sc = ax1.scatter(angles, radii, c=radii, cmap="Spectral_r")
ax2 = fig.add_subplot(1, 3, 3, projection=ccrs.Mercator())
x, y = np.meshgrid(np.linspace(-30, 30, 100), np.linspace(-60, 60, 100))
z = np.exp(-(x*2 + y*2) / 100)
pcm2 = ax2.pcolormesh(x, y, z, cmap="magma", transform=ccrs.PlateCarree())
ax2.coastlines()
ax2.gridlines(draw_labels=True)
ax2.set_extent([-30, 30, -60, 60], crs=ccrs.PlateCarree())
import cartopy.feature as cfeature
ax2.add_feature(cfeature.LAND, facecolor="green")
for i, ax in enumerate([ax0, ax1, ax2]):
ax.set_title(f"[{chr(65+i)}]")
plt.tight_layout()
plt.show()
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#6Earlier quoted context omitted.
> Instead of wrestling with subplot positioning and styling, you can write: This would be more convincing if you showed the equivalent Matplotlib code and demonstrated that any improvements are not just a result of default settings being a closer match for what the example tries to do. The code shown here looks more or less like what I'd expect a Matplotlib hello-world to look like.
You are right. I was doubting whether to make a more complicated example -- but formatting is poor in text boxes. Let me give you a more complex one. Let's say we want a 3-column plot: colormesh, polar, and geo plot. UltraPlot: import ultraplot as uplt, numpy as np fig, ax = uplt.subplots( ncols=3, share=0, proj="cart polar merc".split(), journal="nat2" ) ax[0].pcolormesh( np.random.rand(10, 10), cmap="viko", colorba…
> You are right. I was doubting to make a more complicated example -- but formatting is poor on txt boxes.
I see now that you have an example in the README. I think it would be better still in the README, but as plain text rather than rendered into an SVG.
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#7I was hoping to see more support towards Python typings, which is my biggest annoyance with Matplotlib.
Could you explain more concretely what kind of "support" you have in mind? A graphing library isn't like Pydantic, you aren't supplying typing information from your own code to it as part of the API. Do you just mean that it should provide type annotations in its own interface? Because I do see .pyi typing stubs in the distribution.
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#8For those unfamiliar, ProPlot was widely loved for enabling publication-quality graphics with minimal effort. UltraPlot continues that mission with active development, updated compatibility, and a focus on simplicity. Why UltraPlot? Key improvements over vanilla matplotlib: - Effortless subplot management: build complex multi-panel layouts in one line - GeoAxes support included out of the box - Smarter aesthetics: be…
[deleted]
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#9That comparison between the matplotlib and ultraplot APIs doesn't seem fair. Most of the difference in length is that the separate methods for formatting in matplotlib are bundled into a single format() function in ultraplot. But, in matplotlib, you can pass those as kwargs to add_subplot() [1] which would work out at a similar length (or even shorter).
[1] https://matplotlib.org/stable/api/_as_gen/matplotlib.figure....
Maybe there are much more important API differences (I hope so, as that's a pretty trivial difference to start with.) I just mention it because that's what the screenshot seems to focus on as a justification: "Why UltraPlot? | Write Less, Create More".
Re: Show HN: Ultraplot – A succint wrapper for matplotlib
#10I was hoping to see more support towards Python typings, which is my biggest annoyance with Matplotlib.
We do provide some type hinting but it is more a recent development as we are building on the legacy code from proplot which did not provide any. I am in favor of using typing more.