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Clean up figures #213

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21 changes: 8 additions & 13 deletions tutorials/parquet-catalog-demos/euclid-q1-hats/4-euclid-q1-hats-magnitudes.md
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Original file line number Diff line number Diff line change
Expand Up @@ -66,6 +66,9 @@ import pyarrow.compute as pc # Filter dataset
import pyarrow.dataset # Load the dataset
import pyarrow.fs # Simple S3 filesystem pointer
import pyarrow.parquet # Load the schema

# Increase font size in figures.
plt.rcParams.update({"font.size": 14})
```

```{code-cell} ipython3
Expand Down Expand Up @@ -217,10 +220,6 @@ Let's visualize the template-fit magnitude distributions as a function of PHZ cl
Since the template-fit photometry is recommended for extended objects, we'll separate the point-like objects.
[Euclid Collaboration: Tucci et al., 2025](https://arxiv.org/pdf/2503.15306) defines point-like objects as having `MUMAX_MINUS_MAG < -2.5`.

```{code-cell} ipython3

```

```{code-cell} ipython3
---
jupyter:
Expand Down Expand Up @@ -250,20 +249,20 @@ for (class_name, class_ids), class_color in zip(classes.items(), class_colors):
label = "+Galaxy" if class_name != "Galaxy" else "+any"
# Of those objects, restrict to the ones that are point-like.
classpt_df = class_df.loc[class_df[MUMAX_MINUS_MAG] < -2.5]
pt_label = f"{label} and point-like"
pt_label = f"{label} (point-like)"
# Plot histograms for both sets of objects.
for ax, band in zip(axs, bands):
ax.hist(class_df[band], label=label, linestyle=":", **hist_kwargs)
ax.hist(classpt_df[band], linestyle="-.", label=pt_label, **hist_kwargs)

# Add axis labels, etc.
for ax in axes[:, 0]:
for ax, loc in zip(axes[:, 0], [2, 3, 2]):
ax.legend(loc=loc)
ax.set_ylabel("Counts")
ax.legend(framealpha=0.2, loc=2)
for axs, band in zip(axes.transpose(), bands):
axs[0].set_title(band.split()[0])
axs[-1].set_xlabel(band)
plt.title("Magnitude Distributions by Object Type")
fig.suptitle("Magnitude Distributions by Object Type")
plt.tight_layout()
```

Expand Down Expand Up @@ -293,10 +292,6 @@ This comparison reveals systematic offsets that depend on factors including morp

This figure is inspired by Romelli Fig. 6 (top panel).

```{code-cell} ipython3

```

```{code-cell} ipython3
---
jupyter:
Expand Down Expand Up @@ -358,7 +353,7 @@ for i, ax in enumerate(axes.flatten()):
ax.set_title("Point-like objects")
if i > 2:
ax.set_xlabel(I_MAG)
plt.title("Magnitude Differences: Template-fit - Aperture")
fig.suptitle("Magnitude Offsets (Template fit - Aperture)")
plt.tight_layout()
```

Expand Down