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dis_plot can plot a single point by particle and also a cut #1119

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643ce6e
dis_plot can now plot a single point by particle and also a cut along…
rochSmets Jan 8, 2026
ec6fe21
python module per simulator template permutation (#1047)
PhilipDeegan Jan 29, 2026
b63bdfc
max_level check for restarts (#1130)
PhilipDeegan Jan 30, 2026
a7f8edb
max battle (#1146)
PhilipDeegan Feb 10, 2026
1b6f717
const correctness
PhilipDeegan Jan 26, 2026
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rochSmets Feb 11, 2026
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13 changes: 8 additions & 5 deletions pyphare/pyphare/pharesee/hierarchy/hierarchy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -583,11 +583,14 @@ def dist_plot(self, **kwargs):

if finest:
final = finest_part_data(self)
if axis[0] == "x":
xbins = amr_grid(self, time)
bins = (xbins, vbins)
else:
bins = (vbins, vbins)
if len(axis) == 2:
if axis[0] == "x":
xbins = amr_grid(self, time)
bins = (xbins, vbins)
else:
bins = (vbins, vbins)
elif len(axis) == 1:
bins = vbins
kwargs["bins"] = bins

else:
Expand Down
145 changes: 103 additions & 42 deletions pyphare/pyphare/pharesee/plotting.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@

kwargs:
* axis : ("x", "Vx"), ("x", "Vy"), ("x", "Vz"), ("Vx", "Vy") (default) --
("Vx", "Vz"), ("Vy", "Vz")
("Vx", "Vz"), ("Vy", "Vz"), ("Vx"), (Vy"), ("Vz")
* bins : number of bins in each dimension, default is (50,50)
Comment on lines 20 to 22
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⚠️ Potential issue | 🟡 Minor

Fix malformed axis docstring entry.
Line 21 has (Vy"), which reads as a typo and can confuse users.

✏️ Suggested fix 
-       ("Vx", "Vz"), ("Vy", "Vz"), ("Vx"), (Vy"), ("Vz")
+       ("Vx", "Vz"), ("Vy", "Vz"), ("Vx"), ("Vy"), ("Vz")
🤖 Prompt for AI Agents 
In `@pyphare/pyphare/pharesee/plotting.py` around lines 20 - 22, The docstring for
the "axis" parameter in pyphare.pyphare.pharesee.plotting.py contains a
malformed entry `(Vy")`; update the axis list so all entries are properly quoted
and comma-separated (e.g., replace `(Vy")` with ("Vy") and ensure consistency
like ("Vx"), ("Vy"), ("Vz") and pairs ("Vx","Vy") etc.) in the plotting module's
docstring so the axis options are readable and valid.

* gaussian_filter_sigma : sigma of the gaussian filter, default is (0,0)
* median_filter_size : size of the median filter, default is (0,0)
Expand Down Expand Up @@ -53,50 +53,111 @@
axis = kwargs.get("axis", ("Vx", "Vy"))
vaxis = {"Vx": 0, "Vy": 1, "Vz": 2}

if axis[0] in vaxis:
x = particles.v[:, vaxis[axis[0]]]
elif axis[0] == "x":
x = particles.x
if axis[1] in vaxis:
y = particles.v[:, vaxis[axis[1]]]
if len(axis) == 2:
if axis[0] in vaxis:
x = particles.v[:, vaxis[axis[0]]]
elif axis[0] == "x":
x = particles.x
else:
raise ValueError("Only abscissa and velocity X-axis are supported yet")
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@nicolasaunai nicolasaunai Feb 11, 2026

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do we consider the option (y,v) or (z,v) or (v,y) and (v,z) ?

if axis[1] in vaxis:
y = particles.v[:, vaxis[axis[1]]]
else:
raise ValueError("Only velocity Y-axis are supported yet")

bins = kwargs.get("bins", (50, 50))
h, xh, yh = np.histogram2d(
x, y, bins=bins, weights=particles.weights[:, 0]
)

bins = kwargs.get("bins", (50, 50))
h, xh, yh = np.histogram2d(
x, y, bins=kwargs.get("bins", bins), weights=particles.weights[:, 0]
)
if "gaussian_filter_sigma" in kwargs and "median_filter_size" not in kwargs:
from scipy.ndimage import gaussian_filter

sig = kwargs.get("gaussian_filter_sigma", (0, 0))
image = gaussian_filter(h.T, sigma=sig)
elif "median_filter_size" in kwargs and "gaussian_filter_sigma" not in kwargs:
from scipy.ndimage import median_filter

siz = kwargs.get("median_filter_size", (0, 0))
image = median_filter(h.T, size=siz)
elif "gaussian_filter_sigma" not in kwargs and "median_filter_size" not in kwargs:
image = h.T
else:
raise ValueError(
"gaussian and median filters can not be called at the same time"
)

plain = kwargs.get("plain", False)

if not plain:
cmap = kwargs.get("cmap", "jet")

cmax = kwargs.get("color_max", h.max())
cmin = kwargs.get("color_min", h.min())
cmin = max(cmin, 1e-4)

color_scale = kwargs.get("color_scale", "log")
if color_scale == "log":
norm = LogNorm(vmin=cmin, vmax=cmax)
elif color_scale == "linear":
norm = Normalize(cmin, cmax)
else:
raise ValueError("Only log and linear color_scale values are supported yet")

im = ax.pcolormesh(xh, yh, image, cmap=cmap, norm=norm)

fig.colorbar(im, ax=ax)
else:
color = kwargs.get("color", "k")
stride = kwargs.get("stride", 1)
markersize = kwargs.get("markersize", 0.5)
alpha = kwargs.get("alpha", 0.5)
im = ax.plot(x[::stride], y[::stride],

Check notice

Code scanning / CodeQL

Unused local variable Note

Variable im is not used.
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@rochSmets rochSmets Jan 15, 2026

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yep, like the one defined with the previous pcolormesh. But lets keep this handle around !

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@rochSmets rochSmets Jan 15, 2026

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yep, but let's keep it,

color=color,
linewidth=0,
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@nicolasaunai nicolasaunai Feb 11, 2026

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I think the more correct way to do this plot would be to use ax.scatter() rather than a plot with a 0 size linewidth (which rather should even be linestyle="none")

marker='.',
markersize=markersize,
alpha=alpha)
Comment on lines +111 to +120
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⚠️ Potential issue | 🟡 Minor

Validate stride to avoid invalid slicing.
Line 112 allows stride=0, which raises ValueError in slicing.

🧩 Proposed guard 
         stride = kwargs.get("stride", 1)
+        if stride <= 0:
+            raise ValueError("stride must be a positive integer")
         markersize = kwargs.get("markersize", 0.5)
🤖 Prompt for AI Agents 
In `@pyphare/pyphare/pharesee/plotting.py` around lines 111 - 120, The code reads
stride = kwargs.get("stride", 1) and then uses x[::stride] which fails for
stride=0; update the plotting function to validate/coerce stride before slicing:
ensure stride is an integer >= 1 (e.g. convert via int() and if <= 0 either set
stride = 1 or raise a ValueError with a clear message), and then use that
validated stride when calling ax.plot (the variables to look for are the stride
assignment and the ax.plot call where x[::stride], y[::stride] are used).


ax.set_ylabel(kwargs.get("ylabel", axis[1]))


elif len(axis) == 1:
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@nicolasaunai nicolasaunai Feb 11, 2026

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I think axis should be listified (pyphare.core.phare_utilities.listify) to allow users who just want one axis to do axis="x" rather than having to type axis=("x",)

bins = kwargs.get("bins", (50))
cuts = kwargs.get("cuts", None)
ndim = particles.ndim

if cuts is not None:
from pyphare.core.box import Box
if ndim == 1:
box_new = Box(cuts[0][0], cuts[0][1])
new_particles = particles.select(box_new, box_type="pos")
Comment on lines +127 to +134
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⚠️ Potential issue | 🟠 Major

Handle None entries in cuts as described by the API.
The code assumes every cuts[i] is a tuple; None will throw at cuts[0][0].

🧩 One‑dimensional fix (minimal) 
         if cuts is not None:
             from pyphare.core.box import Box
             if ndim == 1:
-                box_new = Box(cuts[0][0], cuts[0][1])
-                new_particles = particles.select(box_new, box_type="pos")
+                if cuts[0] is None:
+                    new_particles = particles
+                else:
+                    box_new = Box(cuts[0][0], cuts[0][1])
+                    new_particles = particles.select(box_new, box_type="pos")
🤖 Prompt for AI Agents 
In `@pyphare/pyphare/pharesee/plotting.py` around lines 127 - 134, The code
assumes cuts[0] is a tuple and fails if it is None; update the ndim==1 branch to
handle None entries by checking cuts[0] is not None before constructing Box and
calling particles.select: if cuts[0] is None leave new_particles as the original
particles (or skip selection), otherwise create box_new = Box(cuts[0][0],
cuts[0][1]) and set new_particles = particles.select(box_new, box_type="pos");
ensure this pattern (check for None) is applied wherever cuts[i] is used so
particles.select is only called with a valid Box.

elif ndim == 2:
box_new = Box((cuts[0][0], cuts[1][0]), (cuts[0][1], cuts[1][1])) # TODO need to be tested
new_particles = particles.select(box_new, box_type="pos")
else:
box_new = Box((cuts[0][0], cuts[1][0], cuts[2][0]), (cuts[0][1], cuts[1][1], cuts[2][1])) # TODO need to be tested
new_particles = particles.select(box_new, box_type="pos")
else:
new_particles = particles

if "gaussian_filter_sigma" in kwargs and "median_filter_size" not in kwargs:
from scipy.ndimage import gaussian_filter
drawstyle = kwargs.get("drawstyle", "steps-mid")

sig = kwargs.get("gaussian_filter_sigma", (0, 0))
image = gaussian_filter(h.T, sigma=sig)
elif "median_filter_size" in kwargs and "gaussian_filter_sigma" not in kwargs:
from scipy.ndimage import median_filter
if axis[0] in vaxis:
x = new_particles.v[:, vaxis[axis[0]]]
else:
raise ValueError("For 1-D dist_plot, the abscissa has to be a velocity axis")
Comment on lines +146 to +149
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⚠️ Potential issue | 🟠 Major

KDE path breaks for 1‑D axis.
When len(axis)==1, y is never defined, but Line 165 still calls sns.kdeplot(x=x, y=y, ...).

🧩 Proposed fix 
     if kwargs.get("kde", False) is True:
         import seaborn as sns
-
-        sns.kdeplot(x=x, y=y, ax=ax, color="w")
+        if len(axis) == 1:
+            sns.kdeplot(x=x, ax=ax, color="w")
+        else:
+            sns.kdeplot(x=x, y=y, ax=ax, color="w")

Also applies to: 162-165

🧰 Tools
🪛 GitHub Check: CodeQL

[notice] 149-149: Unused local variable
Variable im is not used.

🪛 Ruff (0.14.13)

149-149: Avoid specifying long messages outside the exception class

(TRY003)

🤖 Prompt for AI Agents 
In `@pyphare/pyphare/pharesee/plotting.py` around lines 146 - 149, The 1-D branch
fails because y is never defined but sns.kdeplot is later called with y=y; in
the block handling len(axis)==1 (when axis[0] in vaxis), set y=None (or call
sns.kdeplot without the y argument) and ensure the subsequent call to
sns.kdeplot uses only x when y is None; update the code paths around the
axis/vaxis check and the sns.kdeplot invocation (references: axis, vaxis,
new_particles.v, and sns.kdeplot) so that for 1-D plots you pass only x (or x
and y=None) and avoid referencing an undefined y (apply same fix to the other
occurrence around lines 162-165).


siz = kwargs.get("median_filter_size", (0, 0))
image = median_filter(h.T, size=siz)
elif "gaussian_filter_sigma" not in kwargs and "median_filter_size" not in kwargs:
image = h.T
else:
raise ValueError(
"gaussian and median filters can not be called at the same time"
bins = kwargs.get("bins", 50)
h, xh = np.histogram(
x, bins=bins, weights=new_particles.weights[:, 0]
)

cmap = kwargs.get("cmap", "jet")

cmax = kwargs.get("color_max", h.max())
cmin = kwargs.get("color_min", h.min())
cmin = max(cmin, 1e-4)
xh_ = 0.5*(xh[:-1]+xh[1:])
im = ax.plot(xh_, h, drawstyle=drawstyle)

Check notice

Code scanning / CodeQL

Unused local variable Note

Variable im is not used.
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@rochSmets rochSmets Jan 15, 2026

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see above

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@rochSmets rochSmets Jan 15, 2026

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the same,


color_scale = kwargs.get("color_scale", "log")
if color_scale == "log":
norm = LogNorm(vmin=cmin, vmax=cmax)
elif color_scale == "linear":
norm = Normalize(cmin, cmax)
ax.set_ylabel(kwargs.get("ylabel", "f"))

im = ax.pcolormesh(xh, yh, image, cmap=cmap, norm=norm)

fig.colorbar(im, ax=ax)

if kwargs.get("kde", False) is True:
import seaborn as sns
Expand All @@ -105,7 +166,7 @@

ax.set_title(kwargs.get("title", ""))
ax.set_xlabel(kwargs.get("xlabel", axis[0]))
ax.set_ylabel(kwargs.get("ylabel", axis[1]))

if "xlim" in kwargs:
ax.set_xlim(kwargs["xlim"])
if "ylim" in kwargs:
Expand All @@ -116,15 +177,15 @@
if axis[0] in vaxis:
ax.axvline(
np.average(
particles.v[:, vaxis[axis[0]]], weights=particles.weights
new_particles.v[:, vaxis[axis[0]]], weights=new_particles.weights
),
color="w",
ls="--",
)
if axis[1] in vaxis:
ax.axhline(
np.average(
particles.v[:, vaxis[axis[1]]], weights=particles.weights
new_particles.v[:, vaxis[axis[1]]], weights=new_particles.weights
),
color="w",
ls="--",
Expand Down Expand Up @@ -331,8 +392,8 @@

ax.set_title(kwargs.get("title", ""))

ax.set_xlabel(kwargs.get("xlabel", "$x c / \omega_p$"))
ax.set_ylabel(kwargs.get("ylabel", "$y c / \omega_p$"))
ax.set_xlabel(kwargs.get("xlabel", "$x \\ (d_p)$"))
ax.set_ylabel(kwargs.get("ylabel", "$y \\ (d_p)$"))

if "xlim" in kwargs:
ax.set_xlim(kwargs["xlim"])
Expand Down
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