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Add fixes for vertical line xlim and PDF xlim #1182

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Merged
jwarner8 merged 5 commits into from
Feb 24, 2025
Merged

Add fixes for vertical line xlim and PDF xlim #1182

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9847436
vertical line fix
jwarner8 Feb 20, 2025
b430c6a
fix histograms
jwarner8 Feb 20, 2025
4f18455
Merge branch 'main' into use_json
jwarner8 Feb 20, 2025
7d346e3
Update src/CSET/operators/plot.py
jwarner8 Feb 24, 2025
1e78def
Merge branch 'main' into use_json
jwarner8 Feb 24, 2025
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103 changes: 46 additions & 57 deletions src/CSET/operators/plot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -614,6 +614,9 @@ def _plot_and_save_vertical_line_series(
ax.ticklabel_format(axis="x")
ax.tick_params(axis="y")

# Add gridlines
ax.grid(linestyle="--", color="grey", linewidth=1)

# Save plot.
fig.savefig(filename, bbox_inches="tight", dpi=_get_plot_resolution())
logging.info("Saved line plot to %s", filename)
Expand Down Expand Up @@ -691,7 +694,6 @@ def _plot_and_save_histogram_series(
title: str,
vmin: float,
vmax: float,
histtype: str = "step",
**kwargs,
):
"""Plot and save a histogram series.
Expand All @@ -700,15 +702,6 @@ def _plot_and_save_histogram_series(
----------
cubes: Cube or CubeList
2 dimensional Cube or CubeList of the data to plot as histogram.
Plotting options are fixed:
density=True, histtype='step',stacked=True to ensure that
a probability density is plotted using matplotlib.pyplot.hist
to plot the probability density so that the area under
the histogram integrates to 1.
stacked is set to True so the sum of the histograms is
normalized to 1.
ax.autoscale is switched off and the ylim range
is preset as (0,1) to make figures comparable.
filename: str
Filename of the plot to write.
title: str
Expand All @@ -717,10 +710,6 @@ def _plot_and_save_histogram_series(
minimum for colorbar
vmax: float
maximum for colorbar
histtype: str
The type of histogram to plot. Options are "step" for a line
histogram or "barstacked", "stepfilled". "Step" is the default option,
but can be changed in the rose-suite.conf configuration.
"""
fig = plt.figure(figsize=(10, 10), facecolor="w", edgecolor="k")
ax = plt.gca()
Expand Down Expand Up @@ -774,7 +763,6 @@ def _plot_and_save_postage_stamp_histogram_series(
stamp_coordinate: str,
vmin: float,
vmax: float,
histtype: str,
**kwargs,
):
"""Plot and save postage (ensemble members) stamps for a histogram series.
Expand All @@ -783,15 +771,6 @@ def _plot_and_save_postage_stamp_histogram_series(
----------
cube: Cube
2 dimensional Cube of the data to plot as histogram.
Plotting options are fixed:
density=True, histtype='bar', stacked=True to ensure that
a probability density is plotted using matplotlib.pyplot.hist
to plot the probability density so that the area under
the histogram integrates to 1.
stacked is set to True so the sum of the histograms is
normalized to 1.
ax.autoscale is switched off and the ylim range
is preset as (0,1) to make figures comparable.
filename: str
Filename of the plot to write.
title: str
Expand All @@ -802,11 +781,6 @@ def _plot_and_save_postage_stamp_histogram_series(
minimum for pdf x-axis
vmax: float
maximum for pdf x-axis
histtype: str
The type of histogram to plot. Options are "step" for a line
histogram or "barstacked", "stepfilled". "Step" is the default option,
but can be changed in the rose-suite.conf configuration.

"""
# Use the smallest square grid that will fit the members.
grid_size = int(math.ceil(math.sqrt(len(cube.coord(stamp_coordinate).points))))
Expand All @@ -822,7 +796,7 @@ def _plot_and_save_postage_stamp_histogram_series(
# Reshape cube data into a single array to allow for a single histogram.
# Otherwise we plot xdim histograms stacked.
member_data_1d = (member.data).flatten()
plt.hist(member_data_1d, density=True, histtype=histtype, stacked=True)
plt.hist(member_data_1d, density=True, stacked=True)
ax = plt.gca()
ax.set_title(f"Member #{member.coord(stamp_coordinate).points[0]}")
ax.set_xlim(vmin, vmax)
Expand All @@ -842,7 +816,6 @@ def _plot_and_save_postage_stamps_in_single_plot_histogram_series(
stamp_coordinate: str,
vmin: float,
vmax: float,
histtype: str = "step",
**kwargs,
):
fig, ax = plt.subplots(figsize=(10, 10), facecolor="w", edgecolor="k")
Expand All @@ -858,7 +831,6 @@ def _plot_and_save_postage_stamps_in_single_plot_histogram_series(
plt.hist(
member_data_1d,
density=True,
histtype=histtype,
stacked=True,
label=f"Member #{member.coord(stamp_coordinate).points[0]}",
)
Expand Down Expand Up @@ -1188,6 +1160,9 @@ def plot_vertical_line_series(
# Initialise empty list to hold all data from all cubes in a CubeList
all_data = []

# Store min/max ranges for x range.
x_levels = []

# Iterate over all cubes in cube or CubeList and plot.
for cube_iter in iter_maybe(cubes):
# Ensure we've got a single cube.
Expand All @@ -1209,18 +1184,26 @@ def plot_vertical_line_series(
f"Cube must have a {sequence_coordinate} coordinate or be 1D."
) from err

# Append cube data to the list to calculate vmin and vmax across entire
# cubelist.
all_data.append(cube_iter.data)
# Get minimum and maximum from levels information.
_, levels, _ = _colorbar_map_levels(cube_iter)
if levels is not None:
x_levels.append(min(levels))
x_levels.append(max(levels))
else:
all_data.append(cube_iter.data)

# Combine all data into a single NumPy array
combined_data = np.concatenate(all_data)
if len(x_levels) == 0:
# Combine all data into a single NumPy array
combined_data = np.concatenate(all_data)

# Set the lower and upper limit for the x-axis to ensure all plots have same
# range. This needs to read the whole cube over the range of the sequence
# and if applicable postage stamp coordinate.
vmin = np.floor(combined_data.min())
vmax = np.ceil(combined_data.max())
# Set the lower and upper limit for the x-axis to ensure all plots have same
# range. This needs to read the whole cube over the range of the sequence
# and if applicable postage stamp coordinate.
vmin = np.floor(combined_data.min())
vmax = np.ceil(combined_data.max())
else:
vmin = min(x_levels)
vmax = max(x_levels)

# Create a plot for each value of the sequence coordinate.
# Allowing for multiple cubes in a CubeList to be plotted in the same plot for
Expand Down Expand Up @@ -1356,7 +1339,6 @@ def plot_histogram_series(
sequence_coordinate: str = "time",
stamp_coordinate: str = "realization",
single_plot: bool = False,
histtype: str = "step",
**kwargs,
) -> iris.cube.Cube | iris.cube.CubeList:
"""Plot a histogram plot for each vertical level provided.
Expand Down Expand Up @@ -1389,10 +1371,6 @@ def plot_histogram_series(
If True, all postage stamp plots will be plotted in a single plot. If
False, each postage stamp plot will be plotted separately. Is only valid
if stamp_coordinate exists and has more than a single point.
histtype: str, optional
The type of histogram to plot. Options are "step" for a line histogram
or "barstacked", "stepfilled". "Step" is the default option, but can be
changed in the rose-suite.conf configuration.

Returns
-------
Expand All @@ -1419,6 +1397,9 @@ def plot_histogram_series(
# Initialise empty list to hold all data from all cubes in a CubeList
all_data = []

# Store min/max ranges for xlim.
x_levels = []

# Iterate over all cubes in cube or CubeList and plot.
for cube_iter in iter_maybe(cubes):
# Ensure we've got a single cube.
Expand Down Expand Up @@ -1447,17 +1428,26 @@ def plot_histogram_series(
f"Cube must have a {sequence_coordinate} coordinate."
) from err

# append cube data to the list to calculate vmin and vmax across entire cubelist
all_data.append(cube_iter.data)
# Get minimum and maximum from levels information.
_, levels, _ = _colorbar_map_levels(cube_iter)
if levels is not None:
x_levels.append(min(levels))
x_levels.append(max(levels))
else:
all_data.append(cube_iter.data)

# Combine all data into a single NumPy array
combined_data = np.concatenate(all_data)
if len(x_levels) == 0:
# Combine all data into a single NumPy array
combined_data = np.concatenate(all_data)

# Set the lower and upper limit for the colorbar to ensure all plots have
# same range. This needs to read the whole cube over the range of the
# sequence and if applicable postage stamp coordinate.
vmin = np.floor((combined_data.min()))
vmax = np.ceil((combined_data.max()))
# Set the lower and upper limit for the x-axis to ensure all plots have same
# range. This needs to read the whole cube over the range of the sequence
# and if applicable postage stamp coordinate.
vmin = np.floor(combined_data.min())
vmax = np.ceil(combined_data.max())
else:
vmin = min(x_levels)
vmax = max(x_levels)

# Create a plot for each value of the sequence coordinate.
# Allowing for multiple cubes in a CubeList to be plotted in the same plot for
Expand All @@ -1480,7 +1470,6 @@ def plot_histogram_series(
title=title,
vmin=vmin,
vmax=vmax,
histtype=histtype,
)
plot_index.append(plot_filename)

Expand Down