def scan_plot_energy(
scan_dir: Union[Path, str],
propagation: str = "propagate",
extensions: List[str] = [".png"],
**kwargs,
):
scan_dir = make_path(scan_dir)
plotting_args = PlotArgs2D.from_dict(kwargs)
selection = load_scan(scan_dir)
def plot_func(index, path, parameters):
del path
del parameters
time, _, energy, _ = read_output_hdf5(
scan_dir / "by_index" / str(index) / propagation / "propagate.h5",
"output",
)
fig, axis = plt.subplots(1, 1)
plot_energy(axis, time, energy)
return fig, [axis]
yield doit_plot_individual(
selection,
"energy",
[str(Path(propagation) / "propagate.h5")],
plot_func,
plotting_args,
extensions,
decorator_funcs=kwargs.get("decorator_funcs", []),
)
def scan_plot_gpop(
scan_dir: Union[Path, str],
propagation: str = "propagate",
dof: int = 1,
extensions: List[str] = [
".png",
],
**kwargs,
):
scan_dir = make_path(scan_dir)
plot_name = kwargs.get("plot_name", f"gpop_{dof}")
plotting_args = PlotArgs2D.from_dict(kwargs)
plotting_args.grid = kwargs.get("grid", False)
selection = load_scan(scan_dir)
def plot_func(index, path, parameters):
del path
del parameters
time, grid, density = read_gpop(
str(scan_dir / "by_index" / str(index) / propagation /
"propagate.h5") + "/gpop",
dof=dof,
)
fig, axis = plt.subplots(1, 1)
plot_gpop(axis, time, grid, density)
return fig, [axis]
yield doit_plot_individual(
selection,
plot_name,
[str(Path(propagation) / "propagate.h5")],
plot_func,
plotting_args,
extensions,
decorator_funcs=kwargs.get("decorator_funcs", []),
)
def scan_plot_entropy(
scan_dir: Union[Path, str],
propagation: str = "propagate",
node: int = 1,
dof: int = 1,
extensions: List[str] = [
".png",
],
**kwargs,
):
scan_dir = make_path(scan_dir)
plotting_args = PlotArgs2D.from_dict(kwargs)
selection = load_scan(scan_dir)
def plot_func(index, path, parameters):
del path
del parameters
data = read_natpop(
str(scan_dir / "by_index" / str(index) / propagation /
"propagate.h5") + "/natpop",
node=node,
dof=dof,
)
entropy = compute_entropy(data[1])
fig, axis = plt.subplots(1, 1)
plot_entropy(axis, data[0], entropy)
return fig, [axis]
return doit_plot_individual(
selection,
"entropy",
[str(Path(propagation) / "propagate.h5")],
plot_func,
plotting_args,
extensions,
decorator_funcs=kwargs.get("decorator_funcs", []),
)
def scan_plot_expval(
scan_dir: Union[Path, str],
expval: Union[Path, str],
extensions: List[str] = [
".png",
],
**kwargs,
):
scan_dir = make_path(scan_dir)
expval = make_path(expval)
kwargs["coefficient"] = kwargs.get("coefficient", 1.0)
plotting_args = PlotArgs2D.from_dict(kwargs)
selection = load_scan(scan_dir)
def plot_func(index, path, parameters):
del path
del parameters
data = read_expval_hdf5(
str((scan_dir / "by_index" / str(index) /
expval).with_suffix(".exp.h5")), )
fig, axis = plt.subplots(1, 1)
plot_expval(axis, *data, **kwargs)
return fig, [axis]
return doit_plot_individual(
selection,
f"expval_{str(expval)}".replace("/", "_"),
[str(expval.with_suffix(".exp.h5"))],
plot_func,
plotting_args,
extensions,
decorator_funcs=kwargs.get("decorator_funcs", []),
extra_args={"coefficient": kwargs["coefficient"]},
)