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This commit is contained in:
Noe Brucy
2020-02-29 10:16:27 +01:00
parent 8d7c5296cc
commit 1c2750a7bd
4 changed files with 1669 additions and 32 deletions
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comparator.py
+28 -14
View File
@@ -122,10 +122,10 @@ class Comparator(Aggregator, HDF5Container):
def _time_series(self, getter, arg=None):
series = {}
for run in self.runs:
series[run] = np.zeros(len(self.nums[run]))
series[run] = []
for i, num in enumerate(self.nums[run]):
series[run][i] = getter(run, num, arg=arg)
return series
series[run].apend(getter(run, num, arg=arg))
return np.array(series)
def _comp(self, getter, use_num=True):
prop = np.zeros(len(self.runs))
@@ -137,9 +137,7 @@ class Comparator(Aggregator, HDF5Container):
prop[i] = getter(run)
return prop
def _time_avg(
self, name, start=None, end=None, span=None, ergodic=False, group="/series"
):
def _time_avg(self, name, start=None, end=None, span=None, group="/series"):
mean = np.zeros(len(self.runs))
median = np.zeros(len(self.runs))
std = np.zeros(len(self.runs))
@@ -169,15 +167,11 @@ class Comparator(Aggregator, HDF5Container):
mask = mask & (time >= start_r) & (time <= end_r) & np.isfinite(serie)
mean[i] = np.mean(serie[mask])
std[i] = np.std(serie[mask])
mean[i] = np.mean(serie[mask], axis=0)
std[i] = np.std(serie[mask], axis=0)
v_min[i], q025[i], median[i], q975[i], v_max[i] = np.percentile(
serie[mask], [0, 2.5, 50, 97.5, 100]
serie[mask], [0, 2.5, 50, 97.5, 100], axis=0
)
if ergodic: # If the process is ergodic ...
std[i] = std[i] / np.sqrt(len(serie[mask]))
else:
std[i] = std[i]
return {
"runs": self.runs,
"mean": mean,
@@ -195,6 +189,12 @@ class Comparator(Aggregator, HDF5Container):
node_name = node_name + "_" + str(arg)
return pp.get_attribute(node_name, attr_name)
def get_pp_value(self, name, run, num, arg=None):
pp = self.pp[run][num]
if not arg is None:
name = name + "_" + str(arg)
return pp.get_value(name)
def get_global(self, node_name, run, num, arg=None, unload_cells=False):
if not arg is None:
node_name = node_name + "_" + str(arg)
@@ -509,6 +509,14 @@ class Comparator(Aggregator, HDF5Container):
unit="unit_time",
dependencies=["time_num"],
),
"time_rho_prof": Rule(
self,
partial(
self._time_series, partial(self.get_pp_value, "/profile/rho_prof")
),
group="/series",
dependencies={"time": None, "rho_prof": "__parent__"},
),
"time_pdf_slope_coldens": Rule(
self,
partial(
@@ -535,7 +543,13 @@ class Comparator(Aggregator, HDF5Container):
self._gen_rule_time_global("mwa_sigma", "time_sigma", unit="unit_velocity")
self._gen_rule_time_global("max_fluct_coldens")
for name in ["issfr", "time_sigma", "time_pdf_slope_coldens", "turb_power"]:
for name in [
"issfr",
"time_sigma",
"time_pdf_slope_coldens",
"turb_power",
"time_rho_prof",
]:
self._gen_rule_avg(name)
self._gen_rule_avg("sinks_from_log", "mass_sink")
plotter.py
+43 -17
View File
@@ -129,6 +129,8 @@ class Plotter(Aggregator, BaseProcessor):
if rule.kind == "classic":
try:
runs = kwargs.pop("runs")
if isinstance(runs, RunSelector):
runs = runs.runs
except KeyError:
runs = self.runs
@@ -150,7 +152,12 @@ class Plotter(Aggregator, BaseProcessor):
run=run,
**kwargs
)
except TypeError:
except TypeError as e:
if (
str(e)
!= "'LocatableAxes' object does not support indexing"
):
raise
self._plot_rule(
rule,
save,
@@ -207,7 +214,7 @@ class Plotter(Aggregator, BaseProcessor):
tag_name = "_" + tag_name
if not run is None and not num is None:
fmt = "{out}/{run}/{name}{tag}_{run}_{num:05}_{ext}"
fmt = "{out}/{run}/{name}{tag}_{run}_{num:05}{ext}"
elif not run is None:
fmt = "{out}/{run}/{name}{tag}_{run}{ext}"
else:
@@ -300,6 +307,7 @@ class Plotter(Aggregator, BaseProcessor):
overlays=[],
overlays_kwargs=[],
title=None,
put_title=True,
nml_key=None,
put_time=True,
time_unit=cst.Myr,
@@ -352,19 +360,20 @@ class Plotter(Aggregator, BaseProcessor):
if not label is None:
cbar.set_label(label)
title = self._label_run(run, node, title, nml_key)
if put_title:
title = self._label_run(run, node, title, nml_key)
if put_time:
time = self.save.root._v_attrs.time * self.comp.info["unit_time"]
time_str = self.pp_params.plot.time_fmt.format(
time.express(time_unit), time_unit.latex
)
if len(title) > 0:
title = title + " | " + time_str
else:
title = time_str
if put_time:
time = self.save.root._v_attrs.time * self.comp.info["unit_time"]
time_str = self.pp_params.plot.time_fmt.format(
time.express(time_unit), time_unit.latex
)
if len(title) > 0:
title = title + " | " + time_str
else:
title = time_str
P.title(title)
P.title(title)
for i, plot_overlay in enumerate(overlays):
try:
@@ -470,6 +479,7 @@ class Plotter(Aggregator, BaseProcessor):
xlog=None,
ylog=False,
kind="bar",
color=None,
colors=None,
nml_color=None,
**kwargs
@@ -505,8 +515,7 @@ class Plotter(Aggregator, BaseProcessor):
P.title(title)
color = None
if not colors is None:
if color is None and not colors is None:
if nml_color is None:
color = colors[run]
else:
@@ -547,6 +556,7 @@ class Plotter(Aggregator, BaseProcessor):
self,
name_x,
name_y,
node_arg=None,
xlabel=None,
ylabel=None,
label=None,
@@ -558,14 +568,19 @@ class Plotter(Aggregator, BaseProcessor):
fitlabel=None,
smooth=0,
nml_key=None,
run=None,
runs=None,
yerr_kind="std",
sigma_err=2.0,
grid=True,
colors=None,
nml_color=None,
**kwargs
):
if not node_arg is None:
name_x, name_y = name_x + "_" + node_arg, name_y + "_" + node_arg
node_x = self.save.get_node(name_x)
node_y = self.save.get_node(name_y)
@@ -578,7 +593,9 @@ class Plotter(Aggregator, BaseProcessor):
P.xlabel(xlabel)
P.ylabel(ylabel)
P.grid()
if grid:
P.grid()
yerr = None
if node_y._v_attrs.CLASS == "ARRAY":
@@ -588,7 +605,9 @@ class Plotter(Aggregator, BaseProcessor):
x, y = x[mask], y[mask]
if smooth > 0:
y = gaussian_filter1d(y, sigma=smooth)
(base_line,) = P.plot(x, y, "*", **kwargs)
if not run is None:
label = self._label_run(run, node_y, label, nml_key)
(base_line,) = P.plot(x, y, label=label, **kwargs)
elif "mean" in node_y:
x = node_x.read() * xunit_old.express(xunit)
y = node_y.mean.read() * yunit_old.express(yunit)
@@ -616,6 +635,8 @@ class Plotter(Aggregator, BaseProcessor):
yerr_min[mask],
yerr_max[mask],
)
if not run is None:
label = self._label_run(run, node_y, label, nml_key)
base_line, _, _ = P.errorbar(
x, y, yerr=[y - yerr_min, yerr_max - y], label=label, **kwargs
)
@@ -806,6 +827,11 @@ class Plotter(Aggregator, BaseProcessor):
"P_pdf": PlotRule(
self, partial(self._plot_hist, "P_pdf"), "P-PDF", dependencies=["P_pdf"]
),
"rho_prof": PlotRule(
self,
partial(self._plot, "/profile/axis", "/profile/rho_prof"),
dependencies=["axis", "rho_prof"],
),
}
averageables = ["coldens", "rho", "T", "Q"]
postprocessor.py
+51 -1
View File
@@ -1,5 +1,5 @@
# coding: utf-8
import pandas as pd
from baseprocessor import *
mass_func = lambda dset: dset["rho"] * dset["dx"] ** 3 # Mass function
@@ -141,6 +141,7 @@ class PostProcessor(HDF5Container):
for key in cells_pymses.fields:
self.cells[key] = cells_pymses[key]
self.cells["dx"] = cells_pymses.get_sizes()
self.cells["pos"] = cells_pymses.points
if self.pp_params.process.save_cells:
cells_hdf5 = tables.open_file(self.cells_filename, mode="w")
@@ -195,6 +196,7 @@ class PostProcessor(HDF5Container):
):
"""
Map of the average of a quantity (given by getter) along an axis (ax_los)
Return 2D array
"""
if mass_weighted:
@@ -216,6 +218,38 @@ class PostProcessor(HDF5Container):
datamap = rt.process(self._cam[ax_los], surf_qty=surf_qty)
return datamap.map.T
def _get_axis(self, axis):
if isinstance(axis, str):
axis = self._ax_nb[axis]
self.load_cells()
return np.sort(np.unique(self.cells["pos"][:, axis]))
def _plane_avg_uniform(
self, getter, axis, unit=cst.none, mass_weighted=True, surf_qty=False
):
"""
Profile of the average of a quantity (given by getter) perpendicular to an axis
WARNING : This version only works on an uniform grid, need of a box version for AMR
"""
self.load_cells()
if isinstance(axis, str):
axis = self._ax_nb[axis]
axis_data = self.cells["pos"][:, axis]
value = getter(self.cells)
df = pd.DataFrame({"axis": axis_data})
if mass_weighted:
mass = mass_func(self.cells)
tot_mass = np.sum(mass)
df["value"] = value * mass / tot_mass
else:
df["value"] = value
df.sort_values("axis", inplace=True)
return df.groupby("axis").mean().values[:, 0]
def _vol_avg(self, getter, mass_weighted=True):
self.load_cells()
value = getter(self.cells)
@@ -685,6 +719,22 @@ class PostProcessor(HDF5Container):
"/hist",
unit=self.info["unit_pressure"],
),
# Profiles
"axis": Rule(
self,
partial(self._get_axis),
"Axis",
"/profile",
unit=self.info["unit_length"],
),
"rho_prof": Rule(
self,
partial(self._plane_avg_uniform, partial(simple_getter, "rho")),
"Rho profile",
"/profile",
unit=self.info["unit_density"],
dependencies=["axis"],
),
# globals
"time_num": Rule(
self,
pp_multiarg.py
+1547
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