less verbose

This commit is contained in:
Noe Brucy
2022-08-26 15:28:31 +02:00
parent 87e6d7da08
commit 31bbf9c373
4 changed files with 117 additions and 79 deletions
+1 -1
View File
@@ -1,6 +1,6 @@
from scipy.integrate import solve_ivp
from plotter import U
import select_runs
import select_snapshot
import numpy as np
import pandas as pd
+9 -9
View File
@@ -280,6 +280,7 @@ class Plotter(Aggregator, BaseProcessor):
self.def_rules()
# Generate astrophysix's simulations object
if self.params.astrophysix.generate:
self.gen_simus()
# Initialize pointers
@@ -456,17 +457,18 @@ class Plotter(Aggregator, BaseProcessor):
run=run,
**kwargs,
)
# Save in astrophysix format
df = rule.datafile(name, arg)
df[filetype] = plot_filename
if movie:
filenames[run].append(plot_filename)
# Save in astrophysix format
if self.params.astrophysix.generate:
df = rule.datafile(name, arg)
df[filetype] = plot_filename
if plot_info is not None:
df.plot_info = plot_info
if num is not None:
snap = self.snaps[run][num].snapshot
if overwrite and df.name in snap.datafiles:
del snap.datafiles[df.name]
elif df.name not in snap.datafiles:
@@ -474,7 +476,6 @@ class Plotter(Aggregator, BaseProcessor):
if snap not in self.simulations[run].snapshots:
self.simulations[run].snapshots.add(snap)
datafiles.append(df)
if movie:
@@ -857,6 +858,7 @@ class Plotter(Aggregator, BaseProcessor):
plt.xlim(xlim)
plt.ylim(ylim)
if self.params.astrophysics.generate:
return PlotInfo(
plot_type=PlotType.IMAGE,
xaxis_values=np.linspace(im_extent[0], im_extent[1], dmap.shape[0] + 1),
@@ -1201,6 +1203,7 @@ class Plotter(Aggregator, BaseProcessor):
)
# returns PlotInfo (for Galactica)
if self.params.astrophysics.generate:
edges = np.append(centers - width / 2.0, centers[-1] + width / 2.0)
return PlotInfo(
plot_type=PlotType.HISTOGRAM,
@@ -1822,21 +1825,18 @@ class Plotter(Aggregator, BaseProcessor):
def generic_rule(name):
self.rules["slice_" + name] = PlotRule(
self,
partial(self._plot_map, "slice_" + name),
"{} slice".format(name),
dependencies=["slice_" + name],
)
self.rules[name + "_mwavg"] = PlotRule(
self,
partial(self._plot_map, name + "_mwavg"),
"Ax mass-weighted averaged {}".format(name),
dependencies=[name + "_mwavg"],
)
self.rules[name + "_avg"] = PlotRule(
self,
partial(self._plot_map, name + "_avg"),
"Ax averaged {}".format(name),
dependencies=[name + "_avg"],
+3
View File
@@ -390,6 +390,7 @@ class SnapshotProcessor(HDF5Container):
coeff=factor)
time_in_right_unit = self.time * self.info["unit_time"].express(unit_time)
if self.params.astrophysix.generate:
self.snapshot = Snapshot(
name=str(self.num),
description="",
@@ -488,6 +489,8 @@ class SnapshotProcessor(HDF5Container):
self.open()
if "/maps" not in self.save:
self.save.create_group("/", "maps", "2D maps")
if "/datasets" not in self.save:
self.save.create_group("/", "datasets", "Complex datasets")
self.save.root.maps._v_attrs.center = center
self.save.root.maps._v_attrs.radius = self._radius
self.save.root.maps._v_attrs.im_extent = im_extent
+57 -22
View File
@@ -131,7 +131,7 @@ class StudyProcessor(Aggregator, HDF5Container):
super(StudyProcessor, self)._save_data(name_full, data, description, unit)
self.save.get_node(name_full)._v_attrs.nums = self.nums
def _time_series(self, getter, arg=None):
def time_series(self, getter, arg=None):
series = {}
for run in self.runs:
series[run] = []
@@ -140,17 +140,47 @@ class StudyProcessor(Aggregator, HDF5Container):
series[run] = np.array(series[run], dtype=float)
return series
def _compare(self, getter, use_num=True):
prop = []
for i, run in enumerate(self.runs):
def compare(self, getter, use_num=True, select=None):
if select is None:
runs = self.runs
else:
runs, _ = self.selector.select(**select)
prop = {}
for i, run in enumerate(runs):
if use_num:
num = self.nums[run][0]
prop.append(getter(run, num))
prop[run] = getter(run, num)
else:
prop.append(getter(run))
return np.array(prop)
prop[run] = getter(run)
return np.array(list(prop.keys()))
def _time_avg(self, name, start=None, end=None, span=None, group="/series"):
def time_avg(self, name, start=None, end=None, span=None, unit_time=U.Myr, group="/series", select=None):
"""Do the time average and quantiles of a time series
Parameters
----------
name : str
name of the array to average
start : float, optional
The average is taken between start and end or start + span, by default None
end : float, optional
The average is taken between start and end or end - span, by default None
span : _type_, optional
length of the averaging period (overrrided if both start and end are set), by default None
unit_time : _type_, optional
Time unit to use, by default U.Myr
group : str, optional
group of the data to average, by default "/series"
select : dict, optional
arguments to selector, by default None
Returns
-------
dict
time average and quantiles
"""
serie0 = self.save.get_node(group + "/" + name + "/" + self.runs[0]).read()
if len(serie0.shape) > 1:
shape = [len(self.runs)] + list(serie0.shape[1:])
@@ -166,11 +196,16 @@ class StudyProcessor(Aggregator, HDF5Container):
q16 = np.zeros(shape)
q84 = np.zeros(shape)
for i, run in enumerate(self.runs):
serie = self.save.get_node(group + "/" + name + "/" + run).read()
time = self.save.get_node(group + "/time/" + run).read()
if select is None:
runs = self.runs
else:
runs, _ = self.selector.select(**select)
for i, run in enumerate(runs):
serie = self.get_value(group + "/" + name + "/" + run)
time = self.get_value(group + "/time/" + run, unit=unit_time)
if len(serie.shape) <= 1:
mask = abs(serie) != np.inf
mask = np.isfinite(serie)
if not ((start, end, span) == (None, None, None)):
start_r, end_r = start, end
@@ -202,7 +237,7 @@ class StudyProcessor(Aggregator, HDF5Container):
v_max[i],
) = np.percentile(serie, [0, 2.5, 16, 50, 84, 97.5, 100], axis=0)
return {
"runs": self.runs,
"runs": np.array(runs),
"mean": mean,
"std": std,
"median": median,
@@ -591,7 +626,7 @@ class StudyProcessor(Aggregator, HDF5Container):
self.rules[name] = Rule(
partial(
self._time_series,
self.time_series,
partial(
self.get_global, glob_group + "/" + glob_name, unload_cells=True
),
@@ -635,9 +670,9 @@ class StudyProcessor(Aggregator, HDF5Container):
def fn(arg=None, **kwargs):
if arg is None:
return self._time_avg(src_name, group=group_src, **kwargs)
return self.time_avg(src_name, group=group_src, **kwargs)
else:
return self._time_avg(
return self.time_avg(
src_name + "_" + str(arg), group=group_src, **kwargs
)
@@ -790,7 +825,7 @@ class StudyProcessor(Aggregator, HDF5Container):
# Read from outputs
"time": Rule(
partial(
self._time_series, partial(self.get_global, "/globals/time_num")
self.time_series, partial(self.get_global, "/globals/time_num")
),
group="/series",
unit="unit_time",
@@ -798,28 +833,28 @@ class StudyProcessor(Aggregator, HDF5Container):
),
"time_rho_prof": Rule(
partial(
self._time_series, partial(self.get_snap_value, "/profile/rho_prof")
self.time_series, partial(self.get_snap_value, "/profile/rho_prof")
),
group="/series",
dependencies={"time": None, "rho_prof": "__parent__"},
),
"time_coldens_pdf": Rule(
partial(
self._time_series, partial(self.get_snap_value, "/hist/pdf_coldens")
self.time_series, partial(self.get_snap_value, "/hist/pdf_coldens")
),
group="/series",
dependencies={"time": None, "pdf_coldens": "__parent__"},
),
"time_rho_pdf": Rule(
partial(
self._time_series, partial(self.get_snap_value, "/hist/rho_pdf")
self.time_series, partial(self.get_snap_value, "/hist/rho_pdf")
),
group="/series",
dependencies={"time": None},
),
"time_pdf_slope_coldens": Rule(
partial(
self._time_series,
self.time_series,
partial(
self.get_attr,
"slope",
@@ -839,7 +874,7 @@ class StudyProcessor(Aggregator, HDF5Container):
),
# namelist
"nml": Rule(
lambda nml_key: self._compare(
lambda nml_key: self.compare(
partial(self.get_nml, nml_key), use_num=False
),
group="/comp",