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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
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ismfeed.py
+1 -1
View File
@@ -1,6 +1,6 @@
from scipy.integrate import solve_ivp from scipy.integrate import solve_ivp
from plotter import U from plotter import U
import select_runs import select_snapshot
import numpy as np import numpy as np
import pandas as pd import pandas as pd
plotter.py
+48 -48
View File
@@ -280,7 +280,8 @@ class Plotter(Aggregator, BaseProcessor):
self.def_rules() self.def_rules()
# Generate astrophysix's simulations object # Generate astrophysix's simulations object
self.gen_simus() if self.params.astrophysix.generate:
self.gen_simus()
# Initialize pointers # Initialize pointers
self.current_processor = None self.current_processor = None
@@ -456,26 +457,26 @@ class Plotter(Aggregator, BaseProcessor):
run=run, run=run,
**kwargs, **kwargs,
) )
# Save in astrophysix format
df = rule.datafile(name, arg)
df[filetype] = plot_filename
if movie: if movie:
filenames[run].append(plot_filename) filenames[run].append(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: # Save in astrophysix format
del snap.datafiles[df.name] if self.params.astrophysix.generate:
elif df.name not in snap.datafiles: df = rule.datafile(name, arg)
snap.datafiles.add(df) df[filetype] = plot_filename
if snap not in self.simulations[run].snapshots: if plot_info is not None:
self.simulations[run].snapshots.add(snap) 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:
snap.datafiles.add(df)
datafiles.append(df) if snap not in self.simulations[run].snapshots:
self.simulations[run].snapshots.add(snap)
datafiles.append(df)
if movie: if movie:
for run in runs: for run in runs:
@@ -857,22 +858,23 @@ class Plotter(Aggregator, BaseProcessor):
plt.xlim(xlim) plt.xlim(xlim)
plt.ylim(ylim) plt.ylim(ylim)
return PlotInfo( if self.params.astrophysics.generate:
plot_type=PlotType.IMAGE, return PlotInfo(
xaxis_values=np.linspace(im_extent[0], im_extent[1], dmap.shape[0] + 1), plot_type=PlotType.IMAGE,
yaxis_values=np.linspace(im_extent[2], im_extent[3], dmap.shape[1] + 1), xaxis_values=np.linspace(im_extent[0], im_extent[1], dmap.shape[0] + 1),
values=dmap, yaxis_values=np.linspace(im_extent[2], im_extent[3], dmap.shape[1] + 1),
xaxis_log_scale=False, values=dmap,
yaxis_log_scale=False, xaxis_log_scale=False,
values_log_scale=False, yaxis_log_scale=False,
xaxis_label=xlabel, values_log_scale=False,
yaxis_label=ylabel, xaxis_label=xlabel,
values_label=label, yaxis_label=ylabel,
xaxis_unit=unit_space, values_label=label,
yaxis_unit=unit_space, xaxis_unit=unit_space,
values_unit=unit, yaxis_unit=unit_space,
plot_title=title, values_unit=unit,
) plot_title=title,
)
def _overlay_contour( def _overlay_contour(
self, self,
@@ -1201,19 +1203,20 @@ class Plotter(Aggregator, BaseProcessor):
) )
# returns PlotInfo (for Galactica) # returns PlotInfo (for Galactica)
edges = np.append(centers - width / 2.0, centers[-1] + width / 2.0) if self.params.astrophysics.generate:
return PlotInfo( edges = np.append(centers - width / 2.0, centers[-1] + width / 2.0)
plot_type=PlotType.HISTOGRAM, return PlotInfo(
xaxis_values=edges, plot_type=PlotType.HISTOGRAM,
yaxis_values=values, xaxis_values=edges,
xaxis_log_scale=False, yaxis_values=values,
yaxis_log_scale=ylog, xaxis_log_scale=False,
xaxis_label=xlabel, yaxis_log_scale=ylog,
yaxis_label=ylabel, xaxis_label=xlabel,
xaxis_unit=unit, yaxis_label=ylabel,
yaxis_unit=U.none, xaxis_unit=unit,
plot_title=title, yaxis_unit=U.none,
) plot_title=title,
)
def _plot( def _plot(
self, self,
@@ -1822,21 +1825,18 @@ class Plotter(Aggregator, BaseProcessor):
def generic_rule(name): def generic_rule(name):
self.rules["slice_" + name] = PlotRule( self.rules["slice_" + name] = PlotRule(
self,
partial(self._plot_map, "slice_" + name), partial(self._plot_map, "slice_" + name),
"{} slice".format(name), "{} slice".format(name),
dependencies=["slice_" + name], dependencies=["slice_" + name],
) )
self.rules[name + "_mwavg"] = PlotRule( self.rules[name + "_mwavg"] = PlotRule(
self,
partial(self._plot_map, name + "_mwavg"), partial(self._plot_map, name + "_mwavg"),
"Ax mass-weighted averaged {}".format(name), "Ax mass-weighted averaged {}".format(name),
dependencies=[name + "_mwavg"], dependencies=[name + "_mwavg"],
) )
self.rules[name + "_avg"] = PlotRule( self.rules[name + "_avg"] = PlotRule(
self,
partial(self._plot_map, name + "_avg"), partial(self._plot_map, name + "_avg"),
"Ax averaged {}".format(name), "Ax averaged {}".format(name),
dependencies=[name + "_avg"], dependencies=[name + "_avg"],
snapshotprocessor.py
+10 -7
View File
@@ -390,13 +390,14 @@ class SnapshotProcessor(HDF5Container):
coeff=factor) coeff=factor)
time_in_right_unit = self.time * self.info["unit_time"].express(unit_time) time_in_right_unit = self.time * self.info["unit_time"].express(unit_time)
self.snapshot = Snapshot( if self.params.astrophysix.generate:
name=str(self.num), self.snapshot = Snapshot(
description="", name=str(self.num),
time=(time_in_right_unit, unit_time), description="",
directory_path=self.path, time=(time_in_right_unit, unit_time),
data_reference="OUTPUT_{}".format(self.num), directory_path=self.path,
) data_reference="OUTPUT_{}".format(self.num),
)
try: try:
self.init_pymses() self.init_pymses()
@@ -488,6 +489,8 @@ class SnapshotProcessor(HDF5Container):
self.open() self.open()
if "/maps" not in self.save: if "/maps" not in self.save:
self.save.create_group("/", "maps", "2D maps") 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.center = center
self.save.root.maps._v_attrs.radius = self._radius self.save.root.maps._v_attrs.radius = self._radius
self.save.root.maps._v_attrs.im_extent = im_extent self.save.root.maps._v_attrs.im_extent = im_extent
studyprocessor.py
+57 -22
View File
@@ -131,7 +131,7 @@ class StudyProcessor(Aggregator, HDF5Container):
super(StudyProcessor, self)._save_data(name_full, data, description, unit) super(StudyProcessor, self)._save_data(name_full, data, description, unit)
self.save.get_node(name_full)._v_attrs.nums = self.nums 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 = {} series = {}
for run in self.runs: for run in self.runs:
series[run] = [] series[run] = []
@@ -140,17 +140,47 @@ class StudyProcessor(Aggregator, HDF5Container):
series[run] = np.array(series[run], dtype=float) series[run] = np.array(series[run], dtype=float)
return series return series
def _compare(self, getter, use_num=True): def compare(self, getter, use_num=True, select=None):
prop = []
for i, run in enumerate(self.runs): if select is None:
runs = self.runs
else:
runs, _ = self.selector.select(**select)
prop = {}
for i, run in enumerate(runs):
if use_num: if use_num:
num = self.nums[run][0] num = self.nums[run][0]
prop.append(getter(run, num)) prop[run] = getter(run, num)
else: else:
prop.append(getter(run)) prop[run] = getter(run)
return np.array(prop) 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() serie0 = self.save.get_node(group + "/" + name + "/" + self.runs[0]).read()
if len(serie0.shape) > 1: if len(serie0.shape) > 1:
shape = [len(self.runs)] + list(serie0.shape[1:]) shape = [len(self.runs)] + list(serie0.shape[1:])
@@ -166,11 +196,16 @@ class StudyProcessor(Aggregator, HDF5Container):
q16 = np.zeros(shape) q16 = np.zeros(shape)
q84 = np.zeros(shape) q84 = np.zeros(shape)
for i, run in enumerate(self.runs): if select is None:
serie = self.save.get_node(group + "/" + name + "/" + run).read() runs = self.runs
time = self.save.get_node(group + "/time/" + run).read() 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: if len(serie.shape) <= 1:
mask = abs(serie) != np.inf mask = np.isfinite(serie)
if not ((start, end, span) == (None, None, None)): if not ((start, end, span) == (None, None, None)):
start_r, end_r = start, end start_r, end_r = start, end
@@ -202,7 +237,7 @@ class StudyProcessor(Aggregator, HDF5Container):
v_max[i], v_max[i],
) = np.percentile(serie, [0, 2.5, 16, 50, 84, 97.5, 100], axis=0) ) = np.percentile(serie, [0, 2.5, 16, 50, 84, 97.5, 100], axis=0)
return { return {
"runs": self.runs, "runs": np.array(runs),
"mean": mean, "mean": mean,
"std": std, "std": std,
"median": median, "median": median,
@@ -591,7 +626,7 @@ class StudyProcessor(Aggregator, HDF5Container):
self.rules[name] = Rule( self.rules[name] = Rule(
partial( partial(
self._time_series, self.time_series,
partial( partial(
self.get_global, glob_group + "/" + glob_name, unload_cells=True self.get_global, glob_group + "/" + glob_name, unload_cells=True
), ),
@@ -635,9 +670,9 @@ class StudyProcessor(Aggregator, HDF5Container):
def fn(arg=None, **kwargs): def fn(arg=None, **kwargs):
if arg is None: 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: else:
return self._time_avg( return self.time_avg(
src_name + "_" + str(arg), group=group_src, **kwargs src_name + "_" + str(arg), group=group_src, **kwargs
) )
@@ -790,7 +825,7 @@ class StudyProcessor(Aggregator, HDF5Container):
# Read from outputs # Read from outputs
"time": Rule( "time": Rule(
partial( partial(
self._time_series, partial(self.get_global, "/globals/time_num") self.time_series, partial(self.get_global, "/globals/time_num")
), ),
group="/series", group="/series",
unit="unit_time", unit="unit_time",
@@ -798,28 +833,28 @@ class StudyProcessor(Aggregator, HDF5Container):
), ),
"time_rho_prof": Rule( "time_rho_prof": Rule(
partial( 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", group="/series",
dependencies={"time": None, "rho_prof": "__parent__"}, dependencies={"time": None, "rho_prof": "__parent__"},
), ),
"time_coldens_pdf": Rule( "time_coldens_pdf": Rule(
partial( 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", group="/series",
dependencies={"time": None, "pdf_coldens": "__parent__"}, dependencies={"time": None, "pdf_coldens": "__parent__"},
), ),
"time_rho_pdf": Rule( "time_rho_pdf": Rule(
partial( 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", group="/series",
dependencies={"time": None}, dependencies={"time": None},
), ),
"time_pdf_slope_coldens": Rule( "time_pdf_slope_coldens": Rule(
partial( partial(
self._time_series, self.time_series,
partial( partial(
self.get_attr, self.get_attr,
"slope", "slope",
@@ -839,7 +874,7 @@ class StudyProcessor(Aggregator, HDF5Container):
), ),
# namelist # namelist
"nml": Rule( "nml": Rule(
lambda nml_key: self._compare( lambda nml_key: self.compare(
partial(self.get_nml, nml_key), use_num=False partial(self.get_nml, nml_key), use_num=False
), ),
group="/comp", group="/comp",