black without mortimer
This commit is contained in:
Noe Brucy
+88
-78
@@ -30,7 +30,7 @@ from pymses.analysis import (
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cube3d,
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)
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from pymses.filters import CellsToPoints, RegionFilter
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from pymses.sources.hop.hop import HOP
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from pymses.sources.hop.hop import HOP
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try:
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from fil_finder import FilFinder2D
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@@ -220,9 +220,9 @@ def pspec2d(map2D):
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pmap = pspec.pcube(fmap)
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# Use the power map and the fft to compute the powerspectrum
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# This is typically an histogram of k weighted by the fourier transform value
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pspec, kbins, pspec2, fbins = pspec.pspectrum(pmap, kmap, kbins, 1, 0)
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power, kbins, power2, fbins = pspec.pspectrum(pmap, kmap, kbins, 1, 0)
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# Return bin center and power spectrum
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return 0.5 * (kbins[1:] + kbins[:-1]), pspec
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return 0.5 * (kbins[1:] + kbins[:-1]), power
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def degrade_map(dmap, nnew, integrate=False):
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@@ -387,11 +387,12 @@ class SnapshotProcessor(HDF5Container):
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# Convert time unit
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if isinstance(unit_time, str):
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factor = self.get_nml(unit_time)
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unit_time = U.Unit(
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name=os.path.basename(unit_time),
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base_unit=self.info["unit_time"],
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coeff=factor)
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factor = self.get_nml(unit_time)
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unit_time = U.Unit(
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name=os.path.basename(unit_time),
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base_unit=self.info["unit_time"],
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coeff=factor,
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)
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time_in_right_unit = self.time * self.info["unit_time"].express(unit_time)
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if self.params.astrophysix.generate:
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@@ -405,17 +406,16 @@ class SnapshotProcessor(HDF5Container):
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try:
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self.init_pymses()
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except:
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except IOError:
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self.logger.error("Pymses not initialized", exc_info=1)
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self.def_rules()
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def init_pymses(self):
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# If ratarmount was used
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if os.path.exists(f"{self.path}/output_{self.num:05}/output_{self.num:05}"):
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path = f"{self.path}/output_{self.num:05}"
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else:
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else:
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path = self.path
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self._ro = pymses.RamsesOutput(
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path,
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@@ -494,21 +494,21 @@ class SnapshotProcessor(HDF5Container):
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far_cut_depth=distance,
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up_vector=ax_v,
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map_max_size=self.params.pymses.map_size,
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)
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)
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# Initialize HDF5 group
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try:
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self.open()
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if "/maps" not in self.save:
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self.save.create_group("/", "maps", "2D maps")
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self.save.root.maps._v_attrs.center = center
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self.save.root.maps._v_attrs.radius = self._radius
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self.save.root.maps._v_attrs.im_extent = im_extent
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except:
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self.logger.error("Error in HDF5", exc_info=1)
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raise
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finally:
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self.close()
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try:
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self.open()
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if "/maps" not in self.save:
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self.save.create_group("/", "maps", "2D maps")
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self.save.root.maps._v_attrs.center = center
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self.save.root.maps._v_attrs.radius = self._radius
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self.save.root.maps._v_attrs.im_extent = im_extent
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except Exception() as e:
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self.logger.error("Error in HDF5", exc_info=1)
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raise e
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finally:
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self.close()
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def load_data(self, points_src, filename, save, keys=None):
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"""
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@@ -613,13 +613,13 @@ class SnapshotProcessor(HDF5Container):
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return pos
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def getter_vect_r(self, dset, name_vect):
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""" Radial component of a vector """
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"""Radial component of a vector"""
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r = self.getter_pos_disk(dset)[:, :2]
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ur = np.transpose((np.transpose(r) / np.sqrt(np.sum(r ** 2, axis=1))))
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return np.einsum("ij, ij -> i", dset[name_vect][:, :2], ur)
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def getter_vect_phi(self, dset, name_vect):
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""" Azimuthal component of a vector """
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"""Azimuthal component of a vector"""
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r = self.getter_pos_disk(dset)[:, :2]
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r_norm = np.sqrt(np.sum(r ** 2, axis=1))
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@@ -638,7 +638,7 @@ class SnapshotProcessor(HDF5Container):
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return pos
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def oct_getter_vect_r(self, dset, name_vect):
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""" Radial component of a vector """
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"""Radial component of a vector"""
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r = self.oct_getter_pos_disk(dset)[:, :, :2]
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ur = np.transpose(
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(np.transpose(r, (2, 0, 1)) / np.sqrt(np.sum(r ** 2, axis=2))), (1, 2, 0)
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@@ -646,7 +646,7 @@ class SnapshotProcessor(HDF5Container):
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return np.einsum("ikj, ikj -> ik", dset[name_vect][:, :, :2], ur)
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def oct_getter_vect_phi(self, dset, name_vect):
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""" Azimuthal component of a vector """
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"""Azimuthal component of a vector"""
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r = self.oct_getter_pos_disk(dset)[:, :, :2]
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r_norm = np.sqrt(np.sum(r ** 2, axis=2))
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@@ -660,7 +660,7 @@ class SnapshotProcessor(HDF5Container):
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return self.oct_getter_vect_r(dset, "vel")
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def oct_getter_vphi(self, dset):
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""" Azimuthal velocity """
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"""Azimuthal velocity"""
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return self.oct_getter_vect_phi(dset, "vel")
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def datacube(self, getter, level=None, unit=U.none):
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@@ -685,22 +685,19 @@ class SnapshotProcessor(HDF5Container):
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if level is None:
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level = self.get_nml("amr_params/levelmin")
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size = 1.0
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cam = Camera(
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center=self.params.pymses.center,
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line_of_sight_axis="z",
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region_size=[size, size],
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distance=size / 2.0,
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far_cut_depth=size / 2.0,
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up_vector="y",
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map_max_size=2 ** level,
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)
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center=self.params.pymses.center,
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line_of_sight_axis="z",
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region_size=[size, size],
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distance=size / 2.0,
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far_cut_depth=size / 2.0,
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up_vector="y",
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map_max_size=2 ** level,
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)
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cube = extractor.process(
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cam, cube_size=1.0, resolution=2 ** level
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).data
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cube = extractor.process(cam, cube_size=1.0, resolution=2 ** level).data
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return cube
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def slice(self, getter, ax_los="z", z=0.0, unit=U.none):
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@@ -731,8 +728,9 @@ class SnapshotProcessor(HDF5Container):
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datamap = slicing.SliceMap(self._amr, self._cam[ax_los], op, z=z)
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return datamap.map.T
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def ax_avg(self, oct_getter, ax_los, unit=U.none, mass_weighted=True, surf_qty=False):
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def ax_avg(
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self, oct_getter, ax_los, unit=U.none, mass_weighted=True, surf_qty=False
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):
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"""
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Map of the average of a quantity (given by getter) along an axis (ax_los)
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Returns 2D array if getter returns a scalar quantity
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@@ -847,7 +845,15 @@ class SnapshotProcessor(HDF5Container):
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self.unload_cells()
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return data
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def vol_pdf(self, getter, bins=100, old_unit=None, unit=None, logbins=False, weight_func=vol_func):
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def vol_pdf(
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self,
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getter,
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bins=100,
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old_unit=None,
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unit=None,
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logbins=False,
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weight_func=vol_func,
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):
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self.load_cells()
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data = getter(self.cells)
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if old_unit is not None and unit is not None:
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@@ -1057,7 +1063,9 @@ class SnapshotProcessor(HDF5Container):
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dmap_omega = rt_omega.process(self._cam[ax_los]).map.T
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return dmap_omega
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def _toomreQ_disk(self, ax_los, omega_approx=False, G1_units=False, coarsen_factor=1):
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def _toomreQ_disk(
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self, ax_los, omega_approx=False, G1_units=False, coarsen_factor=1
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):
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"""
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Compute the Toomre Q parameter
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"""
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@@ -1404,8 +1412,8 @@ class SnapshotProcessor(HDF5Container):
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def _sinks(self):
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csv_name = f"{self.path}/output_{self.num:05}/sink_{self.num:05}.csv"
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if not os.path.exists(csv_name): # If ratarmount was used
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csv_name = f"{self.path}/output_{self.num:05}/output_{self.num:05}/sink_{self.num:05}.csv"
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if not os.path.exists(csv_name): # If ratarmount was used
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csv_name = f"{self.path}/output_{self.num:05}/output_{self.num:05}/sink_{self.num:05}.csv"
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f = open(csv_name)
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first_line = f.readline()
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@@ -1449,11 +1457,9 @@ class SnapshotProcessor(HDF5Container):
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def pspec(self, overwrite_file=False, **kwargs):
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outfile = self.pspec_filename
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if overwrite_file or not os.path.exists(self.pspec_filename):
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pspec.pspec(repo=self.path, iouts=[self.num], outfile=outfile, **kwargs)
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pspec.pspec(repo=self.path, iouts=[self.num], outfile=outfile, **kwargs)
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return np.array([self.pspec_filename])
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def _write_particles(self):
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"""Ensure particles are written in the hdf5 file"""
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if not os.path.exists(self.parts_filename) and not self.parts_loaded:
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@@ -1604,50 +1610,57 @@ class SnapshotProcessor(HDF5Container):
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"""
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# Selection of cells
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mask = self.cells["rho"] * self.info["unit_density"].express(U.H_cc) > threshold_density
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mask = (
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self.cells["rho"] * self.info["unit_density"].express(U.H_cc)
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> threshold_density
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)
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ncells = np.sum(mask)
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# fill the matrice with ID, x,y,z and masses of particles
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cells_group = np.zeros((ncells, 6))
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cells_group[:,0] = np.arange(ncells) # index
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position = self.cells["pos"][mask] * self.info["unit_length"].express(U.pc)
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cells_group[:,1:4] = position # position
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density = self.cells["rho"][mask] * self.info["unit_density"].express(U.Msun / U.pc**3)
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size = self.cells["dx"][mask]*self.info["unit_length"].express(U.pc)
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cells_group[:,4] = density * size**3 # mass
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cells_group[:, 0] = np.arange(ncells) # index
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position = self.cells["pos"][mask] * self.info["unit_length"].express(U.pc)
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cells_group[:, 1:4] = position # position
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density = self.cells["rho"][mask] * self.info["unit_density"].express(
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U.Msun / U.pc ** 3
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)
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size = self.cells["dx"][mask] * self.info["unit_length"].express(U.pc)
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cells_group[:, 4] = density * size ** 3 # mass
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# save file.txt
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head = str(ncells)
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np.savetxt(
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self.filename[:-3] + '_hop.txt',
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self.filename[:-3] + "_hop.txt",
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cells_group[:, :-1],
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fmt='%10d %.10e %.10e %.10e %.10e',
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fmt="%10d %.10e %.10e %.10e %.10e",
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header=head,
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delimiter=' ',
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comments=' '
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)
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delimiter=" ",
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comments=" ",
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)
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# save file.den
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f = open(self.filename[:-3] + '_hop.den','wb')
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f.write(pack('I', ncells))
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f = open(self.filename[:-3] + "_hop.den", "wb")
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f.write(pack("I", ncells))
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self.cells["rho"][mask].astype("f").tofile(f)
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f.close()
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# exec HOP algo
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h = HOP(self.filename[:-3] + '_hop.txt', os.path.dirname(self.filename))
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h.process_hop()
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h = HOP(self.filename[:-3] + "_hop.txt", os.path.dirname(self.filename))
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h.process_hop()
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# get the igroup array
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group_ids = h.get_group_ids()
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# sort it and apply the sorting to the coordinates
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# this means that the particules of group 1 are written first then of group 2 etc...
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# this means that the particules of group 1 are written first then of group 2 etc...
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ind_sort = np.argsort(group_ids)
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cells_group = cells_group[ind_sort]
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cells_group[6] = group_ids[ind_sort]
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# Make it a pandas' DataFrame
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cells_group = pd.DataFrame(cells_group, header=["id", "x", "y", "z", "mass", "group"])
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cells_group = pd.DataFrame(
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cells_group, header=["id", "x", "y", "z", "mass", "group"]
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)
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self.clumps = cells_group
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@@ -1658,7 +1671,6 @@ class SnapshotProcessor(HDF5Container):
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cells_group = self.make_clump_hop()
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cells_group.groupby("group")
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def def_rules(self):
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self.rules = {
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@@ -1714,8 +1726,7 @@ class SnapshotProcessor(HDF5Container):
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dependencies=["slice_rho"],
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unit=self.info["unit_pressure"] / self.info["unit_density"],
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),
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"levels": Rule(self._levels, "Max level within line of sight", "/maps"
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),
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"levels": Rule(self._levels, "Max level within line of sight", "/maps"),
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"jeans": Rule(
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self._jeans,
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"Jeans length slice",
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@@ -1769,8 +1780,7 @@ class SnapshotProcessor(HDF5Container):
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},
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),
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"pspec": Rule(self.pspec, "Power spectrum", "/hdf5"),
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"write_particles": Rule(self._write_particles, "Particles file", "/hdf5"
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),
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"write_particles": Rule(self._write_particles, "Particles file", "/hdf5"),
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"write_cells": Rule(self._write_cells, "Cells file", "/hdf5"),
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"filaments": Rule(
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self._filaments,
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@@ -1986,8 +1996,10 @@ class SnapshotProcessor(HDF5Container):
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# Norm
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generic_rule(
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field + "_norm", partial(norm_getter, field), self.unit_key[field],
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oct_getter=partial(oct_norm_getter, field)
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field + "_norm",
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partial(norm_getter, field),
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self.unit_key[field],
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oct_getter=partial(oct_norm_getter, field),
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)
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else:
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@@ -1998,8 +2010,6 @@ class SnapshotProcessor(HDF5Container):
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unit = self.rules[name].unit
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self.rules["rad_avg_" + name] = Rule(
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partial(self._rad_avg, name),
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"Azimuthal average of {}".format(name),
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Reference in New Issue
Block a user