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Quijote snapshots support (#77)
* Renaming * Edit docs * Delete old function * Add a blank space * Rename particle reader * Add comments * Rename * Rename * edit get_snapshots * More renaming * Remove old correction * Add import * Add basics of the Quijote reader * Add a blank space * Fix paths * Rename function * Fix HID and path * Add more FoF reading * Move definition * Adding arguments * Renaming * Add kwargs for backward comp * FoF Quijote return only hids * Add sorting of quijote * Add path to CSiBORG ICs snapshot * Add support for Quijote * initmatch paths for quijote * Add kwargs * Fix blank lines * Rename kwarg * Remove unused import * Remove hardcoded numbers * Update for Quijote * Do not store velocities in QUijote ICs * Box units mass Quijote * Fix typo * Ensure particles are not right at the edge * Add structfit paths for QUuijote * Basic CSiBORG units * Add more quijote halo reading * Add Quijote fitting * Docs changes * Docs changes
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18 changed files with 800 additions and 300 deletions
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@ -352,7 +352,7 @@ def plot_projected_field(kind, nsim, grid, in_rsp, smooth_scale, MAS="PCS",
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"""
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print(f"Plotting projected field `{kind}`. ", flush=True)
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paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
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nsnap = max(paths.get_snapshots(nsim))
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nsnap = max(paths.get_snapshots(nsim, "csiborg"))
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box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths)
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if kind == "overdensity":
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@ -563,10 +563,10 @@ def plot_sky_distribution(field, nsim, grid, nside, smooth_scale=None,
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Whether to save the figure as a pdf.
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"""
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paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
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nsnap = max(paths.get_snapshots(nsim))
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nsnap = max(paths.get_snapshots(nsim, "csiborg"))
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box = csiborgtools.read.CSiBORGBox(nsnap, nsim, paths)
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if kind == "overdensity":
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if field== "overdensity":
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field = load_field("density", nsim, grid, MAS=MAS, in_rsp=False,
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smooth_scale=smooth_scale)
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density_gen = csiborgtools.field.DensityField(box, MAS)
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@ -658,7 +658,8 @@ if __name__ == "__main__":
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if False:
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paths = csiborgtools.read.Paths(**csiborgtools.paths_glamdring)
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d = csiborgtools.read.read_h5(paths.particles(7444))["particles"]
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d = csiborgtools.read.read_h5(paths.particles(7444, "csiborg"))
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d = d["particles"]
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plt.figure()
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plt.hist(d[:100000, 4], bins="auto")
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