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replacing the example / recipes with a tutorial page and improvements #148
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replacing the example / recipes with a tutorial page and improvements #148
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andrewtarzia
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Looking very good!
Co-authored-by: Andrew Tarzia <andrew.tarzia@gmail.com>
Co-authored-by: Andrew Tarzia <andrew.tarzia@gmail.com>
Co-authored-by: Andrew Tarzia <andrew.tarzia@gmail.com>
Co-authored-by: Andrew Tarzia <andrew.tarzia@gmail.com>
Co-authored-by: Andrew Tarzia <andrew.tarzia@gmail.com>
Co-authored-by: Andrew Tarzia <andrew.tarzia@gmail.com>
Co-authored-by: Andrew Tarzia <andrew.tarzia@gmail.com>
| streamline the analysis of many-body trajectories, offering a consistent and | ||
| user-friendly interface across most analysis tasks. | ||
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| This is achieved through the classe, :class:`.trajectory.Trj`, which corresponds to an |
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"class" invece di "classe"
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ops..
matteobecchi
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Very nice! Definitely better organized than before.
| Now the ``trj`` variable contains the trajectory, and using the methods of the | ||
| :class:`.trajectory.Trj` class we can perform all the dynsight analyses on | ||
| this trajectory. For instance, let's say we want to compute the LENS | ||
| descriptor (`published paper <https://doi.org/10.1073/pnas.2300565120>`__). |
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Since in the nex tutorial TimeSOAP is cited as Caruso et al., here it is better to cite lens as "Crippa et al." and not as "published paper"
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| The :class:`.trajectory.Insight` objects can directly be used to perform post-processing such as smoothing (see the other `tutorials pages <../tutorials_menu.html>`_). | ||
| But they can also be used to perform clustering analysis. In this example, we will show how to use the | ||
| ``Onion Clustering`` method (`published paper <https://doi.org/10.1073/pnas.2403771121>`__) to cluster the LENS values computed above. |
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Also here, cite it as Becchi et al.
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| In this tutorial, we will show you the effect of noise reduction by using | ||
| the spatial denoising algorithm implemented in ``dynsight`` (Related paper: `Donkor et al. <https://doi.org/10.1021/acs.jpclett.4c00383>`__, `Martino et al. <https://doi.org/10.1088/2632-2153/adfa66>`__). | ||
| We will also explain a new application of the Onion Clustering algorithm to explore different time resolutions for the classification (:class:`.trajectory.Insight.get_onion_analysis()`). |
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maybe is not "a new application of Onion Clustering", but "another application of Onion Clustering"
ChiaraLionello
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I think now they are very clear and I like how they are organized. Good job!
andrewtarzia
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Looks good! Some comments still to do, and we discussed using doctests in the examples still.
| topo_file=files_path / "ice_water_ox.gro", | ||
| ) | ||
| In this tutorial, we will use the descriptor ``TimeSOAP`` ( `Caruso et al. <https://doi.org/10.1063/5.0147025>`__). |
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remove space before Caruso
| time window the one that corresponds to the highest number of clusters and longest ``delta_t`` (in this case, ``delta_t=37`` frames). | ||
| This choice should guarantee that the clusters identified are stable for longer time. | ||
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| .. code-block:: python |
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Use the same "new line" or "one line" formatting for all, this looks messy
| _, tsoap = trj.get_timesoap( | ||
| soap_insight=soap, | ||
| ) | ||
| """ |
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remove this comment, in my opinion
| n_jobs=4, # Adjust n_jobs according to your computer capabilities | ||
| ) | ||
| the ``soap`` variable is a :class:`.trajectory.Insight` object that contains the computed ``SOAP`` spectra. |
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The*
| examples/info_gain/trj_*.npy | ||
| tests/systems/coex/.* | ||
| tests/systems/.* | ||
| .DS_Store |
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just delete these off your computer?
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It's macOS; every mac user will have this annoying and useless DS_Store. I would ignore it.
If it's a problem, i'll remove that line
hi all;
Just revising the example creating step by step tutorial (GROMACS style)
not finish yet but at least you can have a look.
PS -> there is the possbility to find some "flying" files here and there; don't worry i will clean everything.