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PyGEDM pre-computed maps of Galactic electron density models

<p>Pre-computed HDF5 data cubes for <a href="https://github.com/FRBs/pygedm">PyGEDM</a> web app.</p> <p>Datasets in HDF5 file:</p> <p>Dimension scales distance (pc), DM (pc/cm3), galactic latitude and galactic longitude (deg).</p> <pre>[(&#39;dist&#39;, &lt;HDF5 dataset &quot;dist&quot;: shape (10,), type &quot;&lt;i8&quot;&gt;), (&#39;dm&#39;, &lt;HDF5 dataset &quot;dm&quot;: shape (12,), type &quot;&lt;i8&quot;&gt;), (&#39;gb&#39;, &lt;HDF5 dataset &quot;gb&quot;: shape (361,), type &quot;&lt;f8&quot;&gt;), (&#39;gl&#39;, &lt;HDF5 dataset &quot;gl&quot;: shape (721,), type &quot;&lt;f8&quot;&gt;), gl = np.linspace(-180, 180, 360*2+1) gb = np.linspace(-90, 90, 180*2+1) dist = np.array((0.1, 0.2, 0.5, 1, 2, 5, 8.5, 10, 20, 50)) dm&nbsp;&nbsp; = np.array((1, 2, 5, 10, 20, 50, 100, 200, 500, 1000, 2000, 5000)) Galactocentric coordinates XYZ (pc): (&#39;x&#39;, &lt;HDF5 dataset &quot;x&quot;: shape (100,), type &quot;&lt;i8&quot;&gt;), (&#39;y&#39;, &lt;HDF5 dataset &quot;y&quot;: shape (100,), type &quot;&lt;i8&quot;&gt;), (&#39;z&#39;, &lt;HDF5 dataset &quot;z&quot;: shape (100,), type &quot;&lt;i8&quot;&gt;)]</pre> <p>NE2001 model precomputed datasets:</p> <pre> (&#39;ne2001&#39;, &lt;HDF5 group &quot;/ne2001&quot; (5 members)&gt;),</pre> <pre>[(&#39;ddm&#39;, &lt;HDF5 dataset &quot;ddm&quot;: shape (12, 361, 721), type &quot;&lt;f8&quot;&gt;), (&#39;ddm_tau&#39;, &lt;HDF5 dataset &quot;ddm_tau&quot;: shape (12, 361, 721), type &quot;&lt;f8&quot;&gt;), (&#39;dmd&#39;, &lt;HDF5 dataset &quot;dmd&quot;: shape (10, 361, 721), type &quot;&lt;f8&quot;&gt;), (&#39;dmd_tau&#39;, &lt;HDF5 dataset &quot;dmd_tau&quot;: shape (10, 361, 721), type &quot;&lt;f8&quot;&gt;), (&#39;xyz&#39;, &lt;HDF5 dataset &quot;xyz&quot;: shape (100, 100, 100), type &quot;&lt;f8&quot;&gt;)] YMW16 precomputed datasets: (&#39;ymw16&#39;, &lt;HDF5 group &quot;/ymw16&quot; (5 members)&gt;),</pre> <pre>[(&#39;ddm&#39;, &lt;HDF5 dataset &quot;ddm&quot;: shape (12, 361, 721), type &quot;&lt;f8&quot;&gt;), (&#39;ddm_tau&#39;, &lt;HDF5 dataset &quot;ddm_tau&quot;: shape (12, 361, 721), type &quot;&lt;f8&quot;&gt;), (&#39;dmd&#39;, &lt;HDF5 dataset &quot;dmd&quot;: shape (10, 361, 721), type &quot;&lt;f8&quot;&gt;), (&#39;dmd_tau&#39;, &lt;HDF5 dataset &quot;dmd_tau&quot;: shape (10, 361, 721), type &quot;&lt;f8&quot;&gt;), (&#39;xyz&#39;, &lt;HDF5 dataset &quot;xyz&quot;: shape (100, 100, 100), type &quot;&lt;f8&quot;&gt;)]</pre>

ShareScore

32/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

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