Skip to main content
zenodoopen

Brightness data in Rayleigh for OI 630.0 nm (red line) and OI 557.7 (green line) through the night of August 21-22, 2017 obtained using the HiT&MIS from Carbondale, IL

<p>This file contains brightness data in Rayleigh&nbsp;for OI 630.0 nm (red line), OI 557.7 (green line) and NeI 630.5 nm (cloud indicator) through the night of August 21-22, 2017&nbsp;obtained using the HiT&amp;MIS from Carbondale, IL.</p> <p>This is a python .npz file that contain numpy arrays with uncertainities, so you would need the uncertainties as well as the numpy modules for python.</p> <p>On python it can be opened up as follows:</p> <p>import numpy as np</p> <p>import uncertainties.unumpy as unp</p> <p>dload=np.load(&quot;&lt;file location&gt;/eclipse_night_final.npz&quot;)#brightnesses are saved as numpy array files<br> int630=dload[&quot;int630&quot;] #630 nm red line brightness<br> int557=dload[&quot;int557&quot;] #557.7 nm green line brightness<br> int6305=dload[&quot;int6305&quot;]# Ne I 630.5 nm brightness for cloud activity<br> time=dload[&quot;time&quot;] #capture times (Local times, Central Daylight time)</p> <p># uncertainities can be accessed as</p> <p>b630value=unp.nominal_values(int630) # 630 nm brightnesses values</p> <p>e630=unp.std_devs(int630)# 630 nm uncertainities.</p> <p>&nbsp;</p> <p>please email me at saurav_aryal@student.uml.edu if you have any questions.</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

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

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

Topics