tag:blogger.com,1999:blog-58674002024-03-14T05:49:19.497+11:00Journey's End“A man's reach should exceed his grasp, or what's heaven for” — Robert BrowningStevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comBlogger524125tag:blogger.com,1999:blog-5867400.post-238287959492165342024-01-23T11:00:00.017+11:002024-01-23T23:11:51.839+11:00Estimating a Supernova's Brightness as an Amateur<h1 id="introduction">Introduction</h1>
<p>2023rve is the designation given to a Type II supernova discovered on 2023-09-08 by Mohammad Odeh from UAE. It appears to be part of NGC 1097, a galaxy 45 million light years away. Due to it’s brightness, 2023rve was visible to budget amateur astronomers/astrophotographers like myself.</p>
<p>Below is my first image of 2023rve.</p>
<p><a href="https://www.flickr.com/photos/sentientintelligence/53197562319/" title="2023rve"><img src="https://live.staticflickr.com/65535/53197562319_50421e7b71_c.jpg" width="600" alt="2023rve"></a></p>
<p>This is a stacked image consisting of 64x60s exposures captured using an unmodified Canon 800D attached to an Evostar 72ED. I was and continue to be very excited about this image because supernovas occur but rarely and are generally out of reach for budget setups like mine. Catching glimpse of one is not unlike seeing an unicorn.</p>
<h1 id="light-curves">Light Curves</h1>
<p>2023rve is a <a href="https://en.wikipedia.org/wiki/Supernova#Type_II">type II supernova</a>, and its light curve will look like one of the following depending on its subclassification (II-P, II-L, IIn or IIb).</p>
<p><img src="https://upload.wikimedia.org/wikipedia/commons/thumb/e/e0/Comparative_supernova_type_light_curves.png/640px-Comparative_supernova_type_light_curves.png" alt="Type II-P and type II-L supernova lightcurves"></p>
<p>It occurred to me then that with sufficient images I can have a go at generating such a light curve and figure out what kind of supernova 2023rve is! This is a particular exciting idea to me because it takes supernovas from the realm of theory (knowing about them) into reality (studying them).</p>
<p>In the time since then, I managed 4 captures in total, including the one above, and this post documents my efforts in estimating the magnitude of 2023rve from my data and using that to construct a light curve.</p>
<h1 id="general-approach">General Approach</h1>
<p>The idea is to calibrate my data, which are 60 second exposures of 2023rve, against stars of known visual magnitude. By comparing the pixel values that make up 2023rve vs these calibration stars, I can estimate its apparent visual magnitude. Then, making the assumption 2023rve is part of NGC1097, we can use the distance to NGC1097 to calculate the absolute magnitude of 2023rve and generate a light curve.</p>
<h1 id="identifying-stars">Identifying Stars</h1>
<p>The first step is to find stars and their known magnitudes. While bright stars such as Rigel or Sirius have well known magnitudes, the stars in the vicinity of NGC1097 are less well known and unnamed. In order to look up stars in astronomical databases, we need their right-ascension (RA) and declination (DEC) coordinates. These coordinates serve the same purpose as GPS coordinates of latitude and longitude: they unique identify a position in the sky.</p>
<p>To locate our stars, I loaded my images into <a href="https://siril.org/">Siril</a> and carried out <a href="https://siril.readthedocs.io/en/latest/astrometry/platesolving.html">platesolving</a>, a method of locating images within the sky by looking at the pattern of the stars within the image.</p>
<p><a href="https://www.flickr.com/gp/sentientintelligence/E56975SNJ8" title="Screenshot 2024-01-23 at 12.11.39 pm"><img src="https://live.staticflickr.com/65535/53480520027_7f91185f94_w.jpg" width="318" height="400" alt="Screenshot 2024-01-23 at 12.11.39 pm"></a></p>
<p>Once platesolving is completed, I saved the file as a FITS file which embeds the coordinate information into the file metadata. I then open the FITS file in <a href="https://www.astro.louisville.edu/software/astroimagej/">AstroImageJ</a> and by manually adjusting the upper and lower limits on the histogram in the image viewer and zooming in, I am able to get a good view of NGC1097.</p>
<p><a href="https://www.flickr.com/gp/sentientintelligence/03K34633a3" title="Screenshot 2024-01-23 at 12.50.16 pm"><img src="https://live.staticflickr.com/65535/53481442531_c201484c4c_w.jpg" width="365" height="400" alt="Screenshot 2024-01-23 at 12.50.16 pm"></a></p>
<p>By right clicking on the image, a link to SIMBAD will open which allows all known stellar objects in the vicinity to be queried. Using this, three objects with known visual magnitudes were identified and annotated.</p>
<p><a href="https://www.flickr.com/gp/sentientintelligence/Dy6i2455Wf" title="Screenshot 2024-01-23 at 12.49.26 pm"><img src="https://live.staticflickr.com/65535/53481853235_24a1fb7f9b_w.jpg" width="364" height="400" alt="Screenshot 2024-01-23 at 12.49.26 pm"></a></p>
<p>These are our reference stars and their visual magnitude is tabulated below.</p>
<table>
<thead>
<tr>
<th>Object</th>
<th>Vmag</th>
</tr>
</thead>
<tbody>
<tr>
<td>CD-30 1031</td>
<td>10.3</td>
</tr>
<tr>
<td>TYC 7011-484-1</td>
<td>11.39</td>
</tr>
<tr>
<td>TYC 7011-1028-1</td>
<td>12.15</td>
</tr>
</tbody>
</table><h1 id="measuring-brightness">Measuring Brightness</h1>
<p>In order to relate the brightness of these stars to the measure pixel values, I used AstroImageJ’s single-aperture photometry tool, which samples a central circular region and an annulus around it. The central circular region should just fit the star while the annulus should contain only background. The background pixel value is estimated from the pixels within the annulus and subtracted from the stellar pixel values. This value is reported as <code>Int Cnts</code>. This measurement was done on each of the reference stars and 2023rve, e.g.</p>
<p><a href="https://www.flickr.com/gp/sentientintelligence/7D9H49Mtu8" title="Screenshot 2024-01-22 at 12.32.31 pm"><img src="https://live.staticflickr.com/65535/53481726964_2e239c3458_w.jpg" width="366" height="400" alt="Screenshot 2024-01-22 at 12.32.31 pm"></a></p>
<h1 id="deriving-visual-magnitude">Deriving Visual Magnitude</h1>
<p>Tabulating the <code>Int Cnts</code> obtained across the 4 observations produces the following:</p>
<table>
<thead>
<tr>
<th></th>
<th>CD-30 1031</th>
<th>TYC 7011-484-1</th>
<th>TYC 7011-1028-1</th>
<th>2023rve</th>
</tr>
</thead>
<tbody>
<tr>
<td>2023-09-18</td>
<td>1.09E+06</td>
<td>4.54E+05</td>
<td>2.43E+05</td>
<td>2.77E+04</td>
</tr>
<tr>
<td>2023-09-24</td>
<td>1.09E+06</td>
<td>4.67E+05</td>
<td>2.60E+05</td>
<td>2.49E+04</td>
</tr>
<tr>
<td>2023-11-18</td>
<td>9.65E+05</td>
<td>4.32E+05</td>
<td>2.64E+05</td>
<td>1.20E+04</td>
</tr>
<tr>
<td>2024-01-22</td>
<td>1.14E+06</td>
<td>5.47E+05</td>
<td>2.73E+05</td>
<td>1.06E+03</td>
</tr>
</tbody>
</table><p>It is quite pleasing that the <code>Int Cnts</code> values for the three reference stars are relatively stable, particularly as I am not using an uncooled sensor nor did I control for atmospheric conditions. Of the three reference stars, <code>TYC 7011-1028-1</code> had the fewest saturating pixels and was the most stable over time, and was chosen as the reference against which to measure 2023rve’s brightness:</p>
<table>
<thead>
<tr>
<th></th>
<th>TYC 7011-1028-1</th>
<th>2023rve</th>
<th>(2023rve) / (TYC 7011-1028-1)</th>
</tr>
</thead>
<tbody>
<tr>
<td>2023-09-18</td>
<td>2.43E+05</td>
<td>2.77E+04</td>
<td>0.114</td>
</tr>
<tr>
<td>2023-09-24</td>
<td>2.60E+05</td>
<td>2.49E+04</td>
<td>0.096</td>
</tr>
<tr>
<td>2023-11-18</td>
<td>2.64E+05</td>
<td>1.20E+04</td>
<td>0.045</td>
</tr>
<tr>
<td>2024-01-22</td>
<td>2.73E+05</td>
<td>1.06E+03</td>
<td>0.004</td>
</tr>
</tbody>
</table><p>By expressing 2023rve’s brightness in terms of <code>TYC 7011-1028-1</code> I am implicit assuming the my sensor’s response is approximately linear for the brightness being measured.</p>
<p>Magnitudes are logarithms of ratios, so the brightness ratio in the table above turns into a difference in magnitude given by <code>mag_diff=-2.5log10(x))</code> where <code>x</code> are the values in the final column. By adding this value from the visual magnitude of <code>TYC 7011-1028-1</code> we arrive at an estimated visual magnitude for 2023rve:</p>
<table>
<thead>
<tr>
<th></th>
<th>(2023rve) / (TYC 7011-1028-1)</th>
<th>mag_diff</th>
<th>Vmag</th>
</tr>
</thead>
<tbody>
<tr>
<td>2023-09-18</td>
<td>0.114</td>
<td>2.355</td>
<td>14.505</td>
</tr>
<tr>
<td>2023-09-24</td>
<td>0.096</td>
<td>2.545</td>
<td>14.695</td>
</tr>
<tr>
<td>2023-11-18</td>
<td>0.045</td>
<td>3.355</td>
<td>15.505</td>
</tr>
<tr>
<td>2024-01-22</td>
<td>0.004</td>
<td>6.030</td>
<td>18.180</td>
</tr>
</tbody>
</table><h1 id="verification">Verification</h1>
<p>The estimated visual magnitude of 2023rve looks quite reasonable, but is it correct? Thankfully professional astronomers have made their own measurements which I have collected below:</p>
<table>
<thead>
<tr>
<th>Date</th>
<th>Vmag</th>
</tr>
</thead>
<tbody>
<tr>
<td>2023-09-06</td>
<td>14.5</td>
</tr>
<tr>
<td>2023-09-11</td>
<td>13.9</td>
</tr>
<tr>
<td>2023-09-16</td>
<td>14.43</td>
</tr>
<tr>
<td>2023-09-24</td>
<td>14.390</td>
</tr>
<tr>
<td>2023-11-15</td>
<td>15.500</td>
</tr>
<tr>
<td>2024-01-06</td>
<td>16</td>
</tr>
</tbody>
</table><p>Sources:</p>
<ol>
<li><a href="https://www.wis-tns.org/astronotes/astronote/2023-247">https://www.wis-tns.org/astronotes/astronote/2023-247</a></li>
<li><a href="https://www.rochesterastronomy.org/supernova.html#2023rve">https://www.rochesterastronomy.org/supernova.html#2023rve</a></li>
<li><a href="https://www.flickr.com/photos/snimages/53209027493/in/photostream/">https://www.flickr.com/photos/snimages/53209027493/in/photostream/</a></li>
<li><a href="http://gsaweb.ast.cam.ac.uk/alerts/alert/Gaia23cmp/">http://gsaweb.ast.cam.ac.uk/alerts/alert/Gaia23cmp/</a></li>
</ol>
<p>Compared against these, my visual magnitudes estimates compare quite favourably! I am pleasantly surprised how well things worked out. My last measurement, on 2024-01-22, stands out by how much it differs. It is also the measurement I have the least confidence in as by that point I could no longer reliably identify 2023rve in a single 60s exposure. I have some ideas here: take longer exposures or stack my exposures carefully (keeping values linear) and estimate from the stacked image.</p>
<h1 id="absolute-magnitude">Absolute Magnitude</h1>
<p>The conversion to absolute magnitude is <a href="https://en.wikipedia.org/wiki/Absolute_magnitude#Apparent_magnitude">quite straight-forward</a> as is the subsequent plotting.</p>
<p><a href="https://www.flickr.com/gp/sentientintelligence/kA3Y4216LX" title="Screenshot 2024-01-23 at 1.43.29 pm"><img src="https://live.staticflickr.com/65535/53481520981_5dc983a017_z.jpg" width="640" height="354" alt="Screenshot 2024-01-23 at 1.43.29 pm"></a></p>
<p>Note that because I don’t know when peak brightness occurred, I am using days-since-discovery instead.</p>
<h1 id="type-ii-classification">Type II Classification</h1>
<p>I don’t think there is enough data yet to definitively say what subtype 2023rve is. More data points will decide the matter and I look forward to the next set of clear skies so I can continue this effort.</p>
Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-36246179582623441482023-12-23T12:16:00.003+11:002023-12-23T12:16:42.477+11:00On NS*DateFormatters<p>
There now exists <code>NSDateFormatter</code> and <code>NSISO8601DateFormatter</code> and their behaviour when a timezone is not set is not the same: <code>NSDateFormatter</code> produces strings formatted for <strong>local time</strong> while <code>NSISO8601DateFormatter</code> produces string formatted for <strong>UTC</strong>.
</p>
<p>As an example, given a date-time of <code>2000-12-31T23:00:00Z</code></p>
<dl>
<dt><code>NSDateFormatter</code> with no timezone set and full styles:</dt>
<dd>Monday, January 1, 2001 at 10:00:00 AM Australian Eastern Daylight Time</dd>
<dt><code>NSISO8601DateFormatter</code> with no timezone set:</dt>
<dd>2000-12-31T23:00:00Z</dd>
</dl>
<p>
Note that <code>NSDateFormatter</code> "applies" my local timezone automatically whereas <code>NSISO8601DateFormatter</code> doesn't.
Sidebar: it seems that while <code>NSDate</code> carries no timezone information, it is always interpreted as UTC time.
</p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-46156761533677342592023-10-16T00:50:00.006+11:002023-10-27T15:34:01.431+11:00DIY EQMod Direct USB Cable<p>I am in the process of resurrecting my Eq5 Pro so it is compatible with ASIAir Mini. The first step is to build an EQMod Direct USB cable. While it is possible to buy one pre-made, since I had all the parts I decided to build it myself.</p>
<p>Based on the <a href="https://eq-mod.sourceforge.net/tutindex.html">reference document</a> I need to make an single-ended RJ45 cable. I followed <a href="https://satoms.com/ethernet-cable-pinouts/">T-568A colour scheme</a>:</p>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhoIKn1uYcoaL1b2KpWpO0tvvzG2RSswRZJrb0TZuzc_IksAQCVe2FiPZBrzUumdypSy6YrSsZ8zk9KSoG7KL_dPHoU29iRol_8_w1-b5ehoRCGHC4nKx6kT5enpSHVBoO_c-mFB4OCFnMJ5KRcu5Q68lJvVVEGA5L8ZW6bEcU20ndhtSGheSZMAw/s400/RJ45-Pinout.gif" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" width="320" data-original-height="250" data-original-width="400" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhoIKn1uYcoaL1b2KpWpO0tvvzG2RSswRZJrb0TZuzc_IksAQCVe2FiPZBrzUumdypSy6YrSsZ8zk9KSoG7KL_dPHoU29iRol_8_w1-b5ehoRCGHC4nKx6kT5enpSHVBoO_c-mFB4OCFnMJ5KRcu5Q68lJvVVEGA5L8ZW6bEcU20ndhtSGheSZMAw/s320/RJ45-Pinout.gif"/></a></div>
<p>Based on this colour scheme, the connection to a USB-UART adapter is as follows:</p>
<table style="margin-left:auto;margin-right:auto;width:50%;">
<tr style="border-bottom: 1px solid white"><th>RJ45</th><th>Colour</th><th>USB-UART</th></tr>
<tr><td>4</td><td>Blue</td><td>Ground</td></tr>
<tr><td>5</td><td>Blue-White</td><td>RXI</td></tr>
<tr><td>6</td><td>Orange</td><td>TXO</td></tr>
</table>
<p>Plug the RJ45 end of the cable into the hand-controller port on the control box and the other end into the ASIAir Mini. Then power up the ASIAir Mini as usual and use one of the 12V outputs to power the SynScan. Make sure to switch on the SynScan as it has its own power switch. After this select EQMod for the mount model and leave the baudrate at the default value of 9600. Tap the enable-toggle-switch and the ASIAir Mini will attempt to connect to the mount. After a successful connection you should be able to manually slew the mount in RA and DEC in Preview mode.</p>
<p><strong>Update</strong>: I have to power up the SynScan <em>after</em> the ASIAir has fully booted (made it's beeping noises) in order for them to communicate successfully. If both are powered up at the same time, something goes awry and the ASIAir Mini will not be able to connect.</p>
Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-32361339034335120532023-09-18T00:21:00.002+10:002023-09-18T00:21:15.959+10:00Build Log: SCD41 CO2 Sensor<p>
CO2 concentration is a proxy for how well a space, especially an enclosed one, is ventillated. To this end I build a quick-n-dirty CO2 sensor using a SCD41 breakout board from pimoroni and bits and pieces I had in the workshop.
</p>
<p>
Took the opportunity to practice making enclosures, especially for an irregularly shaped circuit. The enclosure was designed in FreeCAD by taking a picture of the circuit then importing it as a reference image. After correct for scale
the designed enclosure was reasonable accurate, needing only some small tweaks to dimensions to correct forperspective distortion. The result was then 3D printed on my FF Creator Pro.
</p>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUOXXzSGlv5FaZTrdq5B7_Ir4wJXktqnZ0A4V1-4Ad1DxzpURMA26ZfDJb3HCRu8XhaVYP_-uGkEWLcy9K1uwygfgIXjOQwi_fjX83FfwLjceu92Obntm3-F9xhbh7CLYPxas_w1hxaB1R8cHeX2J3kFxblukgfL0L8LAo87JOzfCME-YbPCFD9w/s4032/IMG_5112%202.JPG" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" width="320" data-original-height="3024" data-original-width="4032" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiUOXXzSGlv5FaZTrdq5B7_Ir4wJXktqnZ0A4V1-4Ad1DxzpURMA26ZfDJb3HCRu8XhaVYP_-uGkEWLcy9K1uwygfgIXjOQwi_fjX83FfwLjceu92Obntm3-F9xhbh7CLYPxas_w1hxaB1R8cHeX2J3kFxblukgfL0L8LAo87JOzfCME-YbPCFD9w/s320/IMG_5112%202.JPG"/></a></div>
<p>
The enclosure provides openings for a button (currently unused), a "cage" for the CO2 sensor, display and micro-USB port.
</p>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi9NM0iiKZn7wcmLu9-EOrXo17VNcKBu9ElX3lmDNRoVhUwIu9GeDSsGzH5XVnwZdNTsfB8xoM-6N2Qkfbl21OvwUAIdcYM9aJDTokL8_YOgWJrvPx8ct_uiZ3mxP6_PYFmGBXuOW7S2YtW9g_Nnv9qkoclxDoO-LpU9kAmNVIGxHOyyRdch9yVNw/s4032/IMG_5100%203.JPG" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" width="320" data-original-height="3024" data-original-width="4032" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEi9NM0iiKZn7wcmLu9-EOrXo17VNcKBu9ElX3lmDNRoVhUwIu9GeDSsGzH5XVnwZdNTsfB8xoM-6N2Qkfbl21OvwUAIdcYM9aJDTokL8_YOgWJrvPx8ct_uiZ3mxP6_PYFmGBXuOW7S2YtW9g_Nnv9qkoclxDoO-LpU9kAmNVIGxHOyyRdch9yVNw/s320/IMG_5100%203.JPG"/></a></div>
<p>
In addition to practicing painting techniques, I also wanted to try new ways of "labelling" my projects. Water-slide decals are widely used in model kits, and it turns out you can buy blank sheets with which to make your own decals with! I picked a cheap'ish option off Amazon. Just search for "water slide decal clear laser". Once they arrived it was a simple matter of designing the decals in inkscape, printing it out and cutting them to size. To complete the build, a plastic primer was applied, followed by colour coats, then a clear coat was applied, followed by the decal, followed by 2 more layers of clear coat.
</p>
<div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh0cQ-AwSGDFaZEnbQBIc0M3NW_-amJ_wEv-Tfk2VZM4zRunHsQUfnSp49iI6-6mZDIZzpoDwCMDJz-tvBVnxPV4ciwZ7krJN4pkOdP3gp5Wd_DnfIW91DxVdZ9VFc4WmHKgL5Kw2r98mh-Lw3sUrHD-wWu3cEBuRH981fgCBqUlXNXK8frP18zpQ/s4032/IMG_5111%203.JPG" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" width="320" data-original-height="3024" data-original-width="4032" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh0cQ-AwSGDFaZEnbQBIc0M3NW_-amJ_wEv-Tfk2VZM4zRunHsQUfnSp49iI6-6mZDIZzpoDwCMDJz-tvBVnxPV4ciwZ7krJN4pkOdP3gp5Wd_DnfIW91DxVdZ9VFc4WmHKgL5Kw2r98mh-Lw3sUrHD-wWu3cEBuRH981fgCBqUlXNXK8frP18zpQ/s320/IMG_5111%203.JPG"/></a></div><div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgVzPWv4G_EXCD7N2fmojh8Ew3T8yDpSuE55tEWp-rhDe76fEaotpl1qgKSoKuUB599JvxgoKMWFi3S6zbCTRXengGAPtcKg0lOg9X3YMtEVauMqmaCmJPEB4YXxygI6ekRomMhX2evG9uyAjodDP69DECOEVvWRkUcWZ6cvbpKtCRPYs1Xnv_TmA/s4032/IMG_5114%202.JPG" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" width="320" data-original-height="3024" data-original-width="4032" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgVzPWv4G_EXCD7N2fmojh8Ew3T8yDpSuE55tEWp-rhDe76fEaotpl1qgKSoKuUB599JvxgoKMWFi3S6zbCTRXengGAPtcKg0lOg9X3YMtEVauMqmaCmJPEB4YXxygI6ekRomMhX2evG9uyAjodDP69DECOEVvWRkUcWZ6cvbpKtCRPYs1Xnv_TmA/s320/IMG_5114%202.JPG"/></a></div><div class="separator" style="clear: both;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjxXw39r07Qrrq1AGrqLpkqoMTyUm5MSO9H3dYnoLVVwfO_gJzebyM-zVB5r7LTZNAVzujQX9uhKcW6_Do3sughsl5hNOZqp8M4ZacS7b6z0C8540E9ynF7tdAxdWcgfUtl7JSFiKUmWVT12nfCennzLFi0b-pzGjttMaovmt1kNMHIZr7Z3oDxZw/s4032/IMG_5119.JPG" style="display: block; padding: 1em 0; text-align: center; "><img alt="" border="0" width="320" data-original-height="3024" data-original-width="4032" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjxXw39r07Qrrq1AGrqLpkqoMTyUm5MSO9H3dYnoLVVwfO_gJzebyM-zVB5r7LTZNAVzujQX9uhKcW6_Do3sughsl5hNOZqp8M4ZacS7b6z0C8540E9ynF7tdAxdWcgfUtl7JSFiKUmWVT12nfCennzLFi0b-pzGjttMaovmt1kNMHIZr7Z3oDxZw/s320/IMG_5119.JPG"/></a></div>
<p>
Overall quite happy with the outcome! Could have done more sanding before applying paint to hide the layer lines better and the a matte coat I think would have worked better. Nonetheless the decal idea worked out well and I think it will be my goto - a big improvement over permanent markers.
</p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-91797318643753324282023-03-29T07:58:00.002+11:002023-03-29T07:58:44.981+11:00Unexpected Latency in Tinyproxy<p>I love <a href="https://tinyproxy.github.io/"><code>tinyproxy</code></a>, it is simple to setup and more than enough for my needs. Recently however I noticed that some clients were experiencing unexpected long delays when doing something as simple as <code>curl google.com</code>. After some sleuthing, I tracked it down to the fact I had</p>
<pre>
LogLevel Info
</pre>
<p>in my config. When this is set <code>tinyproxy</code> produces log entries such as</p>
<pre>
CONNECT Mar 28 08:46:41 [7023]: Connect (file descriptor 7): [unknown] [123.123.123.123]
</pre>
<p>the <code>[unknown]</code> is due to <code>tinyproxy</code> attempting and failing to resolve the connecting IP into a hostname. It is this attempt to map IP to hostname that is causing the latencies observed. To resolve this I added offending IP to <code>/etc/hosts</code></p>
<pre>
123.123.123.123 some-host-name
</pre>
<p>with the above entry the latency went away and the log entries now look like</p>
<pre>
CONNECT Mar 28 20:39:49 [6879]: Connect (file descriptor 7): some-host-name [123.123.123.123]
</pre>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-70499440935433795912023-03-29T06:38:00.002+11:002023-03-29T06:39:16.117+11:00Conda and Slow Proxies<p>The default <code>conda</code> connect timeout is 9.15 seconds (no idea why this is, seems to have been the case from day one). If the proxy is slow, e.g. it is in another country or AWS region, this timeout can be triggered and <code>conda</code> will prematurely close the connection.</p>
<p>To diagnose this issue, attempt </p>
<pre>
curl https://repo.anaconda.com/pkgs/main/linux-64/current_repodata.json
</pre>
<p>with proxies enabled. If that works then increase the connect timeout as follows</p>
<pre>conda config --set remote_connect_timeout_secs 30</pre>
<p>conda should now be able to update and install new packages etc.</p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-32328394153039040392023-02-04T13:41:00.003+11:002023-02-04T14:37:08.873+11:00Installing python package arcgis in conda on Apple Silicon<p> In order to install the <a href="https://anaconda.org/Esri/arcgis">arcgis</a> package in <a href="https://docs.conda.io/en/main/miniconda.html">conda</a>, you have to specify the architecture <span style="font-family: courier;">osx-64</span> otherwise the package will not be found. This works because MacOS will capable of running <span style="font-family: courier;">x86_64</span> code on Apple Silicon processors - that is how efficient they are!</p><p> </p>
<pre>conda install -c esri/osx-64 arcgis </pre>
<p>In fact to make everything else work you need to add the channels with architecture specified exactly, e.g. <code>conda-forge/osx-64</code>, <code>esri/osx-64</code> and <code>defaults/osx-64</code>. Otherwise packages will be installed with a mix of architectures and appears not to be able to find each other.</p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-66833790975795870282022-12-26T13:27:00.001+11:002022-12-26T13:27:09.080+11:00Build Log: ATTiny13 LED Dimmer<h2 style="text-align: left;">Introduction <br /></h2><p>Bought some cheap USB driven warm-white LEDs off eBay for lighting display cabinets. Turns out it is just normal LED strips with a simple driver in the USB plug. Wanting to unify control of multiple LED strips into a single point I build a simple PWM based LED driver. It is neither constant current <i>nor</i> constant voltage - for the simple LEDs I have it is Good Enough (tm).</p><h2 style="text-align: left;">Build Details <br /></h2><p>Finished product first, this is the controller mounted on the back of the bookcase where the LED strips are mounted. 5V from a wall plug PSU enters on the left and the LEDs strips are wired in parallel on the right. The single button cycles between on and 3 levels of brightness, with max brightness consuming around 800mA.<br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgGiwF5vISX2mrlldMcUi80q0n8EQDq6O8-eHkF41EBDro9_LTTLZ1SByjWsMDwawAIwZn0wBJq96PPuyRM7WI7H6BUuE0ETYrAhR02sdDvanLA2zn1Dky8GH0upgfhNNkIDgUwOSRKkHgNMHwzjrPko0uSpyVWbb2svtJ7iewMbtXNFgF35l0/s4032/IMG_4477.JPG" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3024" data-original-width="4032" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEgGiwF5vISX2mrlldMcUi80q0n8EQDq6O8-eHkF41EBDro9_LTTLZ1SByjWsMDwawAIwZn0wBJq96PPuyRM7WI7H6BUuE0ETYrAhR02sdDvanLA2zn1Dky8GH0upgfhNNkIDgUwOSRKkHgNMHwzjrPko0uSpyVWbb2svtJ7iewMbtXNFgF35l0/w320-h240/IMG_4477.JPG" width="320" /></a></div><p>With the lid off, the interior layout can be examined. Essentially a single strip board containing all components and socket hardware.</p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjJTYLlzhvsAAlUXaKbSszJi4xdJLBUSYgtGPhllxY6PKD_-oJK7UrRMqPx6P1WM84RnWzKBzTy0kdZCJd2UpK41D7zWVHqguN8h6v3xDBlwB00sn0uOb6xy1sKT_Yd3uH3BrrTiGIATnb-P3C6xqN0WQ2lHxm2FL6vMHUPkIw8NxrGCnuApoM/s4032/IMG_4483.JPG" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3024" data-original-width="4032" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjJTYLlzhvsAAlUXaKbSszJi4xdJLBUSYgtGPhllxY6PKD_-oJK7UrRMqPx6P1WM84RnWzKBzTy0kdZCJd2UpK41D7zWVHqguN8h6v3xDBlwB00sn0uOb6xy1sKT_Yd3uH3BrrTiGIATnb-P3C6xqN0WQ2lHxm2FL6vMHUPkIw8NxrGCnuApoM/s320/IMG_4483.JPG" width="320" /></a></div><p>The strip board is very basic: decouple and smoothing capacitor on the top-right; ATTiny13 in the middle in a socket so it can be reprogrammed; BD135 NPN transistor lower middle with base resistor to turn the LEDs on and off; and some resistors detect button press. Could have used the internal pull-up resistors but the construction demanded that the button be wires on the high side.<br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFg83hBjnAHiPwxLqDBZa7x4sji4NTwVd_8lS2S1t0u1_2EKQa8dsUJubyhYdS1OGURyFxNBR7ofi8MVgCMAuXdPJDcW6F6hHpSyJv6fWSBWxNrGzzdWNWkeX_ETliyE0K8NdLtnEPDX11Qq-nJBRkf3JUOxCMR20eqmEO294QDfgzVQFno1g/s4032/IMG_4479.JPG" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3024" data-original-width="4032" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhFg83hBjnAHiPwxLqDBZa7x4sji4NTwVd_8lS2S1t0u1_2EKQa8dsUJubyhYdS1OGURyFxNBR7ofi8MVgCMAuXdPJDcW6F6hHpSyJv6fWSBWxNrGzzdWNWkeX_ETliyE0K8NdLtnEPDX11Qq-nJBRkf3JUOxCMR20eqmEO294QDfgzVQFno1g/s320/IMG_4479.JPG" width="320" /></a></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhz4gB8-xnUfcpEMFGZBd1uC1swY761kM8hLi6HngBrfpVoGYSNnb8sM3c-6WUyFz80QtRdU8AnmcOqFzb4sEp2pL4l4TVGAyZPyd4kpCEfG0nG4NjyUQj-sRs4Cr0gR3DBuGbPBW2iWWz9XmsRgq-WHYvDbCOdYELCs8w3WDXljbhZdamGHio/s4032/IMG_4480.JPG" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3024" data-original-width="4032" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhz4gB8-xnUfcpEMFGZBd1uC1swY761kM8hLi6HngBrfpVoGYSNnb8sM3c-6WUyFz80QtRdU8AnmcOqFzb4sEp2pL4l4TVGAyZPyd4kpCEfG0nG4NjyUQj-sRs4Cr0gR3DBuGbPBW2iWWz9XmsRgq-WHYvDbCOdYELCs8w3WDXljbhZdamGHio/s320/IMG_4480.JPG" width="320" /></a></div><p>This project was an opportunity to try a new way of encapsulating projects, namely by using PCB spacer to raise the strip board to top of the enclosure and then constructing a lid to match the button's position. This worked quite well, especially here where the NPN transistor needed some room to dissipate heat. The spacer can be seen in the following photo. Note the vents built into it which line up with the case vents.<br /></p><p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg02XecUFF0FV9sxgiXhu-rjjPjE8NP5SdJkEOHjraoReErS8qKUpanWc4HipiIB_wejYMs7kCMteb66ou6hqV78PgiFSoEpYdQ6eDTP4Jg-7fkEdoU688zKpf7xRfQGiO4jOBBa9-rgjvzGnBrNiuZIoiDPjL9eY0g7kenga5KA66Xu7fYj6s/s4032/IMG_4482.JPG" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3024" data-original-width="4032" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEg02XecUFF0FV9sxgiXhu-rjjPjE8NP5SdJkEOHjraoReErS8qKUpanWc4HipiIB_wejYMs7kCMteb66ou6hqV78PgiFSoEpYdQ6eDTP4Jg-7fkEdoU688zKpf7xRfQGiO4jOBBa9-rgjvzGnBrNiuZIoiDPjL9eY0g7kenga5KA66Xu7fYj6s/s320/IMG_4482.JPG" width="320" /></a></div><br />The initial case design had the vents (seen below) built in to reduce printing time, turns out they are also very useful for passive cooling of the NPN transistor. <p></p><p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhE0pMT4MGVTBI2LkYh0Q_OpOR2JfoclZAalCg1v6Pl50-4kZpueAQaw1gFNit9UERKxulWgRMe-x6wzDa5xGWGm_8fGUDj9TOhc3AIjPfqoCpKI7oAZ8ZOg1unIiljeixCBeSnr_4im2G_Y8zYkvYd8Nqdt7J2QOtMQfGSH8Ldbl0w6CZKA_Q/s4032/IMG_4481.JPG" imageanchor="1" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="3024" data-original-width="4032" height="240" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhE0pMT4MGVTBI2LkYh0Q_OpOR2JfoclZAalCg1v6Pl50-4kZpueAQaw1gFNit9UERKxulWgRMe-x6wzDa5xGWGm_8fGUDj9TOhc3AIjPfqoCpKI7oAZ8ZOg1unIiljeixCBeSnr_4im2G_Y8zYkvYd8Nqdt7J2QOtMQfGSH8Ldbl0w6CZKA_Q/s320/IMG_4481.JPG" width="320" /></a></div><p></p><p>In addition to the vents in the case, vents were also added to the lid to aid cooling after observing that the case as a whole was warm to touch. The goal is for the whole system to operate without fail for the ~8hr period it is designed to operate for before turning itself off due to idle timeout.</p><h3 style="text-align: left;">Code and CAD<br /></h3><p style="text-align: left;">The ATTiny13 was programmed using AVR ISPmkII, <a href="https://platformio.org/">PlatformIO</a> and <a href="https://github.com/MCUdude/MicroCore#">MicroCore</a>. <a href="https://www.freecadweb.org/">FreeCAD</a> was used to design the enclosure, using the spreadsheet workflow to parameterise dimensions such as case thickness, inteference-fit-tolerance, etc. </p><p style="text-align: center;"><img alt="" height="160" 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" 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width="205" /></p><h2 style="text-align: left;">To Improve</h2><div style="text-align: left;"><ol style="text-align: left;"><li>Clean up the vents in the case, possibly increase their size and the thickness of the case in that area so it is less flimsy.</li><li>Engrave into the case the LED and 5V labels.</li><li>Screw terminals would have been easier to wire up.<br /></li></ol></div><p><br /></p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-44472867881630592132022-12-20T14:21:00.005+11:002022-12-20T15:37:19.399+11:00Exif Tag Types<p> Went on a journey trying to figure out what valid exif tag types are, in both JPEG and TIFF files. In summary:</p>
<table>
<thead>
<tr>
<th>TYPE #</th>
<th>Name</th>
<th>Exif 2.32</th>
<th>Tiff 6.0</th>
<th>Adobe TN[1]</th>
</tr>
</thead>
<tbody>
<tr>
<td>1</td>
<td>BYTE</td>
<td>X <br></td>
<td>X</td>
<td></td>
</tr>
<tr >
<td>2</td>
<td>ASCII</td>
<td>X</td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>3</td>
<td>SHORT</td>
<td>X</td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>4</td>
<td>LONG <br></td>
<td>X</td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>5</td>
<td>RATIONAL</td>
<td>X</td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>6</td>
<td>SBYTE</td>
<td></td>
<td>X<br></td>
<td></td>
</tr>
<tr>
<td>7</td>
<td>UNDEFINED</td>
<td>X</td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>8</td>
<td>SSHORT</td>
<td></td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>9</td>
<td>SLONG</td>
<td>X</td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>10</td>
<td>SRATIONAL</td>
<td>X</td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>11</td>
<td>FLOAT</td>
<td></td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>12</td>
<td>DOUBLE</td>
<td></td>
<td>X</td>
<td></td>
</tr>
<tr>
<td>13</td>
<td>IFD</td>
<td></td>
<td></td>
<td>X <br></td>
</tr>
</tbody>
</table>
<p>The last 3 columns indicate where the tag type is specified. e.g. Type #9-SLONG, is documented in both Exif 2.32 and Tiff 6.0, whereas type #11-FLOAT is only defined in Tiff 6.0.</p>
<p>[1] Adobe TN refers to "Adobe PageMaker® 6.0 TIFF Technical Notes".</p>
Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-8817801436880183072022-12-04T23:31:00.004+11:002022-12-20T15:33:19.271+11:00FSCK'ing Veracrypt Volumes on macOS<p>Due to unexpected power loss or disconnection of the underlying storage, the filesystem <i>inside</i> Veracrypt volumes is desired to prevent future data loss.</p><p>On macOS I tried using </p>
<pre>diskutil verifyDisk /dev/diskXXX</pre>
<p>This didn't work for some reason, most likely because of some interaction with veracrypt. Same results via Disk Utility application.</p><p>The Veracrypt GUI however offers a "check filesystem" option if you right click on a mounted volume. Unfortunately, as of version 1.25.9, it doesn't work out-of-the-box on macOS: it fails to find </p>
<pre>
/Applications/Utilities/Disk Utility.app
</pre>
<p>The cause is that from at least macOS 12, Disk Utility is located at<br /></p>
<pre>/System/Applications/Utilities/Disk\ Utility.app</pre>
<p>There is a quick and dirty workaround</p>
<pre>
cd /Applications/Utilities
sudo ln -s /System/Applications/Utilities/Disk\ Utility.app ./</pre>
<p>With the above symlink in place it is possible to perform filesystem verification and repair via the context menu items offered in the Veracrypt GUI.<br /></p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-67300670411284588632022-12-03T14:12:00.008+11:002023-01-11T01:40:47.233+11:00Verifying Local iOS Backups<p>Backups are a great idea, and <i>encrypted</i> backups are a even better idea. When backing up iOS devices on macOS, it is possible to set an encryption key to protect local files. There is however no straightforward GUI method to verify the encryption key.</p><p>Enter <span style="font-family: courier;"><a href="https://github.com/mvt-project/mvt">mvt</a></span>:</p>
<pre>conda create -n mvt python=3.10
conda activate mvt
pip install mvt
mvt-ios extract-key /path/to/backup
</pre>
<p>With the right password you will see</p>
<pre>INFO [mvt.ios.decrypt] Derived decryption key for backup at path /path/to/backup is:
"12345678901234567890"
</pre>
<p>Otherwise</p>
<pre>CRITICAL [mvt.ios.decrypt] Failed to decrypt backup. Did you provide the correct password? Did you
point to the right backup path?
</pre>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-61199892376811610832022-07-30T11:51:00.003+10:002022-07-30T11:51:51.403+10:00TigerVNC and Systemd<p>A quick <code>systemd</code> service definition file for <code>tigervnc</code> on Ubuntu 20.04</p>
<pre style="font-size:0.8em"><code><span class="hljs-section">[Unit]</span>
<span class="hljs-attr">Description</span>=tigervnc
<span class="hljs-section">
[Service]</span>
<span class="hljs-attr">Type</span>=forking
<span class="hljs-attr">ExecStart</span>=/usr/bin/vncserver -localhost <span class="hljs-literal">no</span> -depth <span class="hljs-number">24</span> -geometry <span class="hljs-number">1920</span>x1080 -noreset
<span class="hljs-attr">User</span>=steve
<span class="hljs-section">
[Install]</span>
<span class="hljs-attr">WantedBy</span>=multi-user.target
</code></pre><p>Key components:</p>
<ol>
<li><code>Type=forking</code> so <code>systemd</code> correctly identifies the real VNC process, not the perl script that runs and then exits</li>
<li><code>-localhost no</code> so connections from other computers are accepted. This is only needed if you are not using <code>ssh</code> tunneling.</li>
<li><code>User=steve</code> so <code>tigervnc</code> doesn't complain about <code>HOME</code> not defined in the environment and uses my settings for auth and X session. Note that this is a strictly single-user setup.</li>
</ol>
Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-24850340009053118142022-07-22T02:09:00.003+10:002022-07-22T02:09:46.648+10:00Using SubShapeBinders and Assembly4<p>Assembly4 and SubShapeBinders make it possible to assemble Parts, then using their position in the assembly to generate new Parts. However because new Parts depend on Parts in the assembly, if you try to add them to the assembly FreeCAD 0.19 will complain about cyclic redundancy, which makes sense.</p><p>To get around this, one method is to change the Bind Mode of the SubShapeBinders to "Disabled" which copies the geometry but unbinds it from the base object. <br /></p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-50318069353862714722022-06-18T21:34:00.005+10:002022-07-22T02:05:34.384+10:00Kopia: Handling Directories That No Longer Exist<p> Scenario</p><ol style="text-align: left;"><li>There exists a policy that snapshots directory ABC </li><li>Directory ABC now no longer exists</li><li>You want to keep existing snapshots</li><li>You want to stop kopia from attempting to take any more snapshots</li></ol><p>In order to achieve (4):</p><ol style="text-align: left;"><li>Set the policy to manual only</li><li>Disable inheritance from parent/global policy</li></ol><p>(2) is required as otherwise I find ABC's policy somehow inheriting the scheduling settings from the parent/global policy and thus is scheduled even though manual snapshots only is set.</p><p>To carry out the above steps:</p><ul style="text-align: left;"><li><span style="font-family: inherit;">KopiaUI: </span></li><ul><li><span style="font-family: inherit;">Edit Policy </span></li><ul><li><span style="font-family: inherit;"> Scheduling > Manual Snapshots Only<span> </span></span></li><li><span style="font-family: inherit;"><span> Other > Disable Parent Policy Evaluation<br /></span></span></li></ul></ul><li><span style="font-family: inherit;"><code>CLI: set policy --manual --inherit false </code></span><br /></li></ul>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-60733733189013275782022-03-05T15:53:00.003+11:002022-03-05T15:53:19.667+11:00Adventures with Astroberry/KStars/Ekos<p>In astrophotography the combination of a goto mount, a camera and plate-solving is a powerful one. It allows you to do all kind of neat things, like polar-alignment without having a clear view of the south, extremely accurate goto functionality, and automated capture of multiple predefined targets.</p><p>There are roughly speaking three popular single-board-commputers (SBCs) that facilitate this: <a href="https://astronomy-imaging-camera.com/product/asiair-pro">ASIAIR PRO</a>, <a href="https://www.stellarmate.com/">Stellarmate</a> and and <a href="https://www.astroberry.io/">astroberry</a>, in increasing order of technical complexity and reduction in price, with astroberry being free. Both Stellarmate and astroberry use the same underlying software, namely <a href="https://edu.kde.org/kstars/">kstars/ekos</a> and <a href="https://www.indilib.org/about/ekos.html">INDI Library</a>.</p><p>Since both ASIAR and Stellarmate devices were out of stock, but Raspberry Pi 4s (rpi) aren't, I opted to try astroberry. Installation was straightforward, everything worked as advertised. To ease mounting I designed and printed an accessory collar that allows the rpi to be attached and removed easily.</p><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEiFh1LFOFeOQzGj1yVUqWUXIH10nkACYTQ2GP26j_D5EsV2edOX4Q8VdZok0OLPe9bu7J32rGMd0YordRXGeb0ZcGsSAnKpUNUFTjkjA2pVIcNNi6xNuWTkqAqQeXEAEr7pG1vFAQ-2HPIt3591zEP9cdBGSlzbfPjOJ2S4NhMfxhOolqlEM6c=s4032" imageanchor="1" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="3024" data-original-width="4032" height="300" src="https://blogger.googleusercontent.com/img/a/AVvXsEiFh1LFOFeOQzGj1yVUqWUXIH10nkACYTQ2GP26j_D5EsV2edOX4Q8VdZok0OLPe9bu7J32rGMd0YordRXGeb0ZcGsSAnKpUNUFTjkjA2pVIcNNi6xNuWTkqAqQeXEAEr7pG1vFAQ-2HPIt3591zEP9cdBGSlzbfPjOJ2S4NhMfxhOolqlEM6c=w400-h300" width="400" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Raspberry Pi 4 in custom case mounted the accessory collar.<br /></td></tr></tbody></table><br /><p><br /></p><p>The first issue with astroberry, and possibly also with Stellarmate, is that control is done via a remote desktop session over VNC. This isn't a problem other than the fact we are forced to use a desktop software on mobile device with very different aspect ratios and interaction paradigms. The end result is a very janky user experience. There are also concerns that, as the rpi uses passive cooling, it will quickly be thermally throttled, further degrading user experience unless one adds a cooling fan and heatsink.</p><p>So the next evolution is to run only the INDI server on the rpi and run kstars and ekos on a laptop, which provides a native desktop experience appropriate to the device and moves any heavy processing onto a more capable platform. This works, but does take away the main advantages of having a SBC, namely a small and light setup.<br /></p><p>The next issue that arises is that of transfer time. Running kstar/ekos on a laptop means images captured by the rpi must be transferred before any additional algorithms, such as plate-solving, can run. With my Canon 800D it takes up to 15 seconds to transfer a single raw file over the built-in wireless. This is an unacceptable long amount of time.</p><p>The logical step is then to do away with the rpi altogether and run everything on the laptop I am using anyway. In this case a lenovo X220 with extended batteries. This works well, with transfer times of approximately one second. <br /></p><p>As an aside, the default ekos layout doesn't do well on a display that is only 768px high, with many UI elements in the capture tab unusable. Setting ekos to have tabs on the left as opposed to at the top resolved this issue.</p><p>The current setup is thus:</p><ol style="text-align: left;"><li>Canon 800D with 200mm F/2.8L II</li><li>SmartEQ Pro+</li><li>Lenovo X220 with KStars/EKOS/INDI</li></ol><p>Now if only the clouds would go away I can actually see how this performs in anger. <br /></p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-65190707266597791262022-02-23T01:23:00.007+11:002022-02-23T01:32:18.343+11:00Astrophotography Notes: ISO, Light Pollution, Histograms<h3 style="text-align: left;">ISO</h3><p>I, like many people, thought that lower ISO means less noise. However this isn't true, at least not for modern camera. As a first order approximation, my understanding is that the signal path looks something like this:</p><ol style="text-align: left;"><li>Photons impact the sensor<br /></li><li>Sensor generates electrical signal<br /></li><li>ISO amplifier amplifies the signal<br /></li><li>Readout electronics converts the signal into digital numbers</li><li>digital numbers recorded as a RAW file</li></ol><p>Generally speaking there are two major source of noise:</p><ol style="text-align: left;"><li>Random noise inherent in the photons arriving at the sensor</li><li>Noise generated by readout electronics and quantisation noise in the ADC</li><ol><li>aka readout-noise </li></ol></ol><p>We can express the signal-to-noise ration (SNR) of the RAW image as follows:<br /></p><p style="text-align: center;"><span style="font-family: courier;">RAW_SNR = (ISO_gain * S) / (ISO_gain * N + N_readout)</span></p><p>Where <span style="font-family: courier;">S</span> and <span style="font-family: courier;">N</span> is the light signal and noise, and <span style="font-family: courier;">N_readout</span> is the readout-noise. <span style="font-family: courier;">ISO_gain</span> is the gain corresponding to the ISO value, but not the ISO value itself. e.g. ISO 100 doesn't not mean gain of 100.</p><p>Generally speaking <span style="font-family: courier;">S >> N</span>, that is the light signal itself has good SNR. <br /></p><p>In low light situations where <span style="font-family: courier;">S</span> of a similar magnitude to <span style="font-family: courier;">N_readout</span>, if we use a low ISO such that <span style="font-family: courier;">ISO_gain</span> is 1, then </p><p style="text-align: center;"><span style="font-family: courier;">RAW_SNR ~= S / N_readout</span></p><p>as <span style="font-family: courier;">N_readout >> N</span>. </p><p>By increasing the ISO such <span style="font-family: courier;">(ISO_gain * N) >> N_readou</span>t, <br /></p><p style="text-align: center;"><span style="font-family: courier;">RAW_SNR = (ISO_gain * S) / (ISO_gain * N + N_readout) </span></p><p style="text-align: center;"><span style="font-family: courier;"> ~= (ISO_gain * S) / (ISO_gain * N) </span></p><p style="text-align: center;"><span style="font-family: courier;">~= S / N</span></p><p>That is, we approximately recover the original SNR of the signal which is the best that can be asked for without additional processing.</p><p>This bears out in practice. I took a series of images in low light with the same aperture and shutter speed, changing only the ISO. Each image was then digitally processed in darktable with exposure compensation so images are of the same brightness (i.e. 1 extra step of exposure for each reduction in ISO):</p><div class="separator" style="clear: both; text-align: center;"><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEgZ6jX9jNtWJMU__yoWg2eRpM67OjPvhUX3rBScbc3sP48-qjMc2w9cNqzdFcpMGjjkmRyqJyOEnEAnd7joVDWSopzSw6OiW0R06AfG97nEvzq3tCwftJJA3N3Cfv5oB9nUUrB1HOXzeIES-x_rM7IiIbEpJ6AhOSorXVYjdIoOSz_QpkHNcFk=s1372" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1182" data-original-width="1372" height="277" src="https://blogger.googleusercontent.com/img/a/AVvXsEgZ6jX9jNtWJMU__yoWg2eRpM67OjPvhUX3rBScbc3sP48-qjMc2w9cNqzdFcpMGjjkmRyqJyOEnEAnd7joVDWSopzSw6OiW0R06AfG97nEvzq3tCwftJJA3N3Cfv5oB9nUUrB1HOXzeIES-x_rM7IiIbEpJ6AhOSorXVYjdIoOSz_QpkHNcFk=w320-h277" width="320" /></a><a href="https://blogger.googleusercontent.com/img/a/AVvXsEhZp3Daiso92KS-64kotqV2dNCKvuFwGkpsHXH8SaJ0k195acEy2_uQP6I65T0KHinX9hgGbDKJEZFZ-xVANR1d1B5QHeyB8oP5JViQX5bDTwtr_bwjUrleJJUhvpqDX4SQbVgpltbTZhJyvrIJ9x3eRuoEBMGN7Y7BIdidqZIiYy6OntVJuGE=s1368" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1182" data-original-width="1368" height="277" src="https://blogger.googleusercontent.com/img/a/AVvXsEhZp3Daiso92KS-64kotqV2dNCKvuFwGkpsHXH8SaJ0k195acEy2_uQP6I65T0KHinX9hgGbDKJEZFZ-xVANR1d1B5QHeyB8oP5JViQX5bDTwtr_bwjUrleJJUhvpqDX4SQbVgpltbTZhJyvrIJ9x3eRuoEBMGN7Y7BIdidqZIiYy6OntVJuGE=w320-h277" width="320" /></a></div></div><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEilUWd5rBRBCPjHT2vw4dKj_MbIHS5ggLVbLgvsPRfdcicEN6DFtgySAU3GEJOSV4Clap8gmlvvIqs2ZTkO5KQodStd1lWGiuYiBR6LQy26ys6gNrSS_v666moeJUs0ANy66sNBUuMS5uDmtXcIyaplgPgbRcka-1ek8b6fw9seODM3u4PD-YM=s1364" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1186" data-original-width="1372" height="277" src="https://blogger.googleusercontent.com/img/a/AVvXsEiUooDae8pEgzZ7t-E6SZFCnHE1nf2JvR1I0Own0-AdcoaYroT3OabWroLZmVyhDwHZTqPihU9G5dw1-ilk--KXY3fuqkaLT9VsdWtKUNzNkIwSAvtHlomMqdZTK9iTUc915qbSTFcntV6OvahCuQ4B6h-eImJ8DTh04hglyjc0p7hm1m9gnpw=w320-h277" width="320" /></a></div><div class="separator" style="clear: both; text-align: center;"><img border="0" data-original-height="1184" data-original-width="1364" height="278" src="https://blogger.googleusercontent.com/img/a/AVvXsEilUWd5rBRBCPjHT2vw4dKj_MbIHS5ggLVbLgvsPRfdcicEN6DFtgySAU3GEJOSV4Clap8gmlvvIqs2ZTkO5KQodStd1lWGiuYiBR6LQy26ys6gNrSS_v666moeJUs0ANy66sNBUuMS5uDmtXcIyaplgPgbRcka-1ek8b6fw9seODM3u4PD-YM=w320-h278" width="320" /></div><br /><p><br /></p><p>The improvement in image quality at ISO 6400 compared to ISO 400 is significant. </p><h3 style="text-align: left;">Light Pollution</h3><p>With such high ISO, when I take pictures in my backyard in Bortle 7 skies, I get images that appear overexposed due to the high background brightness:</p><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEgY-keoesTUKyeWhiCsMPyb_bkLePHhczTyQXvsyl3MIXb1aT2YE0I74mnx4wXRTbht6EUhNjPzSfbu4d-Ds_0FlTJikEat33la0aZfbpMO_PF9TY6HM2FMKcC9KmmWRLrw3rDRDkZkPgo4wnIHorU0m5u_E3n-5KT0G_guWepUh2pfR7RNOZM=s6000" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="4000" data-original-width="6000" height="213" src="https://blogger.googleusercontent.com/img/a/AVvXsEgY-keoesTUKyeWhiCsMPyb_bkLePHhczTyQXvsyl3MIXb1aT2YE0I74mnx4wXRTbht6EUhNjPzSfbu4d-Ds_0FlTJikEat33la0aZfbpMO_PF9TY6HM2FMKcC9KmmWRLrw3rDRDkZkPgo4wnIHorU0m5u_E3n-5KT0G_guWepUh2pfR7RNOZM=s320" width="320" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Single exposure, high background brightness<br /></td></tr></tbody></table><br /><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEjnokQDg4csoLfSFgDESmKrquMAnZUWi9FsUGgfwmYj6SkKo9u7i2MZqBql0U_BTPEE3ceY45WE3F9qYcVRUxwate7jSTu9Fh-FvX0ZnfA_5wB7HbOfak_0VohhFfN48gEwOUZ7gI1tx9h8P3mk12ywbHe7CDDKP2iJcwBccZ4iVh9EhcW2u6U=s400" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="200" data-original-width="400" height="160" src="https://blogger.googleusercontent.com/img/a/AVvXsEjnokQDg4csoLfSFgDESmKrquMAnZUWi9FsUGgfwmYj6SkKo9u7i2MZqBql0U_BTPEE3ceY45WE3F9qYcVRUxwate7jSTu9Fh-FvX0ZnfA_5wB7HbOfak_0VohhFfN48gEwOUZ7gI1tx9h8P3mk12ywbHe7CDDKP2iJcwBccZ4iVh9EhcW2u6U=s320" width="320" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;">Histogram, plenty of room.<br /></td></tr></tbody></table><br /><p><br /></p><p>Previously I have viewed such images as "unusable". However upon looking at the histogram, it is clear that despite the background brightness, the majority of the signal is properly captured without clipping. Indeed, when post-processed in sirl, the final image does not suffer from the background glow:</p><p></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/a/AVvXsEikFIdPOfY5pes9EXnkf8_lGljl-Ur9w1xJB90Q4Xjh4LI7eMe0lUyRV6TBePklra5mxgq3lQKADpIbLTsxUAsQNs5YjVZUy6Hf_NyrT8f9aG-gdulJ1tUtDOLYNPoTx1tjotjV24CeluUG0hejdbHJJIq7_0H_svuNuXpM_bjfg_Bw1caXjp0=s3129" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2465" data-original-width="3129" height="504" src="https://blogger.googleusercontent.com/img/a/AVvXsEikFIdPOfY5pes9EXnkf8_lGljl-Ur9w1xJB90Q4Xjh4LI7eMe0lUyRV6TBePklra5mxgq3lQKADpIbLTsxUAsQNs5YjVZUy6Hf_NyrT8f9aG-gdulJ1tUtDOLYNPoTx1tjotjV24CeluUG0hejdbHJJIq7_0H_svuNuXpM_bjfg_Bw1caXjp0=w640-h504" width="640" /></a></div>So be not afraid of using high ISO in light polluted skies - as long as the histogram is not clipping the signal is there and can be recovered.<br /><p></p><p><br /></p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-11562866507979202422022-02-19T15:55:00.003+11:002022-02-19T15:55:44.037+11:00GDK/GTK Signal Handling Notes<p> I recently tried my hands at <a href="https://github.com/freespace/toga/commits/sb-dev">implementing motion event support for canvas widgets</a> in <a href="https://beeware.org/project/projects/libraries/toga/">Toga</a> on Linux, which uses GTK3 as its GUI back end. In the process I had learn to navigate GDK's event handling mechanics and documentation. This post is a summary of notes I made during the process.</p><div style="text-align: left;"><h3 style="text-align: left;">Basics</h3></div><div style="text-align: left;">GTK widgets general signals, which you can be notified of if you <span style="font-family: courier;">connect()</span> to the widget by specifying</div><div style="text-align: left;"><ol style="text-align: left;"><li>the name of the signal <br /></li><li>callback to invoke when the event occurs</li></ol><h3 style="text-align: left;">Event Names</h3><p>To find out what signals a widget emits you naturally look at the widget's documentation, e.g. for <span style="font-family: courier;"><a href="https://docs.gtk.org/gtk4/class.DrawingArea.html">DrawingArea</a></span>. However you will quickly realise not <i>all</i> signals are listed. The list does not include signals such as "draw" which is mentioned in <a href="https://athenajc.gitbooks.io/python-gtk-3-api/content/gtk-group/gtkdrawingarea.html">python-gtk-3</a>'s documentation. The actual list of inherited signals can only be seen in the <a href="https://docs.gtk.org/gtk3/class.Widget.html#signals">documentation for <span style="font-family: courier;">Widget</span></a>. Why the disparity? No idea.</p><h3 style="text-align: left;">Event Mask</h3><p>Not that widgets do not emit all possible signals, there is an <a href="https://docs.gtk.org/gdk3/enum.EventType.html">EventMask</a> bitfield that determines which signals a widget will emit. It is not enough to simply <span style="font-family: courier;">connect()</span> to a signal - you must also enable those events you wish to receive if not enabled by default via <span style="font-family: courier;">gtk_widget_add_event()</span>. Note that the relationship between signal names defined and the event-mask required is not explicitly defined. It comes down to guessing the how they are related and trial and error.</p></div><p><br /></p><p><br /></p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-66608835720946437822022-02-09T17:16:00.002+11:002022-02-09T17:16:21.814+11:00Verifying GoTo Mount Settings<p>I recently got a iOptron SmartEQ Pro+ mount and while setting it up I was confused over the time. Should it be local time and then I set the UTC offset in minutes? What do I do with the DST setting?</p><p>One way I found of checking whether my settings is correct is</p><ol style="text-align: left;"><li>Look up the altitude and azimuth coordinates of a bright star like Sirius using a planetarium app</li><li>Command the mount to slew to that star</li><li>On arrival the altitude and azimuth coordinates are displayed on the handset</li><li>Compare the coordinates shown on the handset vs coordinates obtained in step (1). They should match to at least the degree. If not the time and location setting is wrong.</li><li>Tweak settings and repeat from (2) onwards until there is at least degree level agreement between the mount and reference altitude and azimuth coordinates.<br /></li></ol>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-19441487080402381172022-01-02T19:57:00.003+11:002022-01-02T19:57:41.312+11:00Goodbye SpiderOak<p>I have been using SpiderOak One since Edward Snowden recommended it in 2013, almost a decade ago. I have over 1.5T of deduplicated data spread across 6 or so devices. This year, in 2022, I will not be renewing my subscriptions.</p><p>The main issues:</p><ol style="text-align: left;"><li>Lack of updates: the last update to SpiderOak One was in 2019-09. All recent updates have been for CrossClave. It is evident that One is no longer a priority.</li><li>Lack of speed: since day one (ha!) One has always been slower than competitors like Dropbox. In the beginning it wasn't so bad and one must makes some tradeoffs for the security offered. However in recent years this has not improved and setting up a new device takes days if it ever completes the initial synchronisation. Once setup the application is bloated, slow, generates massive amounts of local metadata.<br /></li><li>Lack of control: One installations will randomly stall on sync or update because _another_ device has gone bad. This is not a great situations when I have devices spread across the city.</li></ol><p>To replace SpiderOak One I am currently using:</p><ol style="text-align: left;"><li><a href="https://kopia.io/" target="_blank">Kopia</a> for backup with de-duplication and client-side encryption. The target is backblaze b2.<br /></li><li><a href="http://Sync.com">Sync.com</a> for file sync. Note that Sync.com doesn't provide the same security guarantees as Kopia or SpiderOak, but I am willing to trade that for a sync solution that is fast, quick and affordable.</li><ol><li>There is no native linux client but the Sync.com client runs decently under wine and the performance on my slowest machines are acceptable.</li></ol></ol>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-60264854659113524882021-11-24T02:15:00.002+11:002021-11-24T16:35:49.698+11:00Quick Survey of Some Lightweight Linux Distributions<p style="text-align: left;">On an ASUS E203M <br /></p><h2 style="text-align: left;">Busenlabs Lithium</h2>Installed fine but kernel (4.9?) would immediately shutdown after decrypting the root volume due to incorrect thermal readings. Was not able to disable this via <span style="font-family: courier;">thermal.nocrt=1</span> boot param<br /><h2 style="text-align: left;"> </h2><h2 style="text-align: left;">AntiX 21</h2>Live system did not have working mouse. Did not proceed to installation as I didn't want to be stuck with having to fix the mouse issue. <br /><h2 style="text-align: left;"> </h2><h2 style="text-align: left;">bodhi linux HWE 6.0.0</h2><p>Mouse works in the live system, I like the Enlightenment lineage. No GUI setting to disable tap-to-click on the touchpad, resolved via <a href="https://askubuntu.com/questions/118892/how-do-i-disable-touchpad-tap-to-click" target="_blank"><span style="font-family: courier;">synclient MaxTapTime=0</span></a> so not a deal breaker. However despite being lightweight there was noticable GUI lag when running the installer. </p><h2 style="text-align: left;"> </h2><h2 style="text-align: left;">Q4OS Gemini, Trinity<br /></h2><p>I like the idea of Trinity Desktop and they are using a decently recent kernel as well (5.10). Installed fine but wifi doesn't connect to the 5G network. Worked fine on 2.4G. Had an annoying issue where Alt-Space didn't work, giving me ISO_Next_Group. Fixed it by setting via xkb options to use "both ctrl at the same time" to switch languages which then allowed alt-space to work as intended.<br /></p><p>Systems feels really snappy and the retro look is not bad. Sticking with this one for now.<br /></p>Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-55451769561840195332019-12-14T01:37:00.001+11:002019-12-14T01:38:32.869+11:00How *Not* to Play with Programmable LED Strips<h2>
You Need That Resistor </h2>
That resistor on the data line? Yeah you need it. Otherwise you might blow an LED which renders the entire rest of the strip useless. If that happens cut out the first LED and solder the power and data lines directly to the second LED.<br />
<br />
<h2>
You Want Shorter, Thicker, Wires</h2>
Using jumper wires, of the 300-for-$5 variety is fine for a few LEDs. If however you have 300 LED drawing around 1A then those thin wires have non-negligible voltage drop. For me this was on the order of 0.7V or more. This means even though my power supply was putting out 5V the LED strip was only seeing 4.3V, causing flickering of the LEDs. <br />
<br />
For any piece of wire the voltage drops increases with current simply because of V=IR. Thicker wires have less resistance per unit length and therefore less voltage drop per unit length.Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-51621399879341225682019-11-12T18:20:00.001+11:002021-11-16T13:10:31.350+11:00The Subtle Poison of Religion On the 12th of November 2019, Nationals MP Barnaby Joyce said on TV that:<br />
<blockquote class="tr_bq">
I acknowledge that the two people who died were most likely people who voted for the Green party, so I am not going to start attacking them. That's the last thing I want to do.</blockquote>
Why does the politics of the deceased matter and why would Mr. Joyce make such a speculation? I can't help but think that Mr. Joyce did it because, on some level, he thinks those people deserve it. I think this is the subtle poison of religion: that those who do not believe as I do deserve less than I do.<br />
<br />
This idea is widespread across all variants of Christianity: you are saved if you believe in God and Jesus and the Holy Spirit but damned if you don't. You deserve salvation only if you Believe. It is this idea that motivates the Evangelicals: they must Save you by spreading their Belief so you, too, deserve salvation. It is this idea that underpins the prosperity gospel: those who Believe is deserving of wealth and therefore the harder you Believe, whether by praying harder or donating more to the Church, the more you deserve wealth. Conveniently if you are wealthy then obviously it is because you deserve it due to your faith.<br />
<br />
Once learned and integrated into one's world view via religious instruction, this idea, that those who do not believe as I do deserve less, poisons the lens through which an individual interacts with the world. When a core part of your identify requires you to accept that, on the basis of belief alone, not everyone is equal, then it is a small step to thinking that those who hold different political beliefs deserve less then those whose beliefs align with yours. Maybe they deserve less sympathy. Maybe they deserve less government support. Maybe they deserve less compassion or concession. Whatever the case may be, on the basis of their political belief, they are Other and they are Undeserving -- and in politics this is a problem.<br />
<br />
Some would claim that it is possible to separate one's religious beliefs from one's political actions. I reject such claims in the same way I reject any claims one can be racist and still be a fair judge. Some would claim that some people think thusly even without religion and I would agree. However some religions <u>requires</u> such thinking. Some would say not all religions features undeserving unbelievers and claim my title is inaccurate and I would concede their point but also point out that the major religions do not fall within this category.Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-88766671477702100232019-06-24T12:19:00.001+10:002021-11-16T13:12:22.549+11:003D Printing at Home<h2>
FlashForge Creator Pro</h2>
I finally got my own 3D printer, a <a href="http://www.flashforge.com/creator-pro-3d-printer/" target="_blank">FlashForge Creator Pro</a>, during the EOFY sale. My choices were between the Creator Pro or the Up Mini 2 ES with the build volume of the Creator Pro being the deciding factor. <br />
<br />
Had bit of a rocky start with bed leveling but nothing a bit of patience won't fix. It prints reliably now though I have plans for a semi-assisted bed leveling jig.<br />
<br />
<h2>
Designs</h2>
Over the past week I have worked on and off on an<a href="https://www.thingiverse.com/thing:3710082" target="_blank"> iPad mini holder</a> to position it above my monitor so I can use it as a status screen or as a monitor to watch twitch while I am doing menial tasks.<br />
<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://1.bp.blogspot.com/-4IozKscR4X0/XRAy2HsFRcI/AAAAAAAAfKE/RhSshFIihK4A_cjWLR85fzEV2DsgQQnFgCLcBGAs/s1600/2019-06-23%2B18.35%2B%25281%2529.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1200" data-original-width="1600" height="240" src="https://1.bp.blogspot.com/-4IozKscR4X0/XRAy2HsFRcI/AAAAAAAAfKE/RhSshFIihK4A_cjWLR85fzEV2DsgQQnFgCLcBGAs/s320/2019-06-23%2B18.35%2B%25281%2529.jpg" width="320" /></a></div>
<br />
I also made a<a href="https://www.thingiverse.com/thing:3710023" target="_blank"> small headphone hanger</a> to save a bit of space.<br />
<br />
<div class="separator" style="clear: both; text-align: center;">
<a href="https://1.bp.blogspot.com/-8ajhyt87BKg/XRAy9MI0GNI/AAAAAAAAfKI/YtpNXXyNEac4qeN34hDeJYyCuEsQf4SbQCLcBGAs/s1600/2019-06-24%2B03.03.jpg" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="1600" data-original-width="1200" height="320" src="https://1.bp.blogspot.com/-8ajhyt87BKg/XRAy9MI0GNI/AAAAAAAAfKI/YtpNXXyNEac4qeN34hDeJYyCuEsQf4SbQCLcBGAs/s320/2019-06-24%2B03.03.jpg" width="240" /></a></div>
<br />
<br />
Both of these designs were made in Fusion360, my first with the software. Normally I use blender because that's what I comfortable with but the Fusion brings a lot to the table and I will be using it going forward. It doesn't hurt that experience and skills with Fusion will be useful in an industrial setting.<br />
<br />
Next on the list is some replacement end-stops for a wall hanging and a keypad bruteforcer.Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-79547827366597973122018-08-21T18:54:00.002+10:002019-06-24T12:20:32.729+10:00T102HAAS.303 Considered Harmful For Linux<h1>
<code>T102HAAS.303</code> Breaks Suspend</h1>
<br />
After upgrading my Asus Transformer Mini's BIOS to <code>T102HAAS.303</code> suspend was <b>completely</b> broken. Closing the "lid" would cause some kind of suspend that cannot be disabled in software and from which Linux 4.15.0 cannot successfully resume from (actually it does resume but the display will stay blank).<br />
<br />
This behaviour cannot be disabled in software by editing <code>logind.conf</code> or <code>acpi-support</code> or any of the solutions found on the web about disabling lid action. Messing about with <code>acpi_osi</code> didn't help either.<br />
<br />
<h1>
Downgrading from <code>T102HAAS.303</code></h1>
<br />
If you are reading this after upgrading to <code>T102HAAS.303</code> you probably want to downgrade. Unfortunately the firmware that ships with the computers, version 202, cannot be found on the Asus website. You can however find the 300 firmware if you click on "View all downloads" under the BIOS section. Download this file and put it on a FAT32 formatted USB drive then:<br />
<br />
<ol>
<li>Reboot, hold then ESC to enter Setup</li>
<li>Find the Easy Update entry and press ENTER, starting the easy update program</li>
<li>Navigate to your USB drive, it will be FS0 or FS1</li>
<li>Locate the <code>T102HAAS.303</code> file and press ENTER</li>
<li>When the dialogue complains that the build date is too old type the word <b>risky</b> on the keyboard</li>
<li>Select Yes on the dialogue that appears after</li>
<li>Wait for the computer to reboot</li>
</ol>
<br />
The key to this process is the word <b>risky</b> which is an undocumented feature that by-passes the build date check, allowing you to downgrade. You just type this in when the error dialogue appears, there will be no text box or anything.<br />
<br />
<h1>
Re-enabling Hibernation</h1>
<br />
Downgrading will re-enable Secure Boot, which disables hibernation on Linux. Just disable it and hibernation will work again.<br />
<br />Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.comtag:blogger.com,1999:blog-5867400.post-40747799144689232032018-08-06T00:51:00.001+10:002019-06-24T12:20:19.518+10:00Ubuntu 18.04 on Asus Transformer Mini (T102H)<h2>
Installation</h2>
<br />
Create a USB drive with a single FAT32 partition then extract the installation ISO into it using <code>7z</code>:<br />
<br />
<pre>7z x /path/to/ISO -o/path/to/usb</pre>
<br />
Note that there is no space between <code>-o</code> and the following path.<br />
<br />
Plug in the USB drive then turn on the T102H while pressing the <code>ESC</code> key. This will allow you to enter the settings menu and allow you to boot from USB. Select installation and follow the instructions until asked to reboot.<br />
<br />
<h2>
Xorg Setup</h2>
<br />
An immediate problem is that the display is portrait by default. Additionally the modesetting driver is used which has worse performance than the intel driver. Fix both of these issue by placing the following file in <code>/usr/share/X11/xorg.conf.d/99-transformer.conf</code>:<br />
<br />
<pre>Section "Device"
Identifier "i915"
Driver "intel"
Option "TearFree" "true"
Option "DRI" "2"
Option "Backlight" "intel_backlight"
EndSection
Section "Screen"
Identifier "Screen0"
Monitor "BuiltInLCD"
EndSection
Section "Monitor"
Identifier "BuiltInLCD"
Option "Rotate" "right"
EndSection
Section "InputClass"
Identifier "BuiltInTouchscreen"
MatchProduct "ELAN22A6:00 04F3:22A6"
Option "TransformationMatrix" "0 1 0 -1 0 1 0 0 1"
EndSection
</pre>
<br />
This sets the display driver to <code>intel</code>, rotates the monitor, and also transforms touchscreen inputs to match the landscape orientation.<br />
<br />
<h3>
i915</h3>
To further improve performance place the following into <code>/etc/modprobe.d/i915.conf</code><br />
<pre>options i915 enable_fbc=1 enable_guc=3 enable_psr=1 disable_power_well=0 semaphores=1
</pre>
<br />
<h2>
Backlight</h2>
<br />
Out of the box backlight doesn't work because of <a href="https://bugs.freedesktop.org/show_bug.cgi?id=96571">a module loading order issue [96571]</a>. The easiest fix, found in the bug report thread, is to use <code>dracut</code> to remove the <code>i915</code> module from <code>initramfs</code> so it loads after the PWM modules.<br />
<br />
<pre>sudo apt install dracut
sudo dracut -f --omit-drivers="i915"
sudo update-grub
</pre>
<br />
This issue may be fixed in a later release as <a href="https://bugs.launchpad.net/ubuntu/+source/linux/+bug/1783964">the issue has been reported to Ubuntu</a>.<br />
<br />
After rebooting <code>/sys/class/backlight/intel_backlight/</code> should exist, indicating that backlight control is available.<br />
<br />
<h3>
Keyboard Backlight Control</h3>
<br />
Unfortunately while we can now control the backlight using programs like <code>xbacklight</code>, the screen brightness keys (fn+F5 and fn+F6) don't work. We can get around this by binding control-F5 and control-F6 to trigger <code>xbacklight -dec 20</code> and <code>xbacklight -inc 20</code> respectively to decrement/increment screen brightness by 20% per keyboard press.<br />
<br />
<h2>
Airplane Mode</h2>
<br />
Similar to the backlight control buttons the airplane mode button also doesn't work. The following script uses <code>rfkill</code> to toggle bluetooth and wifi on/off, effectively implementing airplane mode in software. I haven't found a way to disable bluetooth and wifi in hardware.<br />
<br />
<pre>#!/bin/bash
BLUETOOTH_OFF_BY_DEFAULT=1
n_devices="$(rfkill -n | wc -l)"
n_blocked="$(rfkill -n | grep -w blocked | wc -l)"
echo "$n_devices devices, $n_blocked blocked"
if [ "$n_blocked" == "$n_devices" ]; then
rfkill unblock bluetooth wlan
if [ "$BLUETOOTH_OFF_BY_DEFAULT" == "1" ]; then
rfkill block bluetooth
fi
else
rfkill block bluetooth wlan
fi
</pre>
<br />
<h2>
Power Saving</h2>
<br />
It is a good idea to install <code>tlp</code> to improve the running time<br />
<br />
<h2>
TODOs:</h2>
<ul>
<li>Script and keybindings to rotate the screen and touchscreen</li>
<li>Pressure level with the pen</li>
</ul>
Stevehttp://www.blogger.com/profile/08905624839178001596noreply@blogger.com