Digikam is an incredibly powerful media management tool that integrates a great collection of powerful media processing projects into a single, fairly nice and moderately intuitive user interface. The problem is that it make use of SO many projects and libraries that installation is quite fragile and most distributions are many years out of date – that is a typical
sudo apt install digikam will yield version 4.5 while release is (as of this writing) 7.2.
In particular, this newer version has face detection that runs LOCALLY – not on Google or Facebook’s servers – meaning you don’t have to trade your personal photos and all the data implicit in them to a data broker to make use of such a useful tool. Sure, Google once bought and then improved Picasa Desktop which gave you this function, but then they realized this was cutting into their data harvesting business and discontinued Picasa and tried to convince people to let them look at all their pictures with Google Photos. We really, really need to make personal data a toxic asset, such an intolerable liability that any company that holds any personal data has negative value. But until then, use FOSS software on your own hardware where ever possible.
You can compile the latest version on Ubuntu 20.04 Focal Fossa, though not exactly painlessly, or you can install the flatpak easily. I hate flatpaks with a passion, so I went through the exercise and found what appears to be stable success with the following procedure which yielded a fully featured digikam with zero dependency errors or warnings and all features enabled using MariaDB as a backend.
Install and configure MariaDB
sudo apt update sudo apt install mariadb-server sudo mysql_secure_installation
The secure options are all good, accept them unless you know better.
Start the server (if it isn’t)
sudo systemctl start mariadb.service sudo systemctl enable mariadb --now sudo systemctl status mariadb.service
Do some really basic config:
sudo nano /etc/mysql/mariadb.conf.d/50-server.cnf
character-set-server = utf8mb4 collation-server = utf8mb4_general_ci default_storage_engine = InnoDB
Switch to mariadb and create an admin user account and (I’d suggest) one for digikam. It seems this has to be done before the first connect and can’t be fixed after. You’ll probably want to use a different ‘user’ than I did, but feel free.
sudo mariadb CREATE USER 'gessel'@'localhost' IDENTIFIED BY 'password'; GRANT ALL ON *.* TO 'gessel'@'localhost' IDENTIFIED BY 'password'; CREATE DATABASE digikam; GRANT ALL PRIVILEGES ON digikam.* TO 'gessel'@'localhost'; FLUSH PRIVILEGES;
should correctly create the correct user – though check the instructions tab on the database connection options pane for any changes if you’re following these instructions for install of a later version. You will need the socket location to connect to the database so before
mysqladmin -u admin -p version
Should yield something like:
Enter password: mysqladmin Ver 9.1 Distrib 10.3.25-MariaDB, for debian-linux-gnu on x86_64 Copyright (c) 2000, 2018, Oracle, MariaDB Corporation Ab and others. Server version 10.3.25-MariaDB-0ubuntu0.20.04.1 Protocol version 10 Connection Localhost via UNIX socket UNIX socket /var/run/mysqld/mysqld.sock Uptime: 5 hours 26 min 6 sec Threads: 29 Questions: 6322899 Slow queries: 0 Opens: 108 Flush tables: 1 Open tables: 74 Queries per second avg: 323.157
And note the value for
UNIX socket, you’re going to need that later:
/var/run/mysqld/mysqld.sock – yours might vary.
Install digiKam Dependencies
- Updated to libx264-161 and libx265-199
- Added libopencv-dev dependency
- Version change from 7.2.0 to 7.3.0
Digikam has just a few dependencies.… just a few... the below command should install the needed for 7.30 on Ubuntu 20.04. Any other version combination might be different.:
sudo aptitude install \ bison \ checkinstall \ devscripts \ doxygen \ extra-cmake-modules \ ffmpeg \ ffmpegthumbnailer \ flex \ graphviz \ help2man \ jasper \ libavcodec-dev \ libavdevice-dev \ libavfilter-dev \ libavformat-dev \ libavutil-dev \ libboost-dev \ libboost-graph-dev \ libeigen3-dev \ libexiv2-dev \ libgphoto2-dev \ libjasper-dev \ libjasper-runtime \ libjasper4 \ libjpeg-dev \ libkf5akonadicontact-dev \ libkf5calendarcore-dev \ libkf5contacts-dev \ libkf5doctools-dev \ libkf5filemetadata-dev \ libkf5kipi-dev \ libkf5notifications-dev \ libkf5notifyconfig-dev \ libkf5sane-dev \ libkf5solid-dev \ libkf5threadweaver-dev \ libkf5xmlgui-dev \ liblcms2-dev \ liblensfun-dev \ liblqr-1-0-dev \ libmagick++-6.q16-dev \ libmagick++-6.q16hdri-dev \ libmagickcore-dev \ libmarble-dev \ libqt5opengl5-dev \ libqt5sql5-mysql \ libqt5svg5-dev \ libqt5webkit5-dev \ libqt5webview5 \ libqt5webview5-dev \ libqt5x11extras5-dev \ libqt5xmlpatterns5-dev \ libqtav-dev \ libqtwebkit-dev \ libswscale-dev \ libtiff-dev \ libusb-1.0-0-dev \ libx264-161 \ libx264-dev \ libx265-199 \ libx265-dev \ libxml2-dev \ libxslt1-dev \ marble \ pkg-kde-tools \ qtbase5-dev \ qtbase5-dev-tools \ qtmultimedia5-dev \ qtwebengine5-dev \ libopencv-dev \ qtwebengine5-dev-tools
Switch to your projects directory (
~/projects, say) and get the source, cross your fingers, and go to town. The
make -j4 command will take a while to compile everything. There are two basic mechanisms for getting the source code:
wget the taball or
git pull the repository.
Download the tarball
Check the latest version at https://download.kde.org/stable/digikam/ It was 7.2.0, but is now 7.3.0 and will, certainly change again. This is currently a 255.3 MB download (!).
wget https://download.kde.org/stable/digikam/7.3.0/digikam-7.3.0.tar.xz tar -xvf digikam-7.3.0.tar.xz cd digikam-7.3.0.tar.xz
git pull the repository
Git uses branches/tags so check the pull down list of latest branches and tags at the top left, below the many, many branches is the tag list at https://invent.kde.org/graphics/digikam/-/tree/v7.3.0 , latest on top, and currently 7.3.0. This is currently a 1.4 GB git pull (!!).
There was an issue in the v7.3.0 tag that caused built to fail that was fixed in current, so building “stable” isn’t always the best choice for stability.
git clone -b v7.3.0 https://invent.kde.org/graphics/digikam.git cd digikam
Then follow the same steps:
./bootstrap.linux cd build make -j4 su make install/fast
Compiling might take 15-30 minutes depending on CPU. Adjust
-jx to optimize build times, the normal rule of thumb is that x=# of cores or cores+1, YMMV, 4 is a reasonable number if you aren’t confident or interested in experimenting.
The ./bootstrap.linux result should be as below; if it indicates a something is missing then double check dependencies. If you’ve never compiled anything before, you might need to install cmake and and some other basics not in the
apt install list above:
-- ---------------------------------------------------------------------------------- -- digiKam 7.2.0 dependencies results <https://www.digikam.org> -- -- MySQL Database Support will be compiled.. YES (optional) -- MySQL Internal Support will be compiled.. YES (optional) -- DBUS Support will be compiled............ YES (optional) -- App. Style Support will be compiled...... YES (optional) -- QWebEngine Support will be compiled...... YES (optional) -- libboostgraph found...................... YES -- libexiv2 found........................... YES -- libexpat found........................... YES -- libjpeg found............................ YES -- libkde found............................. YES -- liblcms found............................ YES -- libopencv found.......................... YES -- libpng found............................. YES -- libpthread found......................... YES -- libqt found.............................. YES -- libtiff found............................ YES -- bison found.............................. YES (optional) -- doxygen found............................ YES (optional) -- ccache found............................. YES (optional) -- flex found............................... YES (optional) -- libakonadicontact found.................. YES (optional) -- libmagick++ found........................ YES (optional) -- libeigen3 found.......................... YES (optional) -- libgphoto2 found......................... YES (optional) -- libjasper found.......................... YES (optional) -- libkcalendarcore found................... YES (optional) -- libkfilemetadata found................... YES (optional) -- libkiconthemes found..................... YES (optional) -- libkio found............................. YES (optional) -- libknotifications found.................. YES (optional) -- libknotifyconfig found................... YES (optional) -- libksane found........................... YES (optional) -- liblensfun found......................... YES (optional) -- liblqr-1 found........................... YES (optional) -- libmarble found.......................... YES (optional) -- libqtav found............................ YES (optional) -- libthreadweaver found.................... YES (optional) -- libxml2 found............................ YES (optional) -- libxslt found............................ YES (optional) -- libx265 found............................ YES (optional) -- OpenGL found............................. YES (optional) -- libqtxmlpatterns found................... YES (optional) -- digiKam can be compiled.................. YES -- ----------------------------------------------------------------------------------
Launch and configure Digikam
The Configuration options are pretty basic, but note that to configure the Digikam back end you’ll need to use that MariaDB socket value you got before and the user you created like so
On the first run, it will download about 350mb of code for the face recognition engine. Hey – maybe a bit heavy, but you’re not giving the Google or Apple free lookie looks at all your personal pictures. Also, if all this is a bit much (and, Frankly, it is) I’d consider Digikam one of the few applications that makes the whole flatpak thing seem somewhat justified. Maybe.
Some advice on tuning:
Tuning a database is application and computer specific, there’s no one size fits any, certainly not all, and it may change as your database grows. There are far more expert and complete tuning guides available, but here’s what I do:
Pre-Tuning Data Collection
Tuning at the most basic involves instrumenting the database to log problems, running it for a while, then parsing the performance logs for useful hints. The mysqltuner.pl script is far more expert at than I’ll ever be, so I pretty much just trust it. You have to modify your mysqld.cnf file to enable performance data collection (which, BTW, slows down operation, so undo this later) which for MariaDB means adding a few lines:
sudo nano /etc/mysql/mariadb.conf.d/50-server.cnf # enable performance schema to allow optimization, but ironically hit performance, so disable after tuning. # in the [mysqld] section insert performance_schema=ON performance-schema-instrument='stage/%=ON' performance-schema-consumer-events-stages-current=ON performance-schema-consumer-events-stages-history=ON performance-schema-consumer-events-stages-history-long=ON
Follow the instructions for installing mysqltuner.pl at https://github.com/major/MySQLTuner-perl#downloadinstallation
I rather like this guide’s helpful instructions for putting the script in /usr/local/sbin/ so it is in the execution path:
sudo wget https://raw.githubusercontent.com/major/MySQLTuner-perl/master/mysqltuner.pl -O /usr/local/sbin/mysqltuner.pl sudo chmod 700 /usr/local/sbin/mysqltuner.pl sudo mysqltuner.pl
Then restart with
sudo service mariadb restart then go about your business with digikam – make sure you rack up some real hours to gather useful data on your performance. Things like ingesting a large collection should generate useful data. I’d suggest doing disk tuning first because that’s hardware not load dependent.
Databases tend to hammer storage and SSDs, especially SLC/enterprise SSDs, massively improve DB performance over spinning disks – unless you have a massive array of really good ones. I’m running this DB on one spinning disk, so performance is very MEH. MySQL and MariaDB make some assumptions about disk performance which is used to scale some pretty important parameters for write caching. You can meaningfully improve on the defaults by testing your disk with a great linux utility called “fio”.
sudo apt install fio fio --randrepeat=1 --ioengine=libaio --direct=1 --gtod_reduce=1 --name=test --filename=test --bs=4k --iodepth=64 --size=4G --readwrite=randrw --rwmixread=75
This will take a while and will give some very detailed information about the performance of your disk subsystem, the key parameters being average and max write IOPS. I typically create a
# performance tuning section at the end of my
[mysqld] section and before
[embedded] and I’ll put these values in as, say: (your IOPS values will be different):
# performance tuning innodb_io_capacity = 170 innodb_io_capacity_max = 286
sudo service mariadb restart
After you’ve collected some data, there may be a list of tuning options.
sudo nano /etc/mysql/mariadb.conf.d/50-server.cnf
Mine currently look like this, but they’ll change as the database stabilizes and my usage patterns change.
# performance tuning innodb_io_capacity = 170 innodb_io_capacity_max = 286 innodb_stats_on_metadata = 0 innodb_buffer_pool_size = 4G innodb_log_file_size = 512M innodb_buffer_pool_instances = 4 skip_name_resolve = 1 query_cache_size = 0 query_cache_type = 0 query_cache_limit = 2M max_connections = 175 join_buffer_size = 4M tmp_table_size = 24M max_heap_table_size = 24M innodb_buffer_pool_size = 4G max_allowed_packet = 128M
sudo service mariadb restart
max_allowed_packet = 128M comes from this guide. I trust it, but it isn’t a mysqltuner suggestion.
A “fun” part of organizing an MP3 collection is harmonizing the tags so the datas work consistently with whatever management schema you prefer. My preference is management by the file system—genre/artist/year/album/tracks works for me—but consistent metainformation is required and often disharmonious. Finding metaharmony is a chore I find less taxing with a well structured tag editor and to my mind the ur-meta-tag manager is MP3TAG.
The problem is that only works with that dead-end spyware riddled failing legacyware called “Windows.” Fortunately, in Linux-land we have puddletag, a very solid clone of MP3TAG. The issues is that the version in repositories is (as of this writing) 1.20 and I couldn’t find a PPA for the latest, 2.0.1. But compiling from source is super easy and works in both Linux Mint 19 and Ubuntu 20.04 (yay open source!):
- Install pre-reqs to build (don’t worry, if they’re installed, they won’t be double installed)
- get the tarball of the source code
- expand it (into a reasonable directory, like ~/projects)
- switch into that directory
- run the python executable “puddletag” directly to verify it is working
- install it
- tell the desktop manager it’s there – and it should be in your window manager along with the rest of your applications.
The latest version as of this post was 2.0.1 from https://github.com/puddletag/puddletag
sudo apt install python3-pyqt5 python3-pyqt5.qtsvg python3-pyparsing python3-mutagen python3-acoustid libchromaprint-dev libchromaprint-tools libchromaprint1 wget href="https://github.com/puddletag/puddletag/releases/download/2.0.1/puddletag-2.0.1.tar.gz tar -xvf puddletag-2.0.1.tar.gz cd puddletag-2.0.1/ cd puddletag ./puddletag sudo python3 setup.py install sudo desktop-file-install puddletag.desktop
A nice feature is the configuration directory is portable and takes your complete customization with you – it is an extremely customizable program so you can generally configure it as fits your mental model. Just copy the entire puddletag directory located at
Rsync is a great tool – incredibly powerful for synchronizing directories, copying over a network or over SSH, an awesome way to backup a mobile device back to a core network securely and other great functions. it works better than just about anything else developed before or since, but is a command line UI that is easy to forget if you don’t use it for a while and Windows is a challenge.
This isn’t meant to be a comprehensive guide, they’re are lots of those, but a quick summary of what I find useful.
There’s one confusing thing that I have to check often to be sure it is going to do what I think it should – the trailing slash on the source. It works like this:
A quick summary of useful command options (there are many, many) is:
-v, --verbose increase verbosity -r, --recursive recursive (go into subdirectories) -c, --checksum skip based on checksum, not mod-time & size (slow, but accurate) -a, --archive archive mode; equals -rlptgoD (no -H,-A,-X) (weird with SMB/CIFS) -z, --compress compress file data during the transfer, should help over slow links -n, --dry-run trial run, don't move anything -h, --human-readable display the output numbers in a human-readable format -u, --update only copy files that have different sizes and equal or later modification times (-c will enable checksum comparison) --progress show the sync progress during transfer --exclude ".*" exclude files starting with "." --remove-source-files after synced, empty the dir (like mv/merge) --delete any files in dest that aren't in source are deleted in destination (danger) --info=progress2 --info=name0 This yields a pretty usable one line progress meter.
I do not recommend using compression (
-z) on a LAN, it’ll probably slow you down. Over a slower (typically) WAN link it usually helps, but YMMV depending on link and CPU speed. Test it with that one line progress meter if it is a long enough sync to matter – it shows transfer rate a little like this:
1,770,984,121 2% 747.54kB/s 27:46:38 xfr#2159, ir-chk=1028/28648)
If the files really have to be accurately transferred, the checksum (
-c) option is critical – every copy (or at least “move”) function should include this validation, especially before deleting the original.
Some of the coding tricks in H.265 have been incorporated into MPEG-H coding, an ISO standard introduced in 2017, which yields a roughly 2:1 coding efficiency gain over the venerable JPEG, which was introduced in 1992. Remember that? I do; I’m old. I remember having a hardware NUBUS JPEG decoder card. One of the reasons JPEG has lasted so long is that images have become a small storage burden (compared to 4k video, say) and that changing format standards is extremely annoying to everyone.
Apple has elected to make every rational person’s life difficult and put a little barbed wire around their high-fashion walled garden and do something a little special with their brand of a HEVC (h.265) profile for images. Now normally seeing iOS user’s insta images of how fashionable they are isn’t really worth the effort, but now and then a useful correspondent joins the cult and forks over a ton of money to show off a logo and starts sending you stuff in their special proprietary format. Annoying, but fixable.
$ sudo add-apt-repository ppa:jakar/qt-heif $ sudo apt update $ sudo apt install qt-heif-image-plugin
I noticed that my avocado tree was developing brown spots on the leaves, which were almost certainly the result of Persea mites.
So I looked up some possible cures, and it seemed like introducing a predator would be the best option and the least hassle. I’d had good luck with introduced ladybugs a few years back, which formed a stable population that survived for many years after introduction. For this pest, green lacewings are recommended. I found a nearby insectary that could provide larvae on cards and they shipped them overnight.
The little guys look cute just waiting to hatch…
I hung he cards on the leaves of the tree after incubating them overnight in a warm room, and they should hatch sometime in the next day or two, as long as the ants don’t find them first…
Update 8 Sept 2016:
The green lacewings seem to have eaten all the mites. It has been 9 months and there aren’t any signs of damage to this spring’s leaves. Yay!
The new leaves that grew seem to be developing without any bites at all. The old leaves that were too damaged have fallen off, but the surviving older leaves still show the scars of the mites. Green lacewings seem to have done the trick.
Signal is an easy to use chat tool that competes (effectively) with What’sApp or Viber. They’ve just released a desktop version which is being “preview released/buzz generating released.” It is developed by a guy with some cred in the open source and crypto movement, Moxie Marlinspike. I use it, but do not entirely trust it.
I’m not completely on board with Signal. It is open source, and so in theory we can verify the code. But there’s some history I find disquieting. So while I recommend it as the best, easiest to use, (probably) most secure messaging tool available, I do so with some reservations.
- It originally handled encrypted SMS messages. There is a long argument about why they broke SMS support on the mailing lists. I find all of the arguments Whisper Systems made specious and unconvincing and cannot ignore the fact that the SMS tool sent messages through the local carrier (Asiacell, Korek, or Zain here). Breaking that meant secure messages only go through Whisper Systems’ Google-managed servers where all metadata is captured and accessible to the USG. Since it was open source, that version has been forked and is still developed, I use the SMSSecure fork myself
- Signal has captured all the USG funding for messaging systems. Alternatives are not getting funds. This may make sense from a purely managerial point of view, but also creates a single point of infiltration. It is far easier to compromise a single project if there aren’t competing projects. Part of the strength of Open Source is only achieved when competing development teams are trying to one up each other and expose each other’s flaws (FreeBSD and OpenBSD for example). In a monoculture, the checks and balances are weaker.
- Signal has grown more intimate with Google over time. The desktop version sign up uses your “google ID” to get you in the queue. Google is the largest commercial spy agency in the world, collecting more data on more people than any other organization except probably the NSA. They’re currently an advertising company and make their money selling your data to advertisers, something they’re quite disingenuous about, but the data trove they’ve built is regularly mined by organizations with more nefarious aims than merely fleecing you.
What to do? Well, I use signal. I’m pretty confident the encryption is good, or at least as good as anything else available. I know my metadata is being collected and shared, but until Jake convinces Moxie to use anonymous identifiers for accounts and message through Tor hidden nodes, you have to be very tech savvy to get around that and there’s no Civil Society grants going to any other messaging services using, for example, an open standard like a Jabber server on a hidden node with OTR.
For now, take a half step up the security ladder and stop using commercial faux security (or unverifiable security, which is the same thing) and give Signal a try.
Maybe at some later date I’ll write up an easy to follow guide on setting up your own jabber server as a tor hidden service and federating it so you can message securely, anonymously, and keep your data (meta and otherwise) on your own hardware in your own house, where it still has at least a little legal protection.
My kitchen has had halogen lighting for 20 years, from back when it was a slightly more efficient choice than incandescent lighting and had a pleasing, cooler (bluer, meaning the filament runs hotter) color temperature.
Progress has moved on and while fluorescent lights still have a lead in maximum luminous efficacy (lm/w), for example the GE Ecolux Watt-Miser puts out 111 lm/W, they’re less versatile than LEDs and installation is a hassle while low voltage LEDs are easy to install and look cool.
The goal of this project was to add dimmable, pleasing light to the kitchen that I found aesthetically interesting. I wanted a decent color rendering index (CRI), ease of installation, and at reasonable cost. I’ve always liked the look of cable lighting and the flexibility of the individual, adjustable luminaires.
I couldn’t find much information on how variable output LEDs work and what can be used to drive them. I have a pretty good collection of high quality power supplies, which I wanted to take advantage of, but wasn’t sure if I’d be able to effectively dim the bulbs from the documentation I found. So I did some tests.
I bought a few different 12V, Dimmable LEDs and set up a test configuration to verify operation and output with variable voltage and variable current. The one bit of data I had was that using standard commercial controllers, the lowest output is typically stated to be around 70% of maximum output: that is the dimming range is pretty limited with standard (PWM/Transformer) controllers. The results I found were much more encouraging, but revealed some quirks.
I used a laboratory-grade HP power supply with voltage and current control to drive the LEDs, decent multimeters to measure voltage and current, and an inexpensive luminance meter to measure LED output.
I measured 3 different LEDs I selected based on price and expected compatibility with the aesthetics of the project and because they looked like they’d have different internal drivers and covered a range of rated wattage.
These bulbs have internal LED controllers that do some sort of current regulation for the diodes that results in a weird voltage/current/output response. Each bulb has a different turn-on voltage, then responds fairly predictably to increasing input voltage with increasing output, reaches the controller stabilizing voltage and runs very inefficiently until voltage gets over the rated voltage and then becomes increasingly efficient until, presumably, at some point the controller burns out. I find that the bulbs all run more efficiently at 14V than at the rated 12V.
As a side note, to perform the data analysis, I used the excellent
xongrid plugin for excel to perform Kriging interpolation (AKA Gaussian process regression) to fit the data sets to the graphing function’s capabilities. The graphs are generated with WP-Charts and the table with TablePress.
Watts v. Volts
This chart shows the wattage consumed by each of the three LEDs as a function of input voltage, clearly demonstrating both that the power consumption function is non-linear and that power consumption in watts improves when driven over the rated 12V. Watts are calculated as the product of the measured Volts * Amps. Because of the current inversion that happens as the controllers come fully on-line, these LEDs can’t be properly controlled near full brightness with a current-controlled power supply, though it works well to provide continuous and fairly linear dimming at low outputs, once the voltage/current function changes slope, the current limiting controller in the power supply freaks out.
4W LED 5W LED 7.5W LED
Lux v. Volts
This chart shows the lux output by each of the three LEDs as a function of input voltage, revealing the effect of the internal LED driver coming on line and regulating output, which complicates controlling brightness but protects the LEDs. The 5W LEDs have a fairly gentle response slope and start a very low voltage (2V) so are a good choice for a linear power supply. The 4W LEDs don’t begin to light up until just over 6V, and so are a good match for low-cost switch mode supplies that don’t go to zero.
4W LED 5W LED 7.5W LED
Lux/W v. Volts
This chart shows the luminous efficiency (Lux/Watt, Lumen measurement is quite complicated) by each of the three LEDs as a function of input voltage, showing that overdriving the LEDs past the rated 12V can significantly improve efficiency. There’s some risk it will overheat the controller at some point and result in failure. I’ll update this post if my system starts to fry LEDs, but my guess is that 14V, which cuts the power load by 20% over 12V operation with the 7.5W lamps I selected, will not significantly impact operational lifetime.
4W LED 5W LED 7.5W LED
Total System Efficiency
The emitter efficiency is relatively objective, but the total system efficiency includes the power supply. I used a Daiwa SS-330W switching power supply I happened to have in stock to drive the system, which cost less than a dimmable transformer and matching controller, and should be significantly higher quality. The Daiwa doesn’t seem to be easily available any more, but something like this would work well for up to 5A total load and something like this would handle as many as 40 7.5W LEDs on a single control, though the minimum 9V output has to be matched to LEDs to get satisfactory dimming. It is important not to oversize the power supply too much as switch mode supplies are only really efficient as you get close to their rated output. An oversized switchmode power supply can be extremely inefficient.
With the Daiwa, driving 13 7.5W LEDs, I measured 8.46A at 11.94V output or 101 Watts to brightly illuminate the entire kitchen, and providing far more light than 400W of total halogen lights. I measured the input into the power supply at 0.940A at 121.3V or 114 Watts. That means the power supply is 88.6% efficient at 12V, which is more or less as expected for a variable output supply.
Increasing the output voltage to 14.63 Volts lowered the output current to 5.35A or 78 Watts without lowering the brightness at the installation; I measured at 168 lux at both 12.0V at 14.6V. The input current at 14.63V dropped to 0.755A or 91.6 Watts, meaning the power supply is slightly less efficient at lower output currents (as is usually the case).
- Overdriving the 12V rated LEDs to 14.63V improves plug efficiency by 20%.
At the low end, the SS-330W’s minimum output is 4.88V, which yields 12 lux at the counter or a 14x dimming ratio to 7% of maximum illumination, a far better range than is reported for standard dimmer/transformer combinations.
- 7.5W LED modules from JackyLED
- Daiwa power supply (alternate version)
- 16 gauge speaker cable
- MR-16 cable lamp mounts
- Digital light meter
(MS Excel file, you will need the
xongrid plugin to update the data as rendered in the graphs)
I learned two things about Futurama recently which added to my already deep appreciation for the show. The first is that the theme song came from a very cool song by Pierre Henry called Psyche Rock from 1967, which is on youtube. It was remixed by Fatboy Slim in an appealing way.
But what was most interesting recently was to see episode 10 of season 6, the Prisoner of Benda, a spoof of the Prisoner of Zelda but including what may be the first tv-episode publication of the proof of a relatively complex mathematical theorem in group theory as a core plot element.
The problem in the plot is that the Professor’s mind swapping machine creates an immune response which prevents swapping back in one step. So how do you get everyone back to into their original bodies? Well, as Sweet Clyde says, it takes at most two extra players [who haven’t swapped yet]. As the entire cast, including the robo-bucket, have swapped bodies, the situation is pretty complex, but fortunately one of the show’s writers, Ken Keeler, has a PhD in applied mathematics from Harvard and found a proof, which is actually shown in the show (above), and then worked in a fast montage that restores everyone.
In the following table, the heading shows the character name of the body, row 0 shows the occupant of that body by the end of the plot’s permutations and before the globetrotters start the transformations. Rows 1-7 show the steps to restore everyone to their original bodies. Each transformation was animated as a pair using the two “extra players” except the last rotation to restore Sweet Clyde and the Bucket.
It has two defining features:
- it is a convertible and a sporty one at that,
- it comes with a subwoofer equipped stereo which defines the target market.
This is definitely not a car targeted at classical music listeners. The stereo with the fosgate “punch” setting cranked up is a base heavy “boom car” experience. It sounds fine, the base is clean and well rendered, but it isn’t the balanced, well staged clarity of the sound system in a Mercedes, for example, but fits a particular demographic well.
The car itself is quite sporty and handles well. Unlike a lot of lower end convertibles, including the Mustang, the body is very stiff and and takes turns and bumps without any tangible body flex. The car corners flat and understeers predictably and with good control (I discovered unintentionally while making a quick u-turn). The car also has more power than one would expect for such a small vehicle, and can spin the back wheels from a stop without resorting to a neutral drop, also an unintentional discovery. Really.
Road noise with the top up is pretty good for a convertible, and better than most at freeway speeds with the top down.
I’d say it is a pretty good choice for a low cost, youth-oriented convertible.