- Download the last version (currently Kepler) of the Eclipse IDE for C/C Developers package, selecting the Mac OS X 64 Bit version, and uncompress it in your home or applications folder. Now open Eclipse and install the plugins needed: Eclipse CDT, GNU ARM and Zylin embedded CDT.
- Thoug h it happens rarely, after Mac system software undergoes an update (likely to happen after a hard drive change or firmware update or OS upgrade, etc.), it might sometimes get stuck at a.
- The project is named after Claudius Ptolemaeus, the 2nd century Greek astronomer, mathematician, and geographer. The Kepler Project, a community-driven collaboration among researchers at three other University of California campuses has created the Kepler scientific workflow system which is.
- Project: Kepler Mac Os Catalina
- Project: Kepler Mac Os X
- Project: Kepler Mac Os 11
- Project: Kepler Mac Os Download
A few months ago I received an STM32F3DISCOVERY evaluation board, similar to the STM32F4DISCOVERY that I've used for prototyping at work, but for the new STM32 F3 series Cortex-M4. Since ST doesn't provide a development environment like TI and NXP do, and the commercial packages available are expensive and windows only, I've decided to put up a step-by-step tutorial on how to setup an opensource environment for Mac OS X based on eclipse, GCC ARM and openOCD.
All the packages are multi-platform, so it should be easy to configure a similar environment for Linux or Windows.
Right, this is not specific to mac os x, but to maven 3.1.0 Try re running the build with maven 3.0.4, you won't reproduce the issue. It appears that this section.
Download and Install the GCC ARM toolchain, Eclipse IDE + plugins and OpenOCD
GNU Tools for ARM Embedded Processors
Project: Kepler Mac Os Catalina
The first thing you need is a toolchain. The GCC ARM is maintained by ARM employees, and is the best open source compiler you can find. It includes the debugger GDB. Download the mac installation tarball of the 4.7 series release and uncompress it in your home folder, no installation needed.
Eclipse IDE
A lot of the closed source IDE used in ARM development are heavily based on the Eclipse IDE. Download the last version (currently Kepler) of the Eclipse IDE for C/C++ Developers package, selecting the Mac OS X 64 Bit version, and uncompress it in your home or applications folder.
Now open Eclipse and install the plugins needed: Eclipse CDT, GNU ARM and Zylin embedded CDT.
Go to Help > Install New Software. Click on the 'Available software sites', select the CDT checkbox and click OK.
Select CDT from the Work with: dropdown and the packages will appear below. Click all the CDT Main Features and from the CDT Optional Features the ones that are selected in the following image.
Click Finish and the plugins will download and install.
Next we will install the GNU ARM plugin. Click again on Help > Install New Software and now click on the Add… button next to the top dropdown, to add a new repository. Insert the location http://gnuarmeclipse.sourceforge.net/updates and click OK. The component 'CDT GNU Cross Development Tools' will appear below. Select and install it.
Finally, repeat the process to install the Zylin Embedded CDT plugin, necessary to debug and flash. Add the repository with the location http://opensource.zylin.com/zylincdt and install the component 'Zylin Embedded CDT'.
OpenOCD
OpenOCD is an open on-chip debugger and progamming tool. It will communicate with gdb to debug and flash the board by using the stlinkv2 debugger. The easiest way to install it is using Homebrew, a pacakage manager for OS X similar to MacPorts or Fink. If you don't use Homebrew already, follow the one-step installation instructions on its website. After that, open a Terminal and paste the following line:
Once installed, you have to create an empty file called stm32f3discovery.cfg in your home folder, and paste the following lines:
To be able to run OpenOCD inside Eclipse, you have to add it clicking in the menu Run > External Tools > External Tools Configuration…. Create a new item clicking in the New launch configuration icon and fill in the location, working directory and arguments as in the following image and click Apply. The working directory will be where you created the stm32f3discovery.cfg file.
Now connect your STM32F3DISCOVERY board to the computer and click the Run button. If everything is correct, you will see in the console something similar to this:
Every time you start Eclipse, you will need to start OpenOCD with Run > External Tools > OpenOCD. When you exit Eclipse, it will kill the OpenOCD daemon. If for some reason it is still running, paste in a Terminal the command killall openocd.
Creating a new project
After installing all the packages, we are going to create a blinking led example project.
First, click on File > New > C Project and select Executable > STM32F3xx StdPeriph Lib v1.0 C Project and Cross ARM GCC. Give it a name, for example Bliking_STM32F3.
Click Next several times, leaving the default options, until you reach the last step, where you select the toolchain name and path, as you can see in the image. You will have to browse for the path of the bin folder where you installed the GCC ARM Toolchain.
Fantasy mosaics 12: parallel universes mac os. Click Finish and the project will be created.
For now, you can leave the example code as is, but you need to comment the printf lines, since OpenOCD doesn't seem to support retargeting for this board at the moment.
Another thing we should do is enable the FPU unit, that is disabled by default. Go to Project > Properties and select C/C++ > Settings on the left tree. In the Tool Settings, click on the Target Processor item. On the right dropdowns, select the 'FP instructions (hard)' option of the Float ABI menu, and 'fpv4-sp-d16' of the FPU Type and click OK.
After that, click on Project > Build Project. Now that the program is compiled, the only thing left is to add a debug configuration. Click on Run > Debug Configurations… and double-click on Zylin Embedded debug (Native). On the 'Debugger' tab, click on the GDB debugger field and browse to select the gdb executable of the GCC ARM toolchain. It will be something like PATH_TO_GCC/bin/arm-none-eabi-gdb.
Finally, go to the 'Commands' tab and paste this in the ‘Initialize' commands box:
Project: Kepler Mac Os X
Click Apply and then Debug. The debugging session will start, Eclipse will switch to the Debug perspective and the program will be downloaded to flash. Then, when you click on the Resume (F8) icon, the program will start executing, stopping at main. Cryptid low-cation mac os. Clicking again on Resume will continue the execution. If everything is configured correctly, you will see the green led flashing on your board. You can pause/stop the execution, set breakpoints and watch variables and registers.
Citizen Science
PlanetHunters.org
Planet Hunters is a citizen science project that makes it possible for anyone to sieve through data taken by the NASA Kepler space mission. The Kepler spacecraft takes brightness measurements, or 'light curves,' of over 150,000 stars every 30 minutes. People can then hunt for planets by looking for a brief dip in brightness that occurs when a planet passes in front of the star.
Join the search at http://www.planethunters.org, or read on to learn more.
Our Challenge
NASA's Kepler spacecraft is one of the most powerful tools in the hunt for extrasolar planets. The Kepler team's computers are sifting through the data, but we at Planet Hunters are betting that there will be planets which can only be found via the remarkable human ability for pattern recognition.
This is a gamble, a bet if you will, on the ability of humans to beat machines just occasionally. It may be that no new planets are found or that computers have the job down to a fine art. And yet, it's just possible that you might be the first to know that a star somewhere out there in the Milky Way has a companion, just as our Sun does. Fancy giving it a try?
The Kepler Public Data
On March 2009, the NASA Kepler mission was launched with the goal of using the transit technique to detect exoplanets: terrestrial and larger planets orbiting other stars. With this method, planets that pass in front of their host stars block out some of the starlight causing the star to dim slightly for a few hours. The Kepler spacecraft stares at a field of stars in the Cygnus constellation and records the brightness of those stars every thirty minutes to search for transiting planets.
The time series of brightness measurements for a star is called a light curve. The Kepler spacecraft beams data for more than 150,000 stars to Earth at regular intervals. With every download of data, the time baseline of the light curves is extended.
The project's Principal Investigator, Bill Borucki, began planning the Kepler mission in the mid-1980's and his team has been hard at work for more than a decade. To reward them for this hard work, the Kepler team has advanced access to the light curves. We at Planet Hunters are not part of the NASA Kepler team. However, NASA is releasing light curves into the public archive to encourage broader participation and we think that the public can play an important as our scientific partners in this latest Zooniverse project.
Since 1995, more than 500 exoplanets have been discovered by various techniques and it appears that roughly half of the stars in the sky have planets. There are some special challenges for planet detection with the transit technique:
- A special orientation of the orbit is required. Because the technique looks for a dimming in the brightness of the star, all of the planets with orbits that don't pass between the star and our line of sight will be missed.
- Close-in planets are easier to detect. A transit event only occurs once per orbit; planets that are closer to their host stars race around their orbits faster than planets that orbit at larger distances. To confidently detect a transit, at least three dips in the brightness (i.e., three transit events) must occur. Thus, a planet that orbits in one year, like the Earth, requires three years of data for detection, while planets that orbit in ten days can be detected with just thirty days of data.
- Larger planets are easier to detect. The bigger the planet, the more starlight it blocks out. The Kepler mission measures the brightness of stars with such incredible precision that it is sensitive enough to detect transits of planets approaching the size of Earth.
- Planets may be harder to detect against a variable brightness background. This turns out to be less of a problem than one might think. When we look at a light curve, we're seeing how the brightness changes with time. In the Figure below, there are starspots in addition to the transiting planet (lower left spot on the star). However, starspots rotate with the star and cause relatively slow changes in the brightness of the star. Transiting planets cross the star in hours and cause quick dips in the brightness of the star. Look below to see the difference (left image). Spots cause most of the smooth and slowly varying brightness and we're learning that many stars have much larger spots than the Sun.
Humans vs. Machines
The Kepler team has been developing computer algorithms to analyze light curve data because it is not possible for them to visually inspect every light curve. While we expect computer programs to robustly identify things that they are trained to find, we are betting that there will be a number of surprises in the data that the computer algorithms will miss.
Project: Kepler Mac Os 11
The human brain is particularly good at discerning patterns or aberrations and experiments have shown that when many people work together, the collective wisdom of the crowds can be better than an expert. Planet Hunters is an online experiment that taps into the power of human pattern recognition. Participants are partners with our science team, who will analyze group assessments, obtain follow up observations at the telescope to understand the new classification schemes for different families of light curves, identify oddities, and verify transit signals.
Planet Hunters: Sorting the Light Curves
You will be looking at changes in star brightness at a level that has never before been seen. As you sort through the light curves, you will notice different patterns. In many cases, the data scatters in a relatively flat band of points, like the cases shown in Figure 1. Most of this scatter is simply the inevitable noise that comes with any measurement. Other light curves, like those in Figure 2, are obviously variable with time. We think that most of the variability (on timescales of hours to days) is caused by starspots or pulsations. Having Planet Hunters sort families of similar light curves is part of the important scientific research.
The royale we mac os. Figure 1. Even precise measurements are not exactly perfect or reproducible and cause low-level scatter in the data. There is no visible pattern, just white noise, and so these light curves are best categorized with the middle 'quiet' icon.
Project: Kepler Mac Os Download
All the packages are multi-platform, so it should be easy to configure a similar environment for Linux or Windows.
Right, this is not specific to mac os x, but to maven 3.1.0 Try re running the build with maven 3.0.4, you won't reproduce the issue. It appears that this section.
Download and Install the GCC ARM toolchain, Eclipse IDE + plugins and OpenOCD
GNU Tools for ARM Embedded Processors
Project: Kepler Mac Os Catalina
The first thing you need is a toolchain. The GCC ARM is maintained by ARM employees, and is the best open source compiler you can find. It includes the debugger GDB. Download the mac installation tarball of the 4.7 series release and uncompress it in your home folder, no installation needed.
Eclipse IDE
A lot of the closed source IDE used in ARM development are heavily based on the Eclipse IDE. Download the last version (currently Kepler) of the Eclipse IDE for C/C++ Developers package, selecting the Mac OS X 64 Bit version, and uncompress it in your home or applications folder.
Now open Eclipse and install the plugins needed: Eclipse CDT, GNU ARM and Zylin embedded CDT.
Go to Help > Install New Software. Click on the 'Available software sites', select the CDT checkbox and click OK.
Select CDT from the Work with: dropdown and the packages will appear below. Click all the CDT Main Features and from the CDT Optional Features the ones that are selected in the following image.
Click Finish and the plugins will download and install.
Next we will install the GNU ARM plugin. Click again on Help > Install New Software and now click on the Add… button next to the top dropdown, to add a new repository. Insert the location http://gnuarmeclipse.sourceforge.net/updates and click OK. The component 'CDT GNU Cross Development Tools' will appear below. Select and install it.
Finally, repeat the process to install the Zylin Embedded CDT plugin, necessary to debug and flash. Add the repository with the location http://opensource.zylin.com/zylincdt and install the component 'Zylin Embedded CDT'.
OpenOCD
OpenOCD is an open on-chip debugger and progamming tool. It will communicate with gdb to debug and flash the board by using the stlinkv2 debugger. The easiest way to install it is using Homebrew, a pacakage manager for OS X similar to MacPorts or Fink. If you don't use Homebrew already, follow the one-step installation instructions on its website. After that, open a Terminal and paste the following line:
Once installed, you have to create an empty file called stm32f3discovery.cfg in your home folder, and paste the following lines:
To be able to run OpenOCD inside Eclipse, you have to add it clicking in the menu Run > External Tools > External Tools Configuration…. Create a new item clicking in the New launch configuration icon and fill in the location, working directory and arguments as in the following image and click Apply. The working directory will be where you created the stm32f3discovery.cfg file.
Now connect your STM32F3DISCOVERY board to the computer and click the Run button. If everything is correct, you will see in the console something similar to this:
Every time you start Eclipse, you will need to start OpenOCD with Run > External Tools > OpenOCD. When you exit Eclipse, it will kill the OpenOCD daemon. If for some reason it is still running, paste in a Terminal the command killall openocd.
Creating a new project
After installing all the packages, we are going to create a blinking led example project.
First, click on File > New > C Project and select Executable > STM32F3xx StdPeriph Lib v1.0 C Project and Cross ARM GCC. Give it a name, for example Bliking_STM32F3.
Click Next several times, leaving the default options, until you reach the last step, where you select the toolchain name and path, as you can see in the image. You will have to browse for the path of the bin folder where you installed the GCC ARM Toolchain.
Fantasy mosaics 12: parallel universes mac os. Click Finish and the project will be created.
For now, you can leave the example code as is, but you need to comment the printf lines, since OpenOCD doesn't seem to support retargeting for this board at the moment.
Another thing we should do is enable the FPU unit, that is disabled by default. Go to Project > Properties and select C/C++ > Settings on the left tree. In the Tool Settings, click on the Target Processor item. On the right dropdowns, select the 'FP instructions (hard)' option of the Float ABI menu, and 'fpv4-sp-d16' of the FPU Type and click OK.
After that, click on Project > Build Project. Now that the program is compiled, the only thing left is to add a debug configuration. Click on Run > Debug Configurations… and double-click on Zylin Embedded debug (Native). On the 'Debugger' tab, click on the GDB debugger field and browse to select the gdb executable of the GCC ARM toolchain. It will be something like PATH_TO_GCC/bin/arm-none-eabi-gdb.
Finally, go to the 'Commands' tab and paste this in the ‘Initialize' commands box:
Project: Kepler Mac Os X
Click Apply and then Debug. The debugging session will start, Eclipse will switch to the Debug perspective and the program will be downloaded to flash. Then, when you click on the Resume (F8) icon, the program will start executing, stopping at main. Cryptid low-cation mac os. Clicking again on Resume will continue the execution. If everything is configured correctly, you will see the green led flashing on your board. You can pause/stop the execution, set breakpoints and watch variables and registers.
Citizen Science
PlanetHunters.org
Planet Hunters is a citizen science project that makes it possible for anyone to sieve through data taken by the NASA Kepler space mission. The Kepler spacecraft takes brightness measurements, or 'light curves,' of over 150,000 stars every 30 minutes. People can then hunt for planets by looking for a brief dip in brightness that occurs when a planet passes in front of the star.
Join the search at http://www.planethunters.org, or read on to learn more.
Our Challenge
NASA's Kepler spacecraft is one of the most powerful tools in the hunt for extrasolar planets. The Kepler team's computers are sifting through the data, but we at Planet Hunters are betting that there will be planets which can only be found via the remarkable human ability for pattern recognition.
This is a gamble, a bet if you will, on the ability of humans to beat machines just occasionally. It may be that no new planets are found or that computers have the job down to a fine art. And yet, it's just possible that you might be the first to know that a star somewhere out there in the Milky Way has a companion, just as our Sun does. Fancy giving it a try?
The Kepler Public Data
On March 2009, the NASA Kepler mission was launched with the goal of using the transit technique to detect exoplanets: terrestrial and larger planets orbiting other stars. With this method, planets that pass in front of their host stars block out some of the starlight causing the star to dim slightly for a few hours. The Kepler spacecraft stares at a field of stars in the Cygnus constellation and records the brightness of those stars every thirty minutes to search for transiting planets.
The time series of brightness measurements for a star is called a light curve. The Kepler spacecraft beams data for more than 150,000 stars to Earth at regular intervals. With every download of data, the time baseline of the light curves is extended.
The project's Principal Investigator, Bill Borucki, began planning the Kepler mission in the mid-1980's and his team has been hard at work for more than a decade. To reward them for this hard work, the Kepler team has advanced access to the light curves. We at Planet Hunters are not part of the NASA Kepler team. However, NASA is releasing light curves into the public archive to encourage broader participation and we think that the public can play an important as our scientific partners in this latest Zooniverse project.
Since 1995, more than 500 exoplanets have been discovered by various techniques and it appears that roughly half of the stars in the sky have planets. There are some special challenges for planet detection with the transit technique:
- A special orientation of the orbit is required. Because the technique looks for a dimming in the brightness of the star, all of the planets with orbits that don't pass between the star and our line of sight will be missed.
- Close-in planets are easier to detect. A transit event only occurs once per orbit; planets that are closer to their host stars race around their orbits faster than planets that orbit at larger distances. To confidently detect a transit, at least three dips in the brightness (i.e., three transit events) must occur. Thus, a planet that orbits in one year, like the Earth, requires three years of data for detection, while planets that orbit in ten days can be detected with just thirty days of data.
- Larger planets are easier to detect. The bigger the planet, the more starlight it blocks out. The Kepler mission measures the brightness of stars with such incredible precision that it is sensitive enough to detect transits of planets approaching the size of Earth.
- Planets may be harder to detect against a variable brightness background. This turns out to be less of a problem than one might think. When we look at a light curve, we're seeing how the brightness changes with time. In the Figure below, there are starspots in addition to the transiting planet (lower left spot on the star). However, starspots rotate with the star and cause relatively slow changes in the brightness of the star. Transiting planets cross the star in hours and cause quick dips in the brightness of the star. Look below to see the difference (left image). Spots cause most of the smooth and slowly varying brightness and we're learning that many stars have much larger spots than the Sun.
Humans vs. Machines
The Kepler team has been developing computer algorithms to analyze light curve data because it is not possible for them to visually inspect every light curve. While we expect computer programs to robustly identify things that they are trained to find, we are betting that there will be a number of surprises in the data that the computer algorithms will miss.
Project: Kepler Mac Os 11
The human brain is particularly good at discerning patterns or aberrations and experiments have shown that when many people work together, the collective wisdom of the crowds can be better than an expert. Planet Hunters is an online experiment that taps into the power of human pattern recognition. Participants are partners with our science team, who will analyze group assessments, obtain follow up observations at the telescope to understand the new classification schemes for different families of light curves, identify oddities, and verify transit signals.
Planet Hunters: Sorting the Light Curves
You will be looking at changes in star brightness at a level that has never before been seen. As you sort through the light curves, you will notice different patterns. In many cases, the data scatters in a relatively flat band of points, like the cases shown in Figure 1. Most of this scatter is simply the inevitable noise that comes with any measurement. Other light curves, like those in Figure 2, are obviously variable with time. We think that most of the variability (on timescales of hours to days) is caused by starspots or pulsations. Having Planet Hunters sort families of similar light curves is part of the important scientific research.
The royale we mac os. Figure 1. Even precise measurements are not exactly perfect or reproducible and cause low-level scatter in the data. There is no visible pattern, just white noise, and so these light curves are best categorized with the middle 'quiet' icon.
Project: Kepler Mac Os Download
Werther quest mac os. Figure 2. These light curves should be tagged with the 'variable' icon; then you will be asked to decide if the curve is pulsating with one cycle (like the top left curve) or regular (like the top right curve) or irregular (like the bottom curves).
It is challenging for computer algorithms to classify variable patterns so participants are making a particularly important scientific contribution in this step. We will obtain follow-up data at the telescope to understand the underlying mechanisms for these different families of variable curves and to confirm transit candidates.
Planet Hunters: Flagging Transit Events
However, the real treasure hunt is for transiting planets and these present as a relatively sharp dip in brightness in the light curve (Figure 3). A transit could appear in either a quiet or a variable curve. Indeed, it will be more difficult for computer algorithms to find transits imposed on the variable light curves, so we hope that Planet Hunters will pay particular attention to these.
Figure 3. After sorting the light curves as quiet or variable, Planet Hunters will be asked if there are any possible transits in the data. If low points are seen, then answer 'yes' and click on the icon to create a box that can be positioned over the transit features.
The size of the planet is reflected in the depth of the transit points. Earth-sized planets will exhibit a dip in brightness that is buried in the noise of the quiet light curves in Figure 1. The transit events in Figure 3 are for planets that are several times the radius of the Earth.
The time it takes a planet to complete one orbit is called the orbital period. For transiting planets, this can be determined by counting the number of days from one transit to the next. The examples in Figure 3 are fairly obvious. Planets in longer period orbits will be more challenging to detect, both for humans and for computers because a transit will not appear in every 30-day set of light curve data. Just because you don't see a transit in the first block of data doesn't mean that there won't be a transit in another set!
Large planets with short orbital periods are the easiest ones to detect. The most challenging detections will be small planets with long orbital periods. These will require patience and care, but are the real treasures in the Kepler data!
I See a Transit!
App browser com. What happens if Planet Hunters discover a possible transiting planet? We maintain a list of transiting planets that the Kepler team announces, so the first thing that will happen is that we will check that list. If the flagged transit event is for a star that the Kepler team are already keeping an eye on, we'll let you know. If this event has not been identified and several Planet Hunters are flagging the same data, the science team will investigate. If this appears to be a new discovery, then we will follow up to obtain spectroscopic data using the Keck telescope in Hawaii. If the transit candidate passes all of the screening tests, the result will be submitted for publication. Planet Hunters who discover new transiting planets will be included as co-authors on our papers.
Experimental Data: Faking the Transits
To better understand what types of planets are detected or missed by Planet Hunters, we have created a small number of test cases for some of the light curves that participants will classify. These test cases contain fake transit events and are critical for determining the statistical completeness for planets as a function of size (depth of the transit event) and orbital period (number of transits). After participants classify a data set with a fake transit event, a message will appear notifying them that this was a test case, and the fake points will be highlighted.