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Posted by / 21-Nov-2017 21:18

And if you don't know the aerodynamic characteristics of your plane, Moto Calc's lift and drag coefficient estimator will make short work of determining them.

If you are a newcomer to electric flight, Moto Calc's Moto Wizard will ask you a few simple questions about your model and your preferences (such as brand of motor), and will then make suggestions as to the ideal power system.

Joystick): # initialize the infinite loop decorator _infinite_loop = jk.deco_infinite_loop() def _init(self, *args, **kwargs): """ Function called at initialization, see the doc """ self._t0 = time.time() # initialize time self.xdata = np.array([self._t0]) # time x-axis self.ydata = np.array([0.0]) # fake data y-axis # create a graph frame self.mygraph = self.add_frame(jk.

I am trying to find a way to take an ISO image of a bootable CD and make a bootable USB flash drive from it. I have found some linux versions that have an installer to put them on a USB flash drive but nothing to take the ISO file directly to the drive and it seems like it would be mainly just converting the ISO9660 file system to fat file system.

I designed it for plotting a stream of data from the serial port, but it works for any stream.These five steps are described in more detail below.The Moto Wizard is described in great detail in its own section of this manual, so we won't repeat it all here. The Moto Wizard consists of a number of pages on which you answer some basic questions about your model, it's intended performance, information about where you fly, and any preferences you may have.There are a number of ways of animating data in matplotlib, depending on the version you have. Also, check out the more modern animation examples in the matplotlib documentation.Finally, the animation API defines a function Func Animation which animates a function in time.

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Given that you say that your data arrival time is uncertain your best bet is probably just to do something like: import matplotlib.pyplot as plt import numpy hl, = plt.plot([], []) def update_line(hl, new_data): hl.set_xdata(numpy.append(hl.get_xdata(), new_data)) hl.set_ydata(numpy.append(hl.get_ydata(), new_data)) plt.draw() Since there is no call to show(), the plot never appears on the screen.