Thanks for the suggestion! I get an deserialize error. Not really sure how
to make a S available on all processes:
using Winston, PyCall, Reactive
@pyimport seabreeze
seabreeze.use("pyseabreeze")
@pyimport seabreeze.spectrometers as sb
devices = sb.list_devices()
S = sb.Spectrometer(devices[1])
To bad really, because that seems like a really nice and easy solution.
On Tuesday, October 13, 2015 at 7:13:42 PM UTC+10, Mohammed El-Beltagy
wrote:
Short of doing a reimplementation, you could possibly run your python code
> in another process via a remotecall (as described in the manual
> http://julia.readthedocs.org/en/latest/manual/parallel-computing/). In
> that case you REPL would be responsive as the I/O is done in another
> process.
>
> On Monday, October 12, 2015 at 10:10:39 PM UTC+2, Yakir Gagnon wrote:
>>
>> I see, thanks for the great explanation!
>> So there's nothing I can do. Would Escher get around it? I guess I'd need
>> to implement that python code in Julia...
>> On 12/10/2015 11:34 PM, "Steven G. Johnson" <[email protected]> wrote:
>>
>>>
>>>
>>> On Monday, October 12, 2015 at 1:59:59 AM UTC-4, Yakir Gagnon wrote:
>>>>
>>>> One important piece of information is the integration time (similar to
>>>> the shutter speed in a camera): after I set the integration time the
>>>> spectrometer start sampling the spectra at that frequency. When I try to
>>>> retrieve the intensities it will spit them out only when one cycle ends.
>>>> This means that when I try to run the function that retrieves the
>>>> intensities it can take anything from 0 to integration-time seconds.
>>>>
>>>> Here's the weird thing:
>>>> When I run my code the REPL becomes non-responsive for integration-time
>>>> seconds, so if I try to type some text, the letters get typed in only one
>>>> letter at an integration-time (note that CPU usage is less than 3%)...
>>>> But,
>>>> if I replace the function that retrieves the intensities with some mock
>>>> function that `sleep`s for a random amount of time and returns a (equally
>>>> long) vector of random floats, the REPL jitter is gone..!
>>>>
>>>
>>> Julia I/O functions, and functions like sleep(t), use the libuv library
>>> for asynchronous cooperative multitasking. That means that when one task
>>> is waiting on I/O, another task (e.g. the REPL) can wake up if there is
>>> something for it to do.
>>>
>>> However, Python I/O does not use libuv, so when the Python I/O task is
>>> waiting to finish reading something then it just blocks, and nothing else
>>> in Julia can run.
>>>
>>
