Hi Tim and Jeff, Thanks for your help and insights. Being new to Python, I was looking at some Python videos and found my solution, I will make the numpy parameter vectors in the my_init() method "global" and that should solve the problem.
Thank you! Regards, George On Thu, Jan 14, 2021 at 9:57 AM Tim Huggins <huggins.timo...@yahoo.com> wrote: > George, > > "My understanding is the self.x, etc. is used to initialize param > arguments in the def __init__() method and in my case, the only argument in > this method is start" > > > This is not correct, you can add a self.v in there so it looks like: > > def __init__(self, start = True): # only default arguments here > gr.sync_block.__init__( > self, > name='text', # will show up in GRC > in_sig=[()], > out_sig=[()] > ) > # if an attribute with the same name as a parameter is found, > # a callback is registered (properties work, too). > self.start = start > self.v = self.my_init() #or whatever you want the initial value > to be > > Tim > > > On Thursday, January 14, 2021, 10:38:36 AM EST, George Edwards < > gedwards....@gmail.com> wrote: > > > Hi Jeff, > > So I am new to Python programming, so some of the nuances I am not up on > yet. My understanding is the self.x, etc. is used to initialize param > arguments in the def __init__() method and in my case, the only argument in > this method is start, there is no v for me to use self.v = v. v is used the > work() and my_init() methods. At program startup work() calls my_init() > method to get the initial values for the numpy array v (my_init() function > will be called once only at startup when self.start is True). After > initialization and v is passed back to the work(), the values in the numpy > array v inside work will change on a sample to sample computation basis. My > problem is how do I assign v its initial seed value at start up. If my > program was simple with only one parameter v, I would initialize it inside > the work() method, however, I have a bunch of other vector variables to > initialize which is why I want to initialize all parameters inside a > my_init() method that work() calls at startup. > > Thanks for the help. > > George > > On Thu, Jan 14, 2021 at 8:14 AM Jeff Long <willco...@gmail.com> wrote: > > You are already initializing self.start in exactly the same way you should > be initializing self.v, right? > > On Wed, Jan 13, 2021 at 10:46 PM George Edwards <gedwards....@gmail.com> > wrote: > > Hi Jeff, > > Thanks for your answer. You are right, it crashes on the second call. > > So how do I write the program to initialize a bunch of vectors in a > "method strictly for initialization" when it first starts running? If this > cannot be done, then I guess the only solution is to initialize them in the > work() method even though it would make the work() method bulky? > > Thanks again for your help. > > Regards, > George > > On Wed, Jan 13, 2021 at 8:12 PM Jeff Long <willco...@gmail.com> wrote: > > 'v' is a local variable in work(). It is probably crashing on the second > call, where my_init() is not called, and thus there is no 'v'. > > On Wed, Jan 13, 2021 at 7:38 PM George Edwards <gedwards....@gmail.com> > wrote: > > Hello, > > I am using a Gnuradio Python Block in my GRC signal processing and am > having problems initializing my parameters. My system has a number of > vector parameters to be initialized at startup. I will provide the gist of > my goal in a scaled down version of my work. > 1. In the def __init__(self, start = True) method, "start" is the > parameter that will be used in the program to run the initialization > process and is set as follows: > self.start = start > 2. In the work(self, input_items, output_items) method, I have the > following at the start of the method: > if self.start == True: > v = self.my_init() # go initialize all vectors > > output_items[0][:] = in0*v[0] + in1*v[1] + in2*v[2] #computation > using v > # with 3-inputs to > the block > > 3. In the my_init(self) method I have: > self.start = False # set start to False > v = np.array([1., 2., 3.]) #hypothetical to make this simple > return v > > When I run the GRC model, it tells me that "v" is referenced before > assignment. I am confused because I thought that the method my_init() would > have been called before the computation and would return the values for > "v". On the other hand if I do the assignment in the work(...) method as v > = np.array([1., 2., 3.]), it works perfectly. > Question: Why was the my_init() method not called properly to get the > values for the numpy array v? > > Thanks for the help! > > Regards, > George > >
