Hell Tim and Jeff, Problem, so when I make v global in my_init() method and use it is the work() method, it works good if I do not try to change the values in the vector v, let's say v came down as v = np.array([1.0 , 1.0 , 1.0]). If I try to change the values say v[0] += v[0], etc. the program breaks with the message local variable v changes before assignment. I thought it was global and already assigned.
Thanks for your help. George On Thu, Jan 14, 2021 at 9:17 AM George Edwards <gedwards....@gmail.com> wrote: > 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 >> >>
