diff options
Diffstat (limited to 'dpd/src/Model.py')
| -rw-r--r-- | dpd/src/Model.py | 26 | 
1 files changed, 14 insertions, 12 deletions
| diff --git a/dpd/src/Model.py b/dpd/src/Model.py index 2aa9feb..dc526c5 100644 --- a/dpd/src/Model.py +++ b/dpd/src/Model.py @@ -20,7 +20,7 @@ class Model:      """Calculates new coefficients using the measurement and the old      coefficients""" -    def __init__(self, coefs_am, coefs_pm): +    def __init__(self, coefs_am, coefs_pm, plot=False):          self.coefs_am = coefs_am          self.coefs_history = [coefs_am, ]          self.mses = [0, ] @@ -30,6 +30,8 @@ class Model:          self.coefs_pm_history = [coefs_pm, ]          self.errs_phase = [0, ] +        self.plot=plot +      def sample_uniformly(self, txframe_aligned, rxframe_aligned, n_bins=4):          """This function returns tx and rx samples in a way          that the tx amplitudes have an approximate uniform  @@ -144,19 +146,19 @@ class Model:          rx_range = rx_range[(rx_range_dpd > 0) & (rx_range_dpd < 2)]          rx_range_dpd = rx_range_dpd[(rx_range_dpd > 0) & (rx_range_dpd < 2)] -        if logging.getLogger().getEffectiveLevel() == logging.DEBUG: -            logging.debug("txframe: min %f, max %f, median %f" % -                          (np.min(np.abs(txframe_aligned)), -                           np.max(np.abs(txframe_aligned)), -                           np.median(np.abs(txframe_aligned)) -                           )) +        logging.debug("txframe: min %f, max %f, median %f" % +                      (np.min(np.abs(txframe_aligned)), +                       np.max(np.abs(txframe_aligned)), +                       np.median(np.abs(txframe_aligned)) +                       )) -            logging.debug("rxframe: min %f, max %f, median %f" % -                          (np.min(np.abs(rx_choice)), -                           np.max(np.abs(rx_choice)), -                           np.median(np.abs(rx_choice)) -                           )) +        logging.debug("rxframe: min %f, max %f, median %f" % +                      (np.min(np.abs(rx_choice)), +                       np.max(np.abs(rx_choice)), +                       np.median(np.abs(rx_choice)) +                       )) +        if logging.getLogger().getEffectiveLevel() == logging.DEBUG and self.plot:              dt = datetime.datetime.now().isoformat()              fig_path = logging_path + "/" + dt + "_Model.pdf" | 
