diff options
Diffstat (limited to 'dpd/src')
| -rw-r--r-- | dpd/src/Model.py | 24 |
1 files changed, 13 insertions, 11 deletions
diff --git a/dpd/src/Model.py b/dpd/src/Model.py index 827027a..1606441 100644 --- a/dpd/src/Model.py +++ b/dpd/src/Model.py @@ -15,6 +15,7 @@ import numpy as np import matplotlib.pyplot as plt from sklearn import linear_model + class Model: """Calculates new coefficients using the measurement and the old coefficients""" @@ -25,8 +26,8 @@ class Model: MER, coefs_am, coefs_pm, - learning_rate_am=1., - learning_rate_pm=1., + learning_rate_am=0.1, + learning_rate_pm=0.1, plot=False): self.c = c self.SA = SA @@ -122,11 +123,9 @@ class Model: err = np.abs(rx_dpd) - np.abs(tx_choice) mse = np.mean(np.abs((rx_dpd - tx_choice) ** 2)) self.mses_am.append(mse) - self.errs_am.append(np.mean(err**2)) + self.errs_am.append(np.mean(err ** 2)) - reg = linear_model.Ridge(alpha=0.00001) - reg.fit(rx_A, err) - a_delta = reg.coef_ + a_delta = np.linalg.lstsq(rx_A, err)[0] new_coefs_am = self.coefs_am - self.learning_rate_am * a_delta new_coefs_am = new_coefs_am * (self.coefs_am[0] / new_coefs_am[0]) return new_coefs_am @@ -139,15 +138,13 @@ class Model: (np.abs(rx_choice) * np.abs(tx_choice)) ) plt.hist(phase_diff_choice) - plt.savefig('/tmp/hist_' + str(np.random.randint(0,1000)) + '.svg') + plt.savefig('/tmp/hist_' + str(np.random.randint(0, 1000)) + '.svg') plt.clf() phase_diff_est, phase_A = self.dpd_phase(rx_choice) err_phase = phase_diff_est - phase_diff_choice self.errs_pm.append(np.mean(np.abs(err_phase ** 2))) - reg = linear_model.Ridge(alpha=0.00001) - reg.fit(phase_A, err_phase) - p_delta = reg.coef_ + p_delta = np.linalg.lstsq(phase_A, err_phase)[0] new_coefs_pm = self.coefs_pm - self.learning_rate_pm * p_delta return new_coefs_pm, phase_diff_choice @@ -164,6 +161,11 @@ class Model: np.median(np.abs(tx_dpd)) + np.median(np.abs(rx_received))) assert normalization_error < 0.01, "Non normalized signals" + if logging.getLogger().getEffectiveLevel() == logging.DEBUG: + dt = datetime.datetime.now().isoformat() + tx_dpd.tofile(logging_path + "/tx_dpd_" + dt + ".iq") + rx_received.tofile(logging_path + "/rx_received_" + dt + ".iq") + tx_choice, rx_choice = self.sample_uniformly(tx_dpd, rx_received) new_coefs_am = self._next_am_coefficent(tx_choice, rx_choice) new_coefs_pm, phase_diff_choice = self._next_pm_coefficent(tx_choice, rx_choice) @@ -303,7 +305,7 @@ class Model: np.rad2deg(phase_range_dpd_new), linewidth=0.25, label="next") - ax.set_ylim(-60, 60) + ax.set_ylim(-180, 180) ax.set_xlim(0, 1) ax.legend() ax.set_title("Amplifier Characteristic") |