diff options
Diffstat (limited to 'gui/dpd/Capture.py')
| -rw-r--r-- | gui/dpd/Capture.py | 57 |
1 files changed, 32 insertions, 25 deletions
diff --git a/gui/dpd/Capture.py b/gui/dpd/Capture.py index d6d0307..31fa78d 100644 --- a/gui/dpd/Capture.py +++ b/gui/dpd/Capture.py @@ -77,8 +77,12 @@ class Capture: self.binning_n_bins = 64 # Number of bins between binning_start and binning_end self.binning_n_per_bin = 128 # Number of measurements pre bin + self.target_median = 0.01 + self.median_max = self.target_median * 1.4 + self.median_min = self.target_median / 1.4 + # axis 1: 0=tx, 1=rx - self.accumulated_samples = np.zeros((0, 2), dtype=np.complex64) + self.accumulated_bins = [np.zeros((0, 2), dtype=np.complex64) for i in range(self.binning_n_bins)] def _recv_exact(self, sock, num_bytes): """Receive an exact number of bytes from a socket. This is @@ -156,42 +160,45 @@ class Capture: txframe, tx_ts, rxframe, rx_ts = self.receive_tcp() # Normalize received signal with sent signal - rx_median = np.median(np.abs(rxframe)) tx_median = np.median(np.abs(txframe)) - rxframe = rxframe / rx_median * tx_median - txframe_aligned, rxframe_aligned = align_samples(txframe, rxframe) + if self.median_max < tx_median: + raise ValueError("Median {} too high, decrease digital_gain!".format(tx_median)) + elif tx_median < self.median_min: + raise ValueError("Median {} too low, increase digital_gain!".format(tx_median)) + else: + rx_median = np.median(np.abs(rxframe)) + rxframe = rxframe / rx_median * tx_median + + txframe_aligned, rxframe_aligned = align_samples(txframe, rxframe) - self._bin_and_accumulate(txframe_aligned, rxframe_aligned) + self._bin_and_accumulate(txframe_aligned, rxframe_aligned) - return txframe_aligned, tx_ts, tx_median, rxframe_aligned, rx_ts, rx_median + return txframe_aligned, tx_ts, tx_median, rxframe_aligned, rx_ts, rx_median - def num_accumulated(self): - return self.accumulated_samples.shape[0] + def bin_histogram(self): + return [b.shape[0] for b in self.accumulated_bins] def _bin_and_accumulate(self, txframe, rxframe): """Bin the samples and extend the accumulated samples""" bin_edges = np.linspace(self.binning_start, self.binning_end, self.binning_n_bins) - binned_sample_pairs = {} - minsize = self.num_samples_to_request for i, (tx_start, tx_end) in enumerate(zip(bin_edges, bin_edges[1:])): - indices = np.bitwise_and(tx_start < txframe, txframe <= tx_end) - binned_sample_pairs[i] = (txframe[indices], rxframe[indices]) - len_bin = len(txframe[indices]) - - #TODO this doesn't work, the min is always 0 - if len_bin < minsize: - minsize = len_bin - - # axis 0: bins, axis 1: sample index, axis 2: tx(0) and rx(1) - samples = np.zeros((self.binning_n_bins, len_bin, 2), dtype=np.complex64) - - for i in binned_sample_pairs: - tx, rx = binned_sample_pairs[i] - new_samples = np.array((tx[:minsize], rx[:minsize]), dtype=np.complex64) - self.accumulated_samples = np.concatenate((self.accumulated_samples, new_samples.T)) + txframe_abs = np.abs(txframe) + indices = np.bitwise_and(tx_start < txframe_abs, txframe_abs <= tx_end) + txsamples = np.asmatrix(txframe[indices]) + rxsamples = np.asmatrix(rxframe[indices]) + binned_sample_pairs = np.concatenate((txsamples, rxsamples)).T + + missing_in_bin = self.binning_n_per_bin - self.accumulated_bins[i].shape[0] + num_to_append = min(missing_in_bin, binned_sample_pairs.shape[0]) + print("Handling bin {} {}-{}, {} available, {} missing".format(i, tx_start, tx_end, binned_sample_pairs.shape[0], missing_in_bin)) + if num_to_append: + print("Appending {} to bin {} with shape {}".format(num_to_append, i, self.accumulated_bins[i].shape)) + + self.accumulated_bins[i] = np.concatenate((self.accumulated_bins[i], binned_sample_pairs[:num_to_append,...])) + print("{} now has shape {}".format(i, self.accumulated_bins[i].shape)) |