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Faster template correlation for pulsed_timing
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1 changed files with 35 additions and 13 deletions
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@ -65,24 +65,46 @@ def antenna_bp(trace, low_bp, high_bp, dt, order=3):
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return bandpassed
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return bandpassed
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def my_correlation(in1, template):
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def my_correlation(in1, template, lags=None):
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#
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template_length = len(template)
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in1_long = np.zeros( (len(in1)+2*len(template)) )
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in1_length = len(in1)
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in1_long[len(template):-len(template)] = in1
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# fill the template with zeros and copy template
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if lags is None:
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template_long = np.zeros_like(in1_long)
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lags = np.arange(-template_length+1, in1_length + 1)
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template_long[len(template):2*len(template)] = template
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lags = np.arange(-len(template), len(in1) ) - len(template)
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# do the correlation jig
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# do the correlation jig
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corrs = np.zeros_like(lags, dtype=float)
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corrs = np.zeros_like(lags, dtype=float)
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for i, l in enumerate(lags):
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for i, l in enumerate(lags):
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lagged_template = np.roll(template_long, l)
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if l <= 0: # shorten template at the front
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corrs[i] = np.dot(lagged_template, in1_long)
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in1_start = 0
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template_end = template_length
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return corrs, (in1_long, template_long, lags)
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template_start = -template_length - l
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in1_end = max(0, min(in1_length, -template_start)) # 0 =< l + template_length =< in1_lengt
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elif l > in1_length - template_length:
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# shorten template from the back
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in1_end = in1_length
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template_start = 0
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in1_start = min(l, in1_length)
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template_end = max(0, in1_length - l)
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else:
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in1_start = min(l, in1_length)
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in1_end = min(in1_start + template_length, in1_length)
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# full template
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template_start = 0
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template_end = template_length
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# Slice in1 and template
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in1_slice = in1[in1_start:in1_end]
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template_slice = template[template_start:template_end]
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corrs[i] = np.dot(in1_slice, template_slice)
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return corrs, (in1, template, lags)
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def trace_upsampler(template_signal, trace, template_t, trace_t):
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def trace_upsampler(template_signal, trace, template_t, trace_t):
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template_dt = template.t[1] - template.t[0]
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template_dt = template.t[1] - template.t[0]
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@ -297,7 +319,7 @@ if __name__ == "__main__":
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axs[i].axvline(offset, ls='--', **this_kwargs)
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axs[i].axvline(offset, ls='--', **this_kwargs)
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if True: # zoom
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if True: # zoom
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wx = len(template.signal) * (template.t[1] - template.t[0])/2
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wx = len(template.signal) * (template.dt)/2
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t0 = best_time_lag
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t0 = best_time_lag
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old_xlims = axs[0].get_xlim()
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old_xlims = axs[0].get_xlim()
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