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Residual based diffusion #48

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merged 8 commits into from
Aug 18, 2023
Merged

Residual based diffusion #48

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0b486c8
Improve KM plots
arshednabeel Mar 27, 2023
9e1b598
Temporary commit
arshednabeel Mar 28, 2023
f17ce3d
residual based diffusion
arshednabeel Apr 8, 2023
e0ae219
Bugfixes in noise diagnostics computation
arshednabeel Aug 17, 2023
21b35b6
Bugfixes in noise diagnostics computation
arshednabeel Aug 17, 2023
dc4fa5f
Do not rescale residuals in noise diagnostics
arshednabeel Aug 18, 2023
13080e6
Do not rescale residuals in noise diagnostics
arshednabeel Aug 18, 2023
5194f01
Restore model data files
arshednabeel Aug 18, 2023
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Bugfixes in noise diagnostics computation
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@arshednabeel
arshednabeel committed Aug 17, 2023
commit 21b35b69e31681fb345f8628a1822cef85ad84d8
4 changes: 2 additions & 2 deletions pydaddy/analysis.py
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Expand Up @@ -237,8 +237,8 @@ def _residual_timeseries_vector(self, X, Y, Dt, bins_x, bins_y, inc_x, inc_y,
except IndexError:
bin_y = len(bins_y) - 1

res_x[i] = (res_x[i] - avg_drift_x[bin_x, bin_y] * t_int) #/ ((avg_diff_x[bin_x, bin_y] + avg_diff_xy[bin_x, bin_y]) * np.sqrt(t_int))
res_y[i] = (res_y[i] - avg_drift_y[bin_x, bin_y] * t_int) #/ ((avg_diff_y[bin_x, bin_y] + avg_diff_xy[bin_x, bin_y]) * np.sqrt(t_int))
res_x[i] = (res_x[i] - avg_drift_x[bin_x, bin_y] * t_int) #/ np.sqrt((avg_diff_x[bin_x, bin_y] + avg_diff_xy[bin_x, bin_y]) * t_int)
res_y[i] = (res_y[i] - avg_drift_y[bin_x, bin_y] * t_int) #/ np.sqrt((avg_diff_y[bin_x, bin_y] + avg_diff_xy[bin_x, bin_y]) * t_int)

return res_x / np.sqrt(Dt * t_int), res_y / np.sqrt(Dt * t_int)

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