dummy

Technical_notes/timing_dlogL/notes.md

@@ -375,6 +375,11 @@ phase1_timing = traj_timing * 1500 / 3600
 - 12 parameters: aligned spins, tides but phase marginalization
 - flow = 30 Hz => duration = 64 sec
 ```py
+# 64 sec
+len(frequency_domain_strain) = 120833
+ifo.frequency_mask.sum() = 119063
+
+# 128 sec
 len(frequency_domain_strain) = 120833
 ifo.frequency_mask.sum() = 119063
 ```
@@ -382,13 +387,23 @@ ifo.frequency_mask.sum() = 119063
 ### Timing at the end of phase1
 
 ### Timing of functions directly
+- 64 sec
 ```py
 %timeit likelihood_gradient.calculate_dlogL_s_minus_h_dh():
   900 ms ± 14.5 ms ??
+  1.05 s ± 53.1 ms
+  843 ms ± 15.8 ms # (with inner_product_mask_fixed)
+  945 ms ± 16.3 ms # (with inner_product_mask_fixed)
+  1.05 s ± 74 ms # (with inner_product_mask_fixed)
 %timeit waveform_generator.frequency_domain_strain(self.likelihood.parameters):
   31.3 ms ± 283 µs
+%timeit ifo.get_detector_response_geocent(waveform_polarizations, parameters):
+  1.08 ms ± 5.15 µs
+  1.4 ms ± 40.9 µs
 %timeit ifo.get_fd_time_translation(self.likelihood.parameters):
   4.05 ms ± 29.1 µs
+%timeit signal_ifo[self.strain_data.frequency_mask] * exp_two_pi_f_dt:
+  650 µs ± 10.7 µs
 %timeit ifo.get_detector_response(waveform_polarizations, self.likelihood.parameters, exp_two_pi_f_dt=ifo.exp_two_pi_f_dt_at_point):
   2.19 ms ± 34.1 µs
 %timeit ifo.inner_product(template_plus):
@@ -396,6 +411,23 @@ ifo.frequency_mask.sum() = 119063
 %timeit nwip(ifo.fd_strain, template_plus, ifo.psd_array, ifo.strain_data.duration):
   1.15 ms ± 93.9 µs
 ```
+- 128 sec
+```py
+%timeit likelihood_gradient.calculate_dlogL_s_minus_h_dh():
+  1.88 s ± 18.9 ms # (with inner_product_mask_fixed)
+%timeit waveform_generator.frequency_domain_strain(self.likelihood.parameters):
+  71.8 ms ± 298 µs
+%timeit ifo.get_detector_response_geocent(waveform_polarizations, parameters):
+  2.83 ms ± 39 µs
+%timeit ifo.get_fd_time_translation(self.likelihood.parameters):
+  9.66 ms ± 402 µs
+%timeit signal_ifo[self.strain_data.frequency_mask] * exp_two_pi_f_dt:
+  1.31 ms ± 6.4 µs
+%timeit ifo.get_detector_response(waveform_polarizations, self.likelihood.parameters, exp_two_pi_f_dt=ifo.exp_two_pi_f_dt_at_point):
+  4.83 ms ± 140 µs
+%timeit ifo.inner_product_mask_fixed(ifo.template_at_point):
+  3.47 ms ± 36.9 µs
+```
 
 ### Why `ifo.inner_product()` takes longer than `nwip()`
 
@@ -425,47 +457,58 @@ ifo.strain_data._frequency_domain_strain * ifo.strain_data.frequency_mask
 I could create a new nwip function for my Interferometer Class which would be like:
 ```py
 def inner_product_mask_fixed(self, signal_masked):
-  return gwutils.noise_weighted_inner_product(
-      aa=signal_masked,
-      bb=ifo.strain_data.frequency_domain_strain_masked,
-      power_spectral_density=ifo.power_spectral_density_array_windowed_masked,
-      duration=ifo.strain_data.duration)
+  return gwutilsnwip(
+      aa=signal[self.strain_data.frequency_mask],
+      bb=self.frequency_domain_strain_masked,
+      power_spectral_density=self.power_spectral_density_array_masked_windowed,
+      duration=self.strain_data.duration)
 ```
 
 ### Timing analysis
 - Parameters contributions to `dlogL`
 
 
-|  | Diff method | h_source | exp(i * 2pi * f * dt) | s = s * exp(i * 2pi * f * dt) | < h1 \| h2 > |
-|:----|:----|:----:|:----:|:----:|:----:|
-| At point | - | 1 | 3 | 3 | 6 |
-| cos(iota) | Forward | 1 | 0 | 3 | 6 |
-| psi | Forward | 0 | 0 | 3 | 6 |
-| ln(D) | Forward | 1 | 0 | 3 | 6 |
-| ln(Mc) | Central | 2 | 0 | 6 | 9 |
-| ln(mu) | Central | 2 | 0 | 6 | 9 |
-| sin(dec) | Forward | 0 | 3 | 3 | 6 |
-| ra | Forward | 0 | 3 | 3 | 6 |
-| ln(tc) | Central | 0 | 6 | 6 | 9 |
-| chi_1 | Central | 2 | 0 | 6 | 9 |
-| chi_2 | Central | 2 | 0 | 6 | 9 |
-| lambda_1 | Forward | 1 | 0 | 3 | 6 |
-| lambda_2 | Forward | 1 | 0 | 3 | 6 |
-| **TOTAL** | - | 15 | 15 | 54 | 93 |
-| **IMRPhenomD_NRTidal, 30Hz** | **909ms** | 15x31.3ms | 15x4.05ms | 54x2.2ms | 93x2.8ms |
+|  | Diff method | h_source | F+h+ + Fxhx | exp(i * 2pi * f * dt) | s = s * exp(i * 2pi * f * dt) | < h1 \| h2 > |
+|:----|:----|:----:|:----:|:----:|:----:|:----:|
+| At point | - | 1 | 3 | 3 | 3 | 6 |
+| cos(iota) | Forward | 1 | 3 | 0 | 3 | 6 |
+| psi | Forward | 0 | 3 | 0 | 3 | 6 |
+| ln(D) | Forward | 0 | 3 | 0 | 3 | 6 |
+| ln(Mc) | Central | 2 | 6 | 0 | 6 | 9 |
+| ln(mu) | Central | 2 | 6 | 0 | 6 | 9 |
+| sin(dec) | Forward | 0 | 3 | 3 | 3 | 6 |
+| ra | Forward | 0 | 3 | 3 | 3 | 6 |
+| ln(tc) | Central | 0 | 6 | 6 | 6 | 9 |
+| chi_1 | Central | 2 | 6 | 0 | 6 | 9 |
+| chi_2 | Central | 2 | 6 | 0 | 6 | 9 |
+| lambda_1 | Forward | 1 | 3 | 0 | 3 | 6 |
+| lambda_2 | Forward | 1 | 3 | 0 | 3 | 6 |
+| **TOTAL** | - | 12 | 54 | 15 | 54 | 93 |
+| **IMRPhenomD_NRTidal, 30Hz 64sec** | **642ms** | 12x31.3ms | 54x1.24ms | 15x4.05ms | 54x0.65ms | 93x1.2ms |
+| **IMRPhenomD_NRTidal, 23Hz 128sec** | **1.5sec** | 12x71.8ms | 54x2.8ms | 15x9.7ms | 54x1.3ms | 93x3.5ms |
 
 ```py
+# 64 sec
 swg = 31.3
+fphpfchc = 1.1
 exp2pifdt = 4.05
-stimesexp = 2.2
-nwip = 2.4
+stimesexp = 0.65
+nwiprd = 1.2
 
-n_swg = 15
+# 128 sec
+# swg =71.8
+# fphpfchc =2.8
+# exp2pifdt = 9.7
+# stimesexp = 1.3
+# nwiprd = 3.5
+
+n_swg = 12
+n_fphpfchc = 54
 n_exp2pifdt = 15
 n_stimesexp = 54
-n_nwip = 93
+n_nwiprd = 93
 
-timing = n_swg*swg + n_exp2pifdt*exp2pifdt + n_stimesexp*stimesexp + n_nwip*nwip
+timing = n_swg*swg + n_fphpfchc*fphpfchc + n_exp2pifdt*exp2pifdt + n_stimesexp*stimesexp + n_nwiprd*nwiprd
 ```
 
 
@@ -473,6 +516,15 @@ timing = n_swg*swg + n_exp2pifdt*exp2pifdt + n_stimesexp*stimesexp + n_nwip*nwip
 
 
 
+
+
+
+
+
+
+
+
+
 ## Analysis forecasts IMRPhenomPv2_NRTidal with 16 parameters
 
 |  | Diff method | h_source | exp(i * 2pi * f * dt) | s = s * exp(i * 2pi * f * dt) | < h1 \| h2 > |

examples/config_files/config_GW170817_IMRPhenomD_NRTidal.ini

@@ -2,6 +2,7 @@
 # Interferometers to run the analysis on.
 ifos = H1,L1,V1
 approximant = IMRPhenomD_NRTidal
+; minimum_frequency_ifos = {H1: 23.0, L1: 23.0, V1: 23.0}
 minimum_frequency_ifos = {H1: 30.0, L1: 30.0, V1: 30.0}
 ; minimum_frequency = 30
 maximum_frequency = 2048.0