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Move and Rename SDECData to VisualizationData #2928
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property access patterns between virtual and real packet modes
*beep* *bop* 3 RET505 [ ] Unnecessary `else` after `return` statement
3 RET506 [ ] Unnecessary `elif` after `raise` statement
2 F401 [*] `matplotlib.cm` imported but unused
Complete output(might be large): tardis/visualization/plot_util.py:47:5: RET505 Unnecessary `else` after `return` statement
tardis/visualization/tools/liv_plot.py:4:25: F401 [*] `matplotlib.cm` imported but unused
tardis/visualization/tools/liv_plot.py:7:18: F401 [*] `pandas` imported but unused
tardis/visualization/tools/liv_plot.py:313:13: RET506 Unnecessary `elif` after `raise` statement
tardis/visualization/tools/sdec_plot.py:105:13: RET506 Unnecessary `else` after `raise` statement
tardis/visualization/tools/sdec_plot.py:273:13: RET506 Unnecessary `else` after `raise` statement
tardis/visualization/tools/visualization_data.py:213:9: RET505 Unnecessary `else` after `return` statement
tardis/visualization/tools/visualization_data.py:345:9: RET505 Unnecessary `else` after `return` statement
Found 8 errors.
[*] 2 fixable with the `--fix` option.
|
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #2928 +/- ##
==========================================
- Coverage 70.39% 70.04% -0.35%
==========================================
Files 221 222 +1
Lines 16147 16165 +18
==========================================
- Hits 11366 11323 -43
- Misses 4781 4842 +61 ☔ View full report in Codecov by Sentry. |
*beep* *bop* Significantly changed benchmarks: All benchmarks: Benchmarks that have stayed the same:
| Change | Before [7e37d5fe] <master> | After [b71e734c] | Ratio | Benchmark (Parameter) |
|----------|------------------------------|---------------------|---------|-------------------------------------------------------------------------------------------------------------------------------------|
| | 1.91±5μs | 1.37±0.4μs | ~0.72 | transport_geometry_calculate_distances.BenchmarkTransportGeometryCalculateDistances.time_calculate_distance_line |
| | 511±200ns | 531±100ns | 1.04 | opacities_opacity.BenchmarkMontecarloMontecarloNumbaOpacities.time_compton_opacity_calculation |
| | 48.7±20μs | 50.7±30μs | 1.04 | transport_montecarlo_interaction.BenchmarkTransportMontecarloInteraction.time_line_emission |
| | 46.1±20μs | 48.0±20μs | 1.04 | transport_montecarlo_interaction.BenchmarkTransportMontecarloInteraction.time_line_scatter |
| | 2.73±0ms | 2.77±0.01ms | 1.01 | opacities_opacity_state.BenchmarkOpacitiesOpacityState.time_opacity_state_initialize('scatter') |
| | 735±0.3ns | 742±1ns | 1.01 | transport_montecarlo_interaction.BenchmarkTransportMontecarloInteraction.time_thomson_scatter |
| | 62.8±0.01ms | 63.1±0.2ms | 1.01 | transport_montecarlo_packet_trackers.BenchmarkTransportMontecarloPacketTrackers.time_rpacket_trackers_to_dataframe |
| | 2.08±0m | 2.08±0m | 1.00 | spectrum_formal_integral.BenchmarkTransportMontecarloFormalIntegral.time_FormalIntegrator_functions |
| | 37.8±0.04μs | 37.7±0.01μs | 1.00 | transport_montecarlo_packet_trackers.BenchmarkTransportMontecarloPacketTrackers.time_generate_rpacket_tracker_list |
| | 7.88±2μs | 7.91±2μs | 1.00 | transport_montecarlo_vpacket.BenchmarkMontecarloMontecarloNumbaVpacket.time_trace_vpacket_volley |
| | 3.73±0.02ms | 3.71±0.01ms | 0.99 | opacities_opacity_state.BenchmarkOpacitiesOpacityState.time_opacity_state_initialize('macroatom') |
| | 206±0.2ns | 203±0.1ns | 0.99 | spectrum_formal_integral.BenchmarkTransportMontecarloFormalIntegral.time_intensity_black_body |
| | 571±100ns | 561±200ns | 0.98 | opacities_opacity.BenchmarkMontecarloMontecarloNumbaOpacities.time_photoabsorption_opacity_calculation |
| | 39.2±0.03s | 38.4±0s | 0.98 | run_tardis.BenchmarkRunTardis.time_run_tardis |
| | 1.06±0m | 1.04±0m | 0.98 | run_tardis.BenchmarkRunTardis.time_run_tardis_rpacket_tracking |
| | 1.22±0μs | 1.18±0μs | 0.97 | transport_geometry_calculate_distances.BenchmarkTransportGeometryCalculateDistances.time_calculate_distance_boundary |
| | 2.53±0.4ms | 2.45±0.5ms | 0.97 | transport_montecarlo_single_packet_loop.BenchmarkTransportMontecarloSinglePacketLoop.time_single_packet_loop |
| | 23.2±6μs | 22.3±5μs | 0.96 | transport_montecarlo_packet_trackers.BenchmarkTransportMontecarloPacketTrackers.time_generate_rpacket_last_interaction_tracker_list |
| | 1.74±0.02ms | 1.66±0ms | 0.95 | transport_montecarlo_main_loop.BenchmarkTransportMontecarloMontecarloMainLoop.time_montecarlo_main_loop |
| | 3.10±0.6μs | 2.95±0.5μs | 0.95 | transport_montecarlo_vpacket.BenchmarkMontecarloMontecarloNumbaVpacket.time_trace_bad_vpacket |
| | 6.33±1μs | 5.96±1μs | 0.94 | transport_montecarlo_vpacket.BenchmarkMontecarloMontecarloNumbaVpacket.time_trace_vpacket |
| | 571±100ns | 532±200ns | 0.93 | opacities_opacity.BenchmarkMontecarloMontecarloNumbaOpacities.time_pair_creation_opacity_calculation |
| | 2.05±2μs | 1.90±2μs | 0.93 | transport_montecarlo_estimators_radfield_estimator_calcs.BenchmarkMontecarloMontecarloNumbaPacket.time_update_line_estimators |
| | 3.21±0.5μs | 2.98±0.5μs | 0.93 | transport_montecarlo_vpacket.BenchmarkMontecarloMontecarloNumbaVpacket.time_trace_vpacket_within_shell |
If you want to see the graph of the results, you can check it here |
Let's make a notebook showing these in actions. Each plot should be redone with plotly and Matplotlib to check how well that works. |
The class is duplicating a lot of information from the simulation. Could the spectrum, in particular, be separated and simply used via the spectrum class rather than copying the data into this new class? Similarly, the geometry information (v_inner, r_inner etc) is being duplicated. It may be more useful to duplicate the entire geometry class from the simulation if that is what is needed for visualization. If the geometry parts are NOT all needed, then referencing the simulation rather than duplicating the data would be best. As far as the notebook goes, it would be most useful to demonstrate the packet tracking information that is contained in the class, since the spectrum information is already plotted elsewhere e.g. in the quickstart notebook. Please comment etc with your ideas for any better ways to package the data necessary for the SDEC and LIV plots and how that might look. Multiple classes may be needed, but in general it would be good to limit duplication as I noted above. |
📝 Description
Type: 🪲
bugfix
| 🚀feature
| ☣️breaking change
| 🚦testing
| 📝documentation
| 🎢infrastructure
This PR moves and shifts sdec data to VisualizationData for clarity purposes and also refactors some of its methods to improve readability.
📌 Resources
Examples, notebooks, and links to useful references.
🚦 Testing
How did you test these changes?
☑️ Checklist
build_docs
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