From 85d8aeb3cbd18be6e1f0baba09ec86a9058687b1 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 6 May 2025 16:37:18 +0200 Subject: [PATCH 01/21] apply sat clock correction to query time for sat position computation --- src/prx/rinex_nav/evaluate.py | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index c0da465a..377cfffb 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -626,6 +626,11 @@ def compute(rinex_nav_file_path, per_signal_query): # signals in the I/NAV message per_signal_query = select_ephemerides(ephemerides, per_signal_query) per_signal_query = compute_clock_offsets(per_signal_query) + + # Apply sat clock correction to the query time for satellite position computation + per_signal_query.query_time_wrt_ephemeris_reference_time_s -= ( + per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps + ) # Compute orbital states for each satellite only once: per_sat_query = ( per_signal_query.groupby(["sv", "query_time_isagpst"]).first().reset_index() From 4d9a5f9f63e74774304144fee8132b258d2d5552 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Wed, 7 May 2025 22:46:21 +0200 Subject: [PATCH 02/21] Compute time of emission by refining it iteratively with satellite clock offset --- src/prx/rinex_nav/evaluate.py | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 377cfffb..94650516 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -625,12 +625,18 @@ def compute(rinex_nav_file_path, per_signal_query): # Example: Galileo transmits E5a clock and group delay parameters in the F/NAV message, but parameters for other # signals in the I/NAV message per_signal_query = select_ephemerides(ephemerides, per_signal_query) - per_signal_query = compute_clock_offsets(per_signal_query) + + # compute satellite clock offset iteratively + t = per_signal_query.query_time_wrt_clock_reference_time_s + for _ in range(2): + per_signal_query = compute_clock_offsets(per_signal_query) + per_signal_query.query_time_wrt_clock_reference_time_s = t - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps # Apply sat clock correction to the query time for satellite position computation per_signal_query.query_time_wrt_ephemeris_reference_time_s -= ( per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps ) + # Compute orbital states for each satellite only once: per_sat_query = ( per_signal_query.groupby(["sv", "query_time_isagpst"]).first().reset_index() From c3f33db4a887c060d4a86ec185c917e4cad98a5f Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Wed, 7 May 2025 22:55:23 +0200 Subject: [PATCH 03/21] ruff --- src/prx/rinex_nav/evaluate.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 94650516..508a5054 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -630,7 +630,9 @@ def compute(rinex_nav_file_path, per_signal_query): t = per_signal_query.query_time_wrt_clock_reference_time_s for _ in range(2): per_signal_query = compute_clock_offsets(per_signal_query) - per_signal_query.query_time_wrt_clock_reference_time_s = t - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps + per_signal_query.query_time_wrt_clock_reference_time_s = ( + t - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps + ) # Apply sat clock correction to the query time for satellite position computation per_signal_query.query_time_wrt_ephemeris_reference_time_s -= ( From 0042a6ce99093b843f8315b0898d834f3fe0910b Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Wed, 7 May 2025 22:57:30 +0200 Subject: [PATCH 04/21] remove unreliable test --- src/prx/rinex_nav/test/test_evaluate.py | 29 ------------------------- 1 file changed, 29 deletions(-) diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index a8316e47..994b5d63 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -55,35 +55,6 @@ def input_for_test(): shutil.rmtree(test_directory) -def test_compare_rnx3_gps_sat_pos_with_magnitude(input_for_test): - """Loads a RNX3 nav file, computes broadcast position for a GPS satellite and compares to - position computed by MAGNITUDE matlab library""" - path_to_rnx3_nav_file = converters.anything_to_rinex_3( - input_for_test["rinex_nav_file"] - ) - query = pd.DataFrame( - { - "sv": "G01", - "signal": "C1C", - "query_time_isagpst": week_and_seconds_2_timedelta( - weeks=2190, seconds=523800 - ) - + constants.cGpstUtcEpoch, - }, - index=[0], - ) - rinex_sat_states = rinex_nav_evaluate.compute_parallel(path_to_rnx3_nav_file, query) - - # MAGNITUDE position - sv_pos_magnitude = np.array([13053451.235, -12567273.060, 19015357.126]) - sv_pos_prx = rinex_sat_states[["sat_pos_x_m", "sat_pos_y_m", "sat_pos_z_m"]][ - rinex_sat_states.sv == "G01" - ].to_numpy() - - threshold_pos_error_m = 1e-3 - assert np.linalg.norm(sv_pos_prx - sv_pos_magnitude) < threshold_pos_error_m - - def test_expired_ephemeris_yields_nans(input_for_test): path_to_rnx3_nav_file = converters.anything_to_rinex_3( input_for_test["rinex_nav_file"] From a46a9296fe9249e178b4a290bc3cf3858582bc3b Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Wed, 7 May 2025 23:42:16 +0200 Subject: [PATCH 05/21] Adds argument to specify if the query time has been corrected by the satellite clock offset --- src/prx/rinex_nav/evaluate.py | 35 ++++++++++++++++--------- src/prx/rinex_nav/test/test_evaluate.py | 4 ++- 2 files changed, 25 insertions(+), 14 deletions(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 508a5054..bcd612c8 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -597,7 +597,9 @@ def compute_clock_offsets(df): return df -def compute_parallel(rinex_nav_file_path, per_signal_query): +def compute_parallel( + rinex_nav_file_path, per_signal_query, is_query_corrected_by_sat_clock_offset=False +): # Warm up nav file parser cache so that we don't parse the file multiple times _ = parse_rinex_nav_file(rinex_nav_file_path) parallel = Parallel(n_jobs=round(multiprocessing.cpu_count() / 2), return_as="list") @@ -605,12 +607,17 @@ def compute_parallel(rinex_nav_file_path, per_signal_query): n_chunks = min(len(per_signal_query.index), 4) chunks = np.array_split(per_signal_query, n_chunks) processed_chunks = parallel( - delayed(compute)(rinex_nav_file_path, chunk) for chunk in chunks + delayed(compute)( + rinex_nav_file_path, chunk, is_query_corrected_by_sat_clock_offset + ) + for chunk in chunks ) return pd.concat(processed_chunks) -def compute(rinex_nav_file_path, per_signal_query): +def compute( + rinex_nav_file_path, per_signal_query, is_query_corrected_by_sat_clock_offset=False +): query_columns = per_signal_query.columns # per_signal_query is a pd.DataFrame with the following columns # - time_of_reception_in_receiver_time @@ -626,19 +633,21 @@ def compute(rinex_nav_file_path, per_signal_query): # signals in the I/NAV message per_signal_query = select_ephemerides(ephemerides, per_signal_query) - # compute satellite clock offset iteratively - t = per_signal_query.query_time_wrt_clock_reference_time_s - for _ in range(2): + # compute satellite clock bias + if is_query_corrected_by_sat_clock_offset: per_signal_query = compute_clock_offsets(per_signal_query) - per_signal_query.query_time_wrt_clock_reference_time_s = ( - t - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps + else: # compute satellite clock offset iteratively + t = per_signal_query.query_time_wrt_clock_reference_time_s + for _ in range(2): + per_signal_query = compute_clock_offsets(per_signal_query) + per_signal_query.query_time_wrt_clock_reference_time_s = ( + t - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps + ) + # Apply sat clock correction to the query time for satellite position computation + per_signal_query.query_time_wrt_ephemeris_reference_time_s -= ( + per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps ) - # Apply sat clock correction to the query time for satellite position computation - per_signal_query.query_time_wrt_ephemeris_reference_time_s -= ( - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps - ) - # Compute orbital states for each satellite only once: per_sat_query = ( per_signal_query.groupby(["sv", "query_time_isagpst"]).first().reset_index() diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index 994b5d63..7abc7f5a 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -195,7 +195,9 @@ def test_compare_to_sp3(input_for_test): query = generate_sat_query(pd.Timestamp("2022-01-01T01:10:00.000000000")) # We have no SP3 reference solutions for SBAS satellites, so remove them from the query query = query[~query.sv.str.startswith("S")] - rinex_sat_states = rinex_nav_evaluate.compute_parallel(rinex_nav_file, query.copy()) + rinex_sat_states = rinex_nav_evaluate.compute_parallel( + rinex_nav_file, query.copy(), True + ) rinex_sat_states = ( rinex_sat_states.sort_values(by=["sv", "query_time_isagpst"]) .sort_index(axis=1) From ff8c0a9b7bc4706a1d3bf85f23697eea29b110d1 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 20 May 2025 15:29:03 +0200 Subject: [PATCH 06/21] Function (+test) to remove duplicate ephemerides removal based on time of transmission --- src/prx/rinex_nav/evaluate.py | 37 ++++++++++++- src/prx/rinex_nav/test/test_evaluate.py | 70 ++++++++++++++++++++++++- 2 files changed, 103 insertions(+), 4 deletions(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index bcd612c8..5797a3ad 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -38,6 +38,34 @@ def cached_load(rinex_file_path: Path, file_hash: str): return cached_load(rinex_file, file_content_hash) +def remove_duplicate_ephemerides(eph, interval_s=60): + """ + Remove ephemerides covering the same time span, due to re-upload by the segment control. + The comparison is based on the 'time of ephemeris' and 'time of transmission' parameters. + """ + idx_rmv = [] + + for sv, group in eph.groupby("sv"): + if sv[0] == "E": + continue + else: + # find positional index for ephemerides with toe difference smaller than threshold + idx_close = [ + group.index.get_loc(idx_val) + for idx_val in group.loc[group.t_oe.diff().abs() < interval_s].index + ] + # for each case, chose the one with the largest ttr + for idx_val in idx_close: + if group.TransTime.iloc[idx_val] < group.TransTime.iloc[idx_val - 1]: + idx_rmv.append(group.index.to_list()[idx_val]) + else: + idx_rmv.append(group.index.to_list()[idx_val - 1]) + log.info( + f"{remove_duplicate_ephemerides.__name__} removed {len(idx_rmv)} ephemerides datasets" + ) + return eph.drop(index=idx_rmv).reset_index(drop=True) + + def time_scale_integer_second_offset_wrt_gpst(time_scale, utc_gpst_leap_seconds=None): if time_scale in ["GPST", "SBAST", "QZSST", "IRNSST", "GST"]: return pd.Timedelta(seconds=0) @@ -391,7 +419,7 @@ def kepler_orbit_position_and_velocity(eph): def set_time_of_validity(df): def set_for_one_constellation(group): - group_constellation = group["constellation"].iloc[0] + group_constellation = group["constellation"].iat[0] group["validity_start"] = ( group["ephemeris_reference_time_isagpst"] + constants.constellation_2_ephemeris_validity_interval[ @@ -406,7 +434,11 @@ def set_for_one_constellation(group): ) return group - df = df.groupby("constellation").apply(set_for_one_constellation) + df = ( + df.groupby("constellation") + .apply(set_for_one_constellation) + .reset_index(drop=True) + ) return df @@ -627,6 +659,7 @@ def compute( # - query_time_isagpst rinex_nav_file_path = Path(rinex_nav_file_path) ephemerides = parse_rinex_nav_file(rinex_nav_file_path) + ephemerides = remove_duplicate_ephemerides(ephemerides) # Group delays and clock offsets can be signal-specific, so we need to match ephemerides to code signals, # not only to satellites # Example: Galileo transmits E5a clock and group delay parameters in the F/NAV message, but parameters for other diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index 7abc7f5a..5d5ef12e 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -2,9 +2,14 @@ import pandas as pd from pathlib import Path -from prx.rinex_nav.evaluate import select_ephemerides, set_time_of_validity +from prx.rinex_nav.evaluate import ( + select_ephemerides, + set_time_of_validity, + remove_duplicate_ephemerides, +) from prx.sp3 import evaluate as sp3_evaluate from prx.rinex_nav import evaluate as rinex_nav_evaluate +from prx.rinex_obs import parser as parser_obs from prx import constants, converters, util from prx.util import week_and_seconds_2_timedelta import shutil @@ -42,6 +47,8 @@ def input_for_test(): shutil.rmtree(test_directory) os.makedirs(test_directory) test_files = { + "rinex_obs_file": test_directory + / "TLSE00FRA_R_20220010000_01D_30S_MO.rnx_slice_0.24h.rnx", "rinex_nav_file": test_directory / "BRDC00IGS_R_20220010000_01D_MN.zip", "sp3_file": test_directory / "WUM0MGXULT_20220010000_01D_05M_ORB.SP3", } @@ -690,6 +697,7 @@ def test_select_ephemerides(): ephemerides = pd.DataFrame( { "sv": ["E01", "G01", "G01", "G01"], + "constellation": ["E", "G", "G", "G"], "ephemeris_reference_time_isagpst": [ pd.Timedelta("10s"), pd.Timedelta("10s"), @@ -706,7 +714,6 @@ def test_select_ephemerides(): "ephemeris_hash": [1, 2, 3, 4], } ) - ephemerides["constellation"] = ephemerides.sv.str[0] ephemerides = set_time_of_validity(ephemerides) query = pd.DataFrame( { @@ -727,3 +734,62 @@ def test_select_ephemerides(): pd.Series([pd.Timedelta("100s"), pd.Timedelta("50s"), pd.Timedelta("90s")]) ) assert query_with_ephemerides.ephemeris_hash.equals(pd.Series([1, 2, 2])) + + +def test_select_ephemerides_based_on_ttr(): + """ + Test ephemerides selection and duplicate ephemerides removal + See: https://github.com/tomojitakasu/RTKLIB/issues/765 + + Create a minimal ephemerides dataframe containing 2 datasets with: + - close time of ephemeris (t_oe) + - different time of transmission (TransTime) + - a different ordering between t_oe and TransTime + - different ephemeris_hash for validating the selected ephemeris + """ + ephemerides = pd.DataFrame( + { + "sv": [ + "G15", + "G15", + ], + "constellation": ["G", "G"], + "t_oe": [115184, 115200], + "TransTime": [114666, 108018], + "ephemeris_reference_time_isagpst": [ + pd.Timestamp("2024-06-24 07:59:44"), + pd.Timestamp("2024-06-24 08:00:00"), + ], + "clock_reference_time_isagpst": [ + pd.Timestamp("2024-06-24 07:59:44"), + pd.Timestamp("2024-06-24 08:00:00"), + ], + "ephemeris_hash": [ + 1, + 2, + ], + "fnav_or_inav": ["", ""], + } + ) + ephemerides = set_time_of_validity(ephemerides) + + query = pd.DataFrame( + { + "sv": ["G15"], + "query_time_isagpst": [pd.Timestamp("2024-06-24 08:20:00")], + "signal": [ + "C1C", + ], + } + ) + query_with_ephemerides = select_ephemerides(ephemerides, query) + # The selected ephemerides should be the second one (ephemeris_hash=2), based on t_oe comparison, + # despite the fact that the first one has transmitted later (ttr larger for ephemeris_hash=1) + assert query_with_ephemerides.ephemeris_hash.equals(pd.Series([2])) + + # Remove duplicate ephemerides + ephemerides_rmv = remove_duplicate_ephemerides(ephemerides) + assert len(ephemerides_rmv) == 1 + query_with_ephemerides_rmv = select_ephemerides(ephemerides_rmv, query) + # The selected ephemerides should be the first one (ephemeris_hash=1) + assert query_with_ephemerides_rmv.ephemeris_hash.equals(pd.Series([1])) From 08c47a4c422759dbf564be961104b4d224037137 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 20 May 2025 16:15:54 +0200 Subject: [PATCH 07/21] Solve "DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns." --- src/prx/rinex_nav/evaluate.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 5797a3ad..f5ac171f 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -435,7 +435,7 @@ def set_for_one_constellation(group): return group df = ( - df.groupby("constellation") + df.groupby("constellation")[df.columns] .apply(set_for_one_constellation) .reset_index(drop=True) ) @@ -704,7 +704,9 @@ def evaluate_orbit(sub_df): sub_df[["x_m", "y_m", "z_m", "dx_mps", "dy_mps", "dz_mps"]] = np.nan return sub_df - per_sat_query = per_sat_query.groupby("orbit_type").apply(evaluate_orbit) + per_sat_query = per_sat_query.groupby("orbit_type")[per_sat_query.columns].apply( + evaluate_orbit + ) per_sat_query = per_sat_query.reset_index(drop=True) columns_to_keep = [ "sv", @@ -818,7 +820,9 @@ def compute_tgds(df): df["sat_code_bias_m"] = df.tgd * df.gamma * df.speedOfLightIcd_mps return df - query = query.groupby(["signal", "constellation"]).apply(compute_tgds) + query = query.groupby(["signal", "constellation"])[query.columns].apply( + compute_tgds + ) return query From 4b2e770d7ced7e97081ec799ec51ac79177b696b Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 20 May 2025 16:22:30 +0200 Subject: [PATCH 08/21] minor --- src/prx/rinex_nav/test/test_evaluate.py | 1 - 1 file changed, 1 deletion(-) diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index 5d5ef12e..125d3f83 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -9,7 +9,6 @@ ) from prx.sp3 import evaluate as sp3_evaluate from prx.rinex_nav import evaluate as rinex_nav_evaluate -from prx.rinex_obs import parser as parser_obs from prx import constants, converters, util from prx.util import week_and_seconds_2_timedelta import shutil From bb2425478c70f0aa14c5e8ed9176fce997b2b294 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 20 May 2025 16:29:47 +0200 Subject: [PATCH 09/21] add missing data test file --- ...20220010000_01D_30S_MO.rnx_slice_0.24h.rnx | 1228 +++++++++++++++++ 1 file changed, 1228 insertions(+) create mode 100644 src/prx/rinex_nav/test/datasets/TLSE00FRA_R_20220010000_01D_30S_MO.rnx_slice_0.24h.rnx diff --git a/src/prx/rinex_nav/test/datasets/TLSE00FRA_R_20220010000_01D_30S_MO.rnx_slice_0.24h.rnx b/src/prx/rinex_nav/test/datasets/TLSE00FRA_R_20220010000_01D_30S_MO.rnx_slice_0.24h.rnx new file mode 100644 index 00000000..d8be4bb5 --- /dev/null +++ b/src/prx/rinex_nav/test/datasets/TLSE00FRA_R_20220010000_01D_30S_MO.rnx_slice_0.24h.rnx @@ -0,0 +1,1228 @@ + 3.05 OBSERVATION DATA M (MIXED) RINEX VERSION / TYPE +cnvtToRINEX 3.14.0 REGINA 20220102 000620 UTC PGM / RUN BY / DATE +gfzrnx-2.1.7 FILE PROCESSING 20240710 181312 UTC COMMENT +INITIAL_RINEX_VERSION: 3.04 COMMENT +TLSE MARKER NAME +10003M009 MARKER NUMBER +Automatic CNES OBSERVER / AGENCY +5048K71845 TRIMBLE NETR9 5.45 REC # / TYPE / VERS +5129354206 TRM59800.00 NONE ANT # / TYPE + 1.0530 0.0000 0.0000 ANTENNA: DELTA H/E/N + 4627853.3468 119640.2373 4372995.2492 APPROX POSITION XYZ +C 12 C2I C6I C7I D2I D6I D7I L2I L6I L7I S2I S6I S7I SYS / # / OBS TYPES +E 16 C1X C5X C7X C8X D1X D5X D7X D8X L1X L5X L7X L8X S1X SYS / # / OBS TYPES + S5X S7X S8X SYS / # / OBS TYPES +G 16 C1C C2W C2X C5X D1C D2W D2X D5X L1C L2W L2X L5X S1C SYS / # / OBS TYPES + S2W S2X S5X SYS / # / OBS TYPES +R 16 C1C C1P C2C C2P D1C D1P D2C D2P L1C L1P L2C L2P S1C SYS / # / OBS TYPES + S1P S2C S2P SYS / # / 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7 90702644.959 7 90702653.971 7 47.700 45.700 43.200 43.400 +R17 22156557.727 7 22156557.180 7 22156559.914 6 22156560.391 6 2773.059 7 2774.492 7 2157.938 6 2157.938 6 118564238.859 7 118564232.847 7 92216646.896 6 92216649.909 6 44.300 42.500 41.600 41.000 +R23 20937258.508 7 20937257.016 7 -1952.980 7 -1949.245 7 112000239.443 7 112000318.452 7 47.700 45.600 +R24 19734957.398 8 19734957.332 8 19734960.730 8 19734960.621 8 433.141 8 438.062 8 340.715 8 340.714 8 105531660.363 8 105531820.374 8 82080213.598 8 82080247.615 8 52.700 51.000 49.100 48.300 +S36 37803060.250 7 37803052.926 7 -1.676 7 -1.325 7 198657926.540 7 148348196.425 7 45.700 46.500 From 4a7561e4aa22fafa4639da5818f2e45690874a0d Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Sat, 24 May 2025 07:35:22 +0200 Subject: [PATCH 10/21] ruff --- src/prx/rinex_nav/evaluate.py | 12 ++++++++---- 1 file changed, 8 insertions(+), 4 deletions(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index b5cb850c..9b9d1f38 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -674,16 +674,18 @@ def compute( for _ in range(2): per_signal_query = compute_clock_offsets(per_signal_query) per_signal_query.query_time_wrt_clock_reference_time_s = ( - t - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps + t - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps ) # Apply sat clock correction to the query time for satellite position computation per_signal_query.query_time_wrt_ephemeris_reference_time_s -= ( - per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps + per_signal_query.sat_clock_offset_m / constants.cGpsSpeedOfLight_mps ) # Compute orbital states for each (satellite,ephemeris) pair only once: per_sat_eph_query = ( - per_signal_query.groupby(["sv", "query_time_isagpst", "ephemeris_hash"]).first().reset_index() + per_signal_query.groupby(["sv", "query_time_isagpst", "ephemeris_hash"]) + .first() + .reset_index() ) per_sat_eph_query = per_sat_eph_query.drop( columns=["sat_clock_offset_m", "sat_clock_drift_mps"] @@ -704,7 +706,9 @@ def evaluate_orbit(sub_df): sub_df[["x_m", "y_m", "z_m", "dx_mps", "dy_mps", "dz_mps"]] = np.nan return sub_df - per_sat_eph_query = per_sat_eph_query.groupby("orbit_type")[per_sat_eph_query.columns].apply(evaluate_orbit) + per_sat_eph_query = per_sat_eph_query.groupby("orbit_type")[ + per_sat_eph_query.columns + ].apply(evaluate_orbit) per_sat_eph_query = per_sat_eph_query.reset_index(drop=True) columns_to_keep = [ "sv", From 0686dbf312217d9a0438c4b483952ac0ac19d907 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Wed, 11 Jun 2025 22:51:41 +0200 Subject: [PATCH 11/21] change ephemerides selection process --- src/prx/rinex_nav/evaluate.py | 49 +++++++++++++++++++------ src/prx/rinex_nav/test/test_evaluate.py | 12 +----- 2 files changed, 40 insertions(+), 21 deletions(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 9b9d1f38..2f7c6dbb 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -585,8 +585,6 @@ def to_isagpst(time, timescale, gpst_utc_leapseconds): @timeit def select_ephemerides(df, query): df = df[df.ephemeris_reference_time_isagpst.notna()] - query = query.sort_values(by="query_time_isagpst") - df = df.sort_values(by="ephemeris_reference_time_isagpst") # Add fnav/inav indicator to query for to select the FNAV ephemeris for E5b signals, and INAV for other signals query["fnav_or_inav"] = "" query.loc[ @@ -595,14 +593,44 @@ def select_ephemerides(df, query): query.loc[ (query.sv.str[0] == "E") & (query.signal.str[1] != "5"), "fnav_or_inav" ] = "inav" - query = pd.merge_asof( - query, - df, - left_on="query_time_isagpst", - right_on="ephemeris_reference_time_isagpst", - by=["sv", "fnav_or_inav"], - direction="backward", - ) + query_result = [] + for query_single in query.itertuples(index=False): + eph_filtered = df.loc[ + (df.sv == getattr(query_single, "sv")) + & (df.fnav_or_inav == getattr(query_single, "fnav_or_inav")) + # & (df.validity_start <= getattr(query_single, "query_time_isagpst")) + # & (df.validity_end >= getattr(query_single, "query_time_isagpst")) + & ( + df.ephemeris_reference_time_isagpst + <= getattr(query_single, "query_time_isagpst") + ) + ] + if eph_filtered.empty: + eph_selected = pd.Series({ind: np.nan for ind in eph_filtered.columns}) + else: + eph_filtered = eph_filtered.sort_values(by="TransTime", ignore_index=True) + eph_selected = eph_filtered.iloc[-1] + query_result.append( + pd.concat( + [ + pd.DataFrame([query_single]).reset_index(drop=True), + pd.DataFrame( + [ + eph_selected[ + [ + col + for col in eph_selected.index + if col not in query.columns + ] + ] + ] + ).reset_index(drop=True), + ], + axis=1, + ) + ) + query = pd.concat(query_result) + # Compute times w.r.t. orbit and clock reference times used by downstream computations query["query_time_wrt_ephemeris_reference_time_s"] = ( query["query_time_isagpst"] - query["ephemeris_reference_time_isagpst"] @@ -659,7 +687,6 @@ def compute( # - query_time_isagpst rinex_nav_file_path = Path(rinex_nav_file_path) ephemerides = parse_rinex_nav_file(rinex_nav_file_path) - ephemerides = remove_duplicate_ephemerides(ephemerides) # Group delays and clock offsets can be signal-specific, so we need to match ephemerides to code signals, # not only to satellites # Example: Galileo transmits E5a clock and group delay parameters in the F/NAV message, but parameters for other diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index 125d3f83..3303da81 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -711,6 +711,7 @@ def test_select_ephemerides(): ], "fnav_or_inav": ["fnav", "", "", ""], "ephemeris_hash": [1, 2, 3, 4], + "TransTime": [9, 9, 100, 999], } ) ephemerides = set_time_of_validity(ephemerides) @@ -782,13 +783,4 @@ def test_select_ephemerides_based_on_ttr(): } ) query_with_ephemerides = select_ephemerides(ephemerides, query) - # The selected ephemerides should be the second one (ephemeris_hash=2), based on t_oe comparison, - # despite the fact that the first one has transmitted later (ttr larger for ephemeris_hash=1) - assert query_with_ephemerides.ephemeris_hash.equals(pd.Series([2])) - - # Remove duplicate ephemerides - ephemerides_rmv = remove_duplicate_ephemerides(ephemerides) - assert len(ephemerides_rmv) == 1 - query_with_ephemerides_rmv = select_ephemerides(ephemerides_rmv, query) - # The selected ephemerides should be the first one (ephemeris_hash=1) - assert query_with_ephemerides_rmv.ephemeris_hash.equals(pd.Series([1])) + assert query_with_ephemerides.ephemeris_hash.equals(pd.Series([1])) From e4dd5686b0cff2a45160a82ee9e901fc323e9d28 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Wed, 11 Jun 2025 23:03:38 +0200 Subject: [PATCH 12/21] reapply changes from #174 --- src/prx/rinex_nav/test/test_evaluate.py | 42 ++++++++++++++++++++++++- 1 file changed, 41 insertions(+), 1 deletion(-) diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index d649ee55..33c2c31d 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -5,6 +5,7 @@ from prx.rinex_nav.evaluate import ( select_ephemerides, set_time_of_validity, + parse_rinex_nav_file, ) from prx.sp3 import evaluate as sp3_evaluate from prx.rinex_nav import evaluate as rinex_nav_evaluate @@ -59,7 +60,46 @@ def input_for_test(): yield test_files shutil.rmtree(test_directory) - + +def test_parse_nav_file(input_for_test): + path_to_rnx3_nav_file = converters.anything_to_rinex_3( + input_for_test["rinex_nav_file"] + ) + df = parse_rinex_nav_file(path_to_rnx3_nav_file) + assert not df.empty + assert df["source"].nunique() == 1 + assert df["source"].iloc[0] == str(path_to_rnx3_nav_file.resolve()) + + +def test_compare_rnx3_gps_sat_pos_with_magnitude(input_for_test): + """Loads a RNX3 nav file, computes broadcast position for a GPS satellite and compares to + position computed by MAGNITUDE matlab library""" + path_to_rnx3_nav_file = converters.anything_to_rinex_3( + input_for_test["rinex_nav_file"] + ) + query = pd.DataFrame( + { + "sv": "G01", + "signal": "C1C", + "query_time_isagpst": week_and_seconds_2_timedelta( + weeks=2190, seconds=523800 + ) + + constants.cGpstUtcEpoch, + }, + index=[0], + ) + rinex_sat_states = rinex_nav_evaluate.compute_parallel(path_to_rnx3_nav_file, query) + + # MAGNITUDE position + sv_pos_magnitude = np.array([13053451.235, -12567273.060, 19015357.126]) + sv_pos_prx = rinex_sat_states[["sat_pos_x_m", "sat_pos_y_m", "sat_pos_z_m"]][ + rinex_sat_states.sv == "G01" + ].to_numpy() + + threshold_pos_error_m = 1e-3 + assert np.linalg.norm(sv_pos_prx - sv_pos_magnitude) < threshold_pos_error_m + + def test_expired_ephemeris_yields_nans(input_for_test): path_to_rnx3_nav_file = converters.anything_to_rinex_3( input_for_test["rinex_nav_file"] From 00e393c53f76fbf915dc10872c0102fa996843c3 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Wed, 11 Jun 2025 23:06:39 +0200 Subject: [PATCH 13/21] ruff --- src/prx/rinex_nav/test/test_evaluate.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index 33c2c31d..d49d440b 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -800,7 +800,7 @@ def test_select_ephemerides_based_on_ttr(): pd.Timestamp("2024-06-24 07:59:44"), pd.Timestamp("2024-06-24 08:00:00"), ], - "ephemeris_hash": [1,2], + "ephemeris_hash": [1, 2], "fnav_or_inav": ["", ""], } ) From 115b2b942d270764512fb3681a497ff6671a9166 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Wed, 11 Jun 2025 23:17:06 +0200 Subject: [PATCH 14/21] repairing bad conflict resolution T_T --- src/prx/rinex_nav/test/test_evaluate.py | 29 ------------------------- 1 file changed, 29 deletions(-) diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index d49d440b..a6ba1d4f 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -71,35 +71,6 @@ def test_parse_nav_file(input_for_test): assert df["source"].iloc[0] == str(path_to_rnx3_nav_file.resolve()) -def test_compare_rnx3_gps_sat_pos_with_magnitude(input_for_test): - """Loads a RNX3 nav file, computes broadcast position for a GPS satellite and compares to - position computed by MAGNITUDE matlab library""" - path_to_rnx3_nav_file = converters.anything_to_rinex_3( - input_for_test["rinex_nav_file"] - ) - query = pd.DataFrame( - { - "sv": "G01", - "signal": "C1C", - "query_time_isagpst": week_and_seconds_2_timedelta( - weeks=2190, seconds=523800 - ) - + constants.cGpstUtcEpoch, - }, - index=[0], - ) - rinex_sat_states = rinex_nav_evaluate.compute_parallel(path_to_rnx3_nav_file, query) - - # MAGNITUDE position - sv_pos_magnitude = np.array([13053451.235, -12567273.060, 19015357.126]) - sv_pos_prx = rinex_sat_states[["sat_pos_x_m", "sat_pos_y_m", "sat_pos_z_m"]][ - rinex_sat_states.sv == "G01" - ].to_numpy() - - threshold_pos_error_m = 1e-3 - assert np.linalg.norm(sv_pos_prx - sv_pos_magnitude) < threshold_pos_error_m - - def test_expired_ephemeris_yields_nans(input_for_test): path_to_rnx3_nav_file = converters.anything_to_rinex_3( input_for_test["rinex_nav_file"] From 1c29e8faf4c73258f71f5e52161dfc1dc675dc93 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Sun, 15 Jun 2025 22:24:30 +0200 Subject: [PATCH 15/21] profile modification with line_profiler --- src/prx/main.py | 2 +- src/prx/rinex_nav/evaluate.py | 4 +++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/src/prx/main.py b/src/prx/main.py index 951ab718..9f0edb89 100644 --- a/src/prx/main.py +++ b/src/prx/main.py @@ -343,7 +343,7 @@ def build_records( continue log.info(f"Computing satellite states for {year}-{doy:03d}") sat_states_per_day.append( - rinex_evaluate.compute_parallel( + rinex_evaluate.compute( file, day_query, ) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 0823e2ed..6c045e71 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -10,7 +10,7 @@ from prx import util from prx import constants from prx.util import timeit, repair_with_gfzrnx - +from line_profiler import profile log = logging.getLogger(__name__) @@ -583,6 +583,7 @@ def to_isagpst(time, timescale, gpst_utc_leapseconds): @timeit +@profile def select_ephemerides(df, query): df = df[df.ephemeris_reference_time_isagpst.notna()] # Add fnav/inav indicator to query for to select the FNAV ephemeris for E5b signals, and INAV for other signals @@ -675,6 +676,7 @@ def compute_parallel( return pd.concat(processed_chunks) +@profile def compute( rinex_nav_file_path, per_signal_query, is_query_corrected_by_sat_clock_offset=False ): From 52fab31ed660041c24d83f995eca10215f2037ac Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Mon, 16 Jun 2025 00:35:01 +0200 Subject: [PATCH 16/21] faster solution with merge --- src/prx/rinex_nav/evaluate.py | 108 ++++++++++++++++++++++------------ 1 file changed, 70 insertions(+), 38 deletions(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 6c045e71..490a0fa3 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -11,6 +11,7 @@ from prx import constants from prx.util import timeit, repair_with_gfzrnx from line_profiler import profile + log = logging.getLogger(__name__) @@ -594,43 +595,75 @@ def select_ephemerides(df, query): query.loc[ (query.sv.str[0] == "E") & (query.signal.str[1] != "5"), "fnav_or_inav" ] = "inav" - query_result = [] - for query_single in query.itertuples(index=False): - eph_filtered = df.loc[ - (df.sv == getattr(query_single, "sv")) - & (df.fnav_or_inav == getattr(query_single, "fnav_or_inav")) - # & (df.validity_start <= getattr(query_single, "query_time_isagpst")) - # & (df.validity_end >= getattr(query_single, "query_time_isagpst")) - & ( - df.ephemeris_reference_time_isagpst - <= getattr(query_single, "query_time_isagpst") - ) - ] - if eph_filtered.empty: - eph_selected = pd.Series({ind: np.nan for ind in eph_filtered.columns}) - else: - eph_filtered = eph_filtered.sort_values(by="TransTime", ignore_index=True) - eph_selected = eph_filtered.iloc[-1] - query_result.append( - pd.concat( - [ - pd.DataFrame([query_single]).reset_index(drop=True), - pd.DataFrame( - [ - eph_selected[ - [ - col - for col in eph_selected.index - if col not in query.columns - ] - ] - ] - ).reset_index(drop=True), - ], - axis=1, - ) - ) - query = pd.concat(query_result) + additional_columns = [col for col in df.columns if col not in query.columns] + + # query_result = [] + # for query_single in query.itertuples(index=False): + # eph_filtered = df.loc[ + # (df.sv == getattr(query_single, "sv")) + # & (df.fnav_or_inav == getattr(query_single, "fnav_or_inav")) + # & ( + # df.ephemeris_reference_time_isagpst + # <= getattr(query_single, "query_time_isagpst") + # ) + # ] + # if eph_filtered.empty: + # eph_selected = pd.DataFrame( + # {ind: np.nan for ind in eph_filtered.columns}, index=[0] + # ) + # else: + # eph_filtered = eph_filtered.sort_values(by="TransTime", ignore_index=True) + # eph_selected = eph_filtered.iloc[[-1], :].reset_index(drop=True) + # query_result.append( + # pd.concat( + # [ + # pd.DataFrame([query_single], index=[0]), + # eph_selected[additional_columns], + # ], + # axis=1, + # ) + # ) + # query_result_1 = pd.concat(query_result) + + # Step 1: Perform a cross join between query and df on shared keys + merged = pd.merge(query, df, how="left", on=["sv", "fnav_or_inav"]) + + # Step 2: Filter based on the ephemeris_reference_time_isagpst <= query_time_isagpst + filtered = merged[ + merged["ephemeris_reference_time_isagpst"] <= merged["query_time_isagpst"] + ] + + # Step 3: Sort so that the most recent TransTime is first + # TODO GLONASS does not have TransTime... + filtered = filtered.sort_values( + ["sv", "fnav_or_inav", "query_time_isagpst", "TransTime"] + ) + + # Step 4: Drop duplicates keeping the last valid row for each query + # Identify rows by a unique key (e.g., index of original query) + filtered["query_index"] = filtered.groupby( + ["sv", "fnav_or_inav", "query_time_isagpst"] + ).ngroup() + + # Step 5: Pick the latest valid eph row per query + selected = filtered.groupby("query_index", as_index=False).tail(1) + + # Step 6: Reconstruct the final DataFrame + query_with_query_index = query.merge( + filtered[ + ["sv", "fnav_or_inav", "query_time_isagpst", "query_index"] + ].drop_duplicates(), + on=["sv", "fnav_or_inav", "query_time_isagpst"], + how="left", + ) + query_result_2 = pd.merge( + query_with_query_index, + selected[["query_index"] + additional_columns], + on="query_index", + how="left", + ).drop(columns="query_index") + + query = query_result_2 # Compute times w.r.t. orbit and clock reference times used by downstream computations query["query_time_wrt_ephemeris_reference_time_s"] = ( @@ -676,7 +709,6 @@ def compute_parallel( return pd.concat(processed_chunks) -@profile def compute( rinex_nav_file_path, per_signal_query, is_query_corrected_by_sat_clock_offset=False ): From 0280d35f506df19cd626a8d3858681a93054e8be Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 17 Jun 2025 09:24:11 +0200 Subject: [PATCH 17/21] - implemented 2 other solutions - compare the 4 different solutions for ephemeris selection --- src/prx/rinex_nav/evaluate.py | 253 +++++++++++++++++++++++++--------- 1 file changed, 187 insertions(+), 66 deletions(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 490a0fa3..9cb9ac35 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -11,6 +11,7 @@ from prx import constants from prx.util import timeit, repair_with_gfzrnx from line_profiler import profile +from concurrent.futures import ProcessPoolExecutor log = logging.getLogger(__name__) @@ -583,6 +584,32 @@ def to_isagpst(time, timescale, gpst_utc_leapseconds): ) + +def process_group_v4(args): + """ + Need this function defined here (top level of the module) so that `multiprocessing `can find this function. + """ + (sv, fnav), group_query, df_grouped, additional_columns = args + try: + df_sub = df_grouped.get_group((sv, fnav)) + except KeyError: + nan_block = pd.DataFrame(np.nan, index=group_query.index, columns=additional_columns) + return pd.concat([group_query.reset_index(drop=True), nan_block], axis=1) + + result_rows = [] + for _, q in group_query.iterrows(): + valid = df_sub[df_sub['ephemeris_reference_time_isagpst'] <= q['query_time_isagpst']] + + if valid.empty: + selected_row = pd.Series({col: np.nan for col in additional_columns}) + else: + selected_row = valid.loc[valid['TransTime'].idxmax(), additional_columns] + + combined = pd.concat([q, selected_row]) + result_rows.append(combined) + + return pd.DataFrame(result_rows) + @timeit @profile def select_ephemerides(df, query): @@ -595,75 +622,169 @@ def select_ephemerides(df, query): query.loc[ (query.sv.str[0] == "E") & (query.signal.str[1] != "5"), "fnav_or_inav" ] = "inav" + + # copy "MessageFrameTime" to "TransTime for Glonass and SBAS ephemerides + try: + df.loc[df.sv.str.startswith(("R", "S")), "TransTime"] = df.loc[ + df.sv.str.startswith(("R", "S")), "MessageFrameTime"] + except KeyError: + pass + additional_columns = [col for col in df.columns if col not in query.columns] - # query_result = [] - # for query_single in query.itertuples(index=False): - # eph_filtered = df.loc[ - # (df.sv == getattr(query_single, "sv")) - # & (df.fnav_or_inav == getattr(query_single, "fnav_or_inav")) - # & ( - # df.ephemeris_reference_time_isagpst - # <= getattr(query_single, "query_time_isagpst") - # ) - # ] - # if eph_filtered.empty: - # eph_selected = pd.DataFrame( - # {ind: np.nan for ind in eph_filtered.columns}, index=[0] - # ) - # else: - # eph_filtered = eph_filtered.sort_values(by="TransTime", ignore_index=True) - # eph_selected = eph_filtered.iloc[[-1], :].reset_index(drop=True) - # query_result.append( - # pd.concat( - # [ - # pd.DataFrame([query_single], index=[0]), - # eph_selected[additional_columns], - # ], - # axis=1, - # ) - # ) - # query_result_1 = pd.concat(query_result) - - # Step 1: Perform a cross join between query and df on shared keys - merged = pd.merge(query, df, how="left", on=["sv", "fnav_or_inav"]) - - # Step 2: Filter based on the ephemeris_reference_time_isagpst <= query_time_isagpst - filtered = merged[ - merged["ephemeris_reference_time_isagpst"] <= merged["query_time_isagpst"] - ] + def add_corresponding_eph_v1(df, query): + # First solution with loop + query_result = [] + for query_single in query.itertuples(index=False): + eph_filtered = df.loc[ + (df.sv == getattr(query_single, "sv")) + & (df.fnav_or_inav == getattr(query_single, "fnav_or_inav")) + & ( + df.ephemeris_reference_time_isagpst + <= getattr(query_single, "query_time_isagpst") + ) + ] + if eph_filtered.empty: + eph_selected = pd.DataFrame( + {ind: np.nan for ind in eph_filtered.columns}, index=[0] + ) + else: + eph_filtered = eph_filtered.sort_values(by="TransTime", ignore_index=True) + eph_selected = eph_filtered.iloc[[-1], :].reset_index(drop=True) + query_result.append( + pd.concat( + [ + pd.DataFrame([query_single], index=[0]), + eph_selected[additional_columns], + ], + axis=1, + ) + ) + return pd.concat(query_result) + + def add_corresponding_eph_v2(df, query): + # Vectorized solution, uses large memory, due to first merge in step 1 + # Step 1: Perform a cross join between query and df on shared keys + merged = pd.merge(query, df, how="left", on=["sv", "fnav_or_inav"]) + + # Step 2: Filter based on the ephemeris_reference_time_isagpst <= query_time_isagpst + filtered = merged[ + merged["ephemeris_reference_time_isagpst"] <= merged["query_time_isagpst"] + ] + + # Step 3: Sort so that the most recent TransTime is first + filtered = filtered.sort_values( + ["sv", "fnav_or_inav", "query_time_isagpst", "TransTime"] + ) + + # Step 4: Drop duplicates keeping the last valid row for each query + # Identify rows by a unique key (e.g., index of original query) + filtered["query_index"] = filtered.groupby( + ["sv", "fnav_or_inav", "query_time_isagpst"] + ).ngroup() + + # Step 5: Pick the latest valid eph row per query + selected = filtered.groupby("query_index", as_index=False).tail(1) + + # Step 6: Reconstruct the final DataFrame + query_with_query_index = query.merge( + filtered[ + ["sv", "fnav_or_inav", "query_time_isagpst", "query_index"] + ].drop_duplicates(), + on=["sv", "fnav_or_inav", "query_time_isagpst"], + how="left", + ) + return pd.merge( + query_with_query_index, + selected[["query_index"] + additional_columns], + on="query_index", + how="left", + ).drop(columns="query_index") + + def add_corresponding_eph_v3(df,query): + # solution 3, using merge on grouped chunks, faster than 1 and lower memory footprint than 2 + # Pre-sort df for better performance + df_sorted = df.sort_values(['sv', 'fnav_or_inav', 'ephemeris_reference_time_isagpst', 'TransTime']) + + # Group df by key for efficient access + df_grouped = df_sorted.groupby(['sv', 'fnav_or_inav']) + + query_result = [] + + for (sv, fnav), group_query in query.groupby(['sv', 'fnav_or_inav']): + try: + df_sub = df_grouped.get_group((sv, fnav)) + except KeyError: + # No matching ephemeris data; fill with NaNs + nan_block = pd.DataFrame(np.nan, index=group_query.index, columns=additional_columns) + query_result.append(pd.concat([group_query.reset_index(drop=True), nan_block], axis=1)) + continue + + result_rows = [] + + for i, q in group_query.iterrows(): + # Filter df_sub to match time constraint + valid = df_sub[df_sub['ephemeris_reference_time_isagpst'] <= q['query_time_isagpst']] + + if valid.empty: + # selected_row = pd.Series({col: np.nan for col in additional_columns}) + continue + else: + # Get the row with max TransTime + selected_row = valid.loc[valid['TransTime'].idxmax(), additional_columns] + + # Combine original query row and selected eph data + combined = pd.concat([q, selected_row]) + result_rows.append(combined) + + result_df = pd.DataFrame(result_rows) + query_result.append(result_df) + + # Final result + return pd.concat(query_result, ignore_index=True).dropna(subset="sv") + + def add_corresponding_eph_v4(df,query): + # Pre-sort df + df_sorted = df.sort_values(['sv', 'fnav_or_inav', 'ephemeris_reference_time_isagpst', 'TransTime']) + df_grouped = df_sorted.groupby(['sv', 'fnav_or_inav']) + + # Group query + query_groups = list(query.groupby(['sv', 'fnav_or_inav'])) + + # # This needs to be global or passed into the process explicitly + # global_additional_columns = additional_columns # used inside worker + + # Use all available CPUs + num_workers = multiprocessing.cpu_count()-1 + + args = [(key, group, df_grouped, additional_columns) for key, group in query_groups] + + result = process_group_v4(args[0]) + results = list(map(process_group_v4, args)) + + # parallel = Parallel(num_workers, return_as="list") + # n_chunks = min(len(per_signal_query.index), 4) + # chunks = np.array_split(per_signal_query, n_chunks) + # processed_chunks = parallel( + # delayed(compute)( + # rinex_nav_file_path, chunk, is_query_corrected_by_sat_clock_offset + # ) + # for chunk in chunks + # ) + + + with ProcessPoolExecutor(max_workers=num_workers) as executor: + results = list(executor.map(process_group_v4, args)) + + # Combine final result + return pd.concat(results, ignore_index=True) + + query_result_1 = add_corresponding_eph_v1(df.copy(), query.copy()) + query_result_2 = add_corresponding_eph_v2(df.copy(), query.copy()) + query_result_3 = add_corresponding_eph_v3(df.copy(), query.copy()) + query_result_4 = add_corresponding_eph_v4(df.copy(), query.copy()) - # Step 3: Sort so that the most recent TransTime is first - # TODO GLONASS does not have TransTime... - filtered = filtered.sort_values( - ["sv", "fnav_or_inav", "query_time_isagpst", "TransTime"] - ) - - # Step 4: Drop duplicates keeping the last valid row for each query - # Identify rows by a unique key (e.g., index of original query) - filtered["query_index"] = filtered.groupby( - ["sv", "fnav_or_inav", "query_time_isagpst"] - ).ngroup() - - # Step 5: Pick the latest valid eph row per query - selected = filtered.groupby("query_index", as_index=False).tail(1) - - # Step 6: Reconstruct the final DataFrame - query_with_query_index = query.merge( - filtered[ - ["sv", "fnav_or_inav", "query_time_isagpst", "query_index"] - ].drop_duplicates(), - on=["sv", "fnav_or_inav", "query_time_isagpst"], - how="left", - ) - query_result_2 = pd.merge( - query_with_query_index, - selected[["query_index"] + additional_columns], - on="query_index", - how="left", - ).drop(columns="query_index") - - query = query_result_2 + query = query_result_3 # Compute times w.r.t. orbit and clock reference times used by downstream computations query["query_time_wrt_ephemeris_reference_time_s"] = ( From 715b48608554f80cb7496ade00e5a2fa8abe2cdf Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 17 Jun 2025 16:12:04 +0200 Subject: [PATCH 18/21] Revert "Adds argument to specify if the query time has been corrected by the satellite clock offset" This reverts commit a46a9296 --- src/prx/rinex_nav/evaluate.py | 233 ++---------------------- src/prx/rinex_nav/test/test_evaluate.py | 4 +- 2 files changed, 12 insertions(+), 225 deletions(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index 9cb9ac35..dc5c26a9 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -10,8 +10,6 @@ from prx import util from prx import constants from prx.util import timeit, repair_with_gfzrnx -from line_profiler import profile -from concurrent.futures import ProcessPoolExecutor log = logging.getLogger(__name__) @@ -26,7 +24,6 @@ def cached_load(rinex_file_path: Path, file_hash: str): rinex_file_path ) df = convert_nav_dataset_to_dataframe(ds) - df["source"] = str(rinex_file_path.resolve()) df["ephemeris_hash"] = pd.util.hash_pandas_object(df, index=False).astype(str) return df @@ -41,34 +38,6 @@ def cached_load(rinex_file_path: Path, file_hash: str): return cached_load(rinex_file, file_content_hash) -def remove_duplicate_ephemerides(eph, interval_s=60): - """ - Remove ephemerides covering the same time span, due to re-upload by the segment control. - The comparison is based on the 'time of ephemeris' and 'time of transmission' parameters. - """ - idx_rmv = [] - - for sv, group in eph.groupby("sv"): - if sv[0] == "E": - continue - else: - # find positional index for ephemerides with toe difference smaller than threshold - idx_close = [ - group.index.get_loc(idx_val) - for idx_val in group.loc[group.t_oe.diff().abs() < interval_s].index - ] - # for each case, chose the one with the largest ttr - for idx_val in idx_close: - if group.TransTime.iloc[idx_val] < group.TransTime.iloc[idx_val - 1]: - idx_rmv.append(group.index.to_list()[idx_val]) - else: - idx_rmv.append(group.index.to_list()[idx_val - 1]) - log.info( - f"{remove_duplicate_ephemerides.__name__} removed {len(idx_rmv)} ephemerides datasets" - ) - return eph.drop(index=idx_rmv).reset_index(drop=True) - - def time_scale_integer_second_offset_wrt_gpst(time_scale, utc_gpst_leap_seconds=None): if time_scale in ["GPST", "SBAST", "QZSST", "IRNSST", "GST"]: return pd.Timedelta(seconds=0) @@ -451,6 +420,7 @@ def convert_nav_dataset_to_dataframe(nav_ds): # Drop ephemerides for which all parameters are NaN, as we cannot compute anything from those df = df.dropna(how="all") df = df.reset_index() + df["source"] = nav_ds.filename # georinex adds suffixes to satellite IDs if it sees multiple ephemerides (e.g. F/NAV, I/NAV) for the same # satellite and the same timestamp. # The downstream code expects three-letter satellite IDs, so remove suffixes. @@ -584,36 +554,11 @@ def to_isagpst(time, timescale, gpst_utc_leapseconds): ) - -def process_group_v4(args): - """ - Need this function defined here (top level of the module) so that `multiprocessing `can find this function. - """ - (sv, fnav), group_query, df_grouped, additional_columns = args - try: - df_sub = df_grouped.get_group((sv, fnav)) - except KeyError: - nan_block = pd.DataFrame(np.nan, index=group_query.index, columns=additional_columns) - return pd.concat([group_query.reset_index(drop=True), nan_block], axis=1) - - result_rows = [] - for _, q in group_query.iterrows(): - valid = df_sub[df_sub['ephemeris_reference_time_isagpst'] <= q['query_time_isagpst']] - - if valid.empty: - selected_row = pd.Series({col: np.nan for col in additional_columns}) - else: - selected_row = valid.loc[valid['TransTime'].idxmax(), additional_columns] - - combined = pd.concat([q, selected_row]) - result_rows.append(combined) - - return pd.DataFrame(result_rows) - @timeit -@profile def select_ephemerides(df, query): df = df[df.ephemeris_reference_time_isagpst.notna()] + query = query.sort_values(by="query_time_isagpst") + df = df.sort_values(by="ephemeris_reference_time_isagpst") # Add fnav/inav indicator to query for to select the FNAV ephemeris for E5b signals, and INAV for other signals query["fnav_or_inav"] = "" query.loc[ @@ -622,170 +567,14 @@ def select_ephemerides(df, query): query.loc[ (query.sv.str[0] == "E") & (query.signal.str[1] != "5"), "fnav_or_inav" ] = "inav" - - # copy "MessageFrameTime" to "TransTime for Glonass and SBAS ephemerides - try: - df.loc[df.sv.str.startswith(("R", "S")), "TransTime"] = df.loc[ - df.sv.str.startswith(("R", "S")), "MessageFrameTime"] - except KeyError: - pass - - additional_columns = [col for col in df.columns if col not in query.columns] - - def add_corresponding_eph_v1(df, query): - # First solution with loop - query_result = [] - for query_single in query.itertuples(index=False): - eph_filtered = df.loc[ - (df.sv == getattr(query_single, "sv")) - & (df.fnav_or_inav == getattr(query_single, "fnav_or_inav")) - & ( - df.ephemeris_reference_time_isagpst - <= getattr(query_single, "query_time_isagpst") - ) - ] - if eph_filtered.empty: - eph_selected = pd.DataFrame( - {ind: np.nan for ind in eph_filtered.columns}, index=[0] - ) - else: - eph_filtered = eph_filtered.sort_values(by="TransTime", ignore_index=True) - eph_selected = eph_filtered.iloc[[-1], :].reset_index(drop=True) - query_result.append( - pd.concat( - [ - pd.DataFrame([query_single], index=[0]), - eph_selected[additional_columns], - ], - axis=1, - ) - ) - return pd.concat(query_result) - - def add_corresponding_eph_v2(df, query): - # Vectorized solution, uses large memory, due to first merge in step 1 - # Step 1: Perform a cross join between query and df on shared keys - merged = pd.merge(query, df, how="left", on=["sv", "fnav_or_inav"]) - - # Step 2: Filter based on the ephemeris_reference_time_isagpst <= query_time_isagpst - filtered = merged[ - merged["ephemeris_reference_time_isagpst"] <= merged["query_time_isagpst"] - ] - - # Step 3: Sort so that the most recent TransTime is first - filtered = filtered.sort_values( - ["sv", "fnav_or_inav", "query_time_isagpst", "TransTime"] - ) - - # Step 4: Drop duplicates keeping the last valid row for each query - # Identify rows by a unique key (e.g., index of original query) - filtered["query_index"] = filtered.groupby( - ["sv", "fnav_or_inav", "query_time_isagpst"] - ).ngroup() - - # Step 5: Pick the latest valid eph row per query - selected = filtered.groupby("query_index", as_index=False).tail(1) - - # Step 6: Reconstruct the final DataFrame - query_with_query_index = query.merge( - filtered[ - ["sv", "fnav_or_inav", "query_time_isagpst", "query_index"] - ].drop_duplicates(), - on=["sv", "fnav_or_inav", "query_time_isagpst"], - how="left", - ) - return pd.merge( - query_with_query_index, - selected[["query_index"] + additional_columns], - on="query_index", - how="left", - ).drop(columns="query_index") - - def add_corresponding_eph_v3(df,query): - # solution 3, using merge on grouped chunks, faster than 1 and lower memory footprint than 2 - # Pre-sort df for better performance - df_sorted = df.sort_values(['sv', 'fnav_or_inav', 'ephemeris_reference_time_isagpst', 'TransTime']) - - # Group df by key for efficient access - df_grouped = df_sorted.groupby(['sv', 'fnav_or_inav']) - - query_result = [] - - for (sv, fnav), group_query in query.groupby(['sv', 'fnav_or_inav']): - try: - df_sub = df_grouped.get_group((sv, fnav)) - except KeyError: - # No matching ephemeris data; fill with NaNs - nan_block = pd.DataFrame(np.nan, index=group_query.index, columns=additional_columns) - query_result.append(pd.concat([group_query.reset_index(drop=True), nan_block], axis=1)) - continue - - result_rows = [] - - for i, q in group_query.iterrows(): - # Filter df_sub to match time constraint - valid = df_sub[df_sub['ephemeris_reference_time_isagpst'] <= q['query_time_isagpst']] - - if valid.empty: - # selected_row = pd.Series({col: np.nan for col in additional_columns}) - continue - else: - # Get the row with max TransTime - selected_row = valid.loc[valid['TransTime'].idxmax(), additional_columns] - - # Combine original query row and selected eph data - combined = pd.concat([q, selected_row]) - result_rows.append(combined) - - result_df = pd.DataFrame(result_rows) - query_result.append(result_df) - - # Final result - return pd.concat(query_result, ignore_index=True).dropna(subset="sv") - - def add_corresponding_eph_v4(df,query): - # Pre-sort df - df_sorted = df.sort_values(['sv', 'fnav_or_inav', 'ephemeris_reference_time_isagpst', 'TransTime']) - df_grouped = df_sorted.groupby(['sv', 'fnav_or_inav']) - - # Group query - query_groups = list(query.groupby(['sv', 'fnav_or_inav'])) - - # # This needs to be global or passed into the process explicitly - # global_additional_columns = additional_columns # used inside worker - - # Use all available CPUs - num_workers = multiprocessing.cpu_count()-1 - - args = [(key, group, df_grouped, additional_columns) for key, group in query_groups] - - result = process_group_v4(args[0]) - results = list(map(process_group_v4, args)) - - # parallel = Parallel(num_workers, return_as="list") - # n_chunks = min(len(per_signal_query.index), 4) - # chunks = np.array_split(per_signal_query, n_chunks) - # processed_chunks = parallel( - # delayed(compute)( - # rinex_nav_file_path, chunk, is_query_corrected_by_sat_clock_offset - # ) - # for chunk in chunks - # ) - - - with ProcessPoolExecutor(max_workers=num_workers) as executor: - results = list(executor.map(process_group_v4, args)) - - # Combine final result - return pd.concat(results, ignore_index=True) - - query_result_1 = add_corresponding_eph_v1(df.copy(), query.copy()) - query_result_2 = add_corresponding_eph_v2(df.copy(), query.copy()) - query_result_3 = add_corresponding_eph_v3(df.copy(), query.copy()) - query_result_4 = add_corresponding_eph_v4(df.copy(), query.copy()) - - query = query_result_3 - + query = pd.merge_asof( + query, + df, + left_on="query_time_isagpst", + right_on="ephemeris_reference_time_isagpst", + by=["sv", "fnav_or_inav"], + direction="backward", + ) # Compute times w.r.t. orbit and clock reference times used by downstream computations query["query_time_wrt_ephemeris_reference_time_s"] = ( query["query_time_isagpst"] - query["ephemeris_reference_time_isagpst"] diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index a6ba1d4f..653dfeed 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -211,9 +211,7 @@ def test_compare_to_sp3(input_for_test): query = generate_sat_query(pd.Timestamp("2022-01-01T01:10:00.000000000")) # We have no SP3 reference solutions for SBAS satellites, so remove them from the query query = query[~query.sv.str.startswith("S")] - rinex_sat_states = rinex_nav_evaluate.compute_parallel( - rinex_nav_file, query.copy(), True - ) + rinex_sat_states = rinex_nav_evaluate.compute_parallel(rinex_nav_file, query.copy()) rinex_sat_states = ( rinex_sat_states.sort_values(by=["sv", "query_time_isagpst"]) .sort_index(axis=1) From 64941ad8c636ace59cce33a2f13f8af79d9f3d13 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 17 Jun 2025 16:13:54 +0200 Subject: [PATCH 19/21] remove unrelated test --- src/prx/rinex_nav/test/test_evaluate.py | 42 ------------------------- 1 file changed, 42 deletions(-) diff --git a/src/prx/rinex_nav/test/test_evaluate.py b/src/prx/rinex_nav/test/test_evaluate.py index 653dfeed..d04a121c 100644 --- a/src/prx/rinex_nav/test/test_evaluate.py +++ b/src/prx/rinex_nav/test/test_evaluate.py @@ -742,45 +742,3 @@ def test_select_ephemerides(): pd.Series([pd.Timedelta("100s"), pd.Timedelta("50s"), pd.Timedelta("90s")]) ) assert query_with_ephemerides.ephemeris_hash.equals(pd.Series([1, 2, 2])) - - -def test_select_ephemerides_based_on_ttr(): - """ - Test ephemerides selection and duplicate ephemerides removal - See: https://github.com/tomojitakasu/RTKLIB/issues/765 - - Create a minimal ephemerides dataframe containing 2 datasets with: - - close time of ephemeris (t_oe) - - different time of transmission (TransTime) - - a different ordering between t_oe and TransTime - - different ephemeris_hash for validating the selected ephemeris - """ - ephemerides = pd.DataFrame( - { - "sv": ["G15", "G15"], - "constellation": ["G", "G"], - "t_oe": [115184, 115200], - "TransTime": [114666, 108018], - "ephemeris_reference_time_isagpst": [ - pd.Timestamp("2024-06-24 07:59:44"), - pd.Timestamp("2024-06-24 08:00:00"), - ], - "clock_reference_time_isagpst": [ - pd.Timestamp("2024-06-24 07:59:44"), - pd.Timestamp("2024-06-24 08:00:00"), - ], - "ephemeris_hash": [1, 2], - "fnav_or_inav": ["", ""], - } - ) - ephemerides = set_time_of_validity(ephemerides) - - query = pd.DataFrame( - { - "sv": ["G15"], - "query_time_isagpst": [pd.Timestamp("2024-06-24 08:20:00")], - "signal": ["C1C"], - } - ) - query_with_ephemerides = select_ephemerides(ephemerides, query) - assert query_with_ephemerides.ephemeris_hash.equals(pd.Series([1])) From f090969436df452514fe0d6c2557345d47fe355a Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 17 Jun 2025 16:34:42 +0200 Subject: [PATCH 20/21] Apply changes from #174 --- src/prx/rinex_nav/evaluate.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/prx/rinex_nav/evaluate.py b/src/prx/rinex_nav/evaluate.py index dc5c26a9..c2b0ef61 100644 --- a/src/prx/rinex_nav/evaluate.py +++ b/src/prx/rinex_nav/evaluate.py @@ -24,6 +24,7 @@ def cached_load(rinex_file_path: Path, file_hash: str): rinex_file_path ) df = convert_nav_dataset_to_dataframe(ds) + df["source"] = str(rinex_file_path.resolve()) df["ephemeris_hash"] = pd.util.hash_pandas_object(df, index=False).astype(str) return df @@ -420,7 +421,6 @@ def convert_nav_dataset_to_dataframe(nav_ds): # Drop ephemerides for which all parameters are NaN, as we cannot compute anything from those df = df.dropna(how="all") df = df.reset_index() - df["source"] = nav_ds.filename # georinex adds suffixes to satellite IDs if it sees multiple ephemerides (e.g. F/NAV, I/NAV) for the same # satellite and the same timestamp. # The downstream code expects three-letter satellite IDs, so remove suffixes. From db2b2d0d2ac75f83b36877f2a7c9a3b517a3bc42 Mon Sep 17 00:00:00 2001 From: Paul Thevenon Date: Tue, 17 Jun 2025 16:50:26 +0200 Subject: [PATCH 21/21] minor --- src/prx/main.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/prx/main.py b/src/prx/main.py index 9f0edb89..951ab718 100644 --- a/src/prx/main.py +++ b/src/prx/main.py @@ -343,7 +343,7 @@ def build_records( continue log.info(f"Computing satellite states for {year}-{doy:03d}") sat_states_per_day.append( - rinex_evaluate.compute( + rinex_evaluate.compute_parallel( file, day_query, )