geodezyx.time_series package

Submodules

geodezyx.time_series.ts_class module

Created on Fri Aug 2 13:55:33 2019

@author: psakic

class geodezyx.time_series.ts_class.Point(A=0.0, B=0.0, C=0.0, T=0.0, initype='XYZ', sA=0.0, sB=0.0, sC=0.0, name='noname', anex=None)

Bases: object

ENUcalc_pt(refENU)

Calculate East-North-Up (ENU) coordinates relative to a reference point.

Parameters:: refENU (Point) – Reference point for ENU coordinate calculation.
Return type:: None

Notes

Updates the E, N, U attributes and calculates sigmas if available.

ENUset(E=nan, N=nan, U=nan, sE=nan, sN=nan, sU=nan)

Set East-North-Up local topocentric coordinates for the Point.

Parameters:

E (float, optional) – East component in meters. The default is NaN.
N (float, optional) – North component in meters. The default is NaN.
U (float, optional) – Up component in meters. The default is NaN.
sE (float, optional) – Sigma (standard deviation) of E. The default is NaN.
sN (float, optional) – Sigma (standard deviation) of N. The default is NaN.
sU (float, optional) – Sigma (standard deviation) of U. The default is NaN.

Return type:

None

FLHset(F=0.0, L=0.0, H=0.0, sF=0.0, sL=0.0, sH=0.0)

Set geodetic coordinates (F=latitude, L=longitude, H=height) for the Point.

Parameters:

F (float, optional) – Latitude in decimal degrees. The default is 0.
L (float, optional) – Longitude in decimal degrees. The default is 0.
H (float, optional) – Height (altitude) in meters. The default is 0.
sF (float, optional) – Sigma (standard deviation) of F. The default is 0.
sL (float, optional) – Sigma (standard deviation) of L. The default is 0.
sH (float, optional) – Sigma (standard deviation) of H. The default is 0.

Return type:

None

NEDset(N=nan, E=nan, D=nan, sN=nan, sE=nan, sD=nan)

Set North-East-Down local topocentric coordinates for the Point.

Parameters:

N (float, optional) – North component in meters. The default is NaN.
E (float, optional) – East component in meters. The default is NaN.
D (float, optional) – Down component in meters. The default is NaN.
sN (float, optional) – Sigma (standard deviation) of N. The default is NaN.
sE (float, optional) – Sigma (standard deviation) of E. The default is NaN.
sD (float, optional) – Sigma (standard deviation) of D. The default is NaN.

Return type:

None

Tset(T=0)

Set the time/epoch of the Point.

Parameters:: T (float or datetime.datetime, optional) – Time value. If 0, defaults to current time. Can be POSIX timestamp or datetime object. The default is 0.
Return type:: None

Notes

The time is stored in both POSIX timestamp format (self.T) and datetime object format (self.Tdt).

UTMcalc_pt(ellips='wgs84')

Calculate UTM projected coordinates.

Parameters:: ellips (str, optional) – Ellipsoid model to use. The default is ‘wgs84’.
Return type:: None

Notes

Updates the Eutm, Nutm, Uutm attributes.

UTMset(Eutm=nan, Nutm=nan, Uutm=nan, sEutm=nan, sNutm=nan, sUutm=nan)

Set UTM projected coordinates for the Point.

Parameters:

Eutm (float, optional) – UTM Easting coordinate in meters. The default is NaN.
Nutm (float, optional) – UTM Northing coordinate in meters. The default is NaN.
Uutm (float, optional) – Height (altitude) in meters. The default is NaN.
sEutm (float, optional) – Sigma (standard deviation) of Eutm. The default is NaN.
sNutm (float, optional) – Sigma (standard deviation) of Nutm. The default is NaN.
sUutm (float, optional) – Sigma (standard deviation) of Uutm. The default is NaN.

Return type:

None

XYZset(X=0.0, Y=0.0, Z=0.0, sX=0.0, sY=0.0, sZ=0.0)

Set Cartesian XYZ coordinates for the Point.

Parameters:

X (float, optional) – X Cartesian coordinate. The default is 0.
Y (float, optional) – Y Cartesian coordinate. The default is 0.
Z (float, optional) – Z Cartesian coordinate. The default is 0.
sX (float, optional) – Sigma (standard deviation) of X. The default is 0.
sY (float, optional) – Sigma (standard deviation) of Y. The default is 0.
sZ (float, optional) – Sigma (standard deviation) of Z. The default is 0.

Return type:

None

add_offset(dA, dB, dC, coortype='ENU')

Add an offset to the Point coordinates.

Parameters:

dA (float) – Offset for the A component (depends on coortype).
dB (float) – Offset for the B component (depends on coortype).
dC (float) – Offset for the C component (depends on coortype).
coortype (str, optional) – Coordinate type (‘ENU’, ‘XYZ’, ‘FLH’, ‘NED’, ‘UTM’). The default is ‘ENU’.

Return type:

None

helmert_trans(params='itrf2008_2_etrf2000', invert=False)

Apply Helmert transformation to the Point coordinates.

Parameters:

params (str, optional) – Transformation parameter set name. The default is ‘itrf2008_2_etrf2000’.
invert (bool, optional) – If True, apply inverse transformation. The default is False.

Return type:

None

Notes

Updates the Point coordinates in-place based on the Helmert transformation.

keysanex()

Get the keys of the anex (annex data) dictionary.

Returns:: List of keys in the anex dictionary.
Return type:: list

velocity_trans(vx, vy, vz, epoc_init='auto', epoc_end='auto')

Apply velocity-based coordinate transformation over time.

Parameters:

vx (float) – Velocity in X direction (m/year).
vy (float) – Velocity in Y direction (m/year).
vz (float) – Velocity in Z direction (m/year).
epoc_init (float or 'auto', optional) – Initial epoch in decimal years. If ‘auto’, uses the point’s epoch. The default is ‘auto’.
epoc_end (float or 'auto', optional) – Final epoch in decimal years. If ‘auto’, uses the point’s epoch. The default is ‘auto’.

Return type:

None

Notes

At least one of epoc_init or epoc_end must not be ‘auto’. Updates the Point coordinates based on the velocity transformation.

class geodezyx.time_series.ts_class.TimeSeriePoint(stat='STAT')

Bases: object

ENUcalc(refENU)

Calculate ENU coordinates relative to a reference point or time series.

Parameters:: refENU (Point or TimeSeriePoint) – Reference point or time series for ENU calculation.
Return type:: None

Notes

If refENU is a TimeSeriePoint, interpolation is performed to get reference coordinates at each measurement epoch.

ENUcalc_from_first_posi()

Calculate ENU coordinates relative to the first position in the TimeSerie.

Return type:: None

ENUcalc_from_mean_posi(mean_type='median')

Calculate ENU coordinates relative to the mean/median position of the TimeSerie.

Parameters:: mean_type (str, optional) – Type of mean to use (‘median’ or ‘mean’). The default is ‘median’.
Return type:: None

UTMcalc()

Calculate UTM projected coordinates for all points in the TimeSerie.

Return type:: None

Notes

Updates the UTM coordinates (Eutm, Nutm, Uutm) for all points. Sets boolUTM to True.

add_offset(dA, dB, dC, coortype='ENU')

Add an offset to all points in the TimeSerie.

Parameters:

dA (float) – Offset for the A component.
dB (float) – Offset for the B component.
dC (float) – Offset for the C component.
coortype (str, optional) – Coordinate type for offset (‘ENU’, ‘XYZ’, etc.). The default is ‘ENU’.

Return type:

None

add_point(point_inp)

Add a Point to the TimeSerie.

Parameters:: point_inp (Point) – Point object to add to the time series.
Return type:: None

Notes

Marks interpolation as outdated and should be recalculated if needed.

aleapt()

Get a random Point from the TimeSeries.

Returns:: Randomly selected Point object.
Return type:: Point

decimate(dec)

Decimate the TimeSerie by keeping 1 out of every dec points.

Parameters:: dec (int) – Decimation factor (keep 1/dec points).
Return type:: None

Notes

Modifies the TimeSerie in place, removing points to reduce data density.

del_data()

Method to purge the data in the TimeSeriePoint

Return type:: None.

discont_manu_click(fig=1)

Interactively record manual discontinuities by clicking on plot.

Parameters:: fig (int or matplotlib.figure.Figure, optional) – Figure ID or Figure object for interaction. The default is 1.
Returns:: (multi, cid) cursor objects that must be stored as global variables.
Return type:: tuple

Notes

Manual discontinuities are recorded in both the “main” discont list and a separate discont_manu list for identification.

Use SPACE key to record a discontinuity at the cursor position.

Important: cursor objects must be stored as global variables:

multi, cid = tsout.discont_manu_click()

geodezyx.time_series.ts_class_xtra module

Created on Fri Apr 3 2026

@author: psakic

class geodezyx.time_series.ts_class_xtra.Attitude(R=0, P=0, Y=0, T=0, sR=0, sP=0, sY=0, devID='NULL', angtype='deg')

Bases: object

Attitude (Roll, Pitch, Yaw) representation.

Qcalc()

Calculate quaternion from Roll, Pitch, Yaw angles.

Return type:: None

Notes

Stores the quaternion in self.Q.

RPYget()

Get Roll, Pitch, Yaw angles.

Returns:: (Roll, Pitch, Yaw) in degrees.
Return type:: tuple

RPYset(R=0, P=0, Y=0, sR=0, sP=0, sY=0)

Set Roll, Pitch, Yaw angles and their standard deviations.

Parameters:

R (float, optional) – Roll angle in degrees. The default is 0.
P (float, optional) – Pitch angle in degrees. The default is 0.
Y (float, optional) – Yaw angle in degrees. The default is 0.
sR (float, optional) – Standard deviation of Roll. The default is 0.
sP (float, optional) – Standard deviation of Pitch. The default is 0.
sY (float, optional) – Standard deviation of Yaw. The default is 0.

Return type:

None

Tset(T=0)

Set the time/epoch of the Attitude.

Parameters:: T (float or datetime.datetime, optional) – Time value. If 0, defaults to current time. Can be POSIX timestamp or datetime object. The default is 0.
Return type:: None

Notes

The time is stored in both POSIX timestamp format (self.T) and datetime object format (self.Tdt).

class geodezyx.time_series.ts_class_xtra.TimeSerieObs(typeobs='NULL', filepath='')

Bases: object

Time series observation class for homogeneous observation data.

Unlike TimeSeriePoint, objects contain only one type of observation data in a single coordinate form. When reading from files with multiple devices, the read functions return a list of TimeSerieObs objects.

obs

List of observation objects.

Type:: list

typeobs

Type of observations (e.g., ‘RPY’ for Roll-Pitch-Yaw).

Type:: str

nbobs

Number of observations.

Type:: int

add_obs(inObs)

Add an observation to the TimeSerieObs.

Parameters:: inObs (Attitude or observation object) – Observation to add.
Return type:: None

Notes

Marks interpolation as outdated.

aleaobs()

Get a random observation from the TimeSerieObs.

Returns:: Randomly selected observation.
Return type:: observation object

del_data()

Delete all observations from the TimeSerieObs.

Return type:: None

enddate()

Get the last epoch of observations.

Returns:: Last POSIX timestamp.
Return type:: float

interp_get(T)

Get interpolated observations at given times.

Parameters:: T (float or list of float) – Time(s) in POSIX format where interpolation is desired.
Returns:: New TimeSerieObs with interpolated observations at requested times.
Return type:: TimeSerieObs

Notes

Interpolators must be set up first using interp_set().

interp_set(interptype='slinear')

Set up observation interpolators.

Parameters:: interptype (str, optional) – Interpolation type (e.g., ‘slinear’). The default is ‘slinear’.
Return type:: None

Notes

Creates interpolation functions for each observation component. For RPY observations, creates RfT, PfT, YfT interpolators.

interval_nominal()

Get the nominal interval between consecutive observations.

Returns:: Nominal interval in seconds (rounded to 1 decimal place).
Return type:: float

meta_set(path='', devID='NULL', name='')

Set metadata for the TimeSerieObs.

Parameters:

path (str, optional) – File path. The default is ‘’.
devID (str, optional) – Device identifier. The default is ‘NULL’.
name (str, optional) – Observation series name. The default is ‘’.

Return type:

None

plot(diapt=10, alpha=0.8, fig=1, new_style=True)

Plot observations as multi-panel figure.

Parameters:

diapt (float, optional) – Point marker size. The default is 10.
alpha (float, optional) – Alpha (transparency) of points. The default is 0.8.
fig (int or matplotlib.figure.Figure, optional) – Figure ID or Figure object. The default is 1.
new_style (bool, optional) – If True, use 410 layout. If False, use 220 layout. The default is True.

Return type:

None

Notes

Creates a 4-panel plot with phase space and time series for each component.

readfile(filein, indtab=0)

Read observation data from a file.

Parameters:

filein (str) – Path to the file to read.
indtab (int, optional) – Index of the device/table to read. The default is 0.

Return type:

None

Notes

Replaces all internal data with data from file.

startdate()

Get the first epoch of observations.

Returns:: First POSIX timestamp.
Return type:: float

timewin(windows, mode='keep')

Apply a time window filter to the TimeSerieObs.

Parameters:

windows (list) – Time windows to process.
mode (str, optional) – Filter mode (‘keep’ or ‘remove’). The default is ‘keep’.

Return type:

None

to_list()

Export observations as lists of numpy arrays.

Returns:: (A, B, C, T, sA, sB, sC) where: - A, B, C are the main observation components (e.g., R, P, Y for RPY) - T is time (POSIX timestamps) - sA, sB, sC are standard deviations
Return type:: tuple of 7 numpy arrays

class geodezyx.time_series.ts_class_xtra.point_n_click_plot

Bases: object

Interactive point selection tool for plots.

Allows interactive selection of points on a plot by clicking, useful for identifying offsets, discontinuities, or other features of interest.

selectedX

List of selected X-values (timestamps if Xdata_are_time=True).

Type:: list

ver_bar_stk

Stack of vertical bar objects for visualization.

Type:: list

Examples

Basic usage:

>>> PnC = point_n_click_plot()
>>> multi, cid = PnC(fig=1, Xdata_are_time=True)
>>> selected_times = PnC.selectedX

Notes

Press SPACE to record a point
Press R to remove the last recorded point
Cursor objects (multi, cid) must be stored as global variables to keep them in scope during interactive use

geodezyx.time_series.ts_export module

Created on Fri May 12 15:56:33 2023

@author: psakicki

geodezyx.time_series.ts_export.export_ts(ts, outdir, coordtype='ENU', outprefix='', write_header=False)

Export a time series to a custom .ts.dat format.

Parameters:

ts (TimeSeries) – Input time series object containing geodetic data.
outdir (str) – Directory where the output file will be saved.
coordtype (str, optional) – Coordinate type to use for the export (e.g., ‘ENU’), by default ‘ENU’.
outprefix (str, optional) – Prefix to add to the output file name, by default an empty string.
write_header (bool, optional) – If True, writes a header to the output file, by default False.

Notes

The function writes a .ts.dat file containing the time series data.
The file includes geodetic coordinates (East, North, Up or other types) and their uncertainties.
The header, if enabled, describes the columns in the file.

Returns:: The function writes the output file to the specified directory and does not return any value. write_header not well implemented !!!
Return type:: None

geodezyx.time_series.ts_export.export_ts_as_hector_enu(tsin, outdir, outprefix, coordtype='ENU')

export to a HECTOR .enu (and not .neu !) compatible format This format is simpler : just gives MJD E N U

This format is necessary to force a sampling period.

outfile will be writed in /outdir/outprefixSTAT.enu

geodezyx.time_series.ts_export.export_ts_as_midas_tenu(tsin, outdir, outprefix, coordtype='ENU', export_step=True)

Export a time series to a MIDAS .tneu compatible format.

Parameters:

tsin (TimeSeries) – Input time series object containing geodetic data.
outdir (str) – Directory where the output .tneu file will be saved.
outprefix (str) – Prefix to add to the output file name.
coordtype (str, optional) – Coordinate type to use for the export, by default ‘ENU’.
export_step (bool, optional) – If True, exports a step file containing discontinuities, by default True.

Notes

The function writes a .tneu file containing the time series data in MIDAS format.
If export_step is True and the time series contains discontinuities, a separate step file is created.
The .tneu file includes geodetic displacements (East, North, Up) relative to the first point.

Returns:: The function writes the output file(s) to the specified directory and does not return any value.
Return type:: None

geodezyx.time_series.ts_export.export_ts_as_neu(tsin, outdir, outprefix, coordtype='ENU')

Export a time series to a HECTOR .neu compatible format.

Parameters:

tsin (TimeSeries) – Input time series object containing geodetic data.
outdir (str) – Directory where the output .neu file will be saved.
outprefix (str) – Prefix to add to the output file name.
coordtype (str, optional) – Coordinate type to use for the export, by default ‘ENU’.

Notes

The function writes a .neu file containing the time series data in HECTOR format.
The header includes metadata such as the reference epoch, reference position, and field descriptions.
The data section includes geodetic displacements (North, East, Up) relative to the first point.
If the time series lacks XYZ attributes, default values are used for the reference position.

Returns:: The function writes the output file to the specified directory and does not return any value.
Return type:: None

geodezyx.time_series.ts_export.export_ts_as_pbo_pos(tsin, outdir, outprefix='', force=None, force_1st_pt_as_ref=True, verbose=False)

Export a time series to the GAMIT/GLOBK PBO position (.pos) format.

Parameters:

tsin (TimeSeries) – Input time series object containing geodetic data.
outdir (str) – Directory where the output .pos file will be saved.
outprefix (str, optional) – Prefix to add to the output file name, by default an empty string.
force (str, optional) – Determines the data source to use for the export. Can be ‘data’ or ‘data_xyz’. If None, the function decides based on the available attributes, by default None.
force_1st_pt_as_ref (bool, optional) – If True, forces the first point of the time series to be used as the reference position, by default True.
verbose (bool, optional) – If True, enables verbose logging for debugging purposes, by default False.

Notes

The function writes a .pos file containing the time series data in the PBO format.
The header includes metadata such as the reference epoch, reference position, and field descriptions.
The data section includes geodetic coordinates (X, Y, Z) and their uncertainties, along with other metadata.

Returns:: outfile_path – Path to the exported PBO file
Return type:: str

geodezyx.time_series.ts_export.export_ts_as_spotgins(tsin, outdir, ac, data_src='unknown', version=3)

Export time series to SPOTGINS format.

Parameters:

tsin (TimeSeries) – Input time series object
outdir (str) – Output directory path
ac (str) – Analysis Center acronym (3-4 characters)
data_src (str, optional) – Data source identifier, by default “unknown”
version (int, optional) – SPOTGINS format version (2 or 3), by default 2

Returns:

outfile_path – Path to the exported SPOTGINS file

Return type:

str

geodezyx.time_series.ts_export.export_ts_figure_pdf(fig, export_path, filename, close=False): fig can accept a int (id of a Figure) OR the figure Object itself

geodezyx.time_series.ts_export.export_ts_plot(tsin, export_path, coortype='ENU', export_type=('pdf', 'png'), plot_B=False, close_fig_after_export=True): Very beta … to be implemented : merge w/ the export_figure_pdf fct

geodezyx.time_series.ts_fcts module

Created on Fri Aug 2 17:38:41 2019

@author: psakicki

geodezyx.time_series.ts_fcts.add_offset_point(ptin, dA, dB, dC, coortype='ENU')

ONLY IMPLEMENTED FOR ENU FOR THE MOMENT 150415 : remark still necessary ???

coortype == ‘UXYZ’ :: specific case where we correct an Up offset directly in the XYZ coords very usefull for an antenna offset in for a moving GPS (but works only for the up)

geodezyx.time_series.ts_fcts.add_offset_smart_for_GINS_kine(tsin, tslist_offset_3ple, list_windows, coortype='XYZ'): tslist_offset_3ple : list of len N containing (dX,dY,dZ) offsets list_windows : list of len N-1 containing dates of changes

geodezyx.time_series.ts_fcts.add_offset_ts(tsin, dA, dB, dC, coortype='ENU')

return a copy of the tsin (tsin won’t be affected)

coortype == ‘UXYZ’ :: specific case where we correct an Up offset directly in the XYZ coords very usefull for an antenna offset in for a moving GPS (but works only for the up)

geodezyx.time_series.ts_fcts.baselines_calc(ts_list, plani_only=False, substract_offset=<function median>, symetric_calc=False, symetric_storage=True)

Parameters:

ts_list (list) – list of TimeSeries.
plani_only (bool, optional) – If True, compute the baseline varation on the East and North component only. The default is False.
substract_offset (function or None, optional) – A function to substract the offset. Can be np.mean (substract the mean value), np.median (substract the median value), or lambda x: x[0] (substract the 1st value) The default is np.median.
symetric_calc (bool, optional) – If True, compute the baseline variation 2 times, for stat1 > stat2 and stat2 > stat1 Might be useful to compare planimetic computation The default is False.
symetric_storage (bool, optional) – If True, store the baseline variation 2 times, dictstore[stat1][stat2] and dictstore[stat2][stat1] symetric_calc overrides this option The default is True.

Returns:

dictstore – A dictionnary of dictionnaries of Pandas Series, containing the baseline variations e.g. dictstore[stat1][stat2] = bl_series

Return type:

dict

geodezyx.time_series.ts_fcts.bool_cleaner(tsin, boollist, verbose=False): A partir d’une liste de bool de meme longeur que le nbre de points on ne conserve que les points True

geodezyx.time_series.ts_fcts.compar(tstup, coortype='ENU', seuil=3.0, win=[], mode='keep', Dtype='2D3D', namest=0, namend=10, alpha=0.8, diapt=5, verbose=True, print_report=True, plot=True, interp=True)

Compare time series data.

This function compares multiple time series data by calculating differences between a reference time series and other time series. It supports various coordinate types and can perform outlier cleaning using the Median Absolute Deviation (MAD) method.

Parameters:

tstup (tuple of TimeSeriePoint) – Tuple of time series to compare. The first one is the reference.
coortype (str, optional) – Coordinate type (‘ENU’, ‘XYZ’, etc.). Default is ‘ENU’.
seuil (float, optional) – Threshold for MAD cleaning. Default is 3.
win (list, optional) – Time window for comparison. Default is an empty list.
mode (str, optional) – Mode for time window (‘keep’ or ‘del’). Default is ‘keep’.
Dtype (str, optional) – Type of distance calculation (‘2D’, ‘3D’, ‘2D3D’). Default is ‘2D3D’.
namest (int, optional) – Start index for name slicing. Default is 0.
namend (int, optional) – End index for name slicing. Default is 10.
alpha (float, optional) – Alpha value for plotting. Default is 0.8.
diapt (float, optional) – Marker size for plotting. Default is 5.
verbose (bool, optional) – If True, print detailed logs. Default is True.
print_report (bool, optional) – If True, print comparison report. Default is True.
plot (bool, optional) – If True, generate comparison plots. Default is True.
interp (bool, optional) – If True, perform interpolation. Default is True.

Returns:

output – If plot is True, returns a tuple (dicolist, fig). Otherwise, returns dicolist.

Return type:

list or tuple

geodezyx.time_series.ts_fcts.compar_elts_in_ts(ts1, ts2): ts2 must contains less elts than ts1 (ts2 = cleaned one)

geodezyx.time_series.ts_fcts.compar_plot(dico_list_in, namest=0, namend=10, alpha=0.8, diapt=1.5, new_style=True, colormap='gnuplot')

Generate comparison plots for time series data.

This function creates plots to compare multiple time series data. It supports different coordinate types and allows customization of plot appearance.

Parameters:

dico_list_in (list of dict) – List of dictionaries containing time series data to plot.
namest (int, optional) – Start index for name slicing. Default is 0.
namend (int, optional) – End index for name slicing. Default is 10.
alpha (float, optional) – Alpha value for plot markers. Default is 0.8.
diapt (float, optional) – Marker size for plot markers. Default is 1.5.
new_style (bool, optional) – If True, use a new style for the plots. Default is True.
colormap (str, optional) – Colormap to use for the plots. Default is ‘gnuplot’.

Returns:

fig – The generated figure containing the comparison plots.

Return type:

matplotlib.figure.Figure

geodezyx.time_series.ts_fcts.decimate_cleaner(tsin, minval, in_place=False): in_place DOES’NT WORK !!!

geodezyx.time_series.ts_fcts.decimate_cleaner_2(tsin, N, in_place=False): keep a value every N vals

geodezyx.time_series.ts_fcts.detrend_ts(tsin, coortype='ENU', t_origin=None)

geodezyx.time_series.ts_fcts.dist_btwn_2pts(ptA, ptB, coortype='XYZ')

geodezyx.time_series.ts_fcts.dist_diff_btwn_2pts(ptA, ptB)

geodezyx.time_series.ts_fcts.find_pts_from_ts_with_time(tin, tstupin, tol=0.001)

geodezyx.time_series.ts_fcts.helmert_trans(tsin, params='itrf2008_2_etrf2000', invert=False)

geodezyx.time_series.ts_fcts.interpolator_light(T, X, Y, Z)

geodezyx.time_series.ts_fcts.interpolator_with_extrapolated(T, X, Y, Z)

geodezyx.time_series.ts_fcts.linear_regress_find_coeff(tsin, coortype='ENU')

geodezyx.time_series.ts_fcts.linear_regress_ts(tsin, coortype='ENU', titledetails=''): doit être cablé ASAP linear_regress_find_coeff

geodezyx.time_series.ts_fcts.linear_regress_ts_discont(tsin, coortype='ENU')

geodezyx.time_series.ts_fcts.mad_cleaner(tsin, seuil=3.5, method='dist', coortype='ABC', detrend_first=False, output_detrended=False, verbose=False)

Clean time series using Median Absolute Deviation (MAD) method.

Parameters:

tsin (TimeSerie) – Input time series object
seuil (float) – Threshold for outlier detection (default 3.5)
method (str) –
Method of elimination:
- 'dist': eliminate points that are too far in distance from ref position
- 'indep': treat points independently
dist is preferred
coortype (str) – Coordinate type (default 'ABC')
detrend_first (bool) – Remove trend before cleaning (default False)
output_detrended (bool) – Output detrended data (only works if detrend_first is True)
verbose (bool) – Print verbose output (default False)

Returns:

tsout – Cleaned time series

Return type:

TimeSerie

geodezyx.time_series.ts_fcts.mean_list_of_pts(ptslisin): useful for merge fct ONLY IMPLEMENTED FOR ENU coords for the moment

geodezyx.time_series.ts_fcts.mean_posi_multi(tstup)

geodezyx.time_series.ts_fcts.merge(tsin, N): merge N points in one

geodezyx.time_series.ts_fcts.merge_ts(ts_list_in)

Merge several TimeSeriePoint into one

Parameters:: ts_list_in (list of TimeSeriePoint) – list of TimeSeriePoint.
Returns:: ts_out – merged TimeSeriePoint.
Return type:: TimeSeriePoint

geodezyx.time_series.ts_fcts.plot_timeseries(coor_inp, coortype='ENU', diapt=1.5, alpha=0.8, fig=1, errbar=True, symbol='.', errbar_width=1, ylim=None, legend_loc='best', legend_ncol=1, name='', stat='')

Standalone function to plot TimeSerie data.

This function can be called independently to plot time series data with three components (A, B, C) and their uncertainties.

Parameters:

coor_inp (tuple or pd.DataFrame) –
Input coordinates data. It can be either: - a 7-tuple (A, B, C, T, sA, sB, sC) where:
- A, B, C: coordinate components as numpy arrays
- T: time epochs as numpy array (POSIX timestamps)
- sA, sB, sC: uncertainties of the components as numpy arrays
- a DataFrame with columns corresponding to the coordinate type (e.g., ‘e’, ‘n’, ‘u’ for ENU) and their uncertainties (e.g., ‘se’, ‘sn’, ‘su’), along with an ‘epoch’ column for time epochs.
coortype (str, optional) – The coordinates type. The default is ‘ENU’. Options: ‘ENU’, ‘XYZ’, ‘FLH’, ‘UTM’
diapt (float, optional) – Point diameter. The default is 1.5.
alpha (float, optional) – Alpha (transparency) of points. The default is 0.8.
fig (int or Figure object, optional) – Figure ID where the data will be plotted. Can accept an int (id of a Figure) OR the figure Object itself. The default is 1.
errbar (bool, optional) – Plot the error bars. The default is True.
symbol (str, optional) – Marker symbol. The default is ‘.’.
errbar_width (float, optional) – Coefficient for the error bar size. The default is 1.
ylim (tuple, optional) – Y-axis limits. The default is None.
legend_loc (str, optional) – Location of the legend. The default is ‘best’.
legend_ncol (int, optional) – Number of columns in the legend. The default is 1.
name (str, optional) – Name for the plot legend. The default is “”.
stat (str, optional) – Station name for the figure title. The default is “”.

Returns:

figobj (Figure object) – Figure object of the plot.
axes (array of Axes objects) – Array of the 3 axes objects of the plot.

geodezyx.time_series.ts_fcts.print4compar_tabular(dicolist, split=0, print_2D3D_if_any=True)

geodezyx.time_series.ts_fcts.refENU_for_tslist(tslist_in, tsref_marker=0): tsref_marker : indice of the reference time serie OR the ‘all’ keyword in this case all the time series mean position will be averaged

geodezyx.time_series.ts_fcts.retrend_ts(tsin, a_coef, b_coef, coortype='ENU', t_origin=None): a_coefs,b_coefs = 3-tuple/list for the 3 component a_coef = m/s

geodezyx.time_series.ts_fcts.rotate_points_class(tsattin, ptslin, Rtype='R1', xyzreftuple=([1, 0, 0], [0, 1, 0], [0, 0, 1]), angtype='deg')

geodezyx.time_series.ts_fcts.rotate_pt_cls_solo(tsattin, pointin, Rtype='R1', xyzreftuple=([1, 0, 0], [0, 1, 0], [0, 0, 1]), angtype='deg')

ENTREEtsattinune TS d’attitude (N angles): pointin : UN Point en entrée

SORTIE : une TSpoint de N points

geodezyx.time_series.ts_fcts.round_time(tsin, round_to, mode='round')

geodezyx.time_series.ts_fcts.sigma_cleaner(tsin, seuil=3, coortype='ABC', cleantype='any', verbose=False)

geodezyx.time_series.ts_fcts.std_dev_cleaner(tsin, stddev_threshold, coortype='ABC', cleantype='any', verbose=False): A rebooted (1807) version of sigma_cleaner just remove values in a timeserie with a high sigma/std deviation

geodezyx.time_series.ts_fcts.time_gap(tsin, marge=2, mode='del'): ENTREE une TimeSerie SORTIE une window (liste de listes)

geodezyx.time_series.ts_fcts.time_win(tsin, windows, mode='keep', outbool=False)

geodezyx.time_series.ts_fcts.time_win_multi(inplis)

geodezyx.time_series.ts_fcts.time_win_t(Tin, win, mode='del')

geodezyx.time_series.ts_fcts.ts_from_list(A, B, C, T, initype, sA=[], sB=[], sC=[], stat='STAT', name='NoName')

geodezyx.time_series.ts_fcts.velocity_trans(tsin, vx, vy, vz, epoc_init='auto', epoc_end='auto')