pyPSCF package

Submodules

pyPSCF.BackTrajHysplit module

class pyPSCF.BackTrajHysplit.BT(station=None, lat=None, lon=None, alt=None, dateMin=None, dateMax=None, stepHH=None, hBT=None, dirOutput=None, dirGDAS=None, dirHysplit=None, cpu=None)

Bases: object

Compute the back-trajectory for the given station between dateMin and dateMax.

Parameters:

• station (str) – The station
• lat (float) – Latitude of the starting point
• lon (float) – Longitude of the starting point
• alt (float) – Altitude of the starting point
• dateMin (str) – Starting date “YYYY-MM-DD HH:MM”
• dateMax (str) – Ending date “YYYY-MM-DD HH:MM”
• stepHH (int) – Interval between 2 starting hour
• hBT (int (negative)) – Number of hour to go in the past
• dirOutput (str) – path to the output directory
• dirGDAS (str) – path to the GDAS meteorological directory
• dirHysplit (str) – path to the hysplit root directory
• cpu (int) – Number of CPU to use. Beware, each of them is use to its maximum.

compute_BT(date, filename)

Compute the BT for the given datetime

Parameters:

• date (datetime) – The datetime to compute
• filename (str) – The name of the output file

compute_BTs()

Compute all the BT from dateMin to dateMax

get_currentFile(station, d)

Return the name of the file given a station and a date

Parameters:

• station (str) – The name of the station
• d (datetime) – The datetime of the backtrajectory

Returns:

currentFile – traj_{station}_{YYMMDDHH}

Return type:

str

run()

Run compute_BTs one time per cpu each in a subprocess.

update_date(d, stepHH)

Update the date by a given step

Parameters:

• d (datetime) – Previous datetime
• stepHH (int) – Number of hour to go forward

Returns:

datetime – d + stepHH

Return type:

datetime

write_CONTROL_file(curDate, currentFile)

Create the correct CONTROL file for the given date

Parameters:

• curDate (datetime) – The datetime to compute
• currentFile (str) – The name of the file

write_SETUP_file()

Well… write the setup file

pyPSCF.pyPSCF module

class pyPSCF.pyPSCF.PSCF(station, specie, lat0, lon0, folder, prefix, add_hour, concFile, dateMin, dateMax, percentile=75, threshold=None, wfunc=True, wfunc_type='auto', resQuality='110m', smoothplot=True, mapMinMax=None, cutWithRain=True, hourinthepast=72, plotBT=True, plotPolar=True, pd_kwarg=None)

Bases: object

Parameters:

• station (str) – The name of the station.
• specie (str) – The specie to study. Must be specified in the concentration file.
• lat0 (float) – The latitude of the starting point.
• lon0 (float) – The longitude of the starting point.
• folder (str, path) – Path to the backtrajectories files.
• prefix (str) – Prefix of all backtrajectories. Something like ‘traj_OPE_’
• add_hour (list or array) –

  List of backtrajecories starting hours around the reference hour. Example: add_hour=[-3,0,3] and reference hour of 2017-03-15 09:00, the following backtrajectories will be used:

  • 2017-03-15 06:00
  • 2017-03-15 09:00
  • 2017-03-15 12:00

  All theses backtrajecories are associated to the concentration of the refrence hour.

• concFile (str, path.) – The path to the concentration file.
• dateMin (str or datetime object) – The minimal date to account.
• dateMax (str or datetime object) – The maximal date to account.
• percentile (int, default 75) – The percentile to use as threshold.
• threshold (float, default None) – The concentration threshold. It overrides the percentile value.
• wfunc (boolean, default True) – Either or not use a weighting function.
• wfunc_type ("manual" or "auto", default "auto") – Type of weighting function. “auto” is continuous.
• mapMinMax (dict) – Dictionary of minimun/maximum of lat/lon for the map. Example: mapMinMax = {‘latmin’: 37.5, ‘latmax’: 60, ‘lonmin’: -10, ‘lonmax’: 20} This example is the default (France centered).
• cutWithRain (boolean, default True) – Either or not cut the backtrajectory to the last rainning date.
• hourinthepast (integer, default 72) – Number of hour considered for the backtrajectory life.
• resQuality ('110m' or '50m', default '110m') – The quality of the map.
• smoothplot (boolean, default True) – Use a gaussian filter to smooth the map plot.
• plotBT (boolean, default True) – Either or not plot all the backtraj in a new axe.
• plotPolar (boolean, default True) – Either or not plot the direction the distribution of the PSCF in a polar plot.

Other Parameters:  

pd_kwarg (dict, optional) – Dictionary of option pass to pd.read_csv to read the concentration file. By default, pd_kwarg={‘index_col’=0, ‘parse_date’=[‘date’]}.

extractBackTraj()

Sum up back trajectories file into a pandas DataFrame according to the class parameters.

Returns:df Return type:pd.DataFrame

onclick(event, plotType)

Find the BT which pass through the clicked cell.

plot_PSCF()

Plot the PSCF map.

plot_PSCF_polar()

Plot a polar plot of the PSCF

plot_backtraj()

Plot a map of all trajectories.

run()

Run the PSCF model and add 4 attributes to the PSCF object:

Returns:

• ngrid_ (ndarray) – The number of end-point of back-trajectories in each grid cell
• mgrid_ (ndarray) – The number of en-point of back-trajectories in each grid cell accociated with concentration > self.concCrit
• PSCF_ (ndarray) – mgrid/ngrid, the PSCF data.
• trajdensity_ (ndarray) – log_10(ngrid)

toRad(x)

Module contents