opsimsummaryv2.summary_opsim ============================ .. py:module:: opsimsummaryv2.summary_opsim .. autoapi-nested-parse:: Main module to read OpSim output database. Attributes ---------- .. autoapisummary:: opsimsummaryv2.summary_opsim.use_geopandas Classes ------- .. autoapisummary:: opsimsummaryv2.summary_opsim.OpSimSurvey Module Contents --------------- .. py:class:: OpSimSurvey(db_path, mjd_range=None, host_file=None, host_config={}) A class to manipulate OpSim db data and turn them into simulation inputs. .. attribute:: db_path Path to the database file :type: pathlib.Path .. attribute:: sql_engine The sqlalchemy engine link to the db. :type: sqlalchemy.engine.base.Engine .. attribute:: opsimdf Dataframe of the simulated observations. :type: pandas.DataFrame .. attribute:: tree A BallTree used to select observations on the healpy representation of the survey. :type: sklearn.neighbors.BallTree .. attribute:: host Dataframe of the hosts. :type: pandas.DataFrame .. attribute:: hp_rep The healpy representation oif the survey :type: pandas.DataFrame .. attribute:: survey The healpy representation oif the survey :type: pandas.DataFrame .. attribute:: survey_hosts The hosts that are inside the survey. :type: pandas.DataFrame .. py:method:: _get_df_from_sql(sql_engine, mjd_range=None) :staticmethod: Load data from the db file. :param sql_engine: The sqlalchemy engine link to the db. :type sql_engine: sqlalchemy.engine.base.Engine :param mjd_range: Min and Max date to query if float assumed to be mjd, by default None :type mjd_range: ( , ) str or float, optional :returns: Dataframe of the simulated observations. :rtype: pandas.DataFrame .. py:method:: _get_sql_engine(dbname) :staticmethod: Read a sql db Opsim output file. :param dbname: Path to sql file. :type dbname: str :returns: The sqlalchemy engine link to the db. :rtype: sqlalchemy.engine.base.Engine .. py:method:: _read_host_file(host_file, col_ra='ra', col_dec='dec', ra_dec_unit='radians', wgt_map=None, add_SNMAGSHIFT=False) Read a parquet file containing hosts. :param host_file: Path to the parquet file :type host_file: str :param col_ra: Key of column containing RA, by default 'ra' :type col_ra: str, optional :param col_dec: Key of column containing Dec, by default 'dec' :type col_dec: str, optional :param ra_dec_unit: Unit of ra_dec (radians or degrees), by default 'radians' :type ra_dec_unit: str, optional :returns: Dataframe of the hosts. :rtype: pandas.DataFrame .. py:method:: compute_hp_rep(nside=256, minVisits=500, maxVisits=100000, ddf_nobs_thresh=1100, add_ddf_tag=False, angle_sep_tol=10) Compute a healpy version of the survey. :param nside: Healpy nside, by default 256 :type nside: int, optional :param minVisits: Minimum number of observations required in the survey, by default 500 :type minVisits: int, optional :param maxVisits: Maximum number of observations required in the survey, by default 100000 :type maxVisits: int, optional .. py:method:: formatObs(OpSimObs, keep_keys=[]) Format function to get quantities of interest for simulation. :param OpSimObs: Dataframe of OpSim output :type OpSimObs: pandas.DataFrame :param keep_keys: List of keys to keep in addition to formatted quantities :type keep_keys: list(str) :returns: Dataframe that contains quantities for simulation. :rtype: pandas.DataFrame .. rubric:: Notes Quantities are obtained following arxiv:1905.02887 Details of the calculs: The :math:`\sigma_\mathrm{PSF}` in units of :math:`\mathrm{arcsec}^{-1}` is obtained as .. math:: \sigma_\mathrm{PSF} = \frac{\mathbf{seeingFwhmEff}}{2\sqrt{2\ln2}}. The :math:`\mathbf{PSF}` is computed in units of :math:`\mathrm{pixel}^{-1}` as .. math:: \mathbf{PSF} = \frac{\sigma_\mathrm{PSF}}{\mathrm{PixelSize}}, where :math:`\mathrm{PixelSize}` is the pixel size in :math:`\mathrm{arcsec}^{-1}`. The zero-point :math:`\mathbf{ZPT}` is computed as .. math:: \mathbf{ZPT} = 2 m_5 - m_\mathrm{sky} + 2.5 \log\left[25 A \left(1 + A^{-1}10^{-0.4(m_5-m_\mathrm{sky})}\right)\right], where :math:`m_5 = \mathbf{fiveSigmaDepth}`, :math:`m_\mathrm{sky} = \mathbf{skyBrightness}` and :math:`A` is the noise equivalent area given by :math:`A = 4 \pi \sigma_\mathrm{PSF}^2`. The sky noise :math:`\mathbf{SKYSIG}` in unit of :math:`\mathrm{ADU}.\mathrm{pixel}^{-1}` is computed such as .. math:: \mathbf{SKYSIG}^2 = 10^{-0.4\left(m_\mathrm{sky} - \mathbf{ZPT}\right)} \times \mathrm{PixelSize}^2. .. py:method:: get_obs_from_coords(ra, dec, is_deg=True, formatobs=False, keep_keys=[]) Get observations at ra, dec coordinates. :param ra: RA coordinate :type ra: numpy.ndarray(float) :param dec: Dec coordinate :type dec: numpy.ndarray(float) :param is_deg: is RA, Dec given in degrees, by default True :type is_deg: bool, optional :param formatobs: format obs for simulation, by default False :type formatobs: bool, optional :param keep_keys: List of keys to keep in addition to formatted quantities :type keep_keys: list(str) :Yields: *pandas.DatFrame* -- Dataframes of observations. .. py:method:: get_survey_hosts(nworkers=10) Get survey hosts. :param nworkers: Number of cores used to run multiprocessing, by default 10 :type nworkers: int, optional :returns: Dataframe of host inside the survey, matched to their field indicated by GROUPID. :rtype: pandas.DataFrame .. py:method:: get_survey_obs(formatobs=True, keep_keys=[]) Get survey observations. :param formatobs: Format the observation to get only quantities of interest for simulation, by default True :type formatobs: bool, optional :param keep_keys: List of keys to keep in addition to formatted quantities :type keep_keys: list(str) :Yields: *pandas.DatFrame* -- Dataframes of observations. .. py:method:: plot_hp_rep(**hp_mollview_kwargs) Plot the healpy mollview of the survey representation. :returns: The mollview figure :rtype: matplotlib.Figure .. py:method:: sample_survey(N_fields, random_seed=None, nworkers=10) Sample Nfields inside the survey's healpy representation. :param N_fields: Number of fields to sample :type N_fields: int :param random_seed: The random seed used to sample the fields, by default None :type random_seed: int or numpy.random.SeedSquence, optional :param nworkers: Number of cores used to run multiprocessing on host matching, by default 10 :type nworkers: int, optional .. rubric:: Notes Random seed only apply on field sampling. .. py:attribute:: __LSST_DDF_TAGS__ .. py:attribute:: __LSST_FIELD_RADIUS__ .. py:attribute:: __LSST_pixelSize__ :value: 0.2 .. py:attribute:: _hp_rep :value: None .. py:attribute:: _survey :value: None .. py:attribute:: db_path .. py:attribute:: host :value: None .. py:property:: hp_rep .. py:attribute:: opsimdf .. py:attribute:: sql_engine :value: None .. py:property:: survey .. py:property:: survey_hosts .. py:attribute:: tree .. py:data:: use_geopandas :value: True