Metadata-Version: 1.1
Name: cynet
Version: 1.0.3
Summary: Spatio temporal analysis for inferrence of statistical causality using XGenESeSS
Home-page: https://github.com/zeroknowledgediscovery/Cynet
Author: zed.uchicago.edu
Author-email: ishanu@uchicago.edu
License: LICENSE.txt
Download-URL: https://github.com/zeroknowledgediscovery/Cynet/archive/1.0.3.tar.gz
Description: # Spatio temporal analysis for inferrence of statistical causality
        
        @author zed.uchicago.edu
        
        CLASSES spatioTemporal uNetworkModels
        
            class spatioTemporal
             |  Utilities for spatio temporal analysis
             |  @author zed.uchicago.edu
             |
             |  Attributes:
             |      log_store (Pickle): Pickle storage of class data & dataframes
             |      log_file (string): path to CSV of legacy dataframe
             |      ts_store (string): path to CSV containing most recent ts export
             |      DATE (string):
             |      EVENT (string): column label for category filter
             |      coord1 (string): first coordinate level type; is column name
             |      coord2 (string): second coordinate level type; is column name
             |      coord3 (string): third coordinate level type;
             |                       (z coordinate)
             |      end_date (datetime.date): upper bound of daterange
             |      freq (string): timeseries increments; e.g. D for date
             |      columns (list): list of column names to use;
             |          required at least 2 coordinates and event type
             |      types (list of strings): event type list of filters
             |      value_limits (tuple): boundaries (magnitude of event;
             |                            above threshold)
             |      grid (dict): dict with coord and eps (see example)
             |      threshold (float): significance threshold
             |
             |  Methods defined here:
             |
             |  __init__(self, log_store='log.p', log_file=None, ts_store=None, DATE='Date', year=None, month=None, day=None, EVENT='Primary Type', coord1='Latitude', coord2='Longitude', coord3=None, init_date=None, end_date=None, freq=None, columns=None, types=None, value_limits=None, grid=None, threshold=None)
             |
             |  fit(self, grid=None, INIT=None, END=None, THRESHOLD=None, csvPREF='TS')
             |      Utilities for spatio temporal analysis
             |      @author zed.uchicago.edu
             |
             |      Fit dataproc with specified grid parameters and
             |      create timeseries for
             |      date boundaries specified by INIT, THRESHOLD,
             |      and END which do not have
             |      to match the arguments first input
             |      to the dataproc
             |
             |      Inputs:
             |          grid (pd.DataFrame): dataframe of location
             |          timeseries data
             |          INIT (datetime.date): starting timeseries date
             |          END (datetime.date): ending timeseries date
             |          THRESHOLD (float): significance threshold
             |
             |      Outputs:
             |          (None)
             |
             |  getTS(self, _types=None, tile=None)
             |      Utilities for spatio temporal analysis
             |      @author zed.uchicago.edu
             |
             |      Utilities for spatio temporal analysis
             |      @author zed.uchicago.edu
             |
             |      Given location tile boundaries and type category filter, creates the
             |      corresponding timeseries as a pandas DataFrame
             |      (Note: can reassign type filter, does not have to be the same one
             |      as the one initialized to the dataproc)
             |
             |      Inputs:
             |          _types (list of strings): list of category filters
             |          tile (list of floats): location boundaries for tile
             |
             |      Outputs:
             |          pd.Dataframe of timeseries data to corresponding grid tile
             |          pd.DF index is stringified LAT/LON boundaries
             |          with the type filter  included
             |
             |  pull(self, domain='data.cityofchicago.org', dataset_id='crimes', token='ZIgqoPrBu0rsvhRr7WfjyPOzW', store=True, out_fname='pull_df.p', pull_all=False)
             |      Utilities for spatio temporal analysis
             |      @author zed.uchicago.edu
             |
             |      Pulls new entries from datasource
             |      NOTE: should make flexible but for now use city of Chicago data
             |
             |      Input -
             |          domain (string): Socrata database domain hosting data
             |          dataset_id (string): dataset ID to pull
             |          token (string): Socrata token for increased pull capacity
             |          store (boolean): whether or not to write out new dataset
             |          pull_all (boolean): pull complete dataset
             |          instead of just updating
             |
             |      Output -
             |          None (writes out files if store is True and modifies inplace)
             |
             |  timeseries(self, LAT, LON, EPS, _types, CSVfile='TS.csv', THRESHOLD=None)
             |      Utilities for spatio temporal analysis
             |      @author zed.uchicago.edu
             |
             |      Creates DataFrame of location tiles and their
             |      respective timeseries from
             |      input datasource with
             |      significance threshold THRESHOLD
             |      latitude, longitude coordinate boundaries given by LAT, LON
             |      calls on getTS for individual tile then concats them together
             |
             |      Input:
             |          LAT (float):
             |          LON (float):
             |          EPS (float): coordinate increment ESP
             |          _types (list): event type filter; accepted event type list
             |          CSVfile (string): path to output file
             |
             |      Output:
             |          (None): grid pd.Dataframe written out as CSV file
             |                  to path specified
        
            class uNetworkModels
             |  Utilities for storing and manipulating XPFSA models
             |  inferred by XGenESeSS
             |  @author zed.uchicago.edu
             |
             |  Attributes:
             |      jsonFile (string): path to json file containing models
             |
             |  Methods defined here:
             |
             |  __init__(self, jsonFILE)
             |
             |  augmentDistance(self)
             |      Utilities for storing and manipulating XPFSA models
             |      inferred by XGenESeSS
             |      @author zed.uchicago.edu
             |
             |      Calculates the distance between all models and stores
             |      them under the
             |      distance key of each model;
             |
             |      No I/O
             |
             |  select(self, var='gamma', n=None, reverse=False, store=None)
             |      Utilities for storing and manipulating XPFSA models
             |      inferred by XGenESeSS
             |      @author zed.uchicago.edu
             |
             |      Selects the N top models as ranked by var specified value
             |      (in reverse order if reverse is True)
             |
             |      Inputs -
             |          var (string): model parameter to rank by
             |          n (int): number of models to return
             |          reverse (boolean): return in ascending order (True)
             |              or descending (False) order
             |          store (string): name of file to store selection json
             |
             |      Returns -
             |          (dictionary): top n models as ranked by var
             |                       in ascending/descending order
             |
             |  to_json(outFile)
             |      Utilities for storing and manipulating XPFSA models
             |      inferred by XGenESeSS
             |      @author zed.uchicago.edu
             |
             |      Writes out updated models json to file
             |
             |      Input -
             |          outFile (string): name of outfile to write json to
             |
             |      Returns -
             |          Nonexs
             |
             |  ----------------------------------------------------------------------
             |  Data descriptors defined here:
             |
             |  models
        
        FUNCTIONS draw\_screen\_poly(lats, lons, m, ax, val, cmap, ALPHA=0.6)
        utility function to draw polygons on basemap
        
            getalpha(arr, index, F=0.9)
                utility function to normalize transparency of quiver
        
            readTS(TSfile, csvNAME='TS1', BEG=None, END=None)
                Utilities for spatio temporal analysis
                @author zed.uchicago.edu
        
                Reads in output TS logfile into pd.DF
                    and then outputs necessary
                    CSV files in XgenESeSS-friendly format
        
                Input -
                    TSfile (string): filename input TS to read
                    csvNAME (string)
                    BEG (string): start datetime
                    END (string): end datetime
        
                Returns -
                    dfts (pandas.DataFrame)
        
            showGlobalPlot(coords, ts=None, fsize=[14, 14], cmap='jet', m=None, figname='fig', F=2)
                plot global distribution of events
                within time period specified
        
                Inputs -
                    coords (string): filename with coord list as lat1#lat2#lon1#lon2
                    ts (string): time series filename with data in rows, space separated
                    fsize (list):
                    cmap (string):
                    m (mpl.mpl_toolkits.Basemap): mpl instance for plotting
                    figname (string): Name of the Plot
        
                Returns -
                    m (mpl.mpl_toolkits.Basemap): mpl instance of heat map of
                        crimes from fitted data
        
            splitTS(TSfile, csvNAME='TS1', dirname='./', prefix='@', BEG=None, END=None)
                Utilities for spatio temporal analysis
                @author zed.uchicago.edu
        
                Writes out each row of the pd.DataFrame as a separate CSVfile
                For XgenESeSS binary
        
                No I/O
        
            stringify(List)
                Utility function
                @author zed.uchicago.edu
        
                Converts list into string separated by dashes
                         or empty string if input list
                         is not list or is empty
        
                Input:
                    List (list): input list to be converted
        
                Output:
                    (string)
        
            to_json(pydict, outFile)
                Writes dictionary json to file
                @author zed.uchicago.edu
        
                Input -
                    pydict (dict): ditionary to store
                    outFile (string): name of outfile to write json to
        
                Returns -
                    Nonexs
        
            viz(unet, jsonfile=False, colormap='autumn', res='c', drawpoly=False, figname='fig')
                  utility function to visualize spatio temporal
                  interaction networks
                  @author zed.uchicago.edu
        
        
                Inputs -
                    unet (string): json filename
                    unet (python dict):
                    jsonfile (bool): True if unet is string  specifying json filename
                    colormap (string): colormap
                    res (string): 'c' or 'f'
                    drawpoly (bool): if True draws transparent patch showing srcs
                    figname  (string): prefix of pdf image file
                Returns -
                    m (Basemap handle)
                    fig (figure handle)
                    ax (axis handle)
                    cax (colorbar handle)
        
        DATA **DEBUG** = False **version** = '1.0.3'
        
        VERSION 1.0.3
        
Keywords: spatial,temporal,inference,statistical,causality
Platform: UNKNOWN
