Metadata-Version: 1.1
Name: cynet
Version: 1.0.50
Summary: Spatio temporal analysis for inferrence of statistical causality using XGenESeSS
Home-page: https://github.com/zeroknowledgediscovery/
Author: zed.uchicago.edu
Author-email: ishanu@uchicago.edu
License: LICENSE.txt
Download-URL: https://github.com/zeroknowledgediscovery/Cynet/archive/1.0.50.tar.gz
Description: cynet
        =====
        
         **cynet is a spatial-temporal analysis library for inferrence of statistical causality**
        
        **NOTE:** if issues arise with dependencies in python3, be sure that tkinter is installed  
        if not, please run:
        
        
        	sudo apt-get install python3-tk
        
        
        **Usage:**
        
        
        	from cynet import cynet
        	from cynet.cynet import uNetworkModels as models
        	from viscynet import viscynet as vcn
        
        
        cynet module includes:  
        -   cynet
        -   viscynet
        -   bokeh\_pipe
        
        cynet library classes:
        ----------------------
        
        -   spatioTemporal
        -   uNetworkModels
        -   simulateModels
        
        **class spatioTemporal**  
        Utilities for spatial-temporal analysis
        
        **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; requires 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 (dictionary or list of lists): coordinate dictionary with respective ranges and EPS value OR custom list of lists of custom grid tiles as [coord1\_start, coord1\_stop, coord2\_start, coord2\_stop]
        -   grid\_type (string): parameter to determine if grid should be built up from a coordinate start/stop range ('auto') or be built from custom tile coordinates ('custom')
        -   threshold (float): significance threshold
        
        **Methods:**
        
        
        	__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',auto_adjust_time=False,incr=6,max_incr=24):
        
        	getTS(self, _types=None, tile=None, freq=None)
        
        	get_rand_tile(tiles=None,LAT=None,LON=None,EPS=None,_types=None)
        
        	get_opt_freq(df,incr=6,max_incr=24)
        	
        	getGrid(self)
        	
        	pull(self, domain='data.cityofchicago.org', dataset_id='crimes', token=None, store=True, out_fname='pull_df.p', pull_all=False)
        	
        	timeseries(self, LAT=None, LON=None, EPS=None,_types=None,CSVfile='TS.csv',THRESHOLD=None,tiles=None,incr=6,max_incr=24)
         
        
Keywords: spatial,temporal,inference,statistical,causality
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 2.7
