文件列表:

conx.py (242261, 2014-07-17)
error_rare_event_generator.py (9778, 2014-07-17)
event.py (1997, 2014-07-17)
file_tools.py (436, 2014-07-17)
graph.py (1629, 2014-07-17)
lattice.py (2178, 2014-07-17)
lattice_of_sensors.py (12361, 2014-07-17)
linked_list.py (1579, 2014-07-17)
neuralnet.py (9880, 2014-07-17)
plotting_utility.py (5327, 2014-07-17)
project.py (9426, 2014-07-17)
pyrographics.py (28827, 2014-07-17)
sensor.py (409, 2014-07-17)
share.py (392, 2014-07-17)
station.py (2350, 2014-07-17)
time_series.py (2422, 2014-07-17)
time_series_tools.py (974, 2014-07-17)

#Toy Simulator 2014 Authors: Rodny Perez Emily Dolson Josh Nahum This projects aims to develop a simulator for wireless sensors. We will something else later ##Todo - Implementing features: * Sensor dependancy (Done) * Time occilation (The mean changes over time) (Done) * Days or seasons (comming soon) * Sensors that varies in mean and standard deviation * Sensor pattern * Partition sensors by groups (Done) * Multiple sensor type (Done) * Temperature drifts globally - Adding correlations * Change temperature over time (moran process) * Change station to correlated sensor group (Done) * Change mean in station to a periodically changin value such as sine wave. ##Errors and anomalies - Abrupt changes (added) - Large deviation (added) - Unusually low variance (change in result from predicted value) - Deviation from neighbors (variance in result from neigbors) (added) - Drift towards a particular value (0 or something else) (change over time in unforeseen ways) (added) - increasingly mean difference ##Ways of representing anomalies - Change in mean value among multiple sensors. Either within a group or an entire field - Adjusting the correlation between sensor modalities

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