dm.models package

Submodules

dm.models.ModelsUtil module

class dm.models.ModelsUtil.ModelsUtil

Bases: object

static anomaly_diff(devs, cls, lat, lon, actual_time, weather, min_diff, diff_time, a_type)

It detect an anomaly within given time interval.

Parameters
  • devs – information about device

  • cls – list of clients

  • lat – latitude of locality

  • lon – longitude of locality

  • actual_time – current timestamp

  • weather – class that obtains information about weather

  • min_diff – minimal difference between measured values

  • diff_time – window size for anomaly detection

  • a_type – type of anomaly detection (temperature, humidity or co2)

Returns

notification that contains information about anomaly

static dew_point(devs, cls, lat, lon, actual_time, weather)

It calculates dew point.

Parameters
  • devs – information about device

  • cls – list of clients

  • lat – latitude of locality

  • lon – longitude of locality

  • actual_time – current timestamp

  • weather – class that obtains information about weather

Returns

notification that contains information about dew point

static estimate_co2(device, cls, actual_time)

It estimates values in given time on the basis of CO2 concentration.

Parameters
  • device – information about device

  • cls – list of clients

  • actual_time – current timestamp

Returns

notification that contains information about estimation

static estimate_open_co2(device, cls, lat, lon, actual_time, weather)

It estimates if window was open on the basis of CO2 concentration.

Parameters
  • device – information about device

  • cls – list of clients

  • lat – latitude of locality

  • lon – longitude of locality

  • actual_time – current timestamp

  • weather – class that obtains information about weather

Returns

notification that contains information about estimation

static estimate_open_t_h(device, cls, lat, lon, actual_time, weather)

It estimates if window was open on the basis of temperature and humidity.

Parameters
  • device – information about device

  • cls – list of clients

  • lat – latitude of locality

  • lon – longitude of locality

  • actual_time – current timestamp

  • weather – class that obtains information about weather

Returns

notification that contains information about estimation

static estimate_t_h(device, cls, actual_time)

It estimates values in given time on the basis of humidity.

Parameters
  • device – information about device

  • cls – list of clients

  • actual_time – current timestamp

Returns

notification that contains information about estimation

static json_to_file(json_data, filename, log_notification)

It saves JSON structure into the file.

Parameters
  • json_data – JSON structure containing data

  • filename – name of output file

  • log_notification – true if notification is logged

Returns

None

static load_model(type, device)

It loads model for window opening detector from file.

Parameters
  • type – type of model, t_h or co2

  • device – information about device

Returns

loaded model

static load_model_predictor(type, device)

It loads model for predictor from file.

Parameters
  • type – type of model, t_h or co2

  • device – information about device

Returns

loaded model

static predictor(device, cls, lat, lon, actual_time, module_type, weather, decrease=None)

It predicts length of ventilation to decrease quantity to required level.

Parameters
  • device – information about device

  • cls – list of clients

  • lat – latitude of locality

  • lon – longitude of locality

  • actual_time – current timestamp

  • module_type – type of module, t_h or CO2

  • weather – class that obtains information about weather

  • decrease – value that defines how much quantity value should be decreased

Returns

notification that contains information about estimation

static read_generic_data(model_type)

It gets list of attributes from file.

The attributes are used in model for window opening detector.

Parameters

model_type – type of model, t_h or co2

Returns

list of attributes

static replace_co2_ventilation_len(data)

It moves value of CO2 concentration after regression to event attribute.

Parameters

data – list of data

Returns

modified list of data

static replace_nothing_open(data)

It converts value of event attribute to boolean.

Attribute value open is represented by 1 and close by 0.

Parameters

data – list of data

Returns

modified list of data

static replace_ventilation_length(data)

It removes quotation marks in value of ventilation length attribute.

Parameters

data – list of data

Returns

modified list of data

static when_ventilate_summer(devs, cls, lat, lon, actual_time, weather, temperature_diff)

It determines if ventilation should be performed on the basis of temperature difference.

Parameters
  • devs – information about device

  • cls – list of clients

  • lat – latitude of locality

  • lon – longitude of locality

  • actual_time – current timestamp

  • weather – class that obtains information about weather

  • temperature_diff – difference between inside and outside temperature

Returns

notification that contains information about estimation

static write_model(attrs, filename, replace, event_column='event')

It saves model to the output file.

Parameters
  • attrs – list of attributes

  • filename – name of output file

  • replace – function that replaces an attribute

  • event_column – name of attribute that denotes class

Returns

None

Module contents