swmmx Documentation

Getter Reference: Hydraulic Geometry and Water Quality

Rendered from 11_all_get_functions.ipynb.

Inlets and hydraulic geometry

street

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.street.count(ids=None, format=None)derivedintegersingleint scalar count
m.get.street.cross_slope(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.street.crown_width(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.street.curb_height(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.street.depression_storage(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.street.gutter_slope(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.street.gutter_width(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.street.id(ids=None, format=None)userstrsingleOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.street.roughness(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.street.spread(ids=None, format=None)resultfloatsummary/time seriesTime series; NumPy by default, or timestamp-indexed DataFrame with format='df'

Copy-ready call list:

m.get.street.count(ids=None, format=None)
m.get.street.cross_slope(ids=None, format=None)
m.get.street.crown_width(ids=None, format=None)
m.get.street.curb_height(ids=None, format=None)
m.get.street.depression_storage(ids=None, format=None)
m.get.street.gutter_slope(ids=None, format=None)
m.get.street.gutter_width(ids=None, format=None)
m.get.street.id(ids=None, format=None)
m.get.street.roughness(ids=None, format=None)
m.get.street.spread(ids=None, format=None)

inlet

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.inlet.captured_flow(ids=None, format=None)resultfloatsummary/time seriesTime series; NumPy by default, or timestamp-indexed DataFrame with format='df'
m.get.inlet.count(ids=None, format=None)derivedintegersingleint scalar count
m.get.inlet.curb_height(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet.curb_length(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet.grate_length(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet.grate_type(ids=None, format=None)userenumseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet.grate_width(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet.id(ids=None, format=None)userstrsingleOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet.slotted_length(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet.slotted_width(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet.type(ids=None, format=None)userenumseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.inlet.captured_flow(ids=None, format=None)
m.get.inlet.count(ids=None, format=None)
m.get.inlet.curb_height(ids=None, format=None)
m.get.inlet.curb_length(ids=None, format=None)
m.get.inlet.grate_length(ids=None, format=None)
m.get.inlet.grate_type(ids=None, format=None)
m.get.inlet.grate_width(ids=None, format=None)
m.get.inlet.id(ids=None, format=None)
m.get.inlet.slotted_length(ids=None, format=None)
m.get.inlet.slotted_width(ids=None, format=None)
m.get.inlet.type(ids=None, format=None)

inlet_usage

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.inlet_usage.clogging_factor(ids=None, format=None)userfloatseries/tableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet_usage.conduit(ids=None, format=None)refstrseries/tableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet_usage.flow_restriction(ids=None, format=None)userfloatseries/tableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet_usage.inlet(ids=None, format=None)refstrseries/tableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet_usage.node(ids=None, format=None)refstrseries/tableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.inlet_usage.number(ids=None, format=None)userintegerseries/tableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.inlet_usage.clogging_factor(ids=None, format=None)
m.get.inlet_usage.conduit(ids=None, format=None)
m.get.inlet_usage.flow_restriction(ids=None, format=None)
m.get.inlet_usage.inlet(ids=None, format=None)
m.get.inlet_usage.node(ids=None, format=None)
m.get.inlet_usage.number(ids=None, format=None)

transect

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.transect.count(ids=None, format=None)derivedintegersingleint scalar count
m.get.transect.elevations(ids=None, format=None)userfloatsequence/listOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.transect.id(ids=None, format=None)userstrsingleOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.transect.left_bank(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.transect.modifiers(ids=None, format=None)userfloatlist/tableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.transect.right_bank(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.transect.roughness_channel(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.transect.roughness_left(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.transect.roughness_right(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.transect.stations(ids=None, format=None)userfloatsequence/listOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.transect.count(ids=None, format=None)
m.get.transect.elevations(ids=None, format=None)
m.get.transect.id(ids=None, format=None)
m.get.transect.left_bank(ids=None, format=None)
m.get.transect.modifiers(ids=None, format=None)
m.get.transect.right_bank(ids=None, format=None)
m.get.transect.roughness_channel(ids=None, format=None)
m.get.transect.roughness_left(ids=None, format=None)
m.get.transect.roughness_right(ids=None, format=None)
m.get.transect.stations(ids=None, format=None)

Water quality

pollutant

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.pollutant.co_pollutant(ids=None, format=None)refstrseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.co_pollutant_fraction(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.count(ids=None, format=None)derivedintegersingleint scalar count
m.get.pollutant.decay_coefficient(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.dry_weather_flow_concentration(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.groundwater_concentration(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.id(ids=None, format=None)userstrsingleOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.initial_concentration(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.rain_concentration(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.rdii_concentration(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.snow_only(ids=None, format=None)userboolseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.pollutant.units(ids=None, format=None)userenumseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.pollutant.co_pollutant(ids=None, format=None)
m.get.pollutant.co_pollutant_fraction(ids=None, format=None)
m.get.pollutant.count(ids=None, format=None)
m.get.pollutant.decay_coefficient(ids=None, format=None)
m.get.pollutant.dry_weather_flow_concentration(ids=None, format=None)
m.get.pollutant.groundwater_concentration(ids=None, format=None)
m.get.pollutant.id(ids=None, format=None)
m.get.pollutant.initial_concentration(ids=None, format=None)
m.get.pollutant.rain_concentration(ids=None, format=None)
m.get.pollutant.rdii_concentration(ids=None, format=None)
m.get.pollutant.snow_only(ids=None, format=None)
m.get.pollutant.units(ids=None, format=None)

land_use

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.land_use.count(ids=None, format=None)derivedintegersingleint scalar count
m.get.land_use.id(ids=None, format=None)userstrsingleOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.land_use.last_swept(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.land_use.sweeping_availability(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.land_use.sweeping_interval(ids=None, format=None)userfloatseries by IDOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.land_use.count(ids=None, format=None)
m.get.land_use.id(ids=None, format=None)
m.get.land_use.last_swept(ids=None, format=None)
m.get.land_use.sweeping_availability(ids=None, format=None)
m.get.land_use.sweeping_interval(ids=None, format=None)

coverage

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.coverage.land_use(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.coverage.percent(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.coverage.subcatchment(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.coverage.land_use(ids=None, format=None)
m.get.coverage.percent(ids=None, format=None)
m.get.coverage.subcatchment(ids=None, format=None)

loading

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.loading.initial_buildup(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.loading.pollutant(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.loading.subcatchment(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.loading.initial_buildup(ids=None, format=None)
m.get.loading.pollutant(ids=None, format=None)
m.get.loading.subcatchment(ids=None, format=None)

buildup

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.buildup.function(ids=None, format=None)userenumtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.buildup.land_use(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.buildup.maximum_buildup(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.buildup.normalizer(ids=None, format=None)userenumtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.buildup.pollutant(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.buildup.power(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.buildup.rate_constant(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.buildup.function(ids=None, format=None)
m.get.buildup.land_use(ids=None, format=None)
m.get.buildup.maximum_buildup(ids=None, format=None)
m.get.buildup.normalizer(ids=None, format=None)
m.get.buildup.pollutant(ids=None, format=None)
m.get.buildup.power(ids=None, format=None)
m.get.buildup.rate_constant(ids=None, format=None)

washoff

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.washoff.bmp_efficiency(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.washoff.cleaning_efficiency(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.washoff.coefficient(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.washoff.exponent(ids=None, format=None)userfloattableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.washoff.function(ids=None, format=None)userenumtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.washoff.land_use(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.washoff.pollutant(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.washoff.bmp_efficiency(ids=None, format=None)
m.get.washoff.cleaning_efficiency(ids=None, format=None)
m.get.washoff.coefficient(ids=None, format=None)
m.get.washoff.exponent(ids=None, format=None)
m.get.washoff.function(ids=None, format=None)
m.get.washoff.land_use(ids=None, format=None)
m.get.washoff.pollutant(ids=None, format=None)

treatment

Kind: Object collection

GetterSourceDeclared typeDeclared sizeOutput note
m.get.treatment.expression(ids=None, format=None)userexpressiontable/listOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.treatment.node(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame
m.get.treatment.pollutant(ids=None, format=None)refstrtableOne ID → scalar/structured value; many/all IDs → NumPy array or one-row DataFrame

Copy-ready call list:

m.get.treatment.expression(ids=None, format=None)
m.get.treatment.node(ids=None, format=None)
m.get.treatment.pollutant(ids=None, format=None)