SWMM5 5.1.15

SWMM5 calls from python

SWMM5 Python calling interface (c) Assela Pathirana Released under GNU GPL v.3

Release History:

version 1.0.0.1 first production (non-beta) release.

version 1.1.0.1 version with new SWMM 5.1 version (instead of SWMM 5.0)

Installation:

Windows:

As of version 1.0.0.1 SWMM5 is verified to work with Python 3 as well.

Now (as of version 1.0.0.1) the package is provided as python Wheel too. This means for windows the following command should install SWMM5

pip install SWMM5

Alternatively, use the SWMM5-x.y.z.k.win32.exe file downloaded from the repository for click and install.

If you have your own C compilers, then SWMM5-x.y.z.k.zip can be used to install as

python setup.py install

Linux:

Download SWMM5-x.y.z.k.zip can be used to install as

python setup.py install

Or, just with,

pip install SWMM5

Usage:

New Interface:

One should always use the new interface. The old interface (below) is left only for backward compatibility. The key features of new interface are

• More pythonic interface

• A number of convenience functions

Import new interface and run SWMM

>>> from swmm5.swmm5tools import SWMM5Simulation
>>> st=SWMM5Simulation("swmm5/examples/simple/swmm5Example.inp")

Example 1:

Retrive simulation properties.

>>> st.SWMM5_Version()          # Version of underlying SWMM5 engine.
'5.1.000'
>>> st.SWMM5_VERSION            # same thing as an integer
51000
>>> st.Flow_Units()           # Flow units.
'LPS'
>>> st.SWMM_FlowUnits         # returns flow units as an index.  0 = CFS, 1 = GPM, 2 = MGD, 3 = CMS, 4 = LPS, and 5 = LPD
4
>>> st.SWMM_Nperiods          # number of reporting periods
360
>>> st.SWMM_Nsubcatch         # number of subcatchments
6
>>> st.SWMM_Nnodes            # number of drainage system nodes
12
>>> st.SWMM_Nlinks            # number of drainage system links
11
>>> st.SWMM_Npolluts          # number of pollutants tracked
0
>>> print ("%.2f"%st.SWMM_StartDate)  # start date of simulation
40844.00
>>> st.SWMM_ReportStep
60
>>>

Example 2:

Prints available entities

>>> st.entityList()
['SUBCATCH', 'NODE', 'LINK', 'SYS']
>>> st.Subcatch()
['A2', 'A1', 'A3', 'A4', 'A5', 'E1']
>>> st.Node()
['J1', 'J2', 'J3', 'J4', 'J5', 'J6', 'J7', 'J8', 'J9', 'J10', 'J11', 'J12']
>>> st.Link()
['T4-1', 'T4-2', 'T4-3', 'T1-1', 'T1-2', 'T2-1', 'T2-2', 'T2-3', 'T3-1', 'T3-2', 'T5']
>>> st.Sys()
['SYS']
>>> st.Pollutants() # no pollutants in this file.
[]
>>> wq=SWMM5Simulation("swmm5/examples/waterquality/Example5-EXP5.1.inp")
>>> wq.SWMM_Npolluts
1
>>> wq.Pollutants() # TSS in this case.
['TSS']
>>> lst=st.varList("SUBCATCH")
>>> print ("\n".join( "%4i %s"% (i,v) for i,v in  enumerate(lst))) # print in a column with index.
   0 Rainfall (in/hr or mm/hr)
   1 Snow depth (in or mm)
   2 Evaporation loss (in/hr or mm/hr)
   3 Infiltration loss (in/hr or mm/hr)
   4 Runoff rate (flow units)
   5 Groundwater outflow rate (flow units)
   6 Groundwater water table elevation (ft or m)
   7 Soil Moisture (volumetric fraction, less or equal tosoil porosity)



>>> lst=wq.varList("SUBCATCH") # for the network that has pollutants.
>>> print ("\n".join( "%4i %s"% (i,v) for i,v in  enumerate(lst))) # print in a column with index.
   0 Rainfall (in/hr or mm/hr)
   1 Snow depth (in or mm)
   2 Evaporation loss (in/hr or mm/hr)
   3 Infiltration loss (in/hr or mm/hr)
   4 Runoff rate (flow units)
   5 Groundwater outflow rate (flow units)
   6 Groundwater water table elevation (ft or m)
   7 Soil Moisture (volumetric fraction, less or equal tosoil porosity)
   8 Runoff concentration of TSS (mg/l)

>>> lst=wq.varList("NODE")
>>> print ("\n".join( "%4i %s"% (i,v) for i,v in  enumerate(lst))) # print in a column with index.
   0 Depth of water above invert (ft or m)
   1 Hydraulic head (ft or m)
   2 Volume of stored + ponded water (ft3 or m3)
   3 Lateral inflow (flow units)
   4 Total inflow (lateral + upstream) (flow units)
   5 Flow lost to flooding (flow units)
   6 Concentration of TSS (mg/l)
>>> lst=wq.varList("LINK")
>>> print ("\n".join( "%4i %s"% (i,v) for i,v in  enumerate(lst))) # print in a column with index.
   0 Flow rate (flow units)
   1 Flow depth (ft or m)
   2 Flow velocity (ft/s or m/s)
   3 Froude number
   4 Capacity (fraction of conduit filled)
   5 Concentration of TSS (mg/l)
>>> lst=wq.varList("SYS")
>>> print ("\n".join( "%4i %s"% (i,v) for i,v in  enumerate(lst))) # print in a column with index.
   0 Air temperature (deg. F or deg. C)
   1 Rainfall (in/hr or mm/hr)
   2 Snow depth (in or mm)
   3 Evaporation + infiltration loss rate (in/hr or mm/hr)
   4 Runoff flow (flow units)
   5 Dry weather inflow (flow units)
   6 Groundwater inflow (flow units)
   7 RDII inflow (flow units)
   8 User supplied direct inflow (flow units)
   9 Total lateral inflow (sum of variables 4 to 8) (flow units)
  10 Flow lost to flooding (flow units)
  11 Flow leaving through outfalls (flow units)
  12 Volume of stored water (ft3 or m3)
  13 Evaporation rate (in/day or mm/day)

Example 3:

Results

>>> r=list(st.Results('NODE','J1', 4)) # total inflow into node "J1". The Results function returns a generator. We convert it to a list.
>>> print ("\n".join( "%5.2f"% (i) for i in  r[0:10])) # Lets print the first 10 items.
 0.00
 0.00
 0.00
 3.21
13.50
27.90
45.63
64.32
82.79
101.84
>>> r=st.Results('SYS','SYS', 1)  #1 Rainfall (in/hr or mm/hr). This time we use the generator directly.
>>> print ("\n".join(["%5.2f"% (i) for i in  r]))  #doctest: +ELLIPSIS
 0.00
 0.00
 7.20
 7.20
 7.20
 7.60
 7.60
 7.60
 8.00
 ...
 0.00

Example 4:

Pollutant Concentration

>>> wq.Subcatch()
['S1', 'S2', 'S3', 'S4', 'S5', 'S6', 'S7']

>>> r=list(wq.Results('SUBCATCH','S3', 8)) # TSS out of catchment 'S3'. We convert it to a list.
>>> print ("\n".join( "%5.2f"% (i) for i in  r[0:10])) # Lets print the first 10 items.  #doctest.NORMALIZE_WHITESPACE
 0.00
 0.00
 0.00
 0.00
 0.00
13.45
14.11
14.71
15.24
15.70

>>> wq.Node()
['J1', 'J2', 'J3', 'J4', 'J5', 'J6', 'J7', 'J8', 'J9', 'J10', 'J11', 'O1']

>>> r=list(wq.Results('NODE','J3', 6)) # TSS out of Node 'J3'. We convert it to a list.
>>> print ("\n".join( "%5.2f"% (i) for i in  r[0:10])) # Lets print the first 10 items.
 0.00
 0.00
 0.00
 0.00
 0.00
13.26
14.10
14.70
15.23
15.69

>>> wq.Link()
['C1', 'C2', 'C3', 'C4', 'C5', 'C6', 'C7', 'C8', 'C9', 'C10', 'C11']

>>> r=list(wq.Results('LINK','C11', 5)) # TSS out of Link 'C11'. We convert it to a list.
>>> print ("\n".join( "%5.2f"% (i) for i in  r)) # Lets print the first 10 items.  #doctest:  +ELLIPSIS
 0.00
 0.00
 0.00
 0.00
 0.00
 0.00
 0.00
 5.42
 9.96
12.76
14.77
16.43
17.91
19.27
20.56
...
44.65

Example 5:

Tracking output files

>>> simtemp=SWMM5Simulation("swmm5/examples/simple/swmm5Example.inp")
>>> f=simtemp.getFiles()
>>> f #doctest: +ELLIPSIS
['swmm5/examples/simple/swmm5Example.inp', '...swmm5Example....rpt', '...swmm5Example....dat']
>>> from os.path import isfile
>>> [isfile(x) for x in f] # do they exist in the operating system.
[True, True, True]
>>> simtemp.clean()
>>> [isfile(x) for x in f] # do they exist in the operating system.
[True, False, False]

Thread Safety

Calling SWMM5Simulation with input file as only argument (SWMM5Simulation will choose the report and binary output file names) and subsequent use of the object to retreive results is threadsafe to the degree I could verify.

There is a test test_multithreading.py in the test directory, which can be run to test this to some degree. It should be run as python test_multithreading.py.

Legacy interface

Note:

This is provided only for backward compatibility. Always use the new interface (above).

import swmm5 module

>>> from swmm5 import swmm5 as sw
>>>

run a sample network

>>> ret=sw.RunSwmmDll("./swmm5/examples/simple/swmm5Example.inp","swmm5Example.rpt","swmm5.dat")
>>>

should return 0 if everything is OK (according to to swmm convension)

>>> print (ret)
0
>>>

Now it is possible to retrive results. Open the swmm results file

>>> sw.OpenSwmmOutFile("swmm5.dat")
0
>>>

How many time steps are there?

>>> sw.cvar.SWMM_Nperiods
360
>>>

Let’s retrive rainfall in the system. Systems rainfall at fifth timestep

>>> ret,x=sw.GetSwmmResult(3,0,1,5)
>>> print ('%.2f' % x)
7.20
>>>

Acknowlegements

• David Townshend

• Tim Cera