7.6. Module pyDataReporting<a class="headerlink" href="#module-pydatareporting" title="Permalink to this headline">¶

Process¶

dictDomains¶

dictVariables¶

class daeNoOpDataReporter¶: Bases: pyDataReporting.daeDataReporterLocal

class daeDataReporterFile¶

WriteDataToFile((daeDataReporterFile)self) → None¶

class daeTEXTFileDataReporter¶

WriteDataToFile((daeTEXTFileDataReporter)self) → None¶

7.6.2.2. Third-party local data reporters¶

`daePlotDataReporter`()	Plots the specified variables using the Matplotlib library (by Caleb Hattingh).
`daeMatlabMATFileDataReporter`()	Saves data in Matlab MAT format format (.mat) using scipy.io.savemat function.
`daeExcelFileDataReporter`()	Saves data into the Microsoft Excel format (.xlsx) using the openpyxl library (https://openpyxl.readthedocs.io).
`daeJSONFileDataReporter`()	Saves data in JSON text format using the Python json library.
`daeXMLFileDataReporter`()	Saves data in XML format (.xml) using the Python xml library.
`daeHDF5FileDataReporter`()	Saves data in HDF5 format using the Python h5py library.
`daePandasDataReporter`()	Creates a dataset using the Pandas library (available as data_frame property - the Pandas DataFrame object).
`daeVTKDataReporter`()	Saves data in the binary VTK format (.vtr) using the pyEVTK module.
`daePickleDataReporter`()	Saves data as the Python pickle which can be opened in DAE Plotter

class daePlotDataReporter[source]¶

Plots the specified variables using the Matplotlib library (by Caleb Hattingh).

Plot(*args, **kwargs)[source]¶

args can be either:

Instances of daeVariable, or
Lists of daeVariable instances, or
A mixture of both.

Each arg will get its own subplot. The subplots are all automatically arranged such that the resulting figure is as square-like as possible. You can however override the shape by supplying figRows and figCols as keyword args.

Basic Example:

# Create Log, Solver, DataReporter and Simulation object
log = daePythonStdOutLog()
daesolve = daeIDAS()
from daetools.pyDAE.data_reporters import daePlotDataReporter
datareporter = daePlotDataReporter()
simulation = simTutorial()

simulation.m.SetReportingOn(True)
simulation.ReportingInterval = 20
simulation.TimeHorizon = 500

simName = simulation.m.Name + strftime(" [%d.%m.%Y %H:%M:%S]", localtime())
if(datareporter.Connect("", simName) == False):
    sys.exit()

simulation.Initialize(daesolver, datareporter, log)

simulation.m.SaveModelReport(simulation.m.Name + ".xml")
simulation.m.SaveRuntimeModelReport(simulation.m.Name + "-rt.xml")

simulation.SolveInitial()
simulation.Run()

simulation.Finalize()
datareporter.Plot(
    simulation.m.Ci,                       # Subplot 1
    [simulation.m.L, simulation.m.event],  # Subplot 2 (2 sets)
    simulation.m.Vp,                       # Subplot 3
    [simulation.m.L, simulation.m.Vp]      # Subplot 4 (2 sets)
    )

class daeMatlabMATFileDataReporter[source]¶

Saves data in Matlab MAT format format (.mat) using scipy.io.savemat function. Every variable is saved as numpy array (variable names are stripped from illegal characters). In addition, time and domain points for every variable are saved as ‘varName.Times’ and ‘varName.Domains’. Does not require Matlab installed.

WriteDataToFile()[source]¶

class daeExcelFileDataReporter[source]¶

Saves data into the Microsoft Excel format (.xlsx) using the openpyxl library (https://openpyxl.readthedocs.io). Does not require Excel installed and works on all operating systems.

WriteDataToFile()[source]¶

class daeJSONFileDataReporter[source]¶

Saves data in JSON text format using the Python json library.

WriteDataToFile()[source]¶

class daeXMLFileDataReporter[source]¶

Saves data in XML format (.xml) using the Python xml library. The numerical data are saved as json strings (for easier parsing).

WriteDataToFile()[source]¶

class daeHDF5FileDataReporter[source]¶

Saves data in HDF5 format using the Python h5py library. A separate group is created for every variable and contain the following data sets: - Values: multidimensional array with the variable values - Times: 1d array with the time points - DomainNames: names of the domains that the variable is distributed on - Domains: multidimensional array with the domain points - Units: variable units as a string

WriteDataToFile()[source]¶

class daePandasDataReporter[source]¶

Creates a dataset using the Pandas library (available as data_frame property - the Pandas DataFrame object).

data_frame¶

class daeVTKDataReporter[source]¶

Saves data in the binary VTK format (.vtr) using the pyEVTK module. pyEVTK is included in the daetools installation (daetools.ext_libs.pyevtk). A separate file is written into the specified directory for every time point. In addition, the ‘variableName.visit’ files are written for use with the VisIt software. Notate bene:

The original is available at https://pypi.python.org/pypi/PyEVTK. Install using: “pip install pyevtk”.
It is not an original module available at https://bitbucket.org/pauloh/pyevtk.

Does not require VTK installed.

WriteFiles()[source]¶

class daePickleDataReporter[source]¶

Saves data as the Python pickle which can be opened in DAE Plotter or unpickled directly:

f = open(filename, 'rb')
process = pickle.load(f)
f.close()

where process is the dataReceiverProcess instance identical to the daeDataReceiverProcess objects used in the other data reporters below.

WriteDataToFile()[source]¶

7.6.2.3. Data reporters that do send data to a data receiver (remote data reporters)¶

class daeDataReporterRemote¶

SendMessage((daeDataReporterRemote)self, (str)message) → bool¶

class daeTCPIPDataReporter¶

Bases: pyDataReporting.daeDataReporterRemote

SendMessage((daeTCPIPDataReporter)self, (str)message) → bool¶

7.6.2.4. Special-purpose data reporters¶

class daeBlackHoleDataReporter¶

Data reporter that does not process any data and all function calls simply return True. Could be used when no results from the simulation are needed.

class daeDelegateDataReporter¶