7. The Gridsim Input/Output

The input/output module provides loader and saver interfaces.

Currently Gridsim provides loader for CSV file (CSVReader) and savers for CSV file (CSVSaver) and images – .png, .jpg, .pdf, etc. – (FigureSaver).

7.1. Input

class gridsim.iodata.input.Reader(self)

Bases: object

This class is the based class of all readers/loaders.

clear(self)

Empties the data of the Reader.

load(self, data_type=None, nb_data=float("inf"))

This method MUST returns formatted data following this format [(label1, data1], (label2, data2), ...]

with:

  • labelX: a str
  • dataX: a list of data_type
Parameters:
  • data_type (type (default None)) – the type of stored data if None no conversion are done.
  • nb_data (int) – the number of data to load
Returns:

a dict of values
Return type:

dict
class gridsim.iodata.input.CSVReader(self)

Bases: gridsim.iodata.input.Reader

This class reads a CSV file and stores the data as follow:

[(label1, data1], (label2, data2), ...]

with:

  • labelX: a str
  • dataX: a list of data_type
Parameters:stream (str or every type managed by with keyword) – a stream of data or a file name
DEFAULT_DATA_NAME = 'DATA_'

If no header, the label of the dict returned by gridsim.iodata.input.CSVReader.load() will be DATA_X with X an integer representing the column in the file:

0 <= X < column number - 1

clear(self)

Removes all data stored in the object.

Returns:
load(self, data_type=None, nb_data=sys.maxint)

Loads the data from the given CSV data file.

Parameters:
  • data_type (type) – the type of the stored data if None no conversion are done.
  • nb_data (int) – the number of line to load
class gridsim.iodata.input.CSVTimeReader(self)

Bases: gridsim.iodata.input.CSVReader

This class reads a CSV file and stores the data as follow:

[(label1, data1], (label2, data2), ...]

with:

  • labelX: a str
  • dataX: a list of data_type
Parameters:stream (str or every type managed by with keyword) – a stream of data or a file name
load(self, data_type=None, nb_data=float("inf"))

Loads the data from the given CSV data file.

Parameters:
  • data_type (type) – the type of the stored data if None no conversion are done.
  • nb_data (int .. warning:: The first column is consider as time column. nb_data MUST have the same unit as the time in the stream) – the time the load MUST stop

7.2. Output

Module author: Gillian Basso <gillian.basso@hevs.ch>

Code author: Michael Clausen <clm@hevs.ch>

Code author: Gillian Basso <gillian.basso@hevs.ch>

This module provides interfaces to save data.

To use the Saver a class has to implement the AttributesGetter interface.

Example:

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from gridsim.unit import units
from gridsim.simulation import Simulator
from gridsim.thermal.core import ThermalCoupling, ThermalProcess
from gridsim.thermal.element import ConstantTemperatureProcess
from gridsim.recorder import PlotRecorder
from gridsim.iodata.output import FigureSaver, CSVSaver

# Gridsim simulator.
sim = Simulator()

# Create a simple thermal process: Two rooms and the thermal coupling between
# them and to the outside temperature.
#             __________                        ___________
#           |          |   ________________   |           |
#           |   room1  |]-| room1 to room2 |-[| cold_room |
#           |    18 C  |  |_____50_W/K_____|  |    25 C   |      outside 5 C
#  10 W/K -[|          |                      |           |]- 10 W/K
#           |__________|                      |___________|
#
celsius = units(18, units.degC)
room1 = sim.thermal.add(ThermalProcess.room('room1',
                                            50*units.meter*units.meter,
                                            2.5*units.metre,
                                            units.convert(celsius, units.kelvin)))
celsius = units(25, units.degC)
room2 = sim.thermal.add(ThermalProcess.room('room2',
                                            50*units.meter*units.meter,
                                            2.5*units.metre,
                                            units.convert(celsius, units.kelvin)))

celsius = units(5, units.degC)
outside = sim.thermal.add(
    ConstantTemperatureProcess('outside', units.convert(celsius, units.kelvin)))

sim.thermal.add(ThermalCoupling('room1 to outside',
                                10*units.thermal_conductivity,
                                room1, outside))
sim.thermal.add(ThermalCoupling('room2 to outside',
                                10*units.thermal_conductivity,
                                room2, outside))
sim.thermal.add(ThermalCoupling('room1 to room2',
                                50*units.thermal_conductivity,
                                room1, room2))

# Create a plot recorder that records the temperatures of all thermal processes.
kelvin = PlotRecorder('temperature', units.second, units.kelvin)
sim.record(kelvin, sim.thermal.find(has_attribute='temperature'))

# Create a plot recorder that records the temperatures of all thermal
# processes in Kelvin.
celsius = PlotRecorder('temperature', units.minutes, units.degC)
sim.record(celsius, sim.thermal.find(has_attribute='temperature'))

# Create a second plot recorder which records all energy flows
# (thermal couplings) between the different processes.

flow = PlotRecorder('power', units.second, units.watt)
sim.record(flow, sim.thermal.find(element_class=ThermalCoupling))

print("Running simulation...")

# Run the simulation for an hour with a resolution of 1 second.
sim.run(2*units.hour, 1*units.second)

print("Saving data...")

# Save the figures as images.
FigureSaver(kelvin, "Temperature (K)").save('./output/fig1.png')
FigureSaver(celsius, "Temperature (C)").save('./output/fig2.png')
FigureSaver(flow, "Flow").save('./output/fig3.png')

CSVSaver(celsius).save('./output/fig2.csv')
  • On lines 46, 51 and 57, we create Recorder objects.
  • On lines 47, 52 and 58, we add the recorders to the simulation.
  • On lines 68 to 70, we use the recorders as AttributeGetter to save them in figure. Here, the 3 images file saved:
_images/fig1.png
_images/fig2.png
_images/fig3.png
  • On line 72, we use a second saver to save in a csv file the a recorder we already saved, here the 20th first lines:
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minute,outside,room2,room1
0.0,5.0,25.0,18.0
0.0166666666667,5.0,24.9963515755,18.0014593698
0.0333333333333,5.0,24.9927050871,18.0029169487
0.05,5.0,24.9890605334,18.004372738
0.0666666666667,5.0,24.9854179132,18.0058267391
0.0833333333333,5.0,24.9817772251,18.0072789533
0.1,5.0,24.9781384676,18.008729382
0.116666666667,5.0,24.9745016395,18.0101780265
0.133333333333,5.0,24.9708667394,18.0116248882
0.15,5.0,24.9672337658,18.0130699684
0.166666666667,5.0,24.9636027176,18.0145132685
0.183333333333,5.0,24.9599735932,18.0159547898
0.2,5.0,24.9563463914,18.0173945337
0.216666666667,5.0,24.9527211107,18.0188325015
0.233333333333,5.0,24.9490977499,18.0202686946
0.25,5.0,24.9454763076,18.0217031143
0.266666666667,5.0,24.9418567824,18.0231357619
0.283333333333,5.0,24.938239173,18.0245666388
0.3,5.0,24.934623478,18.0259957463
class gridsim.iodata.output.AttributesGetter(self)

Bases: object

This is the based class for all data which have to be saved.

x_values(self)

This method returns x values of data stored.

Returns:a list of values
Return type:list
x_unit(self)

This method returns x unit of data stored.

Returns:a string representing the unit.
Return type:str
y_values(self)

This method returns y values of data stored. As more than one data can be sent, the values have to be sent with the following format: [(label1, data1), (label2, data2), ...] with: * labelX: a string representing the dataX * dataX: a list of data

Returns:a dict of values
Return type:dict
y_unit(self)

This method returns y unit of data stored.

Returns:a string representing the unit.
Return type:str
class gridsim.iodata.output.FigureSaver(self, values, title)

Bases: object

A FigureSaver can be used to record a class:.AttributesGetter and plot it in a file.

Parameters:
  • values (AttributesGetter) – The values to display
  • title (str) – The title of the plot.
x_label
y_label
figure

The matplotlib figure identifier. If the figure was not already rendered, it will do this by calling render() automatically before actually returning the figure.

render(self, y_min=None, y_max=None)

Does the actual figure and returns the matplotlib figure identifier.

Note

you do not need to call this method explicitly as it will get called as soon as needed by other methods like save() or the property getter figure are called. This method offers some fine tuning parameters to control the look of the figure.

Parameters:
  • y_min (float) – Minimal value on the y-axis.
  • y_max (float) – Maximal value on the y-axis.
save(self, file_name)

Saves the figure in the given file (file_name). The format is deduced from the file name extension. The output supported formats available depend on the backend being used. On Unix systems these formats are normally supported:

Scalable Vector Graphics - *.svg, *.svgz (zip *.svg)

Graphics Interchange Format - *.gif

Portable Network Graphics - *.png

JPEG Image - *.jpg, *.jpeg

Postscript - *.ps

Encapsulated Postscript - *.eps

Tagged Image Format File - *.tif, *.tiff

Raw RGBA bitmap - *.raw, *.rgba

Portable Document Format - *.pdf

Parameters:file_name (str) – File name (path) where to save the figure. The file format is deduced from the file extension.
class gridsim.iodata.output.CSVSaver(self, values, separator=', ')

Bases: object

This saver save data as a text file with the csv format with the given.

Parameters:
  • values (AttributesGetter) – The values to display
  • separator (str) – the separator of two data in the same line
save(self, file_name)

Saves the data in the given file (file_name). The format is a text file regardless the extension of the file. The data is store with the csv format and the header are the data returned by gridsim.iodata.output.AttributesGetter.x_unit() and gridsim.iodata.output.AttributesGetter.y_unit()

Parameters:file_name (str) – File name (path) where to save the file.