pyFMI Python simulation different number of output points
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How to pricisely control the number of model outputs
I get an different number of output points based on different input parameters:
model = load_fmu("Trial.fmu") # 64 Bit generated FMU with Dymola+Buildsyspro
tstart = model.get_default_experiment_start_time() #### START TIME
tstop = model.get_default_experiment_stop_time() #### STOP TIME
opts = model.simulate_options () # Setting the output number of outputs
opts['ncp']=194 ## Want to have exactly 194 data points
foo is a function to convert parameters into the righ format
thetaInit are the initial values of paramaters
results=model.simulate(input=foo(thetaInit),options=opts, start_time=tstart, final_time=tstop)
len(results['DC_Power')
267
Changing the initial parameters values by multiplying them with 0.9
results2=model.simulate(input=foo(thetaInit*0.9),options=opts, start_time=tstart, final_time=tstop)
len(results['DC_Power')
263
For calibration issues I need to have the same number of output points. If somebody has a clue how to control this.
python optimization modelica dymola fmi
asked Nov 16 '18 at 14:07
kelamahimkelamahim
701112
add a comment |
How to pricisely control the number of model outputs
I get an different number of output points based on different input parameters:
model = load_fmu("Trial.fmu") # 64 Bit generated FMU with Dymola+Buildsyspro
tstart = model.get_default_experiment_start_time() #### START TIME
tstop = model.get_default_experiment_stop_time() #### STOP TIME
opts = model.simulate_options () # Setting the output number of outputs
opts['ncp']=194 ## Want to have exactly 194 data points
foo is a function to convert parameters into the righ format
thetaInit are the initial values of paramaters
results=model.simulate(input=foo(thetaInit),options=opts, start_time=tstart, final_time=tstop)
len(results['DC_Power')
267
Changing the initial parameters values by multiplying them with 0.9
results2=model.simulate(input=foo(thetaInit*0.9),options=opts, start_time=tstart, final_time=tstop)
len(results['DC_Power')
263
For calibration issues I need to have the same number of output points. If somebody has a clue how to control this.
python optimization modelica dymola fmi
asked Nov 16 '18 at 14:07
kelamahimkelamahim
701112
1
I assume the reason for the extra points are events. I would assume there is a way of turning off storing values at events in pyFMI; but haven't investigated it yet.
– Hans Olsson
Nov 16 '18 at 17:00
add a comment |
How to pricisely control the number of model outputs
I get an different number of output points based on different input parameters:
model = load_fmu("Trial.fmu") # 64 Bit generated FMU with Dymola+Buildsyspro
tstart = model.get_default_experiment_start_time() #### START TIME
tstop = model.get_default_experiment_stop_time() #### STOP TIME
opts = model.simulate_options () # Setting the output number of outputs
opts['ncp']=194 ## Want to have exactly 194 data points
foo is a function to convert parameters into the righ format
thetaInit are the initial values of paramaters
results=model.simulate(input=foo(thetaInit),options=opts, start_time=tstart, final_time=tstop)
len(results['DC_Power')
267
Changing the initial parameters values by multiplying them with 0.9
results2=model.simulate(input=foo(thetaInit*0.9),options=opts, start_time=tstart, final_time=tstop)
len(results['DC_Power')
263
For calibration issues I need to have the same number of output points. If somebody has a clue how to control this.
python optimization modelica dymola fmi
asked Nov 16 '18 at 14:07
kelamahimkelamahim
701112
How to pricisely control the number of model outputs
I get an different number of output points based on different input parameters:
model = load_fmu("Trial.fmu") # 64 Bit generated FMU with Dymola+Buildsyspro
tstart = model.get_default_experiment_start_time() #### START TIME
tstop = model.get_default_experiment_stop_time() #### STOP TIME
opts = model.simulate_options () # Setting the output number of outputs
opts['ncp']=194 ## Want to have exactly 194 data points
foo is a function to convert parameters into the righ format
thetaInit are the initial values of paramaters
results=model.simulate(input=foo(thetaInit),options=opts, start_time=tstart, final_time=tstop)
len(results['DC_Power')
267
Changing the initial parameters values by multiplying them with 0.9
results2=model.simulate(input=foo(thetaInit*0.9),options=opts, start_time=tstart, final_time=tstop)
len(results['DC_Power')
263
For calibration issues I need to have the same number of output points. If somebody has a clue how to control this.
python optimization modelica dymola fmi
python optimization modelica dymola fmi
asked Nov 16 '18 at 14:07
kelamahimkelamahim
701112
asked Nov 16 '18 at 14:07
kelamahimkelamahim
701112
edited Nov 16 '18 at 14:34
kelamahim
asked Nov 16 '18 at 14:07
kelamahimkelamahim
701112
asked Nov 16 '18 at 14:07
kelamahimkelamahim
701112
asked Nov 16 '18 at 14:07
kelamahimkelamahim
701112
701112
1
I assume the reason for the extra points are events. I would assume there is a way of turning off storing values at events in pyFMI; but haven't investigated it yet.
– Hans Olsson
Nov 16 '18 at 17:00
add a comment |
1
I assume the reason for the extra points are events. I would assume there is a way of turning off storing values at events in pyFMI; but haven't investigated it yet.
– Hans Olsson
Nov 16 '18 at 17:00
1
1
I assume the reason for the extra points are events. I would assume there is a way of turning off storing values at events in pyFMI; but haven't investigated it yet.
– Hans Olsson
Nov 16 '18 at 17:00
I assume the reason for the extra points are events. I would assume there is a way of turning off storing values at events in pyFMI; but haven't investigated it yet.
– Hans Olsson
Nov 16 '18 at 17:00
add a comment |
1 Answer
1
active
oldest
votes
As Hans points out the extra points are likely due to events which are stored by default (on top of the ncp). Disabling storing of the event points can be done using:
model = load_fmu(...)
opts = model.simulate_options()
opts["CVode_options"]["store_event_points"] = False
res = model.simulate(options=opts)
answered Nov 16 '18 at 20:58
Christian WintherChristian Winther
7831615
was exactly what I was looking for!
– kelamahim
Nov 19 '18 at 12:49
add a comment |
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1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
As Hans points out the extra points are likely due to events which are stored by default (on top of the ncp). Disabling storing of the event points can be done using:
model = load_fmu(...)
opts = model.simulate_options()
opts["CVode_options"]["store_event_points"] = False
res = model.simulate(options=opts)
answered Nov 16 '18 at 20:58
Christian WintherChristian Winther
7831615
was exactly what I was looking for!
– kelamahim
Nov 19 '18 at 12:49
add a comment |
As Hans points out the extra points are likely due to events which are stored by default (on top of the ncp). Disabling storing of the event points can be done using:
model = load_fmu(...)
opts = model.simulate_options()
opts["CVode_options"]["store_event_points"] = False
res = model.simulate(options=opts)
answered Nov 16 '18 at 20:58
Christian WintherChristian Winther
7831615
was exactly what I was looking for!
– kelamahim
Nov 19 '18 at 12:49
add a comment |
As Hans points out the extra points are likely due to events which are stored by default (on top of the ncp). Disabling storing of the event points can be done using:
model = load_fmu(...)
opts = model.simulate_options()
opts["CVode_options"]["store_event_points"] = False
res = model.simulate(options=opts)
answered Nov 16 '18 at 20:58
Christian WintherChristian Winther
7831615
As Hans points out the extra points are likely due to events which are stored by default (on top of the ncp). Disabling storing of the event points can be done using:
model = load_fmu(...)
opts = model.simulate_options()
opts["CVode_options"]["store_event_points"] = False
res = model.simulate(options=opts)
answered Nov 16 '18 at 20:58
Christian WintherChristian Winther
7831615
answered Nov 16 '18 at 20:58
Christian WintherChristian Winther
7831615
answered Nov 16 '18 at 20:58
Christian WintherChristian Winther
7831615
answered Nov 16 '18 at 20:58
Christian WintherChristian Winther
7831615
7831615
was exactly what I was looking for!
– kelamahim
Nov 19 '18 at 12:49
add a comment |
was exactly what I was looking for!
– kelamahim
Nov 19 '18 at 12:49
was exactly what I was looking for!
– kelamahim
Nov 19 '18 at 12:49
was exactly what I was looking for!
– kelamahim
Nov 19 '18 at 12:49
add a comment |
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1
I assume the reason for the extra points are events. I would assume there is a way of turning off storing values at events in pyFMI; but haven't investigated it yet.
– Hans Olsson
Nov 16 '18 at 17:00