New functions¶
These are recently written functions that have not made it into the main documentation
Python Lesson: Errors and Exceptions¶
# you would normaly install eppy by doing
# python setup.py install
# or
# pip install eppy
# or
# easy_install eppy
# if you have not done so, uncomment the following three lines
import sys
# pathnameto_eppy = 'c:/eppy'
pathnameto_eppy = '../'
sys.path.append(pathnameto_eppy)
When things go wrong in your eppy script, you get “Errors and Exceptions”.
To know more about how this works in python and eppy, take a look at Python: Errors and Exceptions
Setting IDD name¶
When you work with Energyplus you are working with idf files (files that have the extension *.idf). There is another file that is very important, called the idd file. This is the file that defines all the objects in Energyplus. Esch version of Energyplus has a different idd file.
So eppy needs to know which idd file to use. Only one idd file can be used in a script or program. This means that you cannot change the idd file once you have selected it. Of course you have to first select an idd file before eppy can work.
If you use eppy and break the above rules, eppy will raise an exception. So let us use eppy incorrectly and make eppy raise the exception, just see how that happens.
First let us try to open an idf file without setting an idd file.
from eppy import modeleditor
from eppy.modeleditor import IDF
fname1 = "../eppy/resources/idffiles/V_7_2/smallfile.idf"
Now let us open file fname1 without setting the idd file
try:
idf1 = IDF(fname1)
except Exception, e:
raise e
---------------------------------------------------------------------------
IDDNotSetError Traceback (most recent call last)
<ipython-input-3-44ad2b53d42c> in <module>()
2 idf1 = IDF(fname1)
3 except Exception, e:
----> 4 raise e
5
IDDNotSetError: IDD file needed to read the idf file. Set it using IDF.setiddname(iddfile)
OK. It does not let you do that and it raises an exception
So let us set the idd file and then open the idf file
iddfile = "../eppy/resources/iddfiles/Energy+V7_2_0.idd"
IDF.setiddname(iddfile)
idf1 = IDF(fname1)
That worked without raising an exception
Now let us try to change the idd file. Eppy should not let you do this and should raise an exception.
try:
IDF.setiddname("anotheridd.idd")
except Exception, e:
raise e
---------------------------------------------------------------------------
IDDAlreadySetError Traceback (most recent call last)
<ipython-input-5-52df819ac489> in <module>()
2 IDF.setiddname("anotheridd.idd")
3 except Exception, e:
----> 4 raise e
5
IDDAlreadySetError: IDD file is set to: ../eppy/resources/iddfiles/Energy+V7_2_0.idd
Excellent!! It raised the exception we were expecting.
Check range for fields¶
The fields of idf objects often have a range of legal values. The following functions will let you discover what that range is and test if your value lies within that range
demonstrate two new functions:
- EpBunch.getrange(fieldname) # will return the ranges for that field
- EpBunch.checkrange(fieldname) # will throw an exception if the value is outside the range
from eppy import modeleditor
from eppy.modeleditor import IDF
iddfile = "../eppy/resources/iddfiles/Energy+V7_2_0.idd"
fname1 = "../eppy/resources/idffiles/V_7_2/smallfile.idf"
# IDF.setiddname(iddfile)# idd ws set further up in this page
idf1 = IDF(fname1)
building = idf1.idfobjects['building'.upper()][0]
print building
BUILDING,
Empire State Building, !- Name
30.0, !- North Axis
City, !- Terrain
0.04, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
print building.getrange("Loads_Convergence_Tolerance_Value")
{u'maximum<': None, u'minimum': None, u'type': u'real', u'maximum': 0.5, u'minimum>': 0.0}
print building.checkrange("Loads_Convergence_Tolerance_Value")
0.04
Let us set these values outside the range and see what happens
building.Loads_Convergence_Tolerance_Value = 0.6
from eppy.bunch_subclass import RangeError
try:
print building.checkrange("Loads_Convergence_Tolerance_Value")
except RangeError, e:
raise e
---------------------------------------------------------------------------
RangeError Traceback (most recent call last)
<ipython-input-11-a824cb1ec673> in <module>()
4 print building.checkrange("Loads_Convergence_Tolerance_Value")
5 except RangeError, e:
----> 6 raise e
7
RangeError: Value 0.6 is not less or equal to the 'maximum' of 0.5
So the Range Check works
Looping through all the fields in an idf object¶
We have seen how to check the range of field in the idf object. What if you want to do a range check on all the fields in an idf object ? To do this we will need a list of all the fields in the idf object. We can do this easily by the following line
print building.fieldnames
[u'key', u'Name', u'North_Axis', u'Terrain', u'Loads_Convergence_Tolerance_Value', u'Temperature_Convergence_Tolerance_Value', u'Solar_Distribution', u'Maximum_Number_of_Warmup_Days', u'Minimum_Number_of_Warmup_Days']
So let us use this
for fieldname in building.fieldnames:
print "%s = %s" % (fieldname, building[fieldname])
key = BUILDING
Name = Empire State Building
North_Axis = 30.0
Terrain = City
Loads_Convergence_Tolerance_Value = 0.6
Temperature_Convergence_Tolerance_Value = 0.4
Solar_Distribution = FullExterior
Maximum_Number_of_Warmup_Days = 25
Minimum_Number_of_Warmup_Days = 6
Now let us test if the values are in the legal range. We know that “Loads_Convergence_Tolerance_Value” is out of range
from eppy.bunch_subclass import RangeError
for fieldname in building.fieldnames:
try:
building.checkrange(fieldname)
print "%s = %s #-in range" % (fieldname, building[fieldname],)
except RangeError as e:
print "%s = %s #-****OUT OF RANGE****" % (fieldname, building[fieldname],)
key = BUILDING #-in range Name = Empire State Building #-in range North_Axis = 30.0 #-in range Terrain = City #-in range Loads_Convergence_Tolerance_Value = 0.6 #-**OUT OF RANGE** Temperature_Convergence_Tolerance_Value = 0.4 #-in range Solar_Distribution = FullExterior #-in range Maximum_Number_of_Warmup_Days = 25 #-in range Minimum_Number_of_Warmup_Days = 6 #-in range
You see, we caught the out of range value
Blank idf file¶
Until now in all our examples, we have been reading an idf file from disk:
- How do I create a blank new idf file
- give it a file name
- Save it to the disk
Here are the steps to do that
# some initial steps
from eppy.modeleditor import IDF
iddfile = "../eppy/resources/iddfiles/Energy+V7_2_0.idd"
# IDF.setiddname(iddfile) # Has already been set
# - Let us first open a file from the disk
fname1 = "../eppy/resources/idffiles/V_7_2/smallfile.idf"
idf_fromfilename = IDF(fname1) # initialize the IDF object with the file name
idf_fromfilename.printidf()
VERSION,
7.3; !- Version Identifier
SIMULATIONCONTROL,
Yes, !- Do Zone Sizing Calculation
Yes, !- Do System Sizing Calculation
Yes, !- Do Plant Sizing Calculation
No, !- Run Simulation for Sizing Periods
Yes; !- Run Simulation for Weather File Run Periods
BUILDING,
Empire State Building, !- Name
30.0, !- North Axis
City, !- Terrain
0.04, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
SITE:LOCATION,
CHICAGO_IL_USA TMY2-94846, !- Name
41.78, !- Latitude
-87.75, !- Longitude
-6.0, !- Time Zone
190.0; !- Elevation
# - now let us open a file from the disk differently
fname1 = "../eppy/resources/idffiles/V_7_2/smallfile.idf"
fhandle = open(fname1, 'r') # open the file for reading and assign it a file handle
idf_fromfilehandle = IDF(fhandle) # initialize the IDF object with the file handle
idf_fromfilehandle.printidf()
VERSION,
7.3; !- Version Identifier
SIMULATIONCONTROL,
Yes, !- Do Zone Sizing Calculation
Yes, !- Do System Sizing Calculation
Yes, !- Do Plant Sizing Calculation
No, !- Run Simulation for Sizing Periods
Yes; !- Run Simulation for Weather File Run Periods
BUILDING,
Empire State Building, !- Name
30.0, !- North Axis
City, !- Terrain
0.04, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
SITE:LOCATION,
CHICAGO_IL_USA TMY2-94846, !- Name
41.78, !- Latitude
-87.75, !- Longitude
-6.0, !- Time Zone
190.0; !- Elevation
# So IDF object can be initialized with either a file name or a file handle
# - How do I create a blank new idf file
idftxt = "" # empty string
from StringIO import StringIO
fhandle = StringIO(idftxt) # we can make a file handle of a string
idf_emptyfile = IDF(fhandle) # initialize the IDF object with the file handle
idf_emptyfile.printidf()
It did not print anything. Why should it. It was empty.
What if we give it a string that was not blank
# - The string does not have to be blank
idftxt = "VERSION, 7.3;" # Not an emplty string. has just the version number
fhandle = StringIO(idftxt) # we can make a file handle of a string
idf_notemptyfile = IDF(fhandle) # initialize the IDF object with the file handle
idf_notemptyfile.printidf()
VERSION,
7.3; !- Version Identifier
Aha !
Now let us give it a file name
# - give it a file name
idf_notemptyfile.idfname = "notemptyfile.idf"
# - Save it to the disk
idf_notemptyfile.save()
Let us confirm that the file was saved to disk
txt = open("notemptyfile.idf", 'r').read()# read the file from the disk
print txt
!- Darwin Line endings
VERSION,
7.3; !- Version Identifier
Yup ! that file was saved. Let us delete it since we were just playing
import os
os.remove("notemptyfile.idf")
Deleting, copying/adding and making new idfobjects¶
Making a new idf object¶
Let us start with a blank idf file and make some new “MATERIAL” objects in it
# making a blank idf object
blankstr = ""
from StringIO import StringIO
idf = IDF(StringIO(blankstr))
To make and add a new idfobject object, we use the function IDF.newidfobject(). We want to make an object of type “MATERIAL”
newobject = idf.newidfobject("material".upper()) # the key for the object type has to be in upper case
# .upper() makes it upper case
print newobject
MATERIAL,
, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
Let us give this a name, say “Shiny new material object”
newobject.Name = "Shiny new material object"
print newobject
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
anothermaterial = idf.newidfobject("material".upper())
anothermaterial.Name = "Lousy material"
thirdmaterial = idf.newidfobject("material".upper())
thirdmaterial.Name = "third material"
print thirdmaterial
MATERIAL,
third material, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
Let us look at all the “MATERIAL” objects
print idf.idfobjects["MATERIAL"]
[
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
,
MATERIAL,
Lousy material, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
,
MATERIAL,
third material, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
]
As we can see there are three MATERIAL idfobjects. They are:
- Shiny new material object
- Lousy material
- third material
Deleting an idf object¶
Let us remove 2. Lousy material. It is the second material in the list. So let us remove the second material
idf.popidfobject('MATERIAL', 1) # first material is '0', second is '1'
MATERIAL,
Lousy material, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
print idf.idfobjects['MATERIAL']
[
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
,
MATERIAL,
third material, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
]
You can see that the second material is gone ! Now let us remove the first material, but do it using a different function
firstmaterial = idf.idfobjects['MATERIAL'][-1]
idf.removeidfobject(firstmaterial)
print idf.idfobjects['MATERIAL']
[
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
]
So we have two ways of deleting an idf object:
- popidfobject -> give it the idf key: “MATERIAL”, and the index number
- removeidfobject -> give it the idf object to be deleted
Copying/Adding an idf object¶
Having deleted two “MATERIAL” objects, we have only one left. Let us make a copy of this object and add it to our idf file
onlymaterial = idf.idfobjects["MATERIAL"][0]
idf.copyidfobject(onlymaterial)
print idf.idfobjects["MATERIAL"]
[
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
,
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
]
So now we have a copy of the material. You can use this method to copy idf objects from other idf files too.
Making an idf object with named arguments¶
What if we wanted to make an idf object with values for it’s fields? We can do that too.
Renaming an idf object¶
gypboard = idf.newidfobject('MATERIAL', Name="G01a 19mm gypsum board",
Roughness="MediumSmooth",
Thickness=0.019,
Conductivity=0.16,
Density=800,
Specific_Heat=1090)
print gypboard
MATERIAL,
G01a 19mm gypsum board, !- Name
MediumSmooth, !- Roughness
0.019, !- Thickness
0.16, !- Conductivity
800, !- Density
1090, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
newidfobject() also fills in the default values like “Thermal Absorptance”, “Solar Absorptance”, etc.
print idf.idfobjects["MATERIAL"]
[
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
,
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
,
MATERIAL,
G01a 19mm gypsum board, !- Name
MediumSmooth, !- Roughness
0.019, !- Thickness
0.16, !- Conductivity
800, !- Density
1090, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
]
Renaming an idf object¶
It is easy to rename an idf object. If we want to rename the gypboard object that we created above, we simply say:
gypboard.Name = “a new name”.
But this could create a problem. What if this gypboard is part of a “CONSTRUCTION” object. The construction object will refer to the gypboard by name. If we change the name of the gypboard, we should change it in the construction object.
But there may be many constructions objects using the gypboard. Now we will have to change it in all those construction objects. Sounds painfull.
Let us try this with an example:
interiorwall = idf.newidfobject("CONSTRUCTION", Name="Interior Wall",
Outside_Layer="G01a 19mm gypsum board",
Layer_2="Shiny new material object",
Layer_3="G01a 19mm gypsum board")
print interiorwall
CONSTRUCTION,
Interior Wall, !- Name
G01a 19mm gypsum board, !- Outside Layer
Shiny new material object, !- Layer 2
G01a 19mm gypsum board; !- Layer 3
to rename gypboard and have that name change in all the places we call modeleditor.rename(idf, key, oldname, newname)
modeleditor.rename(idf, "MATERIAL", "G01a 19mm gypsum board", "peanut butter")
MATERIAL,
peanut butter, !- Name
MediumSmooth, !- Roughness
0.019, !- Thickness
0.16, !- Conductivity
800, !- Density
1090, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
print interiorwall
CONSTRUCTION,
Interior Wall, !- Name
peanut butter, !- Outside Layer
Shiny new material object, !- Layer 2
peanut butter; !- Layer 3
Now we have “peanut butter” everywhere. At least where we need it. Let us look at the entir idf file, just to be sure
idf.printidf()
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
MATERIAL,
Shiny new material object, !- Name
, !- Roughness
, !- Thickness
, !- Conductivity
, !- Density
, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
MATERIAL,
peanut butter, !- Name
MediumSmooth, !- Roughness
0.019, !- Thickness
0.16, !- Conductivity
800, !- Density
1090, !- Specific Heat
0.9, !- Thermal Absorptance
0.7, !- Solar Absorptance
0.7; !- Visible Absorptance
CONSTRUCTION,
Interior Wall, !- Name
peanut butter, !- Outside Layer
Shiny new material object, !- Layer 2
peanut butter; !- Layer 3
Zone area and volume¶
The idf file has zones with surfaces and windows. It is easy to get the attributes of the surfaces and windows as we have seen in the tutorial. Let us review this once more:
from eppy import modeleditor
from eppy.modeleditor import IDF
iddfile = "../eppy/resources/iddfiles/Energy+V7_2_0.idd"
fname1 = "../eppy/resources/idffiles/V_7_2/box.idf"
# IDF.setiddname(iddfile)
idf = IDF(fname1)
surfaces = idf.idfobjects["BuildingSurface:Detailed".upper()]
surface = surfaces[0]
print "area = %s" % (surface.area, )
print "tilt = %s" % (surface.tilt, )
print "azimuth = %s" % (surface.azimuth, )
area = 30.0
tilt = 180.0
azimuth = 0.0
Can we do the same for zones ?
Not yet .. not yet. Not in this version on eppy
But we can still get the area and volume of the zone
zones = idf.idfobjects["ZONE"]
zone = zones[0]
area = modeleditor.zonearea(idf, zone.Name)
volume = modeleditor.zonevolume(idf, zone.Name)
print "zone area = %s" % (area, )
print "zone volume = %s" % (volume, )
zone area = 30.0
zone volume = 90.0
Not as slick, but still pretty easy
Some notes on the zone area calculation:
- area is calculated by summing up all the areas of the floor surfaces
- if there are no floors, then the sum of ceilings and roof is taken as zone area
- if there are no floors, ceilings or roof, we are out of luck. The function returns 0
Using JSON to update idf¶
we are going to update idf1 using json. First let us print the
idf1 before changing it, so we can see what has changed once we make
an update
idf1.printidf()
VERSION,
7.3; !- Version Identifier
SIMULATIONCONTROL,
Yes, !- Do Zone Sizing Calculation
Yes, !- Do System Sizing Calculation
Yes, !- Do Plant Sizing Calculation
No, !- Run Simulation for Sizing Periods
Yes; !- Run Simulation for Weather File Run Periods
BUILDING,
Empire State Building, !- Name
30.0, !- North Axis
City, !- Terrain
0.6, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
SITE:LOCATION,
CHICAGO_IL_USA TMY2-94846, !- Name
41.78, !- Latitude
-87.75, !- Longitude
-6.0, !- Time Zone
190.0; !- Elevation
import eppy.json_functions as json_functions
json_str = {"idf.VERSION..Version_Identifier":8.5,
"idf.SIMULATIONCONTROL..Do_Zone_Sizing_Calculation": "No",
"idf.SIMULATIONCONTROL..Do_System_Sizing_Calculation": "No",
"idf.SIMULATIONCONTROL..Do_Plant_Sizing_Calculation": "No",
"idf.BUILDING.Empire State Building.North_Axis": 52,
"idf.BUILDING.Empire State Building.Terrain": "Rural",
}
json_functions.updateidf(idf1, json_str)
idf1.printidf()
VERSION,
8.5; !- Version Identifier
SIMULATIONCONTROL,
No, !- Do Zone Sizing Calculation
No, !- Do System Sizing Calculation
No, !- Do Plant Sizing Calculation
No, !- Run Simulation for Sizing Periods
Yes; !- Run Simulation for Weather File Run Periods
BUILDING,
Empire State Building, !- Name
52, !- North Axis
Rural, !- Terrain
0.6, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
SITE:LOCATION,
CHICAGO_IL_USA TMY2-94846, !- Name
41.78, !- Latitude
-87.75, !- Longitude
-6.0, !- Time Zone
190.0; !- Elevation
Compare the first printidf() and the second printidf().
The syntax of the json string is described below:
idf.BUILDING.Empire State Building.Terrain": "Rural"
The key fields are seperated by dots. Let us walk through each field:
idf -> make a change to the idf. (in the future there may be changes that are not related to idf)
BUILDING -> the key for object to be changed
Empire State Building -> The name of the object. In other word - the value of the field `Name`
Terrain -> the field to be changed
"Rural" -> the new value of the field
If the object does not have a `Name` field, you leave a blank between the two dots and the first object will be changed.
This is done for the version number change.
"idf.VERSION..Version_Identifier":8.5
You can also create a new object using JSON, using the same syntax. Take a look at this:
json_str = {"idf.BUILDING.Taj.Terrain": "Rural",}
json_functions.updateidf(idf1, json_str)
idf1.idfobjects['building'.upper()]
# of course, you are creating an invalid E+ file. But we are just playing here.
[
BUILDING,
Empire State Building, !- Name
52, !- North Axis
Rural, !- Terrain
0.6, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
,
BUILDING,
Taj, !- Name
0.0, !- North Axis
Rural, !- Terrain
0.04, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
]
What if you object name had a dot . in it? Will the json_function
get confused?
If the name has a dot in it, there are two ways of doing this.
# first way
json_str = {"idf.BUILDING.Taj.with.dot.Terrain": "Rural",}
json_functions.updateidf(idf1, json_str)
# second way (put the name in single quotes)
json_str = {"idf.BUILDING.'Another.Taj.with.dot'.Terrain": "Rural",}
json_functions.updateidf(idf1, json_str)
idf1.idfobjects['building'.upper()]
[
BUILDING,
Empire State Building, !- Name
52, !- North Axis
Rural, !- Terrain
0.6, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
,
BUILDING,
Taj, !- Name
0.0, !- North Axis
Rural, !- Terrain
0.04, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
,
BUILDING,
Taj.with.dot, !- Name
0.0, !- North Axis
Rural, !- Terrain
0.04, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
,
BUILDING,
Another.Taj.with.dot, !- Name
0.0, !- North Axis
Rural, !- Terrain
0.04, !- Loads Convergence Tolerance Value
0.4, !- Temperature Convergence Tolerance Value
FullExterior, !- Solar Distribution
25, !- Maximum Number of Warmup Days
6; !- Minimum Number of Warmup Days
]
Note When you us the json update function:
- The json function expects the
Namefield to have a value. - If you try to update an object with a blank
Namefield, the results may be unexpected (undefined ? :-). So don’t do this. - If the object has no
Namefield (some don’t), changes are made to the first object in the list. Which should be fine, since usually there is only one item in the list - In any case, if the object does not exist, it is created with the default values
Use Case for JSON update¶
If you have an eppy running on a remote server somewhere on the internet, you can change an idf file by sending it a JSON over the internet. This is very useful if you ever need it. If you don’t need it, you shouldn’t care :-)