EplusJob
class wraps the EnergyPlus command line interface and provides
methods to extract simulation outputs.
eplus_job()
takes an IDF and EPW as input, and returns an EplusJob
object
for running EnergyPlus simulation and collecting outputs.
eplus_job(idf, epw)
A path to an local EnergyPlus IDF file or an Idf
object.
A path to an local EnergyPlus EPW file or an Epw
object. epw
can also be NULL
which will force design-day-only simulation when
$run()
method is called. Note this needs at least one
Sizing:DesignDay
object exists in the Idf.
An EplusJob
object.
eplusr uses the EnergyPlus SQL output for extracting simulation outputs.
EplusJob
has provide some wrappers that do SQL query to get report data
results, i.e. results from Output:Variable
and Output:Meter*
. But for
Output:Table
results, you have to be familiar with the structure of the
EnergyPlus SQL results, especially for table "TabularDataWithStrings". For
details, please see "2.20 eplusout.sql", especially "2.20.4.4 TabularData
Table" in EnergyPlus "Output Details and Examples" documentation. An
object in Output:SQLite
with Option Type
value of SimpleAndTabular
will
be automatically created if it does not exists, to ensure that the output
collection functionality works successfully.
In order to make sure .rdd
(Report Data Dictionary) and .mdd
(Meter Data
Dictionary) files are created during simulation, an object in
Output:VariableDictionary
class with Key Field
value being IDF
will be
automatically created if it does not exists.
ParametricJob class for EnergyPlus parametric simulations.
param_job()
for creating an EnergyPlus parametric job.
new()
Create an EplusJob
object
EplusJob$new(idf, epw)
\dontrun{
if (is_avail_eplus("8.8")) {
name_idf <- "1ZoneUncontrolled.idf"
name_epw <- "USA_CA_San.Francisco.Intl.AP.724940_TMY3.epw"
path_idf <- path_eplus_example("8.8", name_idf)
path_epw <- path_eplus_weather("8.8", name_epw)
# create from local files
job <- eplus_job(path_idf, path_epw)
# create from an Idf and an Epw object
job <- eplus_job(read_idf(path_idf), read_epw(path_epw))
}
}
path()
Get the paths of file that current EpwSql
uses
EplusJob$path(type = c("all", "idf", "epw"))
run()
Run simulation
EplusJob$run(
epw,
dir = NULL,
wait = TRUE,
force = FALSE,
echo = wait,
copy_external = FALSE,
readvars = TRUE
)
epw
A path to an .epw
file or an Epw object. epw
can
also be NULL
which will force design-day-only simulation.
Note this needs EnergyPlus v8.3 and later, and at least one
Sizing:DesignDay
object exists in the Idf
. If not given,
the epw
input used when creating this EplusJob
object will
be used.
dir
The directory to save the simulation results. If NULL
,
the input idf
folder will be used. Default: NULL
.
wait
If TRUE
, R will hang on and wait for the simulation to
complete. EnergyPlus standard output (stdout) and error
(stderr) is printed to R console. If FALSE
, simulation will
be run in a background process. Default: TRUE
.
force
Only applicable when the last job runs with wait
equals to FALSE
and is still running. If TRUE
, current
running job is forced to stop and a new one will start.
Default: FALSE
.
echo
Only applicable when wait
is TRUE
. Whether to show
standard output and error from EnergyPlus. Default: same as
wait
.
copy_external
If TRUE
, the external files that current Idf
object depends on will also be copied into the simulation
output directory. The values of file paths in the Idf will be
changed automatically. This ensures that the output directory
will have all files needed for the model to run. Default is
FALSE
.
readvars
If TRUE
, the ReadVarESO
post-processor will run
to generate CSV files from the ESO output. Since those CSV
files are never used when extracting simulation data in eplusr,
setting it to FALSE
can speed up the simulation if there are
hundreds of output variables or meters. Default: TRUE
.
$run()
runs the simulation using input IDF and EPW file. If wait
is FALSE
, the job is run in the background. You can get updated job
status by just
printing
the EplusJob
object.
Parameter epw
can be used to reset the EPW file to use for
simulation. If not given, the epw
input used when creating
this EplusJob
object will be used.
\dontrun{
# only run design day
job$run(NULL)
# specify output directory
job$run(dir = tempdir())
# run in the background
job$run(wait = TRUE)
# see job status
job$status()
# force to kill background job before running the new one
job$run(force = TRUE)
# do not show anything in the console
job$run(echo = FALSE)
# copy external files used in the model to simulation output directory
job$run(copy_external = TRUE)
# run simulation without generating CSV files from ESO output
job$run(epw, dir = tempdir(), readvars = FALSE)
}
kill()
Kill current running job
status()
Get the job status
$status()
returns a named list of values that indicates the status of the
job:
run_before
: TRUE
if the job has been run before. FALSE
otherwise.
alive
: TRUE
if the simulation is still running in the background.
FALSE
otherwise.
terminated
: TRUE
if the simulation was terminated during last
simulation. FALSE
otherwise. NA
if the job has not been run yet.
successful
: TRUE
if last simulation ended successfully. FALSE
otherwise. NA
if the job has not been run yet.
changed_after
: TRUE
if the IDF file has been changed since last
simulation. FALSE
otherwise. NA
if the job has not been run yet.
errors()
Read simulation errors
$errors() returns an ErrFile object which contains all
contents of the simulation error file (.err
). If info
is FALSE
,
only warnings and errors are printed.
An ErrFile object.
list_files()
List all output files in current simulation
simplify
If TRUE
, a character vector of EnergyPlus input
and output file names in the output directory is given. If FALSE
, a
full named list of all possible input and output types is given. NA
is returned if no input or output files are found for that type.
Default: FALSE
.
full
If TRUE
, the full file paths in the output directory
are returned. Otherwise, only the file names are returned. Default:
FALSE
.
$list_files()
returns all input and output files for current
EnergyPlus simulation.
Description of all possible outputs from EnergyPlus can be found in EnergyPlus documentation "Output Details and Examples".
Below gives a brief summary on the meaning of elements in the returned list.
# | Element | Description |
1 | ads | EnergyPlus AirflowNetwork related output |
2 | audit | EnergyPlus inputs echo |
3 | bnd | EnergyPlus branch node details |
4 | bsmt_audit | Basement input Echo |
5 | bsmt_csv | Basement CSV output |
6 | bsmt_idf | Basement IDF output |
7 | bsmt_out | Basement Output |
8 | cbor | Energyplus CBOR binary output introduced since v9.5 |
9 | dbg | Energyplus debug output |
10 | delight | EnergyPlus DElight simulation inputs and outputs |
11 | dfs | EnergyPlus daylighting factor for exterior windows |
12 | dxf | EnergyPlus surface drawing output |
13 | edd | EnergyPlus EMS report |
14 | eio | EnergyPlus standard and optional reports |
15 | end | EnergyPlus simulation status in one line |
16 | epjson | EnergyPlus epJSON input converted from IDF |
17 | epmdet | EPMacro inputs echo |
18 | epmidf | EPMacro IDF output |
19 | epw | EnergyPlus Weather File input |
20 | err | EnergyPlus error summary |
21 | eso | EnergyPlus standard output |
22 | experr | ExpandObjects error summary |
23 | expidf | ExpandObjects IDF output |
24 | glhe | EnergyPlus ground heat exchange file |
25 | idf | EnergyPlus IDF input |
26 | imf | EPMacro IMF input |
27 | iperr | convertESOMTR error summary |
28 | ipeso | convertESOMTR standard output in IP units |
29 | ipmtr | convertESOMTR meter output in IP units |
30 | json | EnergyPlus JSON time series output introduced since v9.5 |
31 | log | EnergyPlus log output |
32 | map | EnergyPlus daylighting intensity map output |
33 | mdd | EnergyPlus meter list |
34 | meter | EnergyPlus meter CSV output |
35 | msgpack | EnergyPlus MessagePack binary output introduced since v9.5 |
36 | mtd | EnergyPlus meter details |
37 | mtr | EnergyPlus meter output |
38 | perflog | EnergyPlus log for `PerformancePrecisionTradeoffs |
39 | rdd | EnergyPlus report variable names |
40 | rvaudit | ReadVarsESO input echo |
41 | sci | EnergyPlus cost benefit calculation information |
42 | screen | EnergyPlus window screen transmittance map output |
43 | shading | EnergyPlus surface shading CSV output |
44 | shd | EnergyPlus surface shading combination report |
45 | slab_ger | Slab error summary |
46 | slab_gtp | Slab ground temperature output |
47 | slab_out | Slab IDF output |
48 | sln | EnergyPlus Output:Surfaces:List, Lines output |
49 | sqlite | EnergyPlus SQLite output |
50 | sqlite_err | EnergyPlus SQLite error summary |
51 | ssz | EnergyPlus system sizing outputs in CSV, TAB or TXT format |
52 | svg | HVAC-Diagram HVAC diagram output |
53 | table | EnergyPlus tabular outputs in CSV, TAB, TXT, HTM, or XML format |
54 | variable | EnergyPlus report variable CSV output |
55 | wrl | EnergyPlus Output:Surfaces:List, VRML output |
56 | zsz | EnergyPlus system sizing outputs in CSV, TAB or TXT format |
57 | resource | External file resources used for the simulation, e.g. Schedule:File |
\dontrun{
# list all files in the output directory
job$list_files(simplify = TRUE)
# get a full list of all possible inputs and outputs even though they
# may not exist for current simulation
job$list_files()
# return the full paths instead of just file names
job$locate_output(full = TRUE)
}
locate_output()
Get path of output file
read_rdd()
Read Report Data Dictionary (RDD) file
$read_rdd()
return the core data of Report Data Dictionary (RDD)
file. For details, please see read_rdd()
.
An RddFile object.
read_mdd()
Read Report Data Dictionary (RDD) file
$read_mdd()
return the core data of Meter Data Dictionary (MDD)
file. For details, please see read_mdd()
.
An MddFile object.
read_table()
Read a single table from EnergyPlus SQL output
$read_table()
takes a valid table name
of those from
$list_table()
and returns that table data in a data.table::data.table()
format.
report_data_dict()
Read report data dictionary from EnergyPlus SQL output
$report_data_dict()
returns a data.table::data.table()
which
contains all information about report data.
For details on the meaning of each columns, please see "2.20.2.1 ReportDataDictionary Table" in EnergyPlus "Output Details and Examples" documentation.
A data.table::data.table()
of 10 columns:
report_data_dictionary_index
: The integer used to link the
dictionary data to the variable data. Mainly useful when joining
different tables
is_meter
: Whether report data is a meter data. Possible values:
0
and 1
timestep_type
: Type of data timestep. Possible values: Zone
and
HVAC System
key_value
: Key name of the data
name
: Actual report data name
reporting_frequency
: Data reporting frequency
schedule_name
: Name the the schedule that controls reporting
frequency.
units
: The data units
report_data()
Read report data
EplusJob$report_data(
key_value = NULL,
name = NULL,
year = NULL,
tz = "UTC",
case = "auto",
all = FALSE,
wide = FALSE,
period = NULL,
month = NULL,
day = NULL,
hour = NULL,
minute = NULL,
interval = NULL,
simulation_days = NULL,
day_type = NULL,
environment_name = NULL
)
key_value
A character vector to identify key values of the
data. If NULL
, all keys of that variable will be returned.
key_value
can also be data.frame that contains key_value
and name
columns. In this case, name
argument in
$report_data()
is ignored. All available key_value
for
current simulation output can be obtained using
$report_data_dict()
.
Default: NULL
.
name
A character vector to identify names of the data. If
NULL
, all names of that variable will be returned. If
key_value
is a data.frame, name
is ignored. All available
name
for current simulation output can be obtained using
$report_data_dict()
.
Default: NULL
.
year
Year of the date time in column datetime
. If NULL
, it
will calculate a year value that meets the start day of week
restriction for each environment. Default: NULL
.
tz
Time zone of date time in column datetime
. Default:
"UTC"
.
case
If not NULL
, a character column will be added indicates
the case of this simulation. If "auto"
, the name of the IDF
file without extension is used.
all
If TRUE
, extra columns are also included in the returned
data.table::data.table()
.
wide
If TRUE
, the output is formatted in the same way as
standard EnergyPlus csv output file.
period
A Date or POSIXt vector used to specify which time
period to return. The year value does not matter and only
month, day, hour and minute value will be used when
subsetting. If NULL
, all time period of data is returned.
Default: NULL
.
month, day, hour, minute
Each is an integer vector for month,
day, hour, minute subsetting of datetime
column when
querying on the SQL database. If NULL
, no subsetting is
performed on those components. All possible month
, day
,
hour
and minute
can be obtained using
$read_table("Time")
.
Default: NULL
.
interval
An integer vector used to specify which interval
length of report to extract. If NULL
, all interval will be
used. Default: NULL
.
simulation_days
An integer vector to specify which simulation
day data to extract. Note that this number resets after warmup
and at the beginning of an environment period. All possible
simulation_days
can be obtained using
$read_table("Time")
.
If NULL
, all simulation days will be used. Default: NULL
.
day_type
A character vector to specify which day type of data
to extract. All possible day types are: Sunday
, Monday
,
Tuesday
, Wednesday
, Thursday
, Friday
, Saturday
,
Holiday
, SummerDesignDay
, WinterDesignDay
, CustomDay1
,
and CustomDay2
. All possible values for current simulation
output can be obtained using
$read_table("Time")
.
environment_name
A character vector to specify which
environment data to extract. If NULL
, all environment data
are returned. Default: NULL
. All possible
environment_name
for current simulation output can be
obtained using:
$report_data()
extracts the report data in a
data.table::data.table()
using key values, variable names and other
specifications.
$report_data()
can also directly take all or subset output from
$report_data_dict()
as input, and extract all data specified.
The returned column numbers varies depending on all
argument.
all
is FALSE
, the returned data.table::data.table()
has 6 columns:
case
: Simulation case specified using case
argument
datetime
: The date time of simulation result
key_value
: Key name of the data
name
: Actual report data name
units
: The data units
value
: The data value
all
is TRUE
, besides columns described above, extra columns are also
included:
month
: The month of reported date time
day
: The day of month of reported date time
hour
: The hour of reported date time
minute
: The minute of reported date time
dst
: Daylight saving time indicator. Possible values: 0
and 1
interval
: Length of reporting interval
simulation_days
: Day of simulation
day_type
: The type of day, e.g. Monday
, Tuesday
and etc.
environment_period_index
: The indices of environment.
environment_name
: A text string identifying the environment.
is_meter
: Whether report data is a meter data. Possible values: 0
and
1
type
: Nature of data type with respect to state. Possible values: Sum
and Avg
index_group
: The report group, e.g. Zone
, System
timestep_type
: Type of data timestep. Possible values: Zone
and HVAC System
reporting_frequency
: The reporting frequency of the variable, e.g.
HVAC System Timestep
, Zone Timestep
.
schedule_name
: Name of the the schedule that controls reporting
frequency.
With the datetime
column, it is quite straightforward to apply time-series
analysis on the simulation output. However, another painful thing is that
every simulation run period has its own Day of Week for Start Day
. Randomly
setting the year
may result in a date time series that does not have
the same start day of week as specified in the RunPeriod objects.
eplusr provides a simple solution for this. By setting year
to NULL
,
which is the default behavior, eplusr will calculate a year value (from
year 2017 backwards) for each run period that compliances with the start
day of week restriction.
It is worth noting that EnergyPlus uses 24-hour clock system where 24 is only used to denote midnight at the end of a calendar day. In EnergyPlus output, "00:24:00" with a time interval being 15 mins represents a time period from "00:23:45" to "00:24:00", and similarly "00:15:00" represents a time period from "00:24:00" to "00:15:00" of the next day. This means that if current day is Friday, day of week rule applied in schedule time period "00:23:45" to "00:24:00" (presented as "00:24:00" in the output) is also Friday, but not Saturday. However, if you try to get the day of week of time "00:24:00" in R, you will get Saturday, but not Friday. This introduces inconsistency and may cause problems when doing data analysis considering day of week value.
With wide
equals TRUE
, $report_data()
will format the simulation output
in the same way as standard EnergyPlus csv output file. Sometimes this can be
useful as there may be existing tools/workflows that depend on this format.
When both wide
and all
are TRUE
, columns of runperiod environment names
and date time components are also returned, including:
environment_period_index", "environment_name
, simulation_days
,
datetime
, month
, day
, hour
, minute
, day_type
.
For convenience, input character arguments matching in
$report_data()
are case-insensitive.
\dontrun{
# read all report data
job$report_data()
# specify output variables using report data dictionary
dict <- job$report_data_dict()
job$report_data(dict[units == "C"])
# specify output variables using 'key_value' and 'name'
job$report_data("environment", "site outdoor air drybulb temperature")
# explicitly specify year value and time zone
job$report_data(dict[1], year = 2020, tz = "Etc/GMT+8")
# explicitly specify case name
job$report_data(dict[1], case = "example")
# get all possible columns
job$report_data(dict[1], all = TRUE)
# return in a format that is similar as EnergyPlus CSV output
job$report_data(dict[1], wide = TRUE)
# return in a format that is similar as EnergyPlus CSV output with
# extra columns
job$report_data(dict[1], wide = TRUE, all = TRUE)
# only get data at the working hour on the first Monday
job$report_data(dict[1], hour = 8:18, day_type = "monday", simulation_days = 1:7)
# only get specified run period data
job$read_table("EnvironmentPeriods") # possible environment name
job$report_data(dict[1], environment_name = "San Francisco Intl Ap CA USA TMY3 WMO#=724940")
# can also be done using 'environment_period_index' column
job$report_data(dict[1], all = TRUE)[environment_period_index == 3L]
}
tabular_data()
Read tabular data
EplusJob$tabular_data(
report_name = NULL,
report_for = NULL,
table_name = NULL,
column_name = NULL,
row_name = NULL,
wide = FALSE,
string_value = !wide
)
report_name, report_for, table_name, column_name, row_name
Each is a character vector for subsetting when querying the SQL database. For the meaning of each argument, please see the description above.
wide
If TRUE
, each table will be converted into the similar
format as it is shown in EnergyPlus HTML output file. Default:
FALSE
.
string_value
Only applicable when wide
is TRUE
. If
string_value
is FALSE
, instead of keeping all values as
characters, values in possible numeric columns are converted
into numbers. Default: the opposite of wide
. Possible
numeric columns indicate column that:
columns that have associated units
columns that contents numbers
$tabular_data()
extracts the tabular data in a
data.table::data.table()
using report, table, column and row name
specifications. The returned data.table::data.table()
has
9 columns:
case
: Simulation case specified using case
argument
index
: Tabular data index
report_name
: The name of the report that the record belongs to
report_for
: The For
text that is associated with the record
table_name
: The name of the table that the record belongs to
column_name
: The name of the column that the record belongs to
row_name
: The name of the row that the record belongs to
units
: The units of the record
value
: The value of the record in string format by default
For convenience, input character arguments matching in
$tabular_data()
are case-insensitive.
A data.table::data.table()
with 8 columns (when wide
is
FALSE
) or a named list of data.table::data.table()
s where the
names are the combination of report_name
, report_for
and
table_name
.
\dontrun{
# read all tabular data
job$tabular_data()
# explicitly specify data you want
str(job$tabular_data(
report_name = "AnnualBuildingUtilityPerformanceSummary",
table_name = "Site and Source Energy",
column_name = "Total Energy",
row_name = "Total Site Energy"
))
# get tabular data in wide format and coerce numeric values
str(job$tabular_data(
report_name = "AnnualBuildingUtilityPerformanceSummary",
table_name = "Site and Source Energy",
column_name = "Total Energy",
row_name = "Total Site Energy",
wide = TRUE, string_value = FALSE
))
}
print()
Print EplusSql
object
$print()
shows the core information of this EplusJob
object,
including the path of model and weather, the version and path of
EnergyPlus used to run simulations, and the simulation job status.
$print()
is quite useful to get the simulation status, especially
when wait
is FALSE
in $run()
. The job status will be updated
and printed whenever $print()
is called.
## ------------------------------------------------
## Method `EplusJob$new`
## ------------------------------------------------
if (FALSE) { # \dontrun{
if (is_avail_eplus("8.8")) {
name_idf <- "1ZoneUncontrolled.idf"
name_epw <- "USA_CA_San.Francisco.Intl.AP.724940_TMY3.epw"
path_idf <- path_eplus_example("8.8", name_idf)
path_epw <- path_eplus_weather("8.8", name_epw)
# create from local files
job <- eplus_job(path_idf, path_epw)
# create from an Idf and an Epw object
job <- eplus_job(read_idf(path_idf), read_epw(path_epw))
}
} # }
## ------------------------------------------------
## Method `EplusJob$version`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$version()
} # }
## ------------------------------------------------
## Method `EplusJob$path`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$path()
job$path("idf")
job$path("epw")
} # }
## ------------------------------------------------
## Method `EplusJob$run`
## ------------------------------------------------
if (FALSE) { # \dontrun{
# only run design day
job$run(NULL)
# specify output directory
job$run(dir = tempdir())
# run in the background
job$run(wait = TRUE)
# see job status
job$status()
# force to kill background job before running the new one
job$run(force = TRUE)
# do not show anything in the console
job$run(echo = FALSE)
# copy external files used in the model to simulation output directory
job$run(copy_external = TRUE)
# run simulation without generating CSV files from ESO output
job$run(epw, dir = tempdir(), readvars = FALSE)
} # }
## ------------------------------------------------
## Method `EplusJob$kill`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$kill()
} # }
## ------------------------------------------------
## Method `EplusJob$status`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$status()
} # }
## ------------------------------------------------
## Method `EplusJob$errors`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$errors()
# show all information
job$errors(info = TRUE)
} # }
## ------------------------------------------------
## Method `EplusJob$output_dir`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$output_dir()
# Below will open output directory
# job$output_dir(open = TRUE)
} # }
## ------------------------------------------------
## Method `EplusJob$list_files`
## ------------------------------------------------
if (FALSE) { # \dontrun{
# list all files in the output directory
job$list_files(simplify = TRUE)
# get a full list of all possible inputs and outputs even though they
# may not exist for current simulation
job$list_files()
# return the full paths instead of just file names
job$locate_output(full = TRUE)
} # }
## ------------------------------------------------
## Method `EplusJob$locate_output`
## ------------------------------------------------
if (FALSE) { # \dontrun{
# get the file path of the error file
job$locate_output(".err", strict = FALSE)
# can use to detect if certain output file exists
job$locate_output(".expidf", strict = TRUE)
} # }
## ------------------------------------------------
## Method `EplusJob$read_rdd`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$read_rdd()
} # }
## ------------------------------------------------
## Method `EplusJob$read_mdd`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$read_mdd()
} # }
## ------------------------------------------------
## Method `EplusJob$list_table`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$list_table()
} # }
## ------------------------------------------------
## Method `EplusJob$read_table`
## ------------------------------------------------
if (FALSE) { # \dontrun{
# read a specific table
job$read_table("Zones")
} # }
## ------------------------------------------------
## Method `EplusJob$report_data_dict`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$report_data_dict()
} # }
## ------------------------------------------------
## Method `EplusJob$report_data`
## ------------------------------------------------
if (FALSE) { # \dontrun{
# read all report data
job$report_data()
# specify output variables using report data dictionary
dict <- job$report_data_dict()
job$report_data(dict[units == "C"])
# specify output variables using 'key_value' and 'name'
job$report_data("environment", "site outdoor air drybulb temperature")
# explicitly specify year value and time zone
job$report_data(dict[1], year = 2020, tz = "Etc/GMT+8")
# explicitly specify case name
job$report_data(dict[1], case = "example")
# get all possible columns
job$report_data(dict[1], all = TRUE)
# return in a format that is similar as EnergyPlus CSV output
job$report_data(dict[1], wide = TRUE)
# return in a format that is similar as EnergyPlus CSV output with
# extra columns
job$report_data(dict[1], wide = TRUE, all = TRUE)
# only get data at the working hour on the first Monday
job$report_data(dict[1], hour = 8:18, day_type = "monday", simulation_days = 1:7)
# only get specified run period data
job$read_table("EnvironmentPeriods") # possible environment name
job$report_data(dict[1], environment_name = "San Francisco Intl Ap CA USA TMY3 WMO#=724940")
# can also be done using 'environment_period_index' column
job$report_data(dict[1], all = TRUE)[environment_period_index == 3L]
} # }
## ------------------------------------------------
## Method `EplusJob$tabular_data`
## ------------------------------------------------
if (FALSE) { # \dontrun{
# read all tabular data
job$tabular_data()
# explicitly specify data you want
str(job$tabular_data(
report_name = "AnnualBuildingUtilityPerformanceSummary",
table_name = "Site and Source Energy",
column_name = "Total Energy",
row_name = "Total Site Energy"
))
# get tabular data in wide format and coerce numeric values
str(job$tabular_data(
report_name = "AnnualBuildingUtilityPerformanceSummary",
table_name = "Site and Source Energy",
column_name = "Total Energy",
row_name = "Total Site Energy",
wide = TRUE, string_value = FALSE
))
} # }
## ------------------------------------------------
## Method `EplusJob$print`
## ------------------------------------------------
if (FALSE) { # \dontrun{
job$print()
} # }