RxGen: R6 Class for generating a OFPE prescriptions or experimental...
In paulhegedus/OFPE: On-Farm Precision Experiments (OFPE) Data Management and Analysis Tools
RxGen R Documentation
R6 Class for generating a OFPE prescriptions or experimental prescriptions
Description
R6 class for for creating a prescription or experimental prescription
for a field of interest. The user can create a prescription or experimental
prescription based on the optimized rates from the user selected management
scenario for given economic and weather conditions. This process builds off of
the simulation R6 class (SimClass), where the Monte Carlo simulation for a year
or year(s) the user thinks the upcoming year is going to resemble, with the user
specified economic data, is used for identifying the optimum rates for each
management strategy at each part.
If the user decides to do an experimental prescription, the optimum rates of the
user specified management scenario from the simulation is used as the base map
for the experimental prescription. Experimental rates can be generated from gaps
in the optimum rates to create a distribution of rates across the field to be used
for fitting crop response models in upcoming years, or from user specified
experimental rates. These are then randomly applied to the field
according to user specified proportions for each rate, stratified on the
optimum rates.
If the user decides to make an OFPE prescription with no experiment, the
optimum rates for each point for the user specified management scenario is
taken as the prescription. Instead of applying experimental rates, a farmer
selected rate representing the rate they would have applied is randomly
placed across the field, stratified on the optimum rates. These are used
as a check to evaluate the performance of the optimized rates or whether
further experimentation is needed.
When creating an experimental prescription or a prescription, the user must pass
an set up SimClass. This implies that the user has initialized and set up
the required DatClass, ModClass, and EconDat R6 objects. The user must pass a
SimClass object that has been executed. This simulation output data is used to select
the years that the farmer thinks the upcoming year will resemble and generate
the experimental prescriptions and the prescriptions.
This class follows the generator interface that includes an initialization method
and an 'executeOutput' method.
Public fields
dbConDatabase connection object connected to an OFPE formatted
database, see DBCon class.
simClassIf the user is creating an experimental prescription or
prescription an R6 class SimClass object must be supplied. This has to be
set up, however does not need to have the execution method performed.
The RxClass will check the SimClass for simulation output data that matches
the year of the data provided, and execute simulations for any years not
present.
mgmt_scenIf the user is creating a prescription or experimental
prescription, they must provide the management scenario to use for their
prescription. The user can choose from the management options listed in
the SimClass. The options are 'SSOPT': site-specific optimized rates,
'FFOPT': full-field optimum uniform rate, 'FS': farmer selected uniform
rate, 'Min': applying the least intensive input rates (i.e. 0 lbs N/ac, or
25 lbs seed/ac), 'Opp' is omitted because this strategy is the least intensive
input rate in conventional system types, and the farmer selected rate for
organic systems, both of which are already provided.
trt_lengthLength, in meters, for which to apply treatments.
trt_widthWidth, in meters, for which to apply treatments.
headingNumeric, heading in degrees from true north to rotate the
experiment/prescription to. Default is 0 (no rotation). Note that if a
heading is provided, the grid is trimmed based on the buffered boundary but
rotation caused by providing a heading may skew treatment rates so that
they encroach into the cleanup strip.
expvarExperimental variable to optimize, select/input
'As-Applied Nitrogen' or 'As-Applied Seed Rate'. This is the type of
input that is experimentally varied across the field as part of the
on-farm experimentation.
convThe conversion factor between lbs of the input to the
units of the as-applied input (i.e. lbs N/ac to unit input/ac)
base_rateThe rate to apply between the experimental rates
and the field edge, or as check rates in the prescription selected
option.
rx_yearsThe year or vector of years to base the prescription
off of. If the user passes in multiple years, the average optimum rate
from the simulations will be used. If the user has passed in a SimClass
object where the simulation has been executed, the RxClass will check the
output data to avoid redundantly running a simulation.
rx_for_yearProvide the year that the prescription or experiment
is made for. Used for labeling outputs.
out_pathProvide the path to the folder in which to store and
save figures and the prescription Type NA to not create any folders.
You will not be able to save any outputs. (Note, even if a path is provided,
the user can pass FALSE as the sole argument to the 'setupOP' method
to prevent the creation of folders. This will automatically prevent
any plots to be saved.). If not applied and a SimClass object has
been supplied, the selected option in that class will be used.
SAVELogical, whether to save figures and the prescription.
Autofilled to FALSE if a user selects NA in the 'out_path' or is NULL.
Autofilled to TRUE otherwise. If not applied and a SimClass object has
been supplied, the selected option in that class will be used.
opt_rate_lengthProvide the number of oprimum rates to use.
This applies to prescriptions and experimental prescriptions. This
represents the equipment constraints of the farmer. In the case of the
experimental prescription, this number of rates does not include the
number of experimental rates, so take your selections for
the management scenario and number of experimental rates into account.
fld_propThe percent of available cells to
apply check rates to (i.e. 0.05, 0.1).
exp_rate_genLogical, for the experimental prescription provide
TRUE or FALSE for whether to create experimentla rates from gaps in the
optimized rates. These experimental rates are placed between optimum rates
to establish a range of rates for which to improve model predictions in future
years.
exp_rate_lengthProvide the length of experimental rates to apply.
This applies to new experiments and experimental prescriptions. This
represents the equipment constraints of the farmer. In the case of the
experimental prescription, this number of rates does not include the
number of rates for the optimized base map, so take your selections for
the management scenario and number of optimum rates into account.
exp_ratesProvide a vector of experimental rates equal to the
number of experimental rates provided in 'exp_rate_length'. This is
required for all new experiments, however can be left to null for
experimental prescriptions if experimental rates should be generated
based on gaps in optimum rates.
exp_rates_propProvide proportions (0 - 1) for the length
of experimental rates provided in 'exp_rate_length'. This is required
for all new experiments and experimental prescriptions.
buffer_widthThe width of the buffer from the field edge within which
to place experiments or prescriptions. Provided by the user in feet and
converted to meters internally.
min_rate_jumpsOptional, supply either 'N/S' or 'E/W' to indicate
direction in which to minimize rate jumps. This is the predominant direction
that the experimental input is applied across the field. This function minimizes
the difference in rates between adjacent treatments for easier use on the
equipment. Note that this will eradicate any randomization/optimization of
rates and will partially or completely remove stratification. This function makes
sure that the rates do not vary by more than 2 rate levels in the direction
specified. Default is NULL, which prevents execution. This will not guarantee
eradication of all rate jumps, but will reduce the amount.
unique_fieldnameUnique fieldname for the field(s) used for the experiment. This
concatenates multiple fields with an ampersand. Used for labelling.
rx_dtData frame that contains the coordinates of locations to apply
experimental inputs. For an experiment, these are the centroids of the grid
made to aggregate data for the field.
RXTable containing the geographic locations of the experiment. Also
contains the rates in the experimental and as-applied units. This can be
saved as a shapefile and given to the equipment applying the input.
out_nameCreated parameter for the file name of the prescription data,
used for saving the data to the 'Outputs' folder.
out_map_nameCreated parameter with the file name for the map of the
prescription. Used for saving the map to the 'Outputs' folder.
cell_out_map_nameCreated parameter with the file name for the map of the
rate type applied to each cell. Used for saving the map to the 'Outputs' folder.
varThe label of the variable to map. Used in figure labelling for plotting
in RxClass.
var_col_nameThe name of the column of the variable in the
supplied data ('dat'). Used in figure labelling for plotting
in RxClass.
var_labelThe label to be applied to the legend of the map
corresponding to the variable mapped. Used in figure labelling for plotting
in RxClass.
var_main_labelThe main label to apply to the map. Used in figure
labelling for plotting in RxClass.
sizeThe size of the treatment zones, which is the treatment width x
the treatment length.
Methods
Public methods
Method new()
It is recommended to initialize this class through the RxClass,
because it is integrated into the OFPE workflow. This also ensures all of the
inputs are in the correct format and present.
Usage
RxGen$new(
dbCon,
simClass = NULL,
mgmt_scen,
trt_length,
trt_width,
heading = 0,
expvar,
conv,
base_rate,
rx_years,
rx_for_year,
out_path = NULL,
SAVE,
opt_rate_length,
fld_prop,
buffer_width = 0,
min_rate_jumps = NULL,
exp_rate_gen = NULL,
exp_rate_length = NULL,
exp_rates = NULL,
exp_rates_prop = NULL
)
Arguments
dbConDatabase connection object connected to an OFPE formatted
database, see DBCon class.
simClassIf the user is creating an experimental prescription or
prescription an R6 class SimClass object must be supplied. This class is
queried for relevant information, most importantly, a path the the output
data.
mgmt_scenIf the user is creating a prescription or experimental
prescription, they must provide the management scenario to use for their
prescription. The user can choose from the management options listed in
the SimClass. The options are 'SSOPT': site-specific optimized rates,
'FFOPT': full-field optimum uniform rate, 'FS': farmer selected uniform
rate, 'Min': applying the least intensive input rates (i.e. 0 lbs N/ac, or
25 lbs seed/ac), 'Opp' is omitted because this strategy is the least intensive
input rate in conventional system types, and the farmer selected rate for
organic systems, both of which are already provided.
trt_lengthLength, in meters, for which to apply treatments.
trt_widthWidth, in meters, for which to apply treatments.
headingNumeric, heading in degrees from true north to rotate the
experiment/prescription to. Default is 0 (no rotation). Note that if a
heading is provided, the grid is trimmed based on the buffered boundary but
rotation caused by providing a heading may skew treatment rates so that
they encroach into the cleanup strip.
expvarExperimental variable to optimize, select/input
'As-Applied Nitrogen' or 'As-Applied Seed Rate'. This is the type of
input that is experimentally varied across the field as part of the
on-farm experimentation.
convThe conversion factor between lbs of the input to the
units of the as-applied input (i.e. lbs N/ac to unit input/ac)
base_rateThe rate to apply between the experimental rates
and the field edge, or as check rates in the prescription selected
option.
rx_yearsThe year or vector of years to base the prescription
off of. If the user passes in multiple years, the average optimum rate
from the simulations will be used. If the user has passed in a SimClass
object where the simulation has been executed, the RxClass will check the
output data to avoid redundantly running a simulation.
rx_for_yearProvide the year that the prescription or experiment
is made for. Used for labeling outputs.
out_pathProvide the path to the folder in which to store and
save figures and the prescription Type NA to not create any folders.
You will not be able to save any outputs. (Note, even if a path is provided,
the user can pass FALSE as the sole argument to the 'setupOP' method
to prevent the creation of folders. This will automatically prevent
any plots to be saved.). If not applied and a SimClass object has
been supplied, the selected option in that class will be used.
SAVELogical, whether to save figures and the prescription.
Autofilled to FALSE if a user selects NA in the 'out_path' or is NULL.
Autofilled to TRUE otherwise. If not applied and a SimClass object has
been supplied, the selected option in that class will be used.
opt_rate_lengthProvide the number of oprimum rates to use.
This applies to prescriptions and experimental prescriptions. This
represents the equipment constraints of the farmer. In the case of the
experimental prescription, this number of rates does not include the
number of experimental rates, so take your selections for
the management scenario and number of experimental rates into account.
fld_propThe percent of available cells to
apply check rates to (i.e. 0.05, 0.1).
buffer_widthThe width of the buffer from field edge for
experiments or prescriptions (feet).
min_rate_jumpsOptional, supply either 'N/S' or 'E/W' to indicate
direction in which to minimize rate jumps. This is the predominant direction
that the experimental input is applied across the field. This function minimizes
the difference in rates between adjacent treatments for easier use on the
equipment. Note that this will eradicate any randomization/optimization of
rates and will partially or completely remove stratification. This function makes
sure that the rates do not vary by more than 2 rate levels in the direction
specified. Default is NULL, which prevents execution. This will not guarantee
eradication of all rate jumps, but will reduce the amount.
exp_rate_genLogical, for the experimental prescription provide
TRUE or FALSE for whether to create experimentla rates from gaps in the
optimized rates. These experimental rates are placed between optimum rates
to establish a range of rates for which to improve model predictions in future
years. Not needed if pure prescription.
exp_rate_lengthProvide the length of experimental rates to apply.
This applies to new experiments and experimental prescriptions. This
represents the equipment constraints of the farmer. In the case of the
experimental prescription, this number of rates does not include the
number of rates for the optimized base map, so take your selections for
the management scenario and number of optimum rates into account.
Not needed if pure prescription.
exp_ratesProvide a vector of experimental rates equal to the
number of experimental rates provided in 'exp_rate_length'. This is
required for all new experiments, however can be left to null for
experimental prescriptions if experimental rates should be generated
based on gaps in optimum rates. Not needed if pure prescription.
exp_rates_propProvide proportions (0 - 1) for the length
of experimental rates provided in 'exp_rate_length'. This is required
for all new experiments and experimental prescriptions. Not needed if
pure prescription.
Returns
An initialized RxGen R6 class object.
Method executeOutput()
Method for calling the execution method of the experiment
generator. This applies the prescription/experimental rates across
the field. Check rates are stratified across prescription/experimental
rates for representative checks.
Usage
RxGen$executeOutput()
Arguments
NoneAll parameters supplied upon initialization.
Returns
A completed experiment table containing the output.
Method clone()
The objects of this class are cloneable with this method.
Usage
RxGen$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
See Also
DBCon for the database connection class,
SimClass for the class that contains simulation outputs, and
ExpGen for the alternative class that creates new experiments.
paulhegedus/OFPE documentation built on Nov. 23, 2022, 5:09 a.m.
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| RxGen | R Documentation |
R6 Class for generating a OFPE prescriptions or experimental prescriptions
Description
R6 class for for creating a prescription or experimental prescription for a field of interest. The user can create a prescription or experimental prescription based on the optimized rates from the user selected management scenario for given economic and weather conditions. This process builds off of the simulation R6 class (SimClass), where the Monte Carlo simulation for a year or year(s) the user thinks the upcoming year is going to resemble, with the user specified economic data, is used for identifying the optimum rates for each management strategy at each part.
If the user decides to do an experimental prescription, the optimum rates of the user specified management scenario from the simulation is used as the base map for the experimental prescription. Experimental rates can be generated from gaps in the optimum rates to create a distribution of rates across the field to be used for fitting crop response models in upcoming years, or from user specified experimental rates. These are then randomly applied to the field according to user specified proportions for each rate, stratified on the optimum rates.
If the user decides to make an OFPE prescription with no experiment, the optimum rates for each point for the user specified management scenario is taken as the prescription. Instead of applying experimental rates, a farmer selected rate representing the rate they would have applied is randomly placed across the field, stratified on the optimum rates. These are used as a check to evaluate the performance of the optimized rates or whether further experimentation is needed.
When creating an experimental prescription or a prescription, the user must pass an set up SimClass. This implies that the user has initialized and set up the required DatClass, ModClass, and EconDat R6 objects. The user must pass a SimClass object that has been executed. This simulation output data is used to select the years that the farmer thinks the upcoming year will resemble and generate the experimental prescriptions and the prescriptions.
This class follows the generator interface that includes an initialization method and an 'executeOutput' method.
Public fields
dbConDatabase connection object connected to an OFPE formatted database, see DBCon class.
simClassIf the user is creating an experimental prescription or prescription an R6 class SimClass object must be supplied. This has to be set up, however does not need to have the execution method performed. The RxClass will check the SimClass for simulation output data that matches the year of the data provided, and execute simulations for any years not present.
mgmt_scenIf the user is creating a prescription or experimental prescription, they must provide the management scenario to use for their prescription. The user can choose from the management options listed in the SimClass. The options are 'SSOPT': site-specific optimized rates, 'FFOPT': full-field optimum uniform rate, 'FS': farmer selected uniform rate, 'Min': applying the least intensive input rates (i.e. 0 lbs N/ac, or 25 lbs seed/ac), 'Opp' is omitted because this strategy is the least intensive input rate in conventional system types, and the farmer selected rate for organic systems, both of which are already provided.
trt_lengthLength, in meters, for which to apply treatments.
trt_widthWidth, in meters, for which to apply treatments.
headingNumeric, heading in degrees from true north to rotate the experiment/prescription to. Default is 0 (no rotation). Note that if a heading is provided, the grid is trimmed based on the buffered boundary but rotation caused by providing a heading may skew treatment rates so that they encroach into the cleanup strip.
expvarExperimental variable to optimize, select/input 'As-Applied Nitrogen' or 'As-Applied Seed Rate'. This is the type of input that is experimentally varied across the field as part of the on-farm experimentation.
convThe conversion factor between lbs of the input to the units of the as-applied input (i.e. lbs N/ac to unit input/ac)
base_rateThe rate to apply between the experimental rates and the field edge, or as check rates in the prescription selected option.
rx_yearsThe year or vector of years to base the prescription off of. If the user passes in multiple years, the average optimum rate from the simulations will be used. If the user has passed in a SimClass object where the simulation has been executed, the RxClass will check the output data to avoid redundantly running a simulation.
rx_for_yearProvide the year that the prescription or experiment is made for. Used for labeling outputs.
out_pathProvide the path to the folder in which to store and save figures and the prescription Type NA to not create any folders. You will not be able to save any outputs. (Note, even if a path is provided, the user can pass FALSE as the sole argument to the 'setupOP' method to prevent the creation of folders. This will automatically prevent any plots to be saved.). If not applied and a SimClass object has been supplied, the selected option in that class will be used.
SAVELogical, whether to save figures and the prescription. Autofilled to FALSE if a user selects NA in the 'out_path' or is NULL. Autofilled to TRUE otherwise. If not applied and a SimClass object has been supplied, the selected option in that class will be used.
opt_rate_lengthProvide the number of oprimum rates to use. This applies to prescriptions and experimental prescriptions. This represents the equipment constraints of the farmer. In the case of the experimental prescription, this number of rates does not include the number of experimental rates, so take your selections for the management scenario and number of experimental rates into account.
fld_propThe percent of available cells to apply check rates to (i.e. 0.05, 0.1).
exp_rate_genLogical, for the experimental prescription provide TRUE or FALSE for whether to create experimentla rates from gaps in the optimized rates. These experimental rates are placed between optimum rates to establish a range of rates for which to improve model predictions in future years.
exp_rate_lengthProvide the length of experimental rates to apply. This applies to new experiments and experimental prescriptions. This represents the equipment constraints of the farmer. In the case of the experimental prescription, this number of rates does not include the number of rates for the optimized base map, so take your selections for the management scenario and number of optimum rates into account.
exp_ratesProvide a vector of experimental rates equal to the number of experimental rates provided in 'exp_rate_length'. This is required for all new experiments, however can be left to null for experimental prescriptions if experimental rates should be generated based on gaps in optimum rates.
exp_rates_propProvide proportions (0 - 1) for the length of experimental rates provided in 'exp_rate_length'. This is required for all new experiments and experimental prescriptions.
buffer_widthThe width of the buffer from the field edge within which to place experiments or prescriptions. Provided by the user in feet and converted to meters internally.
min_rate_jumpsOptional, supply either 'N/S' or 'E/W' to indicate direction in which to minimize rate jumps. This is the predominant direction that the experimental input is applied across the field. This function minimizes the difference in rates between adjacent treatments for easier use on the equipment. Note that this will eradicate any randomization/optimization of rates and will partially or completely remove stratification. This function makes sure that the rates do not vary by more than 2 rate levels in the direction specified. Default is NULL, which prevents execution. This will not guarantee eradication of all rate jumps, but will reduce the amount.
unique_fieldnameUnique fieldname for the field(s) used for the experiment. This concatenates multiple fields with an ampersand. Used for labelling.
rx_dtData frame that contains the coordinates of locations to apply experimental inputs. For an experiment, these are the centroids of the grid made to aggregate data for the field.
RXTable containing the geographic locations of the experiment. Also contains the rates in the experimental and as-applied units. This can be saved as a shapefile and given to the equipment applying the input.
out_nameCreated parameter for the file name of the prescription data, used for saving the data to the 'Outputs' folder.
out_map_nameCreated parameter with the file name for the map of the prescription. Used for saving the map to the 'Outputs' folder.
cell_out_map_nameCreated parameter with the file name for the map of the rate type applied to each cell. Used for saving the map to the 'Outputs' folder.
varThe label of the variable to map. Used in figure labelling for plotting in RxClass.
var_col_nameThe name of the column of the variable in the supplied data ('dat'). Used in figure labelling for plotting in RxClass.
var_labelThe label to be applied to the legend of the map corresponding to the variable mapped. Used in figure labelling for plotting in RxClass.
var_main_labelThe main label to apply to the map. Used in figure labelling for plotting in RxClass.
sizeThe size of the treatment zones, which is the treatment width x the treatment length.
Methods
Public methods
Method new()
It is recommended to initialize this class through the RxClass, because it is integrated into the OFPE workflow. This also ensures all of the inputs are in the correct format and present.
Usage
RxGen$new( dbCon, simClass = NULL, mgmt_scen, trt_length, trt_width, heading = 0, expvar, conv, base_rate, rx_years, rx_for_year, out_path = NULL, SAVE, opt_rate_length, fld_prop, buffer_width = 0, min_rate_jumps = NULL, exp_rate_gen = NULL, exp_rate_length = NULL, exp_rates = NULL, exp_rates_prop = NULL )
Arguments
dbConDatabase connection object connected to an OFPE formatted database, see DBCon class.
simClassIf the user is creating an experimental prescription or prescription an R6 class SimClass object must be supplied. This class is queried for relevant information, most importantly, a path the the output data.
mgmt_scenIf the user is creating a prescription or experimental prescription, they must provide the management scenario to use for their prescription. The user can choose from the management options listed in the SimClass. The options are 'SSOPT': site-specific optimized rates, 'FFOPT': full-field optimum uniform rate, 'FS': farmer selected uniform rate, 'Min': applying the least intensive input rates (i.e. 0 lbs N/ac, or 25 lbs seed/ac), 'Opp' is omitted because this strategy is the least intensive input rate in conventional system types, and the farmer selected rate for organic systems, both of which are already provided.
trt_lengthLength, in meters, for which to apply treatments.
trt_widthWidth, in meters, for which to apply treatments.
headingNumeric, heading in degrees from true north to rotate the experiment/prescription to. Default is 0 (no rotation). Note that if a heading is provided, the grid is trimmed based on the buffered boundary but rotation caused by providing a heading may skew treatment rates so that they encroach into the cleanup strip.
expvarExperimental variable to optimize, select/input 'As-Applied Nitrogen' or 'As-Applied Seed Rate'. This is the type of input that is experimentally varied across the field as part of the on-farm experimentation.
convThe conversion factor between lbs of the input to the units of the as-applied input (i.e. lbs N/ac to unit input/ac)
base_rateThe rate to apply between the experimental rates and the field edge, or as check rates in the prescription selected option.
rx_yearsThe year or vector of years to base the prescription off of. If the user passes in multiple years, the average optimum rate from the simulations will be used. If the user has passed in a SimClass object where the simulation has been executed, the RxClass will check the output data to avoid redundantly running a simulation.
rx_for_yearProvide the year that the prescription or experiment is made for. Used for labeling outputs.
out_pathProvide the path to the folder in which to store and save figures and the prescription Type NA to not create any folders. You will not be able to save any outputs. (Note, even if a path is provided, the user can pass FALSE as the sole argument to the 'setupOP' method to prevent the creation of folders. This will automatically prevent any plots to be saved.). If not applied and a SimClass object has been supplied, the selected option in that class will be used.
SAVELogical, whether to save figures and the prescription. Autofilled to FALSE if a user selects NA in the 'out_path' or is NULL. Autofilled to TRUE otherwise. If not applied and a SimClass object has been supplied, the selected option in that class will be used.
opt_rate_lengthProvide the number of oprimum rates to use. This applies to prescriptions and experimental prescriptions. This represents the equipment constraints of the farmer. In the case of the experimental prescription, this number of rates does not include the number of experimental rates, so take your selections for the management scenario and number of experimental rates into account.
fld_propThe percent of available cells to apply check rates to (i.e. 0.05, 0.1).
buffer_widthThe width of the buffer from field edge for experiments or prescriptions (feet).
min_rate_jumpsOptional, supply either 'N/S' or 'E/W' to indicate direction in which to minimize rate jumps. This is the predominant direction that the experimental input is applied across the field. This function minimizes the difference in rates between adjacent treatments for easier use on the equipment. Note that this will eradicate any randomization/optimization of rates and will partially or completely remove stratification. This function makes sure that the rates do not vary by more than 2 rate levels in the direction specified. Default is NULL, which prevents execution. This will not guarantee eradication of all rate jumps, but will reduce the amount.
exp_rate_genLogical, for the experimental prescription provide TRUE or FALSE for whether to create experimentla rates from gaps in the optimized rates. These experimental rates are placed between optimum rates to establish a range of rates for which to improve model predictions in future years. Not needed if pure prescription.
exp_rate_lengthProvide the length of experimental rates to apply. This applies to new experiments and experimental prescriptions. This represents the equipment constraints of the farmer. In the case of the experimental prescription, this number of rates does not include the number of rates for the optimized base map, so take your selections for the management scenario and number of optimum rates into account. Not needed if pure prescription.
exp_ratesProvide a vector of experimental rates equal to the number of experimental rates provided in 'exp_rate_length'. This is required for all new experiments, however can be left to null for experimental prescriptions if experimental rates should be generated based on gaps in optimum rates. Not needed if pure prescription.
exp_rates_propProvide proportions (0 - 1) for the length of experimental rates provided in 'exp_rate_length'. This is required for all new experiments and experimental prescriptions. Not needed if pure prescription.
Returns
An initialized RxGen R6 class object.
Method executeOutput()
Method for calling the execution method of the experiment generator. This applies the prescription/experimental rates across the field. Check rates are stratified across prescription/experimental rates for representative checks.
Usage
RxGen$executeOutput()
Arguments
NoneAll parameters supplied upon initialization.
Returns
A completed experiment table containing the output.
Method clone()
The objects of this class are cloneable with this method.
Usage
RxGen$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
See Also
DBCon for the database connection class,
SimClass for the class that contains simulation outputs, and
ExpGen for the alternative class that creates new experiments.
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