| GradELA | R Documentation |
Estimate energy landscape across environmental gradients.
Runs ELA and ELPruning comprehensively across specified environmental parameters.
One environmental parameter can be changed by specifying eid over steps within range.
If env is not given, the mean vector of enmat is used as the reference environmental condition.
GradELA(
sa = sa,
pruning_type = "relative",
eid = NULL,
enmat = enmat,
env = NULL,
range = NULL,
steps = 16,
th = 0.05,
threads = 1,
SS.itr = 20000,
FindingTip.itr = 10000,
lower_qr = 0.05,
bs_params = NULL,
ocmat = NULL
)
sa |
output of runSA function. |
pruning_type |
the type of pruning |
eid |
target environmental factor: the specified environmental factor to be changed. |
enmat |
array/matrix of environmental factors for each sample (normalization required). |
env |
array of environmental factor values.
For the environmental parameters that are not specified for |
range |
range over which the environmental factor specified by eid is changed. |
steps |
number of steps in the range. |
th |
ratio of the depth of the basin to be pruned with respect to the deepest basin. |
threads |
number of cores (threads) used for calculation. |
SS.itr |
number of iterations to identify stable states. |
FindingTip.itr |
number of iterations to identify tipping points. |
lower_qr |
Numeric value. Quantile used for constructing confidence intervals from bootstrap samples to check
whether the estimated energy gaps include zero. Default is |
bs_params |
output of bootstrap_SA. list of estimated parameters using bootstrap resampled data set.
necessary when |
ocmat |
community composition matrix. |
A list of three elements: (1) ELA results for each step (pruned), (2) the sequence of environmental values, and (3) the reference env vector.
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