ENM resolution mix - multiple runs version

Created: 2014-11-13 15:20:55 Last updated: 2015-05-12 05:28:09

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Workflow Components

Authors (1)

Titles (1)

Descriptions (0)

Dependencies (0)

Inputs (7)

Name	Description
min_virtual_niche_prevalence	Minimum virtual niche prevalence (proportion of suitable area in the native range).
max_virtual_niche_prevalence	Maximum virtual niche prevalence (proportion of suitable area in the native range).
num_background_points	Number of background points
num_testing_points	Number of points to be used for testing (an equal number will be used for presences and absences).
min_number_training_points	Minimum number of training points to be used when creating models for the virtual species. The real number will be a random value between minimum and maximum.
max_number_training_points	Maximum number of training points to be used when creating models for the virtual species. The real number will be a random value between minimum and maximum.
replicates	Number of times to repeat the experiment: generate virtual niche, generate models with different resolutions and test them.

Processors (8)

Name	Type	Description
choose_layers_and_mask	workflow
create_and_test_models	workflow
for_loop_triggering	beanshell	Script import java.util.ArrayList; ArrayList trigger_list = new ArrayList(); int end_value = Integer.parseInt(replicates); for (int i = 1; i <= end_value; i += 1) { trigger_list.add(i); }
merge_all_layers	beanshell	Script all_layers = high_resolution_layers + "\n" + low_resolution_layers;
sample_background_points	component	Randomly sample background points on the specified mask using the intersection between all environmental layers (high and low resolution). Points are returned in the absences port. Component sample_points
no	stringconstant	Value no
1	stringconstant	Value 1
demo	stringconstant	Value demo

Beanshells (7)

Name	Inputs	Outputs
for_loop_triggering	replicates	trigger_list
merge_all_layers	high_resolution_layers low_resolution_layers	all_layers
define_random_number_of_training_points	min_points max_points	num_points
get_last_iteration_result	random_proportion_list point_list threshold_list model_xml_list model_values_list	random_proportion point threshold model_xml model_values
suggest_random_suitable_threshold	model_values min_prevalence max_prevalence	threshold proportion
empty_list		empty_list
mix_layers	low_resolution_layers high_resolution_layers	mixed_resolution_layers

Outputs (13)

Name	Description
mask_id
layer_labels
origin_point
model_xml
suitability_threshold
virtual_niche_auc
low_resolution_auc
mixed_resolution_auc
num_training_points
training_points_csv
testing_presence_points_csv
testing_absence_points_csv
prevalence

Datalinks (34)

Source	Sink
choose_layers_and_mask:low_resolution_layers_ids	create_and_test_models:low_resolution_layers
choose_layers_and_mask:high_resolution_layers_ids	create_and_test_models:high_resolution_layers
choose_layers_and_mask:mask_id	create_and_test_models:mask_id
min_number_training_points	create_and_test_models:min_number_training_points
max_number_training_points	create_and_test_models:max_number_training_points
num_testing_points	create_and_test_models:num_testing_points
max_virtual_niche_prevalence	create_and_test_models:max_virtual_niche_prevalence
min_virtual_niche_prevalence	create_and_test_models:min_virtual_niche_prevalence
for_loop_triggering:trigger_list	create_and_test_models:loop_iterator
sample_background_points:absence_points_xml	create_and_test_models:background_points
merge_all_layers:all_layers	create_and_test_models:all_layers
replicates	for_loop_triggering:replicates
choose_layers_and_mask:high_resolution_layers_ids	merge_all_layers:high_resolution_layers
choose_layers_and_mask:low_resolution_layers_ids	merge_all_layers:low_resolution_layers
merge_all_layers:all_layers	sample_background_points:layers
num_background_points	sample_background_points:num_points
choose_layers_and_mask:mask_id	sample_background_points:mask_id
no:value	sample_background_points:environmentally_unique
1:value	sample_background_points:proportion_of_absences
no:value	sample_background_points:spatially_unique
demo:value	sample_background_points:species_label
choose_layers_and_mask:mask_id	mask_id
choose_layers_and_mask:high_resolution_layers_labels	layer_labels
create_and_test_models:origin_point	origin_point
create_and_test_models:model_xml	model_xml
create_and_test_models:suitability_threshold	suitability_threshold
create_and_test_models:virtual_niche_auc	virtual_niche_auc
create_and_test_models:low_resolution_auc	low_resolution_auc
create_and_test_models:mixed_resolution_auc	mixed_resolution_auc
create_and_test_models:num_training_points	num_training_points
create_and_test_models:training_points_csv	training_points_csv
create_and_test_models:testing_presence_points_csv	testing_presence_points_csv
create_and_test_models:testing_absence_points_csv	testing_absence_points_csv
create_and_test_models:prevalence	prevalence

Coordinations (3)

Controller	Target
sample_background_points	create_and_test_models
merge_all_layers	sample_background_points
choose_layers_and_mask	merge_all_layers

Information Workflow Type

Taverna 2

Information Uploader

Renato De Giovanni

Information License

All versions of this Workflow are licensed under:

Information Version 1 (earliest) (of 10)

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Information Statistics

5452 viewings

1427 downloads

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Citations (0)

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Version History

In chronological order:

Compare ENM models created with layers with different spatial resolutions.

Created by Renato De Giovanni on Thursday 13 November 2014 15:20:51 (UTC)
Compare ecological niche models created with layers with different spatial resolutions.

Created by Renato De Giovanni on Friday 14 November 2014 08:46:24 (UTC)

Revision comment:

Removed virtual niche test.
Compare ecological niche models created with layers with different spatial resolutions.

Created by Renato De Giovanni on Friday 14 November 2014 10:18:20 (UTC)

Revision comment:

Increased default number of replicates and removed redundant parameter in nested workflow.
ENM resolution mix - multiple runs version

Created by Renato De Giovanni on Tuesday 18 November 2014 17:16:00 (UTC)

Revision comment:

Updated versions of some components and improved workflow description.
ENM resolution mix - multiple runs version

Created by Renato De Giovanni on Wednesday 19 November 2014 11:40:23 (UTC)

Revision comment:

Upgraded some of the components.
ENM resolution mix - multiple runs version

Created by Renato De Giovanni on Thursday 04 December 2014 16:16:21 (UTC)

Revision comment:

Updated components versions.
ENM resolution mix - multiple runs version

Created by Renato De Giovanni on Friday 05 December 2014 18:43:04 (UTC)

Revision comment:

Initial R code to calculate probability of getting a better AUC when mixing resolutions and to plot a graph comparing the results. Also fixed a bug in threshold calculation and increased the default number of replicates.
ENM resolution mix - multiple runs version

Created by Renato De Giovanni on Tuesday 09 December 2014 20:34:17 (UTC)

Revision comment:

Updated samplePoints component, removed unnecessary loop feedback and fixed R code.
ENM resolution mix - multiple runs version

Created by Renato De Giovanni on Saturday 04 April 2015 21:27:30 (UTC)

Revision comment:

Upgraded interaction components to use github pages.
ENM resolution mix - multiple runs version

Created by Renato De Giovanni on Tuesday 12 May 2015 05:28:09 (UTC)

Revision comment:

This version plots a different graph to compare results and calculates mean and standard deviation of the AUCs differences.