diff --git a/run_workflow_phaeoexplorer.py b/run_workflow_phaeoexplorer.py
index 2c385d476ca128e949e9b9a1353c0679ed5d6958..282dcd77f202a32201c2913114e04606b4977ec7 100755
--- a/run_workflow_phaeoexplorer.py
+++ b/run_workflow_phaeoexplorer.py
@@ -115,7 +115,7 @@ class RunWorkflow(speciesData.SpeciesData):
"""
- logging.debug("Connecting to the galaxy instance (%s)" % self.instance_url)
+ # logging.debug("Connecting to the galaxy instance (%s)" % self.instance_url)
self.instance = galaxy.GalaxyInstance(url=self.instance_url,
email=self.config["galaxy_default_admin_email"],
password=self.config["galaxy_default_admin_password"]
@@ -125,10 +125,10 @@ class RunWorkflow(speciesData.SpeciesData):
try:
self.instance.histories.get_histories()
except bioblend.ConnectionError:
- logging.critical("Cannot connect to galaxy instance (%s) " % self.instance_url)
+ logging.critical("Cannot connect to galaxy instance (%s)" % self.instance_url)
sys.exit()
else:
- logging.debug("Successfully connected to galaxy instance (%s) " % self.instance_url)
+ # logging.debug("Successfully connected to galaxy instance (%s) " % self.instance_url)
return 1
@@ -961,7 +961,10 @@ if __name__ == "__main__":
logging.info("Input organism %s: 1 species detected in input dictionary" % k)
# Set workflow path (1 organism)
- workflow_path = os.path.join(os.path.abspath(script_dir), "workflows_phaeoexplorer/Galaxy-Workflow-chado_load_tripal_synchronize_jbrowse_1org_v2.ga")
+ workflow_path = os.path.join(os.path.abspath(script_dir), "workflows_phaeoexplorer/Galaxy-Workflow-chado_load_tripal_synchronize_jbrowse_1org_v4.ga")
+
+ # Instance object required variables
+ instance_url, email, password = None, None, None
# Set the galaxy instance variables
for k2, v2 in v.items():
@@ -974,13 +977,134 @@ if __name__ == "__main__":
# Check if the versions of tools specified in the workflow are installed in galaxy
install_changesets_revisions_from_workflow(workflow_path=workflow_path, instance=instance)
- # Set datamap (mapping of input files in the workflow)
- datamap = {}
+ organism_key_name = list(v.keys())
+ org_dict = v[organisms_key_names[0]]
+ history_id = org_dict["history_id"]
+
+ # Organism 1 attributes
+ org_genus = org_dict["genus"]
+ org_species = org_dict["species"]
+ org_genus_species = org_dict["genus_species"]
+ org_species_folder_name = org_dict["species_folder_name"]
+ org_full_name = org_dict["full_name"]
+ org_strain = org_dict["sex"]
+ org_sex = org_dict["strain"]
+ org_org_id = org_dict["org_id"]
+ org_genome_analysis_id = org_dict["genome_analysis_id"]
+ org_ogs_analysis_id = org_dict["ogs_analysis_id"]
+ org_genome_hda_id = org_dict["hda_ids"]["genome_hda_id"]
+ org_transcripts_hda_id = org_dict["hda_ids"]["transcripts_hda_id"]
+ org_proteins_hda_id = org_dict["hda_ids"]["proteins_hda_id"]
+ org_gff_hda_id = org_dict["hda_ids"]["gff_hda_id"]
+
+ # Store these values into a dict for parameters logging/validation
+ org_parameters_dict = {
+ "org_genus": org_genus,
+ "org_species": org_species,
+ "org_genus_species": org_genus_species,
+ "org_species_folder_name": org_species_folder_name,
+ "org_full_name": org_full_name,
+ "org_strain": org_strain,
+ "org_sex": org_sex,
+ "org_org_id": org_org_id,
+ "org_genome_analysis_id": org_genome_analysis_id,
+ "org_ogs_analysis_id": org_ogs_analysis_id,
+ "org_genome_hda_id": org_genome_hda_id,
+ "org_transcripts_hda_id": org_transcripts_hda_id,
+ "org_proteins_hda_id": org_proteins_hda_id,
+ "org_gff_hda_id": org_gff_hda_id,
+ }
+
+ # Look for empty parameters values, throw a critical error if a parameter value is invalid
+ for param_name, param_value in org_parameters_dict.items():
+ if param_value is None or param_value == "":
+ logging.critical("Empty parameter value found for organism {0} (parameter: {1}, parameter value: {2})".format(org_full_name, param_name, param_value))
+ sys.exit()
# Set the workflow parameters (individual tools runtime parameters in the workflow)
workflow_parameters = {}
+ GENOME_FASTA_FILE_ORG = "0"
+ GFF_FILE_ORG = "1"
+ PROTEINS_FASTA_FILE_ORG = "2"
+ LOAD_FASTA_ORG = "3"
+ JBROWSE_ORG = "4"
+ LOAD_GFF_ORG = "5"
+ JBROWSE_CONTAINER = "6"
+ SYNC_FEATURES_ORG = "7"
+ POPULATE_MAT_VIEWS = "8"
+ INDEX_TRIPAL_DATA = "9"
+
+ # Input files have no parameters (they are set via assigning the hda IDs in the datamap parameter of the bioblend method)
+ workflow_parameters[GENOME_FASTA_FILE_ORG] = {}
+ workflow_parameters[GFF_FILE_ORG] = {}
+ workflow_parameters[PROTEINS_FASTA_FILE_ORG] = {}
+ workflow_parameters[LOAD_FASTA_ORG] = {"organism": org_org_id,
+ "analysis_id": org_genome_analysis_id,
+ "do_update": "true"}
+ workflow_parameters[JBROWSE_ORG] = {}
+ workflow_parameters[LOAD_GFF_ORG] = {"organism": org_org_id, "analysis_id": org_ogs_analysis_id}
+ workflow_parameters[SYNC_FEATURES_ORG] = {"organism_id": org_org_id}
+ # POPULATE + INDEX DATA
+ workflow_parameters[POPULATE_MAT_VIEWS] = {}
+ workflow_parameters[INDEX_TRIPAL_DATA] = {}
+
+ # Set datamap (mapping of input files in the workflow)
+ datamap = {}
+
+ datamap[GENOME_FASTA_FILE_ORG] = {"src": "hda", "id": org_genome_hda_id}
+ datamap[GFF_FILE_ORG] = {"src": "hda", "id": org_gff_hda_id}
+ datamap[PROTEINS_FASTA_FILE_ORG] = {"src": "hda", "id": org_proteins_hda_id}
+
+
+ with open(workflow_path, 'r') as ga_in_file:
+
+ # Store the decoded json dictionary
+ workflow_dict = json.load(ga_in_file)
+ workflow_name = workflow_dict["name"]
+
+ # For the Jbrowse tool, we unfortunately have to manually edit the parameters instead of setting them
+ # as runtime values, using runtime parameters makes the tool throw an internal critical error ("replace not found" error)
+ # Scratchgmod test: need "http" (or "https"), the hostname (+ port)
+ jbrowse_menu_url_org = "https://{hostname}/sp/{genus_sp}/feature/{Genus}/{species}/mRNA/{id}".format(hostname=config["hostname"], genus_sp=org_genus_species, Genus=org_genus[0].upper() + org_genus[1:], species=org_species, id="{id}")
+ if "menu_url" not in config.keys():
+ jbrowse_menu_url_org = "https://{hostname}/sp/{genus_sp}/feature/{Genus}/{species}/mRNA/{id}".format(hostname=config["hostname"], genus_sp=org_genus_species, Genus=org_genus[0].upper() + org_genus[1:], species=org_species, id="{id}")
+ else:
+ jbrowse_menu_url_org = config["menu_url"] + "/sp/{genus_sp}/feature/{Genus}/{species}/mRNA/{id}".format(genus_sp=org_genus_species, Genus=org_genus[0].upper() + org_genus[1:], species=org_species, id="{id}")
+
+ # show_tool_add_organism = instance.tools.show_tool(tool_id="toolshed.g2.bx.psu.edu/repos/gga/chado_organism_add_organism/organism_add_organism/2.3.4+galaxy0", io_details=True)
+ # print(show_tool_add_organism)
+ # show_jbrowse_tool = instance.tools.show_tool(tool_id="toolshed.g2.bx.psu.edu/repos/iuc/jbrowse/jbrowse/1.16.11+galaxy0", io_details=True)
+ # print(show_jbrowse_tool)
+ # show_jbrowse_container_tool = instance.tools.show_tool(tool_id="toolshed.g2.bx.psu.edu/repos/gga/jbrowse_to_container/jbrowse_to_container/0.5.1", io_details=True)
+ # print(show_jbrowse_container_tool)
+
+ # Replace values in the workflow dictionary
+ workflow_dict["steps"]["4"]["tool_state"] = workflow_dict["steps"]["4"]["tool_state"].replace("__MENU_URL_ORG__", jbrowse_menu_url_org)
+ workflow_dict["steps"]["6"]["tool_state"] = workflow_dict["steps"]["6"]["tool_state"].replace("__DISPLAY_NAME_ORG__", org_full_name).replace("__UNIQUE_ID_ORG__", org_species_folder_name)
+
+ # Import the workflow in galaxy as a dict
+ instance.workflows.import_workflow_dict(workflow_dict=workflow_dict)
+
+ # Get its attributes
+ workflow_attributes = instance.workflows.get_workflows(name=workflow_name)
+ # Then get its ID (required to invoke the workflow)
+ workflow_id = workflow_attributes[0]["id"] # Index 0 is the most recently imported workflow (the one we want)
+ show_workflow = instance.workflows.show_workflow(workflow_id=workflow_id)
+ # Check if the workflow is found
+ try:
+ logging.debug("Workflow ID: %s" % workflow_id)
+ except bioblend.ConnectionError:
+ logging.warning("Error finding workflow %s" % workflow_name)
+
+ # Finally, invoke the workflow alogn with its datamap, parameters and the history in which to invoke it
+ instance.workflows.invoke_workflow(workflow_id=workflow_id, history_id=history_id, params=workflow_parameters, inputs=datamap, allow_tool_state_corrections=True)
+
+ logging.info("Successfully imported and invoked workflow {0}, check the galaxy instance ({1}) for the jobs state".format(workflow_name, instance_url))
+
+
+
if len(list(v.keys())) == 2:
logging.info("Input organism %s: 2 species detected in input dictionary" % k)
@@ -1089,17 +1213,6 @@ if __name__ == "__main__":
logging.critical("Empty parameter value found for organism {0} (parameter: {1}, parameter value: {2})".format(org2_full_name, param_name, param_value))
sys.exit()
-
- jbrowse_menu_url_org1 = "https://{hostname}/sp/{genus_sp}/feature/{Genus}/{species}/mRNA/{id}".format(hostname=config["hostname"], genus_sp=org1_genus_species, Genus=org1_genus[0].upper() + org1_genus[1:], species=org1_species, id="\{id\}")
- jbrowse_menu_url_org2 = "https://{hostname}/sp/{genus_sp}/feature/{Genus}/{species}/mRNA/{id}".format(hostname=config["hostname"], genus_sp=org2_genus_species, Genus=org2_genus[0].upper() + org2_genus[1:], species=org2_species, id="\{id\}")
- if "menu_url" not in config.keys():
- jbrowse_menu_url_org1 = "https://{hostname}/sp/{genus_sp}/feature/{Genus}/{species}/mRNA/{id}".format(hostname=config["hostname"], genus_sp=org1_genus_species, Genus=org1_genus[0].upper() + org1_genus[1:], species=org1_species, id="\{id\}")
- jbrowse_menu_url_org2 = "https://{hostname}/sp/{genus_sp}/feature/{Genus}/{species}/mRNA/{id}".format(hostname=config["hostname"], genus_sp=org2_genus_species, Genus=org2_genus[0].upper() + org2_genus[1:], species=org2_species, id="\{id\}")
- else:
- jbrowse_menu_url_org1 = config["menu_url"]
- jbrowse_menu_url_org2 = "https://{hostname}/sp/{genus_sp}/feature/{Genus}/{species}/mRNA/{id}".format(hostname=config["hostname"], genus_sp=org2_genus_species, Genus=org2_genus[0].upper() + org2_genus[1:], species=org2_species, id="\{id\}")
-
-
# Source files association (ordered by their IDs in the workflow)
# WARNING: Be very careful about how the workflow is "organized" (i.e the order of the steps/datasets, check the .ga if there is any error)
GFF_FILE_ORG1 = "0"
@@ -1181,7 +1294,6 @@ if __name__ == "__main__":
workflow_dict = json.load(ga_in_file)
workflow_name = workflow_dict["name"]
-
# For the Jbrowse tool, we unfortunately have to manually edit the parameters instead of setting them
# as runtime values, using runtime parameters makes the tool throw an internal critical error ("replace not found" error)
# Scratchgmod test: need "http" (or "https"), the hostname (+ port)
diff --git a/workflows_phaeoexplorer/Galaxy-Workflow-chado_load_tripal_synchronize_jbrowse_1org_v4.ga b/workflows_phaeoexplorer/Galaxy-Workflow-chado_load_tripal_synchronize_jbrowse_1org_v4.ga
new file mode 100644
index 0000000000000000000000000000000000000000..0349a497fc1c8baa9ab98ba75c092dad191da08b
--- /dev/null
+++ b/workflows_phaeoexplorer/Galaxy-Workflow-chado_load_tripal_synchronize_jbrowse_1org_v4.ga
@@ -0,0 +1,535 @@
+{
+ "a_galaxy_workflow": "true",
+ "annotation": "",
+ "format-version": "0.1",
+ "name": "chado_load_tripal_synchronize_jbrowse_1org_v4",
+ "steps": {
+ "0": {
+ "annotation": "",
+ "content_id": null,
+ "errors": null,
+ "id": 0,
+ "input_connections": {},
+ "inputs": [
+ {
+ "description": "",
+ "name": "genome"
+ }
+ ],
+ "label": "genome",
+ "name": "Input dataset",
+ "outputs": [],
+ "position": {
+ "bottom": 277.1999969482422,
+ "height": 61.19999694824219,
+ "left": 436.5,
+ "right": 636.5,
+ "top": 216,
+ "width": 200,
+ "x": 436.5,
+ "y": 216
+ },
+ "tool_id": null,
+ "tool_state": "{\"optional\": false}",
+ "tool_version": null,
+ "type": "data_input",
+ "uuid": "fa9981ea-4012-40aa-ad84-6e6f61049104",
+ "workflow_outputs": [
+ {
+ "label": null,
+ "output_name": "output",
+ "uuid": "65bba69d-b8f0-4f7e-a66a-71afa9a8975f"
+ }
+ ]
+ },
+ "1": {
+ "annotation": "",
+ "content_id": null,
+ "errors": null,
+ "id": 1,
+ "input_connections": {},
+ "inputs": [
+ {
+ "description": "",
+ "name": "annotations"
+ }
+ ],
+ "label": "annotations",
+ "name": "Input dataset",
+ "outputs": [],
+ "position": {
+ "bottom": 367.1999969482422,
+ "height": 61.19999694824219,
+ "left": 467.5,
+ "right": 667.5,
+ "top": 306,
+ "width": 200,
+ "x": 467.5,
+ "y": 306
+ },
+ "tool_id": null,
+ "tool_state": "{\"optional\": false}",
+ "tool_version": null,
+ "type": "data_input",
+ "uuid": "61d23082-b459-4014-8584-6ff5b98ce689",
+ "workflow_outputs": [
+ {
+ "label": null,
+ "output_name": "output",
+ "uuid": "acb766e7-fcd7-42e2-8fcf-638024338fc4"
+ }
+ ]
+ },
+ "2": {
+ "annotation": "",
+ "content_id": null,
+ "errors": null,
+ "id": 2,
+ "input_connections": {},
+ "inputs": [
+ {
+ "description": "",
+ "name": "proteins"
+ }
+ ],
+ "label": "proteins",
+ "name": "Input dataset",
+ "outputs": [],
+ "position": {
+ "bottom": 456.1999969482422,
+ "height": 61.19999694824219,
+ "left": 489.5,
+ "right": 689.5,
+ "top": 395,
+ "width": 200,
+ "x": 489.5,
+ "y": 395
+ },
+ "tool_id": null,
+ "tool_state": "{\"optional\": false}",
+ "tool_version": null,
+ "type": "data_input",
+ "uuid": "ea25f583-f55d-4fdd-a7a9-86ffb4b9c731",
+ "workflow_outputs": [
+ {
+ "label": null,
+ "output_name": "output",
+ "uuid": "eba4266d-d468-448f-8ce3-fa87b497cbf8"
+ }
+ ]
+ },
+ "3": {
+ "annotation": "",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_feature_load_fasta/feature_load_fasta/2.3.4+galaxy0",
+ "errors": null,
+ "id": 3,
+ "input_connections": {
+ "fasta": {
+ "id": 0,
+ "output_name": "output"
+ }
+ },
+ "inputs": [
+ {
+ "description": "runtime parameter for tool Chado load fasta",
+ "name": "analysis_id"
+ },
+ {
+ "description": "runtime parameter for tool Chado load fasta",
+ "name": "fasta"
+ },
+ {
+ "description": "runtime parameter for tool Chado load fasta",
+ "name": "organism"
+ },
+ {
+ "description": "runtime parameter for tool Chado load fasta",
+ "name": "wait_for"
+ }
+ ],
+ "label": null,
+ "name": "Chado load fasta",
+ "outputs": [
+ {
+ "name": "results",
+ "type": "json"
+ }
+ ],
+ "position": {
+ "bottom": 356.1999969482422,
+ "height": 143.1999969482422,
+ "left": 766.5,
+ "right": 966.5,
+ "top": 213,
+ "width": 200,
+ "x": 766.5,
+ "y": 213
+ },
+ "post_job_actions": {},
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_feature_load_fasta/feature_load_fasta/2.3.4+galaxy0",
+ "tool_shed_repository": {
+ "changeset_revision": "ba4d07fbaf47",
+ "name": "chado_feature_load_fasta",
+ "owner": "gga",
+ "tool_shed": "toolshed.g2.bx.psu.edu"
+ },
+ "tool_state": "{\"analysis_id\": {\"__class__\": \"RuntimeValue\"}, \"do_update\": \"false\", \"ext_db\": {\"db\": \"\", \"re_db_accession\": \"\"}, \"fasta\": {\"__class__\": \"RuntimeValue\"}, \"match_on_name\": \"false\", \"organism\": {\"__class__\": \"RuntimeValue\"}, \"psql_target\": {\"method\": \"remote\", \"__current_case__\": 0}, \"re_name\": \"\", \"re_uniquename\": \"\", \"relationships\": {\"rel_type\": \"none\", \"__current_case__\": 0}, \"sequence_type\": \"contig\", \"wait_for\": {\"__class__\": \"RuntimeValue\"}, \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "2.3.4+galaxy0",
+ "type": "tool",
+ "uuid": "86b4962b-d001-44f3-b2f5-349e0daccc69",
+ "workflow_outputs": [
+ {
+ "label": null,
+ "output_name": "results",
+ "uuid": "892534b5-0d67-44da-8892-f17da2be9e9c"
+ }
+ ]
+ },
+ "4": {
+ "annotation": "",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/iuc/jbrowse/jbrowse/1.16.11+galaxy0",
+ "errors": null,
+ "id": 4,
+ "input_connections": {
+ "reference_genome|genome": {
+ "id": 0,
+ "output_name": "output"
+ },
+ "track_groups_0|data_tracks_0|data_format|annotation": {
+ "id": 1,
+ "output_name": "output"
+ }
+ },
+ "inputs": [
+ {
+ "description": "runtime parameter for tool JBrowse",
+ "name": "reference_genome"
+ }
+ ],
+ "label": null,
+ "name": "JBrowse",
+ "outputs": [
+ {
+ "name": "output",
+ "type": "html"
+ }
+ ],
+ "position": {
+ "bottom": 572,
+ "height": 184,
+ "left": 753.5,
+ "right": 953.5,
+ "top": 388,
+ "width": 200,
+ "x": 753.5,
+ "y": 388
+ },
+ "post_job_actions": {},
+ "tool_id": "toolshed.g2.bx.psu.edu/repos/iuc/jbrowse/jbrowse/1.16.11+galaxy0",
+ "tool_shed_repository": {
+ "changeset_revision": "4542035c1075",
+ "name": "jbrowse",
+ "owner": "iuc",
+ "tool_shed": "toolshed.g2.bx.psu.edu"
+ },
+ "tool_state": "{\"action\": {\"action_select\": \"create\", \"__current_case__\": 0}, \"gencode\": \"1\", \"jbgen\": {\"defaultLocation\": \"\", \"trackPadding\": \"20\", \"shareLink\": \"true\", \"aboutDescription\": \"\", \"show_tracklist\": \"true\", \"show_nav\": \"true\", \"show_overview\": \"true\", \"show_menu\": \"true\", \"hideGenomeOptions\": \"false\"}, \"plugins\": {\"BlastView\": \"true\", \"ComboTrackSelector\": \"false\", \"GCContent\": \"false\"}, \"reference_genome\": {\"genome_type_select\": \"history\", \"__current_case__\": 1, \"genome\": {\"__class__\": \"RuntimeValue\"}}, \"standalone\": \"minimal\", \"track_groups\": [{\"__index__\": 0, \"category\": \"Annotation\", \"data_tracks\": [{\"__index__\": 0, \"data_format\": {\"data_format_select\": \"gene_calls\", \"__current_case__\": 2, \"annotation\": {\"__class__\": \"RuntimeValue\"}, \"match_part\": {\"match_part_select\": \"false\", \"__current_case__\": 1}, \"index\": \"false\", \"track_config\": {\"track_class\": \"NeatHTMLFeatures/View/Track/NeatFeatures\", \"__current_case__\": 3, \"html_options\": {\"topLevelFeatures\": \"\"}}, \"jbstyle\": {\"style_classname\": \"transcript\", \"style_label\": \"product,name,id\", \"style_description\": \"note,description\", \"style_height\": \"10px\", \"max_height\": \"600\"}, \"jbcolor_scale\": {\"color_score\": {\"color_score_select\": \"none\", \"__current_case__\": 0, \"color\": {\"color_select\": \"automatic\", \"__current_case__\": 0}}}, \"jb_custom_config\": {\"option\": []}, \"jbmenu\": {\"track_menu\": [{\"__index__\": 0, \"menu_action\": \"iframeDialog\", \"menu_label\": \"View transcript report\", \"menu_title\": \"Transcript {id}\", \"menu_url\": \"__MENU_URL_ORG__\", \"menu_icon\": \"dijitIconBookmark\"}]}, \"track_visibility\": \"default_off\", \"override_apollo_plugins\": \"False\", \"override_apollo_drag\": \"False\"}}]}], \"uglyTestingHack\": \"\", \"__page__\": null, \"__rerun_remap_job_id__\": null}",
+ "tool_version": "1.16.11+galaxy0",
+ "type": "tool",
+ "uuid": "4e87e6b5-c37c-4429-a491-2d6a411d8a13",
+ "workflow_outputs": [
+ {
+ "label": null,
+ "output_name": "output",
+ "uuid": "37d09194-4527-4428-963c-85cb351efcba"
+ }
+ ]
+ },
+ "5": {
+ "annotation": "",
+ "content_id": "toolshed.g2.bx.psu.edu/repos/gga/chado_feature_load_gff/feature_load_gff/2.3.4+galaxy0",
+ "errors": null,
+ "id": 5,
+ "input_connections": {
+ "fasta": {
+ "id": 2,
+ "output_name": "output"
+ },
+ "gff": {
+ "id": 1,
+ "output_name": "output"
+ },
+ "wait_for": {
+ "id": 3,
+ "output_name": "results"
+ }
+ },
+ "inputs": [
+ {
+ "description": "runtime parameter for tool Chado load gff",
+ "name": "analysis_id"
+ },
+ {
+ "description": "runtime parameter for tool Chado load gff",
+ "name": "fasta"
+ },
+ {
+ "description": "runtime parameter for tool Chado load gff",
+ "name": "gff"
+ },
+ {
+ "description": "runtime parameter for tool Chado load gff",
+ "name": "organism"
+ },
+ {
+ "description": "runtime parameter for tool Chado load gff",
+ "name": "wait_for"
+ }
+ ],
+ "label": null,
+ "name": "Chado load gff",
+ "outputs": [
+ {
+ "name": "results",
+ "type": "txt"
+ }
+ ],
+ "position": {
+ "bottom": 383.6000061035156,
+ "height": 173.60000610351562,
+ "left": 1043.5,
+ "right": 1243.5,
+ "top": 210,
+ "width": 200,
+ "x": 1043.5,
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