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Commit 962c225d authored by abuddenberg's avatar abuddenberg
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Added support for T2 fields (datasets, activities, contributors) to figures... 

Added support for T2 fields (datasets, activities, contributors) to figures AND images. Added support for copyright limits
parent 0e6a3749
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gcis_clients/gcis_client.py
View file @ 962c225d
......@@ -167,7 +167,6 @@ class GcisClient(object):
@http_resp
def upload_figure_file(self, report_id, chapter_id, figure_id, local_path):
# report/usgcrp-climate-and-health-assessment-draft/chapter/climate-change-and-human-health/figure/files/emissions_levels_determine_temperature_rises/
url = '{b}/report/{rpt}/chapter/{chp}/figure/files/{id}/{fn}'.format(b=self.base_url, rpt=report_id, chp=chapter_id, id=figure_id, fn=basename(local_path))
# For future multi-part encoding support
# return self.s.put(url, headers=headers, files={'file': (filename, open(filepath, 'rb'))})
......
gcis_clients/survey_client.py
View file @ 962c225d
......@@ -5,7 +5,7 @@ import requests
import re
from os.path import join, basename
from gcis_clients.domain import Figure, Image, Dataset, Parent, Contributor, Person, Organization
from gcis_clients.domain import Figure, Image, Dataset, Parent, Contributor, Person, Organization, Activity
import survey_transforms as trans
......@@ -59,12 +59,15 @@ def populate_image(img_json):
def populate_dataset(ds_json):
ds = Dataset({})
try:
ds.name = ds_json['dataset_name']
ds.url = ds_json['dataset_url']
ds = Dataset({
'name': ds_json['dataset_name'],
'url': ds_json['dataset_url']
}, known_ids=trans.DATASET_IDS)
except Exception, e:
print 'Dataset exception: ', e
ds = Dataset({})
image_select = ds_json['imageSelect'] if 'imageSelect' in ds_json else []
associated_images = [idx for idx, value in enumerate(image_select) if value == 'on']
......@@ -72,6 +75,27 @@ def populate_dataset(ds_json):
return ds, associated_images
def populate_activity(mthd_json):
act = Activity({})
try:
act.methodology = mthd_json['dataset_methods_used']
act.data_usage = mthd_json['dataset_how_visualized']
files = [mthd_json['dataset_output_file']]
files.extend([f for f in mthd_json['dataset_files'] if f])
act.output_artifacts = ', '.join(files)
act.duration = mthd_json['dataset_creation_time']
act.computing_environment = mthd_json['dataset_os_used']
act.software = ', '.join([s for s in mthd_json['dataset_software_used'] if s])
act.visualization_software = ', '.join([vs for vs in mthd_json['dataset_visualization_software'] if vs])
except Exception, e:
print 'Activity exception: ', e
return act, mthd_json['image_name'], mthd_json['dataset']
def populate_parent(pub_json):
p = Parent({})
try:
......@@ -124,6 +148,7 @@ class SurveyClient:
full_url = '{b}{url}?token={t}'.format(b=self.base_url, url=fig_url, t=self.token)
survey_json = requests.get(full_url).json()
tier1_json = survey_json[0]['t1'] if len(survey_json) > 0 and survey_json[0]['t1'] is not None else []
tier2_json = survey_json[0]['t2'] if len(survey_json) > 0 and survey_json[0]['t2'] is not None else []
f = None
......@@ -134,26 +159,58 @@ class SurveyClient:
f.remote_path = survey_json[0]['filepath']
f.local_path = join(self.local_download_dir, basename(f.remote_path)) if f.remote_path else None
if 'copyright' in survey_json[0]:
f.usage_limits = trans.COPYRIGHT_TRANSLATIONS[survey_json[0]['copyright']]
if 'origination' in figure_json and figure_json['origination'] not in ('Original',) and 'publication' in figure_json:
f.parents.append(populate_parent(figure_json['publication']))
# elif 'origination' in figure_json and figure_json['origination'] == 'Original':
# f.add_contributor(populate_contributors(figure_json))
if 'images' in tier1_json:
images = [populate_image(img) for img in tier1_json['images']]
f.images.extend(images)
elif 'figure' in tier1_json:
default_image = populate_image(tier1_json['figure'])
f.images.append(default_image)
for img_json in tier1_json['images']:
image_obj = populate_image(img_json)
#Populate image contributor info, if available
if 'origination' in img_json and img_json['origination'] not in ('Original',) and 'publication' in img_json:
image_obj.parents.append(populate_parent(img_json['publication']))
elif 'origination' in img_json and img_json['origination'] == 'Original':
image_obj.add_contributor(populate_contributors(img_json['original_agency']))
f.images.append(image_obj)
# # Recent decision: No default images
# elif 'figure' in tier1_json:
# default_image = populate_image(tier1_json['figure'])
# f.images.append(default_image)
if 'datasets' in tier1_json:
datasets = [populate_dataset(ds) for ds in tier1_json['datasets']]
#Associate datasets with images
# Create activities
activities = [populate_activity(m) for m in tier2_json['methods']] if tier2_json and 'methods' in tier2_json else []
for ds, img_idxs in datasets:
for idx in img_idxs:
try:
f.images[idx].datasets.append(ds)
except Exception, e:
print 'Association exception: ', e
# Associate datasets with images if we have images
if 'images' in tier1_json:
for idx in img_idxs:
# Associate activities with datasets
for act, img_name, ds_name in activities:
if img_name == f.images[idx].title and ds_name == ds.name:
ds.activity = act
try:
f.images[idx].datasets.append(ds)
except Exception, e:
print 'Dataset / Image association exception: ', e
# Else associate the datasets with the figure
else:
f.add_parent(Parent.from_obj(ds))
# Associate activities with datasets
for act, img_name, ds_name in activities:
if img_name == f.title and ds_name == ds.name:
ds.activity = act
if 'poc' in tier1_json:
f.add_contributor(populate_contributors(tier1_json['poc']))
......
gcis_clients/survey_transforms.py
View file @ 962c225d
__author__ = 'abuddenberg'
DATASET_IDS = {
'U.S. Climate Divisional Dataset Version 2': 'nca3-cddv2-r1',
'World Climate Research Program\'s (WCRP\'s) Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model ensemble': 'nca3-cmip5-r1',
'World Climate Research Program\'s (WCRP\'s) Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model ensemble': 'nca3-cmip5-r1'
}
COPYRIGHT_TRANSLATIONS = {
None: None,
'requested': 'Copyright protected. Obtain permission from the original figure source.',
'denied': 'Copyright protected. Obtain permission from the original figure source.',
'obtained': 'Copyright protected. Obtain permission from the original figure source.',
'original_work_nr': 'Free to use with credit to the original figure source.'
}
PARENT_TRANSLATIONS = {
'publicationType': 'publication_type_identifier',
'report_name': 'label',
......
sync_surveys.py
View file @ 962c225d
......@@ -14,81 +14,81 @@ surveys = SurveyClient('https://healthresources.globalchange.gov', survey_token)
sync_metadata_tree = {
'usgcrp-climate-and-health-assessment-draft': OrderedDict([
('executive-summary', []),
('climate-change-and-human-health', [
('/metadata/figures/3698', 'major_u_s__climate_trends'), #1.1 #climate-change-and-human-health
('/metadata/figures/3632', 'percent_changes_in_the_annual_number_of_extreme_precipitation_events_'), #1.2 #climate-change-and-human-health
('/metadata/figures/3635', 'projected_changes_in_temperature_and_precipitation_by_mid_century'), #1.3 #climate-change-and-human-health
('/metadata/figures/3633', 'projected_changes_in_the_hottest_coldest_and_wettest_driest_day_of_the_year'), #1.4 #climate-change-and-human-health
('/metadata/figures/3757', 'climate_change_and_health'), #1.5 #climate-change-and-human-health
]),
('temperature-related-death-and-illness', [
('/metadata/figures/3811', 'climate_change_and_health__extreme_heat'), #2.1 #temperature-related-death-and-illness
('/metadata/figures/3585', 'heat_related_deaths_during_the_1995_chicago_heat_wave'), #2.2 #temperature-related-death-and-illness
('/metadata/figures/3643', 'projected_net_changes_in_extreme_temperature_related_deaths'), #2.3 #temperature-related-death-and-illness
('/metadata/figures/3653', 'projected_changes_in_deaths_in_u_s__cities_by_season'), #2.4 #temperature-related-death-and-illness
]),
('air-quality-impacts', [
('/metadata/figures/3812', 'climate_change_and_health__outdoor_air_quality'), #3.1 #air-quality-impacts
('/metadata/figures/3647', 'projected_change_in_average_daily_maximum_temperature__seasonal_average_maximum_daily_8_hr_ozone__and_ozone_related_premature_deaths_in_2013'), #3.2 #air-quality-impacts
('/metadata/figures/3649', 'projected_change_in_ozone_related_premature_deaths'), #3.3 #air-quality-impacts
('/metadata/figures/3650', 'ragweed_pollen_season_lengthens'), #3.4 #air-quality-impacts
]),
('vectorborne-diseases', [
('/metadata/figures/3807', 'climate_change_and_health__lyme_disease'), #4.1 #vectorborne-diseases
('/metadata/figures/3659', 'changes_in_lyme_disease_case_report_distribution'), #4.2 #vectorborne-diseases
('/metadata/figures/3658', 'life_cycle_of_blacklegged_ticks__ixodes_scapularis'), #4.3 #vectorborne-diseases
('/metadata/figures/3747', 'lyme_disease_onset_week_modeling_scenarios'), #4.4 #vectorborne-diseases
('/metadata/figures/3674', 'incidence_of_west_nile_neuroinvasive_disease_in_the_united_states'), #4.5 #vectorborne-diseases
('/metadata/figures/3675', 'climate_impacts_on_west_nile_virus_transmission'), #4.6 #vectorborne-diseases
]),
('water-related-illnesses', [
('/metadata/figures/3824', 'climate_change_and_health___vibrio'), #5.1 #water-related-illnesses
('/metadata/figures/3700', 'links_between_climate_change__water_quantity_and_quality__and_human_exposure_to_water_related_illness'), #5.2 #water-related-illnesses
('/metadata/figures/3671', 'locations_of_livestock_and_projections_of_heavy_precipitation'), #5.3 #water-related-illnesses
# ('/metadata/figures/3673', 'potential_routes_of_manure_borne_microbial_contaminants_to_ground_and_surface_water_supplies_'), #5.3 #water-related-illnesses UNUSED?
('/metadata/figures/3709', 'projections_of_vibrio_occurrence_and_abundance_in_chesapeake_bay'), #5.4 #water-related-illnesses
('/metadata/figures/3704', 'changes_in_suitable_coastal_vibrio_habitat_in_alaska'), #5.5 #water-related-illnesses
('/metadata/figures/3734', 'projected_changes_in_caribbean_gambierdiscus_species'), #5.6 #water-related-illnesses
('/metadata/figures/3712', 'projections_of_growth_of_alexandrium_fundyense_in_puget_sound'), #5.7 #water-related-illnesses
]),
('food-safety--nutrition--and-distribution', [
('/metadata/figures/3579', 'farm_to_table'), #6.1 #food-safety--nutrition--and-distribution
# ('/metadata/figures/3600', 'mycotoxin_in_corn'), #6.1 #food-safety--nutrition--and-distribution BOX 1?
('/metadata/figures/3809', 'climate_change_and_health__salmonella'), #6.2 #food-safety--nutrition--and-distribution
('/metadata/figures/3748', 'seasonality_of_human_illnesses_associated_with_foodborne_pathogens'), #6.3 #food-safety--nutrition--and-distribution
('/metadata/figures/3688', 'effects_of_carbon_dioxide_on_protein_and_minerals'), #6.4 #food-safety--nutrition--and-distribution
('/metadata/figures/3597', 'mississippi_river_level_at_st__louis__missouri'), #6.5 #food-safety--nutrition--and-distribution
]),
('extreme-weather', [
('/metadata/figures/3810', 'estimated_deaths_and_billion_dollar_losses_from_extreme_weather_events_in_the_u_s__2004_2013'), #7.1 #extreme-weather
# ('/metadata/figures/3772', 'trends_in_flood_magnitude'), #7.2 #extreme-weather NOT USED
('/metadata/figures/3808', 'climate_change_and_health__flooding'), #7.2 #extreme-weather
('/metadata/figures/3760', 'hurricane_induced_flood_effects_in_eastern_and_central_united_states'), #7.3 #extreme-weather
]),
('mental-health-and-well-being', [
('/metadata/figures/3789', 'climate_change_and_mental_health'), #8.1 #mental-health-and-well-being
('/metadata/figures/3722', 'the_impact_of_climate_change_on_physical__mental__and_community_health'), #8.2 #mental-health-and-well-being
]),
# ('executive-summary', []),
# ('climate-change-and-human-health', [
# ('/metadata/figures/3698', 'major_u_s__climate_trends'), #1.1 #climate-change-and-human-health
# ('/metadata/figures/3632', 'percent_changes_in_the_annual_number_of_extreme_precipitation_events_'), #1.2 #climate-change-and-human-health
# ('/metadata/figures/3635', 'projected_changes_in_temperature_and_precipitation_by_mid_century'), #1.3 #climate-change-and-human-health
# ('/metadata/figures/3633', 'projected_changes_in_the_hottest_coldest_and_wettest_driest_day_of_the_year'), #1.4 #climate-change-and-human-health
# ('/metadata/figures/3757', 'climate_change_and_health'), #1.5 #climate-change-and-human-health
# ]),
# ('temperature-related-death-and-illness', [
# ('/metadata/figures/3811', 'climate_change_and_health__extreme_heat'), #2.1 #temperature-related-death-and-illness
# ('/metadata/figures/3585', 'heat_related_deaths_during_the_1995_chicago_heat_wave'), #2.2 #temperature-related-death-and-illness
# ('/metadata/figures/3643', 'projected_net_changes_in_extreme_temperature_related_deaths'), #2.3 #temperature-related-death-and-illness
# ('/metadata/figures/3653', 'projected_changes_in_deaths_in_u_s__cities_by_season'), #2.4 #temperature-related-death-and-illness
# ]),
# ('air-quality-impacts', [
# ('/metadata/figures/3812', 'climate_change_and_health__outdoor_air_quality'), #3.1 #air-quality-impacts
# ('/metadata/figures/3647', 'projected_change_in_average_daily_maximum_temperature__seasonal_average_maximum_daily_8_hr_ozone__and_ozone_related_premature_deaths_in_2013'), #3.2 #air-quality-impacts
# ('/metadata/figures/3649', 'projected_change_in_ozone_related_premature_deaths'), #3.3 #air-quality-impacts
# ('/metadata/figures/3650', 'ragweed_pollen_season_lengthens'), #3.4 #air-quality-impacts
# ]),
# ('vectorborne-diseases', [
# ('/metadata/figures/3807', 'climate_change_and_health__lyme_disease'), #4.1 #vectorborne-diseases
# ('/metadata/figures/3659', 'changes_in_lyme_disease_case_report_distribution'), #4.2 #vectorborne-diseases
# ('/metadata/figures/3658', 'life_cycle_of_blacklegged_ticks__ixodes_scapularis'), #4.3 #vectorborne-diseases
# ('/metadata/figures/3747', 'lyme_disease_onset_week_modeling_scenarios'), #4.4 #vectorborne-diseases
# ('/metadata/figures/3674', 'incidence_of_west_nile_neuroinvasive_disease_in_the_united_states'), #4.5 #vectorborne-diseases
# ('/metadata/figures/3675', 'climate_impacts_on_west_nile_virus_transmission'), #4.6 #vectorborne-diseases
# ]),
# ('water-related-illnesses', [
# ('/metadata/figures/3824', 'climate_change_and_health___vibrio'), #5.1 #water-related-illnesses
# ('/metadata/figures/3700', 'links_between_climate_change__water_quantity_and_quality__and_human_exposure_to_water_related_illness'), #5.2 #water-related-illnesses
# ('/metadata/figures/3671', 'locations_of_livestock_and_projections_of_heavy_precipitation'), #5.3 #water-related-illnesses
# # ('/metadata/figures/3673', 'potential_routes_of_manure_borne_microbial_contaminants_to_ground_and_surface_water_supplies_'), #5.3 #water-related-illnesses UNUSED?
# ('/metadata/figures/3709', 'projections_of_vibrio_occurrence_and_abundance_in_chesapeake_bay'), #5.4 #water-related-illnesses
# ('/metadata/figures/3704', 'changes_in_suitable_coastal_vibrio_habitat_in_alaska'), #5.5 #water-related-illnesses
# ('/metadata/figures/3734', 'projected_changes_in_caribbean_gambierdiscus_species'), #5.6 #water-related-illnesses
# ('/metadata/figures/3712', 'projections_of_growth_of_alexandrium_fundyense_in_puget_sound'), #5.7 #water-related-illnesses
# ]),
# ('food-safety--nutrition--and-distribution', [
# ('/metadata/figures/3579', 'farm_to_table'), #6.1 #food-safety--nutrition--and-distribution
# # ('/metadata/figures/3600', 'mycotoxin_in_corn'), #6.1 #food-safety--nutrition--and-distribution BOX 1?
# ('/metadata/figures/3809', 'climate_change_and_health__salmonella'), #6.2 #food-safety--nutrition--and-distribution
# ('/metadata/figures/3748', 'seasonality_of_human_illnesses_associated_with_foodborne_pathogens'), #6.3 #food-safety--nutrition--and-distribution
# ('/metadata/figures/3688', 'effects_of_carbon_dioxide_on_protein_and_minerals'), #6.4 #food-safety--nutrition--and-distribution
# ('/metadata/figures/3597', 'mississippi_river_level_at_st__louis__missouri'), #6.5 #food-safety--nutrition--and-distribution
# ]),
# ('extreme-weather', [
# ('/metadata/figures/3810', 'estimated_deaths_and_billion_dollar_losses_from_extreme_weather_events_in_the_u_s__2004_2013'), #7.1 #extreme-weather
# # ('/metadata/figures/3772', 'trends_in_flood_magnitude'), #7.2 #extreme-weather NOT USED
# ('/metadata/figures/3808', 'climate_change_and_health__flooding'), #7.2 #extreme-weather
# ('/metadata/figures/3760', 'hurricane_induced_flood_effects_in_eastern_and_central_united_states'), #7.3 #extreme-weather
# ]),
# ('mental-health-and-well-being', [
# ('/metadata/figures/3789', 'climate_change_and_mental_health'), #8.1 #mental-health-and-well-being
# ('/metadata/figures/3722', 'the_impact_of_climate_change_on_physical__mental__and_community_health'), #8.2 #mental-health-and-well-being
# ]),
('populations-of-concern', [
('/metadata/figures/3696', 'determinants_of_vulnerability'), #9.1 #populations-of-concern
# ('/metadata/figures/3696', 'determinants_of_vulnerability'), #9.1 #populations-of-concern
('/metadata/figures/3694', 'social_determinants_of_health'), #9.2 #populations-of-concern
('/metadata/figures/3758', 'children_at_different_lifestages_experience_unique_vulnerabilities_to_climate_change'), #9.3 #populations-of-concern
('/metadata/figures/3714', 'mapping_social_vulnerability'), #9.4 #populations-of-concern
('/metadata/figures/3717', 'mapping_communities_vulnerable_to_heat_in_georgia'), #9.5 #populations-of-concern
# ('/metadata/figures/3758', 'children_at_different_lifestages_experience_unique_vulnerabilities_to_climate_change'), #9.3 #populations-of-concern
# ('/metadata/figures/3714', 'mapping_social_vulnerability'), #9.4 #populations-of-concern
# ('/metadata/figures/3717', 'mapping_communities_vulnerable_to_heat_in_georgia'), #9.5 #populations-of-concern
]),
('appendix-1--technical-support-document', [
('/metadata/figures/3623', 'emissions_levels_determine_temperature_rises'), #1.1 #climate-change-and-human-health
('/metadata/figures/3759', 'the_shared_socioeconomic_pathways'), #1.2 #climate-change-and-human-health
('/metadata/figures/3726', 'example_spatial_resolution_of_climate_models'), #1.3 #climate-change-and-human-health
('/metadata/figures/3638', 'sensitivity_analysis_of_differences_in_modeling_approaches'), #1.4 #climate-change-and-human-health
])
# ('appendix-1--technical-support-document', [
# ('/metadata/figures/3623', 'emissions_levels_determine_temperature_rises'), #1.1 #climate-change-and-human-health
# ('/metadata/figures/3759', 'the_shared_socioeconomic_pathways'), #1.2 #climate-change-and-human-health
# ('/metadata/figures/3726', 'example_spatial_resolution_of_climate_models'), #1.3 #climate-change-and-human-health
# ('/metadata/figures/3638', 'sensitivity_analysis_of_differences_in_modeling_approaches'), #1.4 #climate-change-and-human-health
# ])
])
}
def main():
regenerate_image_id_map()
# regenerate_image_id_map()
image_id_map = pickle.load(open('image_id_cache.pk1', 'r'))
for report_id in sync_metadata_tree:
......@@ -97,16 +97,36 @@ def main():
print survey_url
s = surveys.get_survey(survey_url, do_download=False)
print s.contributors
print s.parents
print s.usage_limits
# for i in s.images:
# i.identifier = image_id_map[i.identifier]
#
# print i.contributors
# print i.parents
#
# for ds in i.datasets:
# if ds.activity and ds.activity.identifier is None:
# ds.activity.identifier = generate_activity_id(i, ds)
# print ds
# realize_parents(gcis, s.parents)
# realize_contributors(gcis, s.contributors)
for i in s.images:
i.identifier = image_id_map[i.identifier]
i.datasets = []
print gcis.create_image(i, report_id=report_id, figure_id=figure_id)
# for i in s.images:
# i.identifier = image_id_map[i.identifier]
# i.datasets = []
# print gcis.create_image(i, report_id=report_id, figure_id=figure_id)
def generate_activity_id(image, dataset):
return '-'.join([image.identifier.split('-')[0], dataset.identifier, '-process'])
def regenerate_image_id_map(existing=None):
from uuid import uuid4
image_id_map = existing if existing else {}
......
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