def main():
f = open("ref_col.csv", "r")
r = csv.reader(f)
next(r) #Skip header
headers = ["acq_by", "acq_from", "acq_date", "add_names", "avai_data", "cat",
"certified", "chem_comp", "CAS", "chem_form", "chem_name", "col_name", "color",
"CI", "name", "comp_type", "contact", "email", "experiments", "fire", "formulation",
"fbarcode", "geo_org", "grid_loc", "health", "manufacturer", "mass_vol", "mix_pigment",
"mix_type", "MSDS", "nat_syn", "notes", "obarcode", "org_date", "other_safe",
"part_col", "phone", "phys_form", "prep", "reactivity", "samp_type", "typ_use",
"warning", "borrower", "inv_status"]
for counter, row in enumerate(r):
rec = dict(zip(headers, row))
# Testing first two rows
if counter < 2:
s = ManMadeObject(label="Sample Object")
# Sample Identification/General Information
# AccessionNumber is used for now, will a new class Barcode - aat:300343361
s.identified_by = Barcode(label="Full Barcode", value=rec['fbarcode'])
s.identified_by = Barcode(label="Old Barcode", value=rec['obarcode'])
s.identified_by = Name(label="Common Name", value=rec['name'])
s.identified_by = Name(label="Additional Names", value=rec['add_names'])
# Sample Type
if rec['samp_type']:
s.classified_as = instances[rec['samp_type'].lower()]
# Typical use
if rec['typ_use']:
s.as_general_use = instances[rec['typ_use'].lower()]
# Physical Form
if rec['phys_form']:
pf = rec['phys_form'].split()
if len(pf) < 4:
i = 0
while i <= 2:
s.classified_as = instances[pf[i].lower().replace(',', '')]
i += 1
break
else:
s.referred_to_by = Description(label="Sample Type", value=rec['phys_form'])
# Color
if rec['color']:
s.classified_as = instances[rec['color']]
# Natural/Synthetic
if rec['nat_syn']:
s.classified_as = instances[rec['nat_syn'].lower()]
elif rec[nat_syn] == "Unknown":
s.classified_as = Type(label="Natural/Synthetic", value="Unknown")
# Grid Location: lab shelf/storage?
loc = Place()
if rec['grid_loc']:
loc.identified_by = Identifier(label="Grid Location", value=rec['grid_loc'])
s.current_location = loc
# Index (CI) No., Preparation, Certified Standard
# Acquisition Information
acq = Acquisition()
gci = Department("http://www.getty.edu/conservation/", label="Getty Research Institute")
s.changed_ownership_through = acq
acq.transferred_title_to = gci
# Acquisition Date
if rec['acq_date']:
acq.timespan = TimeSpan(label=rec['acq_date'])
# Acquired by
if rec['acq_by']:
emp = Actor(label=rec['acq_by'])
acq.carried_out_by = emp
emp.member_of = gci
# Acquired from, debating whether it should be Actor or Group,
# so info of person in contact can be linked
if rec['acq_from']:
acq.transferred_title_from = Actor(label=rec['acq_from'])
# Geographic Origin
if rec['geo_org']:
prod = Production()
origin = Place(label="Geographic Origin")
origin.identified_by = Name(value=rec['geo_org'])
prod.took_place_at = origin
s.produced_by = prod
# Catalog No.
if rec['cat']:
s.identified_by = CatalogNumber(label="Catalog No.", value=rec['cat'])
# Miscellaneous
# Notes
if rec['notes']:
io = InformationObject(value=rec['notes'])
io.classified_as = instances["notes"]
print(factory.toString(s, compact=False))
# print(factory.toString(obj, compact=False))
# Example of Ownership
# from cromulent.model import factory, Acquisition
# from cromulent.vocab import Painting, MuseumOrg, add_art_setter
# add_art_setter()
# acq = Acquisition("https://linked.art/example/activity/28", "Acquisition of Painting")
# org = MuseumOrg("https://linked.art/example/group/16", "Museum")
# obj = Painting("https://linked.art/example/object/62", "Painting", art=1)
# obj.current_owner = org
# org.acquired_title_through = acq
# print(factory.toString(obj, compact=False))
# Example of Location
from cromulent.model import factory, Place
from cromulent.vocab import Painting, add_art_setter
add_art_setter()
loc = Place("https://linked.art/example/place/8", "Gallery W6")
obj = Painting("https://linked.art/example/object/63", "Painting", art=1)
obj.current_location = loc
print(factory.toString(obj, compact=False))
obj = Painting(
"http://www.getty.edu/art/collection/objects/882/rembrandt-harmensz-van-rijn-the-abduction-of-europa-dutch-1632/",
label="The Abduction of Europa",
art=1)
e = MultiExhibition(label="The Age of Rembrandt")
d = TimeSpan(label="1966-1967")
d.begin_of_the_begin = "1966-10-10T00:00:00Z"
d.end_of_the_end = "1967-03-05T23:59:59Z"
e.timespan = d
e1 = Exhibition(label="Exhibition at first location")
c1 = Aggregation()
l1 = MuseumPlace(label="The Fine Arts Museums of San Francisco")
e1.took_place_at = l1
l1.part_of = Place(label="San Francisco")
d1 = TimeSpan(label="1966")
d1.begin_of_the_begin = "1966-10-10T00:00:00Z"
d1.end_of_the_end = "1966-11-13T23:59:59Z"
e1.timespan = d1
c1.aggregates = obj
e1.used_specific_object = c1
e2 = Exhibition(label="Exhibition at second location")
c2 = Aggregation()
l2 = MuseumPlace(label="Toledo Museum of Art")
e2.took_place_at = l2
l2.part_of = Place(label="Toledo")
d2 = TimeSpan(label="1966-1967")
d2.begin_of_the_begin = "1966-11-26T00:00:00Z"
d2.end_of_the_end = "1967-01-08T23:59:59Z"
def main():
f = open("ref_col.csv", "r")
r = csv.reader(f)
next(r) #Skip header
headers = [
"acq_by", "acq_from", "acq_date", "add_names", "avai_data", "cat",
"certified", "chem_comp", "CAS", "chem_form", "chem_name", "coll_name",
"color", "CI", "name", "comp_type", "contact", "email", "experiments",
"fire", "formulation", "fbarcode", "geo_org", "grid_loc", "health",
"manufacturer", "mass_vol", "mix_pigment", "mix_type", "MSDS",
"nat_syn", "notes", "obarcode", "org_date", "other_safe", "part_coll",
"phone", "phys_form", "prep", "reactivity", "samp_type", "typ_use",
"warning", "borrower", "inv_status"
]
for counter, row in enumerate(r):
rec = dict(zip(headers, row))
# Testing first two rows
if counter < 2:
s = ManMadeObject(label=rec['name'])
# Sample Identification/General Information
s.identified_by = Barcode(label="Full Barcode",
value=rec['fbarcode'])
s.identified_by = Barcode(label="Old Barcode",
value=rec['obarcode'])
s.identified_by = PrimaryName(label="Common Name",
value=rec['name'])
s.identified_by = Name(label="Additional Names",
value=rec['add_names'])
# Sample Type
if rec['samp_type']:
try:
s.classified_as = instances[rec['samp_type'].lower()]
except:
s.referred_to_by = Description(label="Sample Type",
value=rec['samp_type'])
# Typical use
if rec['typ_use']:
use = rec['typ_use'].split('/')
for i in range(len(use)):
try:
s.as_general_use = instances[use[i].lower().strip()]
except:
s.referred_to_by = Description(label="Typical Use",
value=use[i])
# Physical Form
if rec['phys_form']:
pf = rec['phys_form'].split()
if len(pf) < 4:
l = []
for i in range(len(pf)):
try:
s.classified_as = instances[pf[i].lower().replace(
',', '').strip()]
except:
l.append(pf[i])
l_join = " ".join(l)
s.referred_to_by = Description(label="Physical Form",
value=l_join)
else:
s.referred_to_by = Description(label="Physical Form",
value=rec['phys_form'])
# Color
if rec['color']:
try:
s.classified_as = instances[rec['color'].lower()]
except:
s.referred_to_by = Description(label="Color",
value=rec['color'])
# Index (CI) Color
# Natural/Synthetic
if rec['nat_syn']:
s.classified_as = instances[rec['nat_syn'].lower()]
elif rec['nat_syn'] == "Unknown":
s.classified_as = Type(label="Natural/Synthetic",
value="Unknown")
# Preparation : go to Production
# Certified Standard
# Grid Location: lab shelf/storage?
loc = Place()
if rec['grid_loc']:
loc.identified_by = Identifier(label="Grid Location",
value=rec['grid_loc'])
s.current_location = loc
# Chemical Information
# Chemical Formula
if rec['chem_form']:
s.identified_by = Formula(value=rec['chem_form'])
if rec['chem_name']:
s.identified_by = Name(label="Chemical Name",
value=rec['chem_name'])
if rec['CAS']:
s.identified_by = Identifier(label="Chemical (CAS) No.",
value=rec['CAS'])
if rec['comp_type']:
comp_type = rec['comp_type'].lower()
try:
s.classified_as = instances[comp_type]
except:
s.classified_as = Type(label="Compound Type",
value=rec['comp_type'])
if rec['mix_type']:
mix_type = rec['mix_type'].split('-')
for i in mix_type:
s.classified_as = instances[i.lower().strip()]
# Acquisition Information
acq = Acquisition()
s.changed_ownership_through = acq
acq.transferred_title_to = v.dept['GCI']
# Acquisition Date
if rec['acq_date']:
adate = rec['acq_date']
tspan = TimeSpan(label=adate)
if len(adate) == 4:
tspan.begin_of_the_begin = str(
parse(adate + 'January',
settings={'PREFER_DAY_OF_MONTH': 'first'}))
tspan.end_of_the_end = str(
parse(adate + 'January',
settings={'PREFER_DAY_OF_MONTH': 'first'}) +
timedelta(days=365))
elif 'ca.' in adate or 'Spring' in adate:
y = adate.split()[1]
tspan.begin_of_the_begin = str(
parse(y + 'January',
settings={'PREFER_DAY_OF_MONTH': 'first'}))
tspan.end_of_the_end = str(
parse(y + 'January',
settings={'PREFER_DAY_OF_MONTH': 'first'}) +
timedelta(days=365))
elif '-' in adate:
y = adate.split('-')
start_year = y[0].strip()
end_year = y[1].strip()
if len(start_year) == 4:
tspan.begin_of_the_begin = str(
parse(start_year + 'January',
settings={'PREFER_DAY_OF_MONTH': 'first'}))
tspan.end_of_the_end = str(
parse(end_year + 'January',
settings={'PREFER_DAY_OF_MONTH': 'first'}) +
timedelta(days=365))
else:
tspan.begin_of_the_begin = str(
parse(adate,
settings={'PREFER_DAY_OF_MONTH': 'first'}))
tspan.end_of_the_end = str(
parse(adate,
settings={'PREFER_DAY_OF_MONTH': 'last'}) +
timedelta(days=1))
else:
tspan.begin_of_the_begin = str(
parse(adate, settings={'PREFER_DAY_OF_MONTH':
'first'}))
tspan.end_of_the_end = str(
parse(adate, settings={'PREFER_DAY_OF_MONTH': 'last'})
+ timedelta(days=1))
acq.timespan = tspan
# Acquired by
if rec['acq_by']:
p = rec['acq_by'].split('-')
pname = p[0].split()
agent = " ".join(pname)
dpt = p[-1]
if agent in v.person:
emp = v.person[agent]
else:
emp = Person(label=agent)
acq.carried_out_by = emp
if dpt in v.dept:
emp.member_of = v.dept[dpt]
# Part of Collection
if rec['part_coll']:
s.referred_to_by = LinguisticObject(label='Part of Collection',
value=rec['part_coll'])
# Acquired from, debating whether it should be Actor or Group,
# so info of person in contact can be linked
global seller
if rec['acq_from']:
if rec['acq_from'] in v.sellers:
seller = v.sellers[rec['acq_from'].strip()]
else:
seller = Actor(label=rec['acq_from'].strip())
acq.transferred_title_from = seller
# Collection Name
if rec['coll_name']:
coll = v.collection[rec['coll_name']]
s.aggregated_by = coll
coll_creation = Creation()
coll.created_by = coll_creation
coll_creation.carried_out_by = seller
# Contact name
if rec['contact']:
if rec['contact'] in v.contact:
contact_name = v.contact[rec['contact'].strip()]
else:
s.related_entity = contact_name
# Email
if rec['email']:
contact_name.contact_point = EMail(label="E-Mail",
value=rec['email'])
# Phone number: could be either the number of the contact person,
# or of the acquired_from
# if rec['phone']:
prod = Production()
s.produced_by = prod
# Preparation
if rec['prep']:
prep = SamplePreparation(value=rec['prep'])
prod.technique = prep
if rec['formulation']:
prep.referred_to_by = Formulation(value=rec['formulation'])
# Geographic Origin
if rec['geo_org']:
origin = Place(label="Geographic Origin")
origin.identified_by = Name(value=rec['geo_org'])
prod.took_place_at = origin
# Manufacturer
if rec['manufacturer']:
if rec['manufacturer'] in v.manufacturers:
mfr = v.manufacturers[rec['manufacturer']]
elif rec['manufacturer'] in v.sellers:
mfr = v.sellers[rec['manufacturer']]
else:
mfr = Group(label=rec['manufacturer'])
prod.carried_out_by = mfr
# Catalog No.
if rec['cat']:
s.identified_by = CatalogNumber(label="Catalog No.",
value=rec['cat'])
# Miscellaneous
# Origination Date
# if rec['org_date']:
# odate = rec['org_date']
# t_span = TimeSpan(label=odate)
# if len(adate) == 4:
# t_span.begin_of_the_begin = str(parse(odate + 'January', settings={'PREFER_DAY_OF_MONTH': 'first'}))
# t_span.end_of_the_end = str(parse(odate + 'January', settings={'PREFER_DAY_OF_MONTH': 'first'}) + timedelta(days=365))
# elif 'ca.' in adate or 'pre' in adate:
# y = odate.split()[1]
# t_span.begin_of_the_begin = str(parse(y + 'January', settings={'PREFER_DAY_OF_MONTH': 'first'}))
# t_span.end_of_the_end = str(parse(y + 'January', settings={'PREFER_DAY_OF_MONTH': 'first'}) + timedelta(days=365))
# elif '-' in adate:
# y = odate.split('-')
# start_year = y[0].strip()
# end_year = y[1].strip()
# if len(start_year) == 4:
# t_span.begin_of_the_begin = str(parse(start_year + 'January', settings={'PREFER_DAY_OF_MONTH': 'first'}))
# t_span.end_of_the_end = str(parse(end_year + 'January', settings={'PREFER_DAY_OF_MONTH': 'first'}) + timedelta(days=365))
# else:
# t_span.begin_of_the_begin = str(parse(odate, settings={'PREFER_DAY_OF_MONTH': 'first'}))
# t_span.end_of_the_end = str(parse(odate, settings={'PREFER_DAY_OF_MONTH': 'last'}) + timedelta(days=1))
# else:
# t_span.begin_of_the_begin = str(parse(odate, settings={'PREFER_DAY_OF_MONTH': 'first'}))
# t_span.end_of_the_end = str(parse(odate, settings={'PREFER_DAY_OF_MONTH': 'last'}) + timedelta(days=1))
# acq.timespan = t_span
# Mass or Volume
if rec['mass_vol']:
mv = rec['mass_vol'].replace('appx.',
'').replace('approx.',
'').split()
if len(mv) == 2:
dim = MassVolume(value=mv[0])
s.dimension = dim
dim.unit = instances[mv[1].replace('.', '')]
else:
try:
u = instances[(mv[1] + " " + mv[2]).replace('.', '')]
dim = MassVolume(value=mv[0])
s.dimension = dim
dim.unit = u
except:
s.referred_to_by = DimensionStatement(
label="Mass or Volume", value=rec['mass_vol'])
# Experiments on Sample
if rec['experiments']:
s.referred_to_by = Description(label="Experiments on Sample",
value=rec['experiments'])
# Notes
if rec['notes']:
s.referred_to_by = Notes(value=rec['notes'])
# Available Data
# MSDS & Safety
# Safety: classified_as or referred_to_by properties
if rec['fire']:
s.classified_as = FireSafety(value=rec['fire'])
if rec['health']:
health_safe = Safety(label="Health Safety",
value=rec['health'])
s.classified_as = health_safe
health_safe.classified_as = instances['health']
if rec['reactivity']:
react_safe = Safety(label="Reactivity Safety",
value=rec['reactivity'])
s.classified_as = react_safe
react_safe.classified_as = instances['reactivity']
if rec['other_safe']:
other_safe = Safety(label="Other Safety",
value=rec['other_safe'])
s.classified_as = other_safe
other_safe.classified_as = instances['other']
print(factory.toString(s, compact=False))
BeginningOfExistence, EndOfExistence, Place, LinguisticObject
from cromulent.vocab import Painting, add_art_setter, Description
add_art_setter()
acq = Acquisition()
obj = Painting("http://www.getty.edu/art/collection/objects/882/rembrandt-harmensz-van-rijn-the-abduction-of-europa-dutch-1632/", label="The Abduction of Europa", art=1)
# Info of acquirer
p = Person(label="Jacques Specx")
birth = BeginningOfExistence(label="Birth")
tob = TimeSpan(label="1585")
tob.begin_of_the_begin = "1585-01-01"
tob.end_of_the_end = "1585-12-31"
pob = Place(label="Amsterdam")
pob.part_of = Place(label="The Netherlands")
birth.timespan = tob
birth.took_place_at = pob
death = EndOfExistence(label="Death")
tod = TimeSpan(label="1652")
tod.begin_of_the_begin = "1652-01-01"
tod.end_of_the_end = "1652-12-31"
pod = Place(label="Amsterdam")
pod.part_of = Place(label="The Netherlands")
death.timespan = tod
death.took_place_at = pod
p.brought_into_existence_by = birth
p.taken_out_of_existence_by = death
# Date of Acquisition
w_in.unit = instances["inches"]
obj.dimension = h_cm
obj.dimension = w_cm
obj.dimension = h_in
obj.dimension = w_in
# Materials
sup = SupportPart(label="Single oak panel")
obj.made_of = instances["oil"]
obj.part = sup
sup.made_of = instances["oak"]
# Current location
loc = Gallery(label="Gallery E205")
mu = MuseumPlace(label="Museum East Pavillion")
place = Place(label="The Getty Center")
loc.part_of = mu
mu.part_of = place
obj.current_location = loc
# Signature
sign = Signature(label="RHL [in ligature]. van Rÿn.1632")
bpart = BottomPart(label="Lower Right")
bpart.carries = sign
obj.part = bpart
# Description
des = Description(
label="Description",
value=
"In the Metamorphoses, the ancient Roman poet Ovid told a story about the god Jupiter, who disguised himself as a white bull in order to seduce the princess Europa away from her companions and carry her across the sea to the distant land that would bear her name.\nDuring his long career Rembrandt rarely painted mythological subjects. Here he conveys a narrative story through dramatic gesture and visual effects. Bewildered, Europa grasps the bull's horn, digs her fingers into his neck, and turns back to look at her companions on the water's edge. One young woman falls to the ground and raises her arms in alarm, dropping the flower garland intended for the bull's neck into her lap, while her friend clasps her hands in consternation and watches helplessly. The carriage driver above rises to his feet and stares at the departing princess in horror. In the background, a city shrouded in mist extends along the horizon, perhaps serving as an allusion to the ancient city of Tyre as well as to contemporary Amsterdam.The dark thicket of trees to the right contrasts with the pink and blue regions of the sea and sky. Sunlight breaks through the clouds and reflects off the water, but the sky behind the trees is dark and foreboding.\nA master of visual effects, Rembrandt took pleasure in describing the varied textures of sumptuous costumes and glittering gold highlights on the carriage and dresses."
BeginningOfExistence, EndOfExistence, Place
from cromulent.vocab import Painting, add_art_setter, Description
add_art_setter()
acq = Acquisition(label="Held in trust by the estate")
obj = Painting("http://www.getty.edu/art/collection/objects/882/rembrandt-harmensz-van-rijn-the-abduction-of-europa-dutch-1632/", label="The Abduction of Europa", art=1)
# Info of acquirer
p = Person(label="Jeanne Baptiste d'Albert de Luynes, comtesse de Verrue")
birth = BeginningOfExistence(label="Birth")
tob = TimeSpan(label="1670")
tob.begin_of_the_begin = "1670-01-01T00:00:00Z"
tob.end_of_the_end = "1670-12-31T23:59:59"
pob = Place(label="Paris")
pob.part_of = Place(label="France")
birth.timespan = tob
birth.took_place_at = pob
death = EndOfExistence(label="Death")
tod = TimeSpan(label="1736")
tod.begin_of_the_begin = "1736-01-01T00:00:00Z"
tod.end_of_the_end = "1736-12-31T23:59:59Z"
pod = Place(label="Savoy")
pod.part_of = Place(label="France")
death.timespan = tod
death.took_place_at = pod
p.brought_into_existence_by = birth
p.taken_out_of_existence_by = death
# Estate