from cromulent.vocab import Painting, add_art_setter, LotNumber, Purchase, Description
add_art_setter()
acq = Purchase()
lot = Aggregation(label="Verrue sale, lot 87")
acq2 = Purchase()
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)
est = Actor(label="The estate of Jeanne Baptiste d'Albert de Luynes, comtesse de Verrue")
lot.identified_by = LotNumber(value="87")
lot.aggregates = obj
# Date of Acquisition
date = TimeSpan()
date.begin_of_the_begin = "1737-03-27T00:00:00Z"
date.end_of_the_end = "1737-03-27T23:59:59Z"
# Description
des = Description(value="1736 - 1737: Estate of Jeanne Baptiste d'Albert de Luynes, comtesse de Verrue, 1670 - 1736 [sold, Verrue sale, Paris, March 27, 1737, lot 87.]")
acq.used_specific_object = lot
acq.part = acq2
acq2.timespan = date
acq2.transferred_title_from = est
acq2.transferred_title_of = obj
acq2.referred_to_by = des
print(factory.toString(acq, compact=False))
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))
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))
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 date = TimeSpan() date.begin_of_the_begin = "1632-01-01T00:00:00Z" date.end_of_the_end = "1652-12-31T23:59:59Z" # Description and Source des = Description(value="- 1652: Jacques Specx, 1585 - 1652 (Amsterdam, The Netherlands)") src = LinguisticObject(label="Source", value="In death inv. of 1652") acq.transferred_title_of = obj acq.timespan = date acq.transferred_title_to = p acq.referred_to_by = des acq.referred_to_by = src print(factory.toString(acq, compact=False))
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."
)
obj.referred_to_by = des
# IIIF digital image
dimg = InformationObject(
"http://media.getty.edu/viewers/mirador/?manifest=https://data.getty.edu/museum/api/iiif/882/manifest.json"
)
io = InformationObject("http://iiif.io/api/presentation")
dimg.conforms_to = io
dimg.format = "application/ld+json;profile=\"http://iiif.io/api/presentation/2/context.json\""
rights = RightsStatement(
"http://www.getty.edu/about/whatwedo/opencontent.html",
label="Open Content Program",
value="This image is available for download, without charge.")
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 est = Actor(label="The estate of Jeanne Baptiste d'Albert de Luynes, comtesse de Verrue") # Date of Acquisition date = TimeSpan() date.begin_of_the_begin = "1736-01-01T00:00:00Z" date.end_of_the_end = "1736-12-31T23:59:59Z" # Description des = Description(value="- 1736: Jeanne Baptiste d'Albert de Luynes, comtesse de Verrue, 1670 - 1736 (Paris, France; Savoy, France), upon her death, held in trust by the estate.") acq.transferred_title_of = obj acq.timespan = date acq.transferred_title_from = p acq.transferred_title_to = est acq.referred_to_by = des print(factory.toString(acq, compact=False))