def _main():
"""Main entry point.
"""
for m, institution_id, model_id, repo in _yield_targets():
if not os.path.exists(repo):
logger.log_warning(
'unmappable cmip5 institution: {}'.format(model_id))
continue
_write(m, institution_id, model_id, repo)
def convert_tab_to_dict(spreadsheet_tab):
"""Return the full dictionary of inputs extracted from a machine tab."""
all_input_cells = find_input_cells(
spreadsheet_tab, get_ws_questions_to_input_cells_mapping())
final_dict = {}
for label, input_cell_or_cells in all_input_cells.items():
if not isinstance(input_cell_or_cells, list):
user_input = spreadsheet_tab.cell(row=input_cell_or_cells,
column=INPUT_COLUMN + 1).value
# Distinguish from Falsy values e.g. False and "None" as user input
if user_input is None:
# Use a placeholder/default that is unlikely to be specified
# (not None, False, etc.) to avoid potential clash with any
# user input, for keeping track of input cells left empty.
final_dict[label] = EMPTY_CELL_MARKER
else: # else store the value, which may (rarely) be string "None"!
# For cases where questions are populated based on institute
# specific values (e.g. applicable models and exps questions),
# also note these values for validation
if label.startswith("1.8.2."):
name = get_top_cell_model_or_exp_name(
input_cell_or_cells, spreadsheet_tab)
final_dict[label] = {name: str(user_input)}
else:
try:
final_dict[label] = str(user_input)
except:
# Python 2 only unicode-escape
logger.log_warning(
"WARNING: Python 2 only unicode issue with:",
label)
final_dict[label] = user_input
elif label.startswith("1.9.2."):
if not spreadsheet_tab.cell(row=input_cell_or_cells[0],
column=INPUT_COLUMN + 1).value:
# Institutes may, against advice, have left some
# experiment input cells blank to indicate no applicable
# experiments by MIP, so to cater for these cases, replace
# empty values with 'NONE'
final_dict[label] = "NONE"
else:
name = get_top_cell_model_or_exp_name(input_cell_or_cells,
spreadsheet_tab)
final_dict[label] = {
name:
extract_inputs_at_input_cells(input_cell_or_cells,
spreadsheet_tab)
}
else:
final_dict[label] = extract_inputs_at_input_cells(
input_cell_or_cells, spreadsheet_tab)
return final_dict
def _write(i):
"""Writes citation JSON file for a particular institute.
"""
try:
spreadsheet = _get_spreadsheet(i)
except IOError:
msg = '{} citations spreadsheet not found'.format(i.canonical_name)
logger.log_warning(msg)
else:
content = _get_content(i, spreadsheet)
if content:
_write_content(i, content)
def _main(args):
"""Main entry point.
"""
for i, s, t in vocabs.yield_topics(args.institution_id):
try:
wb = _get_spreadsheet(i, s, t)
except IOError:
warning = '{} :: {} :: {} :: spreadsheet not found'
warning = warning.format(i.canonical_name, s.canonical_name,
t.canonical_name)
logger.log_warning(warning)
continue
# Set JSON content.
content = _get_content(i, s, t, wb)
# Write JSON file.
io_mgr.write_model_topic_json(i, s, t, content)
def _main(args):
"""Main entry point.
"""
# Write a CIM file per CMIP6 institute | source combination.
institutes = vocabs.get_institutes(args.institution_id)
for i in institutes:
# Escape if settings file not found.
try:
all_settings = io_mgr.load_model_settings(
i, _MODEL_PUBLICATION_FNAME)
except IOError:
warning = '{} model_publications.json not found'
warning = warning.format(i.canonical_name)
logger.log_warning(warning)
continue
for s in vocabs.get_institute_sources(i):
# Escape if source settings undeclared.
try:
settings = all_settings[s.canonical_name]
except KeyError:
warning = '{} :: {} publication settings not found'
warning = warning.format(i.canonical_name, s.canonical_name)
logger.log_warning(warning)
continue
# Escape if no settings are switched 'on'.
settings = {
k: v
for (k, v) in settings.items()
if settings[k]['publish'] == 'on'
}
if not settings:
continue
# Generate content.
content = _get_content(i, s, settings)
if content is None:
warning = '{} :: {} CIM file not found'
warning = warning.format(i.canonical_name, s.canonical_name)
logger.log_warning(warning)
continue
# Write CIM file to fs.
io_mgr.write_model_cim(i, s, content)
for offset in offsets
]
break
# Otherwise it is a simple offset, apply it:
input_box_row = row[INPUT_COLUMN].row + offset
label_to_input_cell_mapping[label] = input_box_row
break
# Remove inapplicable numbers for MIPs and experiments:
if not label_to_input_cell_mapping.get(label, False):
if label.startswith("1.9.2.") or label.startswith("1.8.2."):
# Numbers not valid in this case, too few objects, so it
# we can just skip these...
logger.log_warning("Inapplicable model or MIP number skipped:",
label)
return label_to_input_cell_mapping
def extract_inputs_at_input_cells(input_cells, spreadsheet_tab):
"""Extract and return as a list values at the given input cells."""
values = []
if not isinstance(input_cells, list):
input_cells = [input_cells]
for index, input_cell in enumerate(input_cells):
user_input = spreadsheet_tab.cell(row=input_cell,
column=INPUT_COLUMN + 1).value
# Distinguish from Falsy values e.g. False and 0 as user input
if user_input is None: