def __init__(self, filename):
super(SqliteCaseReader, self).__init__(filename)
if filename is not None:
if not is_valid_sqlite3_db(filename):
raise IOError('File does not contain a valid '
'sqlite database ({0})'.format(filename))
with SqliteDict(self.filename, 'metadata', flag='r') as db:
self.format_version = db.get('format_version', None)
self._load()
self.num_cases = len(self._case_keys)
def view_model(problem_or_filename,
outfile='partition_tree_n2.html',
show_browser=True,
offline=True,
embed=False):
"""
Generates a self-contained html file containing a tree viewer
of the specified type. Optionally pops up a web browser to
view the file.
Args
----
problem_or_filename : Either a Problem() or a string
Problem() : The Problem (after problem.setup()) for the desired tree.
string : The filename of the case recorder file containing the data required to build the tree.
outfile : str, optional
The name of the output html file. Defaults to 'partition_tree_n2.html'.
show_browser : bool, optional
If True, pop up the system default web browser to view the generated html file.
Defaults to True.
offline : bool, optional
If True, embed the javascript d3 library into the generated html file so that the tree can be viewed
offline without an internet connection. Otherwise if False, have the html request the latest d3 file
from https://d3js.org/d3.v4.min.js when opening the html file.
Defaults to True.
embed : bool, optional
If True, export only the innerHTML that is between the body tags, used for embedding the viewer into another html file.
If False, create a standalone HTML file that has the DOCTYPE, html, head, meta, and body tags.
Defaults to False.
"""
viewer = 'partition_tree_n2.template'
code_dir = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(code_dir, viewer), "r") as f:
template = f.read()
html_begin_tags = (
"<!DOCTYPE html>\n"
"<html>\n"
"<head>\n"
" <meta http-equiv=\"Content-Type\" content=\"text/html; charset=UTF-8\">\n"
"</head>\n"
"<body>\n")
html_end_tags = ("</body>\n" "</html>\n")
display_none_attr = ""
if embed:
html_begin_tags = html_end_tags = ""
display_none_attr = " style=\"display:none\""
d3_library = "<script src=\"https://d3js.org/d3.v4.min.js\" charset=\"utf-8\"></script>"
if offline:
with open(os.path.join(code_dir, 'd3.v4.min.js'), "r") as f:
d3_library = "<script type=\"text/javascript\"> %s </script>" % (
f.read())
if isinstance(problem_or_filename, Problem):
model_viewer_data = get_model_viewer_data(problem_or_filename)
else:
# Do not know file type. Try opening to see what works
file_type = None
if is_valid_sqlite3_db(problem_or_filename):
db = SqliteDict(filename=problem_or_filename,
flag='r',
tablename='metadata')
file_type = "sqlite"
else:
try:
hdf = h5py.File(problem_or_filename, 'r')
file_type = 'hdf5'
except:
raise ValueError(
"The given filename is not one of the supported file formats: sqlite or hdf5"
)
if file_type == "sqlite":
model_viewer_data = db['model_viewer_data']
elif file_type == "hdf5":
metadata = hdf.get('metadata', None)
model_viewer_data = pickle.loads(
metadata.get('model_viewer_data').value)
tree_json = json.dumps(model_viewer_data['tree'])
conns_json = json.dumps(model_viewer_data['connections_list'])
with open(outfile, 'w') as f:
f.write(template % (html_begin_tags, display_none_attr, d3_library,
tree_json, conns_json, html_end_tags))
if show_browser:
from openmdao.devtools.webview import webview
webview(outfile)
def view_model(problem_or_filename, outfile='partition_tree_n2.html', show_browser=True, offline=True, embed=False):
"""
Generates a self-contained html file containing a tree viewer
of the specified type. Optionally pops up a web browser to
view the file.
Args
----
problem_or_filename : Either a Problem() or a string
Problem() : The Problem (after problem.setup()) for the desired tree.
string : The filename of the case recorder file containing the data required to build the tree.
outfile : str, optional
The name of the output html file. Defaults to 'partition_tree_n2.html'.
show_browser : bool, optional
If True, pop up the system default web browser to view the generated html file.
Defaults to True.
offline : bool, optional
If True, embed the javascript d3 library into the generated html file so that the tree can be viewed
offline without an internet connection. Otherwise if False, have the html request the latest d3 file
from https://d3js.org/d3.v4.min.js when opening the html file.
Defaults to True.
embed : bool, optional
If True, export only the innerHTML that is between the body tags, used for embedding the viewer into another html file.
If False, create a standalone HTML file that has the DOCTYPE, html, head, meta, and body tags.
Defaults to False.
"""
viewer = 'partition_tree_n2.template'
code_dir = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(code_dir, viewer), "r") as f:
template = f.read()
html_begin_tags = ("<!DOCTYPE html>\n"
"<html>\n"
"<head>\n"
" <meta http-equiv=\"Content-Type\" content=\"text/html; charset=UTF-8\">\n"
"</head>\n"
"<body>\n")
html_end_tags = ("</body>\n"
"</html>\n")
display_none_attr = ""
if embed:
html_begin_tags = html_end_tags = ""
display_none_attr = " style=\"display:none\""
d3_library = "<script src=\"https://d3js.org/d3.v4.min.js\" charset=\"utf-8\"></script>"
if offline:
with open(os.path.join(code_dir, 'd3.v4.min.js'), "r") as f:
d3_library = "<script type=\"text/javascript\"> %s </script>" % (f.read())
with open(os.path.join(code_dir, "fontello.woff"), "rb") as f:
encoded_font = str(base64.b64encode(f.read()).decode("ascii"))
with open(os.path.join(code_dir, 'awesomplete.css'), "r") as f:
awesomplete_css = "%s" % (f.read())
with open(os.path.join(code_dir, 'awesomplete.js'), "r") as f:
awesomplete_js = "%s" % (f.read())
if isinstance(problem_or_filename, Problem):
model_viewer_data = get_model_viewer_data(problem_or_filename)
else:
# Do not know file type. Try opening to see what works
file_type = None
if is_valid_sqlite3_db(problem_or_filename):
db = SqliteDict(filename=problem_or_filename, flag='r', tablename='metadata')
file_type = "sqlite"
else:
try:
hdf = h5py.File(problem_or_filename, 'r')
file_type = 'hdf5'
except:
raise ValueError("The given filename is not one of the supported file formats: sqlite or hdf5")
if file_type == "sqlite":
model_viewer_data = db['model_viewer_data']
elif file_type == "hdf5":
metadata = hdf.get('metadata', None)
model_viewer_data = pickle.loads(metadata.get('model_viewer_data').value)
tree_json = json.dumps(model_viewer_data['tree'])
conns_json = json.dumps(model_viewer_data['connections_list'])
with open(outfile, 'w') as f:
f.write(template % (html_begin_tags, awesomplete_css, encoded_font, display_none_attr, d3_library, awesomplete_js, tree_json, conns_json, html_end_tags))
if show_browser:
from openmdao.devtools.webview import webview
webview(outfile)
