def logo_in_signature():
from .images import favicon
from .. import __version__ as version
sig = Elem('div')
sig << Elem(
'img', {
'width': "14",
'height': "14",
'src': "data:image/png;base64,{}".format(favicon),
'style': 'position:relative;top:2px;'
})
sig << Elem('span', {'class': 'larch_name_signature'},
text=" Larch {}".format(version))
return sig
def __xml__(self):
z = Elem('div')
table = z.put('table', {'class': 'dataframe larch_dataframe'})
thead = table.put('thead')
for i in range(self.index.nlevels):
thead.put('th', text=self.index.names[i])
for c in self.columns:
thead.put('th', text=str(c))
tbody = table.put('tbody')
for i in self.index:
row = tbody.put('tr')
if self.index.nlevels == 1:
row.put('th', text=str(i))
else:
for ii in i:
row.put('th', text=str(ii))
for c in self.columns:
cell = self.loc[i, c]
try:
cell_content = cell.__xml__()
except AttributeError:
if isinstance(cell, float):
row.put('td', text="{0:.6g}".format(cell))
else:
row.put('td', text=str(cell))
else:
row.put('td') << cell_content
return z
def __xml__(self):
from xmle import Elem, Show
x = Elem('div')
t = x.elem('table', style="margin-top:1px;")
if len(self):
tr = t.elem('tr')
tr.elem('th', text="key")
tr.elem('th', text='value', style='text-align:left;')
for k, v in self.items():
tr = t.elem('tr')
tr.elem('td', text=str(k))
try:
if isinstance(v, str) and '\n' not in v and v[:1] != "#":
raise ValueError()
v_ = Show(v)
except (AttributeError, ValueError):
plaintext = pprint.pformat(v)
if isinstance(v, datetime.timedelta):
plaintext = str(v)
if "\n" in plaintext:
tr.elem('td',
style='text-align:left;').elem('pre',
text=plaintext)
else:
tr.elem('td', style='text-align:left;', text=plaintext)
else:
tr.elem('td', style='text-align:left;') << v_
else:
tr = t.elem('tr')
tr.elem('td', text="<empty>")
return x
def plot_as_svg_xhtml(
fig,
classname='figure',
headerlevel=2,
header=None,
anchor=1,
transparent=True,
tooltip=None,
bbox_extra_artists=None,
pad_inches=0.1,
**format,
):
existing_format_keys = list(format.keys())
for key in existing_format_keys:
if key.upper() != key: format[key.upper()] = format[key]
if 'GRAPHWIDTH' not in format and 'GRAPHHEIGHT' in format:
format['GRAPHWIDTH'] = format['GRAPHHEIGHT']
if 'GRAPHWIDTH' in format and 'GRAPHHEIGHT' not in format:
format['GRAPHHEIGHT'] = format['GRAPHWIDTH'] * .67
import xml.etree.ElementTree as ET
ET.register_namespace("", "http://www.w3.org/2000/svg")
ET.register_namespace("xlink", "http://www.w3.org/1999/xlink")
imgbuffer = BytesIO()
fig.savefig(
imgbuffer,
dpi=None,
facecolor="none",
edgecolor='w',
orientation='portrait',
papertype=None,
format='svg',
transparent=transparent,
bbox_inches="tight",
pad_inches=pad_inches,
bbox_extra_artists=bbox_extra_artists,
)
x = Elem("div", {'class': classname})
if header:
x.hn(headerlevel, header, anchor=anchor)
x << ET.fromstring(imgbuffer.getvalue().decode())
if tooltip is not None:
x[0][1].insert(0, Elem("title", text=tooltip))
return x
def floating_table_head():
floatThead = Elem(
tag="script",
attrib={
'src':
"https://cdnjs.cloudflare.com/ajax/libs/floatthead/2.0.3/jquery.floatThead.min.js",
})
floatTheadA = Elem(tag="script",
text="""
$( document ).ready(function() {
var $table = $('table.floatinghead');
$table.floatThead({ position: 'absolute' });
var $tabledf = $('table.dataframe');
$tabledf.floatThead({ position: 'absolute' });
});
$(window).on("hashchange", function () {
window.scrollTo(window.scrollX, window.scrollY - 50);
});
""")
return floatThead, floatTheadA
def _repr_html_(self):
from ..util.styles import _default_css_jupyter, _tooltipped_style_css
style_prefix = "<style>{}\n\n{}</style>\n".format(
_default_css_jupyter, _tooltipped_style_css)
from xmle import Elem
xsign = Elem("div", {'class': 'larch_head_tag'})
from .images import favicon
p = xsign.elem('p', {'style': 'float:left;margin-top:6px'})
p.elem('img', {
'width':
"32",
'height':
"32",
'src':
"data:image/png;base64,{}".format(favicon),
'style':
'float:left;position:relative;top:-3px;padding-right:0.2em;'
},
tail=f" {self.appname} ")
p.elem('span', {'class': 'larch_head_tag_ver'},
text=f" {self.version} ")
if not self.minimal:
p.elem('span', {'class': 'larch_head_tag_pth'},
text=f" {self.path} ")
from .images import camsyslogo_element
xsign << camsyslogo_element
if 'larch' in sys.modules:
from .images import georgiatechlogo_element
xsign << georgiatechlogo_element
if self.extra:
v = '\n│'.join(sys.version.split('\n'))
xsign.elem('br')
xinfo = xsign.elem('div', {
'class': 'larch_head_tag_more',
'style': 'margin-top:10px; padding:7px'
},
text=f'Python {v}')
xinfo.elem('br', tail=f"EXE - {sys.executable}")
xinfo.elem('br', tail=f"CWD - {os.getcwd()}")
xinfo.elem('br', tail=f"PATH - ")
ul = xinfo.elem('ul',
{'style': 'margin-top:0; margin-bottom:0;'})
for p in sys.path:
ul.elem('li', text=p)
return style_prefix + xsign.tostring()
def __xml__(self):
from xmle import Elem
x = Elem('div')
t = x.elem('table', style="margin-top:1px;")
if len(self):
tr = t.elem('tr')
tr.elem('th', text="key")
tr.elem('th', text='value', style='text-align:left;')
for k, v in self.items():
tr = t.elem('tr')
tr.elem('td', text=str(k))
try:
v_ = v.__xml__()
except AttributeError:
tr.elem('td', text=str(v), style='text-align:left;')
else:
tr.elem('td') << v_
else:
tr = t.elem('tr')
tr.elem('td', text="<empty>")
return x
def graph_to_figure(graph, output_format='svg', **format):
try:
import pygraphviz as viz
except ImportError:
import warnings
warnings.warn(
"pygraphviz module not installed, unable to draw nesting tree")
raise NotImplementedError(
"pygraphviz module not installed, unable to draw nesting tree")
existing_format_keys = list(format.keys())
for key in existing_format_keys:
if key.upper() != key: format[key.upper()] = format[key]
if 'SUPPRESSGRAPHSIZE' not in format:
if 'GRAPHWIDTH' not in format: format['GRAPHWIDTH'] = 6.5
if 'GRAPHHEIGHT' not in format: format['GRAPHHEIGHT'] = 4
if 'UNAVAILABLE' not in format: format['UNAVAILABLE'] = True
# x = XML_Builder("div", {'class':"nesting_graph larch_art"})
# x.h2("Nesting Structure", anchor=1, attrib={'class':'larch_art_xhtml'})
from io import BytesIO
if 'SUPPRESSGRAPHSIZE' not in format:
G = viz.AGraph(name='Tree',
directed=True,
size="{GRAPHWIDTH},{GRAPHHEIGHT}".format(**format))
else:
G = viz.AGraph(name='Tree', directed=True)
for n in graph.nodes:
nname = graph.nodes[n].get('name', n)
if nname == n:
G.add_node(n,
label='<{1}>'.format(n, nname),
style='rounded,solid',
shape='box')
else:
G.add_node(n,
label='<{1} <FONT COLOR="#999999">({0})</FONT>>'.format(
n, nname),
style='rounded,solid',
shape='box')
try:
graph.elementals
except AttributeError:
pass
else:
eG = G.add_subgraph(name='cluster_elemental',
nbunch=graph.elementals,
color='#cccccc',
bgcolor='#eeeeee',
label='Elemental Alternatives',
labelloc='b',
style='rounded,solid')
unavailable_nodes = set()
# if format['UNAVAILABLE']:
# if self.is_provisioned():
# try:
# for n, ncode in enumerate(self.alternative_codes()):
# if numpy.sum(self.Data('Avail'),axis=0)[n,0]==0: unavailable_nodes.add(ncode)
# except: raise
# try:
# legible_avail = not isinstance(self.df.queries.avail, str)
# except:
# legible_avail = False
# if legible_avail:
# for ncode,navail in self.df.queries.avail.items():
# try:
# if navail=='0': unavailable_nodes.add(ncode)
# except: raise
# eG.add_subgraph(name='cluster_elemental_unavailable', nbunch=unavailable_nodes, color='#bbbbbb', bgcolor='#dddddd',
# label='Unavailable Alternatives', labelloc='b', style='rounded,solid')
try:
G.add_node(graph.root_id, label="Root")
except AttributeError:
pass
up_nodes = set()
down_nodes = set()
for i, j in graph.edges:
G.add_edge(i, j)
down_nodes.add(j)
up_nodes.add(i)
pyg_imgdata = BytesIO()
try:
G.draw(pyg_imgdata, format=output_format,
prog='dot') # write postscript in k5.ps with neato layout
except ValueError as err:
if 'in path' in str(err):
import warnings
warnings.warn(str(err) + "; unable to draw nesting tree in report")
raise NotImplementedError()
from xmle import Elem
if output_format == 'svg':
import xml.etree.ElementTree as ET
ET.register_namespace("", "http://www.w3.org/2000/svg")
ET.register_namespace("xlink", "http://www.w3.org/1999/xlink")
result = ET.fromstring(pyg_imgdata.getvalue().decode())
else:
result = Elem('span',
attrib={'style': 'color:red'},
text=f"Unable to render output_format '{output_format}'")
x = Elem('div') << result
return x
def _repr_html_(self):
from xmle import Elem
x = Elem('div') << (self.__xml__())
return x.tostring()
def utility_functions(self, subset=None, resolve_parameters=False):
"""
Generate an XHTML output of the utility function(s).
Parameters
----------
subset : Collection, optional
A collection of alternative codes to include. This only has effect if
there are separate utility_co functions set by alternative. It is
recommended to use this parameter if there are a very large number of
alternatives, and the utility functions of most (or all) of them
can be effectively communicated by showing only a few.
resolve_parameters : bool, default False
Whether to resolve the parameters to the current (estimated) value
in the output.
Returns
-------
xmle.Elem
"""
self.unmangle()
from xmle import Elem
x = Elem('div')
t = x.elem('table',
style="margin-top:1px;",
attrib={'class': 'floatinghead'})
if len(self.utility_co):
# t.elem('caption', text=f"Utility Functions",
# style="caption-side:top;text-align:left;font-family:Roboto;font-weight:700;"
# "font-style:normal;font-size:100%;padding:0px;color:black;")
# iterate over all alternatives if a dataframes is attached and lists the alternatives
try:
if self.dataservice is not None:
alts = self.dataservice.alternative_codes()
elif self.dataframes is not None:
alts = self.dataframes.alternative_codes()
else:
alts = self.utility_co.keys()
except:
alts = self.utility_co.keys()
t_head = t.elem('thead')
tr = t_head.elem('tr')
tr.elem('th', text="alt")
tr.elem('th', text='formula', attrib={'style': 'text-align:left;'})
t_body = t.elem('tbody')
for j in alts:
if subset is None or j in subset:
tr = t_body.elem('tr')
tr.elem('td', text=str(j))
utilitycell = tr.elem('td',
attrib={'style': 'text-align:left;'})
utilitycell.elem('div')
anything = False
if len(self.utility_ca):
utilitycell[-1].tail = (utilitycell[-1].tail
or "") + " + "
utilitycell << list(
self.utility_ca.__xml__(
linebreaks=True,
resolve_parameters=self,
value_in_tooltips=not resolve_parameters))
anything = True
if j in self.utility_co:
v = self.utility_co[j]
if len(v):
if anything:
utilitycell << Elem('br')
utilitycell[-1].tail = (utilitycell[-1].tail
or "") + " + "
utilitycell << list(
v.__xml__(
linebreaks=True,
resolve_parameters=self,
value_in_tooltips=not resolve_parameters))
anything = True
if len(self.quantity_ca):
if anything:
utilitycell << Elem('br')
if self.quantity_scale:
utilitycell[-1].tail = (utilitycell[-1].tail
or "") + " + "
from .linear import ParameterRef_C
utilitycell << list(
ParameterRef_C(self.quantity_scale).__xml__(
resolve_parameters=self,
value_in_tooltips=not resolve_parameters))
utilitycell[-1].tail = (utilitycell[-1].tail
or "") + " * log("
else:
utilitycell[-1].tail = (utilitycell[-1].tail
or "") + " + log("
content = self.quantity_ca.__xml__(
linebreaks=True,
lineprefix=" ",
exponentiate_parameters=True,
resolve_parameters=self,
value_in_tooltips=not resolve_parameters)
utilitycell << list(content)
utilitycell.elem('br', tail=")")
else:
# there is no differentiation by alternatives, just give one formula
# t.elem('caption', text=f"Utility Function",
# style="caption-side:top;text-align:left;font-family:Roboto;font-weight:700;"
# "font-style:normal;font-size:100%;padding:0px;color:black;")
tr = t.elem('tr')
utilitycell = tr.elem('td', attrib={'style': 'text-align:left;'})
utilitycell.elem('div')
anything = False
if len(self.utility_ca):
utilitycell[-1].tail = (utilitycell[-1].tail or "") + " + "
utilitycell << list(
self.utility_ca.__xml__(
linebreaks=True,
resolve_parameters=self,
value_in_tooltips=not resolve_parameters))
anything = True
if len(self.quantity_ca):
if anything:
utilitycell << Elem('br')
if self.quantity_scale:
utilitycell[-1].tail = (utilitycell[-1].tail or "") + " + "
from .linear import ParameterRef_C
utilitycell << list(
ParameterRef_C(self.quantity_scale).__xml__(
resolve_parameters=self,
value_in_tooltips=not resolve_parameters))
utilitycell[-1].tail = (utilitycell[-1].tail
or "") + " * log("
else:
utilitycell[-1].tail = (utilitycell[-1].tail
or "") + " + log("
content = self.quantity_ca.__xml__(
linebreaks=True,
lineprefix=" ",
exponentiate_parameters=True,
resolve_parameters=self,
value_in_tooltips=not resolve_parameters)
utilitycell << list(content)
utilitycell.elem('br', tail=")")
return x
def tooltipped_style():
return Elem('style',
attrib={'type': "text/css"},
text=_tooltipped_style_css)
def larch_style():
return Elem(
tag='style',
text=_default_css,
)
def __xml__(self, no_data=False, descriptions=True, dictionaries=False):
from xmle import Elem
x = Elem('div')
t = x.elem('table', style="margin-top:1px;")
t.elem(
'caption',
text=f"<larch.{self.__class__.__name__}>",
style=
"caption-side:top;text-align:left;font-family:Roboto;font-weight:700;font-style:normal;font-size:100%;padding:0px;"
)
#
try:
ident = self.ident
except AttributeError:
pass
else:
tr = t.elem('tr')
tr.elem('th', text='ident')
tr.elem('td', text=ident)
#
try:
filename = self.filename
except AttributeError:
pass
else:
tr = t.elem('tr')
tr.elem('th', text='file')
tr.elem('td', text=truncate_path_for_display(filename))
#
try:
filemode = self.filemode
except AttributeError:
pass
else:
tr = t.elem('tr')
tr.elem('th', text='mode')
tr.elem('td', text=truncate_path_for_display(self.filemode))
#
try:
v_pathname = self._groupnode._v_pathname
except AttributeError:
pass
else:
if self._groupnode._v_pathname != "/":
tr = t.elem('tr')
tr.elem('th', text='node')
tr.elem('td', text=self._groupnode._v_pathname)
#
try:
str_shape = str(self.shape)
except NoKnownShape:
pass
else:
tr = t.elem('tr')
tr.elem('th', text='shape')
tr.elem('td', text=str_shape)
#
try:
str_shape = str(self.metashape)
except (NoKnownShape, AttributeError):
pass
else:
tr = t.elem('tr')
tr.elem('th', text='metashape')
tr.elem('td', text=str_shape)
#
try:
str_durable_mask = f"0x{self.durable_mask:X}"
except (AttributeError):
pass
else:
if str_durable_mask != '0x0':
tr = t.elem('tr')
tr.elem('th', text='durable_mask')
tr.elem('td', text=str_durable_mask)
#
if not no_data:
if len(self._groupnode._v_children):
tr = t.elem('tr')
tr.elem('th', text='data', style='vertical-align:top;')
td = tr.elem('td')
t1 = td.elem('table', cls='dictionary')
t1head = t1.elem('thead')
t1headr = t1head.elem('tr')
t1headr.elem('th', text='name')
t1headr.elem('th', text='dtype')
if descriptions:
t1headr.elem('th', text='description')
any_sources = 0
for i in sorted(self._groupnode._v_children.keys()):
try:
node_dtype = self._groupnode._v_children[i].dtype
except (tb.NoSuchNodeError, AttributeError):
node_dtype = "<no dtype>"
if i not in _reserved_names_:
tr1 = t1.elem('tr')
tr1.elem('td', text=i)
tr1.elem('td', text=node_dtype)
if descriptions:
try:
title = self._groupnode._v_children[
i]._v_attrs['TITLE']
except:
title = ""
else:
tr1.elem('td', text=title)
try:
orig_source = self._groupnode._v_children[
i]._v_attrs['ORIGINAL_SOURCE']
except:
pass
else:
tr1.elem('td', text=orig_source)
any_sources += 1
if any_sources:
t1headr.elem('th', text='source')
else:
tr = t.elem('tr')
tr.elem('th', text='data', style='vertical-align:top;')
tr.elem('td', text='<empty>')
return x
def make_png(
content,
dpi=None,
compress=True,
output='Elem',
close_after=True,
pad_inches=0.1,
facecolor=None,
return_size=False,
return_dpi=False,
):
_bytes_io = None
_img = None
_size = None
if hasattr(content, '_repr_png_'):
content = content._repr_png_()
if isinstance(content, bytes):
_bytes_io = io.BytesIO(content)
if 'matplotlib' in str(type(content)):
from matplotlib import pyplot as plt
import matplotlib.figure
if not isinstance(content, matplotlib.figure.Figure):
try:
content = content.get_figure()
except AttributeError:
if not hasattr(content, 'savefig'):
raise TypeError(
'matplotlib content must provide `get_figure` or `savefig` method.'
)
# content is a Figure or otherwise has a savefig method
try:
fig_number = content.number
except AttributeError:
fig_number = None
if facecolor is None:
try:
facecolor = content.get_facecolor()
except:
facecolor = 'w'
try:
edgecolor = content.get_edgecolor()
except:
edgecolor = 'none'
_bytes_io = io.BytesIO()
content.savefig(
_bytes_io,
dpi=dpi,
orientation='portrait',
format='png',
bbox_inches='tight',
pad_inches=pad_inches,
facecolor=facecolor,
edgecolor=edgecolor,
)
if close_after and fig_number is not None:
plt.close(fig_number)
if _bytes_io.getvalue()[:4] == b'\x89PNG':
_img = Image.open(_bytes_io)
dpi = _img.info.get('dpi', dpi)
if dpi is None:
dpi = [96, 96]
if compress:
_img = _img.convert(mode='P', palette='ADAPTIVE')
_bytes_io = io.BytesIO()
_img.save(_bytes_io, dpi=dpi, format='png')
_size = _img.size
else:
raise ValueError("Not valid PNG data")
if output.lower() == 'elem':
result = Elem(
tag='img',
src="data:image/png;base64,{}".format(
base64.standard_b64encode(_bytes_io.getvalue()).decode()),
)
elif output.lower() == 'bytesio':
result = _bytes_io
else:
result = _img
if return_size:
if isinstance(result, tuple):
result = (*result, _size)
else:
result = result, _size
if return_dpi:
if isinstance(result, tuple):
result = (*result, dpi)
else:
result = result, dpi
return result
eye = 'data:image/png;base64,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'
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"
camsyslogo = 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"
from xmle import Elem
camsyslogo_white = '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'
georgiatechlogo_element = Elem(
'img', {
'src':
"data:image/png;base64,{}".format(georgiatechlogo),
'style':
'float:right;max-height:40px;margin-top:0;margin-right:20px;margin-left:20px'
})
camsyslogo_element = Elem(
'img', {
'src': "data:image/png;base64,{}".format(camsyslogo),
'style': 'float:right;max-height:44px;margin-top:0'
})
_use_local_logo = False
def local_logo(filename=None):
return camsyslogo_white
def __parameter_table_section(self, pname):
from xmle import Elem
pname_str = str(pname)
pf = self.pf
# if pname in self.rename_parameters:
# colspan = 0
# if 'std err' in pf.columns:
# colspan += 1
# if 't stat' in pf.columns:
# colspan += 1
# if 'nullvalue' in pf.columns:
# colspan += 1
# return [
# Elem('td', text="{:.4g}".format(pf.loc[self.rename_parameters[pname],'value'])),
# Elem('td', text="= "+self.rename_parameters[pname], colspan=str(colspan)),
# ]
if pf.loc[pname_str, 'holdfast']:
colspan = 0
if 'std err' in pf.columns:
colspan += 1
if 't stat' in pf.columns:
colspan += 1
if 'nullvalue' in pf.columns:
colspan += 1
# if pf.loc[pname_str,'holdfast'] == holdfast_reasons.asc_but_never_chosen:
# return [
# Elem('td', text="{:.4g}".format(pf.loc[pname_str,'value'])),
# Elem('td', text="fixed value, never chosen", colspan=str(colspan)),
# ]
# elif pf.loc[pname_str, 'holdfast'] == holdfast_reasons.snap_to_constant_eq:
# return [
# Elem('td', text="{:.4g}".format(pf.loc[pname_str, 'value'])),
# Elem('td', text="fixed value", colspan=str(colspan)),
# ]
# elif pf.loc[pname_str, 'holdfast'] == holdfast_reasons.snap_to_constant_le:
# return [
# Elem('td', text="{:.4g}".format(pf.loc[pname_str, 'value'])),
# Elem('td', text="≤ {:.4g}".format(pf.loc[pname_str, 'value']), colspan=str(colspan)),
# ]
# elif pf.loc[pname_str, 'holdfast'] == holdfast_reasons.snap_to_constant_ge:
# return [
# Elem('td', text="{:.4g}".format(pf.loc[pname_str, 'value'])),
# Elem('td', text="≥ {:.4g}".format(pf.loc[pname_str, 'value']), colspan=str(colspan)),
# ]
# elif pf.loc[pname_str, 'note'] != "" and not pandas.isnull(pf.loc[pname_str, 'note']):
# return [
# Elem('td', text="{:.4g}".format(pf.loc[pname_str,'value'])),
# Elem('td', text=pf.loc[pname_str, 'note'], colspan=str(colspan)),
# ]
# else:
return [
Elem('td', text="{:.4g}".format(pf.loc[pname_str, 'value'])),
Elem('td',
text="fixed value",
colspan=str(colspan),
style="text-align: left;"),
]
else:
result = [
Elem('td', text="{:.4g}".format(pf.loc[pname_str, 'value']))
]
if 'std err' in pf.columns:
result += [
Elem('td',
text="{:#.3g}".format(pf.loc[pname_str, 'std err'])),
]
if 't stat' in pf.columns:
result += [
Elem('td',
text="{:#.2f}".format(pf.loc[pname_str, 't stat'])),
]
if 'nullvalue' in pf.columns:
result += [
Elem('td',
text="{:#.2g}".format(pf.loc[pname_str,
'nullvalue'])),
]
return result
