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eaton-lab/toytree
|
toytree/newick.py
|
_get_features_string
|
def _get_features_string(self, features=None):
""" Generates the extended newick string NHX with extra data about a node."""
string = ""
if features is None:
features = []
elif features == []:
features = self.features
for pr in features:
if hasattr(self, pr):
raw = getattr(self, pr)
if type(raw) in ITERABLE_TYPES:
raw = '|'.join([str(i) for i in raw])
elif type(raw) == dict:
raw = '|'.join(
map(lambda x,y: "%s-%s" %(x, y), six.iteritems(raw)))
elif type(raw) == str:
pass
else:
raw = str(raw)
value = re.sub("["+_ILEGAL_NEWICK_CHARS+"]", "_", \
raw)
if string != "":
string +=":"
string +="%s=%s" %(pr, str(value))
if string != "":
string = "[&&NHX:"+string+"]"
return string
|
python
|
def _get_features_string(self, features=None):
""" Generates the extended newick string NHX with extra data about a node."""
string = ""
if features is None:
features = []
elif features == []:
features = self.features
for pr in features:
if hasattr(self, pr):
raw = getattr(self, pr)
if type(raw) in ITERABLE_TYPES:
raw = '|'.join([str(i) for i in raw])
elif type(raw) == dict:
raw = '|'.join(
map(lambda x,y: "%s-%s" %(x, y), six.iteritems(raw)))
elif type(raw) == str:
pass
else:
raw = str(raw)
value = re.sub("["+_ILEGAL_NEWICK_CHARS+"]", "_", \
raw)
if string != "":
string +=":"
string +="%s=%s" %(pr, str(value))
if string != "":
string = "[&&NHX:"+string+"]"
return string
|
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] |
train
|
https://github.com/eaton-lab/toytree/blob/0347ed2098acc5f707fadf52a0ecd411a6d1859c/toytree/newick.py#L405-L434
|
doakey3/DashTable
|
dashtable/data2md/get_column_width.py
|
get_column_width
|
def get_column_width(column, table):
"""
Get the character width of a column in a table
Parameters
----------
column : int
The column index analyze
table : list of lists of str
The table of rows of strings. For this to be accurate, each
string must only be 1 line long.
Returns
-------
width : int
"""
width = 3
for row in range(len(table)):
cell_width = len(table[row][column])
if cell_width > width:
width = cell_width
return width
|
python
|
def get_column_width(column, table):
"""
Get the character width of a column in a table
Parameters
----------
column : int
The column index analyze
table : list of lists of str
The table of rows of strings. For this to be accurate, each
string must only be 1 line long.
Returns
-------
width : int
"""
width = 3
for row in range(len(table)):
cell_width = len(table[row][column])
if cell_width > width:
width = cell_width
return width
|
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Get the character width of a column in a table
Parameters
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column : int
The column index analyze
table : list of lists of str
The table of rows of strings. For this to be accurate, each
string must only be 1 line long.
Returns
-------
width : int
|
[
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] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2md/get_column_width.py#L1-L24
|
eaton-lab/toytree
|
toytree/html.py
|
get_text_mark
|
def get_text_mark(ttree):
""" makes a simple Text Mark object"""
if ttree._orient in ["right"]:
angle = 0.
ypos = ttree.verts[-1*len(ttree.tree):, 1]
if ttree._kwargs["tip_labels_align"]:
xpos = [ttree.verts[:, 0].max()] * len(ttree.tree)
start = xpos
finish = ttree.verts[-1*len(ttree.tree):, 0]
align_edges = np.array([(i, i+len(xpos)) for i in range(len(xpos))])
align_verts = np.array(zip(start, ypos) + zip(finish, ypos))
else:
xpos = ttree.verts[-1*len(ttree.tree):, 0]
elif ttree._orient in ['down']:
angle = -90.
xpos = ttree.verts[-1*len(ttree.tree):, 0]
if ttree._kwargs["tip_labels_align"]:
ypos = [ttree.verts[:, 1].min()] * len(ttree.tree)
start = ypos
finish = ttree.verts[-1*len(ttree.tree):, 1]
align_edges = np.array([(i, i+len(ypos)) for i in range(len(ypos))])
align_verts = np.array(zip(xpos, start) + zip(xpos, finish))
else:
ypos = ttree.verts[-1*len(ttree.tree):, 1]
table = toyplot.data.Table()
table['x'] = toyplot.require.scalar_vector(xpos)
table['y'] = toyplot.require.scalar_vector(ypos, table.shape[0])
table['text'] = toyplot.broadcast.pyobject(ttree.get_tip_labels(), table.shape[0])
table["angle"] = toyplot.broadcast.scalar(angle, table.shape[0])
table["opacity"] = toyplot.broadcast.scalar(1.0, table.shape[0])
table["title"] = toyplot.broadcast.pyobject(None, table.shape[0])
style = toyplot.style.require(ttree._kwargs["tip_labels_style"],
allowed=toyplot.style.allowed.text)
default_color = [toyplot.color.black]
color = toyplot.color.broadcast(
colors=ttree._kwargs["tip_labels_color"],
shape=(table.shape[0], 1),
default=default_color,
)
table["fill"] = color[:, 0]
text_mark = toyplot.mark.Text(
coordinate_axes=['x', 'y'],
table=table,
coordinates=['x', 'y'],
text=["text"],
angle=["angle"],
fill=["fill"],
opacity=["opacity"],
title=["title"],
style=style,
annotation=True,
filename=None
)
return text_mark
|
python
|
def get_text_mark(ttree):
""" makes a simple Text Mark object"""
if ttree._orient in ["right"]:
angle = 0.
ypos = ttree.verts[-1*len(ttree.tree):, 1]
if ttree._kwargs["tip_labels_align"]:
xpos = [ttree.verts[:, 0].max()] * len(ttree.tree)
start = xpos
finish = ttree.verts[-1*len(ttree.tree):, 0]
align_edges = np.array([(i, i+len(xpos)) for i in range(len(xpos))])
align_verts = np.array(zip(start, ypos) + zip(finish, ypos))
else:
xpos = ttree.verts[-1*len(ttree.tree):, 0]
elif ttree._orient in ['down']:
angle = -90.
xpos = ttree.verts[-1*len(ttree.tree):, 0]
if ttree._kwargs["tip_labels_align"]:
ypos = [ttree.verts[:, 1].min()] * len(ttree.tree)
start = ypos
finish = ttree.verts[-1*len(ttree.tree):, 1]
align_edges = np.array([(i, i+len(ypos)) for i in range(len(ypos))])
align_verts = np.array(zip(xpos, start) + zip(xpos, finish))
else:
ypos = ttree.verts[-1*len(ttree.tree):, 1]
table = toyplot.data.Table()
table['x'] = toyplot.require.scalar_vector(xpos)
table['y'] = toyplot.require.scalar_vector(ypos, table.shape[0])
table['text'] = toyplot.broadcast.pyobject(ttree.get_tip_labels(), table.shape[0])
table["angle"] = toyplot.broadcast.scalar(angle, table.shape[0])
table["opacity"] = toyplot.broadcast.scalar(1.0, table.shape[0])
table["title"] = toyplot.broadcast.pyobject(None, table.shape[0])
style = toyplot.style.require(ttree._kwargs["tip_labels_style"],
allowed=toyplot.style.allowed.text)
default_color = [toyplot.color.black]
color = toyplot.color.broadcast(
colors=ttree._kwargs["tip_labels_color"],
shape=(table.shape[0], 1),
default=default_color,
)
table["fill"] = color[:, 0]
text_mark = toyplot.mark.Text(
coordinate_axes=['x', 'y'],
table=table,
coordinates=['x', 'y'],
text=["text"],
angle=["angle"],
fill=["fill"],
opacity=["opacity"],
title=["title"],
style=style,
annotation=True,
filename=None
)
return text_mark
|
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train
|
https://github.com/eaton-lab/toytree/blob/0347ed2098acc5f707fadf52a0ecd411a6d1859c/toytree/html.py#L196-L253
|
eaton-lab/toytree
|
toytree/html.py
|
get_edge_mark
|
def get_edge_mark(ttree):
""" makes a simple Graph Mark object"""
## tree style
if ttree._kwargs["tree_style"] in ["c", "cladogram"]:
a=ttree.edges
vcoordinates=ttree.verts
else:
a=ttree._lines
vcoordinates=ttree._coords
## fixed args
along='x'
vmarker='o'
vcolor=None
vlshow=False
vsize=0.
estyle=ttree._kwargs["edge_style"]
## get axes
layout = toyplot.layout.graph(a, vcoordinates=vcoordinates)
along = toyplot.require.value_in(along, ["x", "y"])
if along == "x":
coordinate_axes = ["x", "y"]
elif along == "y":
coordinate_axes = ["y", "x"]
## broadcast args along axes
vlabel = layout.vids
vmarker = toyplot.broadcast.pyobject(vmarker, layout.vcount)
vsize = toyplot.broadcast.scalar(vsize, layout.vcount)
estyle = toyplot.style.require(estyle, allowed=toyplot.style.allowed.line)
## fixed args
vcolor = toyplot.color.broadcast(colors=None, shape=layout.vcount, default=toyplot.color.black)
vopacity = toyplot.broadcast.scalar(1.0, layout.vcount)
vtitle = toyplot.broadcast.pyobject(None, layout.vcount)
vstyle = None
vlstyle = None
## this could be modified in the future to allow diff color edges
ecolor = toyplot.color.broadcast(colors=None, shape=layout.ecount, default=toyplot.color.black)
ewidth = toyplot.broadcast.scalar(1.0, layout.ecount)
eopacity = toyplot.broadcast.scalar(1.0, layout.ecount)
hmarker = toyplot.broadcast.pyobject(None, layout.ecount)
mmarker = toyplot.broadcast.pyobject(None, layout.ecount)
mposition = toyplot.broadcast.scalar(0.5, layout.ecount)
tmarker = toyplot.broadcast.pyobject(None, layout.ecount)
## tables are required if I don't want to edit the class
vtable = toyplot.data.Table()
vtable["id"] = layout.vids
for axis, coordinates in zip(coordinate_axes, layout.vcoordinates.T):
vtable[axis] = coordinates
#_mark_exportable(vtable, axis)
vtable["label"] = vlabel
vtable["marker"] = vmarker
vtable["size"] = vsize
vtable["color"] = vcolor
vtable["opacity"] = vopacity
vtable["title"] = vtitle
etable = toyplot.data.Table()
etable["source"] = layout.edges.T[0]
#_mark_exportable(etable, "source")
etable["target"] = layout.edges.T[1]
#_mark_exportable(etable, "target")
etable["shape"] = layout.eshapes
etable["color"] = ecolor
etable["width"] = ewidth
etable["opacity"] = eopacity
etable["hmarker"] = hmarker
etable["mmarker"] = mmarker
etable["mposition"] = mposition
etable["tmarker"] = tmarker
edge_mark = toyplot.mark.Graph(
coordinate_axes=['x', 'y'],
ecolor=["color"],
ecoordinates=layout.ecoordinates,
efilename=None,
eopacity=["opacity"],
eshape=["shape"],
esource=["source"],
estyle=estyle,
etable=etable,
etarget=["target"],
ewidth=["width"],
hmarker=["hmarker"],
mmarker=["mmarker"],
mposition=["mposition"],
tmarker=["tmarker"],
vcolor=["color"],
vcoordinates=['x', 'y'],
vfilename=None,
vid=["id"],
vlabel=["label"],
vlshow=False,
vlstyle=None,
vmarker=["marker"],
vopacity=["opacity"],
vsize=["size"],
vstyle=None,
vtable=vtable,
vtitle=["title"],
)
return edge_mark
|
python
|
def get_edge_mark(ttree):
""" makes a simple Graph Mark object"""
## tree style
if ttree._kwargs["tree_style"] in ["c", "cladogram"]:
a=ttree.edges
vcoordinates=ttree.verts
else:
a=ttree._lines
vcoordinates=ttree._coords
## fixed args
along='x'
vmarker='o'
vcolor=None
vlshow=False
vsize=0.
estyle=ttree._kwargs["edge_style"]
## get axes
layout = toyplot.layout.graph(a, vcoordinates=vcoordinates)
along = toyplot.require.value_in(along, ["x", "y"])
if along == "x":
coordinate_axes = ["x", "y"]
elif along == "y":
coordinate_axes = ["y", "x"]
## broadcast args along axes
vlabel = layout.vids
vmarker = toyplot.broadcast.pyobject(vmarker, layout.vcount)
vsize = toyplot.broadcast.scalar(vsize, layout.vcount)
estyle = toyplot.style.require(estyle, allowed=toyplot.style.allowed.line)
## fixed args
vcolor = toyplot.color.broadcast(colors=None, shape=layout.vcount, default=toyplot.color.black)
vopacity = toyplot.broadcast.scalar(1.0, layout.vcount)
vtitle = toyplot.broadcast.pyobject(None, layout.vcount)
vstyle = None
vlstyle = None
## this could be modified in the future to allow diff color edges
ecolor = toyplot.color.broadcast(colors=None, shape=layout.ecount, default=toyplot.color.black)
ewidth = toyplot.broadcast.scalar(1.0, layout.ecount)
eopacity = toyplot.broadcast.scalar(1.0, layout.ecount)
hmarker = toyplot.broadcast.pyobject(None, layout.ecount)
mmarker = toyplot.broadcast.pyobject(None, layout.ecount)
mposition = toyplot.broadcast.scalar(0.5, layout.ecount)
tmarker = toyplot.broadcast.pyobject(None, layout.ecount)
## tables are required if I don't want to edit the class
vtable = toyplot.data.Table()
vtable["id"] = layout.vids
for axis, coordinates in zip(coordinate_axes, layout.vcoordinates.T):
vtable[axis] = coordinates
#_mark_exportable(vtable, axis)
vtable["label"] = vlabel
vtable["marker"] = vmarker
vtable["size"] = vsize
vtable["color"] = vcolor
vtable["opacity"] = vopacity
vtable["title"] = vtitle
etable = toyplot.data.Table()
etable["source"] = layout.edges.T[0]
#_mark_exportable(etable, "source")
etable["target"] = layout.edges.T[1]
#_mark_exportable(etable, "target")
etable["shape"] = layout.eshapes
etable["color"] = ecolor
etable["width"] = ewidth
etable["opacity"] = eopacity
etable["hmarker"] = hmarker
etable["mmarker"] = mmarker
etable["mposition"] = mposition
etable["tmarker"] = tmarker
edge_mark = toyplot.mark.Graph(
coordinate_axes=['x', 'y'],
ecolor=["color"],
ecoordinates=layout.ecoordinates,
efilename=None,
eopacity=["opacity"],
eshape=["shape"],
esource=["source"],
estyle=estyle,
etable=etable,
etarget=["target"],
ewidth=["width"],
hmarker=["hmarker"],
mmarker=["mmarker"],
mposition=["mposition"],
tmarker=["tmarker"],
vcolor=["color"],
vcoordinates=['x', 'y'],
vfilename=None,
vid=["id"],
vlabel=["label"],
vlshow=False,
vlstyle=None,
vmarker=["marker"],
vopacity=["opacity"],
vsize=["size"],
vstyle=None,
vtable=vtable,
vtitle=["title"],
)
return edge_mark
|
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] |
makes a simple Graph Mark object
|
[
"makes",
"a",
"simple",
"Graph",
"Mark",
"object"
] |
train
|
https://github.com/eaton-lab/toytree/blob/0347ed2098acc5f707fadf52a0ecd411a6d1859c/toytree/html.py#L257-L363
|
eaton-lab/toytree
|
toytree/html.py
|
split_styles
|
def split_styles(mark):
""" get shared styles """
markers = [mark._table[key] for key in mark._marker][0]
nstyles = []
for m in markers:
## fill and stroke are already rgb() since already in markers
msty = toyplot.style.combine({
"fill": m.mstyle['fill'],
"stroke": m.mstyle['stroke'],
"opacity": m.mstyle["fill-opacity"],
}, m.mstyle)
msty = _color_fixup(msty)
nstyles.append(msty)
## uses 'marker.size' so we need to loop over it
lstyles = []
for m in markers:
lsty = toyplot.style.combine({
"font-family": "Helvetica",
"-toyplot-vertical-align": "middle",
"fill": toyplot.color.black,
"font-size": "%rpx" % (m.size * 0.75),
"stroke": "none",
"text-anchor": "middle",
}, m.lstyle)
## update fonts
fonts = toyplot.font.ReportlabLibrary()
layout = toyplot.text.layout(m.label, lsty, fonts)
lsty = _color_fixup(layout.style)
lstyles.append(lsty)
nallkeys = set(itertools.chain(*[i.keys() for i in nstyles]))
lallkeys = set(itertools.chain(*[i.keys() for i in lstyles]))
nuniquekeys = []
nsharedkeys = []
for key in nallkeys:
vals = [nstyles[i].get(key) for i in range(len(nstyles))]
if len(set(vals)) > 1:
nuniquekeys.append(key)
else:
nsharedkeys.append(key)
luniquekeys = []
lsharedkeys = []
for key in lallkeys:
vals = [lstyles[i].get(key) for i in range(len(lstyles))]
if len(set(vals)) > 1:
luniquekeys.append(key)
else:
lsharedkeys.append(key)
## keys shared between mark and text markers
repeated = set(lsharedkeys).intersection(set(nsharedkeys))
for repeat in repeated:
## if same then keep only one copy of it
lidx = lsharedkeys.index(repeat)
nidx = nsharedkeys.index(repeat)
if lsharedkeys[lidx] == nsharedkeys[nidx]:
lsharedkeys.remove(repeat)
else:
lsharedkeys.remove(repeat)
luniquekeys.append(repeat)
nsharedkeys.remove(repeat)
nuniquekeys.append(repeat)
## check node values
natt = ["%s:%s" % (key, nstyles[0][key]) for key in sorted(nsharedkeys)]
latt = ["%s:%s" % (key, lstyles[0][key]) for key in sorted(lsharedkeys)]
shared_styles = ";".join(natt+latt)
unique_styles = {
"node": [{k:v for k,v in nstyles[idx].items() if k in nuniquekeys} for idx in range(len(markers))],
"text": [{k:v for k,v in lstyles[idx].items() if k in luniquekeys} for idx in range(len(markers))]
}
return shared_styles, unique_styles
|
python
|
def split_styles(mark):
""" get shared styles """
markers = [mark._table[key] for key in mark._marker][0]
nstyles = []
for m in markers:
## fill and stroke are already rgb() since already in markers
msty = toyplot.style.combine({
"fill": m.mstyle['fill'],
"stroke": m.mstyle['stroke'],
"opacity": m.mstyle["fill-opacity"],
}, m.mstyle)
msty = _color_fixup(msty)
nstyles.append(msty)
## uses 'marker.size' so we need to loop over it
lstyles = []
for m in markers:
lsty = toyplot.style.combine({
"font-family": "Helvetica",
"-toyplot-vertical-align": "middle",
"fill": toyplot.color.black,
"font-size": "%rpx" % (m.size * 0.75),
"stroke": "none",
"text-anchor": "middle",
}, m.lstyle)
## update fonts
fonts = toyplot.font.ReportlabLibrary()
layout = toyplot.text.layout(m.label, lsty, fonts)
lsty = _color_fixup(layout.style)
lstyles.append(lsty)
nallkeys = set(itertools.chain(*[i.keys() for i in nstyles]))
lallkeys = set(itertools.chain(*[i.keys() for i in lstyles]))
nuniquekeys = []
nsharedkeys = []
for key in nallkeys:
vals = [nstyles[i].get(key) for i in range(len(nstyles))]
if len(set(vals)) > 1:
nuniquekeys.append(key)
else:
nsharedkeys.append(key)
luniquekeys = []
lsharedkeys = []
for key in lallkeys:
vals = [lstyles[i].get(key) for i in range(len(lstyles))]
if len(set(vals)) > 1:
luniquekeys.append(key)
else:
lsharedkeys.append(key)
## keys shared between mark and text markers
repeated = set(lsharedkeys).intersection(set(nsharedkeys))
for repeat in repeated:
## if same then keep only one copy of it
lidx = lsharedkeys.index(repeat)
nidx = nsharedkeys.index(repeat)
if lsharedkeys[lidx] == nsharedkeys[nidx]:
lsharedkeys.remove(repeat)
else:
lsharedkeys.remove(repeat)
luniquekeys.append(repeat)
nsharedkeys.remove(repeat)
nuniquekeys.append(repeat)
## check node values
natt = ["%s:%s" % (key, nstyles[0][key]) for key in sorted(nsharedkeys)]
latt = ["%s:%s" % (key, lstyles[0][key]) for key in sorted(lsharedkeys)]
shared_styles = ";".join(natt+latt)
unique_styles = {
"node": [{k:v for k,v in nstyles[idx].items() if k in nuniquekeys} for idx in range(len(markers))],
"text": [{k:v for k,v in lstyles[idx].items() if k in luniquekeys} for idx in range(len(markers))]
}
return shared_styles, unique_styles
|
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get shared styles
|
[
"get",
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train
|
https://github.com/eaton-lab/toytree/blob/0347ed2098acc5f707fadf52a0ecd411a6d1859c/toytree/html.py#L373-L447
|
doakey3/DashTable
|
dashtable/data2rst/cell/center_cell_text.py
|
center_cell_text
|
def center_cell_text(cell):
"""
Horizontally center the text within a cell's grid
Like this::
+---------+ +---------+
| foo | --> | foo |
+---------+ +---------+
Parameters
----------
cell : dashtable.data2rst.Cell
Returns
-------
cell : dashtable.data2rst.Cell
"""
lines = cell.text.split('\n')
cell_width = len(lines[0]) - 2
truncated_lines = ['']
for i in range(1, len(lines) - 1):
truncated = lines[i][2:len(lines[i]) - 2].rstrip()
truncated_lines.append(truncated)
truncated_lines.append('')
max_line_length = get_longest_line_length('\n'.join(truncated_lines))
remainder = cell_width - max_line_length
left_width = math.floor(remainder / 2)
left_space = left_width * ' '
for i in range(len(truncated_lines)):
truncated_lines[i] = left_space + truncated_lines[i]
right_width = cell_width - len(truncated_lines[i])
truncated_lines[i] += right_width * ' '
for i in range(1, len(lines) - 1):
lines[i] = ''.join([
lines[i][0], truncated_lines[i], lines[i][-1]
])
cell.text = '\n'.join(lines)
return cell
|
python
|
def center_cell_text(cell):
"""
Horizontally center the text within a cell's grid
Like this::
+---------+ +---------+
| foo | --> | foo |
+---------+ +---------+
Parameters
----------
cell : dashtable.data2rst.Cell
Returns
-------
cell : dashtable.data2rst.Cell
"""
lines = cell.text.split('\n')
cell_width = len(lines[0]) - 2
truncated_lines = ['']
for i in range(1, len(lines) - 1):
truncated = lines[i][2:len(lines[i]) - 2].rstrip()
truncated_lines.append(truncated)
truncated_lines.append('')
max_line_length = get_longest_line_length('\n'.join(truncated_lines))
remainder = cell_width - max_line_length
left_width = math.floor(remainder / 2)
left_space = left_width * ' '
for i in range(len(truncated_lines)):
truncated_lines[i] = left_space + truncated_lines[i]
right_width = cell_width - len(truncated_lines[i])
truncated_lines[i] += right_width * ' '
for i in range(1, len(lines) - 1):
lines[i] = ''.join([
lines[i][0], truncated_lines[i], lines[i][-1]
])
cell.text = '\n'.join(lines)
return cell
|
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Horizontally center the text within a cell's grid
Like this::
+---------+ +---------+
| foo | --> | foo |
+---------+ +---------+
Parameters
----------
cell : dashtable.data2rst.Cell
Returns
-------
cell : dashtable.data2rst.Cell
|
[
"Horizontally",
"center",
"the",
"text",
"within",
"a",
"cell",
"s",
"grid"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/cell/center_cell_text.py#L4-L50
|
Lilykos/pyphonetics
|
pyphonetics/distance_metrics/hamming.py
|
hamming_distance
|
def hamming_distance(word1, word2):
"""
Computes the Hamming distance.
[Reference]: https://en.wikipedia.org/wiki/Hamming_distance
[Article]: Hamming, Richard W. (1950), "Error detecting and error correcting codes",
Bell System Technical Journal 29 (2): 147–160
"""
from operator import ne
if len(word1) != len(word2):
raise WrongLengthException('The words need to be of the same length!')
return sum(map(ne, word1, word2))
|
python
|
def hamming_distance(word1, word2):
"""
Computes the Hamming distance.
[Reference]: https://en.wikipedia.org/wiki/Hamming_distance
[Article]: Hamming, Richard W. (1950), "Error detecting and error correcting codes",
Bell System Technical Journal 29 (2): 147–160
"""
from operator import ne
if len(word1) != len(word2):
raise WrongLengthException('The words need to be of the same length!')
return sum(map(ne, word1, word2))
|
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Computes the Hamming distance.
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[Article]: Hamming, Richard W. (1950), "Error detecting and error correcting codes",
Bell System Technical Journal 29 (2): 147–160
|
[
"Computes",
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"."
] |
train
|
https://github.com/Lilykos/pyphonetics/blob/7f55cccc1135e6015520a895eb6859318a4b6111/pyphonetics/distance_metrics/hamming.py#L4-L16
|
quantmind/dynts
|
dynts/utils/populate.py
|
polygen
|
def polygen(*coefficients):
'''Polynomial generating function'''
if not coefficients:
return lambda i: 0
else:
c0 = coefficients[0]
coefficients = coefficients[1:]
def _(i):
v = c0
for c in coefficients:
v += c*i
i *= i
return v
return _
|
python
|
def polygen(*coefficients):
'''Polynomial generating function'''
if not coefficients:
return lambda i: 0
else:
c0 = coefficients[0]
coefficients = coefficients[1:]
def _(i):
v = c0
for c in coefficients:
v += c*i
i *= i
return v
return _
|
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Polynomial generating function
|
[
"Polynomial",
"generating",
"function"
] |
train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/utils/populate.py#L34-L49
|
quantmind/dynts
|
dynts/api/main.py
|
timeseries
|
def timeseries(name='', backend=None, date=None, data=None, **kwargs):
'''Create a new :class:`dynts.TimeSeries` instance using a ``backend``
and populating it with provided the data.
:parameter name: optional timeseries name. For multivarate timeseries
the :func:`dynts.tsname` utility function can be used
to build it.
:parameter backend: optional backend name.
If not provided, numpy will be used.
:parameter date: optional iterable over dates.
:parameter data: optional iterable over data.
'''
backend = backend or settings.backend
TS = BACKENDS.get(backend)
if not TS:
raise InvalidBackEnd(
'Could not find a TimeSeries class %s' % backend
)
return TS(name=name, date=date, data=data, **kwargs)
|
python
|
def timeseries(name='', backend=None, date=None, data=None, **kwargs):
'''Create a new :class:`dynts.TimeSeries` instance using a ``backend``
and populating it with provided the data.
:parameter name: optional timeseries name. For multivarate timeseries
the :func:`dynts.tsname` utility function can be used
to build it.
:parameter backend: optional backend name.
If not provided, numpy will be used.
:parameter date: optional iterable over dates.
:parameter data: optional iterable over data.
'''
backend = backend or settings.backend
TS = BACKENDS.get(backend)
if not TS:
raise InvalidBackEnd(
'Could not find a TimeSeries class %s' % backend
)
return TS(name=name, date=date, data=data, **kwargs)
|
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to build it.
:parameter backend: optional backend name.
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:parameter date: optional iterable over dates.
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|
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train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/api/main.py#L7-L25
|
doakey3/DashTable
|
dashtable/dashutils/ensure_table_strings.py
|
ensure_table_strings
|
def ensure_table_strings(table):
"""
Force each cell in the table to be a string
Parameters
----------
table : list of lists
Returns
-------
table : list of lists of str
"""
for row in range(len(table)):
for column in range(len(table[row])):
table[row][column] = str(table[row][column])
return table
|
python
|
def ensure_table_strings(table):
"""
Force each cell in the table to be a string
Parameters
----------
table : list of lists
Returns
-------
table : list of lists of str
"""
for row in range(len(table)):
for column in range(len(table[row])):
table[row][column] = str(table[row][column])
return table
|
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Force each cell in the table to be a string
Parameters
----------
table : list of lists
Returns
-------
table : list of lists of str
|
[
"Force",
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"to",
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"a",
"string"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/dashutils/ensure_table_strings.py#L1-L16
|
doakey3/DashTable
|
dashtable/data2rst/cell/cell.py
|
Cell.left_sections
|
def left_sections(self):
"""
The number of sections that touch the left side.
During merging, the cell's text will grow to include other
cells. This property keeps track of the number of sections that
are touching the left side. For example::
+-----+-----+
section --> | foo | dog | <-- section
+-----+-----+
section --> | cat |
+-----+
Has 2 sections on the left, but 1 on the right
Returns
-------
sections : int
The number of sections on the left
"""
lines = self.text.split('\n')
sections = 0
for i in range(len(lines)):
if lines[i].startswith('+'):
sections += 1
sections -= 1
return sections
|
python
|
def left_sections(self):
"""
The number of sections that touch the left side.
During merging, the cell's text will grow to include other
cells. This property keeps track of the number of sections that
are touching the left side. For example::
+-----+-----+
section --> | foo | dog | <-- section
+-----+-----+
section --> | cat |
+-----+
Has 2 sections on the left, but 1 on the right
Returns
-------
sections : int
The number of sections on the left
"""
lines = self.text.split('\n')
sections = 0
for i in range(len(lines)):
if lines[i].startswith('+'):
sections += 1
sections -= 1
return sections
|
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The number of sections that touch the left side.
During merging, the cell's text will grow to include other
cells. This property keeps track of the number of sections that
are touching the left side. For example::
+-----+-----+
section --> | foo | dog | <-- section
+-----+-----+
section --> | cat |
+-----+
Has 2 sections on the left, but 1 on the right
Returns
-------
sections : int
The number of sections on the left
|
[
"The",
"number",
"of",
"sections",
"that",
"touch",
"the",
"left",
"side",
"."
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/cell/cell.py#L37-L66
|
doakey3/DashTable
|
dashtable/data2rst/cell/cell.py
|
Cell.right_sections
|
def right_sections(self):
"""
The number of sections that touch the right side.
Returns
-------
sections : int
The number of sections on the right
"""
lines = self.text.split('\n')
sections = 0
for i in range(len(lines)):
if lines[i].endswith('+'):
sections += 1
return sections - 1
|
python
|
def right_sections(self):
"""
The number of sections that touch the right side.
Returns
-------
sections : int
The number of sections on the right
"""
lines = self.text.split('\n')
sections = 0
for i in range(len(lines)):
if lines[i].endswith('+'):
sections += 1
return sections - 1
|
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"-",
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] |
The number of sections that touch the right side.
Returns
-------
sections : int
The number of sections on the right
|
[
"The",
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"right",
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"."
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/cell/cell.py#L69-L83
|
doakey3/DashTable
|
dashtable/data2rst/cell/cell.py
|
Cell.top_sections
|
def top_sections(self):
"""
The number of sections that touch the top side.
Returns
-------
sections : int
The number of sections on the top
"""
top_line = self.text.split('\n')[0]
sections = len(top_line.split('+')) - 2
return sections
|
python
|
def top_sections(self):
"""
The number of sections that touch the top side.
Returns
-------
sections : int
The number of sections on the top
"""
top_line = self.text.split('\n')[0]
sections = len(top_line.split('+')) - 2
return sections
|
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"(",
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")",
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"-",
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] |
The number of sections that touch the top side.
Returns
-------
sections : int
The number of sections on the top
|
[
"The",
"number",
"of",
"sections",
"that",
"touch",
"the",
"top",
"side",
"."
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/cell/cell.py#L86-L99
|
doakey3/DashTable
|
dashtable/data2rst/cell/cell.py
|
Cell.bottom_sections
|
def bottom_sections(self):
"""
The number of cells that touch the bottom side.
Returns
-------
sections : int
The number of sections on the top
"""
bottom_line = self.text.split('\n')[-1]
sections = len(bottom_line.split('+')) - 2
return sections
|
python
|
def bottom_sections(self):
"""
The number of cells that touch the bottom side.
Returns
-------
sections : int
The number of sections on the top
"""
bottom_line = self.text.split('\n')[-1]
sections = len(bottom_line.split('+')) - 2
return sections
|
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".",
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"(",
"'+'",
")",
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"-",
"2",
"return",
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] |
The number of cells that touch the bottom side.
Returns
-------
sections : int
The number of sections on the top
|
[
"The",
"number",
"of",
"cells",
"that",
"touch",
"the",
"bottom",
"side",
"."
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/cell/cell.py#L102-L114
|
doakey3/DashTable
|
dashtable/data2rst/cell/cell.py
|
Cell.is_header
|
def is_header(self):
"""
Whether or not the cell is a header
Any header cell will have "=" instead of "-" on its border.
For example, this is a header cell::
+-----+
| foo |
+=====+
while this cell is not::
+-----+
| foo |
+-----+
Returns
-------
bool
Whether or not the cell is a header
"""
bottom_line = self.text.split('\n')[-1]
if is_only(bottom_line, ['+', '=']):
return True
return False
|
python
|
def is_header(self):
"""
Whether or not the cell is a header
Any header cell will have "=" instead of "-" on its border.
For example, this is a header cell::
+-----+
| foo |
+=====+
while this cell is not::
+-----+
| foo |
+-----+
Returns
-------
bool
Whether or not the cell is a header
"""
bottom_line = self.text.split('\n')[-1]
if is_only(bottom_line, ['+', '=']):
return True
return False
|
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Whether or not the cell is a header
Any header cell will have "=" instead of "-" on its border.
For example, this is a header cell::
+-----+
| foo |
+=====+
while this cell is not::
+-----+
| foo |
+-----+
Returns
-------
bool
Whether or not the cell is a header
|
[
"Whether",
"or",
"not",
"the",
"cell",
"is",
"a",
"header"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/cell/cell.py#L117-L145
|
quantmind/dynts
|
dynts/utils/version.py
|
get_git_changeset
|
def get_git_changeset(filename=None):
"""Returns a numeric identifier of the latest git changeset.
The result is the UTC timestamp of the changeset in YYYYMMDDHHMMSS format.
This value isn't guaranteed to be unique, but collisions are very unlikely,
so it's sufficient for generating the development version numbers.
"""
dirname = os.path.dirname(filename or __file__)
git_show = sh('git show --pretty=format:%ct --quiet HEAD',
cwd=dirname)
timestamp = git_show.partition('\n')[0]
try:
timestamp = datetime.datetime.utcfromtimestamp(int(timestamp))
except ValueError:
return None
return timestamp.strftime('%Y%m%d%H%M%S')
|
python
|
def get_git_changeset(filename=None):
"""Returns a numeric identifier of the latest git changeset.
The result is the UTC timestamp of the changeset in YYYYMMDDHHMMSS format.
This value isn't guaranteed to be unique, but collisions are very unlikely,
so it's sufficient for generating the development version numbers.
"""
dirname = os.path.dirname(filename or __file__)
git_show = sh('git show --pretty=format:%ct --quiet HEAD',
cwd=dirname)
timestamp = git_show.partition('\n')[0]
try:
timestamp = datetime.datetime.utcfromtimestamp(int(timestamp))
except ValueError:
return None
return timestamp.strftime('%Y%m%d%H%M%S')
|
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")"
] |
Returns a numeric identifier of the latest git changeset.
The result is the UTC timestamp of the changeset in YYYYMMDDHHMMSS format.
This value isn't guaranteed to be unique, but collisions are very unlikely,
so it's sufficient for generating the development version numbers.
|
[
"Returns",
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"so",
"it",
"s",
"sufficient",
"for",
"generating",
"the",
"development",
"version",
"numbers",
"."
] |
train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/utils/version.py#L31-L46
|
doakey3/DashTable
|
dashtable/html2data/headers_present.py
|
headers_present
|
def headers_present(html_string):
"""
Checks if the html table contains headers and returns True/False
Parameters
----------
html_string : str
Returns
-------
bool
"""
try:
from bs4 import BeautifulSoup
except ImportError:
print("ERROR: You must have BeautifulSoup to use html2data")
return
soup = BeautifulSoup(html_string, 'html.parser')
table = soup.find('table')
if not table:
return False
th = table.findAll('th')
if len(th) > 0:
return True
else:
return False
|
python
|
def headers_present(html_string):
"""
Checks if the html table contains headers and returns True/False
Parameters
----------
html_string : str
Returns
-------
bool
"""
try:
from bs4 import BeautifulSoup
except ImportError:
print("ERROR: You must have BeautifulSoup to use html2data")
return
soup = BeautifulSoup(html_string, 'html.parser')
table = soup.find('table')
if not table:
return False
th = table.findAll('th')
if len(th) > 0:
return True
else:
return False
|
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] |
Checks if the html table contains headers and returns True/False
Parameters
----------
html_string : str
Returns
-------
bool
|
[
"Checks",
"if",
"the",
"html",
"table",
"contains",
"headers",
"and",
"returns",
"True",
"/",
"False"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/html2data/headers_present.py#L1-L28
|
doakey3/DashTable
|
dashtable/html2data/extract_spans.py
|
extract_spans
|
def extract_spans(html_string):
"""
Creates a list of the spanned cell groups of [row, column] pairs.
Parameters
----------
html_string : str
Returns
-------
list of lists of lists of int
"""
try:
from bs4 import BeautifulSoup
except ImportError:
print("ERROR: You must have BeautifulSoup to use html2data")
return
soup = BeautifulSoup(html_string, 'html.parser')
table = soup.find('table')
if not table:
return []
trs = table.findAll('tr')
if len(trs) == 0:
return []
spans = []
for tr in range(len(trs)):
if tr == 0:
ths = trs[tr].findAll('th')
if len(ths) == 0:
ths = trs[tr].findAll('td')
tds = ths
else:
tds = trs[tr].findAll('td')
column = 0
for td in tds:
r_span_count = 1
c_span_count = 1
current_column = column
if td.has_attr('rowspan'):
r_span_count = int(td['rowspan'])
if td.has_attr('colspan'):
c_span_count = int(td['colspan'])
column += c_span_count
else:
column += 1
new_span = []
for r_index in range(tr, tr + r_span_count):
for c_index in range(current_column, column):
if not get_span(spans, r_index, c_index):
new_span.append([r_index, c_index])
if len(new_span) > 0:
spans.append(new_span)
return spans
|
python
|
def extract_spans(html_string):
"""
Creates a list of the spanned cell groups of [row, column] pairs.
Parameters
----------
html_string : str
Returns
-------
list of lists of lists of int
"""
try:
from bs4 import BeautifulSoup
except ImportError:
print("ERROR: You must have BeautifulSoup to use html2data")
return
soup = BeautifulSoup(html_string, 'html.parser')
table = soup.find('table')
if not table:
return []
trs = table.findAll('tr')
if len(trs) == 0:
return []
spans = []
for tr in range(len(trs)):
if tr == 0:
ths = trs[tr].findAll('th')
if len(ths) == 0:
ths = trs[tr].findAll('td')
tds = ths
else:
tds = trs[tr].findAll('td')
column = 0
for td in tds:
r_span_count = 1
c_span_count = 1
current_column = column
if td.has_attr('rowspan'):
r_span_count = int(td['rowspan'])
if td.has_attr('colspan'):
c_span_count = int(td['colspan'])
column += c_span_count
else:
column += 1
new_span = []
for r_index in range(tr, tr + r_span_count):
for c_index in range(current_column, column):
if not get_span(spans, r_index, c_index):
new_span.append([r_index, c_index])
if len(new_span) > 0:
spans.append(new_span)
return spans
|
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Creates a list of the spanned cell groups of [row, column] pairs.
Parameters
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html_string : str
Returns
-------
list of lists of lists of int
|
[
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train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/html2data/extract_spans.py#L4-L64
|
Lilykos/pyphonetics
|
pyphonetics/utils.py
|
translation
|
def translation(first, second):
"""Create an index of mapped letters (zip to dict)."""
if len(first) != len(second):
raise WrongLengthException('The lists are not of the same length!')
return dict(zip(first, second))
|
python
|
def translation(first, second):
"""Create an index of mapped letters (zip to dict)."""
if len(first) != len(second):
raise WrongLengthException('The lists are not of the same length!')
return dict(zip(first, second))
|
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Create an index of mapped letters (zip to dict).
|
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train
|
https://github.com/Lilykos/pyphonetics/blob/7f55cccc1135e6015520a895eb6859318a4b6111/pyphonetics/utils.py#L6-L10
|
doakey3/DashTable
|
dashtable/html2data/restructify/process_tag.py
|
process_tag
|
def process_tag(node):
"""
Recursively go through a tag's children, converting them, then
convert the tag itself.
"""
text = ''
exceptions = ['table']
for element in node.children:
if isinstance(element, NavigableString):
text += element
elif not node.name in exceptions:
text += process_tag(element)
try:
convert_fn = globals()["convert_%s" % node.name.lower()]
text = convert_fn(node, text)
except KeyError:
pass
return text
|
python
|
def process_tag(node):
"""
Recursively go through a tag's children, converting them, then
convert the tag itself.
"""
text = ''
exceptions = ['table']
for element in node.children:
if isinstance(element, NavigableString):
text += element
elif not node.name in exceptions:
text += process_tag(element)
try:
convert_fn = globals()["convert_%s" % node.name.lower()]
text = convert_fn(node, text)
except KeyError:
pass
return text
|
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Recursively go through a tag's children, converting them, then
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|
[
"Recursively",
"go",
"through",
"a",
"tag",
"s",
"children",
"converting",
"them",
"then",
"convert",
"the",
"tag",
"itself",
"."
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/html2data/restructify/process_tag.py#L13-L36
|
quantmind/dynts
|
dynts/utils/iterators.py
|
laggeddates
|
def laggeddates(ts, step=1):
'''Lagged iterator over dates'''
if step == 1:
dates = ts.dates()
if not hasattr(dates, 'next'):
dates = dates.__iter__()
dt0 = next(dates)
for dt1 in dates:
yield dt1, dt0
dt0 = dt1
else:
while done:
done += 1
lag.append(next(dates))
for dt1 in dates:
lag.append(dt1)
yield dt1, lag.pop(0)
|
python
|
def laggeddates(ts, step=1):
'''Lagged iterator over dates'''
if step == 1:
dates = ts.dates()
if not hasattr(dates, 'next'):
dates = dates.__iter__()
dt0 = next(dates)
for dt1 in dates:
yield dt1, dt0
dt0 = dt1
else:
while done:
done += 1
lag.append(next(dates))
for dt1 in dates:
lag.append(dt1)
yield dt1, lag.pop(0)
|
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"lag",
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"(",
"0",
")"
] |
Lagged iterator over dates
|
[
"Lagged",
"iterator",
"over",
"dates"
] |
train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/utils/iterators.py#L4-L20
|
quantmind/dynts
|
dynts/lib/__init__.py
|
make_skiplist
|
def make_skiplist(*args, use_fallback=False):
'''Create a new skiplist'''
sl = fallback.Skiplist if use_fallback else Skiplist
return sl(*args)
|
python
|
def make_skiplist(*args, use_fallback=False):
'''Create a new skiplist'''
sl = fallback.Skiplist if use_fallback else Skiplist
return sl(*args)
|
[
"def",
"make_skiplist",
"(",
"*",
"args",
",",
"use_fallback",
"=",
"False",
")",
":",
"sl",
"=",
"fallback",
".",
"Skiplist",
"if",
"use_fallback",
"else",
"Skiplist",
"return",
"sl",
"(",
"*",
"args",
")"
] |
Create a new skiplist
|
[
"Create",
"a",
"new",
"skiplist"
] |
train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/lib/__init__.py#L6-L9
|
doakey3/DashTable
|
dashtable/data2md/data2md.py
|
data2md
|
def data2md(table):
"""
Creates a markdown table. The first row will be headers.
Parameters
----------
table : list of lists of str
A list of rows containing strings. If any of these strings
consist of multiple lines, they will be converted to single line
because markdown tables do not support multiline cells.
Returns
-------
str
The markdown formatted string
Example
-------
>>> table_data = [
... ["Species", "Coolness"],
... ["Dog", "Awesome"],
... ["Cat", "Meh"],
... ]
>>> print(data2md(table_data))
| Species | Coolness |
|---------|----------|
| Dog | Awesome |
| Cat | Meh |
"""
table = copy.deepcopy(table)
table = ensure_table_strings(table)
table = multis_2_mono(table)
table = add_cushions(table)
widths = []
for column in range(len(table[0])):
widths.append(get_column_width(column, table))
output = '|'
for i in range(len(table[0])):
output = ''.join(
[output, center_line(widths[i], table[0][i]), '|'])
output = output + '\n|'
for i in range(len(table[0])):
output = ''.join([
output, center_line(widths[i], "-" * widths[i]), '|'])
output = output + '\n|'
for row in range(1, len(table)):
for column in range(len(table[row])):
output = ''.join(
[output, center_line(widths[column],
table[row][column]), '|'])
output = output + '\n|'
split = output.split('\n')
split.pop()
table_string = '\n'.join(split)
return table_string
|
python
|
def data2md(table):
"""
Creates a markdown table. The first row will be headers.
Parameters
----------
table : list of lists of str
A list of rows containing strings. If any of these strings
consist of multiple lines, they will be converted to single line
because markdown tables do not support multiline cells.
Returns
-------
str
The markdown formatted string
Example
-------
>>> table_data = [
... ["Species", "Coolness"],
... ["Dog", "Awesome"],
... ["Cat", "Meh"],
... ]
>>> print(data2md(table_data))
| Species | Coolness |
|---------|----------|
| Dog | Awesome |
| Cat | Meh |
"""
table = copy.deepcopy(table)
table = ensure_table_strings(table)
table = multis_2_mono(table)
table = add_cushions(table)
widths = []
for column in range(len(table[0])):
widths.append(get_column_width(column, table))
output = '|'
for i in range(len(table[0])):
output = ''.join(
[output, center_line(widths[i], table[0][i]), '|'])
output = output + '\n|'
for i in range(len(table[0])):
output = ''.join([
output, center_line(widths[i], "-" * widths[i]), '|'])
output = output + '\n|'
for row in range(1, len(table)):
for column in range(len(table[row])):
output = ''.join(
[output, center_line(widths[column],
table[row][column]), '|'])
output = output + '\n|'
split = output.split('\n')
split.pop()
table_string = '\n'.join(split)
return table_string
|
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")",
"table_string",
"=",
"'\\n'",
".",
"join",
"(",
"split",
")",
"return",
"table_string"
] |
Creates a markdown table. The first row will be headers.
Parameters
----------
table : list of lists of str
A list of rows containing strings. If any of these strings
consist of multiple lines, they will be converted to single line
because markdown tables do not support multiline cells.
Returns
-------
str
The markdown formatted string
Example
-------
>>> table_data = [
... ["Species", "Coolness"],
... ["Dog", "Awesome"],
... ["Cat", "Meh"],
... ]
>>> print(data2md(table_data))
| Species | Coolness |
|---------|----------|
| Dog | Awesome |
| Cat | Meh |
|
[
"Creates",
"a",
"markdown",
"table",
".",
"The",
"first",
"row",
"will",
"be",
"headers",
"."
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2md/data2md.py#L10-L73
|
doakey3/DashTable
|
dashtable/data2rst/cell/v_center_cell_text.py
|
v_center_cell_text
|
def v_center_cell_text(cell):
"""
Vertically center the text within the cell's grid.
Like this::
+--------+ +--------+
| foobar | | |
| | | |
| | --> | foobar |
| | | |
| | | |
+--------+ +--------+
Parameters
----------
cell : dashtable.data2rst.Cell
Returns
-------
cell : dashtable.data2rst.Cell
"""
lines = cell.text.split('\n')
cell_width = len(lines[0]) - 2
truncated_lines = []
for i in range(1, len(lines) - 1):
truncated = lines[i][1:len(lines[i]) - 1]
truncated_lines.append(truncated)
total_height = len(truncated_lines)
empty_lines_above = 0
for i in range(len(truncated_lines)):
if truncated_lines[i].rstrip() == '':
empty_lines_above += 1
else:
break
empty_lines_below = 0
for i in reversed(range(len(truncated_lines))):
if truncated_lines[i].rstrip() == '':
empty_lines_below += 1
else:
break
significant_lines = truncated_lines[
empty_lines_above:len(truncated_lines) - empty_lines_below
]
remainder = total_height - len(significant_lines)
blank = cell_width * ' '
above_height = math.floor(remainder / 2)
for i in range(0, above_height):
significant_lines.insert(0, blank)
below_height = math.ceil(remainder / 2)
for i in range(0, below_height):
significant_lines.append(blank)
for i in range(len(significant_lines)):
lines[i + 1] = ''.join([
lines[i + 1][0] + significant_lines[i] + lines[i + 1][-1]
])
cell.text = '\n'.join(lines)
return cell
|
python
|
def v_center_cell_text(cell):
"""
Vertically center the text within the cell's grid.
Like this::
+--------+ +--------+
| foobar | | |
| | | |
| | --> | foobar |
| | | |
| | | |
+--------+ +--------+
Parameters
----------
cell : dashtable.data2rst.Cell
Returns
-------
cell : dashtable.data2rst.Cell
"""
lines = cell.text.split('\n')
cell_width = len(lines[0]) - 2
truncated_lines = []
for i in range(1, len(lines) - 1):
truncated = lines[i][1:len(lines[i]) - 1]
truncated_lines.append(truncated)
total_height = len(truncated_lines)
empty_lines_above = 0
for i in range(len(truncated_lines)):
if truncated_lines[i].rstrip() == '':
empty_lines_above += 1
else:
break
empty_lines_below = 0
for i in reversed(range(len(truncated_lines))):
if truncated_lines[i].rstrip() == '':
empty_lines_below += 1
else:
break
significant_lines = truncated_lines[
empty_lines_above:len(truncated_lines) - empty_lines_below
]
remainder = total_height - len(significant_lines)
blank = cell_width * ' '
above_height = math.floor(remainder / 2)
for i in range(0, above_height):
significant_lines.insert(0, blank)
below_height = math.ceil(remainder / 2)
for i in range(0, below_height):
significant_lines.append(blank)
for i in range(len(significant_lines)):
lines[i + 1] = ''.join([
lines[i + 1][0] + significant_lines[i] + lines[i + 1][-1]
])
cell.text = '\n'.join(lines)
return cell
|
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".",
"text",
"=",
"'\\n'",
".",
"join",
"(",
"lines",
")",
"return",
"cell"
] |
Vertically center the text within the cell's grid.
Like this::
+--------+ +--------+
| foobar | | |
| | | |
| | --> | foobar |
| | | |
| | | |
+--------+ +--------+
Parameters
----------
cell : dashtable.data2rst.Cell
Returns
-------
cell : dashtable.data2rst.Cell
|
[
"Vertically",
"center",
"the",
"text",
"within",
"the",
"cell",
"s",
"grid",
"."
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/cell/v_center_cell_text.py#L4-L73
|
doakey3/DashTable
|
dashtable/data2rst/data2rst.py
|
data2rst
|
def data2rst(table, spans=[[[0, 0]]], use_headers=True,
center_cells=False, center_headers=False):
"""
Convert a list of lists of str into a reStructuredText Grid Table
Parameters
----------
table : list of lists of str
spans : list of lists of lists of int, optional
These are [row, column] pairs of cells that are merged in the
table. Rows and columns start in the top left of the table.For
example::
+--------+--------+
| [0, 0] | [0, 1] |
+--------+--------+
| [1, 0] | [1, 1] |
+--------+--------+
use_headers : bool, optional
Whether or not the first row of table data will become headers.
center_cells : bool, optional
Whether or not cells will be centered
center_headers: bool, optional
Whether or not headers will be centered
Returns
-------
str
The grid table string
Example
-------
>>> spans = [
... [ [3, 1], [4, 1] ],
... [ [3, 2], [4, 2] ],
... [ [2, 1], [2, 2] ],
... ]
>>> table = [
... ["Header 1", "Header 2", "Header 3"],
... ["body row 1", "column 2", "column 3"],
... ["body row 2", "Cells may span columns", ""],
... ["body row 3", "Cells may span rows.", "- Cells\\n-contain\\n-blocks"],
... ["body row 4", "", ""],
... ]
>>> print(dashtable.data2rst(table, spans))
+------------+------------+-----------+
| Header 1 | Header 2 | Header 3 |
+============+============+===========+
| body row 1 | column 2 | column 3 |
+------------+------------+-----------+
| body row 2 | Cells may span columns.|
+------------+------------+-----------+
| body row 3 | Cells may | - Cells |
+------------+ span rows. | - contain |
| body row 4 | | - blocks. |
+------------+------------+-----------+
"""
table = copy.deepcopy(table)
table_ok = check_table(table)
if not table_ok == "":
return "ERROR: " + table_ok
if not spans == [[[0, 0]]]:
for span in spans:
span_ok = check_span(span, table)
if not span_ok == "":
return "ERROR: " + span_ok
table = ensure_table_strings(table)
table = add_cushions(table)
spans = table_cells_2_spans(table, spans)
widths = get_output_column_widths(table, spans)
heights = get_output_row_heights(table, spans)
cells = []
for span in spans:
cell = make_cell(table, span, widths, heights, use_headers)
cells.append(cell)
cells = list(sorted(cells))
if center_cells:
for cell in cells:
if not cell.is_header:
center_cell_text(cell)
v_center_cell_text(cell)
if center_headers:
for cell in cells:
if cell.is_header:
center_cell_text(cell)
v_center_cell_text(cell)
grid_table = merge_all_cells(cells)
return grid_table
|
python
|
def data2rst(table, spans=[[[0, 0]]], use_headers=True,
center_cells=False, center_headers=False):
"""
Convert a list of lists of str into a reStructuredText Grid Table
Parameters
----------
table : list of lists of str
spans : list of lists of lists of int, optional
These are [row, column] pairs of cells that are merged in the
table. Rows and columns start in the top left of the table.For
example::
+--------+--------+
| [0, 0] | [0, 1] |
+--------+--------+
| [1, 0] | [1, 1] |
+--------+--------+
use_headers : bool, optional
Whether or not the first row of table data will become headers.
center_cells : bool, optional
Whether or not cells will be centered
center_headers: bool, optional
Whether or not headers will be centered
Returns
-------
str
The grid table string
Example
-------
>>> spans = [
... [ [3, 1], [4, 1] ],
... [ [3, 2], [4, 2] ],
... [ [2, 1], [2, 2] ],
... ]
>>> table = [
... ["Header 1", "Header 2", "Header 3"],
... ["body row 1", "column 2", "column 3"],
... ["body row 2", "Cells may span columns", ""],
... ["body row 3", "Cells may span rows.", "- Cells\\n-contain\\n-blocks"],
... ["body row 4", "", ""],
... ]
>>> print(dashtable.data2rst(table, spans))
+------------+------------+-----------+
| Header 1 | Header 2 | Header 3 |
+============+============+===========+
| body row 1 | column 2 | column 3 |
+------------+------------+-----------+
| body row 2 | Cells may span columns.|
+------------+------------+-----------+
| body row 3 | Cells may | - Cells |
+------------+ span rows. | - contain |
| body row 4 | | - blocks. |
+------------+------------+-----------+
"""
table = copy.deepcopy(table)
table_ok = check_table(table)
if not table_ok == "":
return "ERROR: " + table_ok
if not spans == [[[0, 0]]]:
for span in spans:
span_ok = check_span(span, table)
if not span_ok == "":
return "ERROR: " + span_ok
table = ensure_table_strings(table)
table = add_cushions(table)
spans = table_cells_2_spans(table, spans)
widths = get_output_column_widths(table, spans)
heights = get_output_row_heights(table, spans)
cells = []
for span in spans:
cell = make_cell(table, span, widths, heights, use_headers)
cells.append(cell)
cells = list(sorted(cells))
if center_cells:
for cell in cells:
if not cell.is_header:
center_cell_text(cell)
v_center_cell_text(cell)
if center_headers:
for cell in cells:
if cell.is_header:
center_cell_text(cell)
v_center_cell_text(cell)
grid_table = merge_all_cells(cells)
return grid_table
|
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")",
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"=",
"merge_all_cells",
"(",
"cells",
")",
"return",
"grid_table"
] |
Convert a list of lists of str into a reStructuredText Grid Table
Parameters
----------
table : list of lists of str
spans : list of lists of lists of int, optional
These are [row, column] pairs of cells that are merged in the
table. Rows and columns start in the top left of the table.For
example::
+--------+--------+
| [0, 0] | [0, 1] |
+--------+--------+
| [1, 0] | [1, 1] |
+--------+--------+
use_headers : bool, optional
Whether or not the first row of table data will become headers.
center_cells : bool, optional
Whether or not cells will be centered
center_headers: bool, optional
Whether or not headers will be centered
Returns
-------
str
The grid table string
Example
-------
>>> spans = [
... [ [3, 1], [4, 1] ],
... [ [3, 2], [4, 2] ],
... [ [2, 1], [2, 2] ],
... ]
>>> table = [
... ["Header 1", "Header 2", "Header 3"],
... ["body row 1", "column 2", "column 3"],
... ["body row 2", "Cells may span columns", ""],
... ["body row 3", "Cells may span rows.", "- Cells\\n-contain\\n-blocks"],
... ["body row 4", "", ""],
... ]
>>> print(dashtable.data2rst(table, spans))
+------------+------------+-----------+
| Header 1 | Header 2 | Header 3 |
+============+============+===========+
| body row 1 | column 2 | column 3 |
+------------+------------+-----------+
| body row 2 | Cells may span columns.|
+------------+------------+-----------+
| body row 3 | Cells may | - Cells |
+------------+ span rows. | - contain |
| body row 4 | | - blocks. |
+------------+------------+-----------+
|
[
"Convert",
"a",
"list",
"of",
"lists",
"of",
"str",
"into",
"a",
"reStructuredText",
"Grid",
"Table"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/data2rst.py#L19-L119
|
eaton-lab/toytree
|
toytree/MultiDrawing.py
|
CloudTree.set_dims_from_tree_size
|
def set_dims_from_tree_size(self):
"Calculate reasonable height and width for tree given N tips"
tlen = len(self.treelist[0])
if self.style.orient in ("right", "left"):
# long tip-wise dimension
if not self.style.height:
self.style.height = max(275, min(1000, 18 * (tlen)))
if not self.style.width:
self.style.width = max(300, min(500, 18 * (tlen)))
else:
# long tip-wise dimension
if not self.style.width:
self.style.width = max(275, min(1000, 18 * (tlen)))
if not self.style.height:
self.style.height = max(225, min(500, 18 * (tlen)))
|
python
|
def set_dims_from_tree_size(self):
"Calculate reasonable height and width for tree given N tips"
tlen = len(self.treelist[0])
if self.style.orient in ("right", "left"):
# long tip-wise dimension
if not self.style.height:
self.style.height = max(275, min(1000, 18 * (tlen)))
if not self.style.width:
self.style.width = max(300, min(500, 18 * (tlen)))
else:
# long tip-wise dimension
if not self.style.width:
self.style.width = max(275, min(1000, 18 * (tlen)))
if not self.style.height:
self.style.height = max(225, min(500, 18 * (tlen)))
|
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Calculate reasonable height and width for tree given N tips
|
[
"Calculate",
"reasonable",
"height",
"and",
"width",
"for",
"tree",
"given",
"N",
"tips"
] |
train
|
https://github.com/eaton-lab/toytree/blob/0347ed2098acc5f707fadf52a0ecd411a6d1859c/toytree/MultiDrawing.py#L153-L167
|
eaton-lab/toytree
|
toytree/MultiDrawing.py
|
CloudTree.add_tip_labels_to_axes
|
def add_tip_labels_to_axes(self):
"""
Add text offset from tips of tree with correction for orientation,
and fixed_order which is usually used in multitree plotting.
"""
# get tip-coords and replace if using fixed_order
if self.style.orient in ("up", "down"):
ypos = np.zeros(self.ntips)
xpos = np.arange(self.ntips)
if self.style.orient in ("right", "left"):
xpos = np.zeros(self.ntips)
ypos = np.arange(self.ntips)
# pop fill from color dict if using color
if self.style.tip_labels_colors:
self.style.tip_labels_style.pop("fill")
# fill anchor shift if None
# (Toytrees fill this at draw() normally when tip_labels != None)
if self.style.tip_labels_style["-toyplot-anchor-shift"] is None:
self.style.tip_labels_style["-toyplot-anchor-shift"] = "15px"
# add tip names to coordinates calculated above
self.axes.text(
xpos,
ypos,
self.tip_labels,
angle=(0 if self.style.orient in ("right", "left") else -90),
style=self.style.tip_labels_style,
color=self.style.tip_labels_colors,
)
# get stroke-width for aligned tip-label lines (optional)
# copy stroke-width from the edge_style unless user set it
if not self.style.edge_align_style.get("stroke-width"):
self.style.edge_align_style['stroke-width'] = (
self.style.edge_style['stroke-width'])
|
python
|
def add_tip_labels_to_axes(self):
"""
Add text offset from tips of tree with correction for orientation,
and fixed_order which is usually used in multitree plotting.
"""
# get tip-coords and replace if using fixed_order
if self.style.orient in ("up", "down"):
ypos = np.zeros(self.ntips)
xpos = np.arange(self.ntips)
if self.style.orient in ("right", "left"):
xpos = np.zeros(self.ntips)
ypos = np.arange(self.ntips)
# pop fill from color dict if using color
if self.style.tip_labels_colors:
self.style.tip_labels_style.pop("fill")
# fill anchor shift if None
# (Toytrees fill this at draw() normally when tip_labels != None)
if self.style.tip_labels_style["-toyplot-anchor-shift"] is None:
self.style.tip_labels_style["-toyplot-anchor-shift"] = "15px"
# add tip names to coordinates calculated above
self.axes.text(
xpos,
ypos,
self.tip_labels,
angle=(0 if self.style.orient in ("right", "left") else -90),
style=self.style.tip_labels_style,
color=self.style.tip_labels_colors,
)
# get stroke-width for aligned tip-label lines (optional)
# copy stroke-width from the edge_style unless user set it
if not self.style.edge_align_style.get("stroke-width"):
self.style.edge_align_style['stroke-width'] = (
self.style.edge_style['stroke-width'])
|
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] |
Add text offset from tips of tree with correction for orientation,
and fixed_order which is usually used in multitree plotting.
|
[
"Add",
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"."
] |
train
|
https://github.com/eaton-lab/toytree/blob/0347ed2098acc5f707fadf52a0ecd411a6d1859c/toytree/MultiDrawing.py#L170-L206
|
eaton-lab/toytree
|
toytree/MultiDrawing.py
|
CloudTree.fit_tip_labels
|
def fit_tip_labels(self):
"""
Modifies display range to ensure tip labels fit. This is a bit hackish
still. The problem is that the 'extents' range of the rendered text
is totally correct. So we add a little buffer here. Should add for
user to be able to modify this if needed. If not using edge lengths
then need to use unit length for treeheight.
"""
if not self.tip_labels:
return
# longest name (this will include html hacks)
longest_name = max([len(i) for i in self.tip_labels])
if longest_name > 10:
multiplier = 0.85
else:
multiplier = 0.25
if self.style.use_edge_lengths:
addon = (self.treelist[0].treenode.height + (
self.treelist[0].treenode.height * multiplier))
else:
addon = self.treelist[0].treenode.get_farthest_leaf(True)[1]
# modify display for orientations
if self.style.orient == "right":
self.axes.x.domain.max = addon
elif self.style.orient == "down":
self.axes.y.domain.min = -1 * addon
|
python
|
def fit_tip_labels(self):
"""
Modifies display range to ensure tip labels fit. This is a bit hackish
still. The problem is that the 'extents' range of the rendered text
is totally correct. So we add a little buffer here. Should add for
user to be able to modify this if needed. If not using edge lengths
then need to use unit length for treeheight.
"""
if not self.tip_labels:
return
# longest name (this will include html hacks)
longest_name = max([len(i) for i in self.tip_labels])
if longest_name > 10:
multiplier = 0.85
else:
multiplier = 0.25
if self.style.use_edge_lengths:
addon = (self.treelist[0].treenode.height + (
self.treelist[0].treenode.height * multiplier))
else:
addon = self.treelist[0].treenode.get_farthest_leaf(True)[1]
# modify display for orientations
if self.style.orient == "right":
self.axes.x.domain.max = addon
elif self.style.orient == "down":
self.axes.y.domain.min = -1 * addon
|
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Modifies display range to ensure tip labels fit. This is a bit hackish
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is totally correct. So we add a little buffer here. Should add for
user to be able to modify this if needed. If not using edge lengths
then need to use unit length for treeheight.
|
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"need",
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"unit",
"length",
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"treeheight",
"."
] |
train
|
https://github.com/eaton-lab/toytree/blob/0347ed2098acc5f707fadf52a0ecd411a6d1859c/toytree/MultiDrawing.py#L209-L238
|
doakey3/DashTable
|
dashtable/html2data/restructify/converters/convert_p.py
|
convert_p
|
def convert_p(element, text):
"""
Adds 2 newlines to the end of text
"""
depth = -1
while element:
if (not element.name == '[document]' and
not element.parent.get('id') == '__RESTRUCTIFY_WRAPPER__'):
depth += 1
element = element.parent
if text:
text = ' ' * depth + text
return text
|
python
|
def convert_p(element, text):
"""
Adds 2 newlines to the end of text
"""
depth = -1
while element:
if (not element.name == '[document]' and
not element.parent.get('id') == '__RESTRUCTIFY_WRAPPER__'):
depth += 1
element = element.parent
if text:
text = ' ' * depth + text
return text
|
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":",
"depth",
"+=",
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".",
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"if",
"text",
":",
"text",
"=",
"' '",
"*",
"depth",
"+",
"text",
"return",
"text"
] |
Adds 2 newlines to the end of text
|
[
"Adds",
"2",
"newlines",
"to",
"the",
"end",
"of",
"text"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/html2data/restructify/converters/convert_p.py#L1-L15
|
doakey3/DashTable
|
dashtable/simple2data/simple2data.py
|
simple2data
|
def simple2data(text):
"""
Convert a simple table to data (the kind used by DashTable)
Parameters
----------
text : str
A valid simple rst table
Returns
-------
table : list of lists of str
spans : list of lists of lists of int
A span is a [row, column] pair that defines a group of merged
cells in the table. In a simple rst table, spans can only be
colspans.
use_headers : bool
Whether or not this table uses headers
headers_row : int
The row where headers are located
Notes
-----
This function requires docutils_.
.. _docutils: http://docutils.sourceforge.net/
Example
-------
>>> html_text = '''
... ====== ===== ======
... Inputs Output
... ------------- ------
... A B A or B
... ====== ===== ======
... False False False
... True False True
... False True True
... True True True
... ====== ===== ======
... '''
>>> from dashtable import simple2data
>>> table, spans, use_headers, headers_row = simple2data(html_text)
>>> from pprint import pprint
>>> pprint(table)
[['Inputs', 'Output', ''],
['A', 'B', 'A or B'],
['False', 'False', 'False'],
['True, 'False', 'True'],
['False', 'True', 'True'],
['True', 'True', 'True']]
>>> print(spans)
[[[0, 0], [0, 1]]]
>>> print(use_headers)
True
>>> print(headers_row)
1
"""
try:
import docutils.statemachine
import docutils.parsers.rst.tableparser
except ImportError:
print("ERROR: You must install the docutils library to use simple2data")
return
lines = text.split('\n')
lines = truncate_empty_lines(lines)
leading_space = lines[0].replace(lines[0].lstrip(), '')
for i in range(len(lines)):
lines[i] = lines[i][len(leading_space)::]
parser = docutils.parsers.rst.tableparser.SimpleTableParser()
block = docutils.statemachine.StringList(list(lines))
simple_data = list(parser.parse(block))
column_widths = simple_data.pop(0)
column_count = len(column_widths)
headers_row = 0
if len(simple_data[0]) > 0:
use_headers = True
headers_row = len(simple_data[0]) - 1
headers = simple_data[0][0]
row_count = len(simple_data[1]) + len(simple_data[0])
while len(simple_data[0]) > 0:
simple_data[1].insert(0, simple_data[0][-1])
simple_data[0].pop(-1)
simple_data.pop(0)
else:
use_headers = False
simple_data.pop(0)
row_count = len(simple_data[0])
simple_data = simple_data[0]
table = make_empty_table(row_count, column_count)
spans = []
for row in range(len(simple_data)):
for column in range(len(simple_data[row])):
try:
text = '\n'.join(simple_data[row][column][3]).rstrip()
table[row][column] = text
extra_rows = simple_data[row][column][0]
extra_columns = simple_data[row][column][1]
span = make_span(row, column, extra_rows, extra_columns)
span = sorted(span)
span = list(span for span,_ in itertools.groupby(span))
if not len(span) == 1:
spans.append(span)
except TypeError:
pass
spans = sorted(spans)
return table, spans, use_headers, headers_row
|
python
|
def simple2data(text):
"""
Convert a simple table to data (the kind used by DashTable)
Parameters
----------
text : str
A valid simple rst table
Returns
-------
table : list of lists of str
spans : list of lists of lists of int
A span is a [row, column] pair that defines a group of merged
cells in the table. In a simple rst table, spans can only be
colspans.
use_headers : bool
Whether or not this table uses headers
headers_row : int
The row where headers are located
Notes
-----
This function requires docutils_.
.. _docutils: http://docutils.sourceforge.net/
Example
-------
>>> html_text = '''
... ====== ===== ======
... Inputs Output
... ------------- ------
... A B A or B
... ====== ===== ======
... False False False
... True False True
... False True True
... True True True
... ====== ===== ======
... '''
>>> from dashtable import simple2data
>>> table, spans, use_headers, headers_row = simple2data(html_text)
>>> from pprint import pprint
>>> pprint(table)
[['Inputs', 'Output', ''],
['A', 'B', 'A or B'],
['False', 'False', 'False'],
['True, 'False', 'True'],
['False', 'True', 'True'],
['True', 'True', 'True']]
>>> print(spans)
[[[0, 0], [0, 1]]]
>>> print(use_headers)
True
>>> print(headers_row)
1
"""
try:
import docutils.statemachine
import docutils.parsers.rst.tableparser
except ImportError:
print("ERROR: You must install the docutils library to use simple2data")
return
lines = text.split('\n')
lines = truncate_empty_lines(lines)
leading_space = lines[0].replace(lines[0].lstrip(), '')
for i in range(len(lines)):
lines[i] = lines[i][len(leading_space)::]
parser = docutils.parsers.rst.tableparser.SimpleTableParser()
block = docutils.statemachine.StringList(list(lines))
simple_data = list(parser.parse(block))
column_widths = simple_data.pop(0)
column_count = len(column_widths)
headers_row = 0
if len(simple_data[0]) > 0:
use_headers = True
headers_row = len(simple_data[0]) - 1
headers = simple_data[0][0]
row_count = len(simple_data[1]) + len(simple_data[0])
while len(simple_data[0]) > 0:
simple_data[1].insert(0, simple_data[0][-1])
simple_data[0].pop(-1)
simple_data.pop(0)
else:
use_headers = False
simple_data.pop(0)
row_count = len(simple_data[0])
simple_data = simple_data[0]
table = make_empty_table(row_count, column_count)
spans = []
for row in range(len(simple_data)):
for column in range(len(simple_data[row])):
try:
text = '\n'.join(simple_data[row][column][3]).rstrip()
table[row][column] = text
extra_rows = simple_data[row][column][0]
extra_columns = simple_data[row][column][1]
span = make_span(row, column, extra_rows, extra_columns)
span = sorted(span)
span = list(span for span,_ in itertools.groupby(span))
if not len(span) == 1:
spans.append(span)
except TypeError:
pass
spans = sorted(spans)
return table, spans, use_headers, headers_row
|
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Convert a simple table to data (the kind used by DashTable)
Parameters
----------
text : str
A valid simple rst table
Returns
-------
table : list of lists of str
spans : list of lists of lists of int
A span is a [row, column] pair that defines a group of merged
cells in the table. In a simple rst table, spans can only be
colspans.
use_headers : bool
Whether or not this table uses headers
headers_row : int
The row where headers are located
Notes
-----
This function requires docutils_.
.. _docutils: http://docutils.sourceforge.net/
Example
-------
>>> html_text = '''
... ====== ===== ======
... Inputs Output
... ------------- ------
... A B A or B
... ====== ===== ======
... False False False
... True False True
... False True True
... True True True
... ====== ===== ======
... '''
>>> from dashtable import simple2data
>>> table, spans, use_headers, headers_row = simple2data(html_text)
>>> from pprint import pprint
>>> pprint(table)
[['Inputs', 'Output', ''],
['A', 'B', 'A or B'],
['False', 'False', 'False'],
['True, 'False', 'True'],
['False', 'True', 'True'],
['True', 'True', 'True']]
>>> print(spans)
[[[0, 0], [0, 1]]]
>>> print(use_headers)
True
>>> print(headers_row)
1
|
[
"Convert",
"a",
"simple",
"table",
"to",
"data",
"(",
"the",
"kind",
"used",
"by",
"DashTable",
")"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/simple2data/simple2data.py#L9-L121
|
doakey3/DashTable
|
dashtable/data2rst/get_output_column_widths.py
|
get_output_column_widths
|
def get_output_column_widths(table, spans):
"""
Gets the widths of the columns of the output table
Parameters
----------
table : list of lists of str
The table of rows of text
spans : list of lists of int
The [row, column] pairs of combined cells
Returns
-------
widths : list of int
The widths of each column in the output table
"""
widths = []
for column in table[0]:
widths.append(3)
for row in range(len(table)):
for column in range(len(table[row])):
span = get_span(spans, row, column)
column_count = get_span_column_count(span)
if column_count == 1:
text_row = span[0][0]
text_column = span[0][1]
text = table[text_row][text_column]
length = get_longest_line_length(text)
if length > widths[column]:
widths[column] = length
for row in range(len(table)):
for column in range(len(table[row])):
span = get_span(spans, row, column)
column_count = get_span_column_count(span)
if column_count > 1:
text_row = span[0][0]
text_column = span[0][1]
text = table[text_row][text_column]
end_column = text_column + column_count
available_space = sum(
widths[text_column:end_column])
available_space += column_count - 1
length = get_longest_line_length(text)
while length > available_space:
for i in range(text_column, end_column):
widths[i] += 1
available_space = sum(
widths[text_column:end_column])
available_space += column_count - 1
if length <= available_space:
break
return widths
|
python
|
def get_output_column_widths(table, spans):
"""
Gets the widths of the columns of the output table
Parameters
----------
table : list of lists of str
The table of rows of text
spans : list of lists of int
The [row, column] pairs of combined cells
Returns
-------
widths : list of int
The widths of each column in the output table
"""
widths = []
for column in table[0]:
widths.append(3)
for row in range(len(table)):
for column in range(len(table[row])):
span = get_span(spans, row, column)
column_count = get_span_column_count(span)
if column_count == 1:
text_row = span[0][0]
text_column = span[0][1]
text = table[text_row][text_column]
length = get_longest_line_length(text)
if length > widths[column]:
widths[column] = length
for row in range(len(table)):
for column in range(len(table[row])):
span = get_span(spans, row, column)
column_count = get_span_column_count(span)
if column_count > 1:
text_row = span[0][0]
text_column = span[0][1]
text = table[text_row][text_column]
end_column = text_column + column_count
available_space = sum(
widths[text_column:end_column])
available_space += column_count - 1
length = get_longest_line_length(text)
while length > available_space:
for i in range(text_column, end_column):
widths[i] += 1
available_space = sum(
widths[text_column:end_column])
available_space += column_count - 1
if length <= available_space:
break
return widths
|
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Gets the widths of the columns of the output table
Parameters
----------
table : list of lists of str
The table of rows of text
spans : list of lists of int
The [row, column] pairs of combined cells
Returns
-------
widths : list of int
The widths of each column in the output table
|
[
"Gets",
"the",
"widths",
"of",
"the",
"columns",
"of",
"the",
"output",
"table"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/get_output_column_widths.py#L5-L69
|
doakey3/DashTable
|
dashtable/dashutils/make_empty_table.py
|
make_empty_table
|
def make_empty_table(row_count, column_count):
"""
Make an empty table
Parameters
----------
row_count : int
The number of rows in the new table
column_count : int
The number of columns in the new table
Returns
-------
table : list of lists of str
Each cell will be an empty str ('')
"""
table = []
while row_count > 0:
row = []
for column in range(column_count):
row.append('')
table.append(row)
row_count -= 1
return table
|
python
|
def make_empty_table(row_count, column_count):
"""
Make an empty table
Parameters
----------
row_count : int
The number of rows in the new table
column_count : int
The number of columns in the new table
Returns
-------
table : list of lists of str
Each cell will be an empty str ('')
"""
table = []
while row_count > 0:
row = []
for column in range(column_count):
row.append('')
table.append(row)
row_count -= 1
return table
|
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"(",
"row",
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Make an empty table
Parameters
----------
row_count : int
The number of rows in the new table
column_count : int
The number of columns in the new table
Returns
-------
table : list of lists of str
Each cell will be an empty str ('')
|
[
"Make",
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"empty",
"table"
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/dashutils/make_empty_table.py#L1-L24
|
quantmind/dynts
|
dynts/lib/fallback/ols.py
|
ols.beta
|
def beta(self):
'''\
The linear estimation of the parameter vector :math:`\beta` given by
.. math::
\beta = (X^T X)^-1 X^T y
'''
t = self.X.transpose()
XX = dot(t,self.X)
XY = dot(t,self.y)
return linalg.solve(XX,XY)
|
python
|
def beta(self):
'''\
The linear estimation of the parameter vector :math:`\beta` given by
.. math::
\beta = (X^T X)^-1 X^T y
'''
t = self.X.transpose()
XX = dot(t,self.X)
XY = dot(t,self.y)
return linalg.solve(XX,XY)
|
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train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/lib/fallback/ols.py#L30-L42
|
quantmind/dynts
|
dynts/api/data.py
|
FormatterDict.oftype
|
def oftype(self, typ):
'''Return a generator of formatters codes of type typ'''
for key, val in self.items():
if val.type == typ:
yield key
|
python
|
def oftype(self, typ):
'''Return a generator of formatters codes of type typ'''
for key, val in self.items():
if val.type == typ:
yield key
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[
"Return",
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"codes",
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"type",
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train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/api/data.py#L7-L11
|
quantmind/dynts
|
dynts/api/data.py
|
Data.names
|
def names(self, with_namespace=False):
'''List of names for series in dataset.
It will always return a list or names with length given by
:class:`~.DynData.count`.
'''
N = self.count()
names = self.name.split(settings.splittingnames)[:N]
n = 0
while len(names) < N:
n += 1
names.append('unnamed%s' % n)
if with_namespace and self.namespace:
n = self.namespace
s = settings.field_separator
return [n + s + f for f in names]
else:
return names
|
python
|
def names(self, with_namespace=False):
'''List of names for series in dataset.
It will always return a list or names with length given by
:class:`~.DynData.count`.
'''
N = self.count()
names = self.name.split(settings.splittingnames)[:N]
n = 0
while len(names) < N:
n += 1
names.append('unnamed%s' % n)
if with_namespace and self.namespace:
n = self.namespace
s = settings.field_separator
return [n + s + f for f in names]
else:
return names
|
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List of names for series in dataset.
It will always return a list or names with length given by
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[
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"."
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train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/api/data.py#L50-L67
|
quantmind/dynts
|
dynts/api/data.py
|
Data.dump
|
def dump(self, format=None, **kwargs):
"""Dump the timeseries using a specific ``format``.
"""
formatter = Formatters.get(format, None)
if not format:
return self.display()
elif not formatter:
raise FormattingException('Formatter %s not available' % format)
else:
return formatter(self, **kwargs)
|
python
|
def dump(self, format=None, **kwargs):
"""Dump the timeseries using a specific ``format``.
"""
formatter = Formatters.get(format, None)
if not format:
return self.display()
elif not formatter:
raise FormattingException('Formatter %s not available' % format)
else:
return formatter(self, **kwargs)
|
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[
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train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/api/data.py#L88-L97
|
quantmind/dynts
|
dynts/dsl/grammar.py
|
p_expression_binop
|
def p_expression_binop(p):
'''expression : expression PLUS expression
| expression MINUS expression
| expression TIMES expression
| expression DIVIDE expression
| expression EQUAL expression
| expression CONCAT expression
| expression SPLIT expression'''
v = p[2]
if v == '+':
p[0] = PlusOp(p[1], p[3])
elif v == '-':
p[0] = MinusOp(p[1], p[3])
elif v == '*':
p[0] = MultiplyOp(p[1], p[3])
elif v == '/':
p[0] = DivideOp(p[1], p[3])
elif v == '=':
p[0] = EqualOp(p[1], p[3])
elif v == settings.concat_operator:
p[0] = ConcatenationOp(p[1], p[3])
elif v == settings.separator_operator:
p[0] = SplittingOp(p[1], p[3])
elif v == settings.field_operator:
p[0] = Symbol(p[1], field=p[3])
|
python
|
def p_expression_binop(p):
'''expression : expression PLUS expression
| expression MINUS expression
| expression TIMES expression
| expression DIVIDE expression
| expression EQUAL expression
| expression CONCAT expression
| expression SPLIT expression'''
v = p[2]
if v == '+':
p[0] = PlusOp(p[1], p[3])
elif v == '-':
p[0] = MinusOp(p[1], p[3])
elif v == '*':
p[0] = MultiplyOp(p[1], p[3])
elif v == '/':
p[0] = DivideOp(p[1], p[3])
elif v == '=':
p[0] = EqualOp(p[1], p[3])
elif v == settings.concat_operator:
p[0] = ConcatenationOp(p[1], p[3])
elif v == settings.separator_operator:
p[0] = SplittingOp(p[1], p[3])
elif v == settings.field_operator:
p[0] = Symbol(p[1], field=p[3])
|
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train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/dsl/grammar.py#L15-L39
|
quantmind/dynts
|
dynts/dsl/grammar.py
|
p_expression_group
|
def p_expression_group(p):
'''expression : LPAREN expression RPAREN
| LSQUARE expression RSQUARE'''
v = p[1]
if v == '(':
p[0] = functionarguments(p[2])
elif v == '[':
p[0] = tsentry(p[2])
|
python
|
def p_expression_group(p):
'''expression : LPAREN expression RPAREN
| LSQUARE expression RSQUARE'''
v = p[1]
if v == '(':
p[0] = functionarguments(p[2])
elif v == '[':
p[0] = tsentry(p[2])
|
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[
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] |
train
|
https://github.com/quantmind/dynts/blob/21ac57c648bfec402fa6b1fe569496cf098fb5e8/dynts/dsl/grammar.py#L42-L49
|
doakey3/DashTable
|
dashtable/data2rst/cell/merge_cells.py
|
merge_cells
|
def merge_cells(cell1, cell2, direction):
"""
Combine the side of cell1's grid text with cell2's text.
For example::
cell1 cell2 merge "RIGHT"
+-----+ +------+ +-----+------+
| foo | | dog | | foo | dog |
| | +------+ | +------+
| | | cat | | | cat |
| | +------+ | +------+
| | | bird | | | bird |
+-----+ +------+ +-----+------+
Parameters
----------
cell1 : dashtable.data2rst.Cell
cell2 : dashtable.data2rst.Cell
"""
cell1_lines = cell1.text.split("\n")
cell2_lines = cell2.text.split("\n")
if direction == "RIGHT":
for i in range(len(cell1_lines)):
cell1_lines[i] = cell1_lines[i] + cell2_lines[i][1::]
cell1.text = "\n".join(cell1_lines)
cell1.column_count += cell2.column_count
elif direction == "TOP":
if cell1_lines[0].count('+') > cell2_lines[-1].count('+'):
cell2_lines.pop(-1)
else:
cell1_lines.pop(0)
cell2_lines.extend(cell1_lines)
cell1.text = "\n".join(cell2_lines)
cell1.row_count += cell2.row_count
cell1.row = cell2.row
cell1.column = cell2.column
elif direction == "BOTTOM":
if (cell1_lines[-1].count('+') > cell2_lines[0].count('+') or
cell1.is_header):
cell2_lines.pop(0)
else:
cell1_lines.pop(-1)
cell1_lines.extend(cell2_lines)
cell1.text = "\n".join(cell1_lines)
cell1.row_count += cell2.row_count
elif direction == "LEFT":
for i in range(len(cell1_lines)):
cell1_lines[i] = cell2_lines[i][0:-1] + cell1_lines[i]
cell1.text = "\n".join(cell1_lines)
cell1.column_count += cell2.column_count
cell1.row = cell2.row
cell1.column = cell2.column
|
python
|
def merge_cells(cell1, cell2, direction):
"""
Combine the side of cell1's grid text with cell2's text.
For example::
cell1 cell2 merge "RIGHT"
+-----+ +------+ +-----+------+
| foo | | dog | | foo | dog |
| | +------+ | +------+
| | | cat | | | cat |
| | +------+ | +------+
| | | bird | | | bird |
+-----+ +------+ +-----+------+
Parameters
----------
cell1 : dashtable.data2rst.Cell
cell2 : dashtable.data2rst.Cell
"""
cell1_lines = cell1.text.split("\n")
cell2_lines = cell2.text.split("\n")
if direction == "RIGHT":
for i in range(len(cell1_lines)):
cell1_lines[i] = cell1_lines[i] + cell2_lines[i][1::]
cell1.text = "\n".join(cell1_lines)
cell1.column_count += cell2.column_count
elif direction == "TOP":
if cell1_lines[0].count('+') > cell2_lines[-1].count('+'):
cell2_lines.pop(-1)
else:
cell1_lines.pop(0)
cell2_lines.extend(cell1_lines)
cell1.text = "\n".join(cell2_lines)
cell1.row_count += cell2.row_count
cell1.row = cell2.row
cell1.column = cell2.column
elif direction == "BOTTOM":
if (cell1_lines[-1].count('+') > cell2_lines[0].count('+') or
cell1.is_header):
cell2_lines.pop(0)
else:
cell1_lines.pop(-1)
cell1_lines.extend(cell2_lines)
cell1.text = "\n".join(cell1_lines)
cell1.row_count += cell2.row_count
elif direction == "LEFT":
for i in range(len(cell1_lines)):
cell1_lines[i] = cell2_lines[i][0:-1] + cell1_lines[i]
cell1.text = "\n".join(cell1_lines)
cell1.column_count += cell2.column_count
cell1.row = cell2.row
cell1.column = cell2.column
|
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] |
Combine the side of cell1's grid text with cell2's text.
For example::
cell1 cell2 merge "RIGHT"
+-----+ +------+ +-----+------+
| foo | | dog | | foo | dog |
| | +------+ | +------+
| | | cat | | | cat |
| | +------+ | +------+
| | | bird | | | bird |
+-----+ +------+ +-----+------+
Parameters
----------
cell1 : dashtable.data2rst.Cell
cell2 : dashtable.data2rst.Cell
|
[
"Combine",
"the",
"side",
"of",
"cell1",
"s",
"grid",
"text",
"with",
"cell2",
"s",
"text",
"."
] |
train
|
https://github.com/doakey3/DashTable/blob/744cfb6a717fa75a8092c83ebcd49b2668023681/dashtable/data2rst/cell/merge_cells.py#L1-L59
|
rbarrois/xworkflows
|
src/xworkflows/utils.py
|
iterclass
|
def iterclass(cls):
"""Iterates over (valid) attributes of a class.
Args:
cls (object): the class to iterate over
Yields:
(str, obj) tuples: the class-level attributes.
"""
for field in dir(cls):
if hasattr(cls, field):
value = getattr(cls, field)
yield field, value
|
python
|
def iterclass(cls):
"""Iterates over (valid) attributes of a class.
Args:
cls (object): the class to iterate over
Yields:
(str, obj) tuples: the class-level attributes.
"""
for field in dir(cls):
if hasattr(cls, field):
value = getattr(cls, field)
yield field, value
|
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Iterates over (valid) attributes of a class.
Args:
cls (object): the class to iterate over
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(str, obj) tuples: the class-level attributes.
|
[
"Iterates",
"over",
"(",
"valid",
")",
"attributes",
"of",
"a",
"class",
"."
] |
train
|
https://github.com/rbarrois/xworkflows/blob/4a94b04ba83cb43f61d4b0f7db6964a667c86b5b/src/xworkflows/utils.py#L9-L21
|
orionvm/potsdb
|
potsdb/client.py
|
_mksocket
|
def _mksocket(host, port, q, done, stop):
"""Returns a tcp socket to (host/port). Retries forever if connection fails"""
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.settimeout(2)
attempt = 0
while not stop.is_set():
try:
s.connect((host, port))
return s
except Exception as ex:
# Simple exponential backoff: sleep for 1,2,4,8,16,30,30...
time.sleep(min(30, 2 ** attempt))
attempt += 1
|
python
|
def _mksocket(host, port, q, done, stop):
"""Returns a tcp socket to (host/port). Retries forever if connection fails"""
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.settimeout(2)
attempt = 0
while not stop.is_set():
try:
s.connect((host, port))
return s
except Exception as ex:
# Simple exponential backoff: sleep for 1,2,4,8,16,30,30...
time.sleep(min(30, 2 ** attempt))
attempt += 1
|
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"2",
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Returns a tcp socket to (host/port). Retries forever if connection fails
|
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"(",
"host",
"/",
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")",
".",
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"connection",
"fails"
] |
train
|
https://github.com/orionvm/potsdb/blob/f242f8ad97c4e5887b3c39a082f6bdc4be46661c/potsdb/client.py#L21-L33
|
orionvm/potsdb
|
potsdb/client.py
|
_push
|
def _push(host, port, q, done, mps, stop, test_mode):
"""Worker thread. Connect to host/port, pull data from q until done is set"""
sock = None
retry_line = None
while not ( stop.is_set() or ( done.is_set() and retry_line == None and q.empty()) ):
stime = time.time()
if sock == None and not test_mode:
sock = _mksocket(host, port, q, done, stop)
if sock == None:
break
if retry_line:
line = retry_line
retry_line = None
else:
try:
line = q.get(True, 1) # blocking, with 1 second timeout
except:
if done.is_set(): # no items in queue, and parent finished
break
else: # no items in queue, but parent might send more
continue
if not test_mode:
try:
sock.sendall(line.encode('utf-8'))
except:
sock = None # notify that we need to make a new socket at start of loop
retry_line = line # can't really put back in q, so remember to retry this line
continue
etime = time.time() - stime #time that actually elapsed
#Expected value of wait_time is 1/MPS_LIMIT, ie. MPS_LIMIT per second.
if mps > 0:
wait_time = (2.0 * random.random()) / (mps)
if wait_time > etime: #if we should wait
time.sleep(wait_time - etime) #then wait
if sock:
sock.close()
|
python
|
def _push(host, port, q, done, mps, stop, test_mode):
"""Worker thread. Connect to host/port, pull data from q until done is set"""
sock = None
retry_line = None
while not ( stop.is_set() or ( done.is_set() and retry_line == None and q.empty()) ):
stime = time.time()
if sock == None and not test_mode:
sock = _mksocket(host, port, q, done, stop)
if sock == None:
break
if retry_line:
line = retry_line
retry_line = None
else:
try:
line = q.get(True, 1) # blocking, with 1 second timeout
except:
if done.is_set(): # no items in queue, and parent finished
break
else: # no items in queue, but parent might send more
continue
if not test_mode:
try:
sock.sendall(line.encode('utf-8'))
except:
sock = None # notify that we need to make a new socket at start of loop
retry_line = line # can't really put back in q, so remember to retry this line
continue
etime = time.time() - stime #time that actually elapsed
#Expected value of wait_time is 1/MPS_LIMIT, ie. MPS_LIMIT per second.
if mps > 0:
wait_time = (2.0 * random.random()) / (mps)
if wait_time > etime: #if we should wait
time.sleep(wait_time - etime) #then wait
if sock:
sock.close()
|
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|
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"/",
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"until",
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"is",
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train
|
https://github.com/orionvm/potsdb/blob/f242f8ad97c4e5887b3c39a082f6bdc4be46661c/potsdb/client.py#L35-L76
|
orionvm/potsdb
|
potsdb/client.py
|
Client.log
|
def log(self, name, val, **tags):
"""Log metric name with value val. You must include at least one tag as a kwarg"""
global _last_timestamp, _last_metrics
# do not allow .log after closing
assert not self.done.is_set(), "worker thread has been closed"
# check if valid metric name
assert all(c in _valid_metric_chars for c in name), "invalid metric name " + name
val = float(val) #Duck type to float/int, if possible.
if int(val) == val:
val = int(val)
if self.host_tag and 'host' not in tags:
tags['host'] = self.host_tag
# get timestamp from system time, unless it's supplied as a tag
timestamp = int(tags.pop('timestamp', time.time()))
assert not self.done.is_set(), "tsdb object has been closed"
assert tags != {}, "Need at least one tag"
tagvals = ' '.join(['%s=%s' % (k, v) for k, v in tags.items()])
# OpenTSDB has major problems if you insert a data point with the same
# metric, timestamp and tags. So we keep a temporary set of what points
# we have sent for the last timestamp value. If we encounter a duplicate,
# it is dropped.
unique_str = "%s, %s, %s, %s, %s" % (name, timestamp, tagvals, self.host, self.port)
if timestamp == _last_timestamp or _last_timestamp == None:
if unique_str in _last_metrics:
return # discard duplicate metrics
else:
_last_metrics.add(unique_str)
else:
_last_timestamp = timestamp
_last_metrics.clear()
line = "put %s %d %s %s\n" % (name, timestamp, val, tagvals)
try:
self.q.put(line, False)
self.queued += 1
except queue.Full:
print("potsdb - Warning: dropping oldest metric because Queue is full. Size: %s" % self.q.qsize(), file=sys.stderr)
self.q.get() #Drop the oldest metric to make room
self.q.put(line, False)
return line
|
python
|
def log(self, name, val, **tags):
"""Log metric name with value val. You must include at least one tag as a kwarg"""
global _last_timestamp, _last_metrics
# do not allow .log after closing
assert not self.done.is_set(), "worker thread has been closed"
# check if valid metric name
assert all(c in _valid_metric_chars for c in name), "invalid metric name " + name
val = float(val) #Duck type to float/int, if possible.
if int(val) == val:
val = int(val)
if self.host_tag and 'host' not in tags:
tags['host'] = self.host_tag
# get timestamp from system time, unless it's supplied as a tag
timestamp = int(tags.pop('timestamp', time.time()))
assert not self.done.is_set(), "tsdb object has been closed"
assert tags != {}, "Need at least one tag"
tagvals = ' '.join(['%s=%s' % (k, v) for k, v in tags.items()])
# OpenTSDB has major problems if you insert a data point with the same
# metric, timestamp and tags. So we keep a temporary set of what points
# we have sent for the last timestamp value. If we encounter a duplicate,
# it is dropped.
unique_str = "%s, %s, %s, %s, %s" % (name, timestamp, tagvals, self.host, self.port)
if timestamp == _last_timestamp or _last_timestamp == None:
if unique_str in _last_metrics:
return # discard duplicate metrics
else:
_last_metrics.add(unique_str)
else:
_last_timestamp = timestamp
_last_metrics.clear()
line = "put %s %d %s %s\n" % (name, timestamp, val, tagvals)
try:
self.q.put(line, False)
self.queued += 1
except queue.Full:
print("potsdb - Warning: dropping oldest metric because Queue is full. Size: %s" % self.q.qsize(), file=sys.stderr)
self.q.get() #Drop the oldest metric to make room
self.q.put(line, False)
return line
|
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|
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train
|
https://github.com/orionvm/potsdb/blob/f242f8ad97c4e5887b3c39a082f6bdc4be46661c/potsdb/client.py#L112-L159
|
cedrus-opensource/pyxid
|
pyxid/serial_wrapper.py
|
GenericSerialPort.available_ports
|
def available_ports():
"""
Scans COM1 through COM255 for available serial ports
returns a list of available ports
"""
ports = []
for i in range(256):
try:
p = Serial('COM%d' % i)
p.close()
ports.append(p)
except SerialException:
pass
return ports
|
python
|
def available_ports():
"""
Scans COM1 through COM255 for available serial ports
returns a list of available ports
"""
ports = []
for i in range(256):
try:
p = Serial('COM%d' % i)
p.close()
ports.append(p)
except SerialException:
pass
return ports
|
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Scans COM1 through COM255 for available serial ports
returns a list of available ports
|
[
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"COM255",
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"serial",
"ports"
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/serial_wrapper.py#L62-L78
|
cedrus-opensource/pyxid
|
pyxid/internal.py
|
XidConnection.get_current_response
|
def get_current_response(self):
"""
reads the current response data from the object and returns
it in a dict.
Currently 'time' is reported as 0 until clock drift issues are
resolved.
"""
response = {'port': 0,
'pressed': False,
'key': 0,
'time': 0}
if len(self.__response_structs_queue) > 0:
# make a copy just in case any other internal members of
# XidConnection were tracking the structure
response = self.__response_structs_queue[0].copy()
# we will now hand over 'response' to the calling code,
# so remove it from the internal queue
self.__response_structs_queue.pop(0)
return response
|
python
|
def get_current_response(self):
"""
reads the current response data from the object and returns
it in a dict.
Currently 'time' is reported as 0 until clock drift issues are
resolved.
"""
response = {'port': 0,
'pressed': False,
'key': 0,
'time': 0}
if len(self.__response_structs_queue) > 0:
# make a copy just in case any other internal members of
# XidConnection were tracking the structure
response = self.__response_structs_queue[0].copy()
# we will now hand over 'response' to the calling code,
# so remove it from the internal queue
self.__response_structs_queue.pop(0)
return response
|
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"__response_structs_queue",
".",
"pop",
"(",
"0",
")",
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] |
reads the current response data from the object and returns
it in a dict.
Currently 'time' is reported as 0 until clock drift issues are
resolved.
|
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] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/internal.py#L230-L250
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
XidScanner.detect_xid_devices
|
def detect_xid_devices(self):
"""
For all of the com ports connected to the computer, send an
XID command '_c1'. If the device response with '_xid', it is
an xid device.
"""
self.__xid_cons = []
for c in self.__com_ports:
device_found = False
for b in [115200, 19200, 9600, 57600, 38400]:
con = XidConnection(c, b)
try:
con.open()
except SerialException:
continue
con.flush_input()
con.flush_output()
returnval = con.send_xid_command("_c1", 5).decode('ASCII')
if returnval.startswith('_xid'):
device_found = True
self.__xid_cons.append(con)
if(returnval != '_xid0'):
# set the device into XID mode
con.send_xid_command('c10')
con.flush_input()
con.flush_output()
# be sure to reset the timer to avoid the 4.66 hours
# problem. (refer to XidConnection.xid_input_found to
# read about the 4.66 hours)
con.send_xid_command('e1')
con.send_xid_command('e5')
con.close()
if device_found:
break
|
python
|
def detect_xid_devices(self):
"""
For all of the com ports connected to the computer, send an
XID command '_c1'. If the device response with '_xid', it is
an xid device.
"""
self.__xid_cons = []
for c in self.__com_ports:
device_found = False
for b in [115200, 19200, 9600, 57600, 38400]:
con = XidConnection(c, b)
try:
con.open()
except SerialException:
continue
con.flush_input()
con.flush_output()
returnval = con.send_xid_command("_c1", 5).decode('ASCII')
if returnval.startswith('_xid'):
device_found = True
self.__xid_cons.append(con)
if(returnval != '_xid0'):
# set the device into XID mode
con.send_xid_command('c10')
con.flush_input()
con.flush_output()
# be sure to reset the timer to avoid the 4.66 hours
# problem. (refer to XidConnection.xid_input_found to
# read about the 4.66 hours)
con.send_xid_command('e1')
con.send_xid_command('e5')
con.close()
if device_found:
break
|
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For all of the com ports connected to the computer, send an
XID command '_c1'. If the device response with '_xid', it is
an xid device.
|
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"an",
"xid",
"device",
"."
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L21-L61
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
XidScanner.device_at_index
|
def device_at_index(self, index):
"""
Returns the device at the specified index
"""
if index >= len(self.__xid_cons):
raise ValueError("Invalid device index")
return self.__xid_cons[index]
|
python
|
def device_at_index(self, index):
"""
Returns the device at the specified index
"""
if index >= len(self.__xid_cons):
raise ValueError("Invalid device index")
return self.__xid_cons[index]
|
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".",
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"[",
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Returns the device at the specified index
|
[
"Returns",
"the",
"device",
"at",
"the",
"specified",
"index"
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L63-L70
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
BaseDevice.query_base_timer
|
def query_base_timer(self):
"""
gets the value from the device's base timer
"""
(_, _, time) = unpack('<ccI', self.con.send_xid_command("e3", 6))
return time
|
python
|
def query_base_timer(self):
"""
gets the value from the device's base timer
"""
(_, _, time) = unpack('<ccI', self.con.send_xid_command("e3", 6))
return time
|
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"send_xid_command",
"(",
"\"e3\"",
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"6",
")",
")",
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gets the value from the device's base timer
|
[
"gets",
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"from",
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"device",
"s",
"base",
"timer"
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L96-L101
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
ResponseDevice.poll_for_response
|
def poll_for_response(self):
"""
Polls the device for user input
If there is a keymapping for the device, the key map is applied
to the key reported from the device.
If a response is waiting to be processed, the response is appended
to the internal response_queue
"""
key_state = self.con.check_for_keypress()
if key_state != NO_KEY_DETECTED:
response = self.con.get_current_response()
if self.keymap is not None:
response['key'] = self.keymap[response['key']]
else:
response['key'] -= 1
self.response_queue.append(response)
|
python
|
def poll_for_response(self):
"""
Polls the device for user input
If there is a keymapping for the device, the key map is applied
to the key reported from the device.
If a response is waiting to be processed, the response is appended
to the internal response_queue
"""
key_state = self.con.check_for_keypress()
if key_state != NO_KEY_DETECTED:
response = self.con.get_current_response()
if self.keymap is not None:
response['key'] = self.keymap[response['key']]
else:
response['key'] -= 1
self.response_queue.append(response)
|
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to the internal response_queue
|
[
"Polls",
"the",
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"for",
"user",
"input"
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L114-L134
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
StimTracker.set_pulse_duration
|
def set_pulse_duration(self, duration):
"""
Sets the pulse duration for events in miliseconds when activate_line
is called
"""
if duration > 4294967295:
raise ValueError('Duration is too long. Please choose a value '
'less than 4294967296.')
big_endian = hex(duration)[2:]
if len(big_endian) % 2 != 0:
big_endian = '0'+big_endian
little_endian = []
for i in range(0, len(big_endian), 2):
little_endian.insert(0, big_endian[i:i+2])
for i in range(0, 4-len(little_endian)):
little_endian.append('00')
command = 'mp'
for i in little_endian:
command += chr(int(i, 16))
self.con.send_xid_command(command, 0)
|
python
|
def set_pulse_duration(self, duration):
"""
Sets the pulse duration for events in miliseconds when activate_line
is called
"""
if duration > 4294967295:
raise ValueError('Duration is too long. Please choose a value '
'less than 4294967296.')
big_endian = hex(duration)[2:]
if len(big_endian) % 2 != 0:
big_endian = '0'+big_endian
little_endian = []
for i in range(0, len(big_endian), 2):
little_endian.insert(0, big_endian[i:i+2])
for i in range(0, 4-len(little_endian)):
little_endian.append('00')
command = 'mp'
for i in little_endian:
command += chr(int(i, 16))
self.con.send_xid_command(command, 0)
|
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|
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train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L196-L221
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
StimTracker.activate_line
|
def activate_line(self, lines=None, bitmask=None,
leave_remaining_lines=False):
"""
Triggers an output line on StimTracker.
There are 8 output lines on StimTracker that can be raised in any
combination. To raise lines 1 and 7, for example, you pass in
the list: activate_line(lines=[1, 7]).
To raise a single line, pass in just an integer, or a list with a
single element to the lines keyword argument:
activate_line(lines=3)
or
activate_line(lines=[3])
The `lines` argument must either be an Integer, list of Integers, or
None.
If you'd rather specify a bitmask for setting the lines, you can use
the bitmask keyword argument. Bitmask must be a Integer value between
0 and 255 where 0 specifies no lines, and 255 is all lines. For a
mapping between lines and their bit values, see the `_lines` class
variable.
To use this, call the function as so to activate lines 1 and 6:
activate_line(bitmask=33)
leave_remaining_lines tells the function to only operate on the lines
specified. For example, if lines 1 and 8 are active, and you make
the following function call:
activate_line(lines=4, leave_remaining_lines=True)
This will result in lines 1, 4 and 8 being active.
If you call activate_line(lines=4) with leave_remaining_lines=False
(the default), if lines 1 and 8 were previously active, only line 4
will be active after the call.
"""
if lines is None and bitmask is None:
raise ValueError('Must set one of lines or bitmask')
if lines is not None and bitmask is not None:
raise ValueError('Can only set one of lines or bitmask')
if bitmask is not None:
if bitmask not in range(0, 256):
raise ValueError('bitmask must be an integer between '
'0 and 255')
if lines is not None:
if not isinstance(lines, list):
lines = [lines]
bitmask = 0
for l in lines:
if l < 1 or l > 8:
raise ValueError('Line numbers must be between 1 and 8 '
'(inclusive)')
bitmask |= self._lines[l]
self.con.set_digital_output_lines(bitmask, leave_remaining_lines)
|
python
|
def activate_line(self, lines=None, bitmask=None,
leave_remaining_lines=False):
"""
Triggers an output line on StimTracker.
There are 8 output lines on StimTracker that can be raised in any
combination. To raise lines 1 and 7, for example, you pass in
the list: activate_line(lines=[1, 7]).
To raise a single line, pass in just an integer, or a list with a
single element to the lines keyword argument:
activate_line(lines=3)
or
activate_line(lines=[3])
The `lines` argument must either be an Integer, list of Integers, or
None.
If you'd rather specify a bitmask for setting the lines, you can use
the bitmask keyword argument. Bitmask must be a Integer value between
0 and 255 where 0 specifies no lines, and 255 is all lines. For a
mapping between lines and their bit values, see the `_lines` class
variable.
To use this, call the function as so to activate lines 1 and 6:
activate_line(bitmask=33)
leave_remaining_lines tells the function to only operate on the lines
specified. For example, if lines 1 and 8 are active, and you make
the following function call:
activate_line(lines=4, leave_remaining_lines=True)
This will result in lines 1, 4 and 8 being active.
If you call activate_line(lines=4) with leave_remaining_lines=False
(the default), if lines 1 and 8 were previously active, only line 4
will be active after the call.
"""
if lines is None and bitmask is None:
raise ValueError('Must set one of lines or bitmask')
if lines is not None and bitmask is not None:
raise ValueError('Can only set one of lines or bitmask')
if bitmask is not None:
if bitmask not in range(0, 256):
raise ValueError('bitmask must be an integer between '
'0 and 255')
if lines is not None:
if not isinstance(lines, list):
lines = [lines]
bitmask = 0
for l in lines:
if l < 1 or l > 8:
raise ValueError('Line numbers must be between 1 and 8 '
'(inclusive)')
bitmask |= self._lines[l]
self.con.set_digital_output_lines(bitmask, leave_remaining_lines)
|
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Triggers an output line on StimTracker.
There are 8 output lines on StimTracker that can be raised in any
combination. To raise lines 1 and 7, for example, you pass in
the list: activate_line(lines=[1, 7]).
To raise a single line, pass in just an integer, or a list with a
single element to the lines keyword argument:
activate_line(lines=3)
or
activate_line(lines=[3])
The `lines` argument must either be an Integer, list of Integers, or
None.
If you'd rather specify a bitmask for setting the lines, you can use
the bitmask keyword argument. Bitmask must be a Integer value between
0 and 255 where 0 specifies no lines, and 255 is all lines. For a
mapping between lines and their bit values, see the `_lines` class
variable.
To use this, call the function as so to activate lines 1 and 6:
activate_line(bitmask=33)
leave_remaining_lines tells the function to only operate on the lines
specified. For example, if lines 1 and 8 are active, and you make
the following function call:
activate_line(lines=4, leave_remaining_lines=True)
This will result in lines 1, 4 and 8 being active.
If you call activate_line(lines=4) with leave_remaining_lines=False
(the default), if lines 1 and 8 were previously active, only line 4
will be active after the call.
|
[
"Triggers",
"an",
"output",
"line",
"on",
"StimTracker",
"."
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L223-L287
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
StimTracker.clear_line
|
def clear_line(self, lines=None, bitmask=None,
leave_remaining_lines=False):
"""
The inverse of activate_line. If a line is active, it deactivates it.
This has the same parameters as activate_line()
"""
if lines is None and bitmask is None:
raise ValueError('Must set one of lines or bitmask')
if lines is not None and bitmask is not None:
raise ValueError('Can only set one of lines or bitmask')
if bitmask is not None:
if bitmask not in range(0, 256):
raise ValueError('bitmask must be an integer between '
'0 and 255')
if lines is not None:
if not isinstance(lines, list):
lines = [lines]
bitmask = 0
for l in lines:
if l < 1 or l > 8:
raise ValueError('Line numbers must be between 1 and 8 '
'(inclusive)')
bitmask |= self._lines[l]
self.con.clear_digital_output_lines(bitmask, leave_remaining_lines)
|
python
|
def clear_line(self, lines=None, bitmask=None,
leave_remaining_lines=False):
"""
The inverse of activate_line. If a line is active, it deactivates it.
This has the same parameters as activate_line()
"""
if lines is None and bitmask is None:
raise ValueError('Must set one of lines or bitmask')
if lines is not None and bitmask is not None:
raise ValueError('Can only set one of lines or bitmask')
if bitmask is not None:
if bitmask not in range(0, 256):
raise ValueError('bitmask must be an integer between '
'0 and 255')
if lines is not None:
if not isinstance(lines, list):
lines = [lines]
bitmask = 0
for l in lines:
if l < 1 or l > 8:
raise ValueError('Line numbers must be between 1 and 8 '
'(inclusive)')
bitmask |= self._lines[l]
self.con.clear_digital_output_lines(bitmask, leave_remaining_lines)
|
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The inverse of activate_line. If a line is active, it deactivates it.
This has the same parameters as activate_line()
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train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L289-L317
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
XidDevice.init_device
|
def init_device(self):
"""
Initializes the device with the proper keymaps and name
"""
try:
product_id = int(self._send_command('_d2', 1))
except ValueError:
product_id = self._send_command('_d2', 1)
if product_id == 0:
self._impl = ResponseDevice(
self.con,
'Cedrus Lumina LP-400 Response Pad System',
lumina_keymap)
elif product_id == 1:
self._impl = ResponseDevice(
self.con,
'Cedrus SV-1 Voice Key',
None,
'Voice Response')
elif product_id == 2:
model_id = int(self._send_command('_d3', 1))
if model_id == 1:
self._impl = ResponseDevice(
self.con,
'Cedrus RB-530',
rb_530_keymap)
elif model_id == 2:
self._impl = ResponseDevice(
self.con,
'Cedrus RB-730',
rb_730_keymap)
elif model_id == 3:
self._impl = ResponseDevice(
self.con,
'Cedrus RB-830',
rb_830_keymap)
elif model_id == 4:
self._impl = ResponseDevice(
self.con,
'Cedrus RB-834',
rb_834_keymap)
else:
raise XidError('Unknown RB Device')
elif product_id == 4:
self._impl = StimTracker(
self.con,
'Cedrus C-POD')
elif product_id == b'S':
self._impl = StimTracker(
self.con,
'Cedrus StimTracker')
elif product_id == -99:
raise XidError('Invalid XID device')
|
python
|
def init_device(self):
"""
Initializes the device with the proper keymaps and name
"""
try:
product_id = int(self._send_command('_d2', 1))
except ValueError:
product_id = self._send_command('_d2', 1)
if product_id == 0:
self._impl = ResponseDevice(
self.con,
'Cedrus Lumina LP-400 Response Pad System',
lumina_keymap)
elif product_id == 1:
self._impl = ResponseDevice(
self.con,
'Cedrus SV-1 Voice Key',
None,
'Voice Response')
elif product_id == 2:
model_id = int(self._send_command('_d3', 1))
if model_id == 1:
self._impl = ResponseDevice(
self.con,
'Cedrus RB-530',
rb_530_keymap)
elif model_id == 2:
self._impl = ResponseDevice(
self.con,
'Cedrus RB-730',
rb_730_keymap)
elif model_id == 3:
self._impl = ResponseDevice(
self.con,
'Cedrus RB-830',
rb_830_keymap)
elif model_id == 4:
self._impl = ResponseDevice(
self.con,
'Cedrus RB-834',
rb_834_keymap)
else:
raise XidError('Unknown RB Device')
elif product_id == 4:
self._impl = StimTracker(
self.con,
'Cedrus C-POD')
elif product_id == b'S':
self._impl = StimTracker(
self.con,
'Cedrus StimTracker')
elif product_id == -99:
raise XidError('Invalid XID device')
|
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Initializes the device with the proper keymaps and name
|
[
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"and",
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] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L363-L417
|
cedrus-opensource/pyxid
|
pyxid/pyxid_impl.py
|
XidDevice._send_command
|
def _send_command(self, command, expected_bytes):
"""
Send an XID command to the device
"""
response = self.con.send_xid_command(command, expected_bytes)
return response
|
python
|
def _send_command(self, command, expected_bytes):
"""
Send an XID command to the device
"""
response = self.con.send_xid_command(command, expected_bytes)
return response
|
[
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".",
"send_xid_command",
"(",
"command",
",",
"expected_bytes",
")",
"return",
"response"
] |
Send an XID command to the device
|
[
"Send",
"an",
"XID",
"command",
"to",
"the",
"device"
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/pyxid_impl.py#L419-L425
|
cedrus-opensource/pyxid
|
pyxid/__init__.py
|
get_xid_devices
|
def get_xid_devices():
"""
Returns a list of all Xid devices connected to your computer.
"""
devices = []
scanner = XidScanner()
for i in range(scanner.device_count()):
com = scanner.device_at_index(i)
com.open()
device = XidDevice(com)
devices.append(device)
return devices
|
python
|
def get_xid_devices():
"""
Returns a list of all Xid devices connected to your computer.
"""
devices = []
scanner = XidScanner()
for i in range(scanner.device_count()):
com = scanner.device_at_index(i)
com.open()
device = XidDevice(com)
devices.append(device)
return devices
|
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Returns a list of all Xid devices connected to your computer.
|
[
"Returns",
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"Xid",
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"connected",
"to",
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"computer",
"."
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/__init__.py#L14-L25
|
cedrus-opensource/pyxid
|
pyxid/__init__.py
|
get_xid_device
|
def get_xid_device(device_number):
"""
returns device at a given index.
Raises ValueError if the device at the passed in index doesn't
exist.
"""
scanner = XidScanner()
com = scanner.device_at_index(device_number)
com.open()
return XidDevice(com)
|
python
|
def get_xid_device(device_number):
"""
returns device at a given index.
Raises ValueError if the device at the passed in index doesn't
exist.
"""
scanner = XidScanner()
com = scanner.device_at_index(device_number)
com.open()
return XidDevice(com)
|
[
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"(",
"device_number",
")",
"com",
".",
"open",
"(",
")",
"return",
"XidDevice",
"(",
"com",
")"
] |
returns device at a given index.
Raises ValueError if the device at the passed in index doesn't
exist.
|
[
"returns",
"device",
"at",
"a",
"given",
"index",
"."
] |
train
|
https://github.com/cedrus-opensource/pyxid/blob/02dba3a825f0d4f4c0bfa044c6a361492e4c25b6/pyxid/__init__.py#L28-L38
|
klen/flask-pw
|
flask_pw/models.py
|
Signal.connect
|
def connect(self, receiver):
"""Append receiver."""
if not callable(receiver):
raise ValueError('Invalid receiver: %s' % receiver)
self.receivers.append(receiver)
|
python
|
def connect(self, receiver):
"""Append receiver."""
if not callable(receiver):
raise ValueError('Invalid receiver: %s' % receiver)
self.receivers.append(receiver)
|
[
"def",
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"%",
"receiver",
")",
"self",
".",
"receivers",
".",
"append",
"(",
"receiver",
")"
] |
Append receiver.
|
[
"Append",
"receiver",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/models.py#L56-L60
|
klen/flask-pw
|
flask_pw/models.py
|
Signal.disconnect
|
def disconnect(self, receiver):
"""Remove receiver."""
try:
self.receivers.remove(receiver)
except ValueError:
raise ValueError('Unknown receiver: %s' % receiver)
|
python
|
def disconnect(self, receiver):
"""Remove receiver."""
try:
self.receivers.remove(receiver)
except ValueError:
raise ValueError('Unknown receiver: %s' % receiver)
|
[
"def",
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",",
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")",
"except",
"ValueError",
":",
"raise",
"ValueError",
"(",
"'Unknown receiver: %s'",
"%",
"receiver",
")"
] |
Remove receiver.
|
[
"Remove",
"receiver",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/models.py#L67-L72
|
klen/flask-pw
|
flask_pw/models.py
|
Signal.send
|
def send(self, instance, *args, **kwargs):
"""Send signal."""
for receiver in self.receivers:
receiver(instance, *args, **kwargs)
|
python
|
def send(self, instance, *args, **kwargs):
"""Send signal."""
for receiver in self.receivers:
receiver(instance, *args, **kwargs)
|
[
"def",
"send",
"(",
"self",
",",
"instance",
",",
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",",
"*",
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"kwargs",
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":",
"receiver",
"(",
"instance",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
Send signal.
|
[
"Send",
"signal",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/models.py#L74-L77
|
klen/flask-pw
|
flask_pw/models.py
|
Model.select
|
def select(cls, *args, **kwargs):
"""Support read slaves."""
query = super(Model, cls).select(*args, **kwargs)
query.database = cls._get_read_database()
return query
|
python
|
def select(cls, *args, **kwargs):
"""Support read slaves."""
query = super(Model, cls).select(*args, **kwargs)
query.database = cls._get_read_database()
return query
|
[
"def",
"select",
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"kwargs",
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".",
"database",
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"cls",
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"_get_read_database",
"(",
")",
"return",
"query"
] |
Support read slaves.
|
[
"Support",
"read",
"slaves",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/models.py#L105-L109
|
klen/flask-pw
|
flask_pw/models.py
|
Model.save
|
def save(self, force_insert=False, **kwargs):
"""Send signals."""
created = force_insert or not bool(self.pk)
self.pre_save.send(self, created=created)
super(Model, self).save(force_insert=force_insert, **kwargs)
self.post_save.send(self, created=created)
|
python
|
def save(self, force_insert=False, **kwargs):
"""Send signals."""
created = force_insert or not bool(self.pk)
self.pre_save.send(self, created=created)
super(Model, self).save(force_insert=force_insert, **kwargs)
self.post_save.send(self, created=created)
|
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"created",
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] |
Send signals.
|
[
"Send",
"signals",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/models.py#L130-L135
|
klen/flask-pw
|
flask_pw/models.py
|
Model.delete_instance
|
def delete_instance(self, *args, **kwargs):
"""Send signals."""
self.pre_delete.send(self)
super(Model, self).delete_instance(*args, **kwargs)
self.post_delete.send(self)
|
python
|
def delete_instance(self, *args, **kwargs):
"""Send signals."""
self.pre_delete.send(self)
super(Model, self).delete_instance(*args, **kwargs)
self.post_delete.send(self)
|
[
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"delete_instance",
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"*",
"kwargs",
")",
"self",
".",
"post_delete",
".",
"send",
"(",
"self",
")"
] |
Send signals.
|
[
"Send",
"signals",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/models.py#L137-L141
|
klen/flask-pw
|
flask_pw/__init__.py
|
get_database
|
def get_database(obj, **params):
"""Get database from given URI/Object."""
if isinstance(obj, string_types):
return connect(obj, **params)
return obj
|
python
|
def get_database(obj, **params):
"""Get database from given URI/Object."""
if isinstance(obj, string_types):
return connect(obj, **params)
return obj
|
[
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"*",
"*",
"params",
")",
"return",
"obj"
] |
Get database from given URI/Object.
|
[
"Get",
"database",
"from",
"given",
"URI",
"/",
"Object",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L244-L248
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.init_app
|
def init_app(self, app, database=None):
"""Initialize application."""
# Register application
if not app:
raise RuntimeError('Invalid application.')
self.app = app
if not hasattr(app, 'extensions'):
app.extensions = {}
app.extensions['peewee'] = self
app.config.setdefault('PEEWEE_CONNECTION_PARAMS', {})
app.config.setdefault('PEEWEE_DATABASE_URI', 'sqlite:///peewee.sqlite')
app.config.setdefault('PEEWEE_MANUAL', False)
app.config.setdefault('PEEWEE_MIGRATE_DIR', 'migrations')
app.config.setdefault('PEEWEE_MIGRATE_TABLE', 'migratehistory')
app.config.setdefault('PEEWEE_MODELS_CLASS', Model)
app.config.setdefault('PEEWEE_MODELS_IGNORE', [])
app.config.setdefault('PEEWEE_MODELS_MODULE', '')
app.config.setdefault('PEEWEE_READ_SLAVES', '')
app.config.setdefault('PEEWEE_USE_READ_SLAVES', True)
# Initialize database
params = app.config['PEEWEE_CONNECTION_PARAMS']
database = database or app.config.get('PEEWEE_DATABASE_URI')
if not database:
raise RuntimeError('Invalid database.')
database = get_database(database, **params)
slaves = app.config['PEEWEE_READ_SLAVES']
if isinstance(slaves, string_types):
slaves = slaves.split(',')
self.slaves = [get_database(slave, **params) for slave in slaves if slave]
self.database.initialize(database)
if self.database.database == ':memory:':
app.config['PEEWEE_MANUAL'] = True
if not app.config['PEEWEE_MANUAL']:
app.before_request(self.connect)
app.teardown_request(self.close)
|
python
|
def init_app(self, app, database=None):
"""Initialize application."""
# Register application
if not app:
raise RuntimeError('Invalid application.')
self.app = app
if not hasattr(app, 'extensions'):
app.extensions = {}
app.extensions['peewee'] = self
app.config.setdefault('PEEWEE_CONNECTION_PARAMS', {})
app.config.setdefault('PEEWEE_DATABASE_URI', 'sqlite:///peewee.sqlite')
app.config.setdefault('PEEWEE_MANUAL', False)
app.config.setdefault('PEEWEE_MIGRATE_DIR', 'migrations')
app.config.setdefault('PEEWEE_MIGRATE_TABLE', 'migratehistory')
app.config.setdefault('PEEWEE_MODELS_CLASS', Model)
app.config.setdefault('PEEWEE_MODELS_IGNORE', [])
app.config.setdefault('PEEWEE_MODELS_MODULE', '')
app.config.setdefault('PEEWEE_READ_SLAVES', '')
app.config.setdefault('PEEWEE_USE_READ_SLAVES', True)
# Initialize database
params = app.config['PEEWEE_CONNECTION_PARAMS']
database = database or app.config.get('PEEWEE_DATABASE_URI')
if not database:
raise RuntimeError('Invalid database.')
database = get_database(database, **params)
slaves = app.config['PEEWEE_READ_SLAVES']
if isinstance(slaves, string_types):
slaves = slaves.split(',')
self.slaves = [get_database(slave, **params) for slave in slaves if slave]
self.database.initialize(database)
if self.database.database == ':memory:':
app.config['PEEWEE_MANUAL'] = True
if not app.config['PEEWEE_MANUAL']:
app.before_request(self.connect)
app.teardown_request(self.close)
|
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"(",
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"close",
")"
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Initialize application.
|
[
"Initialize",
"application",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L30-L70
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.close
|
def close(self, response):
"""Close connection to database."""
LOGGER.info('Closing [%s]', os.getpid())
if not self.database.is_closed():
self.database.close()
return response
|
python
|
def close(self, response):
"""Close connection to database."""
LOGGER.info('Closing [%s]', os.getpid())
if not self.database.is_closed():
self.database.close()
return response
|
[
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"info",
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"is_closed",
"(",
")",
":",
"self",
".",
"database",
".",
"close",
"(",
")",
"return",
"response"
] |
Close connection to database.
|
[
"Close",
"connection",
"to",
"database",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L77-L82
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.Model
|
def Model(self):
"""Bind model to self database."""
Model_ = self.app.config['PEEWEE_MODELS_CLASS']
meta_params = {'database': self.database}
if self.slaves and self.app.config['PEEWEE_USE_READ_SLAVES']:
meta_params['read_slaves'] = self.slaves
Meta = type('Meta', (), meta_params)
return type('Model', (Model_,), {'Meta': Meta})
|
python
|
def Model(self):
"""Bind model to self database."""
Model_ = self.app.config['PEEWEE_MODELS_CLASS']
meta_params = {'database': self.database}
if self.slaves and self.app.config['PEEWEE_USE_READ_SLAVES']:
meta_params['read_slaves'] = self.slaves
Meta = type('Meta', (), meta_params)
return type('Model', (Model_,), {'Meta': Meta})
|
[
"def",
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"Model_",
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")",
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":",
"Meta",
"}",
")"
] |
Bind model to self database.
|
[
"Bind",
"model",
"to",
"self",
"database",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L85-L93
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.models
|
def models(self):
"""Return self.application models."""
Model_ = self.app.config['PEEWEE_MODELS_CLASS']
ignore = self.app.config['PEEWEE_MODELS_IGNORE']
models = []
if Model_ is not Model:
try:
mod = import_module(self.app.config['PEEWEE_MODELS_MODULE'])
for model in dir(mod):
models = getattr(mod, model)
if not isinstance(model, pw.Model):
continue
models.append(models)
except ImportError:
return models
elif isinstance(Model_, BaseSignalModel):
models = BaseSignalModel.models
return [m for m in models if m._meta.name not in ignore]
|
python
|
def models(self):
"""Return self.application models."""
Model_ = self.app.config['PEEWEE_MODELS_CLASS']
ignore = self.app.config['PEEWEE_MODELS_IGNORE']
models = []
if Model_ is not Model:
try:
mod = import_module(self.app.config['PEEWEE_MODELS_MODULE'])
for model in dir(mod):
models = getattr(mod, model)
if not isinstance(model, pw.Model):
continue
models.append(models)
except ImportError:
return models
elif isinstance(Model_, BaseSignalModel):
models = BaseSignalModel.models
return [m for m in models if m._meta.name not in ignore]
|
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"_meta",
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"name",
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"ignore",
"]"
] |
Return self.application models.
|
[
"Return",
"self",
".",
"application",
"models",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L96-L115
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.cmd_create
|
def cmd_create(self, name, auto=False):
"""Create a new migration."""
LOGGER.setLevel('INFO')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
if auto:
auto = self.models
router.create(name, auto=auto)
|
python
|
def cmd_create(self, name, auto=False):
"""Create a new migration."""
LOGGER.setLevel('INFO')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
if auto:
auto = self.models
router.create(name, auto=auto)
|
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"create",
"(",
"name",
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"=",
"auto",
")"
] |
Create a new migration.
|
[
"Create",
"a",
"new",
"migration",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L117-L130
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.cmd_migrate
|
def cmd_migrate(self, name=None, fake=False):
"""Run migrations."""
from peewee_migrate.router import Router, LOGGER
LOGGER.setLevel('INFO')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
migrations = router.run(name, fake=fake)
if migrations:
LOGGER.warn('Migrations are completed: %s' % ', '.join(migrations))
|
python
|
def cmd_migrate(self, name=None, fake=False):
"""Run migrations."""
from peewee_migrate.router import Router, LOGGER
LOGGER.setLevel('INFO')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
migrations = router.run(name, fake=fake)
if migrations:
LOGGER.warn('Migrations are completed: %s' % ', '.join(migrations))
|
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"'Migrations are completed: %s'",
"%",
"', '",
".",
"join",
"(",
"migrations",
")",
")"
] |
Run migrations.
|
[
"Run",
"migrations",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L132-L145
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.cmd_rollback
|
def cmd_rollback(self, name):
"""Rollback migrations."""
from peewee_migrate.router import Router, LOGGER
LOGGER.setLevel('INFO')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
router.rollback(name)
|
python
|
def cmd_rollback(self, name):
"""Rollback migrations."""
from peewee_migrate.router import Router, LOGGER
LOGGER.setLevel('INFO')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
router.rollback(name)
|
[
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"cmd_rollback",
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"self",
",",
"name",
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":",
"from",
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"router",
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"config",
"[",
"'PEEWEE_MIGRATE_TABLE'",
"]",
")",
"router",
".",
"rollback",
"(",
"name",
")"
] |
Rollback migrations.
|
[
"Rollback",
"migrations",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L147-L158
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.cmd_list
|
def cmd_list(self):
"""List migrations."""
from peewee_migrate.router import Router, LOGGER
LOGGER.setLevel('DEBUG')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
LOGGER.info('Migrations are done:')
LOGGER.info('\n'.join(router.done))
LOGGER.info('')
LOGGER.info('Migrations are undone:')
LOGGER.info('\n'.join(router.diff))
|
python
|
def cmd_list(self):
"""List migrations."""
from peewee_migrate.router import Router, LOGGER
LOGGER.setLevel('DEBUG')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
LOGGER.info('Migrations are done:')
LOGGER.info('\n'.join(router.done))
LOGGER.info('')
LOGGER.info('Migrations are undone:')
LOGGER.info('\n'.join(router.diff))
|
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List migrations.
|
[
"List",
"migrations",
"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L160-L175
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.cmd_merge
|
def cmd_merge(self):
"""Merge migrations."""
from peewee_migrate.router import Router, LOGGER
LOGGER.setLevel('DEBUG')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
router.merge()
|
python
|
def cmd_merge(self):
"""Merge migrations."""
from peewee_migrate.router import Router, LOGGER
LOGGER.setLevel('DEBUG')
LOGGER.propagate = 0
router = Router(self.database,
migrate_dir=self.app.config['PEEWEE_MIGRATE_DIR'],
migrate_table=self.app.config['PEEWEE_MIGRATE_TABLE'])
router.merge()
|
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"(",
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Merge migrations.
|
[
"Merge",
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"."
] |
train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L177-L188
|
klen/flask-pw
|
flask_pw/__init__.py
|
Peewee.manager
|
def manager(self):
"""Integrate a Flask-Script."""
from flask_script import Manager, Command
manager = Manager(usage="Migrate database.")
manager.add_command('create', Command(self.cmd_create))
manager.add_command('migrate', Command(self.cmd_migrate))
manager.add_command('rollback', Command(self.cmd_rollback))
manager.add_command('list', Command(self.cmd_list))
manager.add_command('merge', Command(self.cmd_merge))
return manager
|
python
|
def manager(self):
"""Integrate a Flask-Script."""
from flask_script import Manager, Command
manager = Manager(usage="Migrate database.")
manager.add_command('create', Command(self.cmd_create))
manager.add_command('migrate', Command(self.cmd_migrate))
manager.add_command('rollback', Command(self.cmd_rollback))
manager.add_command('list', Command(self.cmd_list))
manager.add_command('merge', Command(self.cmd_merge))
return manager
|
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Integrate a Flask-Script.
|
[
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"-",
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train
|
https://github.com/klen/flask-pw/blob/04d7846f0c89f2b2331b238b1c8223368c2a40a7/flask_pw/__init__.py#L191-L202
|
pimusicbox/mopidy-websettings
|
mopidy_websettings/__init__.py
|
restart_program
|
def restart_program():
"""
DOES NOT WORK WELL WITH MOPIDY
Hack from
https://www.daniweb.com/software-development/python/code/260268/restart-your-python-program
to support updating the settings, since mopidy is not able to do that yet
Restarts the current program
Note: this function does not return. Any cleanup action (like
saving data) must be done before calling this function
"""
python = sys.executable
os.execl(python, python, * sys.argv)
|
python
|
def restart_program():
"""
DOES NOT WORK WELL WITH MOPIDY
Hack from
https://www.daniweb.com/software-development/python/code/260268/restart-your-python-program
to support updating the settings, since mopidy is not able to do that yet
Restarts the current program
Note: this function does not return. Any cleanup action (like
saving data) must be done before calling this function
"""
python = sys.executable
os.execl(python, python, * sys.argv)
|
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DOES NOT WORK WELL WITH MOPIDY
Hack from
https://www.daniweb.com/software-development/python/code/260268/restart-your-python-program
to support updating the settings, since mopidy is not able to do that yet
Restarts the current program
Note: this function does not return. Any cleanup action (like
saving data) must be done before calling this function
|
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train
|
https://github.com/pimusicbox/mopidy-websettings/blob/a9aca8e15a29f323e7d91e3f2237f4605e2892e3/mopidy_websettings/__init__.py#L33-L45
|
garicchi/arff2pandas
|
arff2pandas/a2p.py
|
__load
|
def __load(arff):
"""
load liac-arff to pandas DataFrame
:param dict arff:arff dict created liac-arff
:rtype: DataFrame
:return: pandas DataFrame
"""
attrs = arff['attributes']
attrs_t = []
for attr in attrs:
if isinstance(attr[1], list):
attrs_t.append("%s@{%s}" % (attr[0], ','.join(attr[1])))
else:
attrs_t.append("%s@%s" % (attr[0], attr[1]))
df = pd.DataFrame(data=arff['data'], columns=attrs_t)
return df
|
python
|
def __load(arff):
"""
load liac-arff to pandas DataFrame
:param dict arff:arff dict created liac-arff
:rtype: DataFrame
:return: pandas DataFrame
"""
attrs = arff['attributes']
attrs_t = []
for attr in attrs:
if isinstance(attr[1], list):
attrs_t.append("%s@{%s}" % (attr[0], ','.join(attr[1])))
else:
attrs_t.append("%s@%s" % (attr[0], attr[1]))
df = pd.DataFrame(data=arff['data'], columns=attrs_t)
return df
|
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] |
train
|
https://github.com/garicchi/arff2pandas/blob/6698a3f57a9c227c8f38deb827b53b80b8c6a231/arff2pandas/a2p.py#L5-L21
|
garicchi/arff2pandas
|
arff2pandas/a2p.py
|
__dump
|
def __dump(df,relation='data',description=''):
"""
dump DataFrame to liac-arff
:param DataFrame df:
:param str relation:
:param str description:
:rtype: dict
:return: liac-arff dict
"""
attrs = []
for col in df.columns:
attr = col.split('@')
if attr[1].count('{')>0 and attr[1].count('}')>0:
vals = attr[1].replace('{','').replace('}','').split(',')
attrs.append((attr[0],vals))
else:
attrs.append((attr[0],attr[1]))
data = list(df.values)
result = {
'attributes':attrs,
'data':data,
'description':description,
'relation':relation
}
return result
|
python
|
def __dump(df,relation='data',description=''):
"""
dump DataFrame to liac-arff
:param DataFrame df:
:param str relation:
:param str description:
:rtype: dict
:return: liac-arff dict
"""
attrs = []
for col in df.columns:
attr = col.split('@')
if attr[1].count('{')>0 and attr[1].count('}')>0:
vals = attr[1].replace('{','').replace('}','').split(',')
attrs.append((attr[0],vals))
else:
attrs.append((attr[0],attr[1]))
data = list(df.values)
result = {
'attributes':attrs,
'data':data,
'description':description,
'relation':relation
}
return result
|
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train
|
https://github.com/garicchi/arff2pandas/blob/6698a3f57a9c227c8f38deb827b53b80b8c6a231/arff2pandas/a2p.py#L46-L71
|
garicchi/arff2pandas
|
arff2pandas/a2p.py
|
dump
|
def dump(df,fp):
"""
dump DataFrame to file
:param DataFrame df:
:param file fp:
"""
arff = __dump(df)
liacarff.dump(arff,fp)
|
python
|
def dump(df,fp):
"""
dump DataFrame to file
:param DataFrame df:
:param file fp:
"""
arff = __dump(df)
liacarff.dump(arff,fp)
|
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dump DataFrame to file
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train
|
https://github.com/garicchi/arff2pandas/blob/6698a3f57a9c227c8f38deb827b53b80b8c6a231/arff2pandas/a2p.py#L74-L81
|
eerimoq/textparser
|
textparser.py
|
markup_line
|
def markup_line(text, offset, marker='>>!<<'):
"""Insert `marker` at `offset` into `text`, and return the marked
line.
.. code-block:: python
>>> markup_line('0\\n1234\\n56', 3)
1>>!<<234
"""
begin = text.rfind('\n', 0, offset)
begin += 1
end = text.find('\n', offset)
if end == -1:
end = len(text)
return text[begin:offset] + marker + text[offset:end]
|
python
|
def markup_line(text, offset, marker='>>!<<'):
"""Insert `marker` at `offset` into `text`, and return the marked
line.
.. code-block:: python
>>> markup_line('0\\n1234\\n56', 3)
1>>!<<234
"""
begin = text.rfind('\n', 0, offset)
begin += 1
end = text.find('\n', offset)
if end == -1:
end = len(text)
return text[begin:offset] + marker + text[offset:end]
|
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Insert `marker` at `offset` into `text`, and return the marked
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.. code-block:: python
>>> markup_line('0\\n1234\\n56', 3)
1>>!<<234
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] |
train
|
https://github.com/eerimoq/textparser/blob/5f158210cfd3a20b19775191e92f22a13054a852/textparser.py#L698-L717
|
eerimoq/textparser
|
textparser.py
|
tokenize_init
|
def tokenize_init(spec):
"""Initialize a tokenizer. Should only be called by the
:func:`~textparser.Parser.tokenize` method in the parser.
"""
tokens = [Token('__SOF__', '__SOF__', 0)]
re_token = '|'.join([
'(?P<{}>{})'.format(name, regex) for name, regex in spec
])
return tokens, re_token
|
python
|
def tokenize_init(spec):
"""Initialize a tokenizer. Should only be called by the
:func:`~textparser.Parser.tokenize` method in the parser.
"""
tokens = [Token('__SOF__', '__SOF__', 0)]
re_token = '|'.join([
'(?P<{}>{})'.format(name, regex) for name, regex in spec
])
return tokens, re_token
|
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train
|
https://github.com/eerimoq/textparser/blob/5f158210cfd3a20b19775191e92f22a13054a852/textparser.py#L730-L741
|
eerimoq/textparser
|
textparser.py
|
Parser.tokenize
|
def tokenize(self, text):
"""Tokenize given string `text`, and return a list of tokens. Raises
:class:`~textparser.TokenizeError` on failure.
This method should only be called by
:func:`~textparser.Parser.parse()`, but may very well be
overridden if the default implementation does not match the
parser needs.
"""
names, specs = self._unpack_token_specs()
keywords = self.keywords()
tokens, re_token = tokenize_init(specs)
for mo in re.finditer(re_token, text, re.DOTALL):
kind = mo.lastgroup
if kind == 'SKIP':
pass
elif kind != 'MISMATCH':
value = mo.group(kind)
if value in keywords:
kind = value
if kind in names:
kind = names[kind]
tokens.append(Token(kind, value, mo.start()))
else:
raise TokenizeError(text, mo.start())
return tokens
|
python
|
def tokenize(self, text):
"""Tokenize given string `text`, and return a list of tokens. Raises
:class:`~textparser.TokenizeError` on failure.
This method should only be called by
:func:`~textparser.Parser.parse()`, but may very well be
overridden if the default implementation does not match the
parser needs.
"""
names, specs = self._unpack_token_specs()
keywords = self.keywords()
tokens, re_token = tokenize_init(specs)
for mo in re.finditer(re_token, text, re.DOTALL):
kind = mo.lastgroup
if kind == 'SKIP':
pass
elif kind != 'MISMATCH':
value = mo.group(kind)
if value in keywords:
kind = value
if kind in names:
kind = names[kind]
tokens.append(Token(kind, value, mo.start()))
else:
raise TokenizeError(text, mo.start())
return tokens
|
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This method should only be called by
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train
|
https://github.com/eerimoq/textparser/blob/5f158210cfd3a20b19775191e92f22a13054a852/textparser.py#L809-L842
|
eerimoq/textparser
|
textparser.py
|
Parser.parse
|
def parse(self, text, token_tree=False, match_sof=False):
"""Parse given string `text` and return the parse tree. Raises
:class:`~textparser.ParseError` on failure.
Returns a parse tree of tokens if `token_tree` is ``True``.
.. code-block:: python
>>> MyParser().parse('Hello, World!')
['Hello', ',', 'World', '!']
>>> tree = MyParser().parse('Hello, World!', token_tree=True)
>>> from pprint import pprint
>>> pprint(tree)
[Token(kind='WORD', value='Hello', offset=0),
Token(kind=',', value=',', offset=5),
Token(kind='WORD', value='World', offset=7),
Token(kind='!', value='!', offset=12)]
"""
try:
tokens = self.tokenize(text)
if len(tokens) == 0 or tokens[-1].kind != '__EOF__':
tokens.append(Token('__EOF__', '__EOF__', len(text)))
if not match_sof:
if len(tokens) > 0 and tokens[0].kind == '__SOF__':
del tokens[0]
return Grammar(self.grammar()).parse(tokens, token_tree)
except (TokenizeError, GrammarError) as e:
raise ParseError(text, e.offset)
|
python
|
def parse(self, text, token_tree=False, match_sof=False):
"""Parse given string `text` and return the parse tree. Raises
:class:`~textparser.ParseError` on failure.
Returns a parse tree of tokens if `token_tree` is ``True``.
.. code-block:: python
>>> MyParser().parse('Hello, World!')
['Hello', ',', 'World', '!']
>>> tree = MyParser().parse('Hello, World!', token_tree=True)
>>> from pprint import pprint
>>> pprint(tree)
[Token(kind='WORD', value='Hello', offset=0),
Token(kind=',', value=',', offset=5),
Token(kind='WORD', value='World', offset=7),
Token(kind='!', value='!', offset=12)]
"""
try:
tokens = self.tokenize(text)
if len(tokens) == 0 or tokens[-1].kind != '__EOF__':
tokens.append(Token('__EOF__', '__EOF__', len(text)))
if not match_sof:
if len(tokens) > 0 and tokens[0].kind == '__SOF__':
del tokens[0]
return Grammar(self.grammar()).parse(tokens, token_tree)
except (TokenizeError, GrammarError) as e:
raise ParseError(text, e.offset)
|
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Parse given string `text` and return the parse tree. Raises
:class:`~textparser.ParseError` on failure.
Returns a parse tree of tokens if `token_tree` is ``True``.
.. code-block:: python
>>> MyParser().parse('Hello, World!')
['Hello', ',', 'World', '!']
>>> tree = MyParser().parse('Hello, World!', token_tree=True)
>>> from pprint import pprint
>>> pprint(tree)
[Token(kind='WORD', value='Hello', offset=0),
Token(kind=',', value=',', offset=5),
Token(kind='WORD', value='World', offset=7),
Token(kind='!', value='!', offset=12)]
|
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] |
train
|
https://github.com/eerimoq/textparser/blob/5f158210cfd3a20b19775191e92f22a13054a852/textparser.py#L854-L886
|
DataMedSci/beprof
|
beprof/profile.py
|
Profile.x_at_y
|
def x_at_y(self, y, reverse=False):
"""
Calculates inverse profile - for given y returns x such that f(x) = y
If given y is not found in the self.y, then interpolation is used.
By default returns first result looking from left,
if reverse argument set to True,
looks from right. If y is outside range of self.y
then np.nan is returned.
Use inverse lookup to get x-coordinate of first point:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(5.))
0.0
Use inverse lookup to get x-coordinate of second point,
looking from left:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(10.))
0.1
Use inverse lookup to get x-coordinate of fourth point,
looking from right:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(10., reverse=True))
0.3
Use interpolation between first two points:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(7.5))
0.05
Looking for y below self.y range:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(2.0))
nan
Looking for y above self.y range:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(22.0))
nan
:param y: reference value
:param reverse: boolean value - direction of lookup
:return: x value corresponding to given y or NaN if not found
"""
logger.info('Running %(name)s.y_at_x(y=%(y)s, reverse=%(rev)s)',
{"name": self.__class__, "y": y, "rev": reverse})
# positive or negative direction handles
x_handle, y_handle = self.x, self.y
if reverse:
x_handle, y_handle = self.x[::-1], self.y[::-1]
# find the index of first value in self.y greater or equal than y
cond = y_handle >= y
ind = np.argmax(cond)
# two boundary conditions where x cannot be found:
# A) y > max(self.y)
# B) y < min(self.y)
# A) if y > max(self.y) then condition self.y >= y
# will never be satisfied
# np.argmax( cond ) will be equal 0 and cond[ind] will be False
if not cond[ind]:
return np.nan
# B) if y < min(self.y) then condition self.y >= y
# will be satisfied on first item
# np.argmax(cond) will be equal 0,
# to exclude situation that y_handle[0] = y
# we also check if y < y_handle[0]
if ind == 0 and y < y_handle[0]:
return np.nan
# use lookup if y in self.y:
if cond[ind] and y_handle[ind] == y:
return x_handle[ind]
# alternatively - pure python implementation
# return x_handle[ind] - \
# ((x_handle[ind] - x_handle[ind - 1]) / \
# (y_handle[ind] - y_handle[ind - 1])) * \
# (y_handle[ind] - y)
# use interpolation
sl = slice(ind - 1, ind + 1)
return np.interp(y, y_handle[sl], x_handle[sl])
|
python
|
def x_at_y(self, y, reverse=False):
"""
Calculates inverse profile - for given y returns x such that f(x) = y
If given y is not found in the self.y, then interpolation is used.
By default returns first result looking from left,
if reverse argument set to True,
looks from right. If y is outside range of self.y
then np.nan is returned.
Use inverse lookup to get x-coordinate of first point:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(5.))
0.0
Use inverse lookup to get x-coordinate of second point,
looking from left:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(10.))
0.1
Use inverse lookup to get x-coordinate of fourth point,
looking from right:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(10., reverse=True))
0.3
Use interpolation between first two points:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(7.5))
0.05
Looking for y below self.y range:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(2.0))
nan
Looking for y above self.y range:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(22.0))
nan
:param y: reference value
:param reverse: boolean value - direction of lookup
:return: x value corresponding to given y or NaN if not found
"""
logger.info('Running %(name)s.y_at_x(y=%(y)s, reverse=%(rev)s)',
{"name": self.__class__, "y": y, "rev": reverse})
# positive or negative direction handles
x_handle, y_handle = self.x, self.y
if reverse:
x_handle, y_handle = self.x[::-1], self.y[::-1]
# find the index of first value in self.y greater or equal than y
cond = y_handle >= y
ind = np.argmax(cond)
# two boundary conditions where x cannot be found:
# A) y > max(self.y)
# B) y < min(self.y)
# A) if y > max(self.y) then condition self.y >= y
# will never be satisfied
# np.argmax( cond ) will be equal 0 and cond[ind] will be False
if not cond[ind]:
return np.nan
# B) if y < min(self.y) then condition self.y >= y
# will be satisfied on first item
# np.argmax(cond) will be equal 0,
# to exclude situation that y_handle[0] = y
# we also check if y < y_handle[0]
if ind == 0 and y < y_handle[0]:
return np.nan
# use lookup if y in self.y:
if cond[ind] and y_handle[ind] == y:
return x_handle[ind]
# alternatively - pure python implementation
# return x_handle[ind] - \
# ((x_handle[ind] - x_handle[ind - 1]) / \
# (y_handle[ind] - y_handle[ind - 1])) * \
# (y_handle[ind] - y)
# use interpolation
sl = slice(ind - 1, ind + 1)
return np.interp(y, y_handle[sl], x_handle[sl])
|
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Calculates inverse profile - for given y returns x such that f(x) = y
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By default returns first result looking from left,
if reverse argument set to True,
looks from right. If y is outside range of self.y
then np.nan is returned.
Use inverse lookup to get x-coordinate of first point:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(5.))
0.0
Use inverse lookup to get x-coordinate of second point,
looking from left:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(10.))
0.1
Use inverse lookup to get x-coordinate of fourth point,
looking from right:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(10., reverse=True))
0.3
Use interpolation between first two points:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(7.5))
0.05
Looking for y below self.y range:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(2.0))
nan
Looking for y above self.y range:
>>> float(Profile([[0.0, 5.0], [0.1, 10.0], [0.2, 20.0], [0.3, 10.0]])\
.x_at_y(22.0))
nan
:param y: reference value
:param reverse: boolean value - direction of lookup
:return: x value corresponding to given y or NaN if not found
|
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train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/profile.py#L31-L117
|
DataMedSci/beprof
|
beprof/profile.py
|
Profile.width
|
def width(self, level):
"""
Width at given level
:param level:
:return:
"""
return self.x_at_y(level, reverse=True) - self.x_at_y(level)
|
python
|
def width(self, level):
"""
Width at given level
:param level:
:return:
"""
return self.x_at_y(level, reverse=True) - self.x_at_y(level)
|
[
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"-",
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] |
Width at given level
:param level:
:return:
|
[
"Width",
"at",
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"level",
":",
"param",
"level",
":",
":",
"return",
":"
] |
train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/profile.py#L119-L125
|
DataMedSci/beprof
|
beprof/profile.py
|
Profile.normalize
|
def normalize(self, dt, allow_cast=True):
"""
Normalize to 1 over [-dt, +dt] area, if allow_cast is set
to True, division not in place and casting may occur.
If division in place is not possible and allow_cast is False
an exception is raised.
>>> a = Profile([[0, 0], [1, 5], [2, 10], [3, 5], [4, 0]])
>>> a.normalize(1, allow_cast=True)
>>> print(a.y)
[0. 2. 4. 2. 0.]
:param dt:
:param allow_cast:
"""
if dt <= 0:
raise ValueError("Expected positive input")
logger.info('Running %(name)s.normalize(dt=%(dt)s)', {"name": self.__class__, "dt": dt})
try:
ave = np.average(self.y[np.fabs(self.x) <= dt])
except RuntimeWarning as e:
logger.error('in normalize(). self class is %(name)s, dt=%(dt)s', {"name": self.__class__, "dt": dt})
raise Exception("Scaling factor error: {0}".format(e))
try:
self.y /= ave
except TypeError as e:
logger.warning("Division in place is impossible: %s", e)
if allow_cast:
self.y = self.y / ave
else:
logger.error("Division in place impossible - allow_cast flag set to True should help")
raise
|
python
|
def normalize(self, dt, allow_cast=True):
"""
Normalize to 1 over [-dt, +dt] area, if allow_cast is set
to True, division not in place and casting may occur.
If division in place is not possible and allow_cast is False
an exception is raised.
>>> a = Profile([[0, 0], [1, 5], [2, 10], [3, 5], [4, 0]])
>>> a.normalize(1, allow_cast=True)
>>> print(a.y)
[0. 2. 4. 2. 0.]
:param dt:
:param allow_cast:
"""
if dt <= 0:
raise ValueError("Expected positive input")
logger.info('Running %(name)s.normalize(dt=%(dt)s)', {"name": self.__class__, "dt": dt})
try:
ave = np.average(self.y[np.fabs(self.x) <= dt])
except RuntimeWarning as e:
logger.error('in normalize(). self class is %(name)s, dt=%(dt)s', {"name": self.__class__, "dt": dt})
raise Exception("Scaling factor error: {0}".format(e))
try:
self.y /= ave
except TypeError as e:
logger.warning("Division in place is impossible: %s", e)
if allow_cast:
self.y = self.y / ave
else:
logger.error("Division in place impossible - allow_cast flag set to True should help")
raise
|
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Normalize to 1 over [-dt, +dt] area, if allow_cast is set
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If division in place is not possible and allow_cast is False
an exception is raised.
>>> a = Profile([[0, 0], [1, 5], [2, 10], [3, 5], [4, 0]])
>>> a.normalize(1, allow_cast=True)
>>> print(a.y)
[0. 2. 4. 2. 0.]
:param dt:
:param allow_cast:
|
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train
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https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/profile.py#L135-L166
|
DataMedSci/beprof
|
beprof/curve.py
|
Curve.rescale
|
def rescale(self, factor=1.0, allow_cast=True):
"""
Rescales self.y by given factor, if allow_cast is set to True
and division in place is impossible - casting and not in place
division may occur occur. If in place is impossible and allow_cast
is set to False - an exception is raised.
Check simple rescaling by 2 with no casting
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.float)
>>> c.rescale(2, allow_cast=False)
>>> print(c.y)
[0. 2.5 5. ]
Check rescaling with floor division
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.int)
>>> c.rescale(1.5, allow_cast=True)
>>> print(c.y)
[0 3 6]
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.int)
>>> c.rescale(-1, allow_cast=True)
>>> print(c.y)
[ 0 -5 -10]
:param factor: rescaling factor, should be a number
:param allow_cast: bool - allow division not in place
"""
try:
self.y /= factor
except TypeError as e:
logger.warning("Division in place is impossible: %s", e)
if allow_cast:
self.y = self.y / factor
else:
logger.error("allow_cast flag set to True should help")
raise
|
python
|
def rescale(self, factor=1.0, allow_cast=True):
"""
Rescales self.y by given factor, if allow_cast is set to True
and division in place is impossible - casting and not in place
division may occur occur. If in place is impossible and allow_cast
is set to False - an exception is raised.
Check simple rescaling by 2 with no casting
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.float)
>>> c.rescale(2, allow_cast=False)
>>> print(c.y)
[0. 2.5 5. ]
Check rescaling with floor division
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.int)
>>> c.rescale(1.5, allow_cast=True)
>>> print(c.y)
[0 3 6]
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.int)
>>> c.rescale(-1, allow_cast=True)
>>> print(c.y)
[ 0 -5 -10]
:param factor: rescaling factor, should be a number
:param allow_cast: bool - allow division not in place
"""
try:
self.y /= factor
except TypeError as e:
logger.warning("Division in place is impossible: %s", e)
if allow_cast:
self.y = self.y / factor
else:
logger.error("allow_cast flag set to True should help")
raise
|
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Rescales self.y by given factor, if allow_cast is set to True
and division in place is impossible - casting and not in place
division may occur occur. If in place is impossible and allow_cast
is set to False - an exception is raised.
Check simple rescaling by 2 with no casting
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.float)
>>> c.rescale(2, allow_cast=False)
>>> print(c.y)
[0. 2.5 5. ]
Check rescaling with floor division
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.int)
>>> c.rescale(1.5, allow_cast=True)
>>> print(c.y)
[0 3 6]
>>> c = Curve([[0, 0], [5, 5], [10, 10]], dtype=np.int)
>>> c.rescale(-1, allow_cast=True)
>>> print(c.y)
[ 0 -5 -10]
:param factor: rescaling factor, should be a number
:param allow_cast: bool - allow division not in place
|
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train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/curve.py#L80-L115
|
DataMedSci/beprof
|
beprof/curve.py
|
Curve.change_domain
|
def change_domain(self, domain):
"""
Creating new Curve object in memory with domain passed as a parameter.
New domain must include in the original domain.
Copies values from original curve and uses interpolation to calculate
values for new points in domain.
Calculate y - values of example curve with changed domain:
>>> print(Curve([[0,0], [5, 5], [10, 0]])\
.change_domain([1, 2, 8, 9]).y)
[1. 2. 2. 1.]
:param domain: set of points representing new domain.
Might be a list or np.array.
:return: new Curve object with domain set by 'domain' parameter
"""
logger.info('Running %(name)s.change_domain() with new domain range:[%(ymin)s, %(ymax)s]',
{"name": self.__class__, "ymin": np.min(domain), "ymax": np.max(domain)})
# check if new domain includes in the original domain
if np.max(domain) > np.max(self.x) or np.min(domain) < np.min(self.x):
logger.error('Old domain range: [%(xmin)s, %(xmax)s] does not include new domain range:'
'[%(ymin)s, %(ymax)s]', {"xmin": np.min(self.x), "xmax": np.max(self.x),
"ymin": np.min(domain), "ymax": np.max(domain)})
raise ValueError('in change_domain():' 'the old domain does not include the new one')
y = np.interp(domain, self.x, self.y)
# We need to join together domain and values (y) because we are recreating Curve object
# (we pass it as argument to self.__class__)
# np.dstack((arrays), axis=1) joins given arrays like np.dstack() but it also nests the result
# in additional list and this is the reason why we use [0] to remove this extra layer of list like this:
# np.dstack([[0, 5, 10], [0, 0, 0]]) gives [[[ 0, 0], [ 5, 0], [10, 0]]] so use dtack()[0]
# to get this: [[0,0], [5, 5], [10, 0]]
# which is a 2 dimensional array and can be used to create a new Curve object
obj = self.__class__(np.dstack((domain, y))[0], **self.__dict__['metadata'])
return obj
|
python
|
def change_domain(self, domain):
"""
Creating new Curve object in memory with domain passed as a parameter.
New domain must include in the original domain.
Copies values from original curve and uses interpolation to calculate
values for new points in domain.
Calculate y - values of example curve with changed domain:
>>> print(Curve([[0,0], [5, 5], [10, 0]])\
.change_domain([1, 2, 8, 9]).y)
[1. 2. 2. 1.]
:param domain: set of points representing new domain.
Might be a list or np.array.
:return: new Curve object with domain set by 'domain' parameter
"""
logger.info('Running %(name)s.change_domain() with new domain range:[%(ymin)s, %(ymax)s]',
{"name": self.__class__, "ymin": np.min(domain), "ymax": np.max(domain)})
# check if new domain includes in the original domain
if np.max(domain) > np.max(self.x) or np.min(domain) < np.min(self.x):
logger.error('Old domain range: [%(xmin)s, %(xmax)s] does not include new domain range:'
'[%(ymin)s, %(ymax)s]', {"xmin": np.min(self.x), "xmax": np.max(self.x),
"ymin": np.min(domain), "ymax": np.max(domain)})
raise ValueError('in change_domain():' 'the old domain does not include the new one')
y = np.interp(domain, self.x, self.y)
# We need to join together domain and values (y) because we are recreating Curve object
# (we pass it as argument to self.__class__)
# np.dstack((arrays), axis=1) joins given arrays like np.dstack() but it also nests the result
# in additional list and this is the reason why we use [0] to remove this extra layer of list like this:
# np.dstack([[0, 5, 10], [0, 0, 0]]) gives [[[ 0, 0], [ 5, 0], [10, 0]]] so use dtack()[0]
# to get this: [[0,0], [5, 5], [10, 0]]
# which is a 2 dimensional array and can be used to create a new Curve object
obj = self.__class__(np.dstack((domain, y))[0], **self.__dict__['metadata'])
return obj
|
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Calculate y - values of example curve with changed domain:
>>> print(Curve([[0,0], [5, 5], [10, 0]])\
.change_domain([1, 2, 8, 9]).y)
[1. 2. 2. 1.]
:param domain: set of points representing new domain.
Might be a list or np.array.
:return: new Curve object with domain set by 'domain' parameter
|
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train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/curve.py#L125-L160
|
DataMedSci/beprof
|
beprof/curve.py
|
Curve.rebinned
|
def rebinned(self, step=0.1, fixp=0):
"""
Provides effective way to compute new domain basing on
step and fixp parameters. Then using change_domain() method
to create new object with calculated domain and returns it.
fixp doesn't have to be inside original domain.
Return domain of a new curve specified by
fixp=0 and step=1 and another Curve object:
>>> print(Curve([[0,0], [5, 5], [10, 0]]).rebinned(1, 0).x)
[ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.]
:param step: step size of new domain
:param fixp: fixed point one of the points in new domain
:return: new Curve object with domain specified by
step and fixp parameters
"""
logger.info('Running %(name)s.rebinned(step=%(st)s, fixp=%(fx)s)',
{"name": self.__class__, "st": step, "fx": fixp})
a, b = (np.min(self.x), np.max(self.x))
count_start = abs(fixp - a) / step
count_stop = abs(fixp - b) / step
# depending on position of fixp with respect to the original domain
# 3 cases may occur:
if fixp < a:
count_start = math.ceil(count_start)
count_stop = math.floor(count_stop)
elif fixp > b:
count_start = -math.floor(count_start)
count_stop = -math.ceil(count_stop)
else:
count_start = -count_start
count_stop = count_stop
domain = [fixp + n * step for n in range(int(count_start), int(count_stop) + 1)]
return self.change_domain(domain)
|
python
|
def rebinned(self, step=0.1, fixp=0):
"""
Provides effective way to compute new domain basing on
step and fixp parameters. Then using change_domain() method
to create new object with calculated domain and returns it.
fixp doesn't have to be inside original domain.
Return domain of a new curve specified by
fixp=0 and step=1 and another Curve object:
>>> print(Curve([[0,0], [5, 5], [10, 0]]).rebinned(1, 0).x)
[ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.]
:param step: step size of new domain
:param fixp: fixed point one of the points in new domain
:return: new Curve object with domain specified by
step and fixp parameters
"""
logger.info('Running %(name)s.rebinned(step=%(st)s, fixp=%(fx)s)',
{"name": self.__class__, "st": step, "fx": fixp})
a, b = (np.min(self.x), np.max(self.x))
count_start = abs(fixp - a) / step
count_stop = abs(fixp - b) / step
# depending on position of fixp with respect to the original domain
# 3 cases may occur:
if fixp < a:
count_start = math.ceil(count_start)
count_stop = math.floor(count_stop)
elif fixp > b:
count_start = -math.floor(count_start)
count_stop = -math.ceil(count_stop)
else:
count_start = -count_start
count_stop = count_stop
domain = [fixp + n * step for n in range(int(count_start), int(count_stop) + 1)]
return self.change_domain(domain)
|
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fixp doesn't have to be inside original domain.
Return domain of a new curve specified by
fixp=0 and step=1 and another Curve object:
>>> print(Curve([[0,0], [5, 5], [10, 0]]).rebinned(1, 0).x)
[ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.]
:param step: step size of new domain
:param fixp: fixed point one of the points in new domain
:return: new Curve object with domain specified by
step and fixp parameters
|
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"and",
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] |
train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/curve.py#L162-L199
|
DataMedSci/beprof
|
beprof/curve.py
|
Curve.evaluate_at_x
|
def evaluate_at_x(self, arg, def_val=0):
"""
Returns Y value at arg of self. Arg can be a scalar,
but also might be np.array or other iterable
(like list). If domain of self is not wide enough to
interpolate the value of Y, method will return
def_val for those arguments instead.
Check the interpolation when arg in domain of self:
>>> Curve([[0, 0], [2, 2], [4, 4]]).evaluate_at_x([1, 2 ,3])
array([1., 2., 3.])
Check if behavior of the method is correct when arg
id partly outside the domain:
>>> Curve([[0, 0], [2, 2], [4, 4]]).evaluate_at_x(\
[-1, 1, 2 ,3, 5], 100)
array([100., 1., 2., 3., 100.])
:param arg: x-value to calculate Y (may be an array or list as well)
:param def_val: default value to return if can't interpolate at arg
:return: np.array of Y-values at arg. If arg is a scalar,
will return scalar as well
"""
y = np.interp(arg, self.x, self.y, left=def_val, right=def_val)
return y
|
python
|
def evaluate_at_x(self, arg, def_val=0):
"""
Returns Y value at arg of self. Arg can be a scalar,
but also might be np.array or other iterable
(like list). If domain of self is not wide enough to
interpolate the value of Y, method will return
def_val for those arguments instead.
Check the interpolation when arg in domain of self:
>>> Curve([[0, 0], [2, 2], [4, 4]]).evaluate_at_x([1, 2 ,3])
array([1., 2., 3.])
Check if behavior of the method is correct when arg
id partly outside the domain:
>>> Curve([[0, 0], [2, 2], [4, 4]]).evaluate_at_x(\
[-1, 1, 2 ,3, 5], 100)
array([100., 1., 2., 3., 100.])
:param arg: x-value to calculate Y (may be an array or list as well)
:param def_val: default value to return if can't interpolate at arg
:return: np.array of Y-values at arg. If arg is a scalar,
will return scalar as well
"""
y = np.interp(arg, self.x, self.y, left=def_val, right=def_val)
return y
|
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Returns Y value at arg of self. Arg can be a scalar,
but also might be np.array or other iterable
(like list). If domain of self is not wide enough to
interpolate the value of Y, method will return
def_val for those arguments instead.
Check the interpolation when arg in domain of self:
>>> Curve([[0, 0], [2, 2], [4, 4]]).evaluate_at_x([1, 2 ,3])
array([1., 2., 3.])
Check if behavior of the method is correct when arg
id partly outside the domain:
>>> Curve([[0, 0], [2, 2], [4, 4]]).evaluate_at_x(\
[-1, 1, 2 ,3, 5], 100)
array([100., 1., 2., 3., 100.])
:param arg: x-value to calculate Y (may be an array or list as well)
:param def_val: default value to return if can't interpolate at arg
:return: np.array of Y-values at arg. If arg is a scalar,
will return scalar as well
|
[
"Returns",
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"return",
"def_val",
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"those",
"arguments",
"instead",
"."
] |
train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/curve.py#L201-L225
|
DataMedSci/beprof
|
beprof/curve.py
|
Curve.subtract
|
def subtract(self, curve2, new_obj=False):
"""
Method that calculates difference between 2 curves
(or subclasses of curves). Domain of self must be in
domain of curve2 what means min(self.x) >= min(curve2.x)
and max(self.x) <= max(curve2.x).
Might modify self, and can return the result or None
Use subtract as -= operator, check whether returned value is None:
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[-1, 1], [5, 1]])) is None
True
Use subtract again but return a new object this time.
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[-1, 1], [5, 1]]), new_obj=True).y
DataSet([-1., 0., 1., 0.])
Try using wrong inputs to create a new object,
and check whether it throws an exception:
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[1, -1], [2, -1]]), new_obj=True) is None
Traceback (most recent call last):
...
Exception: curve2 does not include self domain
:param curve2: second object to calculate difference
:param new_obj: if True, method is creating new object
instead of modifying self
:return: None if new_obj is False (but will modify self)
or type(self) object containing the result
"""
# domain1 = [a1, b1]
# domain2 = [a2, b2]
a1, b1 = np.min(self.x), np.max(self.x)
a2, b2 = np.min(curve2.x), np.max(curve2.x)
# check whether domain condition is satisfied
if a2 > a1 or b2 < b1:
logger.error("Domain of self must be in domain of given curve")
raise Exception("curve2 does not include self domain")
# if we want to create and return a new object
# rather then modify existing one
if new_obj:
return functions.subtract(self, curve2.change_domain(self.x))
values = curve2.evaluate_at_x(self.x)
self.y = self.y - values
return None
|
python
|
def subtract(self, curve2, new_obj=False):
"""
Method that calculates difference between 2 curves
(or subclasses of curves). Domain of self must be in
domain of curve2 what means min(self.x) >= min(curve2.x)
and max(self.x) <= max(curve2.x).
Might modify self, and can return the result or None
Use subtract as -= operator, check whether returned value is None:
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[-1, 1], [5, 1]])) is None
True
Use subtract again but return a new object this time.
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[-1, 1], [5, 1]]), new_obj=True).y
DataSet([-1., 0., 1., 0.])
Try using wrong inputs to create a new object,
and check whether it throws an exception:
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[1, -1], [2, -1]]), new_obj=True) is None
Traceback (most recent call last):
...
Exception: curve2 does not include self domain
:param curve2: second object to calculate difference
:param new_obj: if True, method is creating new object
instead of modifying self
:return: None if new_obj is False (but will modify self)
or type(self) object containing the result
"""
# domain1 = [a1, b1]
# domain2 = [a2, b2]
a1, b1 = np.min(self.x), np.max(self.x)
a2, b2 = np.min(curve2.x), np.max(curve2.x)
# check whether domain condition is satisfied
if a2 > a1 or b2 < b1:
logger.error("Domain of self must be in domain of given curve")
raise Exception("curve2 does not include self domain")
# if we want to create and return a new object
# rather then modify existing one
if new_obj:
return functions.subtract(self, curve2.change_domain(self.x))
values = curve2.evaluate_at_x(self.x)
self.y = self.y - values
return None
|
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"=",
"self",
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"y",
"-",
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"return",
"None"
] |
Method that calculates difference between 2 curves
(or subclasses of curves). Domain of self must be in
domain of curve2 what means min(self.x) >= min(curve2.x)
and max(self.x) <= max(curve2.x).
Might modify self, and can return the result or None
Use subtract as -= operator, check whether returned value is None:
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[-1, 1], [5, 1]])) is None
True
Use subtract again but return a new object this time.
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[-1, 1], [5, 1]]), new_obj=True).y
DataSet([-1., 0., 1., 0.])
Try using wrong inputs to create a new object,
and check whether it throws an exception:
>>> Curve([[0, 0], [1, 1], [2, 2], [3, 1]]).subtract(\
Curve([[1, -1], [2, -1]]), new_obj=True) is None
Traceback (most recent call last):
...
Exception: curve2 does not include self domain
:param curve2: second object to calculate difference
:param new_obj: if True, method is creating new object
instead of modifying self
:return: None if new_obj is False (but will modify self)
or type(self) object containing the result
|
[
"Method",
"that",
"calculates",
"difference",
"between",
"2",
"curves",
"(",
"or",
"subclasses",
"of",
"curves",
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"must",
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"what",
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"Might",
"modify",
"self",
"and",
"can",
"return",
"the",
"result",
"or",
"None"
] |
train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/curve.py#L227-L275
|
asweigart/PyMsgBox
|
pymsgbox/_native_win.py
|
alert
|
def alert(text='', title='', button='OK'):
"""Displays a simple message box with text and a single OK button. Returns the text of the button clicked on."""
messageBoxFunc(0, text, title, MB_OK | MB_SETFOREGROUND | MB_TOPMOST)
return button
|
python
|
def alert(text='', title='', button='OK'):
"""Displays a simple message box with text and a single OK button. Returns the text of the button clicked on."""
messageBoxFunc(0, text, title, MB_OK | MB_SETFOREGROUND | MB_TOPMOST)
return button
|
[
"def",
"alert",
"(",
"text",
"=",
"''",
",",
"title",
"=",
"''",
",",
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"=",
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"(",
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",",
"title",
",",
"MB_OK",
"|",
"MB_SETFOREGROUND",
"|",
"MB_TOPMOST",
")",
"return",
"button"
] |
Displays a simple message box with text and a single OK button. Returns the text of the button clicked on.
|
[
"Displays",
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"simple",
"message",
"box",
"with",
"text",
"and",
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"single",
"OK",
"button",
".",
"Returns",
"the",
"text",
"of",
"the",
"button",
"clicked",
"on",
"."
] |
train
|
https://github.com/asweigart/PyMsgBox/blob/c94325d21c08690dd89ebf9ebf1cf1b6ed54a1da/pymsgbox/_native_win.py#L39-L42
|
asweigart/PyMsgBox
|
pymsgbox/_native_win.py
|
confirm
|
def confirm(text='', title='', buttons=['OK', 'Cancel']):
"""Displays a message box with OK and Cancel buttons. Number and text of buttons can be customized. Returns the text of the button clicked on."""
retVal = messageBoxFunc(0, text, title, MB_OKCANCEL | MB_ICONQUESTION | MB_SETFOREGROUND | MB_TOPMOST)
if retVal == 1 or len(buttons) == 1:
return buttons[0]
elif retVal == 2:
return buttons[1]
else:
assert False, 'Unexpected return value from MessageBox: %s' % (retVal)
|
python
|
def confirm(text='', title='', buttons=['OK', 'Cancel']):
"""Displays a message box with OK and Cancel buttons. Number and text of buttons can be customized. Returns the text of the button clicked on."""
retVal = messageBoxFunc(0, text, title, MB_OKCANCEL | MB_ICONQUESTION | MB_SETFOREGROUND | MB_TOPMOST)
if retVal == 1 or len(buttons) == 1:
return buttons[0]
elif retVal == 2:
return buttons[1]
else:
assert False, 'Unexpected return value from MessageBox: %s' % (retVal)
|
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] |
Displays a message box with OK and Cancel buttons. Number and text of buttons can be customized. Returns the text of the button clicked on.
|
[
"Displays",
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"message",
"box",
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"button",
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"on",
"."
] |
train
|
https://github.com/asweigart/PyMsgBox/blob/c94325d21c08690dd89ebf9ebf1cf1b6ed54a1da/pymsgbox/_native_win.py#L44-L52
|
DataMedSci/beprof
|
beprof/functions.py
|
subtract
|
def subtract(curve1, curve2, def_val=0):
"""
Function calculates difference between curve1 and curve2
and returns new object which domain is an union
of curve1 and curve2 domains
Returned object is of type type(curve1)
and has same metadata as curve1 object
:param curve1: first curve to calculate the difference
:param curve2: second curve to calculate the difference
:param def_val: default value for points that cannot be interpolated
:return: new object of type type(curve1) with element-wise difference
(using interpolation if necessary)
"""
coord1 = np.union1d(curve1.x, curve2.x)
y1 = curve1.evaluate_at_x(coord1, def_val)
y2 = curve2.evaluate_at_x(coord1, def_val)
coord2 = y1 - y2
# the below is explained at the end of curve.Curve.change_domain()
obj = curve1.__class__(np.dstack((coord1, coord2))[0], **curve1.__dict__['metadata'])
return obj
|
python
|
def subtract(curve1, curve2, def_val=0):
"""
Function calculates difference between curve1 and curve2
and returns new object which domain is an union
of curve1 and curve2 domains
Returned object is of type type(curve1)
and has same metadata as curve1 object
:param curve1: first curve to calculate the difference
:param curve2: second curve to calculate the difference
:param def_val: default value for points that cannot be interpolated
:return: new object of type type(curve1) with element-wise difference
(using interpolation if necessary)
"""
coord1 = np.union1d(curve1.x, curve2.x)
y1 = curve1.evaluate_at_x(coord1, def_val)
y2 = curve2.evaluate_at_x(coord1, def_val)
coord2 = y1 - y2
# the below is explained at the end of curve.Curve.change_domain()
obj = curve1.__class__(np.dstack((coord1, coord2))[0], **curve1.__dict__['metadata'])
return obj
|
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Returned object is of type type(curve1)
and has same metadata as curve1 object
:param curve1: first curve to calculate the difference
:param curve2: second curve to calculate the difference
:param def_val: default value for points that cannot be interpolated
:return: new object of type type(curve1) with element-wise difference
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|
[
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"as",
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"object"
] |
train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/functions.py#L4-L24
|
DataMedSci/beprof
|
beprof/functions.py
|
medfilt
|
def medfilt(vector, window):
"""
Apply a window-length median filter to a 1D array vector.
Should get rid of 'spike' value 15.
>>> print(medfilt(np.array([1., 15., 1., 1., 1.]), 3))
[1. 1. 1. 1. 1.]
The 'edge' case is a bit tricky...
>>> print(medfilt(np.array([15., 1., 1., 1., 1.]), 3))
[15. 1. 1. 1. 1.]
Inspired by: https://gist.github.com/bhawkins/3535131
"""
if not window % 2 == 1:
raise ValueError("Median filter length must be odd.")
if not vector.ndim == 1:
raise ValueError("Input must be one-dimensional.")
k = (window - 1) // 2 # window movement
result = np.zeros((len(vector), window), dtype=vector.dtype)
result[:, k] = vector
for i in range(k):
j = k - i
result[j:, i] = vector[:-j]
result[:j, i] = vector[0]
result[:-j, -(i + 1)] = vector[j:]
result[-j:, -(i + 1)] = vector[-1]
return np.median(result, axis=1)
|
python
|
def medfilt(vector, window):
"""
Apply a window-length median filter to a 1D array vector.
Should get rid of 'spike' value 15.
>>> print(medfilt(np.array([1., 15., 1., 1., 1.]), 3))
[1. 1. 1. 1. 1.]
The 'edge' case is a bit tricky...
>>> print(medfilt(np.array([15., 1., 1., 1., 1.]), 3))
[15. 1. 1. 1. 1.]
Inspired by: https://gist.github.com/bhawkins/3535131
"""
if not window % 2 == 1:
raise ValueError("Median filter length must be odd.")
if not vector.ndim == 1:
raise ValueError("Input must be one-dimensional.")
k = (window - 1) // 2 # window movement
result = np.zeros((len(vector), window), dtype=vector.dtype)
result[:, k] = vector
for i in range(k):
j = k - i
result[j:, i] = vector[:-j]
result[:j, i] = vector[0]
result[:-j, -(i + 1)] = vector[j:]
result[-j:, -(i + 1)] = vector[-1]
return np.median(result, axis=1)
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Apply a window-length median filter to a 1D array vector.
Should get rid of 'spike' value 15.
>>> print(medfilt(np.array([1., 15., 1., 1., 1.]), 3))
[1. 1. 1. 1. 1.]
The 'edge' case is a bit tricky...
>>> print(medfilt(np.array([15., 1., 1., 1., 1.]), 3))
[15. 1. 1. 1. 1.]
Inspired by: https://gist.github.com/bhawkins/3535131
|
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"-",
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"1D",
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"."
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train
|
https://github.com/DataMedSci/beprof/blob/f94c10929ea357bd0e5ead8f7a2d3061acfd6494/beprof/functions.py#L27-L56
|
JohannesBuchner/regulargrid
|
regulargrid/interpn.py
|
interpn
|
def interpn(*args, **kw):
"""Interpolation on N-D.
ai = interpn(x, y, z, ..., a, xi, yi, zi, ...)
where the arrays x, y, z, ... define a rectangular grid
and a.shape == (len(x), len(y), len(z), ...) are the values
interpolate at xi, yi, zi, ...
"""
method = kw.pop('method', 'cubic')
if kw:
raise ValueError("Unknown arguments: " % kw.keys())
nd = (len(args)-1)//2
if len(args) != 2*nd+1:
raise ValueError("Wrong number of arguments")
q = args[:nd]
qi = args[nd+1:]
a = args[nd]
for j in range(nd):
#print q[j].shape, a.shape
a = interp1d(q[j], a, axis=j, kind=method)(qi[j])
return a
|
python
|
def interpn(*args, **kw):
"""Interpolation on N-D.
ai = interpn(x, y, z, ..., a, xi, yi, zi, ...)
where the arrays x, y, z, ... define a rectangular grid
and a.shape == (len(x), len(y), len(z), ...) are the values
interpolate at xi, yi, zi, ...
"""
method = kw.pop('method', 'cubic')
if kw:
raise ValueError("Unknown arguments: " % kw.keys())
nd = (len(args)-1)//2
if len(args) != 2*nd+1:
raise ValueError("Wrong number of arguments")
q = args[:nd]
qi = args[nd+1:]
a = args[nd]
for j in range(nd):
#print q[j].shape, a.shape
a = interp1d(q[j], a, axis=j, kind=method)(qi[j])
return a
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train
|
https://github.com/JohannesBuchner/regulargrid/blob/8803d8367c6b413d7a70ec474c67cc45ad8c00c8/regulargrid/interpn.py#L4-L24
|
JohannesBuchner/regulargrid
|
regulargrid/interpn.py
|
npinterpn
|
def npinterpn(*args, **kw):
"""Interpolation on N-D.
ai = interpn(x, y, z, ..., a, xi, yi, zi, ...)
where the arrays x, y, z, ... define a rectangular grid
and a.shape == (len(x), len(y), len(z), ...) are the values
interpolate at xi, yi, zi, ...
"""
method = kw.pop('method', 'cubic')
if kw:
raise ValueError("Unknown arguments: " % kw.keys())
nd = (len(args)-1)//2
if len(args) != 2*nd+1:
raise ValueError("Wrong number of arguments")
q = args[:nd]
qi = args[nd+1:]
a = args[nd]
for j in range(nd):
#print q[j].shape, a.shape
a = interp(q[j], a, axis=j, kind=method)(qi[j])
return a
|
python
|
def npinterpn(*args, **kw):
"""Interpolation on N-D.
ai = interpn(x, y, z, ..., a, xi, yi, zi, ...)
where the arrays x, y, z, ... define a rectangular grid
and a.shape == (len(x), len(y), len(z), ...) are the values
interpolate at xi, yi, zi, ...
"""
method = kw.pop('method', 'cubic')
if kw:
raise ValueError("Unknown arguments: " % kw.keys())
nd = (len(args)-1)//2
if len(args) != 2*nd+1:
raise ValueError("Wrong number of arguments")
q = args[:nd]
qi = args[nd+1:]
a = args[nd]
for j in range(nd):
#print q[j].shape, a.shape
a = interp(q[j], a, axis=j, kind=method)(qi[j])
return a
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[
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train
|
https://github.com/JohannesBuchner/regulargrid/blob/8803d8367c6b413d7a70ec474c67cc45ad8c00c8/regulargrid/interpn.py#L26-L46
|
coleifer/wtf-peewee
|
wtfpeewee/orm.py
|
model_fields
|
def model_fields(model, allow_pk=False, only=None, exclude=None,
field_args=None, converter=None):
"""
Generate a dictionary of fields for a given Peewee model.
See `model_form` docstring for description of parameters.
"""
converter = converter or ModelConverter()
field_args = field_args or {}
model_fields = list(model._meta.sorted_fields)
if not allow_pk:
model_fields.pop(0)
if only:
model_fields = [x for x in model_fields if x.name in only]
elif exclude:
model_fields = [x for x in model_fields if x.name not in exclude]
field_dict = {}
for model_field in model_fields:
name, field = converter.convert(
model,
model_field,
field_args.get(model_field.name))
field_dict[name] = field
return field_dict
|
python
|
def model_fields(model, allow_pk=False, only=None, exclude=None,
field_args=None, converter=None):
"""
Generate a dictionary of fields for a given Peewee model.
See `model_form` docstring for description of parameters.
"""
converter = converter or ModelConverter()
field_args = field_args or {}
model_fields = list(model._meta.sorted_fields)
if not allow_pk:
model_fields.pop(0)
if only:
model_fields = [x for x in model_fields if x.name in only]
elif exclude:
model_fields = [x for x in model_fields if x.name not in exclude]
field_dict = {}
for model_field in model_fields:
name, field = converter.convert(
model,
model_field,
field_args.get(model_field.name))
field_dict[name] = field
return field_dict
|
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"model",
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] |
train
|
https://github.com/coleifer/wtf-peewee/blob/f062c59b05ce9ba74467514a272d353f803f37d1/wtfpeewee/orm.py#L194-L221
|
coleifer/wtf-peewee
|
wtfpeewee/orm.py
|
model_form
|
def model_form(model, base_class=Form, allow_pk=False, only=None, exclude=None,
field_args=None, converter=None):
"""
Create a wtforms Form for a given Peewee model class::
from wtfpeewee.orm import model_form
from myproject.myapp.models import User
UserForm = model_form(User)
:param model:
A Peewee model class
:param base_class:
Base form class to extend from. Must be a ``wtforms.Form`` subclass.
:param only:
An optional iterable with the property names that should be included in
the form. Only these properties will have fields.
:param exclude:
An optional iterable with the property names that should be excluded
from the form. All other properties will have fields.
:param field_args:
An optional dictionary of field names mapping to keyword arguments used
to construct each field object.
:param converter:
A converter to generate the fields based on the model properties. If
not set, ``ModelConverter`` is used.
"""
field_dict = model_fields(model, allow_pk, only, exclude, field_args, converter)
return type(model.__name__ + 'Form', (base_class, ), field_dict)
|
python
|
def model_form(model, base_class=Form, allow_pk=False, only=None, exclude=None,
field_args=None, converter=None):
"""
Create a wtforms Form for a given Peewee model class::
from wtfpeewee.orm import model_form
from myproject.myapp.models import User
UserForm = model_form(User)
:param model:
A Peewee model class
:param base_class:
Base form class to extend from. Must be a ``wtforms.Form`` subclass.
:param only:
An optional iterable with the property names that should be included in
the form. Only these properties will have fields.
:param exclude:
An optional iterable with the property names that should be excluded
from the form. All other properties will have fields.
:param field_args:
An optional dictionary of field names mapping to keyword arguments used
to construct each field object.
:param converter:
A converter to generate the fields based on the model properties. If
not set, ``ModelConverter`` is used.
"""
field_dict = model_fields(model, allow_pk, only, exclude, field_args, converter)
return type(model.__name__ + 'Form', (base_class, ), field_dict)
|
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Create a wtforms Form for a given Peewee model class::
from wtfpeewee.orm import model_form
from myproject.myapp.models import User
UserForm = model_form(User)
:param model:
A Peewee model class
:param base_class:
Base form class to extend from. Must be a ``wtforms.Form`` subclass.
:param only:
An optional iterable with the property names that should be included in
the form. Only these properties will have fields.
:param exclude:
An optional iterable with the property names that should be excluded
from the form. All other properties will have fields.
:param field_args:
An optional dictionary of field names mapping to keyword arguments used
to construct each field object.
:param converter:
A converter to generate the fields based on the model properties. If
not set, ``ModelConverter`` is used.
|
[
"Create",
"a",
"wtforms",
"Form",
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"given",
"Peewee",
"model",
"class",
"::"
] |
train
|
https://github.com/coleifer/wtf-peewee/blob/f062c59b05ce9ba74467514a272d353f803f37d1/wtfpeewee/orm.py#L224-L251
|
asweigart/PyMsgBox
|
pymsgbox/__init__.py
|
alert
|
def alert(text='', title='', button=OK_TEXT, root=None, timeout=None):
"""Displays a simple message box with text and a single OK button. Returns the text of the button clicked on."""
assert TKINTER_IMPORT_SUCCEEDED, 'Tkinter is required for pymsgbox'
return _buttonbox(msg=text, title=title, choices=[str(button)], root=root, timeout=timeout)
|
python
|
def alert(text='', title='', button=OK_TEXT, root=None, timeout=None):
"""Displays a simple message box with text and a single OK button. Returns the text of the button clicked on."""
assert TKINTER_IMPORT_SUCCEEDED, 'Tkinter is required for pymsgbox'
return _buttonbox(msg=text, title=title, choices=[str(button)], root=root, timeout=timeout)
|
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train
|
https://github.com/asweigart/PyMsgBox/blob/c94325d21c08690dd89ebf9ebf1cf1b6ed54a1da/pymsgbox/__init__.py#L97-L100
|
asweigart/PyMsgBox
|
pymsgbox/__init__.py
|
confirm
|
def confirm(text='', title='', buttons=[OK_TEXT, CANCEL_TEXT], root=None, timeout=None):
"""Displays a message box with OK and Cancel buttons. Number and text of buttons can be customized. Returns the text of the button clicked on."""
assert TKINTER_IMPORT_SUCCEEDED, 'Tkinter is required for pymsgbox'
return _buttonbox(msg=text, title=title, choices=[str(b) for b in buttons], root=root, timeout=timeout)
|
python
|
def confirm(text='', title='', buttons=[OK_TEXT, CANCEL_TEXT], root=None, timeout=None):
"""Displays a message box with OK and Cancel buttons. Number and text of buttons can be customized. Returns the text of the button clicked on."""
assert TKINTER_IMPORT_SUCCEEDED, 'Tkinter is required for pymsgbox'
return _buttonbox(msg=text, title=title, choices=[str(b) for b in buttons], root=root, timeout=timeout)
|
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"clicked",
"on",
"."
] |
train
|
https://github.com/asweigart/PyMsgBox/blob/c94325d21c08690dd89ebf9ebf1cf1b6ed54a1da/pymsgbox/__init__.py#L103-L106
|
asweigart/PyMsgBox
|
pymsgbox/__init__.py
|
prompt
|
def prompt(text='', title='' , default='', root=None, timeout=None):
"""Displays a message box with text input, and OK & Cancel buttons. Returns the text entered, or None if Cancel was clicked."""
assert TKINTER_IMPORT_SUCCEEDED, 'Tkinter is required for pymsgbox'
return __fillablebox(text, title, default=default, mask=None,root=root, timeout=timeout)
|
python
|
def prompt(text='', title='' , default='', root=None, timeout=None):
"""Displays a message box with text input, and OK & Cancel buttons. Returns the text entered, or None if Cancel was clicked."""
assert TKINTER_IMPORT_SUCCEEDED, 'Tkinter is required for pymsgbox'
return __fillablebox(text, title, default=default, mask=None,root=root, timeout=timeout)
|
[
"def",
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"default",
"=",
"''",
",",
"root",
"=",
"None",
",",
"timeout",
"=",
"None",
")",
":",
"assert",
"TKINTER_IMPORT_SUCCEEDED",
",",
"'Tkinter is required for pymsgbox'",
"return",
"__fillablebox",
"(",
"text",
",",
"title",
",",
"default",
"=",
"default",
",",
"mask",
"=",
"None",
",",
"root",
"=",
"root",
",",
"timeout",
"=",
"timeout",
")"
] |
Displays a message box with text input, and OK & Cancel buttons. Returns the text entered, or None if Cancel was clicked.
|
[
"Displays",
"a",
"message",
"box",
"with",
"text",
"input",
"and",
"OK",
"&",
"Cancel",
"buttons",
".",
"Returns",
"the",
"text",
"entered",
"or",
"None",
"if",
"Cancel",
"was",
"clicked",
"."
] |
train
|
https://github.com/asweigart/PyMsgBox/blob/c94325d21c08690dd89ebf9ebf1cf1b6ed54a1da/pymsgbox/__init__.py#L109-L112
|
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