def _add_single_block(x, y, name, ax):
"""
Add a single block of two gates.
Args:
*x (float)*:
Layer position.
*y (float)*:
Qubit 1 position.
*name (str)*:
Gate name.
*ax (pyplot.Axes)*:
Axes for the figure.
Returns (inplace):
None
"""
ax.add_patch(
patches.Rectangle((x, y),
0.5,
0.5,
facecolor='white',
edgecolor='black'))
tp = TextPath((x, y + 0.16), name, size=0.25)
center = (tp.get_extents().xmax - tp.get_extents().xmin) / 2
tp = TextPath((x + 0.24 - center, y + 0.16), name, size=0.25)
ax.add_patch(patches.PathPatch(tp, color="black"))
def _add_double_block(x, y, name, ax):
ax.add_patch(
patches.Rectangle((x, y),
0.5,
1.5,
facecolor='white',
edgecolor='black'))
tp = TextPath((x, y + 0.66), name, size=0.25)
center = (tp.get_extents().xmax - tp.get_extents().xmin) / 2
tp = TextPath((x + 0.24 - center, y + 0.66), name, size=0.25)
ax.add_patch(patches.PathPatch(tp, color="black"))
def text_banner(axes, text, facecolor="red", edgecolor="darkred", linewidth=1,
alpha=0.3, angleadjust=True, zorder=0):
"""
Paint text across a hole axes.
For height > width, angleadjust should be False.
"""
# draw the text into a patch
textpath = TextPath((0, 0), text, size=20, transform=axes.transAxes)
tp_bbox = textpath.get_extents()
patch = PathPatch(textpath, fc=facecolor, ec=edgecolor, lw=linewidth, alpha=alpha,
transform=IdentityTransform(), zorder=11)
# get angle and scale to transform text to axes coordinates
ax_bbox = axes.get_window_extent()
angle = math.atan2(ax_bbox.height, ax_bbox.width) * \
(ax_bbox.height/ax_bbox.width if angleadjust else 1)
scale = min(*rotated_scale(tp_bbox.width, tp_bbox.height, angle,
ax_bbox.width, ax_bbox.height))*0.95
# paint the patch into the axes
offsetbox = AuxTransformBox(Affine2D().rotate(angle).scale(scale))
offsetbox.add_artist(patch)
artist = AnnotationBbox(offsetbox, (0.5, 0.5),
xycoords='axes fraction',
frameon=False)
artist.set_zorder(zorder)
axes.add_artist(artist)
def make_text_elements(text, x=0.0, y=0.0, width=1.0, height=1.0, color='blue', edgecolor="black",
font = FontProperties(family='monospace')):
tp = TextPath((0.0, 0.0), text, size=1, prop=font)
bbox = tp.get_extents()
bwidth = bbox.x1 - bbox.x0
bheight = bbox.y1 - bbox.y0
trafo = Affine2D()
trafo.translate(-bbox.x0, -bbox.y0)
trafo.scale(1 / bwidth * width, 1 / bheight * height)
trafo.translate(x,y)
tp = tp.transformed(trafo)
return patches.PathPatch(tp, facecolor=color, edgecolor=edgecolor)
def drawNT(ax,
text,
x=0.0,
y=0.0,
width=1.0,
height=1.0,
color="#008000",
edgecolor="None",
font=FontProperties(family="monospace")):
tp = TextPath((0.0, 0.0), text, size=1, prop=font)
bbox = tp.get_extents()
bwidth = bbox.x1 - bbox.x0
bheight = bbox.y1 - bbox.y0
txt = Affine2D()
txt.translate(-bbox.x0, -bbox.y0)
txt.scale(1 / bwidth * width, 1 / bheight * height)
txt.translate(x, y)
tp = tp.transformed(txt)
patch = patches.PathPatch(tp, facecolor=color, edgecolor=edgecolor)
ax.add_patch(patch)
def add_bar_labels(fig, ax, bars, bottom=0):
transOffset = offset_copy(ax.transData,
fig=fig,
x=0.,
y=-2.,
units='points')
transOffsetUp = offset_copy(ax.transData,
fig=fig,
x=0.,
y=1.,
units='points')
for bar in bars:
for i, [patch,
num] in enumerate(zip(bar.patches,
np.arange(len(bar.patches)))):
if len(bottom) == len(bar): b = bottom[i]
else: b = bottom
height = patch.get_height() + b
xi = patch.get_x() + patch.get_width() / 2.
va = 'top'
c = 'w'
t = TextPath((0, 0),
"${xi}$".format(xi=xi),
rotation=0,
ha='center')
transform = transOffset
if patch.get_extents().height <= t.get_extents().height + 5:
va = 'bottom'
c = 'k'
transform = transOffsetUp
ax.text(xi,
height,
"${xi}$".format(xi=int(num)),
color=c,
rotation=0,
ha='center',
va=va,
transform=transform)
ax.set_xticks([])
def add_bar_labels(fig, ax, bars, bottom=0):
transOffset = offset_copy(ax.transData, fig=fig,
x=0., y= -2., units='points')
transOffsetUp = offset_copy(ax.transData, fig=fig,
x=0., y=1., units='points')
for bar in bars:
for i, [patch, num] in enumerate(zip(bar.patches, np.arange(len(bar.patches)))):
if len(bottom) == len(bar): b = bottom[i]
else: b = bottom
height = patch.get_height() + b
xi = patch.get_x() + patch.get_width() / 2.
va = 'top'
c = 'w'
t = TextPath((0, 0), "${xi}$".format(xi=xi), rotation=0, ha='center')
transform = transOffset
if patch.get_extents().height <= t.get_extents().height + 5:
va = 'bottom'
c = 'k'
transform = transOffsetUp
ax.text(xi, height, "${xi}$".format(xi=int(num)), color=c, rotation=0, ha='center', va=va, transform=transform)
ax.set_xticks([])
def formatDateAxis(self,ax):
"""Formatuje etykiety osi czasu."""
chartWidth=int(self.fig.get_figwidth()*self.fig.get_dpi()*self.maxSize)
t = TextPath((0,0), '9999-99-99', size=7)
labelWidth = int(t.get_extents().width)
num_ticks=chartWidth/labelWidth/2
length=len(self.data.date)
if(length>num_ticks):
step=length/num_ticks
else:
step=1
x=range(0,length,step)
ax.xaxis.set_major_locator(FixedLocator(x))
ticks=ax.get_xticks()
labels=[]
for i, label in enumerate(ax.get_xticklabels()):
label.set_size(7)
index=int(ticks[i])
if(index>=len(self.data.date)):
labels.append('')
else:
labels.append(self.data.date[index].strftime("%Y-%m-%d"))
label.set_horizontalalignment('center')
ax.xaxis.set_major_formatter(FixedFormatter(labels))
def plot_ARD(self, fignum=None, ax=None, title='', legend=False):
"""If an ARD kernel is present, plot a bar representation using matplotlib
:param fignum: figure number of the plot
:param ax: matplotlib axis to plot on
:param title:
title of the plot,
pass '' to not print a title
pass None for a generic title
"""
if ax is None:
fig = pb.figure(fignum)
ax = fig.add_subplot(111)
else:
fig = ax.figure
from GPy.util import Tango
from matplotlib.textpath import TextPath
Tango.reset()
xticklabels = []
bars = []
x0 = 0
for p in self.parts:
c = Tango.nextMedium()
if hasattr(p, 'ARD') and p.ARD:
if title is None:
ax.set_title('ARD parameters, %s kernel' % p.name)
else:
ax.set_title(title)
if p.name == 'linear':
ard_params = p.variances
else:
ard_params = 1. / p.lengthscale
x = np.arange(x0, x0 + len(ard_params))
bars.append(ax.bar(x, ard_params, align='center', color=c, edgecolor='k', linewidth=1.2, label=p.name))
xticklabels.extend([r"$\mathrm{{{name}}}\ {x}$".format(name=p.name, x=i) for i in np.arange(len(ard_params))])
x0 += len(ard_params)
x = np.arange(x0)
transOffset = offset_copy(ax.transData, fig=fig,
x=0., y= -2., units='points')
transOffsetUp = offset_copy(ax.transData, fig=fig,
x=0., y=1., units='points')
for bar in bars:
for patch, num in zip(bar.patches, np.arange(len(bar.patches))):
height = patch.get_height()
xi = patch.get_x() + patch.get_width() / 2.
va = 'top'
c = 'w'
t = TextPath((0, 0), "${xi}$".format(xi=xi), rotation=0, ha='center')
transform = transOffset
if patch.get_extents().height <= t.get_extents().height + 3:
va = 'bottom'
c = 'k'
transform = transOffsetUp
ax.text(xi, height, "${xi}$".format(xi=int(num)), color=c, rotation=0, ha='center', va=va, transform=transform)
# for xi, t in zip(x, xticklabels):
# ax.text(xi, maxi / 2, t, rotation=90, ha='center', va='center')
# ax.set_xticklabels(xticklabels, rotation=17)
ax.set_xticks([])
ax.set_xlim(-.5, x0 - .5)
if legend:
if title is '':
mode = 'expand'
if len(bars) > 1:
mode = 'expand'
ax.legend(bbox_to_anchor=(0., 1.02, 1., 1.02), loc=3,
ncol=len(bars), mode=mode, borderaxespad=0.)
fig.tight_layout(rect=(0, 0, 1, .9))
else:
ax.legend()
return ax
def create_picture_from(self, text, format, asbytes=True, context=None):
"""
Creates a picture from text.
@param text the text
@param format text, json, ...
@param context (str) indication on the content of text (error, ...)
@param asbytes results as bytes or as an image
@return tuple (picture, format) or PIL.Image (if asbytes is False)
The picture will be bytes, the format png, bmp...
The size of the picture will depend on the text.
The longer, the bigger. The method relies on matplotlib
and then convert the image into a PIL image.
HTML could be rendered with QWebPage from PyQt (not implemented).
"""
if not isinstance(text, (str, bytes)):
text = str(text)
if "\n" not in text:
rows = []
for i in range(0, len(text), 20):
end = min(i + 20, len(text))
rows.append(text[i:end])
text = "\n".join(text)
if len(text) > 200:
text = text[:200]
size = len(text) // 10
figsize = (3 + size, 3 + size)
lines = text.replace("\t", " ").replace("\r", "").split("\n")
import matplotlib.pyplot as plt
from matplotlib.textpath import TextPath
from matplotlib.font_manager import FontProperties
fig = plt.figure(figsize=figsize)
ax = fig.add_subplot(111)
fp = FontProperties(size=200)
dx = 0
dy = 0
for i, line in enumerate(lines):
if len(line.strip()) > 0:
ax.text(0, -dy, line, fontproperties=fp, va='top')
tp = TextPath((0, -dy), line, prop=fp)
bb = tp.get_extents()
dy += bb.height
dx = max(dx, bb.width)
ratio = abs(dx) / max(abs(dy), 1)
ratio = max(min(ratio, 3), 1)
fig.set_size_inches(int((1 + size) * ratio), 1 + size)
ax.set_xlim([0, dx])
ax.set_ylim([-dy, 0])
ax.set_axis_off()
sio = BytesIO()
fig.savefig(sio, format="png")
plt.close()
if asbytes:
b = sio.getvalue(), "png"
self._check_thumbnail_tuple(b)
return b
try:
from PIL import Image
except ImportError: # pragma: no cover
import Image
img = Image.open(sio)
return img
def _make_patch(self):
"""
Returns an appropriately scaled patch object corresponding to
the Glyph.
"""
# Set height
height = self.ceiling - self.floor
# If height is zero, set patch to None and return None
if height == 0.0:
self.patch = None
return None
# Set bounding box for character,
# leaving requested amount of padding above and below the character
char_xmin = self.p - self.width / 2.0
char_ymin = self.floor + self.vpad * height / 2.0
char_width = self.width
char_height = height - self.vpad * height
bbox = Bbox.from_bounds(char_xmin, char_ymin, char_width, char_height)
# Set font properties of Glyph
font_properties = FontProperties(family=self.font_name,
weight=self.font_weight)
# Create a path for Glyph that does not yet have the correct
# position or scaling
tmp_path = TextPath((0, 0), self.c, size=1, prop=font_properties)
# Create create a corresponding path for a glyph representing
# the max stretched character
msc_path = TextPath((0, 0),
self.dont_stretch_more_than,
size=1,
prop=font_properties)
# If need to flip char, do it within tmp_path
if self.flip:
transformation = Affine2D().scale(sx=1, sy=-1)
tmp_path = transformation.transform_path(tmp_path)
# If need to mirror char, do it within tmp_path
if self.mirror:
transformation = Affine2D().scale(sx=-1, sy=1)
tmp_path = transformation.transform_path(tmp_path)
# Get bounding box for temporary character and max_stretched_character
tmp_bbox = tmp_path.get_extents()
msc_bbox = msc_path.get_extents()
# Compute horizontal stretch factor needed for tmp_path
hstretch_tmp = bbox.width / tmp_bbox.width
# Compute horizontal stretch factor needed for msc_path
hstretch_msc = bbox.width / msc_bbox.width
# Choose the MINIMUM of these two horizontal stretch factors.
# This prevents very narrow characters, such as 'I', from being
# stretched too much.
hstretch = min(hstretch_tmp, hstretch_msc)
# Compute the new character width, accounting for the
# limit placed on the stretching factor
char_width = hstretch * tmp_bbox.width
# Compute how much to horizontally shift the character path
char_shift = (bbox.width - char_width) / 2.0
# Compute vertical stetch factor needed for tmp_path
vstretch = bbox.height / tmp_bbox.height
# THESE ARE THE ESSENTIAL TRANSFORMATIONS
# 1. First, translate char path so that lower left corner is at origin
# 2. Then scale char path to desired width and height
# 3. Finally, translate char path to desired position
# char_path is the resulting path used for the Glyph
transformation = Affine2D() \
.translate(tx=-tmp_bbox.xmin, ty=-tmp_bbox.ymin) \
.scale(sx=hstretch, sy=vstretch) \
.translate(tx=bbox.xmin + char_shift, ty=bbox.ymin)
char_path = transformation.transform_path(tmp_path)
# Convert char_path to a patch, which can now be drawn on demand
self.patch = PathPatch(char_path,
facecolor=self.color,
zorder=self.zorder,
alpha=self.alpha,
edgecolor=self.edgecolor,
linewidth=self.edgewidth)
# add patch to axes
self.ax.add_patch(self.patch)
def plot_ARD(self, fignum=None, ax=None, title='', legend=False):
"""If an ARD kernel is present, plot a bar representation using matplotlib
:param fignum: figure number of the plot
:param ax: matplotlib axis to plot on
:param title:
title of the plot,
pass '' to not print a title
pass None for a generic title
"""
if ax is None:
fig = pb.figure(fignum)
ax = fig.add_subplot(111)
else:
fig = ax.figure
from GPy.util import Tango
from matplotlib.textpath import TextPath
Tango.reset()
xticklabels = []
bars = []
x0 = 0
for p in self.parts:
c = Tango.nextMedium()
if hasattr(p, 'ARD') and p.ARD:
if title is None:
ax.set_title('ARD parameters, %s kernel' % p.name)
else:
ax.set_title(title)
if p.name == 'linear':
ard_params = p.variances
else:
ard_params = 1. / p.lengthscale
x = np.arange(x0, x0 + len(ard_params))
bars.append(
ax.bar(x,
ard_params,
align='center',
color=c,
edgecolor='k',
linewidth=1.2,
label=p.name))
xticklabels.extend([
r"$\mathrm{{{name}}}\ {x}$".format(name=p.name, x=i)
for i in np.arange(len(ard_params))
])
x0 += len(ard_params)
x = np.arange(x0)
transOffset = offset_copy(ax.transData,
fig=fig,
x=0.,
y=-2.,
units='points')
transOffsetUp = offset_copy(ax.transData,
fig=fig,
x=0.,
y=1.,
units='points')
for bar in bars:
for patch, num in zip(bar.patches, np.arange(len(bar.patches))):
height = patch.get_height()
xi = patch.get_x() + patch.get_width() / 2.
va = 'top'
c = 'w'
t = TextPath((0, 0),
"${xi}$".format(xi=xi),
rotation=0,
ha='center')
transform = transOffset
if patch.get_extents().height <= t.get_extents().height + 3:
va = 'bottom'
c = 'k'
transform = transOffsetUp
ax.text(xi,
height,
"${xi}$".format(xi=int(num)),
color=c,
rotation=0,
ha='center',
va=va,
transform=transform)
# for xi, t in zip(x, xticklabels):
# ax.text(xi, maxi / 2, t, rotation=90, ha='center', va='center')
# ax.set_xticklabels(xticklabels, rotation=17)
ax.set_xticks([])
ax.set_xlim(-.5, x0 - .5)
if legend:
if title is '':
mode = 'expand'
if len(bars) > 1:
mode = 'expand'
ax.legend(bbox_to_anchor=(0., 1.02, 1., 1.02),
loc=3,
ncol=len(bars),
mode=mode,
borderaxespad=0.)
fig.tight_layout(rect=(0, 0, 1, .9))
else:
ax.legend()
return ax
if __name__ == '__main__':
import numpy
from pprint import pprint
from itertools import islice
import matplotlib.pyplot as pyplot
axes = pyplot.gca()
test_word = "Phillip Seymore Hoffman" # "pearly"
test_path = TextPath( (0,0), test_word )
top_box = test_path.get_extents()
boxes = splitword(top_box, test_path, limit=1)
# axes.add_patch( PathPatch( test_path, lw=1, facecolor="grey" ) )
for p in cleaned_textpath(test_path):
axes.add_patch( PathPatch( p, lw=1, facecolor='red', alpha=0.2 ) )
for box in boxes:
axes.add_patch(
FancyBboxPatch(
(box.xmin, box.ymin),
abs(box.width), abs(box.height),
boxstyle="square,pad=0.0",
facecolor=(0, 0, 1.0), alpha=0.2 ) )
def build_cloud(wordweights,
loose=False, seed=None, split_limit=2**-3, pad=1.10, visual_limit=2**-5,
highest_weight=None ):
"""Convert a list of words and weights into a list of paths and weights.
You should only use this function if you know what you're doing, or if
you really don't want to cache the generated paths. Otherwise just use
the WordCloud class.
Args:
wordweights: An iterator of the form
[ (word, weight), (word, weight), ... ]
such that the weights are in decreasing order.
loose: If `true', words won't be broken up into rectangles after
insertion. This results in a looser cloud, generated faster.
seed: A random seed to use
split_limit: When words are approximated by rectangles, the rectangles
will have dimensions less than split_limit. Higher values result
in a tighter cloud, at a cost of more CPU time. The largest word
has height 1.0.
pad: Expand a word's bounding box by a factor of `pad' before
inserting it. This can actually result in a tighter cloud if you
have many small words by leaving space between large words.
visual_limit: Words with height smaller than visual_limit will be
discarded.
highest_weight: Experimental feature. If you provide an upper bound
on the weights that will be seen you don't have to provide words
and weights sorted. The resulting word cloud will be noticeably
uglier.
Generates:
Tuples of the form (path, weight) such that:
* No two paths intersect
* Paths are fairly densely packed around the origin
* All weights are normalized to fall in the interval [0, 1]
"""
if seed is not None:
random.seed(seed)
font_properties = font_manager.FontProperties(
family="sans", weight="bold", stretch="condensed")
xheight = TextPath((0,0), "x", prop=font_properties).get_extents().expanded(pad,pad).height
# These are magic numbers. Most wordclouds will not exceed these bounds.
# If they do, it will have to re-index all of the bounding boxes.
index_bounds = (-16, -16, 16, 16)
index = BboxQuadtree(index_bounds)
if highest_weight is None:
# Attempt to pull the first word and weight. If we fail, the wordweights
# list is empty and we should just quit.
#
# All this nonsense is to ensure it accepts an iterator of words
# correctly.
iterwords = iter(wordweights)
try:
first_word, first_weight = iterwords.next()
iterwords = chain([(first_word, first_weight)], iterwords)
except StopIteration:
return
# We'll scale all of the weights down by this much.
weight_scale = 1.0/first_weight
else:
weight_scale = 1.0/highest_weight
iterwords = iter(wordweights)
bboxes = list()
bounds = transforms.Bbox(((-0.5, -0.5), (-0.5, -0.5)))
for tword, tweight in iterwords:
weight = tweight*weight_scale
if weight < visual_limit:
# You're not going to be able to see the word anyway. Quit
# rendering words now.
continue
word_path = TextPath((0,0), tword, prop=font_properties)
word_bbox = word_path.get_extents().expanded(pad, pad)
# word_scale = weight/float(word_bbox.height)
word_scale = weight/float(xheight)
# When we build a TextPath at (0,0) it doesn't necessarily have
# its corner at (0,0). So we have to translate to the origin,
# scale down, then translate to center it. Feel free to simplify
# this if you want.
word_trans = Affine2D.identity().translate(
-word_bbox.xmin,
-word_bbox.ymin
).scale(word_scale).translate(
-0.5*abs(word_bbox.width)*word_scale,
-0.5*abs(word_bbox.height)*word_scale )
word_path = word_path.transformed(word_trans)
word_bbox = word_path.get_extents().expanded(pad, pad)
if weight > split_limit:
# Big words we place carefully, trying to make the dimensions of
# the cloud equal and center it around the origin.
gaps = (
("left", bounds.xmin), ("bottom", bounds.ymin),
("right", bounds.xmax), ("top", bounds.ymax) )
direction = min(gaps, key=lambda g: abs(g[1]))[0]
else:
# Small words we place randomly.
direction = random.choice( [ "left", "bottom", "right", "top" ] )
# Randomly place the word along an edge...
if direction in ( "top", "bottom" ):
center = random_position(bounds.xmin, bounds.xmax)
elif direction in ( "right", "left" ):
center = random_position(bounds.ymin, bounds.ymax)
# And push it toward an axis.
if direction == "top":
bbox = word_bbox.translated( center, index_bounds[3] )
xpos, ypos = push_bbox_down( bbox, bboxes, index )
elif direction == "right":
bbox = word_bbox.translated( index_bounds[2], center )
xpos, ypos = push_bbox_left( bbox, bboxes, index )
elif direction == "bottom":
bbox = word_bbox.translated( center, index_bounds[1] )
xpos, ypos = push_bbox_up( bbox, bboxes, index )
elif direction == "left":
bbox = word_bbox.translated( index_bounds[0], center )
xpos, ypos = push_bbox_right( bbox, bboxes, index )
# Now alternate pushing the word toward different axes until either
# it stops movign or we get sick of it.
max_moves = 2
moves = 0
while moves < max_moves and (moves == 0 or prev_xpos != xpos or prev_ypos != ypos):
moves += 1
prev_xpos = xpos
prev_ypos = ypos
if direction in ["top", "bottom", "vertical"]:
if xpos > 0:
bbox = word_bbox.translated( xpos, ypos )
xpos, ypos = push_bbox_left( bbox, bboxes, index )
elif xpos < 0:
bbox = word_bbox.translated( xpos, ypos )
xpos, ypos = push_bbox_right( bbox, bboxes, index )
direction = "horizontal"
elif direction in ["left", "right", "horizontal"]:
if ypos > 0:
bbox = word_bbox.translated( xpos, ypos )
xpos, ypos = push_bbox_down( bbox, bboxes, index )
elif ypos < 0:
bbox = word_bbox.translated( xpos, ypos )
xpos, ypos = push_bbox_up( bbox, bboxes, index )
direction = "vertical"
wordtrans = Affine2D.identity().translate( xpos, ypos )
transpath = word_path.transformed(wordtrans)
bbox = transpath.get_extents()
# Swallow the new word into the bounding box for the word cloud.
bounds = matplotlib.transforms.Bbox.union( [ bounds, bbox ] )
# We need to check if we've expanded past the bounds of our quad tree.
# If so we'll need to expand the bounds and then re-index.
new_bounds = index_bounds
while not BoxifyWord.bbox_covers(
# FIXME: Why am I not just doing this with a couple of logarithms?
matplotlib.transforms.Bbox(((new_bounds[0], new_bounds[1]),
(new_bounds[2], new_bounds[3]))),
bounds ):
new_bounds = tuple( map( lambda x: 2*x, index_bounds ) )
if new_bounds != index_bounds:
# We need to re-index.
index_bounds = new_bounds
index = BboxQuadtree(index_bounds)
for i, b in enumerate(bboxes):
index.add_bbox(i, b)
# Approximate the new word by rectangles (unless it's too small) and
# insert them into the index.
if not loose and max(abs(bbox.width), abs(bbox.height)) > split_limit:
for littlebox in BoxifyWord.splitword(
bbox, transpath, limit=split_limit ):
bboxes.append( littlebox )
index.add_bbox( len(bboxes)-1, littlebox )
else:
bboxes.append( bbox )
index.add_bbox( len(bboxes)-1, bbox )
yield (transpath, weight)
def create_picture_from(self, text, format, asbytes=True, context=None):
"""
Creates a picture from text.
@param text the text
@param format text, json, ...
@param context (str) indication on the content of text (error, ...)
@param asbytes results as bytes or as an image
@return tuple (picture, format) or PIL.Image (if asbytes is False)
The picture will be bytes, the format png, bmp...
The size of the picture will depend on the text.
The longer, the bigger. The method relies on matplotlib
and then convert the image into a PIL image.
HTML could be rendered with QWebPage from PyQt (not implemented).
"""
if not isinstance(text, (str, bytes)):
text = str(text)
if "\n" not in text:
rows = []
for i in range(0, len(text), 20):
end = min(i + 20, len(text))
rows.append(text[i:end])
text = "\n".join(text)
if len(text) > 200:
text = text[:200]
size = len(text) // 10
figsize = (3 + size, 3 + size)
lines = text.replace("\t", " ").replace("\r", "").split("\n")
import matplotlib.pyplot as plt
from matplotlib.textpath import TextPath
from matplotlib.font_manager import FontProperties
fig = plt.figure(figsize=figsize)
ax = fig.add_subplot(111)
fp = FontProperties(size=200)
dx = 0
dy = 0
for i, line in enumerate(lines):
if len(line.strip()) > 0:
ax.text(0, -dy, line, fontproperties=fp, va='top')
tp = TextPath((0, -dy), line, prop=fp)
bb = tp.get_extents()
dy += bb.height
dx = max(dx, bb.width)
ratio = abs(dx) / max(abs(dy), 1)
ratio = max(min(ratio, 3), 1)
fig.set_size_inches(int((1 + size) * ratio), 1 + size)
ax.set_xlim([0, dx])
ax.set_ylim([-dy, 0])
ax.set_axis_off()
sio = BytesIO()
fig.savefig(sio, format="png")
plt.close()
if asbytes:
b = sio.getvalue(), "png"
self._check_thumbnail_tuple(b)
return b
else:
try:
from PIL import Image
except ImportError:
import Image
img = Image.open(sio)
return img
