我想将matplotlib图表嵌入到由ReportLab直接生成的PDF中 - 即不首先保存为PNG，然后将PNG嵌入到PDF中（我想我会得到更好的输出质量）。
有谁知道是否有一个matplotlib可流动的ReportLab？
谢谢
这是使用pdfrw的解决方案：
#!/usr/bin/env python
# encoding: utf-8
"""matplotlib_example.py
An simple example of how to insert matplotlib generated figures
into a ReportLab platypus document.
"""
import matplotlib
matplotlib.use('PDF')
import matplotlib.pyplot as plt
import cStringIO
from pdfrw import PdfReader
from pdfrw.buildxobj import pagexobj
from pdfrw.toreportlab import makerl
from reportlab.platypus import Flowable
from reportlab.lib.enums import TA_LEFT, TA_CENTER, TA_RIGHT
from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
from reportlab.lib.styles import getSampleStyleSheet
from reportlab.rl_config import defaultPageSize
from reportlab.lib.units import inch
PAGE_HEIGHT=defaultPageSize[1]; PAGE_WIDTH=defaultPageSize[0]
styles = getSampleStyleSheet()
class PdfImage(Flowable):
"""PdfImage wraps the first page from a PDF file as a Flowable
which can be included into a ReportLab Platypus document.
Based on the vectorpdf extension in rst2pdf (http://code.google.com/p/rst2pdf/)"""
def __init__(self, filename_or_object, width=None, height=None, kind='direct'):
from reportlab.lib.units import inch
# If using StringIO buffer, set pointer to begining
if hasattr(filename_or_object, 'read'):
filename_or_object.seek(0)
page = PdfReader(filename_or_object, decompress=False).pages[0]
self.xobj = pagexobj(page)
self.imageWidth = width
self.imageHeight = height
x1, y1, x2, y2 = self.xobj.BBox
self._w, self._h = x2 - x1, y2 - y1
if not self.imageWidth:
self.imageWidth = self._w
if not self.imageHeight:
self.imageHeight = self._h
self.__ratio = float(self.imageWidth)/self.imageHeight
if kind in ['direct','absolute'] or width==None or height==None:
self.drawWidth = width or self.imageWidth
self.drawHeight = height or self.imageHeight
elif kind in ['bound','proportional']:
factor = min(float(width)/self._w,float(height)/self._h)
self.drawWidth = self._w*factor
self.drawHeight = self._h*factor
def wrap(self, aW, aH):
return self.drawWidth, self.drawHeight
def drawOn(self, canv, x, y, _sW=0):
if _sW > 0 and hasattr(self, 'hAlign'):
a = self.hAlign
if a in ('CENTER', 'CENTRE', TA_CENTER):
x += 0.5*_sW
elif a in ('RIGHT', TA_RIGHT):
x += _sW
elif a not in ('LEFT', TA_LEFT):
raise ValueError("Bad hAlign value " + str(a))
xobj = self.xobj
xobj_name = makerl(canv._doc, xobj)
xscale = self.drawWidth/self._w
yscale = self.drawHeight/self._h
x -= xobj.BBox[0] * xscale
y -= xobj.BBox[1] * yscale
canv.saveState()
canv.translate(x, y)
canv.scale(xscale, yscale)
canv.doForm(xobj_name)
canv.restoreState()
Title = "Hello world"
pageinfo = "platypus example"
def myFirstPage(canvas, doc):
canvas.saveState()
canvas.setFont('Times-Bold',16)
canvas.drawCentredString(PAGE_WIDTH/2.0, PAGE_HEIGHT-108, Title)
canvas.setFont('Times-Roman',9)
canvas.drawString(inch, 0.75 * inch, "First Page / %s" % pageinfo)
canvas.restoreState()
def myLaterPages(canvas, doc):
canvas.saveState()
canvas.setFont('Times-Roman',9)
canvas.drawString(inch, 0.75 * inch, "Page %d %s" % (doc.page, pageinfo))
canvas.restoreState()
def go():
fig = plt.figure(figsize=(4, 3))
plt.plot([1,2,3,4])
plt.ylabel('some numbers')
imgdata = cStringIO.StringIO()
fig.savefig(imgdata,format='PDF')
doc = SimpleDocTemplate("document.pdf")
Story = [Spacer(1,2*inch)]
style = styles["Normal"]
for i in range(5):
bogustext = ("This is Paragraph number %s. " % i) *20
p = Paragraph(bogustext, style)
Story.append(p)
Story.append(Spacer(1,0.2*inch))
pi = PdfImage(imgdata)
Story.append(pi)
Story.append(Spacer(1,0.2*inch))
doc.build(Story, onFirstPage=myFirstPage, onLaterPages=myLaterPages)
if __name__ == '__main__':
go()
没有一个，但我自己使用MatLlotLib和ReportLab做的是生成PNG然后嵌入PNG，这样我就不需要也使用PIL了。但是，如果您使用PIL，我相信您应该能够使用MatPlotLib和ReportLab生成和嵌入EPS。
pdfrw的作者Patrick Maupin在另一个question中提供了一个更简单，更简单的答案。 （我感谢他对我以前的答案说的客气话。）他还提到在使用pdfrw提取它们之前将matplotlib数据保存为多页PDF会减少重复资源，从而减少最终reportlab PDF的大小。所以这里是他的代码示例的修改，演示了如何通过首先写入多页matplotlib PDF来减少PDF文件的大小。对于此示例，文件大小减少了大约80％。
注意：这是专门用于matplotlib数字。
import os
from matplotlib import pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from reportlab.platypus import Paragraph, SimpleDocTemplate, Spacer, Flowable
from reportlab.lib.units import inch
from reportlab.lib.styles import getSampleStyleSheet
from pdfrw import PdfReader, PdfDict
from pdfrw.buildxobj import pagexobj
from pdfrw.toreportlab import makerl
try:
from cStringIO import StringIO as BytesIO
except ImportError:
from io import BytesIO
styles = getSampleStyleSheet()
style = styles['Normal']
class PdfImage(Flowable):
"""
Generates a reportlab image flowable for matplotlib figures. It is initialized
with either a matplotlib figure or a pointer to a list of pagexobj objects and
an index for the pagexobj to be used.
"""
def __init__(self, fig=None, width=200, height=200, cache=None, cacheindex=0):
self.img_width = width
self.img_height = height
if fig is None and cache is None:
raise ValueError("Either 'fig' or 'cache' must be provided")
if fig is not None:
imgdata = BytesIO()
fig.savefig(imgdata, format='pdf')
imgdata.seek(0)
page, = PdfReader(imgdata).pages
image = pagexobj(page)
self.img_data = image
else:
self.img_data = None
self.cache = cache
self.cacheindex = cacheindex
def wrap(self, width, height):
return self.img_width, self.img_height
def drawOn(self, canv, x, y, _sW=0):
if _sW > 0 and hasattr(self, 'hAlign'):
a = self.hAlign
if a in ('CENTER', 'CENTRE', TA_CENTER):
x += 0.5*_sW
elif a in ('RIGHT', TA_RIGHT):
x += _sW
elif a not in ('LEFT', TA_LEFT):
raise ValueError("Bad hAlign value " + str(a))
canv.saveState()
if self.img_data is not None:
img = self.img_data
else:
img = self.cache[self.cacheindex]
if isinstance(img, PdfDict):
xscale = self.img_width / img.BBox[2]
yscale = self.img_height / img.BBox[3]
canv.translate(x, y)
canv.scale(xscale, yscale)
canv.doForm(makerl(canv, img))
else:
canv.drawImage(img, x, y, self.img_width, self.img_height)
canv.restoreState()
class PdfImageCache(object):
"""
Saves matplotlib figures to a temporary multi-page PDF file using the 'savefig'
method. When closed the images are extracted and saved to the attribute 'cache'.
The temporary PDF file is then deleted. The 'savefig' returns a PdfImage object
with a pointer to the 'cache' list and an index for the figure. Use of this
cache reduces duplicated resources in the reportlab generated PDF file.
Use is similar to matplotlib's PdfPages object. When not used as a context
manager, the 'close()' method must be explictly called before the reportlab
document is built.
"""
def __init__(self):
self.pdftempfile = '_temporary_pdf_image_cache_.pdf'
self.pdf = PdfPages(self.pdftempfile)
self.cache = []
self.count = 0
def __enter__(self):
return self
def __exit__(self, *args):
self.close()
def close(self, *args):
self.pdf.close()
pages = PdfReader(self.pdftempfile).pages
pages = [pagexobj(x) for x in pages]
self.cache.extend(pages)
os.remove(self.pdftempfile)
def savefig(self, fig, width=200, height=200):
self.pdf.savefig(fig)
index = self.count
self.count += 1
return PdfImage(width=width, height=height, cache=self.cache, cacheindex=index)
def make_report(outfn, nfig=5):
"""
Makes a dummy report with nfig matplotlib plots.
"""
doc = SimpleDocTemplate(outfn)
style = styles["Normal"]
story = [Spacer(0, inch)]
for j in range(nfig):
fig = plt.figure(figsize=(4, 3))
plt.plot([1, 2, 3, 4], [1, 4, 9, 26])
plt.ylabel('some numbers')
plt.title('My Figure %i' % (j+1))
img = PdfImage(fig, width=400, height=400)
plt.close()
for i in range(10):
bogustext = ("Paragraph number %s. " % i)
p = Paragraph(bogustext, style)
story.append(p)
story.append(Spacer(1, 0.2*inch))
story.append(img)
for i in range(10):
bogustext = ("Paragraph number %s. " % i)
p = Paragraph(bogustext, style)
story.append(p)
story.append(Spacer(1, 0.2*inch))
doc.build(story)
def make_report_cached_figs(outfn, nfig=5):
"""
Makes a dummy report with nfig matplotlib plots using PdfImageCache
to reduce PDF file size.
"""
doc = SimpleDocTemplate(outfn)
style = styles["Normal"]
story = [Spacer(0, inch)]
with PdfImageCache() as pdfcache:
for j in range(nfig):
fig = plt.figure(figsize=(4, 3))
plt.plot([1, 2, 3, 4], [1, 4, 9, 26])
plt.ylabel('some numbers')
plt.title('My Figure %i' % (j+1))
img = pdfcache.savefig(fig, width=400, height=400)
plt.close()
for i in range(10):
bogustext = ("Paragraph number %s. " % i)
p = Paragraph(bogustext, style)
story.append(p)
story.append(Spacer(1, 0.2*inch))
story.append(img)
for i in range(10):
bogustext = ("Paragraph number %s. " % i)
p = Paragraph(bogustext, style)
story.append(p)
story.append(Spacer(1, 0.2*inch))
doc.build(story)
make_report("hello_pdf.pdf", 50)
make_report_cached_figs("hello_pdf_cached_figs.pdf", 50)
由于matplotlib的PdfPages仅将文件路径作为输入，因此PdfImageCache对象将多页PDF写入临时文件。试着在内存中做这件事需要做更多的工作。
Python 3的解决方案，并将matplotlib图形嵌入为矢量图像（无光栅化）
import matplotlib.pyplot as plt
from io import BytesIO
from reportlab.pdfgen import canvas
from reportlab.graphics import renderPDF
from svglib.svglib import svg2rlg
fig = plt.figure(figsize=(4, 3))
plt.plot([1,2,3,4])
plt.ylabel('some numbers')
imgdata = BytesIO()
fig.savefig(imgdata, format='svg')
imgdata.seek(0) # rewind the data
drawing=svg2rlg(imgdata)
c = canvas.Canvas('test2.pdf')
renderPDF.draw(drawing,c, 10, 40)
c.drawString(10, 300, "So nice it works")
c.showPage()
c.save()
svglib可从conda-forge获得。
基于上面非常有价值的答案，并在许多其他问题和答案的帮助下，我最近在网上放了一个小的github repo，这实际上有助于用matplotlib和reportlab创建文档。我叫它autobasedoc。
它取决于svglib，matplotlib，reportlab当然是pdfrw。
上面的问题表明，该人希望生成具有大量matplotlib数字的漂亮文档。
问题是，是否有matplotlib可流动，最接近的答案可能是：是的，有一个，请看这里有关如何使用matplotlib函数返回一个reportlab可流动（使用autobasedt autoplt模块提供的装饰器）：
from autobasedoc import ap
@ap.autoPdfImg
def my_plot1(canvaswidth=5): #[inch]
fig, ax = ap.plt.subplots(figsize=(canvaswidth,canvaswidth))
fig.suptitle(title, fontproperties=fontprop)
x=[1,2,3,4,5,6,7,8]
y=[1,6,8,3,9,3,4,2]
ax.plot(x,y,label="legendlabel")
nrow, ncol = 1, 1
handles, labels = ax.get_legend_handles_labels()
leg_fig = ap.plt.figure(figsize=(canvaswidth, 0.2*nrow))
ax.legend(handles, labels, #labels = tuple(bar_names)
ncol=ncol, mode=None,
borderaxespad=0.,
loc='best', # the location of the legend handles
handleheight=None, # the height of the legend handles
#fontsize=9, # prop beats fontsize
markerscale=None,
#frameon=False,
prop=fontprop,
fancybox=True
)
return fig
content.append(my_plot1())