Пример #1
0
    def test_diagram_via_object_pdf(self):
        """Construct and draw PDF using object approach."""
        genbank_entry = self.record
        gdd = Diagram('Test Diagram')

        gdt1 = Track('CDS features',
                     greytrack=True,
                     scale_largetick_interval=1e4,
                     scale_smalltick_interval=1e3,
                     greytrack_labels=10,
                     greytrack_font_color="red",
                     scale_format="SInt")
        gdt2 = Track('gene features',
                     greytrack=1,
                     scale_largetick_interval=1e4)

        # First add some feature sets:
        gdfsA = FeatureSet(name='CDS backgrounds')
        gdfsB = FeatureSet(name='gene background')

        gdfs1 = FeatureSet(name='CDS features')
        gdfs2 = FeatureSet(name='gene features')
        gdfs3 = FeatureSet(name='misc_features')
        gdfs4 = FeatureSet(name='repeat regions')

        prev_gene = None
        cds_count = 0
        for feature in genbank_entry.features:
            if feature.type == 'CDS':
                cds_count += 1
                if prev_gene:
                    # Assuming it goes with this CDS!
                    if cds_count % 2 == 0:
                        dark, light = colors.peru, colors.tan
                    else:
                        dark, light = colors.burlywood, colors.bisque
                    # Background for CDS,
                    a = gdfsA.add_feature(SeqFeature(
                        FeatureLocation(feature.location.start,
                                        feature.location.end,
                                        strand=0)),
                                          color=dark)
                    # Background for gene,
                    b = gdfsB.add_feature(SeqFeature(
                        FeatureLocation(prev_gene.location.start,
                                        prev_gene.location.end,
                                        strand=0)),
                                          color=dark)
                    # Cross link,
                    gdd.cross_track_links.append(CrossLink(a, b, light, dark))
                    prev_gene = None
            if feature.type == 'gene':
                prev_gene = feature

        # Some cross links on the same linear diagram fragment,
        f, c = fill_and_border(colors.red)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(2220, 2230)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(2200, 2210)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c))

        f, c = fill_and_border(colors.blue)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(2150, 2200)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(2220, 2290)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c, flip=True))

        f, c = fill_and_border(colors.green)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(2250, 2560)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(2300, 2860)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c))

        # Some cross links where both parts are saddling the linear diagram fragment boundary,
        f, c = fill_and_border(colors.red)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(3155, 3250)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(3130, 3300)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c))
        # Nestled within that (drawn on top),
        f, c = fill_and_border(colors.blue)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(3160, 3275)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(3180, 3225)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c, flip=True))

        # Some cross links where two features are on either side of the linear diagram fragment boundary,
        f, c = fill_and_border(colors.green)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(6450, 6550)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(6265, 6365)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(CrossLink(a, b, color=f, border=c))
        f, c = fill_and_border(colors.gold)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(6265, 6365)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(6450, 6550)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(CrossLink(a, b, color=f, border=c))
        f, c = fill_and_border(colors.red)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(6275, 6375)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(6430, 6530)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(
            CrossLink(a, b, color=f, border=c, flip=True))
        f, c = fill_and_border(colors.blue)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(6430, 6530)),
                              color=f,
                              border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(6275, 6375)),
                              color=f,
                              border=c)
        gdd.cross_track_links.append(
            CrossLink(a, b, color=f, border=c, flip=True))

        cds_count = 0
        for feature in genbank_entry.features:
            if feature.type == 'CDS':
                cds_count += 1
                if cds_count % 2 == 0:
                    gdfs1.add_feature(feature,
                                      color=colors.pink,
                                      sigil="ARROW")
                else:
                    gdfs1.add_feature(feature, color=colors.red, sigil="ARROW")

            if feature.type == 'gene':
                # Note we set the colour of ALL the genes later on as a test,
                gdfs2.add_feature(feature, sigil="ARROW")

            if feature.type == 'misc_feature':
                gdfs3.add_feature(feature, color=colors.orange)

            if feature.type == 'repeat_region':
                gdfs4.add_feature(feature, color=colors.purple)

        # gdd.cross_track_links = gdd.cross_track_links[:1]

        gdfs1.set_all_features('label', 1)
        gdfs2.set_all_features('label', 1)
        gdfs3.set_all_features('label', 1)
        gdfs4.set_all_features('label', 1)

        gdfs3.set_all_features('hide', 0)
        gdfs4.set_all_features('hide', 0)

        # gdfs1.set_all_features('color', colors.red)
        gdfs2.set_all_features('color', colors.blue)

        gdt1.add_set(gdfsA)  # Before CDS so under them!
        gdt1.add_set(gdfs1)

        gdt2.add_set(gdfsB)  # Before genes so under them!
        gdt2.add_set(gdfs2)

        gdt3 = Track('misc features and repeats',
                     greytrack=1,
                     scale_largetick_interval=1e4)
        gdt3.add_set(gdfs3)
        gdt3.add_set(gdfs4)

        # Now add some graph sets:

        # Use a fairly large step so we can easily tell the difference
        # between the bar and line graphs.
        step = len(genbank_entry) // 200
        gdgs1 = GraphSet('GC skew')

        graphdata1 = apply_to_window(genbank_entry.seq, step, calc_gc_skew,
                                     step)
        gdgs1.new_graph(graphdata1,
                        'GC Skew',
                        style='bar',
                        color=colors.violet,
                        altcolor=colors.purple)

        gdt4 = Track('GC Skew (bar)',
                     height=1.94,
                     greytrack=1,
                     scale_largetick_interval=1e4)
        gdt4.add_set(gdgs1)

        gdgs2 = GraphSet('GC and AT Content')
        gdgs2.new_graph(apply_to_window(genbank_entry.seq, step,
                                        calc_gc_content, step),
                        'GC content',
                        style='line',
                        color=colors.lightgreen,
                        altcolor=colors.darkseagreen)

        gdgs2.new_graph(apply_to_window(genbank_entry.seq, step,
                                        calc_at_content, step),
                        'AT content',
                        style='line',
                        color=colors.orange,
                        altcolor=colors.red)

        gdt5 = Track('GC Content(green line), AT Content(red line)',
                     height=1.94,
                     greytrack=1,
                     scale_largetick_interval=1e4)
        gdt5.add_set(gdgs2)

        gdgs3 = GraphSet('Di-nucleotide count')
        step = len(genbank_entry) // 400  # smaller step
        gdgs3.new_graph(apply_to_window(genbank_entry.seq, step,
                                        calc_dinucleotide_counts, step),
                        'Di-nucleotide count',
                        style='heat',
                        color=colors.red,
                        altcolor=colors.orange)
        gdt6 = Track('Di-nucleotide count',
                     height=0.5,
                     greytrack=False,
                     scale=False)
        gdt6.add_set(gdgs3)

        # Add the tracks (from both features and graphs)
        # Leave some white space in the middle/bottom
        gdd.add_track(gdt4, 3)  # GC skew
        gdd.add_track(gdt5, 4)  # GC and AT content
        gdd.add_track(gdt1, 5)  # CDS features
        gdd.add_track(gdt2, 6)  # Gene features
        gdd.add_track(gdt3, 7)  # Misc features and repeat feature
        gdd.add_track(gdt6, 8)  # Feature depth

        # Finally draw it in both formats, and full view and partial
        gdd.draw(format='circular',
                 orientation='landscape',
                 tracklines=0,
                 pagesize='A0')
        output_filename = os.path.join('Graphics', 'GD_by_obj_circular.pdf')
        gdd.write(output_filename, 'PDF')

        gdd.circular = False
        gdd.draw(format='circular',
                 orientation='landscape',
                 tracklines=0,
                 pagesize='A0',
                 start=3000,
                 end=6300)
        output_filename = os.path.join('Graphics',
                                       'GD_by_obj_frag_circular.pdf')
        gdd.write(output_filename, 'PDF')

        gdd.draw(format='linear',
                 orientation='landscape',
                 tracklines=0,
                 pagesize='A0',
                 fragments=3)
        output_filename = os.path.join('Graphics', 'GD_by_obj_linear.pdf')
        gdd.write(output_filename, 'PDF')

        gdd.set_all_tracks("greytrack_labels", 2)
        gdd.draw(format='linear',
                 orientation='landscape',
                 tracklines=0,
                 pagesize=(30 * cm, 10 * cm),
                 fragments=1,
                 start=3000,
                 end=6300)
        output_filename = os.path.join('Graphics', 'GD_by_obj_frag_linear.pdf')
        gdd.write(output_filename, 'PDF')
Пример #2
0
    def test_diagram_via_object_pdf(self):
        """Construct and draw PDF using object approach."""
        genbank_entry = self.record
        gdd = Diagram('Test Diagram')

        #First add some feature sets:
        gdfs1 = FeatureSet(name='CDS features')
        gdfs2 = FeatureSet(name='gene features')
        gdfs3 = FeatureSet(name='misc_features')
        gdfs4 = FeatureSet(name='repeat regions')

        cds_count = 0
        for feature in genbank_entry.features:
            if feature.type == 'CDS':
                cds_count += 1
                if cds_count % 2 == 0:
                    gdfs1.add_feature(feature, color=colors.pink)
                else:
                    gdfs1.add_feature(feature, color=colors.red)

            if feature.type == 'gene':
                gdfs2.add_feature(feature)

            if feature.type == 'misc_feature':
                gdfs3.add_feature(feature, color=colors.orange)

            if feature.type == 'repeat_region':
                gdfs4.add_feature(feature, color=colors.purple)


        gdfs1.set_all_features('label', 1)
        gdfs2.set_all_features('label', 1)
        gdfs3.set_all_features('label', 1)
        gdfs4.set_all_features('label', 1)

        gdfs3.set_all_features('hide', 0)
        gdfs4.set_all_features('hide', 0)

        #gdfs1.set_all_features('color', colors.red)
        gdfs2.set_all_features('color', colors.blue)

        gdt1 = Track('CDS features', greytrack=True,
                     scale_largetick_interval=1e4,
                     scale_smalltick_interval=1e3,
                     greytrack_labels=10,
                     greytrack_font_color="red",
                     scale_format = "SInt")
        gdt1.add_set(gdfs1)

        gdt2 = Track('gene features', greytrack=1,
                   scale_largetick_interval=1e4)
        gdt2.add_set(gdfs2)
                
        gdt3 = Track('misc features and repeats', greytrack=1,
                   scale_largetick_interval=1e4)
        gdt3.add_set(gdfs3)
        gdt3.add_set(gdfs4)

        #Now add some graph sets:

        #Use a fairly large step so we can easily tell the difference
        #between the bar and line graphs.
        step = len(genbank_entry)/200
        gdgs1 = GraphSet('GC skew')
        
        graphdata1 = apply_to_window(genbank_entry.seq, step, calc_gc_skew, step)
        gdgs1.new_graph(graphdata1, 'GC Skew', style='bar',
                color=colors.violet,
                altcolor=colors.purple)
        
        gdt4 = Track(\
                'GC Skew (bar)',
                height=1.94, greytrack=1,
                scale_largetick_interval=1e4)
        gdt4.add_set(gdgs1)


        gdgs2 = GraphSet('GC and AT Content')
        gdgs2.new_graph(apply_to_window(genbank_entry.seq, step, calc_gc_content, step),
                        'GC content', style='line', 
                        color=colors.lightgreen,
                        altcolor=colors.darkseagreen)

        gdgs2.new_graph(apply_to_window(genbank_entry.seq, step, calc_at_content, step),
                        'AT content', style='line', 
                        color=colors.orange,
                        altcolor=colors.red)    

        gdt5 = Track(\
                'GC Content(green line), AT Content(red line)',
                height=1.94, greytrack=1,
                scale_largetick_interval=1e4)
        gdt5.add_set(gdgs2)

        gdgs3 = GraphSet('Di-nucleotide count')
        step = len(genbank_entry)/400 #smaller step
        gdgs3.new_graph(apply_to_window(genbank_entry.seq, step, calc_dinucleotide_counts, step),
                        'Di-nucleotide count', style='heat', 
                        color=colors.red, altcolor=colors.orange)
        gdt6 = Track('Di-nucleotide count', height=0.5, greytrack=False, scale=False)
        gdt6.add_set(gdgs3)

        #Add the tracks (from both features and graphs)
        #Leave some white space in the middle
        gdd.add_track(gdt4, 3) # GC skew
        gdd.add_track(gdt5, 4) # GC and AT content
        gdd.add_track(gdt1, 5) # CDS features
        gdd.add_track(gdt2, 6) # Gene features
        gdd.add_track(gdt3, 7) # Misc features and repeat feature
        gdd.add_track(gdt6, 8) # Feature depth

        #Finally draw it in both formats,
        gdd.draw(format='circular', orientation='landscape',
             tracklines=0, pagesize='A0', circular=True)
        output_filename = os.path.join('Graphics', 'GD_by_obj_circular.pdf')
        gdd.write(output_filename, 'PDF')

        gdd.draw(format='linear', orientation='landscape',
             tracklines=0, pagesize='A0', fragments=3)
        output_filename = os.path.join('Graphics', 'GD_by_obj_linear.pdf')
        gdd.write(output_filename, 'PDF')
Пример #3
0
    def test_diagram_via_object_pdf(self):
        """Construct and draw PDF using object approach."""
        genbank_entry = self.record
        gdd = Diagram('Test Diagram')

        gdt1 = Track('CDS features', greytrack=True,
                     scale_largetick_interval=1e4,
                     scale_smalltick_interval=1e3,
                     greytrack_labels=10,
                     greytrack_font_color="red",
                     scale_format = "SInt")
        gdt2 = Track('gene features', greytrack=1,
                   scale_largetick_interval=1e4)

        #First add some feature sets:
        gdfsA = FeatureSet(name='CDS backgrounds')
        gdfsB = FeatureSet(name='gene background')

        gdfs1 = FeatureSet(name='CDS features')
        gdfs2 = FeatureSet(name='gene features')
        gdfs3 = FeatureSet(name='misc_features')
        gdfs4 = FeatureSet(name='repeat regions')

        prev_gene = None
        cds_count = 0
        for feature in genbank_entry.features:
            if feature.type == 'CDS':
                cds_count += 1
                if prev_gene:
                    #Assuming it goes with this CDS!
                    if cds_count % 2 == 0:
                        dark, light = colors.peru, colors.tan
                    else:
                        dark, light = colors.burlywood, colors.bisque
                    #Background for CDS,
                    a = gdfsA.add_feature(SeqFeature(FeatureLocation(feature.location.start, feature.location.end, strand=0)),
                                         color=dark)
                    #Background for gene,
                    b = gdfsB.add_feature(SeqFeature(FeatureLocation(prev_gene.location.start, prev_gene.location.end, strand=0)),
                                          color=dark)
                    #Cross link,
                    gdd.cross_track_links.append(CrossLink(a, b, light, dark))
                    prev_gene = None
            if feature.type == 'gene':
                prev_gene = feature

        #Some cross links on the same linear diagram fragment,
        f, c = fill_and_border(colors.red)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(2220,2230)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(2200,2210)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c))

        f, c = fill_and_border(colors.blue)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(2150,2200)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(2220,2290)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c, flip=True))

        f, c = fill_and_border(colors.green)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(2250,2560)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(2300,2860)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c))

        #Some cross links where both parts are saddling the linear diagram fragment boundary,
        f, c = fill_and_border(colors.red)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(3155,3250)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(3130,3300)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c))
        #Nestled within that (drawn on top),
        f, c = fill_and_border(colors.blue)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(3160,3275)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(3180,3225)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, f, c, flip=True))

        #Some cross links where two features are on either side of the linear diagram fragment boundary,
        f, c = fill_and_border(colors.green)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(6450,6550)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(6265,6365)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, color=f, border=c))
        f, c = fill_and_border(colors.gold)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(6265,6365)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(6450,6550)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, color=f, border=c))
        f, c = fill_and_border(colors.red)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(6275,6375)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(6430,6530)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, color=f, border=c, flip=True))
        f, c = fill_and_border(colors.blue)
        a = gdfsA.add_feature(SeqFeature(FeatureLocation(6430,6530)), color=f, border=c)
        b = gdfsB.add_feature(SeqFeature(FeatureLocation(6275,6375)), color=f, border=c)
        gdd.cross_track_links.append(CrossLink(a, b, color=f, border=c, flip=True))

        cds_count = 0
        for feature in genbank_entry.features:
            if feature.type == 'CDS':
                cds_count += 1
                if cds_count % 2 == 0:
                    gdfs1.add_feature(feature, color=colors.pink, sigil="ARROW")
                else:
                    gdfs1.add_feature(feature, color=colors.red, sigil="ARROW")

            if feature.type == 'gene':
                #Note we set the colour of ALL the genes later on as a test,
                gdfs2.add_feature(feature, sigil="ARROW")

            if feature.type == 'misc_feature':
                gdfs3.add_feature(feature, color=colors.orange)

            if feature.type == 'repeat_region':
                gdfs4.add_feature(feature, color=colors.purple)

        #gdd.cross_track_links = gdd.cross_track_links[:1]

        gdfs1.set_all_features('label', 1)
        gdfs2.set_all_features('label', 1)
        gdfs3.set_all_features('label', 1)
        gdfs4.set_all_features('label', 1)

        gdfs3.set_all_features('hide', 0)
        gdfs4.set_all_features('hide', 0)

        #gdfs1.set_all_features('color', colors.red)
        gdfs2.set_all_features('color', colors.blue)

        gdt1.add_set(gdfsA)  # Before CDS so under them!
        gdt1.add_set(gdfs1)

        gdt2.add_set(gdfsB)  # Before genes so under them!
        gdt2.add_set(gdfs2)

        gdt3 = Track('misc features and repeats', greytrack=1,
                   scale_largetick_interval=1e4)
        gdt3.add_set(gdfs3)
        gdt3.add_set(gdfs4)

        #Now add some graph sets:

        #Use a fairly large step so we can easily tell the difference
        #between the bar and line graphs.
        step = len(genbank_entry)//200
        gdgs1 = GraphSet('GC skew')

        graphdata1 = apply_to_window(genbank_entry.seq, step, calc_gc_skew, step)
        gdgs1.new_graph(graphdata1, 'GC Skew', style='bar',
                color=colors.violet,
                altcolor=colors.purple)

        gdt4 = Track(
                'GC Skew (bar)',
                height=1.94, greytrack=1,
                scale_largetick_interval=1e4)
        gdt4.add_set(gdgs1)

        gdgs2 = GraphSet('GC and AT Content')
        gdgs2.new_graph(apply_to_window(genbank_entry.seq, step, calc_gc_content, step),
                        'GC content', style='line',
                        color=colors.lightgreen,
                        altcolor=colors.darkseagreen)

        gdgs2.new_graph(apply_to_window(genbank_entry.seq, step, calc_at_content, step),
                        'AT content', style='line',
                        color=colors.orange,
                        altcolor=colors.red)

        gdt5 = Track(
                'GC Content(green line), AT Content(red line)',
                height=1.94, greytrack=1,
                scale_largetick_interval=1e4)
        gdt5.add_set(gdgs2)

        gdgs3 = GraphSet('Di-nucleotide count')
        step = len(genbank_entry) // 400  # smaller step
        gdgs3.new_graph(apply_to_window(genbank_entry.seq, step, calc_dinucleotide_counts, step),
                        'Di-nucleotide count', style='heat',
                        color=colors.red, altcolor=colors.orange)
        gdt6 = Track('Di-nucleotide count', height=0.5, greytrack=False, scale=False)
        gdt6.add_set(gdgs3)

        #Add the tracks (from both features and graphs)
        #Leave some white space in the middle/bottom
        gdd.add_track(gdt4, 3)  # GC skew
        gdd.add_track(gdt5, 4)  # GC and AT content
        gdd.add_track(gdt1, 5)  # CDS features
        gdd.add_track(gdt2, 6)  # Gene features
        gdd.add_track(gdt3, 7)  # Misc features and repeat feature
        gdd.add_track(gdt6, 8)  # Feature depth

        #Finally draw it in both formats, and full view and partial
        gdd.draw(format='circular', orientation='landscape',
             tracklines=0, pagesize='A0')
        output_filename = os.path.join('Graphics', 'GD_by_obj_circular.pdf')
        gdd.write(output_filename, 'PDF')

        gdd.circular=False
        gdd.draw(format='circular', orientation='landscape',
             tracklines=0, pagesize='A0', start=3000, end=6300)
        output_filename = os.path.join('Graphics', 'GD_by_obj_frag_circular.pdf')
        gdd.write(output_filename, 'PDF')

        gdd.draw(format='linear', orientation='landscape',
             tracklines=0, pagesize='A0', fragments=3)
        output_filename = os.path.join('Graphics', 'GD_by_obj_linear.pdf')
        gdd.write(output_filename, 'PDF')

        gdd.set_all_tracks("greytrack_labels", 2)
        gdd.draw(format='linear', orientation='landscape',
             tracklines=0, pagesize=(30*cm,10*cm), fragments=1,
             start=3000, end=6300)
        output_filename = os.path.join('Graphics', 'GD_by_obj_frag_linear.pdf')
        gdd.write(output_filename, 'PDF')
    def test_diagram_via_object_pdf(self):
        """Construct and draw PDF using object approach."""
        genbank_entry = self.record
        gdd = Diagram('Test Diagram')

        #First add some feature sets:
        gdfs1 = FeatureSet(name='CDS features')
        gdfs2 = FeatureSet(name='gene features')
        gdfs3 = FeatureSet(name='misc_features')
        gdfs4 = FeatureSet(name='repeat regions')

        cds_count = 0
        for feature in genbank_entry.features:
            if feature.type == 'CDS':
                cds_count += 1
                if cds_count % 2 == 0:
                    gdfs1.add_feature(feature, color=colors.pink)
                else:
                    gdfs1.add_feature(feature, color=colors.red)

            if feature.type == 'gene':
                gdfs2.add_feature(feature)

            if feature.type == 'misc_feature':
                gdfs3.add_feature(feature, color=colors.orange)

            if feature.type == 'repeat_region':
                gdfs4.add_feature(feature, color=colors.purple)

        gdfs1.set_all_features('label', 1)
        gdfs2.set_all_features('label', 1)
        gdfs3.set_all_features('label', 1)
        gdfs4.set_all_features('label', 1)

        gdfs3.set_all_features('hide', 0)
        gdfs4.set_all_features('hide', 0)

        #gdfs1.set_all_features('color', colors.red)
        gdfs2.set_all_features('color', colors.blue)

        gdt1 = Track('CDS features',
                     greytrack=True,
                     scale_largetick_interval=1e4,
                     scale_smalltick_interval=1e3,
                     greytrack_labels=10,
                     greytrack_font_color="red",
                     scale_format="SInt")
        gdt1.add_set(gdfs1)

        gdt2 = Track('gene features',
                     greytrack=1,
                     scale_largetick_interval=1e4)
        gdt2.add_set(gdfs2)

        gdt3 = Track('misc features and repeats',
                     greytrack=1,
                     scale_largetick_interval=1e4)
        gdt3.add_set(gdfs3)
        gdt3.add_set(gdfs4)

        #Now add some graph sets:

        #Use a fairly large step so we can easily tell the difference
        #between the bar and line graphs.
        step = len(genbank_entry) // 200
        gdgs1 = GraphSet('GC skew')

        graphdata1 = apply_to_window(genbank_entry.seq, step, calc_gc_skew,
                                     step)
        gdgs1.new_graph(graphdata1,
                        'GC Skew',
                        style='bar',
                        color=colors.violet,
                        altcolor=colors.purple)

        gdt4 = Track(\
                'GC Skew (bar)',
                height=1.94, greytrack=1,
                scale_largetick_interval=1e4)
        gdt4.add_set(gdgs1)

        gdgs2 = GraphSet('GC and AT Content')
        gdgs2.new_graph(apply_to_window(genbank_entry.seq, step,
                                        calc_gc_content, step),
                        'GC content',
                        style='line',
                        color=colors.lightgreen,
                        altcolor=colors.darkseagreen)

        gdgs2.new_graph(apply_to_window(genbank_entry.seq, step,
                                        calc_at_content, step),
                        'AT content',
                        style='line',
                        color=colors.orange,
                        altcolor=colors.red)

        gdt5 = Track(\
                'GC Content(green line), AT Content(red line)',
                height=1.94, greytrack=1,
                scale_largetick_interval=1e4)
        gdt5.add_set(gdgs2)

        gdgs3 = GraphSet('Di-nucleotide count')
        step = len(genbank_entry) // 400  #smaller step
        gdgs3.new_graph(apply_to_window(genbank_entry.seq, step,
                                        calc_dinucleotide_counts, step),
                        'Di-nucleotide count',
                        style='heat',
                        color=colors.red,
                        altcolor=colors.orange)
        gdt6 = Track('Di-nucleotide count',
                     height=0.5,
                     greytrack=False,
                     scale=False)
        gdt6.add_set(gdgs3)

        #Add the tracks (from both features and graphs)
        #Leave some white space in the middle
        gdd.add_track(gdt4, 3)  # GC skew
        gdd.add_track(gdt5, 4)  # GC and AT content
        gdd.add_track(gdt1, 5)  # CDS features
        gdd.add_track(gdt2, 6)  # Gene features
        gdd.add_track(gdt3, 7)  # Misc features and repeat feature
        gdd.add_track(gdt6, 8)  # Feature depth

        #Finally draw it in both formats,
        gdd.draw(format='circular',
                 orientation='landscape',
                 tracklines=0,
                 pagesize='A0',
                 circular=True)
        output_filename = os.path.join('Graphics', 'GD_by_obj_circular.pdf')
        gdd.write(output_filename, 'PDF')

        gdd.draw(format='linear',
                 orientation='landscape',
                 tracklines=0,
                 pagesize='A0',
                 fragments=3)
        output_filename = os.path.join('Graphics', 'GD_by_obj_linear.pdf')
        gdd.write(output_filename, 'PDF')