Exemplo n.º 1
0
    def __init__(self, fig, root, datafile, bedfile, layoutfile,
                 switch=None, tree=None, chr_label=True, pad=.04):

        w, h = fig.get_figwidth(), fig.get_figheight()
        bed = Bed(bedfile)
        order = bed.order
        bf = BlockFile(datafile)
        lo = Layout(layoutfile)
        switch = DictFile(switch, delimiter="\t") if switch else None

        exts = []
        for i in xrange(bf.ncols):
            ext = bf.get_extent(i, order)
            exts.append(ext)

        maxspan = max(exts, key=lambda x: x[-1])[-1]
        scale = maxspan / .65

        self.gg = gg = {}
        self.rr = []
        ymids = []
        vpad = .012 * w / h
        for i in xrange(bf.ncols):
            ext = exts[i]
            r = Region(root, ext, lo[i], bed, scale, switch, chr_label=chr_label, vpad=vpad)
            self.rr.append(r)
            # Use tid and accn to store gene positions
            gg.update(dict(((i, k), v) for k, v in r.gg.items()))
            ymids.append(r.y)

        for i, j in lo.edges:
            for ga, gb, h in bf.iter_pairs(i, j):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, fc="gainsboro", lw=0, alpha=1)

            for ga, gb, h in bf.iter_pairs(i, j, highlight=True):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, alpha=1, highlight=h, zorder=2)

        if tree:
            from jcvi.graphics.tree import draw_tree, read_trees

            trees = read_trees(tree)
            ntrees = len(trees)
            logging.debug("A total of {0} trees imported.".format(ntrees))
            xiv = 1. / ntrees
            yiv = .3
            xstart = 0
            ystart = min(ymids) - .4
            for i in xrange(ntrees):
                ax = fig.add_axes([xstart, ystart, xiv, yiv])
                label, outgroup, tx = trees[i]
                draw_tree(ax, tx, outgroup=outgroup, rmargin=.4)
                xstart += xiv
                RoundLabel(ax, .5, .3, label, fill=True, fc="lavender", color="r")
Exemplo n.º 2
0
    def __init__(self, fig, root, datafile, bedfile, layoutfile,
                 switch=None, tree=None, extra_features=None,
                 chr_label=True, loc_label=True, pad=.05, vpad=.015,
                 scalebar=False):

        w, h = fig.get_figwidth(), fig.get_figheight()
        bed = Bed(bedfile)
        order = bed.order
        bf = BlockFile(datafile)
        self.layout = lo = Layout(layoutfile)
        switch = DictFile(switch, delimiter="\t") if switch else None
        if extra_features:
            extra_features = Bed(extra_features)

        exts = []
        extras = []
        for i in xrange(bf.ncols):
            ext = bf.get_extent(i, order)
            exts.append(ext)
            if extra_features:
                start, end, si, ei, chr, orientation, span = ext
                start, end = start.start, end.end  # start, end coordinates
                ef = list(extra_features.extract(chr, start, end))

                # Pruning removes minor features with < 0.1% of the region
                ef_pruned = [x for x in ef if x.span >= span / 1000]
                print >> sys.stderr, "Extracted {0} features "\
                        "({1} after pruning)".format(len(ef), len(ef_pruned))
                extras.append(ef_pruned)

        maxspan = max(exts, key=lambda x: x[-1])[-1]
        scale = maxspan / .65

        self.gg = gg = {}
        self.rr = []
        ymids = []
        #vpad = .012 * w / h
        for i in xrange(bf.ncols):
            ext = exts[i]
            ef = extras[i] if extras else None
            r = Region(root, ext, lo[i], bed, scale, switch,
                       chr_label=chr_label, loc_label=loc_label,
                       vpad=vpad, extra_features=ef)
            self.rr.append(r)
            # Use tid and accn to store gene positions
            gg.update(dict(((i, k), v) for k, v in r.gg.items()))
            ymids.append(r.y)

        for i, j in lo.edges:
            for ga, gb, h in bf.iter_pairs(i, j):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, fc="gainsboro", lw=0, alpha=1)

            for ga, gb, h in bf.iter_pairs(i, j, highlight=True):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, alpha=1, highlight=h, zorder=2)

        if scalebar:
            print >> sys.stderr, "Build scalebar (scale={})".format(scale)
            # Find the best length of the scalebar
            ar = [1, 2, 5]
            candidates = [1000 * x for x in ar] + [10000 * x for x in ar] + \
                         [100000 * x for x in ar]
            # Find the one that's close to an optimal canvas size
            dists = [(abs(x / scale - .12), x) for x in candidates]
            dist, candidate = min(dists)
            dist = candidate / scale
            x, y, yp = .2, .96, .005
            a, b = x - dist / 2, x + dist / 2
            lsg = "lightslategrey"
            root.plot([a, a], [y - yp, y + yp], "-", lw=2, color=lsg)
            root.plot([b, b], [y - yp, y + yp], "-", lw=2, color=lsg)
            root.plot([a, b], [y, y], "-", lw=2, color=lsg)
            root.text(x, y + .02, human_size(candidate, precision=0),
                      ha="center", va="center")

        if tree:
            from jcvi.graphics.tree import draw_tree, read_trees

            trees = read_trees(tree)
            ntrees = len(trees)
            logging.debug("A total of {0} trees imported.".format(ntrees))
            xiv = 1. / ntrees
            yiv = .3
            xstart = 0
            ystart = min(ymids) - .4
            for i in xrange(ntrees):
                ax = fig.add_axes([xstart, ystart, xiv, yiv])
                label, outgroup, tx = trees[i]
                draw_tree(ax, tx, outgroup=outgroup, rmargin=.4, leaffont=11)
                xstart += xiv
                RoundLabel(ax, .5, .3, label, fill=True, fc="lavender", color="r")
Exemplo n.º 3
0
    def __init__(
        self,
        fig,
        root,
        datafile,
        bedfile,
        layoutfile,
        switch=None,
        tree=None,
        extra_features=None,
        chr_label=True,
        loc_label=True,
        genelabelsize=0,
        pad=0.05,
        vpad=0.015,
        scalebar=False,
        shadestyle="curve",
        glyphstyle="arrow",
        glyphcolor: BasePalette = OrientationPalette(),
    ):
        _, h = fig.get_figwidth(), fig.get_figheight()
        bed = Bed(bedfile)
        order = bed.order
        bf = BlockFile(datafile)
        self.layout = lo = Layout(layoutfile)
        switch = DictFile(switch, delimiter="\t") if switch else None
        if extra_features:
            extra_features = Bed(extra_features)

        exts = []
        extras = []
        for i in range(bf.ncols):
            ext = bf.get_extent(i, order)
            exts.append(ext)
            if extra_features:
                start, end, si, ei, chr, orientation, span = ext
                start, end = start.start, end.end  # start, end coordinates
                ef = list(extra_features.extract(chr, start, end))

                # Pruning removes minor features with < 0.1% of the region
                ef_pruned = [x for x in ef if x.span >= span / 1000]
                print(
                    "Extracted {0} features "
                    "({1} after pruning)".format(len(ef), len(ef_pruned)),
                    file=sys.stderr,
                )
                extras.append(ef_pruned)

        maxspan = max(exts, key=lambda x: x[-1])[-1]
        scale = maxspan / 0.65

        self.gg = gg = {}
        self.rr = []
        ymids = []
        glyphcolor = (
            OrientationPalette()
            if glyphcolor == "orientation"
            else OrthoGroupPalette(bf.grouper())
        )
        for i in range(bf.ncols):
            ext = exts[i]
            ef = extras[i] if extras else None
            r = Region(
                root,
                ext,
                lo[i],
                bed,
                scale,
                switch,
                genelabelsize=genelabelsize,
                chr_label=chr_label,
                loc_label=loc_label,
                vpad=vpad,
                extra_features=ef,
                glyphstyle=glyphstyle,
                glyphcolor=glyphcolor,
            )
            self.rr.append(r)
            # Use tid and accn to store gene positions
            gg.update(dict(((i, k), v) for k, v in r.gg.items()))
            ymids.append(r.y)

        def offset(samearc):
            if samearc == "above":
                return 2 * pad
            if samearc == "above2":
                return 4 * pad
            if samearc == "below":
                return -2 * pad
            if samearc == "below2":
                return -4 * pad

        for i, j, blockcolor, samearc in lo.edges:
            for ga, gb, h in bf.iter_pairs(i, j):
                a, b = gg[(i, ga)], gg[(j, gb)]
                if samearc is not None:
                    ymid = ymids[i] + offset(samearc)
                else:
                    ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, fc=blockcolor, lw=0, alpha=1, style=shadestyle)

            for ga, gb, h in bf.iter_pairs(i, j, highlight=True):
                a, b = gg[(i, ga)], gg[(j, gb)]
                if samearc is not None:
                    ymid = ymids[i] + offset(samearc)
                else:
                    ymid = (ymids[i] + ymids[j]) / 2
                Shade(
                    root, a, b, ymid, alpha=1, highlight=h, zorder=2, style=shadestyle
                )

        if scalebar:
            print("Build scalebar (scale={})".format(scale), file=sys.stderr)
            # Find the best length of the scalebar
            ar = [1, 2, 5]
            candidates = (
                [1000 * x for x in ar]
                + [10000 * x for x in ar]
                + [100000 * x for x in ar]
            )
            # Find the one that's close to an optimal canvas size
            dists = [(abs(x / scale - 0.12), x) for x in candidates]
            dist, candidate = min(dists)
            dist = candidate / scale
            x, y, yp = 0.22, 0.92, 0.005
            a, b = x - dist / 2, x + dist / 2
            lsg = "lightslategrey"
            root.plot([a, a], [y - yp, y + yp], "-", lw=2, color=lsg)
            root.plot([b, b], [y - yp, y + yp], "-", lw=2, color=lsg)
            root.plot([a, b], [y, y], "-", lw=2, color=lsg)
            root.text(
                x,
                y + 0.02,
                human_size(candidate, precision=0),
                ha="center",
                va="center",
            )

        if tree:
            from jcvi.graphics.tree import draw_tree, read_trees

            trees = read_trees(tree)
            ntrees = len(trees)
            logging.debug("A total of {0} trees imported.".format(ntrees))
            xiv = 1.0 / ntrees
            yiv = 0.3
            xstart = 0
            ystart = min(ymids) - 0.4
            for i in range(ntrees):
                ax = fig.add_axes([xstart, ystart, xiv, yiv])
                label, outgroup, color, tx = trees[i]
                draw_tree(
                    ax,
                    tx,
                    outgroup=outgroup,
                    rmargin=0.4,
                    leaffont=11,
                    treecolor=color,
                    supportcolor=color,
                    leafcolor=color,
                )
                xstart += xiv
                RoundLabel(ax, 0.5, 0.3, label, fill=True, fc="lavender", color=color)
Exemplo n.º 4
0
    def __init__(self,
                 fig,
                 root,
                 datafile,
                 bedfile,
                 layoutfile,
                 switch=None,
                 tree=None,
                 extra_features=None,
                 chr_label=True,
                 loc_label=True,
                 pad=.04):

        w, h = fig.get_figwidth(), fig.get_figheight()
        bed = Bed(bedfile)
        order = bed.order
        bf = BlockFile(datafile)
        self.layout = lo = Layout(layoutfile)
        switch = DictFile(switch, delimiter="\t") if switch else None
        if extra_features:
            extra_features = Bed(extra_features)

        exts = []
        extras = []
        for i in xrange(bf.ncols):
            ext = bf.get_extent(i, order)
            exts.append(ext)
            if extra_features:
                start, end, si, ei, chr, orientation, span = ext
                start, end = start.start, end.end  # start, end coordinates
                ef = list(extra_features.extract(chr, start, end))

                # Pruning removes minor features with < 0.1% of the region
                ef_pruned = [x for x in ef if x.span >= span / 1000]
                print >> sys.stderr, "Extracted {0} features "\
                        "({1} after pruning)".format(len(ef), len(ef_pruned))
                extras.append(ef_pruned)

        maxspan = max(exts, key=lambda x: x[-1])[-1]
        scale = maxspan / .65

        self.gg = gg = {}
        self.rr = []
        ymids = []
        vpad = .012 * w / h
        for i in xrange(bf.ncols):
            ext = exts[i]
            ef = extras[i] if extras else None
            r = Region(root,
                       ext,
                       lo[i],
                       bed,
                       scale,
                       switch,
                       chr_label=chr_label,
                       loc_label=loc_label,
                       vpad=vpad,
                       extra_features=ef)
            self.rr.append(r)
            # Use tid and accn to store gene positions
            gg.update(dict(((i, k), v) for k, v in r.gg.items()))
            ymids.append(r.y)

        for i, j in lo.edges:
            for ga, gb, h in bf.iter_pairs(i, j):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, fc="gainsboro", lw=0, alpha=1)

            for ga, gb, h in bf.iter_pairs(i, j, highlight=True):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, alpha=1, highlight=h, zorder=2)

        if tree:
            from jcvi.graphics.tree import draw_tree, read_trees

            trees = read_trees(tree)
            ntrees = len(trees)
            logging.debug("A total of {0} trees imported.".format(ntrees))
            xiv = 1. / ntrees
            yiv = .3
            xstart = 0
            ystart = min(ymids) - .4
            for i in xrange(ntrees):
                ax = fig.add_axes([xstart, ystart, xiv, yiv])
                label, outgroup, tx = trees[i]
                draw_tree(ax, tx, outgroup=outgroup, rmargin=.4, leaffont=11)
                xstart += xiv
                RoundLabel(ax,
                           .5,
                           .3,
                           label,
                           fill=True,
                           fc="lavender",
                           color="r")
Exemplo n.º 5
0
    def __init__(self, fig, root, datafile, bedfile, layoutfile,
                 switch=None, tree=None, extra_features=None,
                 chr_label=True, pad=.04):

        w, h = fig.get_figwidth(), fig.get_figheight()
        bed = Bed(bedfile)
        order = bed.order
        bf = BlockFile(datafile)
        lo = Layout(layoutfile)
        switch = DictFile(switch, delimiter="\t") if switch else None
        if extra_features:
            extra_features = Bed(extra_features)

        exts = []
        extras = []
        for i in xrange(bf.ncols):
            ext = bf.get_extent(i, order)
            exts.append(ext)
            if extra_features:
                start, end, si, ei, chr, orientation, span = ext
                start, end = start.start, end.end  # start, end coordinates
                ef = list(extra_features.extract(chr, start, end))

                # Pruning removes minor features with < 0.1% of the region
                ef_pruned = [x for x in ef if x.span >= span / 1000]
                print >> sys.stderr, "Extracted {0} features "\
                        "({1} after pruning)".format(len(ef), len(ef_pruned))
                extras.append(ef_pruned)

        maxspan = max(exts, key=lambda x: x[-1])[-1]
        scale = maxspan / .65

        self.gg = gg = {}
        self.rr = []
        ymids = []
        vpad = .012 * w / h
        for i in xrange(bf.ncols):
            ext = exts[i]
            ef = extras[i] if extras else None
            r = Region(root, ext, lo[i], bed, scale, switch,
                       chr_label=chr_label, vpad=vpad, extra_features=ef)
            self.rr.append(r)
            # Use tid and accn to store gene positions
            gg.update(dict(((i, k), v) for k, v in r.gg.items()))
            ymids.append(r.y)

        for i, j in lo.edges:
            for ga, gb, h in bf.iter_pairs(i, j):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, fc="gainsboro", lw=0, alpha=1)

            for ga, gb, h in bf.iter_pairs(i, j, highlight=True):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, alpha=1, highlight=h, zorder=2)

        if tree:
            from jcvi.graphics.tree import draw_tree, read_trees

            trees = read_trees(tree)
            ntrees = len(trees)
            logging.debug("A total of {0} trees imported.".format(ntrees))
            xiv = 1. / ntrees
            yiv = .3
            xstart = 0
            ystart = min(ymids) - .4
            for i in xrange(ntrees):
                ax = fig.add_axes([xstart, ystart, xiv, yiv])
                label, outgroup, tx = trees[i]
                draw_tree(ax, tx, outgroup=outgroup, rmargin=.4)
                xstart += xiv
                RoundLabel(ax, .5, .3, label, fill=True, fc="lavender", color="r")
Exemplo n.º 6
0
    def __init__(self,
                 fig,
                 root,
                 datafile,
                 bedfile,
                 layoutfile,
                 switch=None,
                 tree=None,
                 extra_features=None,
                 chr_label=True,
                 loc_label=True,
                 pad=.04,
                 scalebar=False):

        w, h = fig.get_figwidth(), fig.get_figheight()
        bed = Bed(bedfile)
        order = bed.order
        bf = BlockFile(datafile)
        self.layout = lo = Layout(layoutfile)
        switch = DictFile(switch, delimiter="\t") if switch else None
        if extra_features:
            extra_features = Bed(extra_features)

        exts = []
        extras = []
        for i in xrange(bf.ncols):
            ext = bf.get_extent(i, order)
            exts.append(ext)
            if extra_features:
                start, end, si, ei, chr, orientation, span = ext
                start, end = start.start, end.end  # start, end coordinates
                ef = list(extra_features.extract(chr, start, end))

                # Pruning removes minor features with < 0.1% of the region
                ef_pruned = [x for x in ef if x.span >= span / 1000]
                print >> sys.stderr, "Extracted {0} features "\
                        "({1} after pruning)".format(len(ef), len(ef_pruned))
                extras.append(ef_pruned)

        maxspan = max(exts, key=lambda x: x[-1])[-1]
        scale = maxspan / .65

        self.gg = gg = {}
        self.rr = []
        ymids = []
        vpad = .012 * w / h
        for i in xrange(bf.ncols):
            ext = exts[i]
            ef = extras[i] if extras else None
            r = Region(root,
                       ext,
                       lo[i],
                       bed,
                       scale,
                       switch,
                       chr_label=chr_label,
                       loc_label=loc_label,
                       vpad=vpad,
                       extra_features=ef)
            self.rr.append(r)
            # Use tid and accn to store gene positions
            gg.update(dict(((i, k), v) for k, v in r.gg.items()))
            ymids.append(r.y)

        for i, j in lo.edges:
            for ga, gb, h in bf.iter_pairs(i, j):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, fc="gainsboro", lw=0, alpha=1)

            for ga, gb, h in bf.iter_pairs(i, j, highlight=True):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, alpha=1, highlight=h, zorder=2)

        if scalebar:
            print >> sys.stderr, "Build scalebar (scale={})".format(scale)
            # Find the best length of the scalebar
            ar = [1, 2, 5]
            candidates = [1000 * x for x in ar] + [10000 * x for x in ar] + \
                         [100000 * x for x in ar]
            # Find the one that's close to an optimal canvas size
            dists = [(abs(x / scale - .12), x) for x in candidates]
            dist, candidate = min(dists)
            dist = candidate / scale
            x, y, yp = .2, .96, .005
            a, b = x - dist / 2, x + dist / 2
            lsg = "lightslategrey"
            root.plot([a, a], [y - yp, y + yp], "-", lw=2, color=lsg)
            root.plot([b, b], [y - yp, y + yp], "-", lw=2, color=lsg)
            root.plot([a, b], [y, y], "-", lw=2, color=lsg)
            root.text(x,
                      y + .02,
                      human_size(candidate, precision=0),
                      ha="center",
                      va="center")

        if tree:
            from jcvi.graphics.tree import draw_tree, read_trees

            trees = read_trees(tree)
            ntrees = len(trees)
            logging.debug("A total of {0} trees imported.".format(ntrees))
            xiv = 1. / ntrees
            yiv = .3
            xstart = 0
            ystart = min(ymids) - .4
            for i in xrange(ntrees):
                ax = fig.add_axes([xstart, ystart, xiv, yiv])
                label, outgroup, tx = trees[i]
                draw_tree(ax, tx, outgroup=outgroup, rmargin=.4, leaffont=11)
                xstart += xiv
                RoundLabel(ax,
                           .5,
                           .3,
                           label,
                           fill=True,
                           fc="lavender",
                           color="r")
Exemplo n.º 7
0
    def __init__(self,
                 fig,
                 root,
                 datafile,
                 bedfile,
                 layoutfile,
                 switch=None,
                 tree=None,
                 chr_label=True,
                 pad=.04):

        w, h = fig.get_figwidth(), fig.get_figheight()
        bed = Bed(bedfile)
        order = bed.order
        bf = BlockFile(datafile)
        lo = Layout(layoutfile)
        switch = DictFile(switch, delimiter="\t") if switch else None

        exts = []
        for i in xrange(bf.ncols):
            ext = bf.get_extent(i, order)
            exts.append(ext)

        maxspan = max(exts, key=lambda x: x[-1])[-1]
        scale = maxspan / .65

        self.gg = gg = {}
        self.rr = []
        ymids = []
        vpad = .012 * w / h
        for i in xrange(bf.ncols):
            ext = exts[i]
            r = Region(root,
                       ext,
                       lo[i],
                       bed,
                       scale,
                       switch,
                       chr_label=chr_label,
                       vpad=vpad)
            self.rr.append(r)
            # Use tid and accn to store gene positions
            gg.update(dict(((i, k), v) for k, v in r.gg.items()))
            ymids.append(r.y)

        for i, j in lo.edges:
            for ga, gb, h in bf.iter_pairs(i, j):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, fc="gainsboro", lw=0, alpha=1)

            for ga, gb, h in bf.iter_pairs(i, j, highlight=True):
                a, b = gg[(i, ga)], gg[(j, gb)]
                ymid = (ymids[i] + ymids[j]) / 2
                Shade(root, a, b, ymid, alpha=1, highlight=h, zorder=2)

        if tree:
            from jcvi.graphics.tree import draw_tree, read_trees

            trees = read_trees(tree)
            ntrees = len(trees)
            logging.debug("A total of {0} trees imported.".format(ntrees))
            xiv = 1. / ntrees
            yiv = .3
            xstart = 0
            ystart = min(ymids) - .4
            for i in xrange(ntrees):
                ax = fig.add_axes([xstart, ystart, xiv, yiv])
                label, outgroup, tx = trees[i]
                draw_tree(ax, tx, outgroup=outgroup, rmargin=.4)
                xstart += xiv
                RoundLabel(ax,
                           .5,
                           .3,
                           label,
                           fill=True,
                           fc="lavender",
                           color="r")