mavis.illustrate.scatter
class mavis.illustrate.scatter.ScatterPlot
holds settings that will go into matplotlib after conversion using the mapping system
mavis.illustrate.scatter.ScatterPlot.__init__()
def __init__(
self,
points,
y_axis_label,
ymax=None,
ymin=None,
xmin=None,
xmax=None,
hmarkers=None,
height=100,
point_radius=2,
title='',
yticks=None,
colors=None,
density=1,
ymax_color='#FF0000',
):
Args
- points
- y_axis_label
- ymax
- ymin
- xmin
- xmax
- hmarkers
- height
- point_radius
- title
- yticks
- colors
- density
- ymax_color
mavis.illustrate.scatter.bam_to_scatter()
pull data from a bam file to set up a scatter plot of the pileup
def bam_to_scatter(
bam_file,
chrom,
start,
end,
density,
strand=None,
axis_name=None,
ymax=None,
min_mapping_quality=0,
ymax_color='#FF0000',
):
Args
- bam_file (
str
): path to the bam file - chrom (
str
): chromosome name - start (
int
): genomic start position for the plot - end (
int
): genomic end position for the plot - density
- strand (
STRAND
): expected strand - axis_name (
str
): axis name - ymax (
int
): maximum value to plot the y axis - min_mapping_quality (
int
): minimum mapping quality for reads to be considered in the plot - ymax_color
Returns
ScatterPlot
: the scatter plot representing the bam pileup
mavis.illustrate.scatter.draw_scatter()
given a xmapping, draw the scatter plot svg group
def draw_scatter(ds, canvas, plot, xmapping, log=DEVNULL):
Args
- ds (
DiagramSettings
): the settings/constants to use for building the svg - canvas (
svgwrite.canvas
): the svgwrite object used to create new svg elements -
plot (
ScatterPlot
): the plot to be drawn -
log