def scatter_plot_accuracy_vs_numpasses(data,
axis_labels=("Number of passes", "Predicted accuracy (Phred QV)"),
nbins=None, barcolor=None):
"""
"""
npasses, accuracy = data
qvs = accuracy_as_phred_qv(accuracy)
fig, ax = get_fig_axes_lpr()
data = [Line(xData=npasses,
yData=qvs,
style='o')]
apply_line_data(
ax=ax,
line_models=data,
axis_labels=axis_labels,
only_whole_ticks=False)
return fig, ax
def scatter_plot_accuracy_vs_numpasses(
data,
axis_labels=(
get_plot_xlabel(spec, Constants.PG_SCATTER, Constants.P_SCATTER),
get_plot_ylabel(spec, Constants.PG_SCATTER, Constants.P_SCATTER),
),
nbins=None,
barcolor=None,
):
"""
"""
npasses, accuracy = data
qvs = accuracy_as_phred_qv(accuracy)
fig, ax = get_fig_axes_lpr()
data = [Line(xData=npasses, yData=qvs, style="o")]
apply_line_data(ax=ax, line_models=data, axis_labels=axis_labels, only_whole_ticks=False)
return fig, ax
def scatter_plot_accuracy_vs_concordance(
data,
axis_labels=(
meta_rpt.get_meta_plotgroup(Constants.PG_QV_CALIBRATION).get_meta_plot(Constants.P_QV_CALIBRATION).xlabel,
meta_rpt.get_meta_plotgroup(Constants.PG_QV_CALIBRATION).get_meta_plot(Constants.P_QV_CALIBRATION).ylabel,
),
nbins=None,
barcolor=None,
):
accuracy, concordance = data
fig, ax = get_fig_axes_lpr()
data = [Line(xData=accuracy, yData=concordance, style="+")]
apply_line_data(ax=ax, line_models=data, axis_labels=axis_labels, only_whole_ticks=False)
xlim = ax.get_xlim()
xy = np.linspace(xlim[0], xlim[1])
ax.plot(xy, xy, "-", color="r")
return fig, ax
def _create_contig_plot(contig_coverage):
"""
Returns a fig,ax plot for this contig
:param contig_coverage: (ContigCoverage)
"""
npXData = np.array(contig_coverage.xData)
line_fill = LineFill(xData=npXData,
yData=np.array(contig_coverage.yDataMean),
linecolor=Constants.COLOR_STEEL_BLUE_DARK, alpha=0.6,
yDataMin=np.array(contig_coverage.yDataStdevMinus),
yDataMax=np.array(contig_coverage.yDataStdevPlus),
edgecolor=Constants.COLOR_STEEL_BLUE_LIGHT,
facecolor=Constants.COLOR_STEEL_BLUE_LIGHT)
lines_fills = [line_fill]
fig, ax = get_fig_axes_lpr()
apply_line_data(ax, lines_fills, ('Reference Start Position', 'Coverage'))
apply_line_fill_data(ax, lines_fills)
return fig, ax
def scatter_plot_accuracy_vs_numpasses(
data,
axis_labels=(get_plot_xlabel(spec, Constants.PG_SCATTER,
Constants.P_SCATTER),
get_plot_ylabel(spec, Constants.PG_SCATTER,
Constants.P_SCATTER)),
nbins=None,
barcolor=None):
"""
"""
npasses, accuracy = data
qvs = accuracy_as_phred_qv(accuracy)
fig, ax = get_fig_axes_lpr()
data = [Line(xData=npasses, yData=qvs, style='o')]
apply_line_data(ax=ax,
line_models=data,
axis_labels=axis_labels,
only_whole_ticks=False)
return fig, ax
def scatter_plot_accuracy_vs_numpasses(data,
axis_labels=(
meta_rpt.get_meta_plotgroup(Constants.PG_SCATTER).get_meta_plot(Constants.P_SCATTER).xlabel,
meta_rpt.get_meta_plotgroup(Constants.PG_SCATTER).get_meta_plot(Constants.P_SCATTER).ylabel),
nbins=None, barcolor=None):
"""
"""
npasses, accuracy = data
qvs = accuracy_as_phred_qv(accuracy)
fig, ax = get_fig_axes_lpr()
data = [Line(xData=npasses,
yData=qvs,
style='o')]
apply_line_data(
ax=ax,
line_models=data,
axis_labels=axis_labels,
only_whole_ticks=False)
return fig, ax
def scatter_plot_accuracy_vs_concordance(
data,
axis_labels,
nbins,
barcolor):
accuracy, concordance = data
fig, ax = get_fig_axes_lpr()
data = [Line(xData=accuracy,
yData=concordance,
style='+')]
apply_line_data(
ax=ax,
line_models=data,
axis_labels=axis_labels,
only_whole_ticks=False)
xlim = ax.get_xlim()
xy = np.linspace(xlim[0], xlim[1])
ax.plot(xy, xy, '-', color='r')
return fig, ax
def scatter_plot_accuracy_vs_concordance(
data,
axis_labels=(get_plot_xlabel(spec, Constants.PG_QV_CALIBRATION,
Constants.P_QV_CALIBRATION),
get_plot_ylabel(spec, Constants.PG_QV_CALIBRATION,
Constants.P_QV_CALIBRATION)),
nbins=None,
barcolor=None):
accuracy, concordance = data
fig, ax = get_fig_axes_lpr()
data = [Line(xData=accuracy, yData=concordance, style='+')]
apply_line_data(ax=ax,
line_models=data,
axis_labels=axis_labels,
only_whole_ticks=False)
xlim = ax.get_xlim()
xy = np.linspace(xlim[0], xlim[1])
ax.plot(xy, xy, '-', color='r')
return fig, ax
def scatter_plot_accuracy_vs_concordance(
data,
axis_labels=("Predicted accuracy", "Mapped concordance"),
nbins=None,
barcolor=None):
accuracy, concordance = data
fig, ax = get_fig_axes_lpr()
data = [Line(xData=accuracy,
yData=concordance,
style='+')]
apply_line_data(
ax=ax,
line_models=data,
axis_labels=axis_labels,
only_whole_ticks=False)
xlim = ax.get_xlim()
xy = np.linspace(xlim[0], xlim[1])
ax.plot(xy, xy, '-', color='r')
return fig, ax
def _create_contig_plot(contig_coverage):
"""
Returns a fig,ax plot for this contig
:param contig_coverage: (ContigCoverage)
"""
npXData = np.array(contig_coverage.xData)
line_fill = LineFill(xData=npXData,
yData=np.array(contig_coverage.yDataMean),
linecolor=Constants.COLOR_STEEL_BLUE_DARK, alpha=0.6,
yDataMin=np.array(contig_coverage.yDataStdevMinus),
yDataMax=np.array(contig_coverage.yDataStdevPlus),
edgecolor=Constants.COLOR_STEEL_BLUE_LIGHT,
facecolor=Constants.COLOR_STEEL_BLUE_LIGHT)
lines_fills = [line_fill]
fig, ax = get_fig_axes_lpr()
apply_line_data(ax, lines_fills, (meta_rpt.get_meta_plotgroup(Constants.PG_COVERAGE).get_meta_plot(
Constants.P_COVERAGE).xlabel, meta_rpt.get_meta_plotgroup(Constants.PG_COVERAGE).get_meta_plot(Constants.P_COVERAGE).ylabel))
apply_line_fill_data(ax, lines_fills)
return fig, ax
def scatter_plot_accuracy_vs_concordance(
data,
axis_labels=(
get_plot_xlabel(spec, Constants.PG_QV_CALIBRATION,
Constants.P_QV_CALIBRATION),
get_plot_ylabel(spec, Constants.PG_QV_CALIBRATION,
Constants.P_QV_CALIBRATION)),
nbins=None,
barcolor=None):
accuracy, concordance = data
fig, ax = get_fig_axes_lpr()
data = [Line(xData=accuracy,
yData=concordance,
style='+')]
apply_line_data(
ax=ax,
line_models=data,
axis_labels=axis_labels,
only_whole_ticks=False)
xlim = ax.get_xlim()
xy = np.linspace(xlim[0], xlim[1])
ax.plot(xy, xy, '-', color='r')
return fig, ax
def _create_contig_plot(self, contig_coverage):
"""
Returns a fig,ax plot for this contig
:param contig_coverage: (ContigCoverage)
"""
npXData = np.array(contig_coverage.xData)
line_fill = LineFill(xData=npXData,
yData=np.array(contig_coverage.yDataMean),
linecolor=Constants.COLOR_STEEL_BLUE_DARK, alpha=0.6,
yDataMin=np.array(
contig_coverage.yDataStdevMinus),
yDataMax=np.array(contig_coverage.yDataStdevPlus),
edgecolor=Constants.COLOR_STEEL_BLUE_LIGHT,
facecolor=Constants.COLOR_STEEL_BLUE_LIGHT)
lines_fills = [line_fill]
fig, ax = get_fig_axes_lpr()
xlabel = get_plot_xlabel(
self.spec, Constants.PG_COVERAGE, Constants.P_COVERAGE)
ylabel = get_plot_ylabel(
self.spec, Constants.PG_COVERAGE, Constants.P_COVERAGE)
apply_line_data(ax, lines_fills, (xlabel, ylabel))
apply_line_fill_data(ax, lines_fills)
return fig, ax
