def plotSignal(self, ax: plt, n: int, xpos: int, ypos: float, sig: str, sig_type: str) -> None:
if sig_type == "NS1":
color = "deepskyblue"
shift = 3
elif sig_type == "NS2":
color = "deepskyblue"
shift = 4
elif sig_type == "NS3":
color = "deepskyblue"
shift = 4
elif sig_type == "CON1":
color = "goldenrod"
shift = 3
elif sig_type == "CON2":
color = "goldenrod"
shift = 4
elif sig_type == "CON3":
color = "goldenrod"
shift = 4
elif sig_type == "RAP":
color = "violet"
shift = 2
else:
raise ValueError("Wrong sig_type:" + sig_type)
color = "gray"
ax.plot(self.xMl[n - shift: n + 1], self.yMl[n - shift: n + 1], color=color, linewidth=1)
# ax.text(xpos - 30, ypos - 0.004, sig, fontsize=12, color=color, fontweight="bold")
ax.text(xpos - 120, ypos - 0.03, sig_type, fontsize=6, color=color, fontweight="bold")
def plotSignal(self, ax: plt, n: int, xpos: int, ypos: float, sig: str, sig_type: str) -> None:
if sig_type == "CON1":
shift = 3
elif sig_type == "CON3":
shift = 4
elif sig_type == "RAP":
shift = 2
else:
raise ValueError("Wrong sig_type:" + sig_type)
ax.plot(self.xMl[n - shift: n + 1], self.yMl[n - shift: n + 1], color="gray",linewidth=1)
ax.text(xpos - 120, ypos - 0.03, sig_type, fontsize=6, color="gray", fontweight="bold")
def plotSignal(self, ax: plt, n: int, xpos: int, ypos: float, sig: str,
sig_type: str) -> None:
shift = 3 if sig_type == "CON1" else 2
ax.plot(self.xMl[n - shift:n + 1],
self.yMl[n - shift:n + 1],
color="gray",
linewidth=1)
ax.text(xpos - 120,
ypos - 0.03,
sig_type,
fontsize=6,
color="gray",
fontweight="bold")
def add_scatter_and_annotate(self,
fig: plt,
x_all: np.array,
y_all: np.array,
colour: str,
idxs: np.array,
annotate=False):
x = x_all[idxs]
y = y_all[idxs]
ax = fig.scatter(x, y, c=colour, alpha=self.opacity, s=20)
# Check if we want to annotate any of these with their gene IDs
if self.values_to_label is not None:
texts = []
labels = self.df[self.label_column].values[idxs]
for i, name in enumerate(labels):
if name in self.values_to_label:
lbl_bg = self.values_colours.get(name)
color = self.text_colours.get(name)
texts.append(
fig.text(x[i],
y[i],
name,
color=color,
fontsize=self.label_font_size,
bbox=dict(fc=lbl_bg, alpha=1.0)))
adjust_text(texts, force_text=2.0)
# Check if the user wants these labeled
if self.label_big_sig and annotate:
# If they do have a limit on the number of ones we show (i.e. we don't want 10000 gene names...)
max_values = -1 * self.max_labels
if len(y) < self.max_labels:
max_values = -1 * (len(y) - 1)
most_sig_idxs = np.argpartition(y, max_values)[max_values:]
labels = self.df[self.label_column].values[idxs][most_sig_idxs]
x = x[most_sig_idxs]
y = y[most_sig_idxs]
# We only label the ones with the max log fc
for i, name in enumerate(labels):
fig.annotate(name, (x[i], y[i]),
xytext=(0, 10),
textcoords='offset points',
ha='center',
va='bottom',
bbox=dict(boxstyle='round,pad=0.5',
fc='white',
alpha=0.2))
return ax
