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import pandas as pd
from dnafiber.analysis.const import palette
import plotly.express as px
def get_color_association(df):
"""
Get the color association for each image in the dataframe.
"""
unique_name = df["image_name"].unique()
color_association = {i: p for (i, p) in zip(unique_name, palette)}
return color_association
def plot_ratio(df, color_association=None, only_bilateral=True):
df = df[["ratio", "image_name", "fiber_type"]].copy()
df["Image"] = df["image_name"]
df["Fiber Type"] = df["fiber_type"]
df["Ratio"] = df["ratio"]
if only_bilateral:
df = df[df["Fiber Type"] == "double"]
df = df.sort_values(
by=["Image", "Fiber Type"],
ascending=[True, True],
)
# Order the dataframe by the average ratio of each image
image_order = (
df.groupby("Image")["Ratio"].median().sort_values(ascending=True).index
)
df["Image"] = pd.Categorical(df["Image"], categories=image_order, ordered=True)
df.sort_values("Image", inplace=True)
if color_association is None:
color_association = get_color_association(df)
unique_name = df["image_name"].unique()
color_association = {i: p for (i, p) in zip(unique_name, palette)}
this_palette = [color_association[i] for i in unique_name]
fig = px.violin(
df,
y="Ratio",
x="Image",
color="Image",
color_discrete_sequence=this_palette,
box=True, # draw box plot inside the violin
points="all", # can be 'outliers', or False
)
# Make the fig taller
fig.update_layout(
height=500,
width=1000,
title="Ratio of green to red",
yaxis_title="Ratio",
xaxis_title="Image",
legend_title="Image",
)
return fig
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