Draw scatter_3d using plotly 4.10 (SUCCESSFUL)

import plotly.graph_objects as go
import pandas as pd
from sklearn.decomposition import PCA
import numpy as np

# Read in data as a pandas dataframe
#df = pd.DataFrame({
#    'PC1': [-13.999925, -12.504291, -12.443057, -13.065235, -17.316215],
#    'PC2': [-1.498823, -3.342411, -6.067055, -8.205809, 3.293993],
#    'PC3': [-3.335085, 15.207755, -14.725450, 15.078469, -6.917358],
#    'condition': ['GFP d3', 'GFP d3', 'GFP d8', 'GFP d8', 'GFP+mCh d9/12'],
#    'donor': ['DI', 'DII', 'DI', 'DII', 'DI']
#})
df = pd.read_csv('merged_df_28PCs.csv', index_col=0, header=0)

# Fit PCA model to reduce data dimensions to 3
pca = PCA(n_components=3)
pca.fit(df.iloc[:, :-3])
X_reduced = pca.transform(df.iloc[:, :-3])

# Add reduced data back to dataframe
df['PC1'] = X_reduced[:, 0]
df['PC2'] = X_reduced[:, 1]
df['PC3'] = X_reduced[:, 2]

# Create PCA plot with 3D scatter
fig = go.Figure()

#['circle', 'circle-open', 'square', 'square-open', 'diamond', 'diamond-open', 'cross', 'x']
condition_color_map = {'GFP d3': 'blue', 'GFP d8': 'red', 'GFP+mCh d9/12': 'green', 'LT d3': 'orange'}
donor_symbol_map = {'DI': 'circle', 'DII': 'cross'}

for donor, donor_symbol in donor_symbol_map.items():
    for condition, condition_color in condition_color_map.items():
        mask = (df['condition'] == condition) & (df['donor'] == donor)
        fig.add_trace(go.Scatter3d(x=df.loc[mask, 'PC1'], y=df.loc[mask, 'PC2'], z=df.loc[mask, 'PC3'],
                                   mode='markers',
                                   name=f'{condition}' if donor == 'DI' else None,
                                   legendgroup=f'{condition}',
                                   showlegend=True if donor == 'DI' else False,
                                   marker=dict(size=10, opacity=0.8, color=condition_color, symbol=donor_symbol)))

for donor, donor_symbol in donor_symbol_map.items():
    fig.add_trace(go.Scatter3d(x=[None], y=[None], z=[None],
                               mode='markers',
                               name=donor,
                               showlegend=True,
                               marker=dict(size=10, opacity=1, color='black', symbol=donor_symbol),
                               hoverinfo='none'))

# Annotations for the legend blocks
fig.update_layout(
    annotations=[
        dict(x=1.1, y=1.0, xref='paper', yref='paper', showarrow=False,
             text='Condition', font=dict(size=15)),
        dict(x=1.1, y=0.6, xref='paper', yref='paper', showarrow=False,
             text='Donor', font=dict(size=15))
    ],
    scene=dict(
        aspectmode='cube',
        xaxis=dict(gridcolor='black', backgroundcolor='white', zerolinecolor='black', title='PC1: 36% v.'),
        yaxis=dict(gridcolor='black', backgroundcolor='white', zerolinecolor='black', title='PC2: 17% v.'),
        zaxis=dict(gridcolor='black', backgroundcolor='white', zerolinecolor='black', title='PC3: 15% variance'),
        bgcolor='white'
    ),
    margin=dict(l=5, r=5, b=5, t=5)  # Adjust the margins to prevent clipping of axis titles
)

#fig.show()
fig.write_image("fig1.svg")

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