Assigning legends to specific areas of a combined plot

[newtonharry]

Hi,

I'm trying to separate the two legends to the right such that the top one is closer to the middle and the bottom one is closer to the bottom plot:

Here is the code for it:

from marsilea.plotter import Labels
import matplotlib.pyplot as plt

# Initialize the ZeroHeight canvas for the track
fragment_track = ma.ZeroHeight(10, name="track")

# Add the peak area plot (assuming you have peak_counts defined)
fragment_track.add_bottom(
    mp.Area(
        peak_counts,  # Replace with your actual peak count data
        color="#4F6D7A",
        add_outline=False,
        alpha=1,
    ),
    name="peak"
)

# Add a title to the canvas
fragment_track.add_title("A", align="left", pad=0.4, fontsize=20)

# fragment_track.render()
colors = ['black', '#6a5acd', '#77DD77', '#FF5733', "#FFFF00"]  # Define distinct colors for different ranges
custom_cmap = ListedColormap(colors)
# Create the fragment cell heatmap
fragment_cell_heatmap = ma.CatHeatmap(downsampled_matrix.toarray(), cmap=custom_cmap, label="Read Count", height=10, width=10, name="fragment_cell_heatmap")
fragment_cell_heatmap.group_rows(downsampled_cell_types, order=np.unique(downsampled_cell_types), spacing=0.015)

# Add cell type labels on the left with no rotation
fragment_cell_heatmap.add_left(
    ma.plotter.Chunk(np.unique(downsampled_cell_types), rotation=0, props={"fontsize":23})
)

# Add title to the heatmap
fragment_cell_heatmap.add_title("B", align="left", pad=0.4, fontsize=20)

# Create cosine similarity heatmap
similarities = cosine_similarity(downsampled_matrix.toarray().T)
cosine_similarity_heatmap = ma.Heatmap(similarities, cmap="inferno", width=17, height=7, label="Cosine Similarity", name="cosine_similarities")
cosine_similarity_heatmap.add_title("C", align="left", pad=0.4, fontsize=20)
#cosine_similarity_heatmap.render()

# Combine all components into one layout
comb = fragment_track / 2.5 / fragment_cell_heatmap / 2.5 / cosine_similarity_heatmap
comb.add_legends("right", pad=1, stack_by="column")
comb.render()

# Get the Axes object corresponding to the "track" and "peak" plot
ax = comb.get_ax("track", "peak")

# Explicitly show the x-axis and customize it
ax.set_axis_on()
ax.xaxis.set_visible(True)  # Ensure the x-axis is visible
ax.tick_params(axis='x', which='both', bottom=True, labelbottom=True)  # Ensure ticks and labels are shown

# Define the start and end genomic positions (to map the relative positions)
genomic_start = 58572445
genomic_end = 58573849
num_ticks = 7  # Number of tick positions you want to show

# Set relative tick positions (e.g., positions 1 to N)
relative_positions = np.linspace(0, len(peak_counts) - 1, num_ticks).astype(int)

# Set the corresponding genomic positions as the labels
genomic_labels = np.linspace(genomic_start, genomic_end, num_ticks).astype(int)
fragment_count_labels = np.linspace(0, max(peak_counts), 7).astype(int)
# Set the relative tick positions and map them to the genomic labels
ax.set_xticks(relative_positions)
ax.set_xticklabels(["chr19:" + str(label) for label in genomic_labels], rotation=40, fontsize=23)
ax.set_yticks(relative_positions)
ax.set_yticklabels([str(label) for label in fragment_count_labels], fontsize=23)
ax.set_ylabel("Read counts", fontsize=20)
ax.set_xlabel("Genomic position", fontsize=20)
ax.set_ylim(0, max(peak_counts) + 10)
ax.tick_params(axis='y', labelsize=20)

ax = comb.layout.layouts["fragment_cell_heatmap"].get_main_ax()[-1]
ax.set_axis_on()
ax.xaxis.set_visible(True)  # Ensure the x-axis is visible and the y-axis is not
ax.yaxis.set_visible(False)
ax.tick_params(axis='x', which='both', bottom=True, labelbottom=True)  # Ensure ticks and labels are shown
ax.spines['bottom'].set_position(('outward', 20))

ax.set_xticks(relative_positions)
ax.set_xticklabels(["chr19:" + str(label) for label in genomic_labels], rotation=40, fontsize=23)
ax.set_xlabel("Genomic position", fontsize=23)

ax = comb.layout.layouts["cosine_similarities"].get_main_ax()
ax.set_axis_on()
ax.xaxis.set_visible(True)  # Ensure the x-axis is visible and the y-axis is not
ax.yaxis.set_visible(True)
ax.tick_params(axis='x', which='both', bottom=True, labelbottom=True)  # Ensure ticks and labels are shown
ax.spines['bottom'].set_position(('outward', 20))
ax.spines['left'].set_position(('outward', 20))

ax.set_xticks(relative_positions)
ax.set_xticklabels(["chr19:" + str(label) for label in genomic_labels], rotation=40, fontsize=23)
ax.set_xlabel("Genomic position", fontsize=23)

ax.set_yticks(relative_positions)
ax.set_yticklabels(["chr19:" + str(label) for label in genomic_labels], rotation=0, fontsize=23)
ax.set_ylabel("Genomic position", fontsize=23)

[Mr-Milk]

This is a planned feature, we are redesigning the layout algorithm for concatenation of multiple plots.

[newtonharry]

This is a planned feature, we are redesigning the layout algorithm for concatenation of multiple plots.

Since this is based off matplotlib, could you suggest a temporary workaround?

[Mr-Milk]

Well you can simply add an empty canvas and draw legends on it.