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import gradio as gr
import numpy as np
import pandas as pd
import plotly.express as px
import plotly.subplots as sp
from datasets import load_dataset
import umap

# Load dataset function
def load_dataset_from_hub(dataset_name, split="test"):
    try:
        return load_dataset(dataset_name, split=split), None
    except Exception as e:
        return None, str(e)

# Create visualization function
def create_visualization(split, color_col, log):
    # Load the dataset
    dataset, error = load_dataset_from_hub("Smith42/galaxies_with_embeddings", split)
    if error:
        return None, f"Error loading dataset: {error}"
    
    try:
        embedding_cols = ["p16k00_pca", "p16k01_pca", "p16k10_pca"]
        # Extract embeddings and color values
        embeddings = dataset.select_columns(embedding_cols)
        colors = np.array(dataset[color_col], dtype=float)
        if log: colors = np.log(colors)
        fig = sp.make_subplots(cols=3, subplot_titles=["k = 0%", "k = 1%", "k = 10%"])
        
        ii = 0
        for col in range(1, 4):
            embedding_col = embedding_cols[ii]
            emb_ar = np.array(embeddings[embedding_col])
            df = pd.DataFrame({
                'x': emb_ar[:, 0],
                'y': emb_ar[:, 1],
                'color': colors
            }).dropna()
            scatter = px.scatter(df, x='x', y='y', color='color')
            fig.add_trace(scatter.data[0], row=1, col=col)
            ii = ii + 1

        return fig, None
    except Exception as e:
        return None, f"Error creating viz: {str(e)}"

property_groups = {
    "Basic Identifiers": [
        "dr8_id", "ra", "dec", "brickid", "objid", "file_name", "iauname"
    ],

    "Galaxy Morphology": [
        "smooth-or-featured_smooth_fraction", "smooth-or-featured_featured-or-disk_fraction",
        "smooth-or-featured_artifact_fraction", "disk-edge-on_yes_fraction", "disk-edge-on_no_fraction",
        "has-spiral-arms_yes_fraction", "has-spiral-arms_no_fraction",
        "bar_strong_fraction", "bar_weak_fraction", "bar_no_fraction",
        "bulge-size_dominant_fraction", "bulge-size_large_fraction", "bulge-size_moderate_fraction",
        "bulge-size_small_fraction", "bulge-size_none_fraction",
        "how-rounded_round_fraction", "how-rounded_in-between_fraction", "how-rounded_cigar-shaped_fraction",
        "edge-on-bulge_boxy_fraction", "edge-on-bulge_none_fraction", "edge-on-bulge_rounded_fraction",
        "spiral-winding_tight_fraction", "spiral-winding_medium_fraction", "spiral-winding_loose_fraction",
        "spiral-arm-count_1_fraction", "spiral-arm-count_2_fraction", "spiral-arm-count_3_fraction",
        "spiral-arm-count_4_fraction", "spiral-arm-count_more-than-4_fraction", "spiral-arm-count_cant-tell_fraction",
        "merging_none_fraction", "merging_minor-disturbance_fraction", "merging_major-disturbance_fraction",
        "merging_merger_fraction"
    ],

    "Physical Size Parameters": [
        "est_petro_th50", "est_petro_th50_kpc", "petro_theta", "petro_th50", "petro_th90",
        "petro_phi50", "petro_phi90", "petro_ba50", "petro_ba90",
        "elpetro_ba", "elpetro_phi", "elpetro_flux_r", "elpetro_theta_r"
    ],

    "Photometric Properties": [
        "mag_r_desi", "mag_g_desi", "mag_z_desi",
        "mag_f", "mag_n", "mag_u", "mag_g", "mag_r", "mag_i", "mag_z",
        "u_minus_r", "sersic_n", "sersic_ba", "sersic_phi",
        "elpetro_absmag_f", "elpetro_absmag_n", "elpetro_absmag_u",
        "elpetro_absmag_g", "elpetro_absmag_r", "elpetro_absmag_i", "elpetro_absmag_z",
        "sersic_nmgy_f", "sersic_nmgy_n", "sersic_nmgy_u", "sersic_nmgy_g",
        "sersic_nmgy_r", "sersic_nmgy_i", "sersic_nmgy_z"
    ],

    "Mass and Redshift": [
        "elpetro_mass", "elpetro_mass_log", "redshift", "redshift_nsa",
        "redshift_ossy", "photo_z", "photo_zerr", "spec_z"
    ],

    "Star Formation Properties": [
        "fibre_sfr_avg", "fibre_sfr_entropy", "fibre_sfr_median", "fibre_sfr_mode",
        "fibre_sfr_p16", "fibre_sfr_p2p5", "fibre_sfr_p84", "fibre_sfr_p97p5",
        "fibre_ssfr_avg", "fibre_ssfr_entropy", "fibre_ssfr_median", "fibre_ssfr_mode",
        "fibre_ssfr_p16", "fibre_ssfr_p2p5", "fibre_ssfr_p84", "fibre_ssfr_p97p5",
        "total_ssfr_avg", "total_ssfr_entropy", "total_ssfr_flag", "total_ssfr_median",
        "total_ssfr_mode", "total_ssfr_p16", "total_ssfr_p2p5", "total_ssfr_p84",
        "total_ssfr_p97p5", "total_sfr_avg", "total_sfr_entropy", "total_sfr_flag",
        "total_sfr_median", "total_sfr_mode", "total_sfr_p16", "total_sfr_p2p5",
        "total_sfr_p84", "total_sfr_p97p5"
    ],

    "AGN Properties": [
        "log_l_oiii", "fwhm", "e_fwhm", "equiv_width", "log_l_ha",
        "log_m_bh", "upper_e_log_m_bh", "lower_e_log_m_bh", "log_bolometric_l"
    ],

    "HI Properties": [
        "W50", "sigW", "W20", "HIflux", "sigflux", "SNR", "RMS",
        "Dist", "sigDist", "logMH", "siglogMH"
    ],

    "PhotoZ Catalog": [
        "photoz_id", "ra_photoz", "dec_photoz", "mag_abs_g_photoz", "mag_abs_r_photoz",
        "mag_abs_z_photoz", "mass_inf_photoz", "mass_med_photoz", "mass_sup_photoz",
        "sfr_inf_photoz", "sfr_sup_photoz", "ssfr_inf_photoz", "ssfr_med_photoz",
        "ssfr_sup_photoz", "sky_separation_arcsec_from_photoz"
    ]
}

# Define the Gradio interface
with gr.Blocks(title="Galaxy embeddings") as demo:
    gr.Markdown("# Sparse galaxy embeddings")
    
    with gr.Row():
        split_input = gr.Dropdown(
            label="Split", 
            value="test",
            choices=["test", "validation"]
        )
        group_dropdown = gr.Dropdown(
            label="Property category",
            choices=list(property_groups.keys()),
            value=list(property_groups.keys())[0]
        )
        color_col = gr.Dropdown(
            label="Property",
            choices=property_groups[list(property_groups.keys())[0]]
        )
        log = gr.Checkbox(
            label="Take log?",
            value=False
        )
        visualize_btn = gr.Button("Let's go!")

    error_output = gr.Textbox(label="Errors", visible=False)

    def update_properties(group):
        return gr.update(choices=property_groups[group], value=property_groups[group][0])

    group_dropdown.change(
        fn=update_properties,
        inputs=[group_dropdown],
        outputs=[color_col]
    )
        
    with gr.Row():
        plot_output = gr.Plot(label="Visualization")
    
    visualize_btn.click(
        fn=create_visualization,
        inputs=[split_input, color_col, log],
        outputs=[plot_output, error_output]
    )

demo.launch()