"""
EM Embedded - Utility Functions

Contains shared utilities for grid snapping, coordinate helpers,
regex patterns, and logo loading.
"""
import re
import os
import base64
import numpy as np

__all__ = [
    "SAMPLE_PAIR_RE",
    "nearest_node_index",
    "snap_samples_to_grid",
    "nearest_gridline",
    "load_logo_data_uri",
    "normalized_position_label",
    "format_grid_label",
]

# Regex pattern for parsing coordinate pairs like "(0.5, 0.5)"
SAMPLE_PAIR_RE = re.compile(r"\(\s*([-+]?\d*\.?\d+)\s*,\s*([-+]?\d*\.?\d+)\s*\)")


def nearest_node_index(x: float, y: float, nx: int, ny: int = None) -> tuple:
    """Map normalized [0,1] coordinates to nearest node index on an nx×ny grid."""
    if ny is None:
        ny = nx
    ix = int(round(x * (nx - 1)))
    iy = int(round(y * (ny - 1)))
    ix = max(0, min(nx - 1, ix))
    iy = max(0, min(ny - 1, iy))
    return ix, iy


def nearest_gridline(val: float, nx: int) -> float:
    """Snap a value to the nearest gridline."""
    return round(val * (nx - 1)) / (nx - 1) if nx > 1 else val


def snap_samples_to_grid(sample_str: str, nx: int) -> tuple:
    """
    Parse and snap sample points to grid.
    
    Returns:
        tuple: (snapped_gridpoints_str, display_info_str)
    """
    if nx is None or nx < 2:
        return "", ""
    
    matches = SAMPLE_PAIR_RE.findall(sample_str)
    if not matches:
        return "", "Enter sample position(s) as (x, y) pairs in [0,1] x [0,1]."
    
    snapped = []
    info_parts = []
    
    for x_str, y_str in matches:
        try:
            x_norm = float(x_str)
            y_norm = float(y_str)
            # Clamp to [0, 1]
            x_norm = max(0.0, min(1.0, x_norm))
            y_norm = max(0.0, min(1.0, y_norm))
            # Snap to grid
            ix = int(round(x_norm * (nx - 1)))
            iy = int(round(y_norm * (nx - 1)))
            ix = max(0, min(nx - 1, ix))
            iy = max(0, min(nx - 1, iy))
            snapped.append((ix, iy))
            # Compute snapped normalized coords for display
            x_snapped = ix / (nx - 1) if nx > 1 else 0.0
            y_snapped = iy / (nx - 1) if nx > 1 else 0.0
            changed = (abs(x_norm - x_snapped) > 1e-9 or abs(y_norm - y_snapped) > 1e-9)
            descriptor = "adjusted" if changed else "aligned"
            info_parts.append(f"Input ({x_norm:.3f}, {y_norm:.3f}) {descriptor} to ({x_snapped:.3f}, {y_snapped:.3f}) → ({ix}, {iy})")
        except (ValueError, ZeroDivisionError):
            continue
    
    gridpoints_str = ", ".join(f"({ix}, {iy})" for ix, iy in snapped)
    info_str = "\n".join(info_parts)
    
    return gridpoints_str, info_str


def normalized_position_label(px: int, py: int, gw: int, gh: int) -> str:
    """Create a normalized position label like 'Position (0.500, 0.500)'."""
    px_i, py_i = int(px), int(py)
    denom_x = float(max(gw - 1, 1))
    denom_y = float(max(gh - 1, 1))
    x_norm = px_i / denom_x
    y_norm = py_i / denom_y
    return f"Position ({x_norm:.3f}, {y_norm:.3f})"


def format_grid_label(px: int, py: int, field: str = None, nx: int = None, label_map: dict = None) -> str:
    """Format a grid position label, optionally using a label map."""
    px_i, py_i = int(px), int(py)
    
    if label_map and field:
        label = label_map.get((str(field), px_i, py_i))
        if label:
            return label
    
    if label_map:
        for (fld, gx, gy), label in label_map.items():
            if gx == px_i and gy == py_i:
                return label
    
    if nx:
        denom = float(max(int(nx) - 1, 1))
        return f"Position ({px_i / denom:.3f}, {py_i / denom:.3f})"
    
    return f"Position ({px_i}, {py_i})"


def load_logo_data_uri() -> str:
    """Load the Synopsys logo as a data URI."""
    base_dir = os.path.dirname(os.path.dirname(__file__))  # quantum_embedded folder
    candidates = [
        os.path.join(base_dir, "ansys-part-of-synopsys-logo.svg"),
        # Also check in parent quantum folder
        os.path.join(os.path.dirname(base_dir), "quantum", "ansys-part-of-synopsys-logo.svg"),
    ]
    
    for p in candidates:
        if os.path.exists(p):
            ext = os.path.splitext(p)[1].lower()
            if ext == ".svg":
                mime = "image/svg+xml"
            elif ext == ".png":
                mime = "image/png"
            else:
                mime = "image/jpeg"
            try:
                with open(p, "rb") as f:
                    b64 = base64.b64encode(f.read()).decode("ascii")
                return f"data:{mime};base64,{b64}"
            except Exception:
                continue
    
    return None


def install_synopsys_plotly_theme():
    """Install a Synopsys-aligned Plotly theme."""
    import plotly.io as pio
    import plotly.graph_objects as go
    
    base = go.layout.Template(pio.templates["plotly_white"])
    base.layout.update(
        font=dict(
            family="Inter, Segoe UI, Roboto, Helvetica, Arial, sans-serif",
            size=13,
            color="#1A1A1A",
        ),
        paper_bgcolor="#FFFFFF",
        plot_bgcolor="#FFFFFF",
        colorway=["#5F259F", "#7A3DB5", "#AE8BD8", "#1f77b4", "#ff7f0e", "#2ca02c", "#d62728"],
        hoverlabel=dict(bgcolor="#FFFFFF", bordercolor="#5F259F", font=dict(color="#1A1A1A")),
        legend=dict(orientation="h", x=1, xanchor="right", y=1.02, yanchor="bottom", title_text=""),
        margin=dict(l=40, r=20, t=40, b=40),
    )
    base.layout.xaxis.update(
        showgrid=True,
        gridcolor="rgba(95,37,159,0.1)",
        zeroline=False,
        linecolor="rgba(0,0,0,.2)",
        ticks="outside",
        tickformat=".2f",
    )
    base.layout.yaxis.update(
        showgrid=True,
        gridcolor="rgba(95,37,159,0.1)",
        zeroline=True,
        zerolinecolor="rgba(0,0,0,.25)",
        linecolor="rgba(0,0,0,.2)",
        ticks="outside",
        tickformat=".3g",
    )
    pio.templates["syn_white"] = base
    pio.templates.default = "syn_white"