Spaces:
Paused
Paused
File size: 6,005 Bytes
7f9a25d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 |
"""
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"
|