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| import gradio as gr | |
| import pandas as pd | |
| import numpy as np | |
| import io | |
| import os | |
| from datetime import datetime, time | |
| from typing import Union, Optional, Tuple, Dict, List | |
| import plotly.graph_objects as go | |
| # ====== 常數與預設 ====== | |
| EXCEL_LETTERS = ["A", "B", "K", "L", "M", "V", "W", "X", "Y"] | |
| TARGET_NAMES = ["data", "time", "⊿Ptop", "⊿Pmid", "⊿Pbot", "H2%", "CO%", "CO2%", "CH4%"] | |
| DEFAULT_COLORS = [ | |
| "#1f77b4","#ff7f0e","#2ca02c","#d62728","#9467bd", | |
| "#8c564b","#e377c2","#7f7f7f","#bcbd22","#17becf" | |
| ] | |
| DASH_OPTIONS = ["solid","dot","dash","longdash","dashdot","longdashdot"] | |
| PALETTES = { | |
| "Plotly10": DEFAULT_COLORS, | |
| "Tableau10": ["#4E79A7","#F28E2B","#E15759","#76B7B2","#59A14F","#EDC948","#B07AA1","#FF9DA7","#9C755F","#BAB0AC"], | |
| "Set2": ["#66c2a5","#fc8d62","#8da0cb","#e78ac3","#a6d854","#ffd92f","#e5c494","#b3b3b3"], | |
| "Dark2": ["#1b9e77","#d95f02","#7570b3","#e7298a","#66a61e","#e6ab02","#a6761d","#666666"], | |
| "Okabe-Ito (CB-safe)": ["#0072B2","#E69F00","#009E73","#D55E00","#CC79A7","#F0E442","#56B4E9","#000000"] | |
| } | |
| MAX_SERIES = 10 # 顏色/線型/寬度控制最多顯示前 10 條 | |
| # ====== 工具函式 ====== | |
| def letters_to_index_zero_based(letter: str) -> int: | |
| idx = 0 | |
| for ch in letter.upper(): | |
| idx = idx * 26 + (ord(ch) - ord('A') + 1) | |
| return idx - 1 | |
| TARGET_INDICES = [letters_to_index_zero_based(L) for L in EXCEL_LETTERS] | |
| def get_lower_name(file_input: Union[str, os.PathLike, io.BytesIO, bytes, object]) -> str: | |
| if isinstance(file_input, (str, os.PathLike)): | |
| return os.path.basename(str(file_input)).lower() | |
| name_attr = getattr(file_input, "name", None) | |
| if isinstance(name_attr, (str, os.PathLike)): | |
| return os.path.basename(str(name_attr)).lower() | |
| return "" | |
| def load_dataframe(file_input) -> pd.DataFrame: | |
| lower_name = get_lower_name(file_input) | |
| if isinstance(file_input, (str, os.PathLike)): | |
| path = str(file_input) | |
| if lower_name.endswith((".xlsx", ".xls")): | |
| return pd.read_excel(path, engine="openpyxl") | |
| elif lower_name.endswith(".csv"): | |
| try: | |
| return pd.read_csv(path, sep=None, engine="python") | |
| except Exception: | |
| return pd.read_csv(path) | |
| else: | |
| try: | |
| return pd.read_excel(path, engine="openpyxl") | |
| except Exception: | |
| try: | |
| return pd.read_csv(path, sep=None, engine="python") | |
| except Exception: | |
| return pd.read_csv(path) | |
| if hasattr(file_input, "read"): | |
| raw = file_input.read() | |
| bio = io.BytesIO(raw) | |
| if lower_name.endswith((".xlsx", ".xls")): | |
| bio.seek(0); return pd.read_excel(bio, engine="openpyxl") | |
| elif lower_name.endswith(".csv"): | |
| try: | |
| bio.seek(0); return pd.read_csv(bio, sep=None, engine="python") | |
| except Exception: | |
| bio.seek(0); return pd.read_csv(bio) | |
| else: | |
| try: | |
| bio.seek(0); return pd.read_excel(bio, engine="openpyxl") | |
| except Exception: | |
| try: | |
| bio.seek(0); return pd.read_csv(bio, sep=None, engine="python") | |
| except Exception: | |
| bio.seek(0); return pd.read_csv(bio) | |
| if isinstance(file_input, (bytes, bytearray)): | |
| bio = io.BytesIO(file_input) | |
| try: | |
| bio.seek(0); return pd.read_excel(bio, engine="openpyxl") | |
| except Exception: | |
| try: | |
| bio.seek(0); return pd.read_csv(bio, sep=None, engine="python") | |
| except Exception: | |
| bio.seek(0); return pd.read_csv(bio) | |
| raise ValueError("不支援的檔案型態，請上傳 .xlsx 或 .csv 檔。") | |
| def extract_and_rename(df: pd.DataFrame) -> pd.DataFrame: | |
| n_cols = df.shape[1] | |
| existing_positions = [i for i in TARGET_INDICES if i < n_cols] | |
| if not existing_positions: | |
| raise ValueError("上傳的資料欄位數不足，無法擷取指定欄位（A,B,K,L,M,V,W,X,Y）。") | |
| out = df.iloc[:, existing_positions].copy() | |
| name_map = [] | |
| for pos in existing_positions: | |
| idx_in_targets = TARGET_INDICES.index(pos) | |
| name_map.append(TARGET_NAMES[idx_in_targets]) | |
| out.columns = name_map | |
| return out | |
| def clamp_int(x, lo, hi): | |
| if x is None or (isinstance(x, str) and x.strip() == ""): | |
| return None | |
| try: | |
| xi = int(float(x)) | |
| except Exception: | |
| raise ValueError("時間欄位需為數字（整數）") | |
| return max(lo, min(hi, xi)) | |
| def parse_time_to_seconds(h, m, s): | |
| h = clamp_int(h, 0, 23) | |
| m = clamp_int(m, 0, 59) | |
| s = clamp_int(s, 0, 59) | |
| if h is None or m is None or s is None: | |
| return None | |
| return h * 3600 + m * 60 + s | |
| def _hhmmss_int_to_seconds(n: int): | |
| if n < 0 or n > 235959: return pd.NA | |
| ss = n % 100; n //= 100 | |
| mm = n % 100; n //= 100 | |
| hh = n % 100 | |
| if 0 <= hh <= 23 and 0 <= mm <= 59 and 0 <= ss <= 59: | |
| return hh*3600 + mm*60 + ss | |
| return pd.NA | |
| def series_time_to_seconds_of_day(series: pd.Series) -> pd.Series: | |
| s = series.copy() | |
| if pd.api.types.is_datetime64_any_dtype(s): | |
| return (s.dt.hour*3600 + s.dt.minute*60 + s.dt.second).astype("float") | |
| if pd.api.types.is_timedelta64_dtype(s): | |
| total_sec = s.dt.total_seconds() | |
| return (total_sec % 86400).astype("float") | |
| parsed = pd.to_datetime(s, errors="coerce") | |
| sec_parsed = (parsed.dt.hour*3600 + parsed.dt.minute*60 + parsed.dt.second).astype("float") | |
| num = pd.to_numeric(s, errors="coerce") | |
| sec_excel = ((num % 1) * 86400).round().astype("float") | |
| result = sec_parsed.where(~sec_parsed.isna(), other=np.nan) | |
| result = np.where(np.isnan(result), sec_excel, result) | |
| result = pd.Series(result, index=s.index, dtype="float") | |
| mask_intlike = num.notna() & (num == np.floor(num)) | |
| sec_hhmmss = pd.Series(np.nan, index=s.index, dtype="float") | |
| if mask_intlike.any(): | |
| ints = num[mask_intlike].astype("int64") | |
| sec_hhmmss.loc[mask_intlike] = ints.map(_hhmmss_int_to_seconds).astype("float") | |
| fill_mask = result.isna() & sec_hhmmss.notna() | |
| result.loc[fill_mask] = sec_hhmmss.loc[fill_mask] | |
| if result.isna().any(): | |
| obj_mask = result.isna() | |
| subset = s[obj_mask] | |
| def time_obj_to_sec(x): | |
| if isinstance(x, time): | |
| return x.hour*3600 + x.minute*60 + x.second | |
| return np.nan | |
| result.loc[obj_mask] = subset.map(time_obj_to_sec) | |
| return result.astype("float") | |
| def pad_time(h, m, s): | |
| def to2(x): return "??" if x is None else f"{int(x):02d}" | |
| return f"{to2(h)}:{to2(m)}:{to2(s)}" | |
| def parse_hhmmss_or_number(s: Optional[str]) -> Optional[float]: | |
| if s is None: return None | |
| if isinstance(s, (int, float)): return float(s) | |
| text = str(s).strip() | |
| if text == "": return None | |
| if ":" in text: | |
| parts = text.split(":") | |
| try: | |
| if len(parts) == 2: | |
| mm, ss = int(parts[0]), int(parts[1]); return mm*60 + ss | |
| elif len(parts) == 3: | |
| hh, mm, ss = int(parts[0]), int(parts[1]), int(parts[2]); return hh*3600 + mm*60 + ss | |
| except Exception: | |
| return None | |
| try: | |
| return float(text) | |
| except Exception: | |
| return None | |
| def prepare_x_series(df: pd.DataFrame, x_col: str) -> Tuple[pd.Series, bool]: | |
| x = df[x_col] | |
| if x_col == "time" or x.dtype == object: | |
| secs = series_time_to_seconds_of_day(x) | |
| x_dt = pd.to_datetime(secs, unit="s", origin="unix", errors="coerce") | |
| return x_dt, True | |
| else: | |
| num = pd.to_numeric(x, errors="coerce") | |
| return num, False | |
| def styles_to_map(y_cols: List[str], | |
| colors: List[Optional[str]], | |
| dashes: List[Optional[str]], | |
| widths: List[Optional[float]]) -> Dict[str, Dict]: | |
| """ | |
| 最終用於繪圖的樣式：{series: {color, width, dash}} | |
| - color：ColorPicker | |
| - dash：Dropdown | |
| - width：Number | |
| """ | |
| m: Dict[str, Dict] = {} | |
| for i, s in enumerate(y_cols): | |
| col = colors[i] if i < len(colors) and colors[i] else DEFAULT_COLORS[i % len(DEFAULT_COLORS)] | |
| dash = dashes[i] if i < len(dashes) and dashes[i] in DASH_OPTIONS else "solid" | |
| try: | |
| w = float(widths[i]) if i < len(widths) and widths[i] is not None and str(widths[i]).strip() != "" else 2.0 | |
| except Exception: | |
| w = 2.0 | |
| m[s] = {"color": col, "width": w, "dash": dash} | |
| return m | |
| def make_line_figure(df: pd.DataFrame, x_col: str, y_cols: list, | |
| fig_w: int, fig_h: int, | |
| auto_x: bool, x_min: Optional[str], x_max: Optional[str], x_dtick: Optional[str], | |
| auto_y: bool, y_min: Optional[str], y_max: Optional[str], y_dtick: Optional[str], | |
| style_map: Dict[str, Dict]): | |
| if df is None or len(df) == 0: | |
| raise ValueError("沒有可繪圖的資料。") | |
| if not x_col or not y_cols: | |
| raise ValueError("請選擇 X 與至少一個 Y 欄位。") | |
| for c in [x_col, *y_cols]: | |
| if c not in df.columns: | |
| raise ValueError(f"找不到欄位：{c}") | |
| x_series, is_time = prepare_x_series(df, x_col) | |
| if x_series.notna().sum() < 2: | |
| raise ValueError("X 軸無法解析為有效序列或點數不足。") | |
| fig = go.Figure() | |
| for idx, y_col in enumerate(y_cols): | |
| y = pd.to_numeric(df[y_col], errors="coerce") | |
| mask = x_series.notna() & y.notna() | |
| if mask.sum() < 2: | |
| continue | |
| st = style_map.get(y_col, {"color": DEFAULT_COLORS[idx % len(DEFAULT_COLORS)], | |
| "width": 2.0, "dash": "solid"}) | |
| fig.add_trace( | |
| go.Scatter( | |
| x=x_series[mask], | |
| y=y[mask], | |
| mode="lines", | |
| name=y_col, | |
| line=dict(color=st["color"], width=st["width"], dash=st["dash"]) | |
| ) | |
| ) | |
| fig.update_layout( | |
| width=int(fig_w) if fig_w else None, | |
| height=int(fig_h) if fig_h else None, | |
| margin=dict(l=60, r=20, t=40, b=60), | |
| legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1), | |
| hovermode="x unified" | |
| ) | |
| # X 軸 | |
| xaxis = {} | |
| if is_time: | |
| xaxis["type"] = "date" | |
| xaxis["tickformat"] = "%H:%M:%S" | |
| if not auto_x: | |
| xmin_s = parse_hhmmss_or_number(x_min) | |
| xmax_s = parse_hhmmss_or_number(x_max) | |
| if xmin_s is not None and xmax_s is not None: | |
| xmin_dt = pd.to_datetime(xmin_s, unit="s", origin="unix") | |
| xmax_dt = pd.to_datetime(xmax_s, unit="s", origin="unix") | |
| xaxis["range"] = [xmin_dt, xmax_dt] | |
| dtick_s = parse_hhmmss_or_number(x_dtick) | |
| if dtick_s and dtick_s > 0: | |
| xaxis["dtick"] = dtick_s * 1000.0 | |
| else: | |
| if not auto_x: | |
| xmin = parse_hhmmss_or_number(x_min) | |
| xmax = parse_hhmmss_or_number(x_max) | |
| if xmin is not None and xmax is not None: | |
| xaxis["range"] = [xmin, xmax] | |
| dtick = parse_hhmmss_or_number(x_dtick) | |
| if dtick and dtick > 0: | |
| xaxis["dtick"] = dtick | |
| fig.update_xaxes(**xaxis) | |
| # Y 軸 | |
| yaxis = {} | |
| if not auto_y: | |
| ymin = parse_hhmmss_or_number(y_min) | |
| ymax = parse_hhmmss_or_number(y_max) | |
| if ymin is not None and ymax is not None: | |
| yaxis["range"] = [ymin, ymax] | |
| y_dt = parse_hhmmss_or_number(y_dtick) | |
| if y_dt and y_dt > 0: | |
| yaxis["dtick"] = y_dt | |
| fig.update_yaxes(**yaxis) | |
| fig.update_yaxes(showgrid=True) | |
| fig.update_xaxes(showgrid=True) | |
| return fig | |
| # ====== 介面 ====== | |
| with gr.Blocks(title="Excel/CSV 指定欄位擷取器 (Biomass gasification-單槽系統使用)") as demo: | |
| gr.Markdown("### 自動擷取欄位（A,B,K,L,M,V,W,X,Y）轉換為 data, time, ⊿Ptop, ⊿Pmid, ⊿Pbot, H2%, CO%, CO2%, CH4%。") | |
| df_state = gr.State(value=None) | |
| inp = gr.File(label="上傳 .xlsx 或 .csv 檔案", file_types=[".xlsx", ".csv"], type="filepath") | |
| with gr.Row(): | |
| gr.Markdown("**開始時間 (hh:mm:ss)**") | |
| with gr.Row(): | |
| sh = gr.Number(label="Start HH (0-23)", value="") | |
| sm = gr.Number(label="Start MM (0-59)", value="") | |
| ss = gr.Number(label="Start SS (0-59)", value="") | |
| with gr.Row(): | |
| gr.Markdown("**結束時間 (hh:mm:ss)**") | |
| with gr.Row(): | |
| eh = gr.Number(label="End HH (0-23)", value="") | |
| em = gr.Number(label="End MM (0-59)", value="") | |
| es = gr.Number(label="End SS (0-59)", value="") | |
| run_btn = gr.Button("開始處理", variant="primary") | |
| file_out = gr.File(label="下載處理後的 Excel", visible=False) | |
| msg = gr.Markdown() | |
| preview = gr.Dataframe(label="預覽（前 20 列）", wrap=True) | |
| gr.Markdown("### 互動線圖設定") | |
| with gr.Row(): | |
| x_sel = gr.Dropdown(label="X 軸欄位", choices=[], value=None) | |
| y_sel = gr.Dropdown(label="Y 軸欄位（可複選）", choices=[], value=None, multiselect=True) | |
| with gr.Accordion("外觀與座標調整", open=False): | |
| with gr.Row(): | |
| fig_w = gr.Number(label="圖寬 (px)", value=900) | |
| fig_h = gr.Number(label="圖高 (px)", value=500) | |
| with gr.Row(): | |
| auto_x = gr.Checkbox(label="X 自動範圍", value=True) | |
| x_min = gr.Textbox(label="X 最小（time: hh:mm[:ss] 或 數值）", value="") | |
| x_max = gr.Textbox(label="X 最大（time: hh:mm[:ss] 或 數值）", value="") | |
| x_dtick = gr.Textbox(label="X 刻度間距 dtick（time: hh:mm[:ss]；數值：數字）", value="") | |
| with gr.Row(): | |
| auto_y = gr.Checkbox(label="Y 自動範圍", value=True) | |
| y_min = gr.Textbox(label="Y 最小（數值）", value="") | |
| y_max = gr.Textbox(label="Y 最大（數值）", value="") | |
| y_dtick = gr.Textbox(label="Y 刻度間距 dtick（數值）", value="") | |
| # ---- 樣式控制（每條線一組：ColorPicker + Dash Dropdown + Width Number） ---- | |
| gr.Markdown("### 樣式（前 10 條線）：顏色 / 線型 / 線寬") | |
| with gr.Row(): | |
| palette_dd = gr.Dropdown(label="色盤", choices=list(PALETTES.keys()), value="Okabe-Ito (CB-safe)") | |
| apply_palette_btn = gr.Button("套用色盤到 Y（依序）") | |
| # 兩排 × 5 組，每組三個控制：ColorPicker + Dropdown + Number | |
| color_pickers, dash_dds, width_nums = [], [], [] | |
| for row in range(2): | |
| with gr.Row(): | |
| for i in range(5): | |
| idx = row*5 + i | |
| with gr.Column(scale=1): | |
| color_pickers.append(gr.ColorPicker(label=f"系列 {idx+1} 顏色", value="#000000", visible=False)) | |
| dash_dds.append(gr.Dropdown(label=f"系列 {idx+1} 線型", choices=DASH_OPTIONS, value="solid", visible=False)) | |
| width_nums.append(gr.Number(label=f"系列 {idx+1} 線寬", value=2.0, visible=False)) | |
| plot_btn = gr.Button("繪製線圖（互動）") | |
| plot_out = gr.Plot(label="互動線圖") | |
| plot_msg = gr.Markdown() | |
| # --------- 回呼邏輯 --------- | |
| def run_pipeline(file_path_str, sh_, sm_, ss_, eh_, em_, es_): | |
| # 預設隱藏樣式控制 | |
| hidden_colors = [gr.update(visible=False) for _ in range(MAX_SERIES)] | |
| hidden_dashes = [gr.update(visible=False) for _ in range(MAX_SERIES)] | |
| hidden_widths = [gr.update(visible=False) for _ in range(MAX_SERIES)] | |
| if not file_path_str: | |
| return (gr.update(visible=False), "請先上傳檔案。", pd.DataFrame(), | |
| None, gr.update(choices=[], value=None), gr.update(choices=[], value=None), | |
| *hidden_colors, *hidden_dashes, *hidden_widths) | |
| try: | |
| df = load_dataframe(file_path_str) | |
| out = extract_and_rename(df) | |
| except Exception as e: | |
| return (gr.update(visible=False), f"處理失敗：{e}", pd.DataFrame(), | |
| None, gr.update(choices=[], value=None), gr.update(choices=[], value=None), | |
| *hidden_colors, *hidden_dashes, *hidden_widths) | |
| original_rows = len(out) | |
| try: | |
| start_sec = parse_time_to_seconds(sh_, sm_, ss_) | |
| end_sec = parse_time_to_seconds(eh_, em_, es_) | |
| except Exception as e: | |
| return (gr.update(visible=False), f"時間輸入錯誤：{e}", pd.DataFrame(), | |
| None, gr.update(choices=[], value=None), gr.update(choices=[], value=None), | |
| *hidden_colors, *hidden_dashes, *hidden_widths) | |
| parsed_ok = None | |
| if (start_sec is not None) and (end_sec is not None): | |
| if "time" not in out.columns: | |
| return (gr.update(visible=False), "找不到 'time' 欄，無法做時間過濾。", pd.DataFrame(), | |
| None, gr.update(choices=[], value=None), gr.update(choices=[], value=None), | |
| *hidden_colors, *hidden_dashes, *hidden_widths) | |
| secs = series_time_to_seconds_of_day(out["time"]) | |
| parsed_ok = int(secs.notna().sum()) | |
| valid_mask = secs.notna() | |
| secs_valid = secs.where(valid_mask, other=-1) | |
| if start_sec <= end_sec: | |
| keep = valid_mask & (secs_valid >= start_sec) & (secs_valid <= end_sec) | |
| else: | |
| keep = valid_mask & ((secs_valid >= start_sec) | (secs_valid <= end_sec)) | |
| out = out.loc[keep].reset_index(drop=True) | |
| ts = datetime.now().strftime("%Y%m%d_%H%M%S") | |
| out_path = f"/tmp/extracted_columns_{ts}.xlsx" | |
| try: | |
| out.to_excel(out_path, index=False, engine="openpyxl") | |
| except Exception as e: | |
| return (gr.update(visible=False), f"輸出 Excel 失敗：{e}", pd.DataFrame(), | |
| None, gr.update(choices=[], value=None), gr.update(choices=[], value=None), | |
| *hidden_colors, *hidden_dashes, *hidden_widths) | |
| cols = out.columns.tolist() | |
| default_x = "time" if "time" in cols else (cols[0] if cols else None) | |
| default_y = [c for c in ["H2%", "CO%", "CO2%", "CH4%"] if c in cols] or ([cols[1]] if len(cols) > 1 else cols) | |
| note_lines = [f"完成！原始列數：**{original_rows}**", | |
| f"輸出列數：**{len(out)}**"] | |
| if parsed_ok is not None: | |
| note_lines.insert(1, f"可解析時間列數：**{parsed_ok}**") | |
| note_lines.insert(2, f"時間區段：**{pad_time(sh_, sm_, ss_)} → {pad_time(eh_, em_, es_)}**") | |
| note_lines.append("下方預覽、右側可下載；選欄位與樣式後繪圖。") | |
| note = "｜".join(note_lines) | |
| # 初始顯示前 N 條控制 | |
| color_updates, dash_updates, width_updates = [], [], [] | |
| for i in range(MAX_SERIES): | |
| if i < len(default_y): | |
| series = default_y[i] | |
| color_updates.append(gr.update(visible=True, value=DEFAULT_COLORS[i % len(DEFAULT_COLORS)], label=f"{series} 顏色")) | |
| dash_updates.append(gr.update(visible=True, choices=DASH_OPTIONS, value="solid", label=f"{series} 線型")) | |
| width_updates.append(gr.update(visible=True, value=2.0, label=f"{series} 線寬")) | |
| else: | |
| color_updates.append(gr.update(visible=False)) | |
| dash_updates.append(gr.update(visible=False)) | |
| width_updates.append(gr.update(visible=False)) | |
| return ( | |
| gr.update(value=out_path, visible=True), | |
| note, | |
| out.head(20), | |
| out, # df_state | |
| gr.update(choices=cols, value=default_x), | |
| gr.update(choices=cols, value=default_y), | |
| *color_updates, | |
| *dash_updates, | |
| *width_updates | |
| ) | |
| def on_y_change(y_cols): | |
| y_cols = y_cols or [] | |
| color_updates, dash_updates, width_updates = [], [], [] | |
| for i in range(MAX_SERIES): | |
| if i < len(y_cols): | |
| series = y_cols[i] | |
| color_updates.append(gr.update(visible=True, value=DEFAULT_COLORS[i % len(DEFAULT_COLORS)], label=f"{series} 顏色")) | |
| dash_updates.append(gr.update(visible=True, choices=DASH_OPTIONS, value="solid", label=f"{series} 線型")) | |
| width_updates.append(gr.update(visible=True, value=2.0, label=f"{series} 寬度")) | |
| else: | |
| color_updates.append(gr.update(visible=False)) | |
| dash_updates.append(gr.update(visible=False)) | |
| width_updates.append(gr.update(visible=False)) | |
| return (*color_updates, *dash_updates, *width_updates) | |
| def apply_palette(y_cols, palette_name): | |
| y_cols = y_cols or [] | |
| pal = PALETTES.get(palette_name, DEFAULT_COLORS) | |
| color_updates = [] | |
| for i in range(MAX_SERIES): | |
| if i < len(y_cols): | |
| color_updates.append(gr.update(visible=True, value=pal[i % len(pal)], label=f"{y_cols[i]} 顏色")) | |
| else: | |
| color_updates.append(gr.update(visible=False)) | |
| # 線型與寬度不改 | |
| dash_updates = [] | |
| width_updates = [] | |
| for i in range(MAX_SERIES): | |
| if i < len(y_cols): | |
| dash_updates.append(gr.update(visible=True, choices=DASH_OPTIONS, label=f"{y_cols[i]} 線型")) | |
| width_updates.append(gr.update(visible=True, label=f"{y_cols[i]} 寬度")) | |
| else: | |
| dash_updates.append(gr.update(visible=False)) | |
| width_updates.append(gr.update(visible=False)) | |
| return (*color_updates, *dash_updates, *width_updates) | |
| def plot_handler(df, x_col, y_cols, fig_w_, fig_h_, | |
| auto_x_, x_min_, x_max_, x_dtick_, | |
| auto_y_, y_min_, y_max_, y_dtick_, | |
| *style_values): | |
| if df is None: | |
| return None, "尚未有可用資料，請先完成上方處理。" | |
| # style_values: [colors (10), dashes (10), widths (10)] 依序 | |
| colors = list(style_values[:MAX_SERIES]) | |
| dashes = list(style_values[MAX_SERIES:MAX_SERIES*2]) | |
| widths = list(style_values[MAX_SERIES*2:MAX_SERIES*3]) | |
| try: | |
| y_cols = y_cols or [] | |
| s_map = styles_to_map(y_cols, colors, dashes, widths) | |
| fig = make_line_figure( | |
| df, x_col, y_cols, | |
| fig_w=int(fig_w_ or 900), fig_h=int(fig_h_ or 500), | |
| auto_x=bool(auto_x_), x_min=x_min_, x_max=x_max_, x_dtick=x_dtick_, | |
| auto_y=bool(auto_y_), y_min=y_min_, y_max=y_max_, y_dtick=y_dtick_, | |
| style_map=s_map | |
| ) | |
| return fig, f"完成繪圖：Y 數量 {len(y_cols)}。" | |
| except Exception as e: | |
| return None, f"繪圖失敗：{e}" | |
| # 綁定事件 | |
| base_outputs = [file_out, msg, preview, df_state, x_sel, y_sel] | |
| style_outputs = color_pickers + dash_dds + width_nums | |
| run_btn.click( | |
| run_pipeline, | |
| inputs=[inp, sh, sm, ss, eh, em, es], | |
| outputs=base_outputs + style_outputs | |
| ) | |
| # Y 變更時同步顯示/標籤 | |
| y_sel.change( | |
| on_y_change, | |
| inputs=[y_sel], | |
| outputs=style_outputs | |
| ) | |
| # 套用色盤 | |
| apply_palette_btn.click( | |
| apply_palette, | |
| inputs=[y_sel, palette_dd], | |
| outputs=style_outputs | |
| ) | |
| # 繪圖（把所有樣式控制的值傳入） | |
| plot_btn.click( | |
| plot_handler, | |
| inputs=[df_state, x_sel, y_sel, fig_w, fig_h, auto_x, x_min, x_max, x_dtick, auto_y, y_min, y_max, y_dtick] + style_outputs, | |
| outputs=[plot_out, plot_msg] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |