# ==========================================
# 気象GPV 局地分析ツール ビューワー (App B)
# VERSION INFO: 121.0 (GSM 132h以降の全要素6時間間隔・降水差分バグ完全対応版)
# ==========================================
import sys, os, glob, re, gc, time, logging
import numpy as np
import textwrap
from datetime import datetime, timedelta
import scipy.ndimage as ndimage
from PyQt6.QtWidgets import (QApplication, QMainWindow, QWidget, QVBoxLayout,
QHBoxLayout, QSlider, QPushButton, QLabel,
QTabWidget, QListWidget, QTextEdit, QComboBox, QFileDialog, QDialog,
QMessageBox, QLineEdit, QTableWidget, QTableWidgetItem, QHeaderView)
from PyQt6.QtCore import Qt, QTimer, QSettings
from PyQt6.QtGui import QColor, QFont, QCloseEvent
os.environ['QT_API'] = 'pyqt6'
import matplotlib
matplotlib.use('qtagg')
import matplotlib.colors as mcolors
import matplotlib as mpl
import matplotlib.path as mpath
import matplotlib.pyplot as plt
mpl.rcParams['font.family'] = 'MS Gothic'
from matplotlib.backends.backend_qtagg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import cartopy.io.shapereader as shpreader
STATIONS = [
("札幌", 43.060, 141.328), ("函館", 41.817, 140.753), ("室蘭", 42.315, 140.975),
("帯広", 42.922, 143.212), ("釧路", 42.985, 144.380), ("網走", 44.018, 144.279),
("稚内", 45.415, 141.680), ("旭川", 43.760, 142.360)
]
CACHED_SHAPES = {'other_cities': None, 'sapporo_districts': None, 'sapporo_city': None, 'kamikawa': None}
SHAPEFILE_FOUND = False
def search_shapefile():
paths = glob.glob('**/N03*.shp', recursive=True)
return paths[0] if paths else None
def get_simplified_geometries():
global CACHED_SHAPES, SHAPEFILE_FOUND
if CACHED_SHAPES['other_cities'] is not None: return CACHED_SHAPES['other_cities'], CACHED_SHAPES['sapporo_districts'], CACHED_SHAPES['sapporo_city'], CACHED_SHAPES['kamikawa']
shp_path = search_shapefile()
if not shp_path or not os.path.exists(shp_path): return [], [], [], []
SHAPEFILE_FOUND = True
other_cities_g = []; sapporo_districts_g = {}; sapporo_city_g = []; kamikawa_g = []
sapporo_dist_names = ['中央区', '北区', '東区', '白石区', '厚別区', '豊平区', '清田区', '南区', '西区', '手稲区']
for d_name in sapporo_dist_names: sapporo_districts_g[d_name] = []
try:
reader = shpreader.Reader(shp_path, encoding='cp932')
for r in reader.records():
geom = r.geometry
try: geom = geom.simplify(0.002, preserve_topology=False)
except: pass
pref_name = str(r.attributes.get('N03_001', '')); subpref_name = str(r.attributes.get('N03_002', ''))
city_name = str(r.attributes.get('N03_004', '')); cit_name_spec = str(r.attributes.get('N03_003', ''))
is_sap_dist = False
if '札幌市' in cit_name_spec:
for d_name in sapporo_dist_names:
if d_name == city_name: is_sap_dist = True; sapporo_districts_g[d_name].append(geom); sapporo_city_g.append(geom); break
if '上川' in subpref_name: kamikawa_g.append(geom)
if not is_sap_dist and '北海道' in pref_name:
try:
if geom.area > 0.0005: other_cities_g.append(geom)
except: pass
CACHED_SHAPES['other_cities'] = other_cities_g; CACHED_SHAPES['sapporo_districts'] = sapporo_districts_g;
CACHED_SHAPES['sapporo_city'] = sapporo_city_g; CACHED_SHAPES['kamikawa'] = kamikawa_g
return other_cities_g, sapporo_districts_g, sapporo_city_g, kamikawa_g
except Exception as e:
logging.error(f"Shapefile processing error: {e}")
return [], [], [], []
def calc_t_td(t, rh):
rh_s = np.clip(rh, 1.0, 100.0)
e = 6.112 * np.exp((17.67 * t) / (t + 243.5)) * (rh_s / 100.0)
e = np.clip(e, 0.001, 1000)
td = (243.5 * np.log(e / 6.112)) / (17.67 - np.log(e / 6.112))
return t - td
def rh_from_t_td(t, t_td):
td = t - t_td
e = 6.112 * np.exp((17.67 * td) / (td + 243.5))
es = 6.112 * np.exp((17.67 * t) / (t + 243.5))
rh = (e / es) * 100.0
return np.clip(rh, 0.0, 100.0)
def calc_ept(t, rh, p):
t_k = t + 273.15
rh_s = np.clip(rh, 1.0, 100.0)
e = 6.112 * np.exp((17.67 * t) / (t + 243.5)) * (rh_s / 100.0)
e = np.clip(e, 0.001, p - 0.1)
q = 0.622 * e / (p - e)
tlcl = 2840.0 / (3.5 * np.log(t_k) - np.log(e) - 4.805) + 55.0
theta = t_k * (1000.0 / p) ** 0.2854
ept = theta * np.exp(((3376.0 / tlcl) - 2.54) * q * (1.0 + 0.81 * q))
return ept
def get_t_from_ept(target_ept, p):
t_min, t_max = -80.0, 50.0
for _ in range(15):
t_mid = (t_min + t_max) / 2.0
ept_mid = calc_ept(t_mid, 100.0, p)
if ept_mid < target_ept: t_min = t_mid
else: t_max = t_mid
return (t_min + t_max) / 2.0
class SingleImageWindow(QDialog):
def __init__(self, parent, title, model_name, stat_name, init_z_str, canvas):
super().__init__(parent)
self.model_name = model_name; self.stat_name = stat_name; self.init_z_str = init_z_str
self.setWindowTitle(title)
self.resize(1100, 950)
self.setStyleSheet("QDialog { background-color: #0A192F; color: #E0E0E0; }")
layout = QVBoxLayout(self)
layout.setContentsMargins(10, 10, 10, 10)
layout.addWidget(canvas, stretch=1)
btn_layout = QHBoxLayout()
btn_layout.setContentsMargins(10, 10, 10, 10)
save_btn = QPushButton("📷 画像として保存")
save_btn.setStyleSheet("background-color: #27AE60; color: white; font-size: 14pt; font-weight: bold; padding: 12px; border-radius: 5px;")
save_btn.clicked.connect(self.save_image)
close_btn = QPushButton("閉じる")
close_btn.setStyleSheet("background-color: #C0392B; color: white; font-size: 14pt; font-weight: bold; padding: 12px; border-radius: 5px;")
close_btn.clicked.connect(self.accept)
btn_layout.addStretch()
btn_layout.addWidget(save_btn)
btn_layout.addWidget(close_btn)
btn_layout.addStretch()
layout.addLayout(btn_layout)
def save_image(self):
desktop = os.path.expanduser("~/Desktop")
filename = f"{self.model_name}_{self.stat_name}_{self.init_z_str}.png"
path, _ = QFileDialog.getSaveFileName(self, "画像を保存", os.path.join(desktop, filename), "Images (*.png)")
if path:
canvas_widget = self.layout().itemAt(0).widget()
pixmap = canvas_widget.grab() if hasattr(canvas_widget, 'grab') else None
if pixmap: pixmap.save(path)
else: self.layout().itemAt(0).widget().figure.savefig(path, dpi=150, bbox_inches='tight', facecolor='white')
QMessageBox.information(self, "保存完了", f"保存しました:\n{os.path.basename(path)}")
class AdminPanelDialog(QDialog):
def __init__(self, parent_app):
super().__init__(parent_app)
self.setWindowTitle("⚙️ コントロールパネル")
self.setFixedSize(500, 300)
self.setStyleSheet("""
QDialog { background-color: #0A192F; color: #E0E0E0;}
QLabel { color: #E0E0E0; font-size: 11pt; }
QPushButton { background-color: #1D3557; color: white; padding: 12px; border-radius: 5px; font-weight: bold; font-size: 12pt; margin: 5px; border: 1px solid #457B9D;}
QPushButton:hover { background-color: #457B9D; }
""")
layout = QVBoxLayout(self)
self.parent_app = parent_app
lbl = QLabel("【システム設定メニュー】")
lbl.setStyleSheet("font-size: 14pt; font-weight: bold; color: #64FFDA;")
layout.addWidget(lbl)
self.dir_lbl = QLabel(f"現在の読込先:\n{self.parent_app.cache_dir}")
self.dir_lbl.setWordWrap(True)
self.dir_lbl.setStyleSheet("color: #8892B0; font-size: 10pt;")
layout.addWidget(self.dir_lbl)
dir_btn = QPushButton("📁 読込先フォルダを変更")
dir_btn.clicked.connect(self.change_dir)
layout.addWidget(dir_btn)
sync_btn = QPushButton("🔄 画面手動強制同期")
sync_btn.clicked.connect(self.manual_sync)
layout.addWidget(sync_btn)
close_btn = QPushButton("閉じる")
close_btn.setStyleSheet("background-color: #C0392B;")
close_btn.clicked.connect(self.accept)
layout.addWidget(close_btn)
def change_dir(self):
directory = QFileDialog.getExistingDirectory(self, "GPVデータ(npz)が保存されるフォルダを選択", self.parent_app.cache_dir)
if directory:
self.parent_app.cache_dir = directory
self.parent_app.settings.setValue('cache_dir', directory)
self.parent_app.setup_logging()
self.dir_lbl.setText(f"現在の読込先:\n{directory}")
QMessageBox.information(self, "設定完了", "読込先フォルダを更新しました")
def manual_sync(self):
self.parent_app.scan_cache_dir(force_draw=True)
QMessageBox.information(self, "同期完了", "画面の強制同期を実行しました")
class SplashWindow(QWidget):
def __init__(self):
super().__init__()
self.setWindowFlags(Qt.WindowType.FramelessWindowHint | Qt.WindowType.WindowStaysOnTopHint)
self.setFixedSize(480, 250)
self.setStyleSheet("background-color: #0A192F; border: 3px solid #64FFDA; border-radius: 12px;")
layout = QVBoxLayout(self)
title_lbl = QLabel("気象GPV 局地分析ツール\n(Ver 121.0)")
title_lbl.setAlignment(Qt.AlignmentFlag.AlignCenter)
title_lbl.setStyleSheet("font-size: 18pt; font-weight: bold; color: #E0E0E0; border: none; margin-top: 15px;")
layout.addWidget(title_lbl)
msg_lbl = QLabel("最新の解析データをロードしています...\n(約5秒で自動起動します)")
msg_lbl.setAlignment(Qt.AlignmentFlag.AlignCenter)
msg_lbl.setStyleSheet("font-size: 14pt; color: #64FFDA; border: none;")
layout.addWidget(msg_lbl)
class WeatherApp(QMainWindow):
def __init__(self):
super().__init__()
self.settings = QSettings('WeatherApp', 'Viewer')
self.cache_dir = self.settings.value('cache_dir', os.path.join(os.getcwd(), "gpv_cache_npz"))
self.setup_logging()
self.setWindowTitle("気象GPV 局地分析ツール (Ver 121.0 - GSM132h以降 完全対応版)")
self.resize(1850, 1050)
self.model_init_times = {"MSM": None, "GSM_JP": None, "MSM_GUID": None, "GSM_GUID": None, "ANAL": None}
self.tab_ui = {}
self.monitor_timer = QTimer(self); self.monitor_timer.timeout.connect(self.scan_cache_dir)
self.anim_timer = QTimer(self); self.anim_timer.timeout.connect(self.anim_step)
self.current_anim_model = None
self.setStyleSheet("""
* { font-size: 13pt; font-family: "MS Gothic", sans-serif; color: #E0E0E0; }
QMainWindow, QDialog, QMessageBox { background-color: #0A192F; color: #E0E0E0; }
QMessageBox QLabel { color: #E0E0E0; }
QMessageBox QPushButton { background-color: #1D3557; color: white; padding: 5px 15px; border-radius: 3px; font-weight: bold; }
QMessageBox QPushButton:hover { background-color: #457B9D; }
QTabWidget::pane { border: 1px solid #444; background: #112240; }
QTabBar::tab { background: #1B2B4A; color: #8892B0; padding: 12px 25px; border: 1px solid #333; border-bottom: none; }
QTabBar::tab:selected { background: #112240; color: #64FFDA; font-weight: bold; border-top: 3px solid #64FFDA; }
QSlider::groove:vertical { border: 1px solid #444; background: #0A192F; width: 14px; border-radius: 7px; }
QSlider::handle:vertical { background: #64FFDA; border: 2px solid #000; height: 32px; margin: 0 -10px; border-radius: 16px; }
QPushButton { background-color: #1D3557; border: 1px solid #457B9D; padding: 8px; border-radius: 4px; color: #F1FAEE; }
QPushButton:hover { background-color: #457B9D; }
QPushButton::checked { background-color: #E63946; color: white; font-weight: bold; }
QListWidget { background: #112240; border: 1px solid #444; color: #E0E0E0; }
QListWidget::item { padding: 3px 5px; margin: 1px 5px; background: #1D3557; border: 1px solid #333; border-radius: 6px; }
QListWidget::item:selected { background: #E63946; color: white; font-weight: bold; }
QListWidget::item:hover:!selected { background: #457B9D; }
QComboBox { background: #112240; border: 1px solid #8892B0; color: white; padding: 5px; }
QComboBox QAbstractItemView { background: #112240; color: white; }
QLabel { background: transparent; }
QTextEdit { background-color: #112240; color: #64FFDA; border: 1px solid #444; }
.NavButton { background-color: #2980B9; color: white; font-weight: bold; padding: 5px; border-radius: 5px; }
.PlayButton { background-color: #27AE60; color: white; font-weight: bold; padding: 5px 15px; border-radius: 5px; }
.StopButton { background-color: #C0392B; color: white; font-weight: bold; padding: 5px 15px; border-radius: 5px; }
.SyncButton { background-color: #F39C12; color: white; font-weight: bold; border: 2px solid #D68910; border-radius: 5px; padding: 5px 15px;}
.SaveButton { background-color: #8E44AD; color: white; font-weight: bold; border-radius: 5px; padding: 4px 10px; font-size: 10pt;}
.MetaButton { background-color: #16A085; color: white; font-weight: bold; border: 2px solid #0E6655; border-radius: 5px; padding: 5px 15px; }
.MetaButton:checked { background-color: #0E6655; border: 2px solid #1ABC9C; }
.AdminButton { background-color: #34495E; color: white; font-weight: bold; border-radius: 5px; padding: 4px 10px; font-size: 10pt;}
""")
main_widget = QWidget(); self.setCentralWidget(main_widget); main_layout = QVBoxLayout(main_widget)
self.tabs = QTabWidget()
corner_widget = QWidget()
corner_layout = QHBoxLayout(corner_widget)
corner_layout.setContentsMargins(0, 0, 5, 0)
self.status_banner = QLabel("待機中...")
self.status_banner.setStyleSheet("color: white; font-weight: bold; background-color: #E63946; padding: 4px 10px; border-radius: 4px; font-size: 10pt;")
self.save_img_btn = QPushButton("📷 画面保存")
self.save_img_btn.setProperty("class", "SaveButton")
self.save_img_btn.clicked.connect(self.save_current_image)
self.admin_btn = QPushButton("⚙️ 設定")
self.admin_btn.setProperty("class", "AdminButton")
self.admin_btn.clicked.connect(self.open_admin_panel)
self.exit_app_btn = QPushButton("🛑 完全停止")
self.exit_app_btn.setProperty("class", "StopButton")
self.exit_app_btn.clicked.connect(self.close)
corner_layout.addWidget(self.status_banner)
corner_layout.addWidget(self.save_img_btn)
corner_layout.addWidget(self.admin_btn)
corner_layout.addWidget(self.exit_app_btn)
self.tabs.setCornerWidget(corner_widget, Qt.Corner.TopRightCorner)
self.setup_tab("MSM", "MSM GPV", is_guidance=False, is_anal=False)
self.setup_tab("GSM_JP", "GSM 日本域 GPV", is_guidance=False, is_anal=False)
self.setup_tab("ANAL", "毎時大気解析", is_guidance=False, is_anal=True)
self.setup_tab("MSM_GUID", "MSM ガイダンス", is_guidance=True, is_anal=False)
self.setup_tab("GSM_GUID", "GSM ガイダンス", is_guidance=True, is_anal=False)
self.setup_history_tab()
main_layout.addWidget(self.tabs)
get_simplified_geometries()
self.splash = SplashWindow()
self.splash.show()
QTimer.singleShot(5000, self.finish_startup_loading)
def closeEvent(self, event: QCloseEvent):
reply = QMessageBox.question(self, '終了の確認', 'システムを完全に停止してよろしいですか？',
QMessageBox.StandardButton.Yes | QMessageBox.StandardButton.No, QMessageBox.StandardButton.No)
if reply == QMessageBox.StandardButton.Yes:
event.accept()
else:
event.ignore()
def setup_logging(self):
self.log_file = os.path.join(self.cache_dir, "system_log.txt")
logging.basicConfig(filename=self.log_file, level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s', encoding='utf-8')
def open_admin_panel(self):
panel = AdminPanelDialog(self)
panel.exec()
def finish_startup_loading(self):
self.splash.close()
self.scan_cache_dir(quiet=True)
self.monitor_timer.start(5000)
for i in range(self.tabs.count()):
if "MSM" in self.tabs.tabText(i) and "ガイダンス" not in self.tabs.tabText(i):
self.tabs.setCurrentIndex(i); break
if "MSM" in self.tab_ui:
items = self.tab_ui["MSM"]['list'].findItems("地上気圧", Qt.MatchFlag.MatchExactly)
if items: self.tab_ui["MSM"]['list'].setCurrentItem(items[0])
self.show()
def save_current_image(self):
current_tab = self.tabs.tabText(self.tabs.currentIndex())
if "MSM ガイダンス" in current_tab: model_name = "MSM_GUID"
elif "GSM ガイダンス" in current_tab: model_name = "GSM_GUID"
elif "毎時大気" in current_tab: model_name = "ANAL"
elif "MSM" in current_tab: model_name = "MSM"
elif "日本域" in current_tab: model_name = "GSM_JP"
else: return
if model_name not in self.tab_ui or self.tab_ui[model_name]['ax'] is None: return
ui = self.tab_ui[model_name]
val = ui['slider'].value(); elem = ui['list'].currentItem().text()
it_str = self.model_init_times.get(model_name)
if not it_str: return
dt_utc = datetime.strptime(it_str, "%Y%m%d%H%M%S")
init_z = dt_utc.strftime("%m%d%H") + "Z"
filename = f"{model_name}_{elem}_{init_z}_FT{val:02d}.png"
desktop = os.path.expanduser("~/Desktop")
path, _ = QFileDialog.getSaveFileName(self, "画像を保存", os.path.join(desktop, filename), "Images (*.png *.jpg)")
if path:
ui['fig'].savefig(path, dpi=150, bbox_inches='tight', facecolor='white')
self.status_banner.setText(f"保存完了: {os.path.basename(path)}")
def init_map(self, fig, area_idx, model):
fig.clear()
ax = fig.add_subplot(1, 1, 1, projection=ccrs.PlateCarree())
ax.set_extent(self.get_extent(area_idx, model), crs=ccrs.PlateCarree())
self.draw_base_map(ax, area_idx)
fig.subplots_adjust(left=0.05, right=0.9, top=0.92, bottom=0.05)
return ax
def get_extent(self, area_index, model_name):
if area_index == 0: return [120, 150, 27.5, 48] if "MSM" in model_name or "ANAL" in model_name else [120, 150, 20, 50]
elif area_index == 1: return [138.5, 146.5, 40.5, 46.5]
elif area_index == 2: return [141.6, 143.6, 42.8, 45.0]
else: return [141.15, 141.55, 42.92, 43.20]
def crop_data(self, lon, lat, data, extent):
if lon is None or lat is None or data is None:
return np.array([]), np.array([]), np.array([])
buffer = 1.0; lon_min, lon_max = extent[0] - buffer, extent[1] + buffer; lat_min, lat_max = extent[2] - buffer, extent[3] + buffer
if lon.ndim == 1:
m_lon = (lon >= lon_min) & (lon <= lon_max); m_lat = (lat >= lat_min) & (lat <= lat_max)
if not np.any(m_lon) or not np.any(m_lat): return np.array([]), np.array([]), np.array([])
return lon[m_lon], lat[m_lat], data[np.ix_(m_lat, m_lon)]
else:
mask = (lon >= lon_min) & (lon <= lon_max) & (lat >= lat_min) & (lat <= lat_max)
j, i = np.where(mask)
if len(j) == 0: return np.array([]), np.array([]), np.array([])
return lon[j.min():j.max()+1, i.min():i.max()+1], lat[j.min():j.max()+1, i.min():i.max()+1], data[j.min():j.max()+1, i.min():i.max()+1]
def draw_base_map(self, ax, area_index):
SEA_COLOR = '#A4C2E4'; LAND_COLOR = '#F5F5F0'; COASTLINE_COLOR = '#333333'
ax.set_facecolor(SEA_COLOR); ax.add_feature(cfeature.LAND.with_scale('10m'), facecolor=LAND_COLOR, zorder=0)
ax.add_feature(cfeature.OCEAN.with_scale('10m'), facecolor=SEA_COLOR, zorder=0)
ax.add_feature(cfeature.LAKES.with_scale('10m'), edgecolor='#4682B4', facecolor=SEA_COLOR, zorder=1)
ax.add_feature(cfeature.RIVERS.with_scale('10m'), linewidth=0.8, edgecolor='#4682B4', zorder=1)
ax.add_feature(cfeature.COASTLINE.with_scale('10m'), linewidth=0.6, edgecolor=COASTLINE_COLOR, zorder=2)
other_cities_g, sapporo_districts_g, sapporo_city_g, kamikawa_g = get_simplified_geometries()
if area_index >= 1 and other_cities_g: ax.add_geometries(other_cities_g, ccrs.PlateCarree(), edgecolor='#888888', facecolor='none', linewidth=0.6, linestyle=':', zorder=3)
if area_index == 3 and sapporo_districts_g:
for d_name, geoms in sapporo_districts_g.items():
if geoms: ax.add_geometries(geoms, ccrs.PlateCarree(), edgecolor='#FF0000', facecolor='none', linewidth=1.5, zorder=10)
if sapporo_city_g and area_index == 3: ax.add_geometries(sapporo_city_g, ccrs.PlateCarree(), edgecolor='#FF0000', facecolor='#FF8C00', alpha=0.3, linewidth=2.0, linestyle='-', zorder=4)
elif sapporo_city_g and area_index >= 1: ax.add_geometries(sapporo_city_g, ccrs.PlateCarree(), edgecolor='#FF0000', facecolor='#FF8C00', alpha=0.2, linewidth=1.0, linestyle='-', zorder=4)
if area_index >= 1 and kamikawa_g: ax.add_geometries(kamikawa_g, ccrs.PlateCarree(), edgecolor='#FF0000', facecolor='#FF8C00', alpha=0.25 if area_index == 2 else 0.15, linewidth=1.5, linestyle='-', zorder=5)
pref_lines = cfeature.NaturalEarthFeature('cultural', 'admin_1_states_provinces_lines', '10m', edgecolor='#444444', facecolor='none')
ax.add_feature(pref_lines, linewidth=0.8, linestyle='-.', zorder=7)
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=True, linewidth=0.5, color='gray', alpha=0.5, linestyle='--', zorder=6)
gl.top_labels = False; gl.right_labels = False
gl.xlabel_style = {'size': 11, 'color': 'black', 'fontname': 'MS Gothic'}; gl.ylabel_style = {'size': 11, 'color': 'black', 'fontname': 'MS Gothic'}
if area_index == 3: gl.xlocator = mpl.ticker.MultipleLocator(0.05); gl.ylocator = mpl.ticker.MultipleLocator(0.05)
elif area_index == 2: gl.xlocator = mpl.ticker.MultipleLocator(0.5); gl.ylocator = mpl.ticker.MultipleLocator(0.5)
elif area_index == 1: gl.xlocator = mpl.ticker.MultipleLocator(1.0); gl.ylocator = mpl.ticker.MultipleLocator(1.0)
else: gl.xlocator = mpl.ticker.MultipleLocator(5.0) if area_index == 0 else mpl.ticker.MultipleLocator(1.0); gl.ylocator = mpl.ticker.MultipleLocator(5.0) if area_index == 0 else mpl.ticker.MultipleLocator(1.0)
def get_local_info(self, elem_name, lon, lat, data, u=None, v=None, area_index=0, model_name=""):
if data is None or lon is None or lat is None or data.size == 0: return ""
target_lon, target_lat, loc_name = (142.368, 43.760, "旭川") if area_index == 2 else (141.35, 43.06, "札幌")
if lon.ndim == 1: lon_2d, lat_2d = np.meshgrid(lon, lat)
else: lon_2d, lat_2d = lon, lat
dist = (lon_2d - target_lon)**2 + (lat_2d - target_lat)**2
sy, sx = np.unravel_index(np.argmin(dist), dist.shape)
if sy >= data.shape[0] or sx >= data.shape[1]: return ""
s_val = data[sy, sx]
if np.isnan(s_val): return ""
if "降水量" in elem_name or "降水" in elem_name: info = f"[{loc_name}現況]\n降水量: {s_val:.1f} mm"
elif "降雪量" in elem_name or "降雪" in elem_name: info = f"[{loc_name}現況]\n降雪量: {s_val:.1f} cm"
else: info = f"[{loc_name}現況]\n"
if "降水" not in elem_name and "降雪" not in elem_name:
if "気圧" in elem_name: info += f"気圧: {s_val:.1f} hPa"
elif "確率" in elem_name and "発雷" not in elem_name: info += f"{elem_name}: {s_val:.0f} %"
elif "発雷確率" in elem_name: info += f"発雷確率: {s_val:.0f} %"
elif "天気" in elem_name:
wx_map = {0: "晴", 1: "曇", 2: "雨", 3: "雪", 4: "不明"}
info += f"卓越天気: {wx_map.get(int(s_val), '不明')}"
elif "雲量" in elem_name: info += f"{elem_name}: {s_val:.1f} %"
elif "高度" in elem_name: info += f"{elem_name[:6]}高度: {s_val:.0f} m"
elif "渦度" in elem_name: info += f"正渦度(10^-5/s): {s_val:.1f}"
elif "気温" in elem_name: info += f"{elem_name[:6]}気温: {s_val:.1f} ℃"
elif "鉛直流" in elem_name: info += f"鉛直流: {s_val:.1f} hPa/h"
elif "湿数" in elem_name: info += f"{elem_name[:6]}湿数: {s_val:.1f} ℃"
elif "相当温位" in elem_name: info += f"{elem_name[:6]}相当温位: {s_val:.1f} K"
else: info += f"値: {s_val:.1f}"
if u is not None and v is not None and sy < u.shape[0] and sx < u.shape[1]: info += f"\n風速: {np.hypot(u[sy, sx], v[sy, sx]):.1f} m/s"
return info
def on_area_btn_clicked(self, model_name, idx):
ui = self.tab_ui[model_name]
for i, btn in enumerate(ui['area_btns']): btn.setChecked(i == idx)
is_meta_btn = ("メタグラム" in ui['area_btns'][-1].text() and idx == len(ui['area_btns'])-1)
if is_meta_btn:
ui['canvas'].hide()
if 'info_panel' in ui: ui['info_panel'].hide()
if 'meta_ctrl' in ui: ui['meta_ctrl'].show()
else:
if 'meta_ctrl' in ui: ui['meta_ctrl'].hide()
ui['canvas'].show()
self.draw_frame(model_name, ui['slider'].value())
def on_init_changed(self, model_name, idx):
ui = self.tab_ui[model_name]
if idx < 0: return
selected_time_str = ui['init_combo'].itemData(idx)
if selected_time_str:
self.model_init_times[model_name] = selected_time_str
self.update_slider_max(model_name, selected_time_str)
if len(ui['area_btns']) > 4 and ui['area_btns'][-2].isChecked(): return
elem_name = ui['list'].currentItem().text()
val = ui['slider'].value()
if "降水" in elem_name and val == 0 and "確率" not in elem_name and "時間降水" not in elem_name and model_name != "ANAL":
val = ui['step']
ui['slider'].blockSignals(True)
ui['slider'].setValue(val)
ui['slider'].blockSignals(False)
self.draw_frame(model_name, val)
def on_element_changed(self, model_name):
ui = self.tab_ui[model_name]
elem_name = ui['list'].currentItem().text()
if "GUID" in model_name:
min_ft = 0
if "6時間" in elem_name: min_ft = 6
elif "24時間" in elem_name: min_ft = 24
elif "3時間" in elem_name: min_ft = 3
ui['slider'].setMinimum(min_ft)
if ui['slider'].value() < min_ft:
ui['slider'].blockSignals(True)
ui['slider'].setValue(min_ft)
ui['slider'].blockSignals(False)
else:
ui['slider'].setMinimum(0)
self.on_slider_changed(model_name, ui['slider'].value())
def on_slider_changed(self, model_name, val):
self.draw_frame(model_name, val)
def update_slider_max(self, ui_key, init_time_str):
ui = self.tab_ui.get(ui_key)
if not ui: return
files = glob.glob(os.path.join(self.cache_dir, f"{ui_key}_{init_time_str}_FT*.npz"))
max_ft_found = max([0] + [int(re.search(r'_FT(\d+)\.npz', f).group(1)) for f in files if re.search(r'_FT(\d+)\.npz', f)])
hh = init_time_str[8:10] if len(init_time_str) >= 10 else '00'
if ui_key == "MSM": default_max = 78 if hh in ['00', '12'] else 39; step = 1; tick_step = 6
elif ui_key == "GSM_JP": default_max = 264 if hh in ['00', '12'] else 132; step = 3; tick_step = 12
elif ui_key == "ANAL": default_max = 0; step = 1; tick_step = 1
elif ui_key == "MSM_GUID": default_max = 84; step = 1; tick_step = 6
elif ui_key == "GSM_GUID": default_max = 84; step = 3; tick_step = 12
else: default_max = 132; step = 6; tick_step = 24
final_max = max(default_max, max_ft_found); final_max = (final_max // step) * step
ui['slider'].setMaximum(final_max)
ui['slider'].setTickInterval(step); ui['slider'].setSingleStep(step); ui['slider'].setPageStep(step)
ticks_layout = ui['ticks_layout']
for i in reversed(range(ticks_layout.count())):
w = ticks_layout.itemAt(i).widget()
if w: w.setParent(None)
if ui_key != "ANAL":
for t in range(0, final_max + 1, tick_step):
lbl = QLabel(f"{t}h"); lbl.setStyleSheet("font-size: 8pt; color: #8892B0;"); lbl.setAlignment(Qt.AlignmentFlag.AlignLeft | Qt.AlignmentFlag.AlignVCenter); ticks_layout.addWidget(lbl)
def create_compressed_left_panel(self, model_name):
left_panel = QVBoxLayout(); left_panel.setContentsMargins(5, 5, 5, 5)
step = 1 if model_name in ["MSM", "ANAL", "MSM_GUID"] else 3
left_panel.addWidget(QLabel(f"📡 {model_name} 初期時刻(UTC):", styleSheet="font-weight: bold; font-size: 11pt; color: #E0E0E0;"))
init_combo = QComboBox(); init_combo.addItem("(データ待機中...)", None); left_panel.addWidget(init_combo)
interval_label = QLabel(f"【{step}時間間隔表示】", styleSheet="color: #64FFDA; font-weight: bold; font-size: 11pt;"); left_panel.addWidget(interval_label)
mid_hbox = QHBoxLayout(); elem_vbox = QVBoxLayout(); elem_vbox.addWidget(QLabel("■ 要素選択"))
element_list = QListWidget(); element_list.setFixedWidth(200)
if "GUID" in model_name:
elems = ["卓越天気", "3時間降水量", "6時間降水量", "24時間降水量", "3時間降雪量", "6時間降雪量", "24時間降雪量", "発雷確率"]
elif model_name == "ANAL":
elems = ["地上気温", "地上風向風速", "300hpa風向・風速", "500hpa風向・風速", "500hpa気温", "700hpa気温・風", "850hpa気温・風", "925hpa気温・風", "975hpa気温・風"]
else:
elems = ["地上気圧","地上風向風速", "地上降水", "全雲量", "上層雲量", "中層雲量", "下層雲量", "300hpa高度", "300hpa風向・風速", "500hpa高度", "500hpa風向・風速", "500hpa渦度", "500hpa気温", "700hpa湿数・風", "700hpa鉛直流", "850hpa気温・風", "850hpa相当温位", "850hpa湿数・風", "925hpa相当温位", "925hpa湿数・風", "975hpa相当温位", "975hpa湿数・風"]
element_list.addItems(elems); element_list.setCurrentRow(0); elem_vbox.addWidget(element_list); mid_hbox.addLayout(elem_vbox)
slider_vbox = QVBoxLayout()
time_label = QLabel("FT=0h\n(--/--)"); time_label.setStyleSheet("font-weight: bold; color: #64FFDA; font-size: 11pt; background: #1D3557; padding: 5px; border: 2px solid #457B9D; border-radius: 5px;"); time_label.setAlignment(Qt.AlignmentFlag.AlignCenter); slider_vbox.addWidget(time_label)
slider_control_hbox = QHBoxLayout()
btn_prev = QPushButton("▲"); btn_prev.setProperty("class", "NavButton"); btn_prev.setFixedWidth(30)
btn_next = QPushButton("▼"); btn_next.setProperty("class", "NavButton"); btn_next.setFixedWidth(30)
slider = QSlider(Qt.Orientation.Vertical); slider.setRange(0, 39); slider.setTickPosition(QSlider.TickPosition.TicksLeft); slider.setTickInterval(step); slider.setSingleStep(step); slider.setPageStep(step); slider.setInvertedAppearance(True)
btn_vbox = QVBoxLayout(); btn_vbox.addWidget(slider, stretch=1); btn_vbox.setAlignment(Qt.AlignmentFlag.AlignHCenter)
nav_hbox = QHBoxLayout(); nav_hbox.addWidget(btn_prev); nav_hbox.addWidget(btn_next)
inner_slider_vbox = QVBoxLayout(); inner_slider_vbox.addLayout(nav_hbox); inner_slider_vbox.addLayout(btn_vbox); slider_control_hbox.addLayout(inner_slider_vbox)
ticks_vbox = QVBoxLayout(); ticks_vbox.setContentsMargins(0, 30, 0, 10)
slider_control_hbox.addLayout(ticks_vbox); slider_vbox.addLayout(slider_control_hbox, stretch=1)
play_hbox = QHBoxLayout()
btn_play = QPushButton("▶"); btn_play.setProperty("class", "PlayButton"); btn_play.setFixedWidth(40)
btn_stop = QPushButton("■"); btn_stop.setProperty("class", "StopButton"); btn_stop.setFixedWidth(40)
play_hbox.addWidget(btn_play); play_hbox.addWidget(btn_stop); slider_vbox.addLayout(play_hbox)
combo_speed = QComboBox(); combo_speed.addItems(["速1", "速2", "速3", "速4", "速5"]); combo_speed.setCurrentIndex(2); slider_vbox.addWidget(combo_speed)
mid_hbox.addLayout(slider_vbox); left_panel.addLayout(mid_hbox, stretch=1)
return left_panel, init_combo, interval_label, element_list, time_label, btn_prev, btn_next, slider, btn_play, btn_stop, combo_speed, ticks_vbox
def setup_tab(self, model_name, tab_title, is_guidance=False, is_anal=False):
tab = QWidget(); main_hbox = QHBoxLayout(tab)
left_panel, init_combo, interval_label, element_list, time_label, btn_prev, btn_next, slider, btn_play, btn_stop, combo_speed, ticks_layout = self.create_compressed_left_panel(model_name)
main_hbox.addLayout(left_panel, stretch=2)
right_panel = QVBoxLayout()
area_layout = QHBoxLayout(); area_layout.addWidget(QLabel("表示領域:"))
area_btns = [QPushButton("日本周辺"), QPushButton("北海道全域"), QPushButton("上川地方"), QPushButton("札幌近郊")]
for i, btn in enumerate(area_btns):
btn.setCheckable(True); area_layout.addWidget(btn); btn.clicked.connect(lambda checked, idx=i, m=model_name: self.on_area_btn_clicked(m, idx))
area_btns[0].setChecked(True)
if not is_anal:
btn_meta_text = "メタグラム表(A4画像化)" if is_guidance else f"{model_name}メタグラム"
btn_meta_draw = QPushButton(btn_meta_text)
btn_meta_draw.setProperty("class", "MetaButton")
btn_meta_draw.setCheckable(True)
area_layout.addWidget(btn_meta_draw); area_btns.append(btn_meta_draw)
btn_meta_draw.clicked.connect(lambda checked, m=model_name: self.on_area_btn_clicked(m, len(area_btns)-1))
area_layout.addStretch()
right_panel.addLayout(area_layout)
fig = Figure(figsize=(14, 13)); fig.patch.set_facecolor('white'); canvas = FigureCanvas(fig)
meta_ctrl_widget = QWidget(); meta_ctrl_layout = QVBoxLayout(meta_ctrl_widget)
h_ctrl = QHBoxLayout()
h_ctrl.addWidget(QLabel("地点選択:")); station_combo = QComboBox()
for name, lat, lon in STATIONS: station_combo.addItem(name, (lat, lon))
h_ctrl.addWidget(station_combo)
if not is_anal:
btn_text = "表示 (A4横サイズ テーブル画像生成)" if is_guidance else "表示 (図解メタグラム生成)"
btn_generate_meta = QPushButton(btn_text)
btn_generate_meta.setProperty("class", "SyncButton")
if is_guidance: btn_generate_meta.clicked.connect(lambda: self.draw_guidance_metagram(station_combo, model_name))
elif model_name == "GSM_JP": btn_generate_meta.clicked.connect(lambda: self.draw_gsm_visual_metagram(station_combo))
elif model_name == "MSM": btn_generate_meta.clicked.connect(lambda: self.draw_msm_visual_metagram(station_combo))
h_ctrl.addWidget(btn_generate_meta)
h_ctrl.addStretch()
meta_ctrl_layout.addLayout(h_ctrl); meta_ctrl_layout.addStretch(); meta_ctrl_widget.hide()
right_panel.addWidget(canvas, stretch=10)
right_panel.addWidget(meta_ctrl_widget, stretch=10)
main_hbox.addLayout(right_panel, stretch=8)
info_panel = QLabel(canvas)
info_panel.setStyleSheet("background-color: rgba(17, 34, 64, 0.85); border: 2px solid #64FFDA; border-radius: 5px; padding: 5px; font-weight: bold; font-size: 12pt; color: #E0E0E0;"); info_panel.hide()
step = 1 if model_name in ["MSM", "ANAL", "MSM_GUID"] else 3
self.tab_ui[model_name] = {
'list': element_list, 'area_btns': area_btns, 'slider': slider, 'time_label': time_label, 'init_combo': init_combo,
'interval_label': interval_label, 'fig': fig, 'canvas': canvas, 'meta_ctrl': meta_ctrl_widget, 'ax': None, 'current_area_index': -1,
'dynamic_artists': [], 'colorbars': [], 'info_panel': info_panel, 'combo_speed': combo_speed, 'ticks_layout': ticks_layout,
'step': step
}
if is_anal:
btn_play.hide(); btn_stop.hide(); combo_speed.hide()
btn_prev.hide(); btn_next.hide()
slider.hide()
for i in range(ticks_layout.count()):
w = ticks_layout.itemAt(i).widget()
if w: w.hide()
interval_label.setText("【現況解析のみ(FT=0)】")
def step_slider(val_change, m=model_name):
ui = self.tab_ui[m]; s_step = ui['step']
new_val = ui['slider'].value() + (s_step * val_change)
if new_val > ui['slider'].maximum(): new_val = ui['slider'].minimum()
if new_val < ui['slider'].minimum(): new_val = ui['slider'].maximum()
ui['slider'].setValue(new_val)
if not is_anal:
btn_prev.clicked.connect(lambda: step_slider(-1)); btn_next.clicked.connect(lambda: step_slider(1))
slider.valueChanged.connect(lambda val, m=model_name: self.on_slider_changed(m, val))
btn_play.clicked.connect(lambda: self.start_animation(model_name)); btn_stop.clicked.connect(self.stop_animation)
element_list.itemSelectionChanged.connect(lambda m=model_name: self.on_element_changed(m))
self.tabs.addTab(tab, tab_title)
def get_exact_key(self, data_obj, exact_candidates):
for c in exact_candidates:
if c in data_obj.files: return c
for k in data_obj.files:
if k.lower() in [c.lower() for c in exact_candidates]: return k
return None
def get_precip_key(self, data):
return self.get_exact_key(data, ['precip', 'pr', 'tp', 'apcp', 'prate', 'rain', 'rn', 'pop', 'var_0_1_8', 'var_0_1_52'])
def get_w_key(self, data):
return self.get_exact_key(data, ['w', 'w700', 'vvel', 'vvel700', 'dzdt', 'dzdt700'])
def get_coords_for_data(self, data_obj, data_array):
if data_array is None: return None, None
ny = data_array.shape[0]; nx = data_array.shape[1] if data_array.ndim > 1 else len(data_array)
for k in data_obj.files:
if 'lon' in k.lower():
if (data_obj[k].ndim == 1 and data_obj[k].shape[0] == nx) or (data_obj[k].ndim == 2 and data_obj[k].shape == data_array.shape):
lat_k = k.replace('lon', 'lat').replace('Lon', 'Lat')
if lat_k in data_obj.files: return data_obj[k], data_obj[lat_k]
for lk in data_obj.files:
if 'lat' in lk.lower() and ((data_obj[lk].ndim == 1 and data_obj[lk].shape[0] == ny) or data_obj[lk].shape == data_array.shape):
return data_obj[k], data_obj[lk]
return None, None
def extract_val_with_key(self, data, key, stat_lon, stat_lat):
if key not in data.files: return np.nan
arr = data[key]
lon_arr, lat_arr = self.get_coords_for_data(data, arr)
if lon_arr is None or lat_arr is None:
lon_k = next((k for k in data.files if 'lon' in k.lower()), None)
lat_k = next((k for k in data.files if 'lat' in k.lower()), None)
if not lon_k or not lat_k: return np.nan
lon_arr, lat_arr = data[lon_k], data[lat_k]
if lon_arr.ndim == 1 and arr.shape == (len(lon_arr), len(lat_arr)):
arr = arr.T
if lon_arr.ndim == 1 and arr.shape != (len(lat_arr), len(lon_arr)):
if arr.shape[1] > arr.shape[0] and len(lat_arr) > len(lon_arr):
arr = arr.T
lon_arr = np.linspace(lon_arr.min(), lon_arr.max(), arr.shape[1])
lat_arr = np.linspace(lat_arr.min(), lat_arr.max(), arr.shape[0])
if lon_arr.ndim == 1: lon_2d, lat_2d = np.meshgrid(lon_arr, lat_arr)
else: lon_2d, lat_2d = lon_arr, lat_arr
dist = (lon_2d - stat_lon)**2 + (lat_2d - stat_lat)**2
sy, sx = np.unravel_index(np.argmin(dist), dist.shape)
if sy < arr.shape[0] and sx < arr.shape[1]:
v = arr[sy, sx]
if np.isnan(v) or v > 200000 or v < -10000: return np.nan
return float(v)
return np.nan
def extract_val_robust(self, data, keys, stat_lon, stat_lat):
k = self.get_exact_key(data, keys)
if not k:
for dk in data.files:
if any(x in dk.lower() for x in keys):
k = dk; break
if not k: return np.nan
return self.extract_val_with_key(data, k, stat_lon, stat_lat)
# --- MSM用メタグラム ---
def draw_msm_visual_metagram(self, station_combo):
it_str = self.model_init_times.get("MSM")
if not it_str:
QMessageBox.warning(self, "エラー", "データが存在しません。"); return
stat_name = station_combo.currentText(); stat_lat, stat_lon = station_combo.currentData()
dt_utc = datetime.strptime(it_str, "%Y%m%d%H%M%S") # UTC
dt_jst = dt_utc + timedelta(hours=9)
init_z_str = f"{dt_utc.strftime('%m%d%H')}Z"
title_time_str = f"{dt_utc.strftime('%m月%d日%H')}Z / {dt_jst.strftime('%H')}JST"
max_ft = self.tab_ui['MSM']['slider'].maximum()
fts_surf = list(range(0, max_ft + 1))
fts_prof = [ft for ft in fts_surf if ft % 3 == 0]
plevs = [1000, 975, 950, 925, 850, 700, 600, 500, 300]; y_coords = [0.0, 0.05, 0.1, 0.15, 0.25, 0.5, 0.625, 0.75, 1.0]
T_prof = np.full((len(plevs), len(fts_prof)), np.nan); RH_prof = np.full((len(plevs), len(fts_prof)), np.nan)
U_prof = np.full((len(plevs), len(fts_prof)), np.nan); V_prof = np.full((len(plevs), len(fts_prof)), np.nan)
SSI_850_series = np.full(len(fts_prof), np.nan); SSI_700_series = np.full(len(fts_prof), np.nan); SSI_925_series = np.full(len(fts_prof), np.nan)
P_surf_series = np.full(len(fts_surf), np.nan); T_surf_series = np.full(len(fts_surf), np.nan); Pr_surf_series = np.full(len(fts_surf), np.nan)
for c_idx, ft in enumerate(fts_surf):
gpv_file = os.path.join(self.cache_dir, f"MSM_{it_str}_FT{ft:02d}.npz")
if not os.path.exists(gpv_file): continue
try:
d = np.load(gpv_file)
P_surf_series[c_idx] = self.extract_val_robust(d, ['prmsl', 'mslet', 'msl', 'slp'], stat_lon, stat_lat)
if not np.isnan(P_surf_series[c_idx]) and P_surf_series[c_idx] > 2000: P_surf_series[c_idx] /= 100.0
T_surf_series[c_idx] = self.extract_val_robust(d, ['t2m', 'tmp2m', 'temp2m'], stat_lon, stat_lat)
if not np.isnan(T_surf_series[c_idx]) and T_surf_series[c_idx] > 100: T_surf_series[c_idx] -= 273.15
p_key = self.get_precip_key(d)
if p_key:
pr = self.extract_val_with_key(d, p_key, stat_lon, stat_lat)
Pr_surf_series[c_idx] = pr if not np.isnan(pr) else 0.0
else:
Pr_surf_series[c_idx] = 0.0
d.close()
except Exception as e: logging.error(f"Error reading {gpv_file}: {e}")
for c_idx, ft in enumerate(fts_prof):
gpv_file = os.path.join(self.cache_dir, f"MSM_{it_str}_FT{ft:02d}.npz")
if not os.path.exists(gpv_file): continue
try:
d = np.load(gpv_file)
t2m = self.extract_val_robust(d, ['t2m', 'tmp2m', 'temp2m'], stat_lon, stat_lat)
if not np.isnan(t2m) and t2m > 100: t2m -= 273.15
T_prof[0, c_idx] = t2m
RH_prof[0, c_idx] = self.extract_val_robust(d, ['rh2m', 'r2m'], stat_lon, stat_lat)
U_prof[0, c_idx] = self.extract_val_robust(d, ['u10', '10u', 'u_10m'], stat_lon, stat_lat)
V_prof[0, c_idx] = self.extract_val_robust(d, ['v10', '10v', 'v_10m'], stat_lon, stat_lat)
h_map = {975:1, 950:2, 925:3, 850:4, 700:5, 600:6, 500:7, 300:8}
for p_lvl, idx in h_map.items():
t_val = self.extract_val_robust(d, [f't{p_lvl}', f'tmp{p_lvl}', f't_{p_lvl}', f'tmp_{p_lvl}'], stat_lon, stat_lat)
if not np.isnan(t_val) and t_val > 100: t_val -= 273.15
rh_val = self.extract_val_robust(d, [f'rh{p_lvl}', f'r{p_lvl}', f'rh_{p_lvl}', f'r_{p_lvl}'], stat_lon, stat_lat)
if np.isnan(rh_val) and not np.isnan(t_val):
t_td = self.extract_val_robust(d, [f't_td{p_lvl}', f'dew{p_lvl}'], stat_lon, stat_lat)
if not np.isnan(t_td): rh_val = rh_from_t_td(t_val, t_td)
T_prof[idx, c_idx] = rh_val if not np.isnan(rh_val) else 0.0
T_prof[idx, c_idx] = t_val
RH_prof[idx, c_idx] = rh_val if not np.isnan(rh_val) else 0.0
U_prof[idx, c_idx] = self.extract_val_robust(d, [f'u{p_lvl}', f'u_{p_lvl}'], stat_lon, stat_lat)
V_prof[idx, c_idx] = self.extract_val_robust(d, [f'v{p_lvl}', f'v_{p_lvl}'], stat_lon, stat_lat)
t925 = T_prof[3, c_idx]; rh925 = RH_prof[3, c_idx]
t850 = T_prof[4, c_idx]; rh850 = RH_prof[4, c_idx]
t700 = T_prof[5, c_idx]; rh700 = RH_prof[5, c_idx]
t500 = T_prof[7, c_idx]
if not np.isnan(t500):
if not np.isnan(t850) and not np.isnan(rh850):
SSI_850_series[c_idx] = t500 - get_t_from_ept(calc_ept(t850, rh850, 850), 500)
if not np.isnan(t700) and not np.isnan(rh700):
SSI_700_series[c_idx] = t500 - get_t_from_ept(calc_ept(t700, rh700, 700), 500)
if not np.isnan(t700) and not np.isnan(t925) and not np.isnan(rh925):
SSI_925_series[c_idx] = t700 - get_t_from_ept(calc_ept(t925, rh925, 925), 700)
d.close()
except: pass
fig = Figure(figsize=(10, 16)); fig.patch.set_facecolor('white')
fig.subplots_adjust(left=0.08, right=0.98, top=0.92, bottom=0.08, hspace=0.65)
fig.suptitle(f"MSM 図解メタグラム - {stat_name} (初期時: {title_time_str})", fontsize=14, weight='bold', y=0.97)
gs = fig.add_gridspec(14, 1)
ax_cross = fig.add_subplot(gs[0:5, 0]); ax_slp = fig.add_subplot(gs[5:7, 0], sharex=ax_cross)
ax_t2m = fig.add_subplot(gs[7:9, 0], sharex=ax_cross); ax_pr = fig.add_subplot(gs[9:11, 0], sharex=ax_cross)
ax_ssi = fig.add_subplot(gs[11:14, 0], sharex=ax_cross)
X_prof, Y_prof = np.meshgrid(fts_prof, y_coords)
cmap = mcolors.ListedColormap(['#E8F8F5', '#A3E4D7', '#48C9B0', '#117A65'])
bounds = [70, 80, 90, 95, 100]; norm = mcolors.BoundaryNorm(bounds, cmap.N)
cf = ax_cross.contourf(X_prof, Y_prof, RH_prof, levels=bounds, cmap=cmap, norm=norm, extend='max', alpha=0.6)
cs = ax_cross.contour(X_prof, Y_prof, T_prof, levels=np.arange(-60, 40, 6), colors='red', linewidths=1.0, alpha=0.7)
ax_cross.clabel(cs, inline=True, fontsize=9, fmt='%1.0f')
cs_zero = ax_cross.contour(X_prof, Y_prof, T_prof, levels=[0], colors='blue', linewidths=2.0)
ax_cross.clabel(cs_zero, inline=True, fontsize=10, fmt='0℃')
ax_cross.barbs(X_prof[:, ::1], Y_prof[:, ::1], U_prof[:, ::1], V_prof[:, ::1], length=4.5, color='black', linewidth=0.6)
ax_cross.set_yticks(y_coords); ax_cross.set_yticklabels([str(p) for p in plevs])
ax_cross.set_ylabel("気\n圧\n\n[hPa]", weight='bold', rotation=0, labelpad=10, va='center')
ax_cross.set_title("湿域・気温・風 断面図 (3時間毎)", loc='left', weight='bold')
ax_slp.plot(fts_surf, P_surf_series, color='#2980B9', marker='s', markersize=3, linestyle='-', linewidth=2, label="海面気圧")
ax_slp.set_ylabel("海\n面\n気\n圧\n\n[hPa]", color='#2980B9', weight='bold', rotation=0, labelpad=10, va='center')
ax_slp.legend(loc='upper left')
ax_top_jst = ax_slp.twiny()
ax_top_jst.set_xlim(ax_slp.get_xlim())
ax_top_jst.set_xticks(range(0, fts_surf[-1]+1, 6))
jsts = [(dt_jst + timedelta(hours=x)).strftime("%d日%H時") for x in range(0, fts_surf[-1]+1, 6)]
ax_top_jst.set_xticklabels(jsts, fontsize=9, color='#333333', weight='bold')
ax_t2m.plot(fts_surf, T_surf_series, color='#E74C3C', marker='o', markersize=3, linestyle='-', linewidth=2, label="地上気温")
ax_t2m.set_ylabel("地\n上\n気\n温\n\n[℃]", color='#E74C3C', weight='bold', rotation=0, labelpad=10, va='center')
ax_t2m.legend(loc='upper left')
ax_pr.bar(fts_surf, Pr_surf_series, width=0.6, color='#3498DB', alpha=0.9, label="期間降水量 (1時間積算)")
ax_pr.set_ylabel("降\n水\n量\n\n[mm]", color='#3498DB', weight='bold', rotation=0, labelpad=10, va='center')
ax_pr.legend(loc='upper left')
ax_pr.axhline(0, color='gray', linewidth=1.0)
ax_ssi.plot(fts_prof, SSI_850_series, color='#C0392B', marker='o', markersize=4, linestyle='-', linewidth=2, label="SSI (850-500)")
ax_ssi.plot(fts_prof, SSI_700_series, color='#E67E22', marker='^', markersize=4, linestyle='-', linewidth=2, label="SSI (700-500)")
ax_ssi.plot(fts_prof, SSI_925_series, color='#8E44AD', marker='s', markersize=4, linestyle='-', linewidth=2, label="SSI (925-700)")
ax_ssi.axhline(0, color='gray', linestyle=':', linewidth=1)
ax_ssi.set_ylabel("Ｓ\nＳ\nＩ\n\n[℃]", weight='bold', rotation=0, labelpad=10, va='center')
ax_ssi.set_xlabel("予報時間 (FT)", weight='bold', fontsize=12)
ax_ssi.legend(loc='lower left')
for ax in [ax_cross, ax_slp, ax_t2m, ax_pr, ax_ssi]:
ax.set_xlim(fts_surf[0]-1, fts_surf[-1]+1)
ax.set_xticks(range(0, fts_surf[-1]+1, 6))
ax.grid(True, axis='x', color='gray', linestyle='--', alpha=0.5)
ax.grid(True, axis='y', color='gray', linestyle='--', alpha=0.3)
if ax != ax_ssi:
plt.setp(ax.get_xticklabels(), visible=False)
ax_top = ax_cross.twiny()
ax_top.set_xlim(ax_cross.get_xlim())
ax_top.set_xticks(range(0, fts_surf[-1]+1, 6))
ax_top.set_xticklabels([f"FT{x}" for x in range(0, fts_surf[-1]+1, 6)], fontsize=10, weight='bold')
plt.setp(ax_ssi.get_xticklabels(), rotation=45, ha='right', fontsize=11)
fig.align_ylabels([ax_cross, ax_slp, ax_t2m, ax_pr, ax_ssi])
canvas = FigureCanvas(fig)
win = SingleImageWindow(self, f"MSM 図解メタグラム - {stat_name}", "MSM", stat_name, init_z_str, canvas)
win.exec()
# --- GSM用メタグラム (修正済み) ---
def draw_gsm_visual_metagram(self, station_combo):
it_str = self.model_init_times.get("GSM_JP")
if not it_str:
QMessageBox.warning(self, "エラー", "データが存在しません。"); return
stat_name = station_combo.currentText(); stat_lat, stat_lon = station_combo.currentData()
dt_utc = datetime.strptime(it_str, "%Y%m%d%H%M%S") # UTC
dt_jst = dt_utc + timedelta(hours=9)
init_z_str = f"{dt_utc.strftime('%m%d%H')}Z"
title_time_str = f"{dt_utc.strftime('%m月%d日%H')}Z / {dt_jst.strftime('%H')}JST"
max_ft = self.tab_ui['GSM_JP']['slider'].maximum()
fts = list(range(0, max_ft + 1, 3))
plevs = [1000, 975, 950, 925, 850, 700, 600, 500, 300]; y_coords = [0.0, 0.05, 0.1, 0.15, 0.25, 0.5, 0.625, 0.75, 1.0]
T_prof = np.full((len(plevs), len(fts)), np.nan); RH_prof = np.full((len(plevs), len(fts)), np.nan)
U_prof = np.full((len(plevs), len(fts)), np.nan); V_prof = np.full((len(plevs), len(fts)), np.nan)
SSI_850_series = np.full(len(fts), np.nan); SSI_700_series = np.full(len(fts), np.nan); SSI_925_series = np.full(len(fts), np.nan)
P_surf_series = np.full(len(fts), np.nan); T_surf_series = np.full(len(fts), np.nan); Pr_surf_series = np.full(len(fts), np.nan)
# 修正: 132h以降は地上・上空とも6時間間隔になるため、全て disp_ft にフォールバックして処理
for c_idx, ft in enumerate(fts):
disp_ft = ft if ft <= 132 or ft % 6 == 0 else ft - (ft % 6)
gpv_file = os.path.join(self.cache_dir, f"GSM_JP_{it_str}_FT{disp_ft:02d}.npz")
if os.path.exists(gpv_file):
try:
d = np.load(gpv_file)
P_surf_series[c_idx] = self.extract_val_robust(d, ['prmsl', 'mslet', 'msl', 'slp'], stat_lon, stat_lat)
if not np.isnan(P_surf_series[c_idx]) and P_surf_series[c_idx] > 2000: P_surf_series[c_idx] /= 100.0
T_surf_series[c_idx] = self.extract_val_robust(d, ['t2m', 'tmp2m', 'temp2m'], stat_lon, stat_lat)
if not np.isnan(T_surf_series[c_idx]) and T_surf_series[c_idx] > 100: T_surf_series[c_idx] -= 273.15
# 修正: 132h以降の降水差分計算エラー防止
p_key = self.get_precip_key(d)
if p_key:
pr = self.extract_val_with_key(d, p_key, stat_lon, stat_lat)
if disp_ft >= 3:
offset = 6 if disp_ft > 132 else 3
prev_file = os.path.join(self.cache_dir, f"GSM_JP_{it_str}_FT{disp_ft-offset:02d}.npz")
if os.path.exists(prev_file):
try:
with np.load(prev_file) as d_prev:
prev_p_key = self.get_precip_key(d_prev)
if prev_p_key:
prev_pr = self.extract_val_with_key(d_prev, prev_p_key, stat_lon, stat_lat)
if not np.isnan(prev_pr): pr = max(0, pr - prev_pr)
except: pass
Pr_surf_series[c_idx] = pr if not np.isnan(pr) else 0.0
else:
Pr_surf_series[c_idx] = 0.0
# 上空データ
T_prof[0, c_idx] = T_surf_series[c_idx] if not np.isnan(T_surf_series[c_idx]) else self.extract_val_robust(d, ['t2m', 'tmp2m', 'temp2m'], stat_lon, stat_lat)
RH_prof[0, c_idx] = self.extract_val_robust(d, ['rh2m', 'r2m'], stat_lon, stat_lat)
U_prof[0, c_idx] = self.extract_val_robust(d, ['u10', '10u', 'u_10m'], stat_lon, stat_lat)
V_prof[0, c_idx] = self.extract_val_robust(d, ['v10', '10v', 'v_10m'], stat_lon, stat_lat)
h_map = {975:1, 950:2, 925:3, 850:4, 700:5, 600:6, 500:7, 300:8}
for p_lvl, idx in h_map.items():
t_val = self.extract_val_robust(d, [f't{p_lvl}', f'tmp{p_lvl}', f't_{p_lvl}'], stat_lon, stat_lat)
if not np.isnan(t_val) and t_val > 100: t_val -= 273.15
rh_val = self.extract_val_robust(d, [f'rh{p_lvl}', f'r{p_lvl}', f'rh_{p_lvl}'], stat_lon, stat_lat)
if np.isnan(rh_val) and not np.isnan(t_val):
t_td = self.extract_val_robust(d, [f't_td{p_lvl}', f'dew{p_lvl}'], stat_lon, stat_lat)
if not np.isnan(t_td): rh_val = rh_from_t_td(t_val, t_td)
T_prof[idx, c_idx] = t_val
RH_prof[idx, c_idx] = rh_val if not np.isnan(rh_val) else 0.0
U_prof[idx, c_idx] = self.extract_val_robust(d, [f'u{p_lvl}', f'u_{p_lvl}'], stat_lon, stat_lat)
V_prof[idx, c_idx] = self.extract_val_robust(d, [f'v{p_lvl}', f'v_{p_lvl}'], stat_lon, stat_lat)
t925 = T_prof[3, c_idx]; rh925 = RH_prof[3, c_idx]
t850 = T_prof[4, c_idx]; rh850 = RH_prof[4, c_idx]
t700 = T_prof[5, c_idx]; rh700 = RH_prof[5, c_idx]
t500 = T_prof[7, c_idx]
if not np.isnan(t500):
if not np.isnan(t850) and not np.isnan(rh850):
SSI_850_series[c_idx] = t500 - get_t_from_ept(calc_ept(t850, rh850, 850), 500)
if not np.isnan(t700) and not np.isnan(rh700):
SSI_700_series[c_idx] = t500 - get_t_from_ept(calc_ept(t700, rh700, 700), 500)
if not np.isnan(t700) and not np.isnan(t925) and not np.isnan(rh925):
SSI_925_series[c_idx] = t700 - get_t_from_ept(calc_ept(t925, rh925, 925), 700)
d.close()
except: pass
fig = Figure(figsize=(15, 12)); fig.patch.set_facecolor('white')
fig.subplots_adjust(left=0.08, right=0.98, top=0.91, bottom=0.08, hspace=0.65)
fig.suptitle(f"GSM_JP 図解メタグラム - {stat_name} (初期時: {title_time_str})", fontsize=14, weight='bold', y=0.97)
gs = fig.add_gridspec(12, 1); ax_cross = fig.add_subplot(gs[0:4, 0]); ax_slp = fig.add_subplot(gs[4:6, 0], sharex=ax_cross)
ax_t2m = fig.add_subplot(gs[6:8, 0], sharex=ax_cross); ax_pr = fig.add_subplot(gs[8:10, 0], sharex=ax_cross); ax_ssi = fig.add_subplot(gs[10:12, 0], sharex=ax_cross)
X, Y = np.meshgrid(fts, y_coords)
cmap = mcolors.ListedColormap(['#E8F8F5', '#A3E4D7', '#48C9B0', '#117A65'])
bounds = [70, 80, 90, 95, 100]; norm = mcolors.BoundaryNorm(bounds, cmap.N)
cf = ax_cross.contourf(X, Y, RH_prof, levels=bounds, cmap=cmap, norm=norm, extend='max', alpha=0.6)
cs = ax_cross.contour(X, Y, T_prof, levels=np.arange(-60, 40, 6), colors='red', linewidths=1.0, alpha=0.7)
ax_cross.clabel(cs, inline=True, fontsize=9, fmt='%1.0f')
cs_zero = ax_cross.contour(X, Y, T_prof, levels=[0], colors='blue', linewidths=2.0)
ax_cross.clabel(cs_zero, inline=True, fontsize=10, fmt='0℃')
ax_cross.barbs(X[:, ::1], Y[:, ::1], U_prof[:, ::1], V_prof[:, ::1], length=4.5, color='black', linewidth=0.6)
ax_cross.set_yticks(y_coords); ax_cross.set_yticklabels([str(p) for p in plevs])
ax_cross.set_ylabel("気\n圧\n\n[hPa]", weight='bold', rotation=0, labelpad=10, va='center'); ax_cross.set_title("湿域・気温・風 断面図 (※132h以降は全要素6時間間隔で補間展開)", loc='left', weight='bold')
ax_slp.plot(fts, P_surf_series, color='#2980B9', marker='s', markersize=4, linestyle='-', linewidth=2, label="海面気圧")
ax_slp.set_ylabel("海\n面\n気\n圧\n\n[hPa]", color='#2980B9', weight='bold', rotation=0, labelpad=10, va='center')
ax_slp.legend(loc='upper left')
ax_top_jst = ax_slp.twiny()
ax_top_jst.set_xlim(ax_slp.get_xlim())
ax_top_jst.set_xticks(range(0, fts[-1]+1, 12))
jsts = [(dt_jst + timedelta(hours=x)).strftime("%d日%H時") for x in range(0, fts[-1]+1, 12)]
ax_top_jst.set_xticklabels(jsts, fontsize=9, color='#333333', weight='bold')
ax_t2m.plot(fts, T_surf_series, color='#E74C3C', marker='o', markersize=4, linestyle='-', linewidth=2, label="地上気温")
ax_t2m.set_ylabel("地\n上\n気\n温\n\n[℃]", color='#E74C3C', weight='bold', rotation=0, labelpad=10, va='center')
ax_t2m.legend(loc='upper left')
ax_pr.bar(fts, Pr_surf_series, width=1.8, color='#3498DB', alpha=0.9, label="期間降水量 (差分)")
ax_pr.set_ylabel("降\n水\n量\n\n[mm]", color='#3498DB', weight='bold', rotation=0, labelpad=10, va='center')
ax_pr.legend(loc='upper left')
ax_pr.axhline(0, color='gray', linewidth=1.0)
ax_ssi.plot(fts, SSI_850_series, color='#C0392B', marker='o', markersize=4, linestyle='-', linewidth=2, label="SSI (850-500)")
ax_ssi.plot(fts, SSI_700_series, color='#E67E22', marker='^', markersize=4, linestyle='-', linewidth=2, label="SSI (700-500)")
ax_ssi.plot(fts, SSI_925_series, color='#8E44AD', marker='s', markersize=4, linestyle='-', linewidth=2, label="SSI (925-700)")
ax_ssi.axhline(0, color='gray', linestyle=':', linewidth=1)
ax_ssi.set_ylabel("Ｓ\nＳ\nＩ\n\n[℃]", weight='bold', rotation=0, labelpad=10, va='center')
ax_ssi.set_xlabel("予報時間 (FT)", weight='bold', fontsize=12)
ax_ssi.legend(loc='lower left')
for ax in [ax_cross, ax_slp, ax_t2m, ax_pr, ax_ssi]:
ax.set_xlim(fts[0]-1, fts[-1]+1)
ax.set_xticks(range(0, fts[-1]+1, 12))
ax.grid(True, axis='x', color='gray', linestyle='--', alpha=0.5)
ax.grid(True, axis='y', color='gray', linestyle='--', alpha=0.3)
if ax != ax_ssi:
plt.setp(ax.get_xticklabels(), visible=False)
ax_top = ax_cross.twiny()
ax_top.set_xlim(ax_cross.get_xlim())
ax_top.set_xticks(range(0, fts[-1]+1, 12))
ax_top.set_xticklabels([f"FT{x}" for x in range(0, fts[-1]+1, 12)], fontsize=10, weight='bold')
plt.setp(ax_ssi.get_xticklabels(), rotation=45, ha='right', fontsize=11)
fig.align_ylabels([ax_cross, ax_slp, ax_t2m, ax_pr, ax_ssi])
canvas = FigureCanvas(fig)
win = SingleImageWindow(self, f"GSM_JP 図解メタグラム - {stat_name}", "GSM_JP", stat_name, init_z_str, canvas)
win.exec()
def draw_guidance_metagram(self, station_combo, model_name):
it_str = self.model_init_times.get(model_name)
if not it_str:
QMessageBox.warning(self, "エラー", "データが存在しません。"); return
stat_name = station_combo.currentText(); stat_lat, stat_lon = station_combo.currentData()
dt_utc = datetime.strptime(it_str, "%Y%m%d%H%M%S") # UTC
fig = Figure(figsize=(11.69, 8.27)); fig.patch.set_facecolor('white')
ax = fig.add_subplot(111); ax.axis('off')
table_data = []
headers = ["FT", "日時(JST)", "卓越天気", "降水量", "降雪量", "発雷確率", "気温(℃)", "風向", "風速(m/s)"]
max_ft = self.tab_ui[model_name]['slider'].maximum()
fts = list(range(0, max_ft + 1, 3))
gpv_model = "MSM" if model_name == "MSM_GUID" else "GSM_JP"
gpv_it_str = self.model_init_times.get(gpv_model)
for ft in fts:
target_jst = dt_utc + timedelta(hours=9+ft)
row = [f"FT={ft:02d}", target_jst.strftime("%m/%d %H:00"), "-", "-", "-", "-", "-", "-", "-"]
guid_file = os.path.join(self.cache_dir, f"{model_name}_{it_str}_FT{ft:02d}.npz")
if os.path.exists(guid_file):
try:
d = np.load(guid_file)
pop = self.extract_val_robust(d, ['precip', 'tp', 'apcp', 'pop', 'var_0_1_8', 'var_0_1_52'], stat_lon, stat_lat)
pos = self.extract_val_robust(d, ['snow', 'weasd', 'snod', 'var_0_1_11', 'var_0_1_13', 'var_0_1_29'], stat_lon, stat_lat)
pol = self.extract_val_robust(d, ['thund', 'pol', 'lig', 'thunder', 'tstm', 'var_0_19_193'], stat_lon, stat_lat)
wx = self.extract_val_robust(d, ['wea', 'weather', 'wx', 'var_-1_-1_-1', 'var_0_19_192'], stat_lon, stat_lat)
if not np.isnan(wx): row[2] = {0:"晴", 1:"曇", 2:"雨", 3:"雪"}.get(int(wx), "不明")
if not np.isnan(pop): row[3] = f"{pop:.1f} mm"
if not np.isnan(pos): row[4] = f"{pos:.1f} cm"
if not np.isnan(pol): row[5] = f"{pol:.0f} %"
d.close()
except: pass
if gpv_it_str:
gpv_ft = ft
if gpv_model == "GSM_JP" and ft > 132:
gpv_ft = ft - (ft % 6) if ft % 6 != 0 else ft
gpv_file = os.path.join(self.cache_dir, f"{gpv_model}_{gpv_it_str}_FT{gpv_ft:02d}.npz")
if os.path.exists(gpv_file):
try:
d = np.load(gpv_file)
t = self.extract_val_robust(d, ['t2m', 'tmp2m', 'temp2m'], stat_lon, stat_lat)
if not np.isnan(t): row[6] = f"{(t - 273.15 if t > 100 else t):.1f}"
u = self.extract_val_robust(d, ['u10', '10u', 'u_10m'], stat_lon, stat_lat)
v = self.extract_val_robust(d, ['v10', '10v', 'v_10m'], stat_lon, stat_lat)
if not np.isnan(u) and not np.isnan(v):
row[8] = f"{np.hypot(u, v):.1f}"
deg = (np.degrees(np.arctan2(u, v)) + 180) % 360
dirs = ["北", "北北東", "北東", "東北東", "東", "東南東", "南東", "南南東", "南", "南南西", "南西", "西南西", "西", "西北西", "北西", "北北西", "北"]
row[7] = dirs[int(round(deg / 22.5)) % 16]
d.close()
except: pass
table_data.append(row)
table = ax.table(cellText=table_data, colLabels=headers, loc='center', cellLoc='center')
table.auto_set_font_size(False)
table.set_fontsize(10)
table.scale(1, 1.4)
for j in range(len(headers)):
cell = table[0, j]
cell.set_facecolor('#1D3557')
cell.get_text().set_color('white')
cell.get_text().set_weight('bold')
fig.suptitle(f"{stat_name} 統合ガイダンス時系列表 (初期時: {dt_utc.strftime('%m/%d %H:00Z')})", fontsize=15, weight='bold', y=0.96)
canvas = FigureCanvas(fig)
win = SingleImageWindow(self, f"GUID_{stat_name}", model_name, stat_name, dt_utc.strftime("%m%d%H") + "Z", canvas)
win.exec()
def plot_contour(self, ax, lon, lat, data, ui, levels, color, extent, linewidths=1.5):
lon_c, lat_c, data_c = self.crop_data(lon, lat, data, extent)
if lon_c.size == 0 or lat_c.size == 0 or data_c.size == 0: return None
cs = ax.contour(lon_c, lat_c, data_c, levels=levels, colors=color, linewidths=linewidths, transform=ccrs.PlateCarree(), zorder=7)
ui['dynamic_artists'].append(cs); ax.clabel(cs, inline=True, fontsize=11, fmt='%1.0f'); return cs
def plot_contourf(self, ax, lon, lat, data, ui, levels, cmap_or_colors, extent, extend='both', alpha=0.6, norm=None):
lon_c, lat_c, data_c = self.crop_data(lon, lat, data, extent)
if lon_c.size == 0 or lat_c.size == 0 or data_c.size == 0: return None
kwargs = {'levels': levels, 'extend': extend, 'transform': ccrs.PlateCarree(), 'alpha': alpha, 'zorder': 6}
if isinstance(cmap_or_colors, str) or isinstance(cmap_or_colors, mcolors.Colormap): kwargs['cmap'] = cmap_or_colors
else: kwargs['colors'] = cmap_or_colors
if norm is not None: kwargs['norm'] = norm
cf = ax.contourf(lon_c, lat_c, data_c, **kwargs)
ui['dynamic_artists'].append(cf)
return cf
def plot_blocky(self, ax, lon, lat, data, ui, cmap_or_colors, extent, norm=None, alpha=0.85):
lon_c, lat_c, data_c = self.crop_data(lon, lat, data, extent)
if lon_c.size == 0 or lat_c.size == 0 or data_c.size == 0: return None
if lon_c.ndim == 1:
lon_c, lat_c = np.meshgrid(lon_c, lat_c)
kwargs = {'transform': ccrs.PlateCarree(), 'alpha': alpha, 'zorder': 6, 'shading': 'nearest'}
if isinstance(cmap_or_colors, str) or isinstance(cmap_or_colors, mcolors.Colormap): kwargs['cmap'] = cmap_or_colors
else: kwargs['cmap'] = mcolors.ListedColormap(cmap_or_colors)
if norm is not None: kwargs['norm'] = norm
pm = ax.pcolormesh(lon_c, lat_c, data_c, **kwargs)
ui['dynamic_artists'].append(pm)
return pm
def plot_barbs(self, ax, lon, lat, u, v, ui, area_index, extent, model_name=""):
lon_c, lat_c, u_c = self.crop_data(lon, lat, u, extent)
_, _, v_c = self.crop_data(lon, lat, v, extent)
if lon_c.size == 0 or lat_c.size == 0 or u_c.size == 0 or v_c.size == 0: return None
u_c = np.nan_to_num(u_c, nan=0.0); v_c = np.nan_to_num(v_c, nan=0.0)
if lon_c.ndim == 1: lon_2d, lat_2d = np.meshgrid(lon_c, lat_c)
else: lon_2d, lat_2d = lon_c, lat_c
if lon_2d.shape != u_c.shape: return None
if area_index == 0: skip = 20
elif area_index == 3: skip = 1
elif area_index == 2: skip = 1
elif "MSM" in model_name or "ANAL" in model_name: skip = 4
else: skip = 3
q = ax.barbs(lon_2d[::skip,::skip], lat_2d[::skip,::skip], u_c[::skip,::skip], v_c[::skip,::skip], length=5.5, color='black', transform=ccrs.PlateCarree(), zorder=10)
ui['dynamic_artists'].append(q)
def show_error_msg(self, ax, ui, msg):
wrapped_msg = "\n".join(textwrap.wrap(msg, width=50))
txt = ax.text(0.5, 0.5, wrapped_msg, transform=ax.transAxes, color='red', fontsize=12, ha='center', va='center', weight='bold', bbox=dict(facecolor='white', alpha=0.9, edgecolor='red'))
ui['dynamic_artists'].append(txt)
def draw_guidance(self, ax, ui, data, elem_name, val, extent, area_index, model_name, it_str):
drawn_flag = False; info_text = ""
def _cl(arr, minv, maxv, fill=0.0):
if arr is None: return None
a = np.array(arr, dtype=float)
a = np.nan_to_num(a, nan=fill, posinf=fill, neginf=fill)
return np.clip(a, minv, maxv)
def add_vertical_colorbar(mappable, label_text):
cax = ui['fig'].add_axes([0.89, 0.15, 0.02, 0.7])
cb = ui['fig'].colorbar(mappable, cax=cax, orientation='vertical')
cb.set_label(label_text, fontsize=12, weight='bold'); ui['colorbars'].append(cb)
if "降水量" in elem_name or "降雪量" in elem_name:
accum_hours = 3
if "6時間" in elem_name: accum_hours = 6
elif "24時間" in elem_name: accum_hours = 24
accum_val = None; valid_data = False; lon_c = None; lat_c = None
for hr_offset in range(0, accum_hours, 3):
target_ft = val - hr_offset
if target_ft <= 0: continue
d_curr = None
if target_ft == val: d_curr = data
else:
target_file = os.path.join(self.cache_dir, f"{model_name}_{it_str}_FT{target_ft:02d}.npz")
if os.path.exists(target_file):
try: d_curr = np.load(target_file)
except: pass
if d_curr is not None:
if "降水量" in elem_name: key = self.get_exact_key(d_curr, ['precip', 'tp', 'apcp', 'pop', 'var_0_1_8', 'var_0_1_52'])
else: key = self.get_exact_key(d_curr, ['snow', 'weasd', 'snod', 'var_0_1_11', 'var_0_1_13', 'var_0_1_29', 'asnow'])
if key:
v = _cl(d_curr[key], 0, 1000, 0.0)
if accum_val is None:
accum_val = v.copy()
lon_c, lat_c = self.get_coords_for_data(d_curr, v)
valid_data = True
else:
accum_val += v
if target_ft != val: d_curr.close()
if valid_data and accum_val is not None:
accum_val_masked = np.ma.masked_less(accum_val, 0.1)
levels = [0.1, 1, 5, 10, 20, 30, 50, 80]
if "降水量" in elem_name:
cmap = mcolors.ListedColormap(['#A0E8A0', '#D4F05A', '#FFFF00', '#FFA500', '#FF5500', '#FF0000', '#FF00FF'])
cmap.set_under('none'); cmap.set_over('#800080')
label_text = f'降水量 ({accum_hours}時間積算) [mm]'
else:
cmap = mcolors.ListedColormap(['#E8EAF6', '#C5CAE9', '#9FA8DA', '#7986CB', '#5C6BC0', '#3F51B5', '#303F9F'])
cmap.set_under('none'); cmap.set_over('#1A237E')
label_text = f'降雪量 ({accum_hours}時間積算) [cm等]'
norm = mcolors.BoundaryNorm(levels, cmap.N)
pm = self.plot_blocky(ax, lon_c, lat_c, accum_val_masked, ui, cmap, extent, norm=norm, alpha=0.45)
if pm:
add_vertical_colorbar(pm, label_text)
stat_lon = 141.35; stat_lat = 43.06
if lon_c.ndim == 1: lon_2d, lat_2d = np.meshgrid(lon_c, lat_c)
else: lon_2d, lat_2d = lon_c, lat_c
dist = (lon_2d - stat_lon)**2 + (lat_2d - stat_lat)**2
sy, sx = np.unravel_index(np.argmin(dist), dist.shape)
local_val = accum_val[sy, sx] if (sy < accum_val.shape[0] and sx < accum_val.shape[1]) else np.nan
info_text = f"[札幌現況]\n降水量({accum_hours}h): {local_val:.1f} mm" if "降水" in elem_name else f"[札幌現況]\n降雪量({accum_hours}h): {local_val:.1f} cm"
drawn_flag = True
if area_index == 3:
lc, lac, dc = self.crop_data(lon_c, lat_c, accum_val, extent)
if lc.size > 0:
l2, la2 = np.meshgrid(lc, lac) if lc.ndim == 1 else (lc, lac)
min_lon, max_lon, min_lat, max_lat = extent
try:
import scipy.ndimage as ndimage
import matplotlib.patheffects as pe
zoom_factor = 8 if "GSM" in model_name else 2
dc_z = ndimage.zoom(dc, zoom_factor, order=1)
if lc.ndim == 1:
lc_z = ndimage.zoom(lc, zoom_factor, order=1)
lac_z = ndimage.zoom(lac, zoom_factor, order=1)
l2_z, la2_z = np.meshgrid(lc_z, lac_z)
else:
l2_z = ndimage.zoom(l2, zoom_factor, order=1)
la2_z = ndimage.zoom(la2, zoom_factor, order=1)
for r in range(dc_z.shape[0]):
for c in range(dc_z.shape[1]):
lon_v, lat_v, val_p = l2_z[r, c], la2_z[r, c], dc_z[r, c]
if r % zoom_factor == 0 and c % zoom_factor == 0: continue
if val_p >= 0.1 and min_lon <= lon_v <= max_lon and min_lat <= lat_v <= max_lat:
txt = ax.text(lon_v, lat_v, f"{val_p:.1f}", color='#1f77b4', fontsize=10, ha='center', va='center', transform=ccrs.PlateCarree(), zorder=12, weight='bold', clip_on=True, path_effects=[pe.withStroke(linewidth=2, foreground='white')])
ui['dynamic_artists'].append(txt)
for r in range(dc.shape[0]):
for c in range(dc.shape[1]):
lon_v, lat_v, val_p = l2[r, c], la2[r, c], dc[r, c]
if val_p >= 0.1 and min_lon <= lon_v <= max_lon and min_lat <= lat_v <= max_lat:
txt = ax.text(lon_v, lat_v, f"{val_p:.1f}", color='black', fontsize=11, ha='center', va='center', transform=ccrs.PlateCarree(), zorder=13, weight='bold', bbox=dict(facecolor='white', edgecolor='black', boxstyle='square,pad=0.2', alpha=0.9), clip_on=True)
ui['dynamic_artists'].append(txt)
except Exception as e:
print(f"内挿描画エラー: {e}")
elif "発雷" in elem_name:
key = None
for k in data.files:
if any(x in k.lower() for x in ['thund', 'pol', 'lig', 'ts', 'tstm', 'var_0_19_193']): key = k; break
if key:
try:
val_data = _cl(data[key], 0, 100, 0.0)
lon_c, lat_c = self.get_coords_for_data(data, val_data)
if lon_c is None or lat_c is None:
lon_k = next((k for k in data.files if 'lon' in k.lower()), None)
lat_k = next((k for k in data.files if 'lat' in k.lower()), None)
if lon_k and lat_k: lon_c, lat_c = data[lon_k], data[lat_k]
if lon_c is not None and lat_c is not None:
if lon_c.ndim == 1 and val_data.shape == (len(lon_c), len(lat_c)):
val_data = val_data.T
if lon_c.ndim == 1 and val_data.shape != (len(lat_c), len(lon_c)):
if val_data.shape[1] > val_data.shape[0] and len(lat_c) > len(lon_c):
val_data = val_data.T
lon_c = np.linspace(lon_c.min(), lon_c.max(), val_data.shape[1])
lat_c = np.linspace(lat_c.min(), lat_c.max(), val_data.shape[0])
val_masked = np.ma.masked_less(val_data, 1.0)
levels = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
cmap = mcolors.ListedColormap(['#FFF3E0', '#FFE0B2', '#FFCC80', '#FFB74D', '#FFA726', '#FF9800', '#FB8C00', '#F57C00', '#EF6C00'])
cmap.set_under('none')
norm = mcolors.BoundaryNorm(levels, cmap.N)
pm = self.plot_blocky(ax, lon_c, lat_c, val_masked, ui, cmap, extent, norm=norm, alpha=0.6)
if pm:
add_vertical_colorbar(pm, '発雷確率 [%]')
info_text = self.get_local_info(elem_name, lon_c, lat_c, val_data, area_index=area_index, model_name=model_name)
drawn_flag = True
except Exception as e:
print(f"平面地図発雷描画エラー: {e}")
elif "天気" in elem_name:
key = None
for k in data.files:
if any(x in k.lower() for x in ['wea', 'wx', 'var_-1_-1_-1', 'var_0_19_192']): key = k; break
if key:
val_data = _cl(data[key], 0, 4, 0.0)
lon_c, lat_c = self.get_coords_for_data(data, val_data)
if lon_c is None or lat_c is None:
lon_k = next((k for k in data.files if 'lon' in k.lower()), None)
lat_k = next((k for k in data.files if 'lat' in k.lower()), None)
if lon_k and lat_k: lon_c, lat_c = data[lon_k], data[lat_k]
if lon_c is not None and lat_c is not None:
if lon_c.ndim == 1 and val_data.shape == (len(lon_c), len(lat_c)):
val_data = val_data.T
levels = [-0.5, 0.5, 1.5, 2.5, 3.5]
colors = ['#FFD700', '#B0C4DE', '#1E90FF', '#FFFFFF']
cmap_wx = mcolors.ListedColormap(colors); norm_wx = mcolors.BoundaryNorm(levels, cmap_wx.N)
pm = self.plot_blocky(ax, lon_c, lat_c, val_data, ui, cmap_wx, extent, norm=norm_wx, alpha=0.6)
if pm:
add_vertical_colorbar(pm, '卓越天気 (0:晴 1:曇 2:雨 3:雪)')
info_text = self.get_local_info(elem_name, lon_c, lat_c, val_data, area_index=area_index, model_name=model_name)
drawn_flag = True
return drawn_flag, info_text
def extract_2d_array(self, data, exact_keys, target_level=None, fuzzy_keys=None):
for k in exact_keys:
if k in data.files:
arr = np.squeeze(data[k])
if arr.ndim == 2: return arr
if fuzzy_keys:
for k in data.files:
kl = k.lower()
if any(fk in kl for fk in fuzzy_keys) and not any(ex in kl for ex in ['lon', 'lat', 'time', 'valid']):
arr = np.squeeze(data[k])
if arr.ndim == 2: return arr
if arr.ndim == 3 and target_level is not None:
levels_16 = [1000, 925, 850, 700, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, 10]
levels_msm = [1000, 975, 950, 925, 900, 850, 800, 700, 600, 500, 400, 300]
axis = 0 if arr.shape[0] < arr.shape[1] else 2
sz = arr.shape[axis]
if sz == len(levels_16) and target_level in levels_16:
return arr[levels_16.index(target_level),:,:] if axis == 0 else arr[:,:,levels_16.index(target_level)]
elif sz == len(levels_msm) and target_level in levels_msm:
return arr[levels_msm.index(target_level),:,:] if axis == 0 else arr[:,:,levels_msm.index(target_level)]
return None
def draw_frame(self, model_name, val):
ui = self.tab_ui[model_name]; it_str = self.model_init_times.get(model_name)
if not it_str:
self.show_error_msg(ui['ax'] if ui['ax'] else self.init_map(ui['fig'], 0, model_name), ui, f"{model_name} のデータがありません。")
ui['canvas'].draw_idle(); return
elem_name = ui['list'].currentItem().text()
display_val = val
fallback_msg = ""
# 修正: GSM 132h以降のフォールバックロジックを【全要素（地上・上空とも）】に適用
if model_name == "GSM_JP" and val > 132 and val % 6 != 0:
display_val = val - (val % 6)
fallback_msg = f" (※132h以降は全要素6時間間隔のため FT={display_val}h を代替表示)"
elif model_name == "MSM" and "hpa" in elem_name.lower() and val % 3 != 0:
display_val = (val // 3) * 3
fallback_msg = f" (※上空データ3時間間隔のため FT={display_val}h を代替表示)"
if "GUID" in model_name and "気温" not in elem_name and "風" not in elem_name:
if val % 3 != 0:
display_val = (val // 3) * 3
fallback_msg += f" (※3時間間隔データのため FT={display_val}h を代替表示)"
dt_utc = datetime.strptime(it_str, "%Y%m%d%H%M%S")
dt_jst = dt_utc + timedelta(hours=9)
target_time = dt_jst + timedelta(hours=val)
ui['time_label'].setText(f"FT={val:02d}h\n({target_time.strftime('%m/%d %H:00')})")
area_index = next(i for i, btn in enumerate(ui['area_btns']) if btn.isChecked())
if ui['ax'] is None or ui['current_area_index'] != area_index:
ui['ax'] = self.init_map(ui['fig'], area_index, model_name)
ui['current_area_index'] = area_index
ax = ui['ax']
extent = self.get_extent(area_index, model_name)
while ui['dynamic_artists']:
art = ui['dynamic_artists'].pop(0)
try:
if hasattr(art, 'collections'):
for c in art.collections:
try: c.remove()
except: pass
else: art.remove()
except: pass
for cb in ui['colorbars']:
try: cb.remove()
except: pass
ui['colorbars'].clear(); ui['info_panel'].hide()
# The code `ax.title.set` appears to be incomplete and does not perform any specific action.
# It seems like there might be a typo or missing part of the code. If you provide more context
# or complete the code snippet, I can help you understand its purpose.
ax.title.set_text(f"[{model_name}] {elem_name} / 初期時刻(UTC): {dt_utc.strftime('%m/%d %H:00Z')} / FT={val}h ({target_time.strftime('%m/%d %H:00')} JST){fallback_msg}")
target_file = os.path.join(self.cache_dir, f"{model_name}_{it_str}_FT{display_val:02d}.npz")
print(f"DEBUG: 読み込み試行 -> FT={display_val} / {target_file}")
if not os.path.exists(target_file):
if "降水" in elem_name and val == 0 and "確率" not in elem_name and "時間降水" not in elem_name and model_name != "ANAL": self.show_error_msg(ax, ui, "【初期時のためデータなし】")
else: self.show_error_msg(ax, ui, f"データが存在しません (FT={display_val}h)")
ui['canvas'].draw_idle(); return
try:
data = np.load(target_file)
lon_key = self.get_exact_key(data, ['lon_surf', 'lon', 'lon_p', 'lon_pall'])
lat_key = self.get_exact_key(data, ['lat_surf', 'lat', 'lat_p', 'lat_pall'])
if not lon_key or not lat_key:
self.show_error_msg(ax, ui, f"[!] {elem_name} の座標データが見つかりません。(キー: {data.files})")
data.close(); ui['canvas'].draw_idle(); return
def add_vertical_colorbar(mappable, label_text):
cax = ui['fig'].add_axes([0.89, 0.15, 0.02, 0.7])
cb = ui['fig'].colorbar(mappable, cax=cax, orientation='vertical')
cb.set_label(label_text, fontsize=12, weight='bold'); ui['colorbars'].append(cb)
def _cl(arr, minv, maxv, fill=0.0):
if arr is None: return None
a = np.array(arr, dtype=float)
a = np.nan_to_num(a, nan=fill, posinf=fill, neginf=fill)
return np.clip(a, minv, maxv)
drawn_flag = False; info_text = ""
if "GUID" in model_name:
drawn_flag, info_text = self.draw_guidance(ax, ui, data, elem_name, val, extent, area_index, model_name, it_str)
elif elem_name == "地上気温":
t_val = self.extract_2d_array(data, ['t2m', 'tmp2m', 'temp2m'], fuzzy_keys=['tmp', 'temp', 't'])
if t_val is not None:
if np.nanmax(t_val) > 100: t_val = t_val - 273.15
t_val = _cl(t_val, -50, 40, 0.0)
lon_c, lat_c = self.get_coords_for_data(data, t_val)
cf = self.plot_contourf(ax, lon_c, lat_c, t_val, ui, np.arange(-30, 40, 3), 'jet', extent, extend='both', alpha=0.4)
self.plot_contour(ax, lon_c, lat_c, t_val, ui, np.arange(-30, 40, 3), 'black', extent, linewidths=0.5)
if cf:
add_vertical_colorbar(cf, '地上気温 [℃]')
info_text = self.get_local_info(elem_name, lon_c, lat_c, t_val, area_index=area_index, model_name=model_name); drawn_flag = True
elif elem_name == "地上気圧":
slp = self.extract_2d_array(data, ['prmsl', 'mslet', 'msl', 'slp'], fuzzy_keys=['msl', 'prmsl'])
if slp is not None:
if np.nanmax(slp) > 2000: slp = slp / 100.0
slp_hpa = _cl(slp, 800, 1150, 1013.0)
lon_c, lat_c = self.get_coords_for_data(data, slp_hpa)
import scipy.ndimage as ndimage
slp_smooth = ndimage.gaussian_filter(slp_hpa, sigma=1.0)
levels = np.arange(940, 1060, 4)
cs = self.plot_contour(ax, lon_c, lat_c, slp_smooth, ui, levels, '#2980B9', extent)
if cs: info_text += self.get_local_info("気圧", lon_c, lat_c, slp, area_index=area_index, model_name=model_name); drawn_flag = True
elif elem_name == "地上風向風速":
u_val = self.extract_2d_array(data, ['u10', '10u', 'u_10m'], fuzzy_keys=['u10', 'u_wind'])
v_val = self.extract_2d_array(data, ['v10', '10v', 'v_10m'], fuzzy_keys=['v10', 'v_wind'])
if u_val is not None and v_val is not None:
u_val = _cl(u_val, -200, 200, 0.0); v_val = _cl(v_val, -200, 200, 0.0)
spd = np.hypot(u_val, v_val); lon_c, lat_c = self.get_coords_for_data(data, spd)
levels = [2, 4, 6, 8, 10, 15, 20, 25]; colors = ['#E0F7FA', '#B2EBF2', '#4DD0E1', '#00BCD4', '#00838F', '#9C27B0', '#4A148C']
cf = self.plot_contourf(ax, lon_c, lat_c, spd, ui, levels, colors, extent, extend='max', alpha=0.5)
if cf:
add_vertical_colorbar(cf, '地上風速 [m/s]')
self.plot_barbs(ax, lon_c, lat_c, u_val, v_val, ui, area_index, extent, model_name)
info_text = self.get_local_info("風向風速", lon_c, lat_c, spd, u_val, v_val, area_index=area_index, model_name=model_name); drawn_flag = True
elif "地上降水" in elem_name:
p_key = self.get_precip_key(data)
if p_key:
pval = _cl(data[p_key], 0, 1000, 0.0)
# 修正: GSM 132h以降の降水量差分計算 (引くファイルを6時間前へ変更し、valではなくdisplay_valを使用)
if model_name == "GSM_JP" and display_val >= 3:
offset = 6 if display_val > 132 else 3
prev_file = os.path.join(self.cache_dir, f"{model_name}_{it_str}_FT{display_val-offset:02d}.npz")
if os.path.exists(prev_file):
try:
with np.load(prev_file) as d_prev:
prev_p_key = self.get_precip_key(d_prev)
if prev_p_key:
prev_pval = _cl(d_prev[prev_p_key], 0, 1000, 0.0)
if prev_pval.shape == pval.shape: pval = np.clip(pval - prev_pval, 0, None)
except: pass
lon_c, lat_c = self.get_coords_for_data(data, pval)
if pval.ndim == 1 and lon_c.ndim == 1 and lat_c.ndim == 1 and pval.size == len(lat_c) * len(lon_c):
pval = pval.reshape((len(lat_c), len(lon_c)))
import scipy.ndimage as ndimage
pval_smooth = ndimage.gaussian_filter(pval, sigma=0.2)
pval_smooth = np.ma.masked_less(pval_smooth, 0.1)
levels = [0.1, 1, 5, 10, 20, 30, 50, 80]
cmap_precip = mcolors.ListedColormap(['#A0E8A0', '#D4F05A', '#FFFF00', '#FFA500', '#FF5500', '#FF0000', '#FF00FF'])
cmap_precip.set_under('none'); cmap_precip.set_over('#800080')
norm_precip = mcolors.BoundaryNorm(levels, cmap_precip.N)
cf = self.plot_contourf(ax, lon_c, lat_c, pval_smooth, ui, levels, cmap_precip, extent, extend='max', alpha=0.85, norm=norm_precip)
if cf:
self.plot_contour(ax, lon_c, lat_c, pval_smooth, ui, levels, '#444444', extent, linewidths=0.5)
add_vertical_colorbar(cf, f'降水量 [mm]')
info_text = self.get_local_info("降水", lon_c, lat_c, pval, area_index=area_index, model_name=model_name); drawn_flag = True
else:
if display_val != 0 or model_name == "ANAL":
self.show_error_msg(ax, ui, f"[!] 降水キー不明。\nデータが未収録の可能性があります。")
drawn_flag = True
elif "雲量" in elem_name:
c_val = None
if elem_name == "全雲量": c_val = self.extract_2d_array(data, ['tcc', 'tcdc', 'lcdc', 'cloud', 'hcc', 'mcc', 'lcc'], fuzzy_keys=['tcc'])
elif elem_name == "上層雲量": c_val = self.extract_2d_array(data, ['hcc', 'hcdc', 'high', 'tcc'], fuzzy_keys=['hcc', 'high'])
elif elem_name == "中層雲量": c_val = self.extract_2d_array(data, ['mcc', 'mcdc', 'mid', 'tcc'], fuzzy_keys=['mcc', 'mid'])
elif elem_name == "下層雲量": c_val = self.extract_2d_array(data, ['lcc', 'lcdc', 'low', 'tcc'], fuzzy_keys=['lcc', 'low'])
if c_val is not None:
c_val = _cl(c_val, 0, 150, 0.0)
lon_c, lat_c = self.get_coords_for_data(data, c_val)
if np.nanmax(c_val) <= 1.0 and np.nanmax(c_val) > 0: c_val = c_val * 100.0
levels = [20, 30, 40, 50, 60, 70, 80, 90, 100]
cmap_cloud = mcolors.ListedColormap(['#D9D9D9', '#BDBDBD', '#969696', '#737373', '#525252', '#252525', '#0F0F0F', '#000000'])
cmap_cloud.set_under('none'); cmap_cloud.set_over('#000000'); norm_cloud = mcolors.BoundaryNorm(levels, cmap_cloud.N)
cf = self.plot_contourf(ax, lon_c, lat_c, c_val, ui, levels, cmap_cloud, extent, extend='max', alpha=0.7, norm=norm_cloud)
if cf:
add_vertical_colorbar(cf, f'{elem_name} [%]'); info_text = self.get_local_info(elem_name, lon_c, lat_c, c_val, area_index=area_index, model_name=model_name); drawn_flag = True
elif "300hpa高度" in elem_name:
h_val = self.extract_2d_array(data, ['gh300', 'hgt300', 'hgt_300'], 300, ['hgt', 'gh', 'z'])
if h_val is not None:
h_val = _cl(h_val, -500, 20000, 0.0); lon_p, lat_p = self.get_coords_for_data(data, h_val)
levels = np.arange(8400, 10800, 60); cf = self.plot_contourf(ax, lon_p, lat_p, h_val, ui, levels, 'PuBu', extent, alpha=0.6)
self.plot_contour(ax, lon_p, lat_p, h_val, ui, levels, 'darkblue', extent)
if cf: add_vertical_colorbar(cf, '300hPa 高度 [m]'); info_text = self.get_local_info(elem_name, lon_p, lat_p, h_val, area_index=area_index, model_name=model_name); drawn_flag = True
elif "300hpa風向・風速" in elem_name:
u_val = self.extract_2d_array(data, ['u300', 'u_300'], 300, ['u', 'ugrd'])
v_val = self.extract_2d_array(data, ['v300', 'v_300'], 300, ['v', 'vgrd'])
if u_val is not None and v_val is not None:
u_val = _cl(u_val, -300, 300, 0.0); v_val = _cl(v_val, -300, 300, 0.0)
spd = np.hypot(u_val, v_val); lon_p, lat_p = self.get_coords_for_data(data, spd)
levels = [20, 30, 40, 50, 60, 80, 100]
cf = self.plot_contourf(ax, lon_p, lat_p, spd, ui, levels, 'YlOrRd', extent, extend='max', alpha=0.35)
self.plot_barbs(ax, lon_p, lat_p, u_val, v_val, ui, area_index, extent, model_name)
if cf: add_vertical_colorbar(cf, '300hPa 風速 [m/s]'); info_text = self.get_local_info(elem_name, lon_p, lat_p, spd, u_val, v_val, area_index=area_index, model_name=model_name); drawn_flag = True
elif "500hpa高度" in elem_name or "500hPa高度" in elem_name:
h_val = self.extract_2d_array(data, ['gh500', 'hgt500', 'hgt_500'], 500, ['hgt', 'gh', 'z'])
if h_val is not None:
h_val = _cl(h_val, -500, 20000, 0.0); lon_p, lat_p = self.get_coords_for_data(data, h_val)
levels = np.arange(4800, 6000, 60); cf = self.plot_contourf(ax, lon_p, lat_p, h_val, ui, levels, 'Greens', extent, alpha=0.6)
self.plot_contour(ax, lon_p, lat_p, h_val, ui, levels, 'darkgreen', extent)
if cf: add_vertical_colorbar(cf, '500hPa 高度 [m]'); info_text = self.get_local_info(elem_name, lon_p, lat_p, h_val, area_index=area_index, model_name=model_name); drawn_flag = True
elif "500hpa風向・風速" in elem_name:
u_val = self.extract_2d_array(data, ['u500', 'u_500'], 500, ['u', 'ugrd'])
v_val = self.extract_2d_array(data, ['v500', 'v_500'], 500, ['v', 'vgrd'])
if u_val is not None and v_val is not None:
u_val = _cl(u_val, -300, 300, 0.0); v_val = _cl(v_val, -300, 300, 0.0)
spd = np.hypot(u_val, v_val); lon_p, lat_p = self.get_coords_for_data(data, spd)
levels = [10, 20, 30, 40, 50, 60, 80]
cf = self.plot_contourf(ax, lon_p, lat_p, spd, ui, levels, 'YlOrRd', extent, extend='max', alpha=0.35)
self.plot_barbs(ax, lon_p, lat_p, u_val, v_val, ui, area_index, extent, model_name)
if cf: add_vertical_colorbar(cf, '500hPa 風速 [m/s]'); info_text = self.get_local_info(elem_name, lon_p, lat_p, spd, u_val, v_val, area_index=area_index, model_name=model_name); drawn_flag = True
elif "500hpa渦度" in elem_name:
vort = self.extract_2d_array(data, ['vort500', 'vort', 'abs_vort'], 500, ['vort', 'abs_vort'])
if vort is not None:
vort = _cl(vort, -1000, 1000, 0.0); lon_p, lat_p = self.get_coords_for_data(data, vort)
levels = [-50, -20, 0, 20, 40, 60, 80, 100, 150, 200]
colors = ['#ffffff', '#fdf0e6', '#fad7a1', '#f8c471', '#f39c12', '#d35400', '#c0392b', '#922b21', '#641e16']
cf = self.plot_contourf(ax, lon_p, lat_p, vort, ui, levels, colors, extent, extend='both', alpha=0.5)
self.plot_contour(ax, lon_p, lat_p, vort, ui, levels, '#4A235A', extent)
if cf: add_vertical_colorbar(cf, '500hPa 正渦度 [10^-5/s]'); info_text = self.get_local_info(elem_name, lon_p, lat_p, vort, area_index=area_index, model_name=model_name); drawn_flag = True
elif "hpa気温" in elem_name.lower():
w = re.search(r'(\d+)hpa', elem_name.lower())
if w:
lvl = int(w.group(1))
t_val = self.extract_2d_array(data, [f't{lvl}', f'tmp{lvl}', f't_{lvl}', f'tmp_{lvl}'], lvl, ['tmp', 'temp', 't'])
if t_val is not None:
if np.nanmax(t_val) > 100: t_val = t_val - 273.15
t_val = _cl(t_val, -100, 60, 0.0); lon_p, lat_p = self.get_coords_for_data(data, t_val)
cf = self.plot_contourf(ax, lon_p, lat_p, t_val, ui, np.arange(-54, 40, 3), 'jet', extent, extend='both', alpha=0.3)
self.plot_contour(ax, lon_p, lat_p, t_val, ui, np.arange(-54, 40, 3), 'blue', extent, linewidths=0.5)
if cf:
add_vertical_colorbar(cf, f'{lvl}hPa 気温 [℃]')
lon_c, lat_c, t_c = self.crop_data(lon_p, lat_p, t_val, extent)
if lon_c.size > 0:
cs = ax.contour(lon_c if lon_c.ndim==1 else lon_c,
lat_c if lat_c.ndim==1 else lat_c,
t_c, levels=[-36, -6, 0, 15, 30], colors='red', linewidths=2.0, transform=ccrs.PlateCarree(), zorder=8)
ui['dynamic_artists'].append(cs); ax.clabel(cs, inline=True, fontsize=12, fmt='%1.0f')
u_val = self.extract_2d_array(data, [f'u{lvl}', f'u_{lvl}'], lvl, ['u', 'ugrd'])
v_val = self.extract_2d_array(data, [f'v{lvl}', f'v_{lvl}'], lvl, ['v', 'vgrd'])
if u_val is not None: u_val = _cl(u_val, -200, 200, 0.0)
if v_val is not None: v_val = _cl(v_val, -200, 200, 0.0)
info_text = self.get_local_info(elem_name, lon_p, lat_p, t_val, u_val, v_val, area_index=area_index, model_name=model_name)
drawn_flag = True
if u_val is not None and v_val is not None: self.plot_barbs(ax, lon_p, lat_p, u_val, v_val, ui, area_index, extent, model_name)
elif "700hpa湿数" in elem_name:
t = self.extract_2d_array(data, ['t700', 'tmp700', 't_700'], 700, ['tmp', 'temp', 't'])
rh_raw = self.extract_2d_array(data, ['rh700', 'r700', 'rh_700'], 700, ['rh', 'hum', 'r'])
if t is not None and rh_raw is not None:
if np.nanmax(t) > 100: t = t - 273.15
rh = _cl(rh_raw, 0, 150, 0.0)
if np.nanmax(rh) <= 1.0 and np.nanmax(rh) > 0: rh = rh * 100.0
lon_p, lat_p = self.get_coords_for_data(data, t); t_td = calc_t_td(t, rh)
levels = [0, 3, 6, 9, 12, 15]; colors = ['#27AE60', '#82E0AA', '#D5F5E3', '#F9E79F', '#F5CBA7', '#E74C3C']
cf = self.plot_contourf(ax, lon_p, lat_p, t_td, ui, levels, colors, extent, extend='max', alpha=0.35)
u_val = self.extract_2d_array(data, ['u700', 'u_700'], 700, ['u', 'ugrd'])
v_val = self.extract_2d_array(data, ['v700', 'v_700'], 700, ['v', 'vgrd'])
if u_val is not None: u_val = _cl(u_val, -200, 200, 0.0)
if v_val is not None: v_val = _cl(v_val, -200, 200, 0.0)
if cf:
add_vertical_colorbar(cf, '700hPa 湿数 [℃]')
info_text = self.get_local_info("湿数", lon_p, lat_p, t_td, u_val, v_val, area_index=area_index, model_name=model_name); drawn_flag = True
if u_val is not None and v_val is not None: self.plot_barbs(ax, lon_p, lat_p, u_val, v_val, ui, area_index, extent, model_name)
elif "700hpa鉛直流" in elem_name:
w_val = self.extract_2d_array(data, ['w', 'w700', 'vvel', 'vvel700', 'dzdt', 'dzdt700'], 700, ['w', 'vvel', 'dzdt'])
if w_val is not None:
if np.nanmax(np.abs(w_val)) < 15.0: w_val = w_val * 36.0
w_val = _cl(w_val, -500, 500, 0.0); lon_p, lat_p = self.get_coords_for_data(data, w_val)
import scipy.ndimage as ndimage
w_val = ndimage.gaussian_filter(w_val, sigma=0.8)
w_val_masked = np.ma.masked_inside(w_val, -4.9, 4.9)
levels = [-50, -30, -20, -10, -5, 5, 10, 20, 30, 50]
cf = self.plot_contourf(ax, lon_p, lat_p, w_val_masked, ui, levels, 'PiYG', extent, extend='both', alpha=0.8)
if cf: add_vertical_colorbar(cf, '700hPa 鉛直流 [hPa/h]'); info_text = self.get_local_info(elem_name, lon_p, lat_p, w_val, area_index=area_index, model_name=model_name); drawn_flag = True
elif "850hpa相当温位" in elem_name:
t = self.extract_2d_array(data, ['t850', 'tmp850', 't_850'], 850, ['tmp', 'temp', 't'])
rh_raw = self.extract_2d_array(data, ['rh850', 'r850', 'rh_850'], 850, ['rh', 'hum', 'r'])
if t is not None and rh_raw is not None:
if np.nanmax(t) > 100: t = t - 273.15
rh = _cl(rh_raw, 0, 150, 0.0)
if np.nanmax(rh) <= 1.0 and np.nanmax(rh) > 0: rh = rh * 100.0
lon_p, lat_p = self.get_coords_for_data(data, t); ept = calc_ept(t, rh, 850); levels = np.arange(270, 360, 6)
cf = self.plot_contourf(ax, lon_p, lat_p, ept, ui, levels, 'rainbow', extent, extend='both', alpha=0.6)
self.plot_contour(ax, lon_p, lat_p, ept, ui, levels, 'black', extent)
if cf: add_vertical_colorbar(cf, '850hPa 相当温位 [K]'); info_text = self.get_local_info(elem_name, lon_p, lat_p, ept, area_index=area_index, model_name=model_name); drawn_flag = True
elif "850hpa湿数" in elem_name:
t = self.extract_2d_array(data, ['t850', 'tmp850', 't_850'], 850, ['tmp', 'temp', 't'])
rh_raw = self.extract_2d_array(data, ['rh850', 'r850', 'rh_850'], 850, ['rh', 'hum', 'r'])
if t is not None and rh_raw is not None:
if np.nanmax(t) > 100: t = t - 273.15
rh = _cl(rh_raw, 0, 150, 0.0)
if np.nanmax(rh) <= 1.0 and np.nanmax(rh) > 0: rh = rh * 100.0
lon_p, lat_p = self.get_coords_for_data(data, t); t_td = calc_t_td(t, rh)
levels = [0, 3, 6, 9, 12, 15]; colors = ['#27AE60', '#82E0AA', '#D5F5E3', '#F9E79F', '#F5CBA7', '#E74C3C']
cf = self.plot_contourf(ax, lon_p, lat_p, t_td, ui, levels, colors, extent, extend='max', alpha=0.35)
u_val = self.extract_2d_array(data, ['u850', 'u_850'], 850, ['u', 'ugrd'])
v_val = self.extract_2d_array(data, ['v850', 'v_850'], 850, ['v', 'vgrd'])
if u_val is not None: u_val = _cl(u_val, -200, 200, 0.0)
if v_val is not None: v_val = _cl(v_val, -200, 200, 0.0)
if cf:
add_vertical_colorbar(cf, '850hPa 湿数 [℃]')
info_text = self.get_local_info("湿数", lon_p, lat_p, t_td, u_val, v_val, area_index=area_index, model_name=model_name); drawn_flag = True
if u_val is not None and v_val is not None: self.plot_barbs(ax, lon_p, lat_p, u_val, v_val, ui, area_index, extent, model_name)
elif "925hpa" in elem_name or "975hpa" in elem_name:
lvl = 925 if "925" in elem_name else 975
t = self.extract_2d_array(data, [f't{lvl}', f'tmp{lvl}', f't_{lvl}'], lvl, ['tmp', 'temp', 't'])
rh_raw = self.extract_2d_array(data, [f'rh{lvl}', f'r{lvl}', f'rh_{lvl}'], lvl, ['rh', 'hum', 'r'])
if t is not None and rh_raw is not None:
if np.nanmax(t) > 100: t = t - 273.15
rh = _cl(rh_raw, 0, 150, 0.0)
if np.nanmax(rh) <= 1.0 and np.nanmax(rh) > 0: rh = rh * 100.0
lon_p, lat_p = self.get_coords_for_data(data, t)
if "相当温位" in elem_name:
ept = calc_ept(t, rh, lvl); levels = np.arange(270, 360, 6)
cf = self.plot_contourf(ax, lon_p, lat_p, ept, ui, levels, 'rainbow', extent, extend='both', alpha=0.6)
self.plot_contour(ax, lon_p, lat_p, ept, ui, levels, 'black', extent)
if cf: add_vertical_colorbar(cf, f'{lvl}hPa 相当温位 [K]'); info_text = self.get_local_info(elem_name, lon_p, lat_p, ept, area_index=area_index, model_name=model_name); drawn_flag = True
else:
t_td = calc_t_td(t, rh)
levels = [0, 3, 6, 9, 12, 15]; colors = ['#27AE60', '#82E0AA', '#D5F5E3', '#F9E79F', '#F5CBA7', '#E74C3C']
cf = self.plot_contourf(ax, lon_p, lat_p, t_td, ui, levels, colors, extent, extend='max', alpha=0.35)
u_val = self.extract_2d_array(data, [f'u{lvl}', f'u_{lvl}'], lvl, ['u', 'ugrd'])
v_val = self.extract_2d_array(data, [f'v{lvl}', f'v_{lvl}'], lvl, ['v', 'vgrd'])
if u_val is not None: u_val = _cl(u_val, -200, 200, 0.0)
if v_val is not None: v_val = _cl(v_val, -200, 200, 0.0)
if cf:
add_vertical_colorbar(cf, f'{lvl}hPa 湿数 [℃]')
info_text = self.get_local_info("湿数", lon_p, lat_p, t_td, u_val, v_val, area_index=area_index, model_name=model_name); drawn_flag = True
if u_val is not None and v_val is not None: self.plot_barbs(ax, lon_p, lat_p, u_val, v_val, ui, area_index, extent, model_name)
data.close(); del data
if info_text:
ui['info_panel'].setText(info_text); ui['info_panel'].adjustSize(); ui['info_panel'].move(10, 10); ui['info_panel'].show()
if not drawn_flag:
if "降水" in elem_name and display_val == 0 and "確率" not in elem_name and "時間降水" not in elem_name and model_name != "ANAL": self.show_error_msg(ax, ui, "【初期時のためデータなし。次画像から表示】")
elif not ("降水" in elem_name and display_val != 0 and "確率" not in elem_name and "時間降水" not in elem_name):
self.show_error_msg(ax, ui, f"[!] {elem_name} のデータがありません。\n保存時の変数名が異なっている可能性があります。")
except Exception as e: logging.error(f"Draw Error for {elem_name} at FT={display_val}: {e}")
ui['canvas'].draw_idle(); gc.collect()
def setup_history_tab(self):
tab = QWidget(); layout = QVBoxLayout(tab); history_text = QTextEdit(); history_text.setReadOnly(True)
history_text.setStyleSheet("background-color: #112240; color: #E0E0E0; font-family: 'MS Gothic'; font-size: 12pt; padding: 10px; border: none;")
html_content = """
<h2 style='color: #64FFDA;'>気象GPV 局地分析ツール 更新履歴</h2><hr style='border-color: #457B9D;'><ul>
<li><b>Ver 121.0 (GSM 132h以降 完全対応版)</b><br>
1. <b>132時間以降のGSMフォールバック処理を修正</b>: 上空要素だけでなく、地上のすべての要素に対して、GSMの6時間間隔データへの自動フォールバック（間引き読み込み）を適用。<br>
2. <b>降水量差分計算のバグ修正</b>: GSMの132時間以降の降水量（積算）の差分を求める際、常に3時間前を引いていたため発生していたデータ消失・スパイクエラーを、動的に6時間前を参照するよう修正。<br>
3. <b>メタグラムの互換性向上</b>: 132時間以降のGSMメタグラムにおいて、ファイルの読み込み参照を自動で6時間ごとに補正するよう改善。
</ul>"""
history_text.setHtml(html_content); layout.addWidget(history_text); self.tabs.addTab(tab, "更新履歴")
def scan_cache_dir(self, quiet=False, force_draw=False):
if not os.path.exists(self.cache_dir): return
files = glob.glob(os.path.join(self.cache_dir, "*.npz"))
updated = False
for m in ["MSM", "GSM_JP", "ANAL", "MSM_GUID", "GSM_GUID"]:
m_files = [f for f in files if os.path.basename(f).startswith(f"{m}_")]
times = sorted(list(set(re.search(r'_(\d{14})_', f).group(1) for f in m_files if re.search(r'_(\d{14})_', f))), reverse=True)
if times:
combo = self.tab_ui.get(m, {}).get('init_combo')
if combo:
current_items = [combo.itemData(i) for i in range(combo.count())]
if current_items != times:
combo.blockSignals(True); combo.clear()
for t in times:
dt_utc = datetime.strptime(t, "%Y%m%d%H%M%S") # UTC完全準拠
dt_jst = dt_utc + timedelta(hours=9)
combo.addItem(dt_utc.strftime('%m/%d %H:%M Z') + (" (最新)", "")[t != times[0]], t)
combo.blockSignals(False)
if self.model_init_times.get(m) not in times:
self.model_init_times[m] = times[0];
self.update_slider_max(m, times[0])
self.tab_ui[m]['slider'].setValue(0); combo.setCurrentIndex(0); updated = True
if (updated or force_draw) and not quiet:
self.status_banner.setText("最新データを画面に同期しました")
current_tab_name = self.tabs.tabText(self.tabs.currentIndex())
if "MSM ガイダンス" in current_tab_name: current_m = "MSM_GUID"
elif "GSM ガイダンス" in current_tab_name: current_m = "GSM_GUID"
elif "毎時大気" in current_tab_name: current_m = "ANAL"
elif "MSM" in current_tab_name: current_m = "MSM"
elif "日本域" in current_tab_name: current_m = "GSM_JP"
else: current_m = None
if current_m in self.tab_ui:
if len(self.tab_ui[current_m]['area_btns']) > 4 and self.tab_ui[current_m]['area_btns'][-2].isChecked(): pass
else: self.draw_frame(current_m, self.tab_ui[current_m]['slider'].value())
def start_animation(self, model_name):
self.current_anim_model = model_name
speeds = [2000, 1000, 500, 200, 50]
self.anim_timer.start(speeds[self.tab_ui[model_name]['combo_speed'].currentIndex()])
def stop_animation(self):
self.anim_timer.stop()
def anim_step(self):
if not self.current_anim_model: return
ui = self.tab_ui[self.current_anim_model]
new_val = ui['slider'].value() + ui['step']
ui['slider'].setValue(new_val if new_val <= ui['slider'].maximum() else ui['slider'].minimum())
if __name__ == '__main__':
import traceback
try:
app = QApplication(sys.argv); window = WeatherApp(); sys.exit(app.exec())
except Exception as e:
print("起動時にエラーが発生しました:")
traceback.print_exc()
input("Enterキーを押すと終了します...")
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