如何在 PyQt5 中嵌入 MetPy SkewT 图
How to embed MetPy SkewT plot in PyQt5
我想在 PyQT5 GUI 中嵌入 MetPy SkewT 图。以下代码创建一个 SkewT 图：
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import SkewT
from metpy.units import units
###########################################
# Change default to be better for skew-T
plt.rcParams['figure.figsize'] = (9, 9)
###########################################
# Upper air data can be obtained using the siphon package, but for this example we will use
# some of MetPy's sample data.
col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']
df = pd.read_fwf(get_test_data('jan20_sounding.txt', as_file_obj=False),
skiprows=5, usecols=[0, 1, 2, 3, 6, 7], names=col_names)
# Drop any rows with all NaN values for T, Td, winds
df = df.dropna(subset=('temperature', 'dewpoint', 'direction', 'speed'
), how='all').reset_index(drop=True)
###########################################
# We will pull the data out of the example dataset into individual variables and
# assign units.
p = df['pressure'].values * units.hPa
T = df['temperature'].values * units.degC
Td = df['dewpoint'].values * units.degC
wind_speed = df['speed'].values * units.knots
wind_dir = df['direction'].values * units.degrees
u, v = mpcalc.wind_components(wind_speed, wind_dir)
###########################################
skew = SkewT()
# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
skew.plot(p, T, 'r')
skew.plot(p, Td, 'g')
# Set spacing interval--Every 50 mb from 1000 to 100 mb
my_interval = np.arange(100, 1000, 50) * units('mbar')
# Get indexes of values closest to defined interval
ix = mpcalc.resample_nn_1d(p, my_interval)
# Plot only values nearest to defined interval values
skew.plot_barbs(p[ix], u[ix], v[ix])
# Add the relevant special lines
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()
skew.ax.set_ylim(1000, 100)
# Show the plot
plt.show()
结果类似于下图：
我尝试了不同的代码，使用 FigureCanvasQTAgg() 在 PyQt5 GUI 中嵌入这个 SkewT 图。其中一项努力如下：
from PyQt5 import QtGui, QtCore
from PyQt5.QtWidgets import QApplication, QMainWindow, QWidget, QVBoxLayout
import sys
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
from matplotlib.figure import Figure
import pandas as pd
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import SkewT
from metpy.units import units
class Window(QMainWindow):
def __init__(self):
super().__init__()
widget=QWidget()
vbox=QVBoxLayout()
widget.setLayout(vbox)
plot1 = FigureCanvas(Figure(tight_layout=True, linewidth=3))
ax1 = plot1.figure.subplots()
###########################################
# Upper air data can be obtained using the siphon package, but for this example we will use
# some of MetPy's sample data.
col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']
df = pd.read_fwf(get_test_data('jan20_sounding.txt', as_file_obj=False),
skiprows=5, usecols=[0, 1, 2, 3, 6, 7], names=col_names)
# Drop any rows with all NaN values for T, Td, winds
df = df.dropna(subset=('temperature', 'dewpoint', 'direction', 'speed'
), how='all').reset_index(drop=True)
###########################################
# We will pull the data out of the example dataset into individual variables and
# assign units.
p = df['pressure'].values * units.hPa
T = df['temperature'].values * units.degC
Td = df['dewpoint'].values * units.degC
wind_speed = df['speed'].values * units.knots
wind_dir = df['direction'].values * units.degrees
u, v = mpcalc.wind_components(wind_speed, wind_dir)
###########################################
skew = SkewT(ax1)
# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
skew.plot(p, T, 'r')
skew.plot(p, Td, 'g')
skew.plot_barbs(p, u, v)
# Add the relevant special lines
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()
skew.ax.set_ylim(1000, 100)
self.setCentralWidget(widget)
self.setWindowTitle('Example')
self.setMinimumSize(1000, 600)
# self.showMaximized()
self.show()
App = QApplication(sys.argv)
window = Window()
sys.exit(App.exec())
但它给出了一些错误。
我建议您创建一个单独的 python 文件 ui.py，您可以在其中设置 PyQt5 window、小部件、布局等。我使用 Qt Designer这个目的。
您应该将工作目录组织为：
├── workind_directory
├── main.py
└── ui.py
ui.py 文件的起点可以是：
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(600, 600)
MainWindow.setMinimumSize(QtCore.QSize(600, 600))
self.centralwidget = QtWidgets.QWidget(MainWindow)
self.centralwidget.setObjectName("centralwidget")
self.gridLayout = QtWidgets.QGridLayout(self.centralwidget)
self.gridLayout.setObjectName("gridLayout")
self.FigureLayout = QtWidgets.QVBoxLayout()
self.FigureLayout.setObjectName("FigureLayout")
self.gridLayout.addLayout(self.FigureLayout, 0, 0, 1, 1)
self.ToolbarLayout = QtWidgets.QVBoxLayout()
self.ToolbarLayout.setObjectName("ToolbarLayout")
self.gridLayout.addLayout(self.ToolbarLayout, 1, 0, 1, 1)
self.plotButton = QtWidgets.QPushButton(self.centralwidget)
self.plotButton.setObjectName("plotButton")
self.gridLayout.addWidget(self.plotButton, 2, 0, 1, 1)
MainWindow.setCentralWidget(self.centralwidget)
self.plotButton.setText("PLOT")
你有一个绘图布局，另一个工具栏布局（如果需要）和一个更新绘图的按钮。
然后你可以设置你的 main.py 文件：
from PyQt5.QtWidgets import QApplication, QMainWindow
import sys
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
import pandas as pd
import numpy as np
import ui
import matplotlib.pyplot as plt
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import SkewT
from metpy.units import units
class Window(QMainWindow, ui.Ui_MainWindow):
def __init__(self, parent = None):
super(Window, self).__init__(parent)
self.setupUi(self)
self.plotButton.clicked.connect(self.plotting)
self.Figure = plt.figure()
self.Canvas = FigureCanvas(self.Figure)
self.FigureLayout.addWidget(self.Canvas)
self.Toolbar = NavigationToolbar(self.Canvas, self)
self.ToolbarLayout.addWidget(self.Toolbar)
def plotting(self):
###########################################
# Upper air data can be obtained using the siphon package, but for this example we will use
# some of MetPy's sample data.
col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']
df = pd.read_fwf(get_test_data('jan20_sounding.txt', as_file_obj = False),
skiprows = 5, usecols = [0, 1, 2, 3, 6, 7], names = col_names)
# Drop any rows with all NaN values for T, Td, winds
df = df.dropna(subset = ('temperature', 'dewpoint', 'direction', 'speed'
), how = 'all').reset_index(drop = True)
###########################################
# We will pull the data out of the example dataset into individual variables and
# assign units.
p = df['pressure'].values*units.hPa
T = df['temperature'].values*units.degC
Td = df['dewpoint'].values*units.degC
wind_speed = df['speed'].values*units.knots
wind_dir = df['direction'].values*units.degrees
u, v = mpcalc.wind_components(wind_speed, wind_dir)
###########################################
skew = SkewT(fig = self.Figure)
# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
skew.plot(p, T, 'r')
skew.plot(p, Td, 'g')
# skew.plot_barbs(p, u, v)
# Set spacing interval--Every 50 mb from 1000 to 100 mb
my_interval = np.arange(100, 1000, 50) * units('mbar')
# Get indexes of values closest to defined interval
ix = mpcalc.resample_nn_1d(p, my_interval)
# Plot only values nearest to defined interval values
skew.plot_barbs(p[ix], u[ix], v[ix])
# Add the relevant special lines
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()
skew.ax.set_ylim(1000, 100)
plt.draw()
App = QApplication(sys.argv)
window = Window()
window.show()
sys.exit(App.exec_())
此 main.py 文件继承了 ui.py 的布局。注意__init__()方法，其中创建图形，canvas，工具栏并放置在各自的布局中。
然后是 plotting() 方法，您可以在其中实际绘制您想要的图。
这里有一个稍微不同的方法，它不使用 PyQt5，但使用 PySide2 作为 Python Qt5 绑定：
from PySide2 import QtWidgets, QtCore
from matplotlib.backends.backend_qt5agg import (
FigureCanvas, NavigationToolbar2QT as NavigationToolbar)
import metpy.calc as mpcalc
from metpy.plots import SkewT
from metpy.units import pandas_dataframe_to_unit_arrays
from siphon.simplewebservice.wyoming import WyomingUpperAir
class ApplicationWindow(QtWidgets.QMainWindow):
def __init__(self):
super().__init__()
self._main = QtWidgets.QWidget()
self.setCentralWidget(self._main)
mainLayout = QtWidgets.QHBoxLayout(self._main)
self.skew = SkewT()
self.skew.ax.set_ylim(1050, 100)
self.skew.ax.set_xlim(-50, 40)
self.skew.plot_dry_adiabats()
self.skew.plot_moist_adiabats()
self.skew.plot_mixing_lines()
self._temp_line, = self.skew.plot([], [], 'tab:red')
self._dewp_line, = self.skew.plot([], [], 'tab:blue')
self._prof_line, = self.skew.plot([], [], 'black')
self._canvas = FigureCanvas(self.skew.ax.figure)
mainLayout.addWidget(self._canvas, stretch=0)
configLayout = QtWidgets.QGridLayout()
updateButton = QtWidgets.QPushButton('Update')
updateButton.clicked.connect(self._update_data)
configLayout.addWidget(updateButton, 4, 1)
configLayout.setRowStretch(3, 1)
configLayout.addWidget(QtWidgets.QLabel('Site:'), 0, 0)
self._site_select = QtWidgets.QLineEdit('OUN')
configLayout.addWidget(self._site_select, 0, 1)
configLayout.addWidget(QtWidgets.QLabel('Date:'), 1, 0)
self._date_select = QtWidgets.QDateTimeEdit(QtCore.QDateTime(2019, 3, 20, 12, 0, 0))
configLayout.addWidget(self._date_select, 1, 1)
self._parcel_check = QtWidgets.QCheckBox('Surface Parcel')
self._parcel_check.toggled.connect(self._handle_prof)
configLayout.addWidget(self._parcel_check, 2, 0)
mainLayout.addLayout(configLayout, stretch=1)
self._update_data()
self._handle_prof()
@QtCore.Slot()
def _update_data(self):
try:
print(self._date_select.dateTime().toPython(), self._site_select.text())
self._data = WyomingUpperAir.request_data(self._date_select.dateTime().toPython(),
self._site_select.text())
self._data = pandas_dataframe_to_unit_arrays(self._data)
self._temp_line.set_data(self._data['temperature'].m, self._data['pressure'].m)
self._dewp_line.set_data(self._data['dewpoint'].m, self._data['pressure'].m)
self.flush()
except ValueError as e:
print(e)
def flush(self):
self._canvas.draw()
self._main.repaint()
@QtCore.Slot()
def _handle_prof(self):
if self._parcel_check.isChecked():
prof_press, _, _, prof_temp = mpcalc.parcel_profile_with_lcl(self._data['pressure'],
self._data['temperature'],
self._data['dewpoint'])
self._prof_line.set_data(prof_temp.to('degC').m, prof_press.to('hPa').m)
else:
self._prof_line.set_data([], [])
self.flush()
if __name__ == "__main__":
import sys
qapp = QtWidgets.QApplication(sys.argv)
app = ApplicationWindow()
app.show()
qapp.exec_()
我想在 PyQT5 GUI 中嵌入 MetPy SkewT 图。以下代码创建一个 SkewT 图：
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import SkewT
from metpy.units import units
###########################################
# Change default to be better for skew-T
plt.rcParams['figure.figsize'] = (9, 9)
###########################################
# Upper air data can be obtained using the siphon package, but for this example we will use
# some of MetPy's sample data.
col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']
df = pd.read_fwf(get_test_data('jan20_sounding.txt', as_file_obj=False),
skiprows=5, usecols=[0, 1, 2, 3, 6, 7], names=col_names)
# Drop any rows with all NaN values for T, Td, winds
df = df.dropna(subset=('temperature', 'dewpoint', 'direction', 'speed'
), how='all').reset_index(drop=True)
###########################################
# We will pull the data out of the example dataset into individual variables and
# assign units.
p = df['pressure'].values * units.hPa
T = df['temperature'].values * units.degC
Td = df['dewpoint'].values * units.degC
wind_speed = df['speed'].values * units.knots
wind_dir = df['direction'].values * units.degrees
u, v = mpcalc.wind_components(wind_speed, wind_dir)
###########################################
skew = SkewT()
# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
skew.plot(p, T, 'r')
skew.plot(p, Td, 'g')
# Set spacing interval--Every 50 mb from 1000 to 100 mb
my_interval = np.arange(100, 1000, 50) * units('mbar')
# Get indexes of values closest to defined interval
ix = mpcalc.resample_nn_1d(p, my_interval)
# Plot only values nearest to defined interval values
skew.plot_barbs(p[ix], u[ix], v[ix])
# Add the relevant special lines
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()
skew.ax.set_ylim(1000, 100)
# Show the plot
plt.show()
结果类似于下图：
我尝试了不同的代码，使用 FigureCanvasQTAgg() 在 PyQt5 GUI 中嵌入这个 SkewT 图。其中一项努力如下：
from PyQt5 import QtGui, QtCore
from PyQt5.QtWidgets import QApplication, QMainWindow, QWidget, QVBoxLayout
import sys
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
from matplotlib.figure import Figure
import pandas as pd
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import SkewT
from metpy.units import units
class Window(QMainWindow):
def __init__(self):
super().__init__()
widget=QWidget()
vbox=QVBoxLayout()
widget.setLayout(vbox)
plot1 = FigureCanvas(Figure(tight_layout=True, linewidth=3))
ax1 = plot1.figure.subplots()
###########################################
# Upper air data can be obtained using the siphon package, but for this example we will use
# some of MetPy's sample data.
col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']
df = pd.read_fwf(get_test_data('jan20_sounding.txt', as_file_obj=False),
skiprows=5, usecols=[0, 1, 2, 3, 6, 7], names=col_names)
# Drop any rows with all NaN values for T, Td, winds
df = df.dropna(subset=('temperature', 'dewpoint', 'direction', 'speed'
), how='all').reset_index(drop=True)
###########################################
# We will pull the data out of the example dataset into individual variables and
# assign units.
p = df['pressure'].values * units.hPa
T = df['temperature'].values * units.degC
Td = df['dewpoint'].values * units.degC
wind_speed = df['speed'].values * units.knots
wind_dir = df['direction'].values * units.degrees
u, v = mpcalc.wind_components(wind_speed, wind_dir)
###########################################
skew = SkewT(ax1)
# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
skew.plot(p, T, 'r')
skew.plot(p, Td, 'g')
skew.plot_barbs(p, u, v)
# Add the relevant special lines
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()
skew.ax.set_ylim(1000, 100)
self.setCentralWidget(widget)
self.setWindowTitle('Example')
self.setMinimumSize(1000, 600)
# self.showMaximized()
self.show()
App = QApplication(sys.argv)
window = Window()
sys.exit(App.exec())
但它给出了一些错误。
我建议您创建一个单独的 python 文件 ui.py，您可以在其中设置 PyQt5 window、小部件、布局等。我使用 Qt Designer这个目的。
您应该将工作目录组织为：
├── workind_directory
├── main.py
└── ui.py
ui.py 文件的起点可以是：
from PyQt5 import QtCore, QtGui, QtWidgets
class Ui_MainWindow(object):
def setupUi(self, MainWindow):
MainWindow.setObjectName("MainWindow")
MainWindow.resize(600, 600)
MainWindow.setMinimumSize(QtCore.QSize(600, 600))
self.centralwidget = QtWidgets.QWidget(MainWindow)
self.centralwidget.setObjectName("centralwidget")
self.gridLayout = QtWidgets.QGridLayout(self.centralwidget)
self.gridLayout.setObjectName("gridLayout")
self.FigureLayout = QtWidgets.QVBoxLayout()
self.FigureLayout.setObjectName("FigureLayout")
self.gridLayout.addLayout(self.FigureLayout, 0, 0, 1, 1)
self.ToolbarLayout = QtWidgets.QVBoxLayout()
self.ToolbarLayout.setObjectName("ToolbarLayout")
self.gridLayout.addLayout(self.ToolbarLayout, 1, 0, 1, 1)
self.plotButton = QtWidgets.QPushButton(self.centralwidget)
self.plotButton.setObjectName("plotButton")
self.gridLayout.addWidget(self.plotButton, 2, 0, 1, 1)
MainWindow.setCentralWidget(self.centralwidget)
self.plotButton.setText("PLOT")
你有一个绘图布局，另一个工具栏布局（如果需要）和一个更新绘图的按钮。
然后你可以设置你的 main.py 文件：
from PyQt5.QtWidgets import QApplication, QMainWindow
import sys
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
import pandas as pd
import numpy as np
import ui
import matplotlib.pyplot as plt
import metpy.calc as mpcalc
from metpy.cbook import get_test_data
from metpy.plots import SkewT
from metpy.units import units
class Window(QMainWindow, ui.Ui_MainWindow):
def __init__(self, parent = None):
super(Window, self).__init__(parent)
self.setupUi(self)
self.plotButton.clicked.connect(self.plotting)
self.Figure = plt.figure()
self.Canvas = FigureCanvas(self.Figure)
self.FigureLayout.addWidget(self.Canvas)
self.Toolbar = NavigationToolbar(self.Canvas, self)
self.ToolbarLayout.addWidget(self.Toolbar)
def plotting(self):
###########################################
# Upper air data can be obtained using the siphon package, but for this example we will use
# some of MetPy's sample data.
col_names = ['pressure', 'height', 'temperature', 'dewpoint', 'direction', 'speed']
df = pd.read_fwf(get_test_data('jan20_sounding.txt', as_file_obj = False),
skiprows = 5, usecols = [0, 1, 2, 3, 6, 7], names = col_names)
# Drop any rows with all NaN values for T, Td, winds
df = df.dropna(subset = ('temperature', 'dewpoint', 'direction', 'speed'
), how = 'all').reset_index(drop = True)
###########################################
# We will pull the data out of the example dataset into individual variables and
# assign units.
p = df['pressure'].values*units.hPa
T = df['temperature'].values*units.degC
Td = df['dewpoint'].values*units.degC
wind_speed = df['speed'].values*units.knots
wind_dir = df['direction'].values*units.degrees
u, v = mpcalc.wind_components(wind_speed, wind_dir)
###########################################
skew = SkewT(fig = self.Figure)
# Plot the data using normal plotting functions, in this case using
# log scaling in Y, as dictated by the typical meteorological plot
skew.plot(p, T, 'r')
skew.plot(p, Td, 'g')
# skew.plot_barbs(p, u, v)
# Set spacing interval--Every 50 mb from 1000 to 100 mb
my_interval = np.arange(100, 1000, 50) * units('mbar')
# Get indexes of values closest to defined interval
ix = mpcalc.resample_nn_1d(p, my_interval)
# Plot only values nearest to defined interval values
skew.plot_barbs(p[ix], u[ix], v[ix])
# Add the relevant special lines
skew.plot_dry_adiabats()
skew.plot_moist_adiabats()
skew.plot_mixing_lines()
skew.ax.set_ylim(1000, 100)
plt.draw()
App = QApplication(sys.argv)
window = Window()
window.show()
sys.exit(App.exec_())
此 main.py 文件继承了 ui.py 的布局。注意__init__()方法，其中创建图形，canvas，工具栏并放置在各自的布局中。
然后是 plotting() 方法，您可以在其中实际绘制您想要的图。
这里有一个稍微不同的方法，它不使用 PyQt5，但使用 PySide2 作为 Python Qt5 绑定：
from PySide2 import QtWidgets, QtCore
from matplotlib.backends.backend_qt5agg import (
FigureCanvas, NavigationToolbar2QT as NavigationToolbar)
import metpy.calc as mpcalc
from metpy.plots import SkewT
from metpy.units import pandas_dataframe_to_unit_arrays
from siphon.simplewebservice.wyoming import WyomingUpperAir
class ApplicationWindow(QtWidgets.QMainWindow):
def __init__(self):
super().__init__()
self._main = QtWidgets.QWidget()
self.setCentralWidget(self._main)
mainLayout = QtWidgets.QHBoxLayout(self._main)
self.skew = SkewT()
self.skew.ax.set_ylim(1050, 100)
self.skew.ax.set_xlim(-50, 40)
self.skew.plot_dry_adiabats()
self.skew.plot_moist_adiabats()
self.skew.plot_mixing_lines()
self._temp_line, = self.skew.plot([], [], 'tab:red')
self._dewp_line, = self.skew.plot([], [], 'tab:blue')
self._prof_line, = self.skew.plot([], [], 'black')
self._canvas = FigureCanvas(self.skew.ax.figure)
mainLayout.addWidget(self._canvas, stretch=0)
configLayout = QtWidgets.QGridLayout()
updateButton = QtWidgets.QPushButton('Update')
updateButton.clicked.connect(self._update_data)
configLayout.addWidget(updateButton, 4, 1)
configLayout.setRowStretch(3, 1)
configLayout.addWidget(QtWidgets.QLabel('Site:'), 0, 0)
self._site_select = QtWidgets.QLineEdit('OUN')
configLayout.addWidget(self._site_select, 0, 1)
configLayout.addWidget(QtWidgets.QLabel('Date:'), 1, 0)
self._date_select = QtWidgets.QDateTimeEdit(QtCore.QDateTime(2019, 3, 20, 12, 0, 0))
configLayout.addWidget(self._date_select, 1, 1)
self._parcel_check = QtWidgets.QCheckBox('Surface Parcel')
self._parcel_check.toggled.connect(self._handle_prof)
configLayout.addWidget(self._parcel_check, 2, 0)
mainLayout.addLayout(configLayout, stretch=1)
self._update_data()
self._handle_prof()
@QtCore.Slot()
def _update_data(self):
try:
print(self._date_select.dateTime().toPython(), self._site_select.text())
self._data = WyomingUpperAir.request_data(self._date_select.dateTime().toPython(),
self._site_select.text())
self._data = pandas_dataframe_to_unit_arrays(self._data)
self._temp_line.set_data(self._data['temperature'].m, self._data['pressure'].m)
self._dewp_line.set_data(self._data['dewpoint'].m, self._data['pressure'].m)
self.flush()
except ValueError as e:
print(e)
def flush(self):
self._canvas.draw()
self._main.repaint()
@QtCore.Slot()
def _handle_prof(self):
if self._parcel_check.isChecked():
prof_press, _, _, prof_temp = mpcalc.parcel_profile_with_lcl(self._data['pressure'],
self._data['temperature'],
self._data['dewpoint'])
self._prof_line.set_data(prof_temp.to('degC').m, prof_press.to('hPa').m)
else:
self._prof_line.set_data([], [])
self.flush()
if __name__ == "__main__":
import sys
qapp = QtWidgets.QApplication(sys.argv)
app = ApplicationWindow()
app.show()
qapp.exec_()