I'm trying to make the PYQT embedded Matplotlib plot redraw when new data is selected. It draws the first plots perfectly. I've tried variations of many things that I've seen online to no avail. Any help is much appreciated.
def mpl_plot(self, plot_page, replot = 0): #Data stored in lists
if plot_page == 1: #Plot 1st Page
plt = self.mplwidget.axes
fig = self.mplwidget.figure #Add a figure
if plot_page == 2: #Plot 2nd Page
plt = self.mplwidget_2.axes
fig = self.mplwidget_2.figure #Add a figure
if plot_page == 3: #Plot 3rd Page
plt = self.mplwidget_3.axes
fig = self.mplwidget_3.figure #Add a figure
par1 = fig.add_subplot(1,1,1)
par2 = fig.add_subplot(1,1,1)
#Add Axes
ax1 = par1.twinx()
ax2 = par2.twinx()
ax2.spines["right"].set_position(("outward", 25))
self.make_patch_spines_invisible(ax2)
ax2.spines["right"].set_visible(True)
impeller = str(self.comboBox_impellers.currentText()) #Get Impeller
fac_curves = self.mpl_factory_specs(impeller)
fac_lift = fac_curves[0]
fac_power = fac_curves[1]
fac_flow = fac_curves[2]
fac_eff = fac_curves[3]
fac_max_eff = fac_curves[4]
fac_max_eff_bpd = fac_curves[5]
fac_ranges = self.mpl_factory_ranges()
min_range = fac_ranges[0]
max_range = fac_ranges[1]
#Plot Chart
plt.hold(True) #Has to be included for multiple curves
plt.plot(fac_flow, fac_lift, 'b', linestyle = "dashed", linewidth = 1)
#plt.plot(flow,f_lift,'b.') #Plot datapoints only
#Plot Factory Power
ax1.plot(fac_flow, fac_power, 'r', linestyle = "dashed", linewidth = 1)
#ax1.plot(flow,f_power,'r.') #Plot datapoints only
ax2.plot(fac_flow, fac_eff, 'g', linestyle = "dashed", linewidth = 1)
#Plot x axis minor tick marks
minorLocatorx = AutoMinorLocator()
ax1.xaxis.set_minor_locator(minorLocatorx)
ax1.tick_params(which='both', width= 0.5)
ax1.tick_params(which='major', length=7)
ax1.tick_params(which='minor', length=4, color='k')
#Plot y axis minor tick marks
minorLocatory = AutoMinorLocator()
plt.yaxis.set_minor_locator(minorLocatory)
plt.tick_params(which='both', width= 0.5)
plt.tick_params(which='major', length=7)
plt.tick_params(which='minor', length=4, color='k')
#Make Border of Chart White
#Plot Grid
plt.grid(b=True, which='both', color='k', linestyle='-')
#set shaded Area
plt.axvspan(min_range, max_range, facecolor='#9BE2FA', alpha=0.5) #Yellow rectangular shaded area
#Set Vertical Lines
plt.axvline(fac_max_eff_bpd, color = '#69767A')
bep = fac_max_eff * 0.90
bep_corrected = bep * 0.90
ax2.annotate('BEP', xy=(fac_max_eff_bpd, bep_corrected), xycoords='data',
xytext=(-50, 30), textcoords='offset points',
bbox=dict(boxstyle="round", fc="0.8"),
arrowprops=dict(arrowstyle="-|>",
shrinkA=0, shrinkB=10,
connectionstyle="angle,angleA=0,angleB=90,rad=10"),
)
#Set Scales
plt.set_ylim(0,max(fac_lift) + (max(fac_lift) * 0.40)) #Pressure
#plt.set_xlim(0,max(fac_flow))
ax1.set_ylim(0,max(fac_power) + (max(fac_power) * 0.40)) #Power
ax2.set_ylim(0,max(fac_eff) + (max(fac_eff) * 0.40)) #Effiency
# Set Axes Colors
plt.tick_params(axis='y', colors='b')
ax1.tick_params(axis='y', colors='r')
ax2.tick_params(axis='y', colors='g')
# Set Chart Labels
plt.set_xlabel("BPD")
plt.set_ylabel("Feet" , color = 'b')
#ax1.set_ylabel("BHP", color = 'r')
#ax1.set_ylabel("Effiency", color = 'g')
# Set tight layout
fig = self.mplwidget.figure.tight_layout()
fig = self.mplwidget_2.figure.tight_layout()
fig = self.mplwidget_3.figure.tight_layout()
You should use the object-oriented API instead of pyplot when embedding matplotlib. For an example of embedding in PyQt4 see here
To redraw the plot, call the draw() method of your FigureCanvas object.
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
fig = Figure()
ax = fig.add_subplot(111)
canvas = FigureCanvas(fig)
canvas.show()
canvas.draw() # Redraw figure