Someone suggested earlier that I call fig.canvas.draw() to refresh my plot with new data. It worked great on the main plot, however I also have subplots included in the chart. The subplots are getting redrawn, however the old subplots, along with axes and other items are not getting cleared. Does anyone know how to get rid of the old subplot curves and other items when I replot?
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
if replot == 1:
#self.mplwidget_2.figure.clear()
print replot
par1 = fig.add_subplot(111)
par2 = fig.add_subplot(111)
#Add Axes
ax1 = par1.twinx()
ax2 = par2.twinx()
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]
#bep = fac_ranges[2]
#Plot Chart
plt.hold(False) #Has to be included for multiple curves
#Plot Factory Pressure
plt.plot(fac_flow, fac_lift, 'b', linestyle = "dashed", linewidth = 1)
#Plot Factory Power
ax1.plot(fac_flow, fac_power, 'r', linestyle = "dashed", linewidth = 1)
ax2.plot(fac_flow, fac_eff, 'g', linestyle = "dashed", linewidth = 1)
#Move spines
ax2.spines["right"].set_position(("outward", 25))
self.make_patch_spines_invisible(ax2)
ax2.spines["right"].set_visible(True)
#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 MARKER *** Can change marker style if needed
bep = fac_max_eff * 0.90 #bep is 90% of maximum efficiency point
bep_corrected = bep * 0.90 # We knock off another 10% to place the arrow correctly on chart
ax2.annotate('BEP', xy=(fac_max_eff_bpd, bep_corrected), xycoords='data', #Subtract 2.5 shows up correctly on chart
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')
#To redraw plot
fig.canvas.draw()
