From 7a2e623de866c797b759ca8b91c8896d4e724e4b Mon Sep 17 00:00:00 2001
From: weisse02 <andreas.weissenbrunner@ptb.de>
Date: Thu, 10 Nov 2022 16:36:28 +0100
Subject: [PATCH] make uncertainty calculation only for one case
---
GUI_Elbow.py | 107 ++++++++++++++++++++++++++++++---------------------
1 file changed, 63 insertions(+), 44 deletions(-)
diff --git a/GUI_Elbow.py b/GUI_Elbow.py
index 9eb15ca..fc7c14c 100644
--- a/GUI_Elbow.py
+++ b/GUI_Elbow.py
@@ -622,50 +622,66 @@ class mainPanel(wx.Panel):
#
def OnClicked_btn_uncertainty(self,e):
# calculate the uncertainty for the flow meter
+ # calculate for the whole dataset
+ calc_all = False
+
if self.pathint.any():
- if flow.case == "SingleElbow":
- self.fm_mean = np.zeros((len(flow.Rk),len(flow.dist),len(flow.phi)))
- self.fm_std = np.zeros((len(flow.Rk),len(flow.dist),len(flow.phi)))
- for i,rc in enumerate(flow.Rk):
- for j,dist in enumerate(flow.dist):
- for k,phi in enumerate(flow.phi[:,0]):
- self.fm_mean[i,j,k], self.fm_std[i,j,k] = self.get_uncertainty(rc,0,dist,phi)
+ if calc_all:
+ if flow.case == "SingleElbow":
+ self.fm_mean = np.zeros((len(flow.Rk),len(flow.dist),len(flow.phi)))
+ self.fm_std = np.zeros((len(flow.Rk),len(flow.dist),len(flow.phi)))
+ for i,rc in enumerate(flow.Rk):
+ for j,dist in enumerate(flow.dist):
+ for k,phi in enumerate(flow.phi[:,0]):
+ self.fm_mean[i,j,k], self.fm_std[i,j,k] = self.get_uncertainty(rc,0,dist,phi)
+ #
#
- #
- print(rc)
- #
- self.regint_mean = interpol.RegularGridInterpolator((flow.Rk,flow.dist,flow.phi[:,0]),self.fm_mean,bounds_error = False,fill_value=None)
- self.regint_std = interpol.RegularGridInterpolator((flow.Rk,flow.dist,flow.phi[:,0]),self.fm_std,bounds_error = False,fill_value=None)
- else:
- self.fm_mean = np.zeros((len(flow.Rk),len(flow.dl),len(flow.dist),len(flow.phi)))
- self.fm_std = np.zeros((len(flow.Rk),len(flow.dl),len(flow.dist),len(flow.phi)))
- for i,rc in enumerate(flow.Rk):
- for j,dl in enumerate(flow.dl):
- for k,dist in enumerate(flow.dist):
- for p,phi in enumerate(flow.phi[:,0]):
- self.fm_mean[i,j,k,p], self.fm_std[i,j,k,p] = self.get_uncertainty(rc,dl,dist,phi)
+ print(rc)
+ # end loops
+ self.regint_mean = interpol.RegularGridInterpolator((flow.Rk,flow.dist,flow.phi[:,0]),self.fm_mean,bounds_error = False,fill_value=None)
+ self.regint_std = interpol.RegularGridInterpolator((flow.Rk,flow.dist,flow.phi[:,0]),self.fm_std,bounds_error = False,fill_value=None)
+ else:
+ self.fm_mean = np.zeros((len(flow.Rk),len(flow.dl),len(flow.dist),len(flow.phi)))
+ self.fm_std = np.zeros((len(flow.Rk),len(flow.dl),len(flow.dist),len(flow.phi)))
+ for i,rc in enumerate(flow.Rk):
+ for j,dl in enumerate(flow.dl):
+ for k,dist in enumerate(flow.dist):
+ for p,phi in enumerate(flow.phi[:,0]):
+ self.fm_mean[i,j,k,p], self.fm_std[i,j,k,p] = self.get_uncertainty(rc,dl,dist,phi)
+ #
#
#
- #
- print(rc)
+ print(rc)
+ # end loops
+ self.regint_mean = interpol.RegularGridInterpolator((flow.Rk,flow.dl,flow.dist,flow.phi[:,0]),self.fm_mean,bounds_error = False,fill_value=None)
+ self.regint_std = interpol.RegularGridInterpolator((flow.Rk,flow.dl,flow.dist,flow.phi[:,0]),self.fm_std,bounds_error = False,fill_value=None)
#
- self.regint_mean = interpol.RegularGridInterpolator((flow.Rk,flow.dl,flow.dist,flow.phi[:,0]),self.fm_mean,bounds_error = False,fill_value=None)
- self.regint_std = interpol.RegularGridInterpolator((flow.Rk,flow.dl,flow.dist,flow.phi[:,0]),self.fm_std,bounds_error = False,fill_value=None)
- #
+ # the uncertainty is only calculated for the one case that is selected
+ else:
+ self.fm_mean = np.zeros((len(flow.dist),len(flow.phi)))
+ self.fm_std = np.zeros((len(flow.dist),len(flow.phi)))
+ print("calculating uncertainty for distance:")
+ for j,dist in enumerate(flow.dist):
+ print(dist)
+ for k,phi in enumerate(flow.phi[:,0]):
+ self.fm_mean[j,k], self.fm_std[j,k] = self.get_uncertainty(self.Rc,self.dl,dist,phi)
+ #
+ self.regint_mean = interpol.RegularGridInterpolator((flow.dist,flow.phi[:,0]),self.fm_mean,bounds_error = False,fill_value=None)
+ self.regint_std = interpol.RegularGridInterpolator((flow.dist,flow.phi[:,0]),self.fm_std,bounds_error = False,fill_value=None)
self.draw_meter()
#
def interpol_meter(self,Rc,dl,dist,phi):
y_u = np.zeros(0)
if flow.case == "SingleElbow":
if self.fm_mean.any():
- y = self.regint_mean((Rc,dist,phi))
- y_u = self.regint_std((Rc,dist,phi))
+ y = self.regint_mean((dist,phi))
+ y_u = self.regint_std((dist,phi))
else:
y = self.regint_fm((Rc,dist,phi))
else:
if self.fm_mean.any():
- y = self.regint_mean((Rc,dl,dist,phi))
- y_u = self.regint_std((Rc,dl,dist,phi))
+ y = self.regint_mean((dist,phi))
+ y_u = self.regint_std((dist,phi))
else:
y = self.regint_fm((Rc,dl,dist,phi))
return y, y_u
@@ -737,32 +753,35 @@ class mainPanel(wx.Panel):
self.ax_meter.set_xlabel(xlabel)
self.ax_meter.set_ylabel(ylabel)
self.ax_meter.plot(x,y,'-')
-
-
-
+ #
+ # get the y-limits of the plot
ymin = self.ax_meter.get_ylim()[0]
ymax = self.ax_meter.get_ylim()[1]
- ydiff = ymax-ymin
- #print(ydiff)
- if ydiff < ylimiter:
- ymin = self.ax_meter.get_ylim()[0]-(ylimiter-ydiff)/2
- ymax = self.ax_meter.get_ylim()[1]+(ylimiter-ydiff)/2
- # print("min")
- # print(ymin)
- # print("max")
- # print(ymax)
- self.ax_meter.set_ylim(ymin,ymax)
#
- # the line-plot of the selected parameter within the x axes
- self.ax_meter.plot([x_selected,x_selected],[ymin,ymax],'r-',linewidth=1)
if y_u.any():
self.ax_meter.fill_between(x, y - y_u, y + y_u,
facecolor='green',
alpha = 0.3,
interpolate=True, label="std")
+ # if the axis zoom is too large set the axis limits to be larger
+ ymin = self.ax_meter.get_ylim()[0]
+ ymax = self.ax_meter.get_ylim()[1]
self.ax_meter.text(x_selected, ymin, " " + str(np.round(np.interp(x_selected,x, y),2)) + " | " + str(np.round(np.interp(x_selected,x, y_u),2)), fontsize=14,color='r')
+
else:
self.ax_meter.text(x_selected, ymin, " " + str(np.round(np.interp(x_selected,x, y),2)), fontsize=14,color='r')
+ #
+ # if the axis zoom is too large set the axis limits to be larger
+ ydiff = ymax -ymin
+ #print(ydiff)
+ if ydiff < ylimiter:
+ ymin = self.ax_meter.get_ylim()[0]-(ylimiter-ydiff)/2
+ ymax = self.ax_meter.get_ylim()[1]+(ylimiter-ydiff)/2
+ # set the axis limits of the y axis
+ self.ax_meter.set_ylim(ymin,ymax)
+
+ # the line-plot of the selected parameter within the x axes
+ self.ax_meter.plot([x_selected,x_selected],[ymin,ymax],'r-',linewidth=1)
self.ax_meter.grid("on")
self.fig_meter.tight_layout()
--
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