Improve configuring aatributes

src/ScanPGunVgrid.py

@@ -11,6 +11,7 @@
 #        attr;ScriptErr;string;''
 #        attr;publish_to_elog;bool;1
 #        attr;graph_title;string;GUN grid Scan
+#        attr;elog_text;string;Scan Graph
 #        attr;best_vgrid_result;double;0
 #        attr;plot_best_vgrid;bool;1
 
@@ -23,12 +24,14 @@ import io
 import matplotlib.pyplot as plt
 import requests
 
-def fig2elog(fig):
+def fig2elog(fig, text):
+
     buf = io.BytesIO()
+    
     fig.savefig(buf)
     buf.seek(0)
     try:
-        rs = requests.post('http://elog.elettra.eu/upload/upload.php', files={'file': ('booster_performance.png', buf, 'image/png')})
+        rs = requests.post('http://elog.elettra.eu/upload/upload.php', files={'file': ('booster_performance.png', buf, 'image/png')}, data={'string':text})
     except Exception as e:
         selfseq_dev.write_attribute("ScriptErr", f"{type(e).__name__} while connection to elog: {e}")      # scrive l'eventuale errore sull'attributo "ScriptErr" della sequenza
         sys.exit(1)
@@ -47,28 +50,46 @@ def main():
         scan_start = selfseq_dev.read_attribute("scan_start").value
         scan_stop = selfseq_dev.read_attribute("scan_stop").value
         scan_step = selfseq_dev.read_attribute("scan_step").value
-        dcct_samples = selfseq_dev.read_attribute("dcct_mean_samples").value
+        dcct_samples = int(selfseq_dev.read_attribute("dcct_mean_samples").value)
         starting_gun = gun_dev.read_attribute('GridVoltage').value
         selfseq_dev.write_attribute("ScriptErr","")
         publish_to_elog = bool(selfseq_dev.read_attribute("publish_to_elog").value)
         plot_best_vgrid = bool(selfseq_dev.read_attribute("plot_best_vgrid").value)
         graph_title = selfseq_dev.read_attribute("graph_title").value
+        elog_text = str(selfseq_dev.read_attribute("elog_text").value)
+        trigger_gun = PyTango.DeviceProxy('booster/accessi/plc_accessi')
+        timing_enable = PyTango.DeviceProxy('b/timing/injexttiming_b')
     except Exception as e:
         #print(str(e))
         selfseq_dev.write_attribute("ScriptErr", f"{type(e).__name__} while defining tango devices: {e}")      # scrive l'eventuale errore sull'attributo "ScriptErr" della sequenza
         sys.exit(1)
+    
+    if bool(trigger_gun.read_attribute("gun_trigger_on").value) == False:
+       selfseq_dev.write_attribute("ScriptErr", 'GUN DISABLED')
+       sys.exit(1)
 
 
+       
     first_time = False
     for x in np.arange(scan_start,scan_stop,scan_step):
         if str(selfseq_dev.State()) != 'RUNNING':
             selfseq_dev.write_attribute("ScriptErr","Sequence not running")
+            gun_dev.write_attribute('FastGridVoltage',starting_gun)
             sys.exit(1)
+        if bool(timing_enable.read_attribute("ExtractionEnabled").value) == False:
+           selfseq_dev.write_attribute("ScriptErr", 'SE Extraction DISABLED')
+           sys.exit(1)
+       
+        if float(gun_dev.read_attribute('GridVoltage').value) < 0.5 :
+            selfseq_dev.write_attribute("ScriptErr","Grid disabled or zero voltage during scan")
+            gun_dev.write_attribute('FastGridVoltage',starting_gun)
+            sys.exit(1)
+
         #print("valore gun: " + str(x))
         gun_dev.write_attribute('FastGridVoltage',x)
         if not first_time: 
             #print('first time')
-            time.sleep(0.1)
+            time.sleep(0.3)
             first_time = True
         temp_store =0
         for mean in range(0, dcct_samples,1):
@@ -78,34 +99,40 @@ def main():
         X.append(x)
         Y.append(dcct_value)
 
-
-    gun_dev.write_attribute('FastGridVoltage',starting_gun)
+    smooth_width = 50
+    z = np.polyfit(X, Y, 5)
+    p = np.poly1d(z)
+    xp = np.linspace(scan_start, scan_stop, smooth_width)
+    # create convolution kernel for calculating
     # the smoothed second order derivative
-    smooth_width = int((scan_stop - scan_start)/scan_step)
+    xp = xp[:-3]
     x1 = np.linspace(-3,3,smooth_width)
     norm = np.sum(np.exp(-x1**2)) * (x1[1]-x1[0]) # ad hoc normalization
     y1 = (4*x1**2 - 2) * np.exp(-x1**2) / smooth_width *8#norm*(x1[1]-x1[0])
     
-
+    yp=p(xp)
     # calculate second order deriv.
-    y_conv = np.convolve(Y, y1, mode="same")
-    #print(np.where(y_conv == np.amin(y_conv))[0][0]) 
-    best_vgrid = X[np.where(y_conv == np.amin(y_conv))[0][0]]
+    y_conv = np.convolve(y1, yp, mode="same")
+    best_vgrid = xp[np.where(y_conv == np.amin(y_conv))[0][0]]
+    best_current = yp[np.where(y_conv == np.amin(y_conv))[0][0]]
+    
+    gun_dev.write_attribute('FastGridVoltage',best_vgrid)
     selfseq_dev.write_attribute("best_vgrid_result", float(best_vgrid))
-    best_current = Y[np.where(y_conv == np.amin(y_conv))[0][0]]
-    #print(best_vgrid)
+
     if publish_to_elog == True:
+        plt.style.use(['seaborn-darkgrid'])
         if plot_best_vgrid == True:
             plt.plot(best_vgrid, best_current, marker="o", markersize=15, markeredgecolor="red", markerfacecolor="green")
-            plt.text(scan_start+((scan_stop-scan_start)/2), 0.05, 'Best gun Vgrid: '+str(best_vgrid)+'V', fontsize = 12, bbox = dict(facecolor = 'red', alpha = 0.5))
-        plt.plot(X, Y,label = "GUN Vgrid")
-        #plt.plot(X,y_conv, label = "second deriv")
+            plt.text(scan_start+((scan_stop-scan_start)/2), 0.05,'Best Vgrid: '+f'{best_vgrid:.2f}'+'V', fontsize = 12, bbox = dict(facecolor = 'red', alpha = 0.5))
+        plt.scatter(X, Y,label = "GUN Vgrid scan data")
+        plt.plot(xp,p(xp), label = "Fitting")
+        #plt.plot(xp,y_conv[:-3], label = "2nd order derivate")
         plt.title(str(graph_title))
-        plt.xlabel('Vgrid')
+        plt.xlabel('GUN Vgrid')
         plt.ylabel('Booster current')
         plt.legend(loc=0)
         fig = plt.gcf()
-        fig2elog(fig)
+        fig2elog(fig,elog_text)
     sys.exit(0)