camera tests; holography sample motion

devices/holo_sample_motion.py

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+import numpy as np
+
+from slic.core.adjustable import Adjustable, Converted, Combined
+from slic.core.device import SimpleDevice
+
+
+FACTOR2 = 1/np.sin(30 * np.pi/180)
+FACTOR1 = -np.cos(30 * np.pi/180)
+
+
+class HoloSample(Adjustable):
+
+    def __init__(self, m1, m2, ID="HOLOGRAPHY-SAMPLE", name="Holography sample Y", units="mm"):
+        super().__init__(ID, name=name, units=units)
+        self.m1 = m1
+        self.m2 = m2
+        #self.adjs = SimpleDevice(ID, combined=self, m1=m1, m2=m2)
+
+
+    # one master, others are following
+    def get_current_value(self):
+        return self.m2.get_current_value()/FACTOR2
+
+    # current value is average of all
+    #def get_current_value(self):
+    #    converted_values = [
+    #        self.m1.get_current_value(),
+    #        self.m2.get_current_value()
+    #    ]
+    #    return np.mean(converted_values)
+
+
+    def set_target_value(self, value):
+        #print('current val m1', self.m1.get_current_value())
+        #print('current val m2', self.m2.get_current_value())
+        #print('F1: %f F2 %f'%(FACTOR1, FACTOR2) )
+        #print('requested val: ', value)
+
+        
+        tasks = [
+            self.m1.set_target_value(value * FACTOR1),
+            self.m2.set_target_value(value * FACTOR2)
+        ]
+        
+        for t in tasks:
+            t.wait()
+
+
+    def is_moving(self):
+        return self.m1.is_moving() or self.m2.is_moving()
+
+
+
+#def g1(x): return x / FACTOR1
+#def g2(x): return x / FACTOR2
+#def s1(x): return x * FACTOR1
+#def s2(x): return x * FACTOR2
+
+#m1 = SmarActAxis("SATES21-XSMA166:MOT7", internal=True)
+#m2 = SmarActAxis("SATES21-XSMA166:MOT8", internal=True)
+#c1 = Converted("C1", m1, g1, s1, internal=True)
+#c2 = Converted("C2", m2, g2, s2, internal=True)
+#comb = Combined("COMBINED", (c1, c2), name="Holo")
+
+
+