update triangle waveform calculation

Author: annie-xd-wang

src/navigate/model/waveforms.py

@@ -217,18 +217,16 @@ def remote_focus_ramp_triangular(
         sample_rate=100000,
         exposure_time=0.2,
         sweep_time=0.24,
-        remote_focus_delay=7.5,
-        camera_delay=10,
-        fall=2.5,
+        remote_focus_delay=0.005,
+        camera_delay=0.001,
         amplitude=1,
         offset=0,
         ramp_type='Rising'
 ):
     """Returns a numpy array with a triangular ramp typically used for remote focusing
 
     The waveform starts at offset and stays there for the delay period, then
-    rises linearly to 2x amplitude (amplitude here refers to 1/2 peak-to-peak)
-    and drops back down to the offset voltage during the fall period.
+    rises linearly to 2x amplitude (amplitude here refers to 1/2 peak-to-peak).
 
     Switching from a left to right remote focus ramp is possible by exchanging the
     rise and fall periods.
@@ -242,11 +240,9 @@ def remote_focus_ramp_triangular(
     sweep_time : Float
         Unit - Seconds
     remote_focus_delay : Float
-        Unit - Percent
+        Unit - Seconds
     camera_delay : Float
-        Unit - Percent
-    fall : Float
-        Unit - Percent
+        Unit - Seconds
     amplitude : Float
         Unit - Volts
     offset : Float
@@ -266,53 +262,29 @@ def remote_focus_ramp_triangular(
     """
     # create an array just containing the negative amplitude voltage:
     # In theory, delay here should be 4H.
-    delay_samples = int(remote_focus_delay * exposure_time * sample_rate / 100)
+    delay_samples = int(remote_focus_delay  * sample_rate)
     delay_array = np.zeros(delay_samples) + offset
 
-    # 10-7.5 -> 1.025 * .2
-    #
-    rise_ramp_samples = int(
-        (exposure_time + exposure_time * (0 - remote_focus_delay) / 100)
-        * sample_rate
-    )
-    fall_ramp_samples = int(
-        (exposure_time + exposure_time * (camera_delay - remote_focus_delay) / 100)
+    # ramp samples
+    ramp_samples = int(
+        (exposure_time + camera_delay - remote_focus_delay)
         * sample_rate
     )
-    rise_ramp_array = np.linspace(offset - amplitude, offset + amplitude, rise_ramp_samples)
-    fall_ramp_array = np.linspace(offset + amplitude, offset - amplitude, fall_ramp_samples)
-
-    # fall_samples = .025 * .2 * 100000 = 500
-    settle_samples = int(fall * exposure_time * sample_rate / 100)
-    settle_array = np.zeros(settle_samples) + offset
+    rise_ramp_array = np.linspace(offset - amplitude, offset + amplitude, ramp_samples)
+    fall_ramp_array = np.linspace(offset + amplitude, offset - amplitude, ramp_samples)
 
-    extra_samples = int(
+    settle_samples = int(
         int(np.multiply(sample_rate, sweep_time))
-        - (delay_samples + rise_ramp_samples + settle_samples)
+        - (delay_samples + ramp_samples)
     )
+    settle_array = np.zeros(settle_samples) + offset
 
-    if extra_samples > 0:
-        print("extra samples:", extra_samples)
-        extra_array = np.zeros(extra_samples) + offset
-        if ramp_type == 'Rising':
-            waveform = np.hstack(
-                [delay_array - amplitude, rise_ramp_array, settle_array + amplitude,
-                 delay_array + amplitude, fall_ramp_array, settle_array - amplitude, extra_array - amplitude, extra_array - amplitude]
-            )
-        elif ramp_type == 'Falling':
-            waveform = np.hstack(
-                [delay_array + amplitude, fall_ramp_array, settle_array - amplitude, extra_array - amplitude,
-                 delay_array - amplitude, rise_ramp_array, settle_array + amplitude, extra_array + amplitude]
-            )
-    else:
-        if ramp_type == 'Rising':
-            waveform = np.hstack([delay_array - amplitude, rise_ramp_array, settle_array + amplitude,
-                                  delay_array + amplitude, fall_ramp_array, settle_array - amplitude]
-                                 )
-        elif ramp_type == 'Falling':
-            waveform = np.hstack([delay_array + amplitude, fall_ramp_array, settle_array - amplitude,
-                                  delay_array - amplitude, rise_ramp_array, settle_array + amplitude]
-                                 )
+    if ramp_type == 'Rising':
+        waveform = np.hstack([delay_array - amplitude, rise_ramp_array, settle_array + amplitude,
+                                delay_array + amplitude, fall_ramp_array, settle_array - amplitude])
+    elif ramp_type == 'Falling':
+        waveform = np.hstack([delay_array + amplitude, fall_ramp_array, settle_array - amplitude,
+                                delay_array - amplitude, rise_ramp_array, settle_array + amplitude])
 
     return waveform