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…d in the main, master motor class, enum for movement type
…ian blurring of the reference decided by the user (depending on exp type) now in pixel but in microns as soon as I have the calibrations
# Conflicts: # twop/scanning.py # twop/state.py # twop/streaming_save.py
| self.extra_planes = Param(11, (1, 500)) | ||
| self.dz = Param(1.0, (0.1, 20.0), unit="um") | ||
| self.xy_th = Param(5.0, (0.1, 20.0), unit="um") | ||
| self.z_th = Param(self.dz, (self.dz, self.dz * 4), unit="um") |
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you might have problems with parameters that depend on other parameters (I think here the values will just be copied)
| self.n_frames_ref = Param(10, (1, 500)) | ||
| self.extra_planes = Param(11, (1, 500)) | ||
| self.dz = Param(1.0, (0.1, 20.0), unit="um") | ||
| self.xy_th = Param(5.0, (0.1, 20.0), unit="um") |
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the _th are thresholds? please use longer names
| n_frames_exp = st.n_frames_exp | ||
| sigma_k = st.sigma_k | ||
| size_k = st.size_k | ||
| rp = ReferenceParameters(n_frames_ref=n_frames_ref, |
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if all the names are same, you can covert settings to a dictionary (provided by lighparam). Also we should add a possibility to make a dataclass out of a Parameterized
| errors = [] | ||
| planes = np.size(self.reference, 0) | ||
| for i in range(planes): | ||
| ref_im = np.squeeze(self.reference[i, :, :]) |
| planes = np.size(self.reference, 0) | ||
| for i in range(planes): | ||
| ref_im = np.squeeze(self.reference[i, :, :]) | ||
| output = register_translation(ref_im, test_image) |
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once you upgrade scikit-image to 0.17 the function has been moved
| z_disp = ind - ((self.reference_params.n_planes - 1) / 2) | ||
| vector = vectors[ind] | ||
| np.append(vector, z_disp) | ||
| vector = self.real_units(vector) |
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a more concise way of doing thse would be self.to_real_units(np.r_[vector, z_disp]) without the np.append np.r_ is a shortcut to concatenate
| while not self.stop_event.is_set(): | ||
| number_of_frames = 0 | ||
| frame_container = [] | ||
| while number_of_frames == self.reference_params.n_frames_exp: |
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this is a bit strange condition? I aussume it will never be fullfilled unless self.reference_params.n_frames_exp is 0, because the loop does not update the self.reference_params
| self.encoding = encoding | ||
| self.port = port | ||
| self.device = device | ||
| rm = pyvisa.ResourceManager() |
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I guess you will have to put this back. For testing I suggest a FakeLaserPowerController class
| w_fov = conv_fact * self.scanning_parameters.voltage_x | ||
| return (self.scanning_parameters.n_x / w_fov) / 1000 | ||
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| def save_reference(self, raw_reference): |
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I don't think this class should be managing the saving of the reference. Try to constrain it just to do drift correction and nothing else.
| self.input_commands_queues["y"].put((vector[0], self.mov_type)) | ||
| self.input_commands_queues["z"].put((vector[2], self.mov_type)) | ||
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| def reference_processing(self, input_ref): |
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A tip for speed: once you received the reference, you can immediately fourier transform it and low-pass filter it in fourier space. That way the register_translation will be much faster (see the space argument here https://scikit-image.org/docs/stable/api/skimage.registration.html?highlight=phase_cross_correlation#phase-cross-correlation and the source code of the function)
| self.name = "reference" | ||
| self.n_frames_ref = Param(10, (1, 500)) | ||
| self.extra_planes = Param(11, (1, 500)) | ||
| self.dz = Param(1.0, (0.1, 20.0), unit="um") |
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Isn't there already a parameter like this in status? Don't duplicate parameters, move them through queues
| z_th: float = 1 | ||
| n_frames_exp: int = 5 | ||
| size_k: int = 0 | ||
| sigma_k: int = 5 |
| self.calibration_vector = None | ||
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| def run(self): | ||
| while True: |
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this should be while not stop_event.is_set() otherwise this process won't close properly. Also make sure it is .join() in the experiment termination function
| self.calibration_vector = [pix_millimeter, pix_millimeter, self.reference_params.dz] # x,y,z cal vect | ||
| while not self.stop_event.is_set(): | ||
| number_of_frames = 0 | ||
| frame_container = [] |
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Do you know the size of the frame container? If so better use a preallocated numpy then index it
| frame_container = [] | ||
| while number_of_frames == self.reference_params.n_frames_exp: | ||
| try: | ||
| frame = self.data_queue.get(timeout=0.001) |
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If you get from data_queue does the Saver still get the same data? You have to have into account that the get() method in a multiprocessing.queue not only obtains an element of the queue but also deletes it from the queue.
| out = queue.get(timeout=0.001) | ||
| except Empty: | ||
| pass | ||
| return out |
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This while will freeze the process here if nothing is received for whatever reason
| def calculate_fov(self): | ||
| # calculate pix per millimeters | ||
| # formula: width FOV (microns) = 167.789 * Voltage | ||
| conv_fact = 167.789 |
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conv_fact should not be declared here. Add it to a ParametrizedQt class here or in the state and set the attribute gui=False
| ) | ||
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| def toggle_start(self): | ||
| if self.chk_drift_corr.isChecked() is True: |
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is True is redundant as the if statement is already evaluating isChecked() which returns only True or False
| self.duration_queue = duration_queue | ||
| self.n_frames_queue = Queue() | ||
| self.correction_event = correction | ||
| self.correction_status = False |
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why having a boolean and an event when you can just have the event?
| self.setup_tasks(read_task, write_task, shutter_task) | ||
| if self.scanning_parameters.reset_shutter or toggle_shutter: | ||
| self.toggle_shutter(shutter_task) | ||
| pass |
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