diff --git a/openwfs/calibration/__init__.py b/openwfs/calibration/__init__.py
index ccb6d44..ab7ffba 100644
--- a/openwfs/calibration/__init__.py
+++ b/openwfs/calibration/__init__.py
@@ -1,2 +1 @@
 from .fringe_analysis_slm_calibrator import FringeAnalysisSLMCalibrator
-from .inline_slm_calibrator import InlineSLMCalibrator
diff --git a/openwfs/calibration/inline_slm_calibrator.py b/openwfs/calibration/inline_slm_calibrator.py
deleted file mode 100644
index 3f251ce..0000000
--- a/openwfs/calibration/inline_slm_calibrator.py
+++ /dev/null
@@ -1,68 +0,0 @@
-# External (3rd party)
-import numpy as np
-
-# External (ours)
-from openwfs import Detector, PhaseSLM
-
-
-class InlineSLMCalibrator:
-    """
-    Inline SLM Calibrator
-
-    Calibrate an SLM phase response based on feedback measurements.
-    """
-
-    def __init__(self, feedback: Detector, slm: PhaseSLM, num_of_phase_steps=256):
-        self.feedback = feedback
-        self.slm = slm
-        self.num_of_phase_steps = num_of_phase_steps
-        self.phase_response = None
-
-    def execute(self):
-        # TODO: must be updated to work
-        Nx = 4
-        Ny = 4
-        static_phase = 0
-
-        # Create checkerboard phase mask
-        y_check = np.arange(Ny).reshape((Ny, 1))
-        x_check = np.arange(Nx).reshape((1, Nx))
-        checkerboard = np.mod(x_check + y_check, 2)
-        static_phase_pattern = static_phase * (1 - checkerboard)
-
-        # Random SLM pattern to destroy focus
-        self.slm.set_phases(2 * np.pi * np.random.rand(300, 300))
-        self.slm.update()
-
-        # Read dark frame
-        dark_frame = self.feedback.read()
-        dark_var = dark_frame.var()
-
-        count = 0
-        data_shape = self.feedback.data_shape
-        img_stack = np.zeros((data_shape[0], data_shape[1], self.num_of_phase_steps))
-        phase_range = np.linspace(0, 2 * np.pi, self.num_of_phase_steps)
-        for phase in phase_range:
-            phase_pattern = static_phase_pattern + phase * checkerboard
-            self.slm.set_phases(phase_pattern)
-            self.slm.update()
-
-            img_stack[:, :, count] = self.feedback.read().copy()
-            count += 1
-
-        self.slm.set_phases(2 * np.pi * np.random.rand(300, 300))
-        self.slm.update()
-
-        # Plot frames
-        # fig = plt.figure()
-        # for n in range(num_of_phase_steps):
-        #     fig.clear()
-        #     plt.imshow(img_stack[:, :, n].squeeze())
-        #     plt.title(f'{n}')
-        #     plt.draw()
-        #     plt.pause(1e-3)
-
-        # STD of frame, corrected for background noise
-        stack_std_corrected = np.sqrt((img_stack.var(axis=(0, 1)) - dark_var).clip(min=0))
-        block_size_pix = int(slm.shape[0] / Ny)
-        return self.phase_response