<jupyter_start><jupyter_text>Auto-Alignment args:         chip: an instance of a Chip class (found in chip.py)        mmc: Mico-Manager instance (can get from sc_utils.get_stage_controller())        save_dir: directory to save images to         chip_number: string to identify chip        alignment_model_name: name of the trained model for alignment        alignment_model_path: path to the trained model for alignment        naming_scheme: Beginning of image file names        focus_delta_z: amount to change in the z direction between getting                        focus prediction        focus_total_z: total z in each direction to look for an individual                        focus point or the first focus point in a set        focus_next_point_range: total z in each direction to look for each                        focus point that directly follows a nearby point that                        we have already focused (this will need to be increased                       for chips that are not relatively flat)        number_of_focus_points_x: Number of positions to focus at in the x                        direction (must be greater than 3 for interpolation to                        work propertly)        number_of_focus_points_y: Number of positions to focus at in the y                        direction (must be greater than 3 for interpolation to                        work propertly)        save_jpg: Saves images as both tiff files and jpg files if True<jupyter_code>run.auto_image_chip(curr_chip,
                    mmc,
                    save_dir,
                    chip_number,
                    alignemnt_model_name="alignment_30.h5",
                    alignemnt_model_path='.',
                    naming_scheme='BFF',
                    focus_delta_z=5,
                    focus_total_z=150,
                    focus_next_point_range=35,
                    number_of_focus_points_x=5,
                    number_of_focus_points_y=4,
                    save_jpg=False)<jupyter_output><empty_output><jupyter_text>Image chip from previously saved positions args:        chip: an instance of a Chip class (found in chip.py)        chip_number: string to identify chip        save_dir: directory to save images to        mmc: Mico-Manager instance (can get from sc_utils.get_stage_controller())        realign: If true, find the alignment marks again         alignment_model_name: name of the trained model for alignment        alignment_model_path: path to the trained model for alignment        naming_scheme: Beginning of image file names        save_jpg: Saves images as both tiff files and jpg files if True<jupyter_code>curr_chip = chip.ML_Chip()
run.image_from_saved_positions(curr_chip, 
                               chip_number, 
                               save_dir, 
                               mmc, 
                               realign=False, 
                               alignemnt_model_name="alignment_30.h5",
                               alignemnt_model_path='.', 
                               naming_scheme='BFF', 
                               save_jpg=True)<jupyter_output><empty_output>
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