neuralib.suite2p.core.Suite2pGUIOptions
- class neuralib.suite2p.core.Suite2pGUIOptions[source]
Bases:
TypedDictSuite2p GUI setting.
- __init__(*args, **kwargs)
Methods
__init__(*args, **kwargs)clear()copy()fromkeys(iterable[, value])Create a new dictionary with keys from iterable and values set to value.
get(key[, default])Return the value for key if key is in the dictionary, else default.
items()keys()pop(k[,d])If the key is not found, return the default if given; otherwise, raise a KeyError.
popitem()Remove and return a (key, value) pair as a 2-tuple.
setdefault(key[, default])Insert key with a value of default if key is not in the dictionary.
update([E, ]**F)If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values()Attributes
- look_one_level_down: float
- fast_disk: str
- delete_bin: bool
- mesoscan: bool
- bruker: bool
- h5py: list
- h5py_key: str
- save_path0: str
- save_folder: str
- subfolders: list
- move_bin: bool
- nplanes: Required[int]
- nchannels: Required[int]
- functional_chan: int
- tau: Required[float]
- fs: Required[float]
- force_sktiff: bool
- frames_include: int
- multiplane_parallel: float
- preclassify: float
- save_mat: bool
- save_NWB: float
- combined: float
- aspect: float
- do_bidiphase: bool
- bidiphase: float
- bidi_corrected: bool
- do_registration: int
- two_step_registration: float
- keep_movie_raw: bool
- nimg_init: int
- batch_size: int
- maxregshift: float
- align_by_chan: int
- reg_tif: bool
- reg_tif_chan2: bool
- subpixel: int
- smooth_sigma_time: float
- smooth_sigma: float
- th_badframes: float
- norm_frames: bool
- force_refImg: bool
- pad_fft: bool
- nonrigid: bool
- block_size: tuple[int, int]
- snr_thresh: float
- maxregshiftNR: float
- oneP_reg: bool
- spatial_hp: int
- spatial_hp_reg: float
- spatial_hp_detect: int
- pre_smooth: float
- spatial_taper: float
- roidetect: bool
- spikedetect: bool
- anatomical_only: float
- sparse_mode: bool
- diameter: float
- spatial_scale: float
- connected: bool
- nbinned: int
- max_iterations: int
- threshold_scaling: float
- max_overlap: float
- high_pass: float
- denoise: bool
- soma_crop: bool
- neuropil_extract: bool
- inner_neuropil_radius: float
- min_neuropil_pixels: int
- lam_percentile: float
- allow_overlap: bool
- use_builtin_classifier: bool
- classifier_path: int
- chan2_thres: float
- baseline: str
- win_baseline: Required[float]
- sig_baseline: Required[float]
- prctile_baseline: Required[float]
- neucoeff: Required[int]
- suite2p_version: str
- data_path: list[str]
- sbx_ndeadcols: int
- input_format: str
- save_path: str
- ops_path: str
- reg_file: str
- filelist: list[str]
- nframes_per_folder: ndarray
- sbx_ndeadrows: int
- meanImg: Required[ndarray]
- meanImg_chan2: Required[ndarray]
- nframes: int
- Ly: Required[int]
- Lx: Required[int]
- date_proc: datetime
- refImg: ndarray
- rmin: int
- rmax: int
- yblock: list[ndarray]
- xblock: list[ndarray]
- nblocks: list[int]
- NRsm: ndarray
- yoff: Required[ndarray]
- xoff: Required[ndarray]
- corrXY: Required[ndarray]
- yoff1: Required[ndarray]
- xoff1: Required[ndarray]
- corrXY1: Required[ndarray]
- badframes: ndarray
- yrange: list[int]
- xrange: list[int]
- tPC: ndarray
- regPC: ndarray
- regDX: ndarray
- Lyc: int
- Lxc: int
- max_proj: ndarray
- Vmax: ndarray
- ihop: ndarray
- Vsplit: ndarray
- Vcorr: ndarray
- Vmap: list[ndarray]
- spatscale_pix: ndarray
- meanImgE: ndarray
- timing: dict[str, float]