Remove OTBObject
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This was quite simple starting from your branch and I'm happy with the result. Now it finally make sense to use abstract base class...with abstract methods write and key_image_output.
Initially -20 lines for code, just by moving all image and numpy related code to RasterInterface. I kept App.__init__ as it was in my previous MR, since your changes with the "name" attr provoked undesired side effects on the pipeline tests.
Also made small improvements in type hints and exceptions not raised properly, and :
- Make App internal attributes all_param_types and out_param_types private
- Slicer functions name (renamed create_one_input_fake_exp and create_fake_exp to something more explicit)
- Now raise attribute error if trying to access app["unknown key"] (see commit )
- Print warning if writing to an already existing file path
Edit : with latest small commits the diff is now +356 -421 =)
If you approve I think we should merge and squash your MR first (because of duplicated commit messages) then merge this one without squash (there are several commits that we should keep apart).
P.S. : I won't go to the office tomorrow
classDiagram
class ABC{
AbstactBaseClass
}
class App {
_all_param_types
_out_param_types
_time_end : int
_time_start : int
app
data
elapsed_time
exports_dic : dict
frozen : bool
image_dic : NoneType
key_input
key_input_image
key_output_image
name : str
parameters : dict
parameters_keys : tuple
quiet : bool
used_outputs
execute()
find_outputs() tuple[str]
flush()
get_first_key(param_types: list[int]) str
propagate_dtype(target_key: str, dtype: int)
save_objects()
set_parameters()
summarize() dict[str, str | dict[str, Any]]
write()
}
class Input {
name
path : str
}
class LogicalOperation {
logical_exp : str
logical_exp_bands : list
build_fake_expressions(operator: str, inputs: list[App | str | int | float], nb_bands: int)
}
class OTBTFApp {
set_nb_sources()
}
class Operation {
exp : str
exp_bands : list
fake_exp_bands : list
im_count : int
im_dic : dict
inputs : list
logical_fake_exp_bands : list
name
nb_channels : dict
operator : str
unique_inputs
build_fake_expressions(operator: str, inputs: list[App | str | int | float], nb_bands: int)
get_real_exp(fake_exp_bands: str) tuple[list[str], str]
make_fake_exp(x: App | str, band: int, keep_logical: bool) tuple[str, list[App], int]
}
class Output {
app
filepath : NoneType, Path
key_output_image
name
param_key : Optional[str]
parent_pyotb_app
exists() bool
make_parent_dirs()
write(filepath: None | str | Path)
}
class RasterInterface {
app
dtype
exports_dic : dict
key_output_image
metadata
shape
transform
channels_list_from_slice(bands: int) list[int]
export(key: str, preserve_dtype: bool) dict[str, dict[str, np.ndarray]]
get_infos() dict[str, (str, float, list[float])]
get_statistics() dict[str, (str, float, list[float])]
read_values_at_coords(row: int, col: int, bands: int) list[int | float] | int | float
to_numpy(key: str, preserve_dtype: bool, copy: bool) np.ndarray
to_rasterio() tuple[np.ndarray, dict[str, Any]]
write()
xy_to_rowcol(x: float, y: float) tuple[int, int]
}
class Slicer {
cols
input
name : str
one_band_sliced
rows
}
RasterInterface --|> ABC
OTBTFApp --|> App
App --|> RasterInterface
Input --|> App
LogicalOperation --|> Operation
Operation --|> App
Output --|> RasterInterface
Slicer --|> App
App --* Output : parent_app
``