fix #66 : Compare colors #68
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| raise ValueError("Expected None or LinearGradient instance for `bg_gradient` argument") | ||
| if bg_value is not None and not (isinstance(bg_value, np.ndarray) and bg_value.ndim == 2): | ||
| raise ValueError("Expected None or 2D Numpy ndarray with shape {} for `bg_value` argument" | ||
| .format(self._data.shape)) |
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you use the precise shape in the error message but not in the check. I guess you should replace bg_value.ndim == 2 by bg_value.shape == self._data.shape.
larray_editor/arraymodel.py
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| value = bg_value.data.flat[idx] | ||
| return self.bg_gradient[value] | ||
| i, j = index.row(), index.column() | ||
| return self.bg_gradient[self.bg_value[i][j]] |
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why not use self.bg_value[i, j]?
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Forgot that bg_value is a Numpy ndarray.
| self.current_filter = {} | ||
| self.la_data = la.aslarray(data) | ||
| self.bg_value = la.aslarray(bg_value) if bg_value is not None else None | ||
| self.bg_gradient = bg_gradient |
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I do not think storing/handling the bg_gradient in the adapter adds any value.
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Well, the changes made in PR #64 works fine as long as we do not play with user defined gradient.
In case of user defined gradient, it is overwritten as soon as we call the method reset_minmax() from DataArrayModel.
In the current commit, bg_gradient is first overwritten by reset_minmax() and then reset to the user defined gradient but the call to self.data_model.set_background(self.bg_gradient, bg_value_2D) at the end of update_filtered_data in the Adapter. This is bad, I know...
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Ok, that will do for now. I will fix that in the "gradient combobox" branch I just spoke about because I need to touch that code anyway.
alixdamman
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could you squash the 2 commits? |
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