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The resolution of a diffraction data set conveys the details that one expects to distinguish in the Fourier maps calculated with these data. For example, individual atoms in a macromolecular chain cannot be resolved in the maps calculated with 2 Å resolution data sets, while they can be resolved in accurate maps calculated with 1 Å resolution data. However, if a data set is incomplete its high-resolution cutoff becomes less straightforward to interpret. For instance, a Fourier map calculated using a 1 Å resolution data set with many high-resolution reflections missing may rather resemble a map corresponding to 2 Å resolution data. The authors have proposed a method that redefines the traditional notion of data resolution, making it more formal and general. This manuscript presents the corresponding tool, the program EFRESOL. For a data set of an arbitrary completeness, the program calculates its mean, highest and lowest effective resolutions. These values are established through the minimum distance between two point scatterers when their images are still resolved as separate peaks in the Fourier maps calculated with the given data set. Additionally, the program calculates the optical resolution, which is defined as the minimum distance for typical atoms of the structure when they are resolved in a hypothetical synthesis obtained with the given amplitudes and the exact phases if they are known. Both effective and optical resolutions show the `resolving power' of the diffraction data set.

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