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updating README
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README.md

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@@ -299,12 +299,14 @@ Example usage:
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$ cryodrgn backproject_voxel projections.128.mrcs \
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--poses pose.pkl \
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--ctf ctf.pkl \
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-o backproject.128.mrc
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-o backproject.128 \
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--first 10000
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The output structure `backproject.128.mrc` will not match the consensus reconstruction exactly
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as the `backproject_voxel` command backprojects phase-flipped particles onto the voxel grid,
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and by default only uses the first 10k images.
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If the structure is too noisy, you can increase the number of images that are used with the `--first` argument.
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The output structure `backproject.128/backproject.mrc` will not match the consensus reconstruction exactly
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as the `backproject_voxel` command backprojects phase-flipped particles onto the voxel grid, and because here we
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performed backprojection using only the first 10k images in the stack for quicker results.
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If the structure is too noisy, we can try using more images with `--first` or the
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entire stack instead (without `--first`).
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**Note:** If the volume does not resemble your structure, you may need to use the flag `--uninvert-data`.
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This flips the data sign (e.g. light-on-dark or dark-on-light), which may be needed depending on the
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[3] In particular, you may find it useful to perform filtering of particles separately from other analyses. This can
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done using our interactive interface available from the command line: `cryodrgn filter 01_cryodrgn256`.
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[4] `--Apix` only needs to be given if it is not present (or not accurate) in the CTF file that was used in training.
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### Generating additional volumes
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A simple way of generating additional volumes is to increase the number of k-means samples in `cryodrgn analyze`

cryodrgn/commands_utils/fsc.py

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if out_file is not None:
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fsc_vals.reset_index(inplace=True, drop=False)
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logger.info(f"Saving FSC values to {out_file}")
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fsc_vals.columns = fsc_vals.columns.str.replace(" ", "")
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fsc_vals.round(6).to_csv(out_file, sep=" ", header=True, index=False)
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return fsc_vals

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