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Convert zernike parameters #94

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f5f0add
CTF parameter conversion (messy, half finished)
GenevieveBuckley Sep 20, 2022
9cfc465
More work on CTF parameter metadata
GenevieveBuckley Sep 21, 2022
08fa0a5
Merge branch 'master' into metadata
GenevieveBuckley Sep 21, 2022
baee79a
Calculate electron wavelength with more precision
GenevieveBuckley Sep 26, 2022
2ee74df
Fix equations related to defocus
GenevieveBuckley Sep 26, 2022
3efd694
Remove variable name 'unit_conversion_odd', simplifies things slightly
GenevieveBuckley Sep 26, 2022
e5d4c02
Update Zernike coefficient equations for tilt and trefoil
GenevieveBuckley Sep 26, 2022
2dbbda9
phi = cs['ctf/phase_shift_rad']
GenevieveBuckley Sep 26, 2022
e9f6668
Fix typo in name 'ctf/tetra_A'
GenevieveBuckley Sep 26, 2022
c86cdd6
Convert dataframe columns to string before concatenating Zernike coeffs
GenevieveBuckley Sep 26, 2022
4a4a0b2
Merge pull request #87 from GenevieveBuckley/metadata
asarnow Sep 26, 2022
dbbd427
Zernike coefs concatenated when writing star file
asarnow Sep 26, 2022
9b4ae52
Force 1 to float, remove extra parens
asarnow Sep 26, 2022
8a255b2
Checkout pyem/star.py from master
asarnow Sep 26, 2022
183787c
Fix constant references
asarnow Sep 26, 2022
9dcf99e
Refactor to match other modules (pyem.ctf)
asarnow Sep 26, 2022
226fc6a
Arccos to convert % to rad
asarnow Sep 26, 2022
63533a5
Refactored conversions
asarnow Sep 26, 2022
8e6fadd
-2 * pi for Zernike shift
asarnow Sep 26, 2022
d094787
Conversion formulas reviewed
asarnow Sep 26, 2022
d87ada1
Moved shift conversion before tilt to match e.g. table from wikipedia
asarnow Sep 26, 2022
5367513
Precomputed pre-factors for all conversions
asarnow Sep 26, 2022
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55 changes: 43 additions & 12 deletions pyem/metadata.py
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Original file line number Diff line number Diff line change
Expand Up @@ -292,23 +292,53 @@ def cryosparc_2_cs_ctf_parameters(cs, df=None):
log = logging.getLogger('root')
if df is None:
df = pd.DataFrame()
if 'ctf/tilt_A' in cs.dtype.names:
log.debug("Recovering beam tilt and converting to mrad")
df[star.Relion.BEAMTILTX] = np.arcsin(cs['ctf/tilt_A'][:, 0] / cs['ctf/cs_mm'] * 1e-7) * 1e3
df[star.Relion.BEAMTILTY] = np.arcsin(cs['ctf/tilt_A'][:, 1] / cs['ctf/cs_mm'] * 1e-7) * 1e3
if 'ctf/shift_A' in cs.dtype.names:
pass
if 'ctf/trefoil_A' in cs.dtype.names:
pass
# df[star.Relion.ODDZERNIKE] = cs['ctf/trefoil_A']
if 'ctf/tetrafoil_A' in cs.dtype.names:
pass
# df[star.Relion.EVENZERNIKE] = cs['ctf/tetra_A']
assert 'ctf/accel_kv' in cs.dtype.names
# Calculate electron wavelentgh
kv = cs['ctf/accel_kv']
wl = 12.2643247 / np.sqrt(kv * (1. + kv * 0.978466e-6))
wl2 = wl**2
wl3 = wl**3
half_pi = 0.5 * np.pi
two_pi = 2 * np.pi
pi_wl = np.pi * wl
two_pi_wl2 = two_pi * wl2
neg_half_pi_wl3 = -half_pi * wl3
if 'ctf/anisomag' in cs.dtype.names:
df[star.Relion.MAGMAT00] = cs['ctf/anisomag'][:, 0]
df[star.Relion.MAGMAT01] = cs['ctf/anisomag'][:, 1]
df[star.Relion.MAGMAT10] = cs['ctf/anisomag'][:, 2]
df[star.Relion.MAGMAT11] = cs['ctf/anisomag'][:, 3]
if 'ctf/tilt_A' in cs.dtype.names:
log.debug("Recovering beam tilt and converting to mrad")
df[star.Relion.BEAMTILTX] = np.arcsin(cs['ctf/tilt_A'][:, 0] / cs['ctf/cs_mm'] * 1e-7) * 1e3
df[star.Relion.BEAMTILTY] = np.arcsin(cs['ctf/tilt_A'][:, 1] / cs['ctf/cs_mm'] * 1e-7) * 1e3
log.debug("Converting odd Zernike moments")
if 'ctf/shift_A' in cs.dtype.names:
df[star.UCSF.Z_neg1_1] = -two_pi * cs['ctf/shift_A'][:, 0]
df[star.UCSF.Z_1_1] = -two_pi * cs['ctf/shift_A'][:, 1]
if 'ctf/tilt_A' in cs.dtype.names:
df[star.UCSF.Z_neg1_3] = two_pi_wl2 * cs['ctf/tilt_A'][:, 0]
df[star.UCSF.Z_1_3] = two_pi_wl2 * cs['ctf/tilt_A'][:, 1]
if 'ctf/trefoil_A' in cs.dtype.names and 'ctf/cs_mm' in cs.dtype.names:
df[star.UCSF.Z_neg3_3] = two_pi_wl2 * cs['ctf/trefoil_A'][:, 0]
df[star.UCSF.Z_3_3] = two_pi_wl2 * cs['ctf/trefoil_A'][:, 1]
log.debug("Converting even Zernike moments")
if 'ctf/amp_contrast' in cs.dtype.names:
df[star.UCSF.Z_0_0] = cs['ctf/phase_shift_rad'] - np.arccos(cs['ctf/amp_contrast'])
if 'ctf/df1_A' in cs.dtype.names and 'ctf/df2_A' in cs.dtype.names and 'ctf/df_angle_rad' in cs.dtype.names:
df_avg = (cs['ctf/df1_A'] + cs['ctf/df2_A']) / 2
df_dev = (cs['ctf/df1_A'] - cs['ctf/df2_A']) / 2
two_angast = 2 * cs['ctf/df_angle_rad']
df[star.UCSF.Z_0_2] = pi_wl * df_avg
df[star.UCSF.Z_neg2_2] = pi_wl * np.cos(two_angast) * df_dev # Defocus asigmatism major (Z1).
df[star.UCSF.Z_2_2] = pi_wl * np.sin(two_angast) * df_dev # Defocus astigmatism minor (Z2).
if 'ctf/cs_mm' in cs.dtype.names:
df[star.UCSF.Z_0_4] = neg_half_pi_wl3 * cs['ctf/cs_mm'] * 1e7 # Spherical aberration in Å.
if 'ctf/tetra_A' in cs.dtype.names:
df[star.UCSF.Z_neg4_4] = neg_half_pi_wl3 * cs['ctf/tetra_A'][:, 0]
df[star.UCSF.Z_neg2_4] = neg_half_pi_wl3 * cs['ctf/tetra_A'][:, 1]
df[star.UCSF.Z_2_4] = neg_half_pi_wl3 * cs['ctf/tetra_A'][:, 2]
df[star.UCSF.Z_4_4] = neg_half_pi_wl3 * cs['ctf/tetra_A'][:, 3]
return df


Expand Down Expand Up @@ -430,6 +460,7 @@ def parse_cryosparc_2_cs(csfile, passthroughs=None, minphic=0, boxsize=None,
df = cryosparc_2_cs_model_parameters(cs, df, minphic=minphic)
df = cryosparc_2_cs_array_parameters(cs, df)
df = cryosparc_2_cs_filament_parameters(cs, df)
df = cryosparc_2_cs_ctf_parameters(cs, df)
if passthroughs is not None:
for passthrough in passthroughs:
if type(passthrough) is np.ndarray:
Expand Down