def test_write_simple():
df = dynamotable.read(simple_table)
file_out = Path().joinpath('test', 'data', 'simple_out.tbl')
dynamotable.write(df, file_out)
df2 = dynamotable.read(file_out)
for column in df.columns:
assert_series_equal(df[column], df2[column])
def test_write_simple(self):
df = dynamotable.open(self.simple)
outfile = Path().joinpath('test', 'data', 'simple_out.tbl')
dynamotable.write(df, outfile)
df2 = dynamotable.open(outfile)
for column in df.columns:
assert_series_equal(df[column],
df2[column],
check_less_precise=True)
def test_write_w_table_map():
df = dynamotable.read(complex_table, tomogram_table_map_complex)
outfile = Path().joinpath('test', 'data', 'complex_out.tbl')
dynamotable.write(df, outfile)
tmap_file = str(outfile).replace('.tbl', '.doc')
assert Path(tmap_file).exists()
df2 = dynamotable.read(outfile, tmap_file)
for column in df.columns:
assert_series_equal(df[column], df2[column])
def test_write_w_table_map(self):
df = dynamotable.read(self.complex, self.tmap_complex)
outfile = Path().joinpath('test', 'data', 'complex_out.tbl')
dynamotable.write(df, outfile)
tmap_file = str(outfile).replace('.tbl', '.doc')
self.assertTrue(Path(tmap_file).exists())
df2 = dynamotable.read(outfile, tmap_file)
for column in df.columns:
assert_series_equal(df[column],
df2[column],
check_less_precise=True)
def test_read_tbl(tmp_path):
df = pd.DataFrame({
'x': [1, 2],
'y': [1, 2],
'z': [1, 2],
'dx': [1, 2],
'dy': [1, 2],
'dz': [1, 2],
'tdrot': [1, 2],
'tilt': [1, 2],
'narot': [1, 2],
'tomo': [1, 2],
})
file_path = tmp_path / 'test.tbl'
dynamotable.write(df, file_path)
particleblocks = read_tbl(file_path)
assert all(isinstance(pb, ParticleBlock) for pb in particleblocks)
def warp2dynamo(warp_star_file, output_dynamo_table_file, extracted_box_size):
"""
Converts a Warp STAR file into a Dynamo table file.
Outputs a few things
1) dynamo table and corresponding table map (.doc)
2) dynamo STAR file as data container (to avoid reextraction)
3) a separate table for reextraction as a dynamo data folder
(STAR container didn't work in my hands for alignment projects)
"""
# Read STAR file
relion_star = starfile.read(warp_star_file)
# Initialise empty dict for dynamo
dynamo_data = {}
# Get XYZ positions and put into data
for axis in ('x', 'y', 'z'):
relion_heading = 'rlnCoordinate' + axis.upper()
dynamo_data[axis] = relion_star[relion_heading]
# Get euler angles and convert to dynamo convention (only if eulers present in STAR file)
if 'rlnAngleRot' in relion_star.columns:
eulers_relion = relion_star[['rlnAngleRot', 'rlnAngleTilt', 'rlnAnglePsi']].to_numpy()
eulers_dynamo = convert_eulers(eulers_relion,
source_meta='relion',
target_meta='dynamo')
dynamo_data['tdrot'] = eulers_dynamo[:, 0]
dynamo_data['tilt'] = eulers_dynamo[:, 1]
dynamo_data['narot'] = eulers_dynamo[:, 2]
# Add tomogram info
dynamo_data['tomo_file'] = relion_star['rlnMicrographName']
# Convert to DataFrame
df = pd.DataFrame.from_dict(dynamo_data)
# Write table file
output_dynamo_table_file = sanitise_dynamo_table_filename(output_dynamo_table_file)
click.echo(
f"Writing out Dynamo table file '{output_dynamo_table_file}' and corresponding table map file with appropriate info...\n")
dynamotable.write(df, output_dynamo_table_file)
# Write out dynamo STAR file to avoid reextraction
dynamo_star_name = output_dynamo_table_file + '.star'
click.echo(
f"Writing out Dynamo format STAR file '{dynamo_star_name}' to avoid reextraction...\n")
tags = [x + 1 for x in range(df.shape[0])]
particle_files = relion_star['rlnImageName']
dynamo_star = {'tag': tags,
'particleFile': particle_files}
dynamo_star = pd.DataFrame.from_dict(dynamo_star)
starfile.write(dynamo_star, dynamo_star_name)
# Write out reextraction table and .doc file (STAR files with mrc volumes didn't work in dynamo 1.1.509 in my hands)
# Get extraction table name
reextraction_table_name = reextract_table_filename(output_dynamo_table_file)
# Change xyz positions to match centers of extracted boxes
for axis in ('x', 'y', 'z'):
df[axis] = np.ones_like(df[axis]) * (extracted_box_size / 2)
# Change tomo_file to point to individual particles and make tomo equal to tags
df['tomo_file'] = relion_star['rlnImageName']
df['tomo'] = dynamo_star['tag']
# Write
click.echo(
f"Writing out table and table map to facilitate reextraction if dynamo STAR file doesn't work...")
click.echo(
f"General reextraction command: dtcrop <tomogram_table_map.doc> <tableForAllTomograms> <outputfolder> <sidelength> -asBoxes 1")
extraction_command = f"dtcrop {reextraction_table_name.replace('.tbl', '.doc')} {reextraction_table_name} <outputfolder> {extracted_box_size} -asBoxes 1"
reextraction_matlab = output_dynamo_table_file.replace('.tbl', 'reextraction_script.m')
with open(reextraction_matlab, 'w') as f:
f.write(f'{extraction_command}\n')
dynamotable.write(df, reextraction_table_name)
click.echo(f"\nDone! Converted Warp output '{warp_star_file}' into Dynamo input files")
return