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inout.py
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inout.py
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import os
import json
import pickle
import warnings
from collections import OrderedDict
import numpy as np
import holopy as hp
from holopy.core.io import load_average
from holopy.core.process import subimage, normalize, center_find
from lmfit.minimizer import MinimizerResult, Parameters
RGB_CHANNEL = None
HOLOGRAM_SIZE = 256
HERE = os.path.dirname(__file__)
def load_mcmc_result_PS_mieonly(frame=1, fmt='pkl'):
folder = 'fits/Polystyrene2-4um-60xWater-042919/'
file = ('polystyrene-mieonly-frame={}-size=256-npx=10000-mcmc'.format(frame))
return _load_mcmc_result(folder + file, fmt)
def load_mcmc_result_PS_mielens(frame=1, fmt='pkl'):
folder = 'fits/Polystyrene2-4um-60xWater-042919/'
file = ('polystyrene-mielensalpha-frame={}-size=256-npx=10000-mcmc'.format(frame))
return _load_mcmc_result(folder + file, fmt)
def _load_mcmc_result(file, fmt):
if fmt == 'json':
return load_MinimizerResult_from_json(file + '.json')
elif fmt == 'pkl':
return load_pickle(file + '.pkl')
def load_pickle(filename):
with open(filename, 'rb') as f:
return pickle.load(f)
def save_pickle(obj, filename):
with open(filename, 'wb') as f:
return pickle.dump(obj, f)
def load_json(filename):
with open(filename, 'r') as f:
return json.load(f, object_pairs_hook=OrderedDict)
def save_json(obj, filename):
if isinstance(obj, MinimizerResult):
_save_MinimizerResult_to_json(obj, filename)
else:
with open(filename, 'w') as f:
json.dump(obj, f, indent=4)
def load_polystyrene_sedimentation_data(size=HOLOGRAM_SIZE, holonums=range(1000),
recenter=True):
camera_resolution = 5.6983 # px / um
metadata = {'spacing' : 1 / camera_resolution,
'medium_index' : 1.33,
'illum_wavelen' : .660,
'illum_polarization' : (1, 0)}
position = [270, 370] # leaves all the particles mostly in the hologram
paths = ["data/Polystyrene2-4um-60xWater-042919/raw/im"
+ zfill(num, 4) + ".tif" for num in holonums]
refimg = hp.load_image(paths[0], **metadata)
bkg = load_bkg(
"data/Polystyrene2-4um-60xWater-042919/raw/",
bg_prefix='bg', refimg=refimg)
dark = load_dark(
"data/Polystyrene2-4um-60xWater-042919/raw/",
df_prefix='dark', refimg=refimg)
holos = []
for path in paths:
this_holo = load_bgdivide_crop(
path=path, metadata=metadata, particle_position=position,
bkg=bkg, dark=dark, size=size, recenter=recenter)[0]
holos.append(this_holo)
return holos
def fastload_polystyrene_sedimentation_data(size=HOLOGRAM_SIZE, recenter=True):
camera_resolution = 5.6983 # px / um
metadata = {'spacing' : 1 / camera_resolution,
'medium_index' : 1.33,
'illum_wavelen' : .660,
'illum_polarization' : (1, 0)}
folder = 'data/Polystyrene2-4um-60xWater-042919/processed-{}'.format(size)
if recenter is False: folder += '-uncentered'
folder = os.path.join(HERE, folder)
paths = [os.path.join(folder + '/im' + zfill(num) + '.tif')
for num in range(1000)]
data = [hp.load_image(path, **metadata) for path in paths]
return data
def load_polystyrene_sedimentation_params():
mo_fits = load_json('fits/Polystyrene2-4um-60xWater-042919/mieonly_fits.json')
ml_fits = load_json('fits/Polystyrene2-4um-60xWater-042919/mielensalpha_fits.json')
return mo_fits, ml_fits
def load_silica_sedimentation_params():
mo_fits = load_json('fits/Silica1um-60xWater-021519/mieonly_guesses.json')
ml_fits = load_json('fits/Silica1um-60xWater-021519/mielens_guesses.json')
return mo_fits, ml_fits
def load_polystyrene_sedimentation_fits(date_subdir="04-02"):
mo_fits = load_pickle('fits/sedimentation/newdata/fits_mo4.pkl')
ml_fits = load_pickle('fits/sedimentation/newdata/fits_ml3.pkl')
return mo_fits, ml_fits
def load_bkg(path, bg_prefix, refimg):
bkg_paths = get_bkg_paths(path, bg_prefix)
bkg = load_average(bkg_paths, refimg=refimg, channel=RGB_CHANNEL)
return bkg
def load_dark(path, df_prefix, refimg):
return load_bkg(path, df_prefix, refimg) if df_prefix is not None else None
def get_bkg_paths(path, bg_prefix):
subdir = os.path.dirname(path)
bkg_paths = [subdir + '/' + pth for pth in os.listdir(subdir) if bg_prefix in pth]
return bkg_paths
def load_bgdivide_crop(
path, metadata, particle_position, bkg, dark, channel=RGB_CHANNEL,
size=HOLOGRAM_SIZE, recenter=True):
data = hp.load_image(path, channel=channel, **metadata)
data = bg_correct(data, bkg, dark)
if recenter:
bbox = subimage(data, particle_position, size)
bbox_corner = np.array([bbox.x.min(), bbox.y.min()])
found_position = np.round(
center_find(bbox) + bbox_corner / metadata['spacing'])
data = subimage(data, found_position, size)
else:
data = subimage(data, particle_position, size)
data = normalize(data)
if recenter:
return data, found_position
return data, None
def bg_correct(raw, bg, df=None):
if df is None:
df = raw.copy()
df[:] = 0
denominator = bg - df
denominator.values = np.clip(denominator.values, 1e-7, np.inf)
holo = (raw - df) / denominator
holo = hp.core.copy_metadata(raw, holo)
return holo
def zfill(n, nzeros=4):
return str(n).rjust(nzeros, '0')
RESULT_ATTRS = ['params', 'status', 'var_names', 'covar', 'init_vals',
'init_values', 'nfev', 'success', 'errorbars', 'message', 'ier',
'lmdif_message', 'nvarys', 'ndata', 'nfree', 'residual',
'chisqr', 'redchi', 'aic', 'bic', 'chain', 'method', 'lnprob']
def _save_MinimizerResult_to_json(result, filename):
serialized_result = _serialize_MinimizerResult(result)
with open(filename, 'w') as f:
json.dump(serialized_result, f, indent=4)
def _serialize_MinimizerResult(result):
attrs = [a for a in RESULT_ATTRS if hasattr(result, a)]
serialized = {a: getattr(result, a) for a in attrs}
serialized['params'] = serialized['params'].dumps()
for k, v in serialized.items():
if isinstance(v, np.ndarray):
serialized[k] = v.tolist()
elif isinstance(v, bool) or isinstance(v, np.bool_):
serialized[k] = 'True' if serialized[k] else 'False'
return serialized
def load_MinimizerResult_from_json(filename):
serialized_result = load_json(filename)
unserialized_result = _unserialize_MinimizerResult(serialized_result)
return MinimizerResult(**unserialized_result)
def _unserialize_MinimizerResult(serialized):
unserialized = serialized
unserialized['params'] = Parameters().loads(serialized['params'])
for k in ['covar', 'residual', 'init_vals', 'lnprob', 'chain']:
if k in serialized:
unserialized[k] = np.array(serialized[k])
if 'success' in serialized:
unserialized['success'] = True if serialized['success'] == 'True' else False
if 'errorbars' in serialized:
unserialized['errorbars'] = (np.bool_(True)
if serialized['errorbars'] == 'True'
else np.bool_(False))
return unserialized
def save_fits_to_json(fits, filename):
params = OrderedDict()
for i, fit in enumerate(fits):
params.update({str(i): fit.params.valuesdict()})
save_json(params, filename)
def load_example_data():
imagepath = hp.core.io.get_example_data_path('image01.jpg')
raw_holo = hp.load_image(imagepath, spacing = 0.0851, medium_index = 1.33,
illum_wavelen = 0.66, illum_polarization = (1,0))
bgpath = hp.core.io.get_example_data_path(['bg01.jpg', 'bg02.jpg', 'bg03.jpg'])
bg = hp.core.io.load_average(bgpath, refimg = raw_holo)
holo = hp.core.process.bg_correct(raw_holo, bg)
holo = hp.core.process.subimage(holo, [250,250], 200)
holo = hp.core.process.normalize(holo)
return holo
def load_gold_example_data():
return normalize(hp.load(hp.core.io.get_example_data_path('image0001.h5')))
def load_silica_sedimentation_data(size=HOLOGRAM_SIZE, holonums=range(100),
recenter=True):
camera_resolution = 5.6983# * 1.5 # px / um
metadata = {'spacing' : 1 / camera_resolution,
'medium_index' : 1.33,
'illum_wavelen' : .660,
'illum_polarization' : (1, 0)}
position = [553, 725] # leaves the particle in the hologram for most frames
paths = ["data/Silica1um-60xWater-021519/raw/image"
+ zfill(num, 4) + ".tif" for num in holonums]
refimg = hp.load_image(paths[0], **metadata)
bkg = load_bkg(
"data/Silica1um-60xWater-021519/raw/",
bg_prefix='bg', refimg=refimg)
dark = load_dark(
"data/Silica1um-60xWater-021519/raw/",
df_prefix='dark', refimg=refimg)
holos = []
all_positions = []
new_pos = None
for path in paths:
this_holo, new_pos = load_bgdivide_crop(
path=path, metadata=metadata, particle_position=position,
bkg=bkg, dark=dark, size=size, recenter=recenter)
holos.append(this_holo)
if new_pos is not None: position = new_pos; all_positions.append([tuple(new_pos)])
return holos
def centerfind_xy_positions_silica(size=HOLOGRAM_SIZE, holonums=range(1000)):
camera_resolution = 5.6983 * 1.5 # px / um
metadata = {'spacing' : 1 / camera_resolution,
'medium_index' : 1.33,
'illum_wavelen' : .660,
'illum_polarization' : (1, 0)}
position = [650, 587] # leaves the particle in the hologram for most frames
paths = ["data/Silica1um-60xWater-080619/raw0[x1.5]/im"
+ zfill(num, 4) + ".tif" for num in holonums]
refimg = hp.load_image(paths[0], **metadata)
bkg = load_bkg(
"data/Silica1um-60xWater-080619/raw0[x1.5]/",
bg_prefix='bg', refimg=refimg)
dark = load_dark(
"data/Silica1um-60xWater-080619/raw0[x1.5]/",
df_prefix='dark', refimg=refimg)
all_positions = []
for path in paths:
this_holo, position = load_bgdivide_crop(
path=path, metadata=metadata, particle_position=position,
bkg=bkg, dark=dark, size=size, recenter=True)
all_positions.append(tuple(position))
return all_positions
def fastload_silica_sedimentation_data(size=HOLOGRAM_SIZE, recenter=True):
camera_resolution = 5.6983# * 1.5 # px / um
metadata = {'spacing' : 1 / camera_resolution,
'medium_index' : 1.33,
'illum_wavelen' : .660,
'illum_polarization' : (1, 0)}
folder = 'data/Silica1um-60xWater-021519/processed-{}'.format(size)
if recenter is False: folder += '-uncentered'
folder = os.path.join(HERE, folder)
paths = [os.path.join(folder + '/im' + zfill(num) + '.h5')
for num in range(100)]
data = [hp.load(path) for path in paths]
return data