Source code for dclab.features.emodulus.load

import copy
import json
import pathlib
from pkg_resources import resource_filename

import numpy as np

from ... import definitions as dfn

#: Dictionary of look-up tables shipped with dclab.
    "LE-2D-FEM-19": "emodulus_lut_LE-2D-FEM-19.txt",

#: Dictionary of look-up tables that the user added via :func:`register_lut`.

[docs]def get_lut_path(path_or_id): """Find the path to a LUT path_or_id: str or pathlib.Path Identifier of a LUT. This can be either an existing path (checked first), or an internal identifier (see :const:`INTERNAL_LUTS`). """ if path_or_id == "FEM-2Daxis": # backwards compatibility path_or_id = "LE-2D-FEM-19" if pathlib.Path(path_or_id).exists(): lut_path = pathlib.Path(path_or_id) elif path_or_id in INTERNAL_LUTS: lut_path = resource_filename("dclab.features.emodulus", INTERNAL_LUTS[path_or_id]) elif path_or_id in EXTERNAL_LUTS: lut_path = EXTERNAL_LUTS[path_or_id] else: raise ValueError("File or LUT identifier does not exist: " + "'{}'".format(path_or_id)) return lut_path
[docs]def load_lut(lut_data="LE-2D-FEM-19"): """Load LUT data from disk Parameters ---------- lut_data: path, str, or tuple of (np.ndarray of shape (N, 3), dict) The LUT data to use. If it is a key in :const:`INTERNAL_LUTS`, then the respective LUT will be used. Otherwise, a path to a file on disk or a tuple (LUT array, meta data) is possible. Returns ------- lut: np.ndarray of shape (N, 3) The LUT data for interpolation meta: dict The LUT metadata Notes ----- If lut_data is a tuple of (lut, meta), then nothing is actually done (this is implemented for user convenience). """ if isinstance(lut_data, tuple): lut, meta = lut_data lut = np.array(lut, copy=True) # copy, because of normalization meta = copy.deepcopy(meta) # copy, for the sake of consistency elif isinstance(lut_data, (str, pathlib.Path)): lut_path = get_lut_path(lut_data) lut, meta = load_mtext(lut_path) else: raise ValueError("`name_path_arr` must be path, identifier, or array, " "got '{}'!".format(lut_data)) return lut, meta
[docs]def load_mtext(path): """Load column-based data from text files with metadata This file format is used for isoelasticity lines and look-up table data in dclab. The text file is loaded with `numpy.loadtxt`. The metadata are stored as a json string between the "BEGIN METADATA" and the "END METADATA" tags. The last comment (#) line before the actual data defines the features with units in square brackets and tab-separated. For instance: # [...] # # BEGIN METADATA # { # "authors": "A. Mietke, C. Herold, J. Guck", # "channel_width": 20.0, # "channel_width_unit": "um", # "date": "2018-01-30", # "dimensionality": "2Daxis", # "flow_rate": 0.04, # "flow_rate_unit": "uL/s", # "fluid_viscosity": 15.0, # "fluid_viscosity_unit": "mPa s", # "identifier": "LE-2D-ana-18", # "method": "analytical", # "model": "linear elastic", # "publication": "", # "software": "custom Matlab code", # "summary": "2D-axis-symmetric analytical solution" # } # END METADATA # # [...] # # area_um [um^2] deform emodulus [kPa] 3.75331e+00 5.14496e-03 9.30000e-01 4.90368e+00 6.72683e-03 9.30000e-01 6.05279e+00 8.30946e-03 9.30000e-01 7.20064e+00 9.89298e-03 9.30000e-01 [...] """ path = pathlib.Path(path).resolve() # Parse metadata size = path.stat().st_size dump = [] injson = False prev_line = "" with"r", errors='replace') as fd: while True: line = fd.readline() if fd.tell() == size: # something went wrong raise ValueError("EOF: Could not parse '{}'!".format(path)) elif len(line.strip()) == 0: # ignore empty lines continue elif not line.strip().startswith("#"): # we are done here if prev_line == "": raise ValueError("No column header in '{}'!".format( path)) break elif line.startswith("# BEGIN METADATA"): injson = True continue elif line.startswith("# END METADATA"): injson = False if injson: dump.append(line.strip("#").strip()) else: # remember last line for header prev_line = line # metadata if dump: meta = json.loads("\n".join(dump)) else: raise ValueError("No metadata json dump in '{}'!".format(path)) # header feats = [] units = [] for hh in prev_line.strip("# ").split("\t"): if hh.count(" "): ft, un = hh.strip().split(" ") un = un.strip("[]") else: ft = hh un = "" if not dfn.scalar_feature_exists(ft): raise ValueError("Scalar feature not known: '{}'".format(ft)) feats.append(ft) units.append(un) # data data = np.loadtxt(path) meta["column features"] = feats meta["column units"] = units # sanity checks assert meta["channel_width_unit"] == "um" assert meta["flow_rate_unit"] == "uL/s" assert meta["fluid_viscosity_unit"] == "mPa s" for ft, un in zip(feats, units): if ft == "deform": assert un == "" elif ft == "area_um": assert un == "um^2" elif ft == "emodulus": assert un == "kPa" elif ft == "volume": assert un == "um^3" else: assert False, "Please add sanity check for {}!".format(ft) return data, meta
[docs]def register_lut(path, identifier=None): """Register an external LUT file in dclab This will add it to :const:`EXTERNAL_LUTS`, which is required for emodulus computation as an ancillary feature. Parameters ---------- path: str or pathlib.Path Path to the external LUT file identifier: str or None The identifier is used for ancillary emodulus computation via the [calculation]: "emodulus lut" key. It is also used as the key in :const:`EXTERNAL_LUTS` during registration. If not specified, (default) then the identifier given as JSON metadata in `path` is used. """ if identifier is None: _, md = load_mtext(path) try: identifier = md["identifier"] except KeyError: raise ValueError("The given LUT file '{}' does ".format(path) + "not contain the 'identifier' keyword. You may " + "specify it via the `identifier` keyword to " + "this function.") if identifier in EXTERNAL_LUTS: raise ValueError("A LUT with an identifier '{}' ".format(identifier) + "has already been registered!") elif identifier in INTERNAL_LUTS: raise ValueError("The identifier '{}' is already ".format(identifier) + "in use by an internal LUT!") EXTERNAL_LUTS[identifier] = path