Source code for


# --- import --------------------------------------------------------------------------------------

import os
import pathlib
import time
import warnings

import numpy as np

from ._data import Data
from .. import exceptions as wt_exceptions
from ..kit import _timestamp as timestamp

# --- define --------------------------------------------------------------------------------------

__all__ = ["from_Solis"]

# --- from function -------------------------------------------------------------------------------

[docs]def from_Solis(filepath, name=None, parent=None, verbose=True) -> Data: """Create a data object from Andor Solis software (ascii exports). Parameters ---------- filepath : path-like Path to file (should be .asc format). Can be either a local or remote file (http/ftp). Can be compressed with gz/bz2, decompression based on file name. name : string (optional) Name to give to the created data object. If None, filename is used. Default is None. parent : WrightTools.Collection (optional) Collection to place new data object within. Default is None. verbose : boolean (optional) Toggle talkback. Default is True. Returns ------- data : WrightTools.Data New data object. Channels: `signal`. If exposure time is in metadata, signal is given as a count rate (Hz). Variables, Axes: `yindex` and `xindex` (no grating) or `wm` (grating) Notes ----- When exporting as ascii, including metadata is optional. It is _strongly recommended_ that you include metadata in exports. Metadata informs the image creation date, exposure time, and axes. However, if metadata is not present, this importer will make its best guesses to populate these fields accurately. Saving processed data (e.g. vertically-binned data) in Solis software can remove/omit important metadata, so we advise exporting the raw camera images. """ # parse filepath filestr = os.fspath(filepath) filepath = pathlib.Path(filepath) if not ".asc" in filepath.suffixes: wt_exceptions.WrongFileTypeWarning.warn(filepath, ".asc") # parse name if not name: name =".")[0] # create data ds = np.DataSource(None) f =, "rt") axis0 = [] arr = [] attrs = {} line0 = f.readline().strip()[:-1] line0 = [float(x) for x in line0.split(",")] # TODO: robust to space, tab, comma axis0.append(line0.pop(0)) arr.append(line0) def get_frames(f, arr, axis0): axis0_written = False while True: line = f.readline().strip()[:-1] if len(line) == 0: break else: line = [float(x) for x in line.split(",")] # signature of new frames is restart of axis0 if not axis0_written and (line[0] == axis0[0]): axis0_written = True if axis0_written: line.pop(0) else: axis0.append(line.pop(0)) arr.append(line) return arr, axis0 arr, axis0 = get_frames(f, arr, axis0) nframes = len(arr) // len(axis0) i = 0 while i < 3: line = f.readline().strip() if len(line) == 0: i += 1 else: try: key, val = line.split(":", 1) except ValueError: pass else: attrs[key.strip()] = val.strip() f.close() try: created = attrs["Date and Time"] # is this UTC? created = time.strptime(created, "%a %b %d %H:%M:%S %Y") created = timestamp.TimeStamp(time.mktime(created)).RFC3339 except KeyError: # use file creation time created = os.stat(filepath).st_mtime created = timestamp.TimeStamp(created).RFC3339 warnings.warn( f"{} has no 'Date and Time' field: using file modified time instead: {created}" ) kwargs = {"name": name, "kind": "Solis", "source": filestr, "created": created} if parent is None: data = Data(**kwargs) else: data = parent.create_data(**kwargs) axis0 = np.array(axis0) try: groove_density = float(attrs["Grating Groove Density (l/mm)"]) except KeyError: # assume no grating warnings.warn( f"{} has no 'Grating Groove Density (1/mm)' field: guessing x axis units." ) groove_density = isinstance(axis0[0], float) if groove_density == 0: xname = "xindex" xunits = None else: xname = "wm" xunits = "nm" axes = [xname, "yindex"] if nframes == 1: arr = np.array(arr) data.create_variable(name=xname, values=axis0[:, None], units=xunits) data.create_variable(name="yindex", values=np.arange(arr.shape[-1])[None, :], units=None) else: arr = np.array(arr).reshape(nframes, len(axis0), len(arr[0])) data.create_variable(name="frame", values=np.arange(nframes)[:, None, None], units=None) data.create_variable(name=xname, values=axis0[None, :, None], units=xunits) data.create_variable( name="yindex", values=np.arange(arr.shape[-1])[None, None, :], units=None ) axes = ["frame"] + axes data.transform(*axes) try: exposure_time = float(attrs["Exposure Time (secs)"]) if exposure_time == 0: raise ZeroDivisionError arr /= exposure_time except (KeyError, ZeroDivisionError) as e: # do not normalize warnings.warn(f"{} camera signal cannot be given as a count rate.") data.create_channel(name="signal", values=arr, signed=False) else: # signal has units of Hz because time normalized data.create_channel(name="signal", values=arr, signed=False, units="Hz") for key, val in attrs.items(): data.attrs[key] = val # finish if verbose: print("data created at {0}".format(data.fullpath)) print(" axes: {0}".format(data.axis_names)) print(" shape: {0}".format(data.shape)) return data