text: # coding: utf-8
  #
  #    Project: Azimuthal integration
  #             https://github.com/silx-kit/pyFAI
  #
  #    Copyright (C) 2015-2019 European Synchrotron Radiation Facility, Grenoble, France
  #
  #    Principal author:       Jérôme Kieffer (Jerome.Kieffer@ESRF.eu)
  #
  # Permission is hereby granted, free of charge, to any person obtaining a copy
  # of this software and associated documentation files (the "Software"), to deal
  # in the Software without restriction, including without limitation the rights
  # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
  # copies of the Software, and to permit persons to whom the Software is
  # furnished to do so, subject to the following conditions:
  #
  # The above copyright notice and this permission notice shall be included in
  # all copies or substantial portions of the Software.
  #
  # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
  # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
  # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
  # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
  # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  # THE SOFTWARE.
  
  """Module for "high-performance" writing in either 1D with Ascii ,
  or 2D with FabIO or even nD with n varying from  2 to 4 using HDF5
  
  Stand-alone module which tries to offer interface to HDF5 via H5Py and
  capabilities to write EDF or other formats using fabio.
  
  Can be imported without h5py but then limited to fabio & ascii formats.
  
  TODO:
  
  - Add monitor to HDF5
  """
  
  from __future__ import absolute_import, print_function, division
  
  __author__ = "Jerome Kieffer"
  __contact__ = "Jerome.Kieffer@ESRF.eu"
  __license__ = "MIT"
  __copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
  __date__ = "02/04/2020"
  __status__ = "production"
  __docformat__ = 'restructuredtext'
  
  import json
  import logging
  import numpy
  import os
  import posixpath
  import sys
  import threading
  import time
  from collections import OrderedDict
  import __main__ as main
  from pyFAI.third_party import six
  from ..utils import StringTypes, fully_qualified_name
  from .. import units
  from .. import version
  from .. import containers
  
  logger = logging.getLogger(__name__)
  try:
      import fabio
  except ImportError:
      fabio = None
      logger.error("fabio module missing")
  
  from .nexus import get_isotime, from_isotime, is_hdf5, Nexus, h5py
  
  # Activating compression has an important performance penalty and,
  # as we are saving Float32, the compression obtained is far from optimal
  #
  # # If compression is activated, thetest pyFAI.test.test_io is likely to fail
  #
  # try:
  #     import hdf5plugin
  # except ImportError:
  #     CMP = {}
  # else:
  #     CMP = hdf5plugin.Bitshuffle()
  CMP = {}
  
  
  class Writer(object):
      """
      Abstract class for writers.
      """
      CONFIG_ITEMS = ["filename", "dirname", "extension", "subdir", "hpath"]
  
      def __init__(self, filename=None, extension=None):
          """
          Constructor of the class
          """
          # FIXME: Writer interface should have no constructor arguments
          #     (that's specific to each writers)
          self.filename = filename
          if filename is not None and os.path.exists(filename):
              logger.warning("Destination file %s exists", filename)
          self._sem = threading.Semaphore()
          self.dirname = None
          self.subdir = None
          self.extension = extension
          self.fai_cfg = {}
          self.lima_cfg = {}
  
      def __repr__(self):
          return "Generic writer on file %s" % (self.filename)
  
      def init(self, fai_cfg=None, lima_cfg=None):
          """
          Creates the directory that will host the output file(s)
          :param fai_cfg: configuration for worker
          :param lima_cfg: configuration for acquisition
          """
  
          with self._sem:
              if fai_cfg is not None:
                  self.fai_cfg = fai_cfg
              if lima_cfg is not None:
                  self.lima_cfg = lima_cfg
              if self.filename is not None:
                  dirname = os.path.dirname(self.filename)
                  if dirname and not os.path.exists(dirname):
                      try:
                          os.makedirs(dirname)
                      except Exception as err:
                          logger.info("Problem while creating directory %s: %s", dirname, err)
  
      def flush(self, *arg, **kwarg):
          """
          To be implemented
          """
          pass
  
      def write(self, data):
          """
          To be implemented
          """
          pass
  
      def setJsonConfig(self, json_config=None):
          """
          Sets the JSON configuration
          """
  
          if type(json_config) in StringTypes:
              if os.path.isfile(json_config):
                  with open(json_config, "r") as f:
                      config = json.load(f)
              else:
                  config = json.loads(json_config)
          else:
              config = dict(json_config)
          for k, v in config.items():
              if k in self.CONFIG_ITEMS:
                  self.__setattr__(k, v)
  
  
  class HDF5Writer(Writer):
      """
      Class allowing to write HDF5 Files.
      """
      CONFIG = "configuration"
      DATASET_NAME = "data"
  
      MODE_ERROR = "error"
      MODE_DELETE = "delete"
      MODE_APPEND = "append"
      MODE_OVERWRITE = "overwrite"
  
      def __init__(self, filename, hpath=None, entry_template=None, fast_scan_width=None, append_frames=False, mode=MODE_ERROR):
          """
          Constructor of an HDF5 writer:
  
          :param str filename: name of the file
          :param str hpath: Name of the entry group that will contains the NXprocess.
          :param str entry_template: Formattable template to create a new entry (if hpath is not specified)
          :param int fast_scan_width: set it to define the width of
          """
          Writer.__init__(self, filename)
          if entry_template is None:
              entry_template = "entry_{num:04}"
          self._entry_template = entry_template
  
          self.hpath = hpath
  
          self.fast_scan_width = None
          if fast_scan_width is not None:
              try:
                  self.fast_scan_width = int(fast_scan_width)
              except ValueError:
                  pass
          self.nxs = None
          self.entry_grp = None
          self.process_grp = None
          self.nxdata_grp = None
          self.intensity_ds = None
          self.error_ds = None
          self.stored_input = set()
  
          self.config_grp = None
          self.radial_ds = None
          self.azimuthal_ds = None
          self.error_ds = None
          self.has_radial_values = False
          self.has_azimuthal_values = False
          self.has_error_values = False
          self.chunk = None
          self.shape = None
          self.ndim = None
          self.do2D = None
          self._current_frame = None
          self._append_frames = append_frames
          self._mode = mode
  
      def __repr__(self):
          return "HDF5 writer on file %s:%s %sinitialized" % (self.filename, self.hpath, "" if self._initialized else "un")
  
      def _require_main_entry(self, mode):
          """
          Create and return the main entry used to store the data processing.
  
          Update `self.hpath` is needed.
  
          Load and return the entry while will contains the data processing.
  
          According to modes, this function will delete and recreate the file,
          or append the data to a new entry, or overwrite the existing entry.
          """
          if h5py is None:
              logger.error("No h5py library, no chance")
              raise RuntimeError("No h5py library, no chance")
  
          try:
              if mode == self.MODE_DELETE:
                  self.nxs = Nexus(self.filename, mode="w", creator="pyFAI")
              else:
                  self.nxs = Nexus(self.filename, mode="a", creator="pyFAI")
          except IOError:  # typically a corrupted HDF5 file !
              if mode == self.MODE_DELETE:
                  logger.error("File can't be read. File %s deleted.", self.filename)
                  os.unlink(self.filename)
                  self.nxs = Nexus(self.filename, mode="w", creator="pyFAI")
              else:
                  raise
  
          name = self.hpath or self._entry_template.split("_")[0]
          if "/" in name:
              logger.error("NXentry should always be at the NXroot level. Please consider using a NXsubentry then")
              force_name = True
          else:
              force_name = False
  
          try:
              entry = self.nxs.new_entry(entry=name, program_name="pyFAI",
                                         title=None, force_name=force_name)
          except TypeError:  # object already exists
              nb_entries = len(self.nxs.get_entries())
              entry_base = self.hpath or self._entry_template.split("_")[0]
              entry_name = "%s_%04i" % (entry_base, nb_entries)
              if mode == self.MODE_OVERWRITE:
                  del self.nxs.h5[entry_name]
                  entry = self.nxs.new_entry(entry=entry_name, force_name=True,
                                             program_name="pyFAI", title=None)
              elif mode == self.MODE_ERROR:
                  raise IOError("Entry name %s::%s already exists" % (self.filename, entry_name))
              elif mode == self.MODE_APPEND:
                  while entry_name in self.nxs.h5:
                      nb_entries += 1
                      entry_name = "%s_%04i" % (entry_base, nb_entries)
                  entry = self.nxs.new_entry(entry=entry_name, force_name=True,
                                             program_name="pyFAI", title=None)
              else:
                  assert(False)
          entry["program_name"].attrs["version"] = version
          self.hpath = entry.name
          return entry
  
      def init(self, fai_cfg=None, lima_cfg=None):
          """
          Initializes the HDF5 file for writing
          :param fai_cfg: the configuration of the worker as a dictionary
          """
          logger.debug("Init")
          Writer.init(self, fai_cfg, lima_cfg)
  
          with self._sem:
              if logger.isEnabledFor(logging.DEBUG):
                  open("fai_cfg.debug.json", "w").write(json.dumps(self.fai_cfg, indent=4))
                  open("lima_cfg.debug.json", "w").write(json.dumps(self.lima_cfg, indent=4))
  
              self.fai_cfg["nbpt_rad"] = self.fai_cfg.get("nbpt_rad", 1000)
  
              self.entry_grp = self._require_main_entry(self._mode)
  
              self.nxs.h5.attrs["default"] = self.hpath
              self.entry_grp.attrs["default"] = "integrate/results"
              self.process_grp = self.nxs.new_class(self.entry_grp, "integrate", class_type="NXprocess")
              self.process_grp["program"] = getattr(main, '__file__', u'pyFAI')
              self.process_grp["version"] = version
              self.process_grp["date"] = get_isotime()
              self.process_grp["sequence_index"] = 1
              self.process_grp.attrs["default"] = "results"
  
              self.nxdata_grp = self.nxs.new_class(self.process_grp, "results", "NXdata")
              self.nxdata_grp.attrs["signal"] = self.DATASET_NAME
  
              self.config_grp = self.nxs.new_class(self.process_grp, self.CONFIG, "NXnote")
              self.config_grp.attrs["desc"] = "PyFAI worker configuration"
              self.config_grp["type"] = "text/json"
              self.config_grp["data"] = json.dumps(self.fai_cfg, indent=2, separators=(",\r\n", ": "))
  
              rad_name, rad_unit = str(self.fai_cfg.get("unit", "2th_deg")).split("_", 1)
  
              self.radial_ds = self.nxdata_grp.require_dataset("radial", (self.fai_cfg["nbpt_rad"],), numpy.float32)
              self.radial_ds.attrs["unit"] = rad_unit
              self.radial_ds.attrs["interpretation"] = "scalar"
              self.radial_ds.attrs["name"] = rad_name
              self.radial_ds.attrs["long_name"] = "Diffraction radial direction %s (%s)" % (rad_name, rad_unit)
  
              self.do2D = self.fai_cfg.get("do_2D", self.fai_cfg.get("nbpt_azim", 0) > 0)
  
              if self.do2D:
                  self.azimuthal_ds = self.nxdata_grp.require_dataset("chi", (self.fai_cfg["nbpt_azim"],), numpy.float32)
                  self.azimuthal_ds.attrs["unit"] = "deg"
                  self.azimuthal_ds.attrs["interpretation"] = "scalar"
                  self.azimuthal_ds.attrs["long_name"] = "Azimuthal angle χ (degree)"
                  self.nxdata_grp["title"] = "2D azimuthaly integrated data"
              else:
                  self.nxdata_grp["title"] = "Azimuthaly integrated data"
  
              if self.fast_scan_width:
                  self.fast_motor = self.entry_grp.require_dataset("fast", (self.fast_scan_width,), numpy.float32)
                  self.fast_motor.attrs["long_name"] = "Fast motor position"
                  self.fast_motor.attrs["interpretation"] = "scalar"
                  if self.do2D:
                      chunk = 1, self.fast_scan_width, self.fai_cfg["nbpt_azim"], self.fai_cfg["nbpt_rad"]
                      self.ndim = 4
                      axis_definition = [".", "fast", "chi", "radial"]
                  else:
                      chunk = 1, self.fast_scan_width, self.fai_cfg["nbpt_rad"]
                      self.ndim = 3
                      axis_definition = [".", "fast", "radial"]
              else:
                  if self.do2D:
                      axis_definition = [".", "chi", "radial"]
                      chunk = 1, self.fai_cfg["nbpt_azim"], self.fai_cfg["nbpt_rad"]
                      self.ndim = 3
                  else:
                      axis_definition = [".", "radial"]
                      chunk = 1, self.fai_cfg["nbpt_rad"]
                      self.ndim = 2
  
              utf8vlen_dtype = h5py.special_dtype(vlen=six.text_type)
              self.nxdata_grp.attrs["axes"] = numpy.array(axis_definition, dtype=utf8vlen_dtype)
  
              if self.DATASET_NAME in self.nxdata_grp:
                  del self.nxdata_grp[self.DATASET_NAME]
              shape = list(chunk)
              if self.lima_cfg.get("number_of_frames", 0) > 0:
                  if self.fast_scan_width is not None:
                      shape[0] = 1 + self.lima_cfg["number_of_frames"] // self.fast_scan_width
                  else:
                      shape[0] = self.lima_cfg["number_of_frames"]
              dtype = self.lima_cfg.get("dtype") or self.fai_cfg.get("dtype")
              if dtype is None:
                  dtype = numpy.float32
              else:
                  dtype = numpy.dtype(dtype)
              self.chunk = tuple(chunk)
              self.shape = tuple(shape)
              self.intensity_ds = self._require_dataset(self.DATASET_NAME, dtype=dtype)
              name = "Mapping " if self.fast_scan_width else "Scanning "
              name += "2D" if self.fai_cfg.get("nbpt_azim", 0) > 1 else "1D"
              name += " experiment"
              self.entry_grp["title"] = name
  
      def flush(self, radial=None, azimuthal=None):
          """
          Update some data like axis units and so on.
  
          :param radial: position in radial direction
          :param  azimuthal: position in azimuthal direction
          """
          with self._sem:
              if not (self.nxs and self.nxs.h5):
                  raise RuntimeError('No opened file')
              if radial is not None:
                  if radial.shape == self.radial_ds.shape:
                      self.radial_ds[:] = radial
                  else:
                      logger.warning("Unable to assign radial axis position")
              if azimuthal is not None:
                  if azimuthal.shape == self.azimuthal_ds.shape:
                      self.azimuthal_ds[:] = azimuthal
                  else:
                      logger.warning("Unable to assign azimuthal axis position")
              self.nxs.flush()
  
      def close(self):
          logger.debug("Close")
          if self.nxs:
              self.flush()
              with self._sem:
                  # Remove any links to HDF5 file
                  self.entry_grp = None
                  self.nxdata_grp = None
                  self.config_grp = None
                  self.process_grp = None
                  self.intensity_ds = None
                  self.error_ds = None
                  self.radial_ds = None
                  self.azimuthal_ds = None
                  self.fast_motor = None
                  # Close the file
                  self.nxs.close()
                  self.nxs = None
  
      def write(self, data, index=None):
          """
          Minimalistic method to limit the overhead.
          :param data: array with intensities or tuple (2th,I) or (I,2th,chi)
          """
          if index is None:
              if self._append_frames:
                  if self._current_frame is None:
                      self._current_frame = 0
                  else:
                      self._current_frame = self._current_frame + 1
                  index = self._current_frame
              else:
                  index = 0
          logger.debug("Write frame %s", index)
          radial = None
          azimuthal = None
          error = None
          if isinstance(data, containers.Integrate1dResult):
              intensity = data.intensity
              radial = data.radial
              error = data.sigma
          elif isinstance(data, containers.Integrate2dResult):
              intensity = data.intensity
              radial = data.radial
              azimuthal = data.azimuthal
              error = data.sigma
          elif isinstance(data, numpy.ndarray):
              intensity = data
          elif isinstance(data, (list, tuple)):
              n = len(data)
              if n == 2:
                  radial, intensity = data
              elif n == 3:
                  if data[0].ndim == 2:
                      intensity, radial, azimuthal = data
                  else:
                      radial, intensity, error = data
          with self._sem:
              if self.intensity_ds is None:
                  logger.warning("Writer not initialized !")
                  return
              if error is not None and self.error_ds is None:
                  self.error_ds = self._require_dataset(self.DATASET_NAME + "_errors", dtype=error.dtype)
  
              if self.fast_scan_width:
                  index0, index1 = (index // self.fast_scan_width, index % self.fast_scan_width)
                  if index0 >= self.intensity_ds.shape[0]:
                      self.intensity_ds.resize(index0 + 1, axis=0)
                      if error is not None:
                          self.error_ds.resize(index0 + 1, axis=0)
                  self.intensity_ds[index0, index1] = data
                  if error is not None:
                      self.error_ds [index0, index1] = error
              else:
                  if index >= self.intensity_ds.shape[0]:
                      self.intensity_ds.resize(index + 1, axis=0)
                      if error is not None:
                          self.error_ds.resize(index + 1, axis=0)
                  self.intensity_ds[index] = intensity
                  if error is not None:
                      self.error_ds [index] = error
  
              if (not self.has_azimuthal_values) and \
                 (azimuthal is not None) and \
                 self.azimuthal_ds is not None:
                  self.azimuthal_ds[:] = azimuthal
              if (not self.has_azimuthal_values) and \
                 (azimuthal is not None) and \
                 self.azimuthal_ds is not None:
                  self.azimuthal_ds[:] = azimuthal
                  self.has_azimuthal_values = True
              if (not self.has_radial_values) and \
                 (radial is not None) and \
                 self.radial_ds is not None:
                  self.radial_ds[:] = radial
                  self.has_radial_values = True
  
      def _require_dataset(self, name, dtype):
          """Returns the dataset to store data/error ."""
  
          if self.do2D:
              result = self.nxdata_grp.require_dataset(name,
                                                       shape=self.shape,
                                                       dtype=dtype,
                                                       chunks=self.chunk,
                                                       maxshape=(None,) + self.chunk[1:],
                                                       **CMP)
              result.attrs["interpretation"] = u"image"
          else:
              result = self.nxdata_grp.require_dataset(name,
                                                       shape=self.shape,
                                                       dtype=dtype,
                                                       chunks=self.chunk,
                                                       maxshape=(None,) + self.chunk[1:])
  
              result.attrs["interpretation"] = u"spectrum"
          return result
  
      def set_hdf5_input_dataset(self, dataset):
          "record the input dataset with an external link"
          if not isinstance(dataset, h5py.Dataset):
              return
          if not (self.nxs and self.nxs.h5 and self.entry_grp):
              return
          id_ = id(dataset)
          if id_ in self.stored_input:
              return
          else:
              self.stored_input.add(id_)
          # Process 0: measurement group
          if "measurement" in self.entry_grp:
              measurement_grp = self.entry_grp["measurement"]
          else:
              measurement_grp = self.nxs.new_class(self.entry_grp, "measurement", "NXdata")
          here = os.path.dirname(os.path.abspath(self.nxs.filename))
          there = os.path.abspath(dataset.file.filename)
          name = "images_%04i" % len(self.stored_input)
          measurement_grp[name] = h5py.ExternalLink(os.path.relpath(there, here), dataset.name)
          if "signal" not in measurement_grp.attrs:
              measurement_grp.attrs["signal"] = name
  
  
  class DefaultAiWriter(Writer):
  
      def __init__(self, filename, engine=None):
          """Constructor of the historical writer of azimuthalIntegrator.
  
          :param filename: name of the output file
          :param ai: integrator, should provide make_headers method.
          """
          super(DefaultAiWriter, self).__init__(filename, engine)
          self._filename = filename
          self._engine = engine
          self._already_written = False
  
      def init(self, fai_cfg=None, lima_cfg=None):
          pass
  
      def set_filename(self, filename):
          """
          Define the filename while will be used
          """
          self._filename = filename
          self._already_written = False
  
      def make_headers(self, hdr="#", has_mask=None, has_dark=None, has_flat=None,
                       polarization_factor=None, normalization_factor=None,
                       metadata=None):
          """
          :param hdr: string used as comment in the header
          :type hdr: str
          :param has_dark: save the darks filenames (default: no)
          :type has_dark: bool
          :param has_flat: save the flat filenames (default: no)
          :type has_flat: bool
          :param polarization_factor: the polarization factor
          :type polarization_factor: float
  
          :return: the header
          :rtype: str
          """
          if "make_headers" in dir(self._engine):
              header_lst = self._engine.make_headers()
          else:
              header_lst = [str(self._engine), ""]
  
          header_lst += ["Mask applied: %s" % has_mask,
                         "Dark current applied: %s" % has_dark,
                         "Flat field applied: %s" % has_flat,
                         "Polarization factor: %s" % polarization_factor,
                         "Normalization factor: %s" % normalization_factor]
  
          if metadata is not None:
              header_lst += ["", "Headers of the input frame:"]
              header_lst += [i.strip() for i in json.dumps(metadata, indent=2).split("\n")]
          header = "\n".join(["%s %s" % (hdr, i) for i in header_lst])
  
          return header
  
      def save1D(self, filename, dim1, I, error=None, dim1_unit="2th_deg",
                 has_mask=None, has_dark=False, has_flat=False,
                 polarization_factor=None, normalization_factor=None, metadata=None):
          """This method save the result of a 1D integration as ASCII file.
  
          :param filename: the filename used to save the 1D integration
          :type filename: str
          :param dim1: the x coordinates of the integrated curve
          :type dim1: numpy.ndarray
          :param I: The integrated intensity
          :type I: numpy.mdarray
          :param error: the error bar for each intensity
          :type error: numpy.ndarray or None
          :param dim1_unit: the unit of the dim1 array
          :type dim1_unit: pyFAI.units.Unit
          :param has_mask: a mask was used
          :param has_dark: a dark-current was applied
          :param has_flat: flat-field was applied
          :param polarization_factor: the polarization factor
          :type polarization_factor: float, None
          :param normalization_factor: the monitor value
          :type normalization_factor: float, None
          :param metadata: JSON serializable dictionary containing the metadata
          """
          dim1_unit = units.to_unit(dim1_unit)
          with open(filename, "w") as f:
              f.write(self.make_headers(has_mask=has_mask, has_dark=has_dark,
                                        has_flat=has_flat,
                                        polarization_factor=polarization_factor,
                                        normalization_factor=normalization_factor,
                                        metadata=metadata))
              try:
                  f.write("\n# --> %s\n" % (filename))
              except UnicodeError:
                  f.write("\n# --> %s\n" % (filename.encode("utf8")))
              if error is None:
                  f.write("#%14s %14s\n" % (dim1_unit, "I "))
                  f.write("\n".join(["%14.6e  %14.6e" % (t, i) for t, i in zip(dim1, I)]))
              else:
                  f.write("#%14s  %14s  %14s\n" %
                          (dim1_unit, "I ", "sigma "))
                  f.write("\n".join(["%14.6e  %14.6e %14.6e" % (t, i, s) for t, i, s in zip(dim1, I, error)]))
              f.write("\n")
  
      def save2D(self, filename, I, dim1, dim2, error=None, dim1_unit="2th_deg",
                 has_mask=None, has_dark=False, has_flat=False,
                 polarization_factor=None, normalization_factor=None,
                 metadata=None):
          """This method save the result of a 2D integration.
  
          :param filename: the filename used to save the 2D histogram
          :type filename: str
          :param dim1: the 1st coordinates of the histogram
          :type dim1: numpy.ndarray
          :param dim1: the 2nd coordinates of the histogram
          :type dim1: numpy.ndarray
          :param I: The integrated intensity
          :type I: numpy.mdarray
          :param error: the error bar for each intensity
          :type error: numpy.ndarray or None
          :param dim1_unit: the unit of the dim1 array
          :type dim1_unit: pyFAI.units.Unit
          :param has_mask: a mask was used
          :param has_dark: a dark-current was applied
          :param has_flat: flat-field was applied
          :param polarization_factor: the polarization factor
          :type polarization_factor: float, None
          :param normalization_factor: the monitor value
          :type normalization_factor: float, None
          :param metadata: JSON serializable dictionary containing the metadata
          """
          if fabio is None:
              raise RuntimeError("FabIO module is needed to save EDF images")
          dim1_unit = units.to_unit(dim1_unit)
  
          # Remove \n and \t)
          engine_info = " ".join(str(self._engine).split())
          header = OrderedDict()
          header["Engine"] = engine_info
  
          if "make_headers" in dir(self._engine):
              header.update(self._engine.make_headers("dict"))
  
          header[dim1_unit.name + "_min"] = str(dim1.min())
          header[dim1_unit.name + "_max"] = str(dim1.max())
  
          header["chi_min"] = str(dim2.min())
          header["chi_max"] = str(dim2.max())
  
          header["has_mask_applied"] = str(has_mask)
          header["has_dark_correction"] = str(has_dark)
          header["has_flat_correction"] = str(has_flat)
          header["polarization_factor"] = str(polarization_factor)
          header["normalization_factor"] = str(normalization_factor)
  
          if metadata is not None:
              blacklist = ['HEADERID', 'IMAGE', 'BYTEORDER', 'DATATYPE', 'DIM_1',
                           'DIM_2', 'DIM_3', 'SIZE']
              for key, value in metadata.items():
                  if key.upper() in blacklist or key in header:
                      continue
                  else:
                      header[key] = value
          try:
              img = fabio.edfimage.edfimage(data=I.astype("float32"),
                                            header=header)
  
              if error is not None:
                  img.appendFrame(data=error, header={"EDF_DataBlockID": "1.Image.Error"})
              img.write(filename)
          except IOError:
              logger.error("IOError while writing %s", filename)
  
      def write(self, data):
          """
          Minimalistic method to limit the overhead.
  
          :param data: array with intensities or tuple (2th,I) or (I,2th,chi)\
          :type data: Integrate1dResult, Integrate2dResult
          """
  
          if self._already_written:
              raise Exception("This file format do not support multi frame. You have to change the filename.")
          self._already_written = True
  
          if isinstance(data, containers.Integrate1dResult):
              self.save1D(filename=self._filename,
                          dim1=data.radial,
                          I=data.intensity,
                          error=data.sigma,
                          dim1_unit=data.unit,
                          has_mask=data.has_mask_applied,
                          has_dark=data.has_dark_correction,
                          has_flat=data.has_flat_correction,
                          polarization_factor=data.polarization_factor,
                          normalization_factor=data.normalization_factor,
                          metadata=data.metadata)
  
          elif isinstance(data, containers.Integrate2dResult):
              self.save2D(filename=self._filename,
                          I=data.intensity,
                          dim1=data.radial,
                          dim2=data.azimuthal,
                          error=data.sigma,
                          dim1_unit=data.unit,
                          has_mask=data.has_mask_applied,
                          has_dark=data.has_dark_correction,
                          has_flat=data.has_flat_correction,
                          polarization_factor=data.polarization_factor,
                          normalization_factor=data.normalization_factor,
                          metadata=data.metadata)
          else:
              raise Exception("Unsupported data type: %s" % type(data))
  
      def flush(self):
          pass
  
      def close(self):
          pass
  
  
  class AsciiWriter(Writer):
      """
      Ascii file writer (.xy or .dat)
      """
  
      def __init__(self, filename=None, prefix="fai_", extension=".dat"):
          """
  
          """
          Writer.__init__(self, filename, extension)
          self.header = None
          if os.path.isdir(filename):
              self.directory = filename
          else:
              self.directory = os.path.dirname(filename)
          self.prefix = prefix
          self.index_format = "%04i"
          self.start_index = 0
  
      def __repr__(self):
          return "Ascii writer on file %s" % (self.filename)
  
      def init(self, fai_cfg=None, lima_cfg=None):
          """
          Creates the directory that will host the output file(s)
  
          """
          Writer.init(self, fai_cfg, lima_cfg)
          with self._sem:
              header_lst = ["", "== Detector =="]
              if "detector" in self.fai_cfg:
                  header_lst.append("Detector: %s" % self.fai_cfg["detector"])
              if "splineFile" in self.fai_cfg:
                  header_lst.append("SplineFile: %s" % self.fai_cfg["splineFile"])
              if "pixel1" in self.fai_cfg:
                  header_lst.append("PixelSize: %.3e, %.3e m" % (self.fai_cfg["pixel1"], self.fai_cfg["pixel2"]))
              if "mask_file" in self.fai_cfg:
                  header_lst.append("MaskFile: %s" % (self.fai_cfg["mask_file"]))
  
              header_lst.append("== pyFAI calibration ==")
              if "poni1" in self.fai_cfg:
                  header_lst.append("PONI: %.3e, %.3e m" % (self.fai_cfg["poni1"], self.fai_cfg["poni2"]))
              if "dist" in self.fai_cfg:
                  header_lst.append("Distance Sample to Detector: %s m" % self.fai_cfg["dist"])
              if "rot1" in self.fai_cfg:
                  header_lst.append("Rotations: %.6f %.6f %.6f rad" % (self.fai_cfg["rot1"], self.fai_cfg["rot2"], self.fai_cfg["rot3"]))
              if "wavelength" in self.fai_cfg:
                  header_lst.append("Wavelength: %s" % self.fai_cfg["wavelength"])
              if "dark_current" in self.fai_cfg:
                  header_lst.append("Dark current: %s" % self.fai_cfg["dark_current"])
              if "flat_field" in self.fai_cfg:
                  header_lst.append("Flat field: %s" % self.fai_cfg["flat_field"])
              if "polarization_factor" in self.fai_cfg:
                  header_lst.append("Polarization factor: %s" % self.fai_cfg["polarization_factor"])
              header_lst.append("")
              if "do_poisson" in self.fai_cfg:
                  header_lst.append("%14s %14s %s" % (self.fai_cfg["unit"], "I", "sigma"))
              else:
                  header_lst.append("%14s %14s" % (self.fai_cfg["unit"], "I"))
  #            header_lst.append("")
              self.header = os.linesep.join([""] + ["# " + i for i in header_lst] + [""])
          self.prefix = lima_cfg.get("prefix", self.prefix)
          self.index_format = lima_cfg.get("index_format", self.index_format)
          self.start_index = lima_cfg.get("start_index", self.start_index)
          if not self.subdir:
              self.directory = lima_cfg.get("directory", self.directory)
          elif self.subdir.startswith("/"):
              self.directory = self.subdir
          else:
              self.directory = os.path.join(lima_cfg.get("directory", self.directory), self.subdir)
          if not os.path.exists(self.directory):
              logger.warning("Output directory: %s does not exist,creating it", self.directory)
              try:
                  os.makedirs(self.directory)
              except Exception as error:
                  logger.info("Problem while creating directory %s: %s", self.directory, error)
  
      def write(self, data, index=0):
          filename = os.path.join(self.directory, self.prefix + (self.index_format % (self.start_index + index)) + self.extension)
          if filename:
              with open(filename, "w") as f:
                  f.write("# Processing time: %s%s" % (get_isotime(), self.header))
                  numpy.savetxt(f, data)
  
  
  class FabioWriter(Writer):
      """
      Image file writer based on FabIO
  
      TODO !!!
      """
  
      def __init__(self, filename=None):
          """
  
          """
          Writer.__init__(self, filename)
          self.header = None
          self.directory = None
          self.prefix = None
          self.index_format = "%04i"
          self.start_index = 0
          self.fabio_class = None
          if fabio is None:
              raise RuntimeError("FabIO module is needed to save images")
  
      def __repr__(self):
          return "Image writer on file %s" % (self.filename)
  
      def init(self, fai_cfg=None, lima_cfg=None):
          """
          Creates the directory that will host the output file(s)
  
          """
          Writer.init(self, fai_cfg, lima_cfg)
          with self._sem:
              # dim1_unit = units.to_unit(fai_cfg.get("unit", "r_mm"))
              _header_keys = ["dist", "poni1", "poni2", "rot1", "rot2", "rot3",
                              ]
              _header = {"dist": str(fai_cfg.get("dist")),
                         "poni1": str(fai_cfg.get("poni1")),
                         "poni2": str(fai_cfg.get("poni2")),
                         "rot1": str(fai_cfg.get("rot1")),
                         "rot2": str(fai_cfg.get("rot2")),
                         "rot3": str(fai_cfg.get("rot3")),
                         # "chi_min": str(fai_cfg.get("chi_min")),
                         # "chi_max": str(fai_cfg.get("chi_max")),
                         # dim1_unit.REPR + "_min": str(fai_cfg.get("dist")),
                         # dim1_unit.REPR + "_max": str(fai_cfg.get("dist")),
                         # "pixelX": str(fai_cfg.get("dist")),  # this is not a bug ... most people expect dim1 to be X
                         # "pixelY": str(fai_cfg.get("dist")),  # this is not a bug ... most people expect dim2 to be Y
                         # "polarization_factor": str(fai_cfg.get("dist")),
                         # "normalization_factor":str(fai_cfg.get("dist")),
                         }
  
  #            if self.splineFile:
  #                header["spline"] = str(self.splineFile)
  #
  #            if dark is not None:
  #                if self.darkfiles:
  #                    header["dark"] = self.darkfiles
  #                else:
  #                    header["dark"] = 'unknown dark applied'
  #            if flat is not None:
  #                if self.flatfiles:
  #                    header["flat"] = self.flatfiles
  #                else:
  #                    header["flat"] = 'unknown flat applied'
  #            f2d = self.getFit2D()
  #            for key in f2d:
  #                header["key"] = f2d[key]
          self.prefix = fai_cfg.get("prefix", "")
          self.index_format = fai_cfg.get("index_format", "%04i")
          self.start_index = fai_cfg.get("start_index", 0)
          if not self.subdir:
              self.directory = directory
          elif self.subdir.startswith("/"):
              self.directory = self.subdir
          else:
              self.directory = os.path.join(directory, self.subdir)
          if not os.path.exists(self.directory):
              logger.warning("Output directory: %s does not exist,creating it", self.directory)
              try:
                  os.makedirs(self.directory)
              except Exception as error:
                  logger.info("Problem while creating directory %s: %s", self.directory, error)
  
      def write(self, data, index=0):
          filename = os.path.join(self.directory, self.prefix + (self.index_format % (self.start_index + index)) + self.extension)
          if filename:
              with open(filename, "w") as f:
                  f.write("# Processing time: %s%s" % (get_isotime(), self.header))
                  numpy.savetxt(f, data)
  
  