# -*- coding: utf-8 -*- ''' Created on 17 Feb 2016 @author: Kimon Tsitsikas Copyright © 2016 Kimon Tsitsikas, Delmic This file is part of Odemis. Odemis is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License version 2 as published by the Free Software Foundation. Odemis is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with Odemis. If not, see http://www.gnu.org/licenses/. ''' from __future__ import absolute_import, division import csv import logging import math import numpy from odemis import model from odemis.util import spectrum FORMAT = "CSV" # list of file-name extensions possible, the first one is the default when saving a file EXTENSIONS = [u".csv"] LOSSY = True # because it only supports AR in phi/theta and spectrum in wavelength/intensity format export CAN_SAVE_PYRAMID = False def export(filename, data): ''' Write a CSV file: - If the given data is AR data then just dump the phi/data array - If the given data is spectrum data write it as series of wavelength/intensity filename (unicode): filename of the file to create (including path). data (model.DataArray): the data to export. Metadata is taken directly from the DA object. raises: ValueError in case the spectrum does not contain wavelength metadata. ''' if data.metadata.get(model.MD_ACQ_TYPE, None) == model.MD_AT_SPECTRUM: dims = data.metadata.get(model.MD_DIMS, "CTZYX"[-data.ndim:]) if dims == "C" and data.ndim == 1: spectrum_range, unit = spectrum.get_spectrum_range(data) if unit == "m": spectrum_range = [s * 1e9 for s in spectrum_range] unit = "nm" logging.debug("Exporting spectrum data to CSV") if unit == "nm": # turn range to nm spectrum_tuples = [(s, d) for s, d in zip(spectrum_range, data)] headers = ['# wavelength (nm)', 'intensity'] else: logging.info("Exporting spectrum without wavelength information") spectrum_tuples = data.reshape(data.shape[0], 1) headers = ['# intensity'] with open(filename, 'w') as fd: csv_writer = csv.writer(fd) csv_writer.writerow(headers) csv_writer.writerows(spectrum_tuples) elif dims == "T" and data.ndim == 1: time_range, unit = spectrum.get_time_range(data) if unit == "s": time_range = [t * 1e12 for t in time_range] unit = "ps" logging.debug("Exporting chronogram data to CSV") if unit == "ps": # turn range to nm time_tuples = [(s, d) for s, d in zip(time_range, data)] headers = ['# Time (ps)', 'intensity'] else: logging.info("Exporting chronogram without time list information") time_tuples = data.reshape(data.shape[0], 1) headers = ['# intensity'] with open(filename, 'w') as fd: csv_writer = csv.writer(fd) csv_writer.writerow(headers) csv_writer.writerows(time_tuples) elif data.ndim == 2 and dims == "XC": logging.debug("Exporting spectrum-line data to CSV") spectrum_range, unit = spectrum.get_spectrum_range(data) if unit == "m": spectrum_range = [s * 1e9 for s in spectrum_range] unit = "nm" # attach distance as first row line_length = data.shape[1] * data.metadata[model.MD_PIXEL_SIZE][1] distance_lin = numpy.linspace(0, line_length, data.shape[0]) distance_lin.shape = (distance_lin.shape[0], 1) data = numpy.append(distance_lin, data, axis=1) # Data should be in the form of (X, C+1), with the first row and column the # distance_from_origin\wavelength with open(filename, 'w') as fd: csv_writer = csv.writer(fd) # Set the 'header' in the 0,0 element first_row = ['distance_from_origin(m)\\wavelength(' + unit + ')'] + spectrum_range csv_writer.writerow(first_row) # dump the array csv_writer.writerows(data) else: raise ValueError("Unknown type of data to be exported as CSV") elif data.metadata.get(model.MD_ACQ_TYPE, None) == model.MD_AT_TEMPSPECTRUM: spectrum_range, unit_c = spectrum.get_spectrum_range(data) if unit_c == "m": spectrum_range = [s * 1e9 for s in spectrum_range] unit_c = "nm" time_range, unit_t = spectrum.get_time_range(data) if unit_t == "s": time_range = [t * 1e12 for t in time_range] unit_t = "ps" headers = ["time(" + unit_t + ")\\wavelength(" + unit_c + ")"] + spectrum_range rows = [(t,) + tuple(d) for t, d in zip(time_range, data)] with open(filename, 'w') as fd: csv_writer = csv.writer(fd) csv_writer.writerow(headers) csv_writer.writerows(rows) elif data.metadata.get(model.MD_ACQ_TYPE, None) == model.MD_AT_AR: logging.debug("Exporting AR data to CSV") # Data should be in the form of (Y+1, X+1), with the first row and column the angles with open(filename, 'w') as fd: csv_writer = csv.writer(fd) # TODO: put theta/phi angles in metadata? Read back from MD theta/phi and then add as additional line/column # add the phi and theta values as an extra line/column in order to be displayed in the csv-file # attach theta as first column theta_lin = numpy.linspace(0, math.pi / 2, data.shape[0]) data = numpy.append(theta_lin.reshape(theta_lin.shape[0], 1), data, axis=1) # attach phi as first row phi_lin = numpy.linspace(0, 2 * math.pi, data.shape[1]-1) phi_lin = numpy.append([[0]], phi_lin.reshape(1, phi_lin.shape[0]), axis=1) data = numpy.append(phi_lin, data, axis=0) # Set the 'header' in the 0,0 element first_row = ['theta\\phi[rad]'] + [d for d in data[0, 1:]] csv_writer.writerow(first_row) # dump the array csv_writer.writerows(data[1:, :]) else: raise ValueError("Unknown acquisition type of data to be exported as CSV")