Exemplo n.º 1
0
def save_metadata(instance, schema, metadata):
    parameters = get_parameters(schema, metadata)
    logger.debug("parameters=%s" % parameters)
    if not parameters:
        return None

    try:
        ps = DatasetParameterSet.objects.get(schema=schema, dataset=instance)
        # return ps
    except DatasetParameterSet.DoesNotExist:
        ps = DatasetParameterSet(schema=schema, dataset=instance)
        ps.save()

    logger.debug("ps=%s\n" % ps)
    logger.debug("metadata2=%s\n" % metadata)

    for p in parameters:
        logger.debug("p=%s\n" % p)
        if p.name in metadata:
            logger.debug("found p =%s %s\n" % (p.name, p.units))
            try:
                dfp = DatasetParameter.objects.get(parameterset=ps, name=p)
            except DatasetParameter.DoesNotExist:
                dfp = DatasetParameter(parameterset=ps, name=p)

            # TODO: handle bad type
            if p.isNumeric():
                dfp.numerical_value = metadata[p.name][0]
                logger.debug("numeric")
            else:
                dfp.string_value = metadata[p.name][0]
            logger.debug("dfp=%(dfp)s" % locals())
            dfp.save()
Exemplo n.º 2
0
def _save_metadata(instance, schema, metadataset):
    """ Creates schema from the metadataset and associates it 
        with the instance.  If metadata value is empty, then 
        existing value is unchanged.  
    """
    parameters = _get_parameters(schema, metadataset)
    logger.debug("parameters=%s" % parameters)
    if not parameters:
        return None
    try:
        ps = DatasetParameterSet.objects.get(schema=schema, dataset=instance)
    except DatasetParameterSet.DoesNotExist:
        ps = DatasetParameterSet(schema=schema, dataset=instance)
        ps.save()
    logger.debug("ps=%s\n" % ps)
    logger.debug("metadata2=%s\n" % metadataset)
    for p in parameters:
        logger.debug("p=%s\n" % p)
        if p.name in metadataset:
            logger.debug("found p =%s %s\n" % (p.name, p.units))

            if p.isNumeric():
                val = metadataset[p.name][0]
                if val:

                    dfp = DatasetParameter.objects.filter(parameterset=ps,
                                                          name=p)
                    if not dfp:
                        dfp = DatasetParameter(parameterset=ps, name=p)
                        dfp.numerical_value = val
                        logger.debug("new numeric")
                        dfp.save()
                    else:
                        for dp in dfp:
                            dp.numerical_value = val
                            dp.save()
                        logger.debug("numeric")
            else:
                val = metadataset[p.name][0]
                logger.debug("val=%s" % val)
                if val:
                    dfp = DatasetParameter.objects.filter(parameterset=ps,
                                                          name=p)
                    if not dfp:
                        dfp = DatasetParameter(parameterset=ps, name=p)
                        dfp.string_value = metadataset[p.name][0]
                        dfp.save()
                        logger.debug("new string")
                    else:
                        for dp in dfp:
                            dp.string_value = metadataset[p.name][0]
                            dp.save()
                            logger.debug("string")
                        logger.debug("done")
Exemplo n.º 3
0
def _save_metadata(instance,schema,metadataset):
    """ Creates schema from the metadataset and associates it 
        with the instance.  If metadata value is empty, then 
        existing value is unchanged.  
    """
    parameters = _get_parameters(schema, metadataset)
    logger.debug("parameters=%s" % parameters)
    if not parameters:
        return None
    try:
        ps = DatasetParameterSet.objects.get(schema=schema,
                                                dataset=instance)
    except DatasetParameterSet.DoesNotExist:
        ps = DatasetParameterSet(schema=schema,dataset=instance)
        ps.save()
    logger.debug("ps=%s\n" % ps)
    logger.debug("metadata2=%s\n" % metadataset)
    for p in parameters:
        logger.debug("p=%s\n" % p)
        if p.name in metadataset:
            logger.debug("found p =%s %s\n" % (p.name,p.units))
            
            if p.isNumeric():
                val = metadataset[p.name][0]
                if val:
                        
                    dfp = DatasetParameter.objects.filter(parameterset=ps,
                                                           name=p)
                    if not dfp:
                        dfp = DatasetParameter(parameterset=ps,
                                               name=p)                    
                        dfp.numerical_value = val
                        logger.debug("new numeric")
                        dfp.save()    
                    else:
                        for dp in dfp:
                            dp.numerical_value = val
                            dp.save()    
                        logger.debug("numeric")
            else:
                val = metadataset[p.name][0]
                logger.debug("val=%s" % val)
                if val:
                    dfp = DatasetParameter.objects.filter(parameterset=ps,
                                                           name=p)
                    if not dfp:
                        dfp = DatasetParameter(parameterset=ps,
                                               name=p)
                        dfp.string_value = metadataset[p.name][0]
                        dfp.save()
                        logger.debug("new string")
                    else:
                        for dp in dfp:
                            dp.string_value = metadataset[p.name][0]
                            dp.save()
                            logger.debug("string")
                        logger.debug("done")
def get_image_to_show(dataset):

    try:
        sch = Schema.objects.get(namespace__exact=HRMC_DATASET_SCHEMA)
    except Schema.DoesNotExist:
        logger.debug("no hrmc schema")
        return None
    except MultipleObjectsReturned:
        logger.error("multiple hrmc schemas returned")
        return None
    #FIXME: possible that more than once dataset can appear, so pick only one.
    try:
        ps = DatasetParameterSet.objects.get(schema=sch, dataset=dataset)
    except DatasetParameterSet.DoesNotExist:
        logger.debug("datset parameterset not found")
        return None
    except MultipleObjectsReturned:
        logger.error("multiple dataset paramter sets returned")
        # NB: If admin tool added additional param set,
        # we know that all data will be the same for this schema
        # so can safely delete any extras we find.
        pslist = [x.id for x in DatasetParameterSet.objects.filter(schema=sch,
            dataset=dataset)]
        logger.debug("pslist=%s" % pslist)
        DatasetParameterSet.objects.filter(id__in=pslist[1:]).delete()
        ps = DatasetParameterSet.objects.get(id=pslist[0])


    logger.debug("found ps=%s" % ps)
    for param in DatasetParameter.objects.filter(parameterset=ps):
        logger.debug("param=%s" % param)
        logger.debug("param.name=%s" % param.name)

        if "plot" in param.name.name:
            logger.debug("found existing image")
            return param

    logger.debug("building plots")
    display_image = None
    grfinal_file = None
    grexp_file = None
    for df in Dataset_File.objects.filter(dataset=dataset):
        logger.debug("testing %s" % df.filename)
        if "grexp.dat" in df.filename:
            grexp_file = df
        if df.filename.startswith("grfinal"):
            grfinal_file = df
    if grexp_file and grfinal_file and is_matplotlib_imported:
        logger.debug("found both")
        fp = grexp_file.get_absolute_filepath()
        grexp_buff = []
        with open(fp) as f:
            for d in f.read():
                grexp_buff.append(d)

        fp = grfinal_file.get_absolute_filepath()
        grfinal_buff = []
        with open(fp) as f:
            for d in f.read():
                grfinal_buff.append(d)

        mat = re.compile("grfinal(\d+)\.dat").match(grfinal_file.filename)
        if mat:
            grlabel = "Calculation %s" % mat.group(1)
        else:
            grlabel = grfinal_file.filename

        xs = []
        ys = []
        for l in ''.join(grfinal_buff).split("\n"):
            #logger.debug("l=%s" % l)
            if l:
                x, y = l.split()
                xs.append(float(x))
                ys.append(float(y))
        matplotlib.pyplot.plot(xs, ys, color="blue", markeredgecolor = 'blue', marker="D", label=str(grlabel))

        xs = []
        ys = []
        for l in ''.join(grexp_buff).split("\n"):
            #logger.debug("l=%s" % l)
            if l:
                x, y = l.split()
                xs.append(float(x))
                ys.append(float(y))
        matplotlib.pyplot.plot(xs, ys, color="red", markeredgecolor = 'red', marker="o", label="Experiment")

        import tempfile
        pfile = tempfile.mktemp()
        logger.debug("pfile=%s" % pfile)

        pyplot.xlabel("r (Angstroms)")
        pyplot.ylabel("g(r)")
        pyplot.grid(True)
        #legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
        legend()
        pyplot.xlim(xmin=0)

        fig = matplotlib.pyplot.gcf()
        fig.set_size_inches(15.5, 13.5)
        matplotlib.pyplot.savefig("%s.png" % pfile, dpi=100)

        with open("%s.png" % pfile) as pf:
            read = pf.read()
            encoded = base64.b64encode(read)
            matplotlib.pyplot.close()
        try:
            pn = ParameterName.objects.get(schema=sch, name="plot")
        except DatasetParameterSet.DoesNotExist:
            logger.error("schema is missing plot parameter")
            return None
        except MultipleObjectsReturned:
            logger.error("schema is multiple plot parameters")
            return None

        logger.debug("ready to save")

        dfp = DatasetParameter(parameterset=ps,
                                        name=pn)
        dfp.string_value = encoded
        dfp.save()
        display_image = dfp
    else:
        logger.debug("one or more files unavailable")
        return None
    logger.debug("made display_image  %s" % display_image)
    return display_image
Exemplo n.º 5
0
    def test_parameter(self):
        exp = Experiment(
            title='test exp1',
            institution_name='Australian Synchrotron',
            approved=True,
            created_by=self.user,
            public_access=Experiment.PUBLIC_ACCESS_NONE,
        )
        exp.save()

        dataset = Dataset(description="dataset description")
        dataset.save()
        dataset.experiments.add(exp)
        dataset.save()

        df_file = DataFile(dataset=dataset,
                           filename='file.txt',
                           size=42,
                           md5sum='bogus')
        df_file.save()

        df_schema = Schema(namespace='http://www.cern.ch/felzmann/schema1.xml',
                           type=Schema.DATAFILE)
        df_schema.save()

        ds_schema = Schema(namespace='http://www.cern.ch/felzmann/schema2.xml',
                           type=Schema.DATASET)
        ds_schema.save()

        exp_schema = Schema(
            namespace='http://www.cern.ch/felzmann/schema3.xml',
            type=Schema.EXPERIMENT)
        exp_schema.save()

        df_parname = ParameterName(schema=df_schema,
                                   name='name',
                                   full_name='full_name',
                                   units='image/jpg',
                                   data_type=ParameterName.FILENAME)
        df_parname.save()

        ds_parname = ParameterName(schema=ds_schema,
                                   name='name',
                                   full_name='full_name',
                                   units='image/jpg',
                                   data_type=ParameterName.FILENAME)
        ds_parname.save()

        exp_parname = ParameterName(schema=exp_schema,
                                    name='name',
                                    full_name='full_name',
                                    units='image/jpg',
                                    data_type=ParameterName.FILENAME)
        exp_parname.save()

        df_parset = DatafileParameterSet(schema=df_schema, datafile=df_file)
        df_parset.save()

        ds_parset = DatasetParameterSet(schema=ds_schema, dataset=dataset)
        ds_parset.save()

        exp_parset = ExperimentParameterSet(schema=exp_schema, experiment=exp)
        exp_parset.save()

        with self.settings(METADATA_STORE_PATH=os.path.dirname(__file__)):
            filename = 'test.jpg'
            df_parameter = DatafileParameter(name=df_parname,
                                             parameterset=df_parset,
                                             string_value=filename)
            df_parameter.save()

            ds_parameter = DatasetParameter(name=ds_parname,
                                            parameterset=ds_parset,
                                            string_value=filename)
            ds_parameter.save()

            exp_parameter = ExperimentParameter(name=exp_parname,
                                                parameterset=exp_parset,
                                                string_value=filename)
            exp_parameter.save()

            self.assertEqual(
                "<a href='/display/DatafileImage/load/%i/' target='_blank'><img style='width: 300px;' src='/display/DatafileImage/load/%i/' /></a>"
                %  # noqa
                (df_parameter.id, df_parameter.id),
                df_parameter.get())

            self.assertEqual(
                "<a href='/display/DatasetImage/load/%i/' target='_blank'><img style='width: 300px;' src='/display/DatasetImage/load/%i/' /></a>"
                %  # noqa
                (ds_parameter.id, ds_parameter.id),
                ds_parameter.get())

            self.assertEqual(
                "<a href='/display/ExperimentImage/load/%i/' target='_blank'><img style='width: 300px;' src='/display/ExperimentImage/load/%i/' /></a>"
                %  # noqa
                (exp_parameter.id, exp_parameter.id),
                exp_parameter.get())
Exemplo n.º 6
0
def get_image_to_show(dataset):

    try:
        sch = Schema.objects.get(namespace__exact=HRMC_DATASET_SCHEMA)
    except Schema.DoesNotExist:
        logger.debug("no hrmc schema")
        return None
    except MultipleObjectsReturned:
        logger.error("multiple hrmc schemas returned")
        return None
    #FIXME: possible that more than once dataset can appear, so pick only one.
    try:
        ps = DatasetParameterSet.objects.get(schema=sch, dataset=dataset)
    except DatasetParameterSet.DoesNotExist:
        logger.debug("datset parameterset not found")
        return None
    except MultipleObjectsReturned:
        logger.error("multiple dataset paramter sets returned")
        # NB: If admin tool added additional param set,
        # we know that all data will be the same for this schema
        # so can safely delete any extras we find.
        pslist = [
            x.id for x in DatasetParameterSet.objects.filter(schema=sch,
                                                             dataset=dataset)
        ]
        logger.debug("pslist=%s" % pslist)
        DatasetParameterSet.objects.filter(id__in=pslist[1:]).delete()
        ps = DatasetParameterSet.objects.get(id=pslist[0])

    logger.debug("found ps=%s" % ps)
    for param in DatasetParameter.objects.filter(parameterset=ps):
        logger.debug("param=%s" % param)
        logger.debug("param.name=%s" % param.name)

        if "plot" in param.name.name:
            logger.debug("found existing image")
            return param

    logger.debug("building plots")
    display_image = None
    grfinal_file = None
    grexp_file = None
    for df in Dataset_File.objects.filter(dataset=dataset):
        logger.debug("testing %s" % df.filename)
        if "grexp.dat" in df.filename:
            grexp_file = df
        if df.filename.startswith("grfinal"):
            grfinal_file = df
    if grexp_file and grfinal_file and is_matplotlib_imported:
        logger.debug("found both")
        fp = grexp_file.get_absolute_filepath()
        grexp_buff = []
        with open(fp) as f:
            for d in f.read():
                grexp_buff.append(d)

        fp = grfinal_file.get_absolute_filepath()
        grfinal_buff = []
        with open(fp) as f:
            for d in f.read():
                grfinal_buff.append(d)

        mat = re.compile("grfinal(\d+)\.dat").match(grfinal_file.filename)
        if mat:
            grlabel = "Calculation %s" % mat.group(1)
        else:
            grlabel = grfinal_file.filename

        xs = []
        ys = []
        for l in ''.join(grfinal_buff).split("\n"):
            #logger.debug("l=%s" % l)
            if l:
                x, y = l.split()
                xs.append(float(x))
                ys.append(float(y))
        matplotlib.pyplot.plot(xs,
                               ys,
                               color="blue",
                               markeredgecolor='blue',
                               marker="D",
                               label=str(grlabel))

        xs = []
        ys = []
        for l in ''.join(grexp_buff).split("\n"):
            #logger.debug("l=%s" % l)
            if l:
                x, y = l.split()
                xs.append(float(x))
                ys.append(float(y))
        matplotlib.pyplot.plot(xs,
                               ys,
                               color="red",
                               markeredgecolor='red',
                               marker="o",
                               label="Experiment")

        import tempfile
        pfile = tempfile.mktemp()
        logger.debug("pfile=%s" % pfile)

        pyplot.xlabel("r (Angstroms)")
        pyplot.ylabel("g(r)")
        pyplot.grid(True)
        #legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)
        legend()
        pyplot.xlim(xmin=0)

        fig = matplotlib.pyplot.gcf()
        fig.set_size_inches(15.5, 13.5)
        matplotlib.pyplot.savefig("%s.png" % pfile, dpi=100)

        with open("%s.png" % pfile) as pf:
            read = pf.read()
            encoded = base64.b64encode(read)
            matplotlib.pyplot.close()
        try:
            pn = ParameterName.objects.get(schema=sch, name="plot")
        except DatasetParameterSet.DoesNotExist:
            logger.error("schema is missing plot parameter")
            return None
        except MultipleObjectsReturned:
            logger.error("schema is multiple plot parameters")
            return None

        logger.debug("ready to save")

        dfp = DatasetParameter(parameterset=ps, name=pn)
        dfp.string_value = encoded
        dfp.save()
        display_image = dfp
    else:
        logger.debug("one or more files unavailable")
        return None
    logger.debug("made display_image  %s" % display_image)
    return display_image