def data_last_updated(self, update=False, view=None, pval=None):
pval = resolve_pval(self.parametisation, view=view, pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
latest = None
Statistic = apps.get_app_config("widget_def").get_model("Statistic")
for s in Statistic.objects.filter(tile__widget=self):
slu = s.data_last_updated(update, view, pval)
if latest is None:
latest = slu
elif slu and slu > latest:
latest = slu
self._lud_cache[pval.id] = latest
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
lud_statdata = StatisticData.objects.filter(statistic__tile__widget=self).aggregate(lud=models.Max('last_updated'))['lud']
lud_listdata = StatisticListItem.objects.filter(statistic__tile__widget=self).aggregate(lud=models.Max('last_updated'))['lud']
lud_graphdata = GraphData.objects.filter(graph__tile__widget=self).aggregate(lud=models.Max("last_updated"))["lud"]
luds_mapdata = [None]
for t in self.tiledefinition_set.all():
for ds in t.geo_datasets.all():
luds_mapdata.append(ds.data_last_updated(update))
self._lud_cache = max_with_nulls(lud_statdata, lud_listdata, lud_graphdata, *luds_mapdata)
return self._lud_cache
def data_last_updated(self, update=False, view=None, pval=None):
pval=resolve_pval(self.tile.widget.parametisation,view=view,pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
if self.is_data_list():
self._lud_cache[pval.id] = StatisticListItem.objects.filter(statistic=self,param_value=pval).aggregate(lud=models.Max('last_updated'))['lud']
else:
try:
self._lud_cache[pval.id] = StatisticData.objects.get(statistic=self,param_value=pval).last_updated
except StatisticData.DoesNotExist:
self._lud_cache[pval.id] = None
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
if self.is_data_list():
self._lud_cache = StatisticListItem.objects.filter(statistic=self).aggregate(lud=models.Max('last_updated'))['lud']
else:
try:
self._lud_cache = StatisticData.objects.get(statistic=self).last_updated
except StatisticData.DoesNotExist:
self._lud_cache = None
return self._lud_cache
def data_last_updated(self, update=False, view=None, pval=None):
"""
Return the date the data for this widget was last updated.
update: If true, the objects last-updated cache is flushed and recalculated.
view, pval: One of these must be supplied for a parametised widget (unless a non-None wd has been passed in)
"""
pval = resolve_pval(self.parametisation, view=view, pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
latest = None
Statistic = apps.get_app_config("widget_def").get_model("Statistic")
for s in Statistic.objects.filter(tile__widget=self):
slu = s.data_last_updated(update, view, pval)
if latest is None:
latest = slu
elif slu and slu > latest:
latest = slu
self._lud_cache[pval.id] = latest
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
lud_statdata = StatisticData.objects.filter(statistic__tile__widget=self).aggregate(lud=models.Max('last_updated'))['lud']
lud_listdata = StatisticListItem.objects.filter(statistic__tile__widget=self).aggregate(lud=models.Max('last_updated'))['lud']
lud_graphdata = GraphData.objects.filter(graph__tile__widget=self).aggregate(lud=models.Max("last_updated"))["lud"]
luds_mapdata = [None]
for t in self.tiledefinition_set.all():
for ds in t.geo_datasets.all():
luds_mapdata.append(ds.data_last_updated(update))
self._lud_cache = max_with_nulls(lud_statdata, lud_listdata, lud_graphdata, *luds_mapdata)
return self._lud_cache
def data_last_updated(self, update=False, view=None, pval=None):
"""
Return when the data for this statistic was last updated (with parametisation if necessary).
update: If true and the last_updated value is cached, then the cached value is dropped and recalculated.
"""
pval=resolve_pval(self.tile.widget.parametisation,view=view,pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
if self.is_data_list():
self._lud_cache[pval.id] = StatisticListItem.objects.filter(statistic=self,param_value=pval).aggregate(lud=models.Max('last_updated'))['lud']
else:
try:
self._lud_cache[pval.id] = StatisticData.objects.get(statistic=self,param_value=pval).last_updated
except StatisticData.DoesNotExist:
self._lud_cache[pval.id] = None
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
if self.is_data_list():
self._lud_cache = StatisticListItem.objects.filter(statistic=self).aggregate(lud=models.Max('last_updated'))['lud']
else:
try:
self._lud_cache = StatisticData.objects.get(statistic=self).last_updated
except StatisticData.DoesNotExist:
self._lud_cache = None
return self._lud_cache
def api_get_graph_data(widget, view=None, pval=None, verbose=False):
pval = resolve_pval(widget.parametisation, view=view, pval=pval)
graph_json = {}
for graph in GraphDefinition.objects.filter(tile__widget=widget):
graph_json[graph.tile.url] = api_get_single_graph_data(graph,
view,
pval=pval,
verbose=verbose)
return graph_json
def csv(self, writer, view=None):
"""Write out a CSV for the dataset to the provided writer (e.g. an HttpResponse object)"""
pval = resolve_pval(self.widget.parametisation, view=view)
writer.write(self.csv_header(view))
if pval:
for rec in self.rawdatarecord_set.filter(param_value=pval):
writer.write(rec.csv)
else:
for rec in self.rawdatarecord_set.all():
writer.write(rec.csv)
def json(self, pval=None, view=None):
"""Return a json-serialisable dump of this dataset."""
result = []
pval = resolve_pval(self.widget.parametisation, view=view, pval=pval)
if pval:
for rec in self.rawdatarecord_set.all(param_value=pval):
yield rec.json()
else:
for rec in self.rawdatarecord_set.all():
yield rec.json()
def json(self, pval=None, view=None):
"""Return a json-serialisable dump of this dataset."""
result = []
pval = resolve_pval(self.widget.parametisation, view=view, pval=pval)
if pval:
for rec in self.rawdatarecord_set.all(param_value=pval):
yield rec.json()
else:
for rec in self.rawdatarecord_set.all():
yield rec.json()
def csv(self, writer, view=None):
"""Write out a CSV for the dataset to the provided writer (e.g. an HttpResponse object)"""
pval = resolve_pval(self.widget.parametisation, view=view)
writer.write(self.csv_header(view))
if pval:
for rec in self.rawdatarecord_set.all(param_value=pval):
writer.write(rec.csv)
else:
for rec in self.rawdatarecord_set.all():
writer.write(rec.csv)
def api_get_raw_data(widget, request, rds_url, view=None, pval=None):
try:
rds = RawDataSet.objects.get(widget=widget, url=rds_url)
except RawDataSet.DoesNotExist:
return HttpResponseNotFound("This Raw Data Set does not exist")
pval = resolve_pval(rds.widget.parametisation, view=view, pval=pval)
if request.GET.get("format", "csv") != "csv":
return rds.json(pval=pval)
response = HttpResponse()
response['content-type'] = 'application/csv'
response['content-disposition'] = 'attachment; filename=%s' % rds.filename
rds.csv(response, view=view)
return response
def api_get_raw_data(widget, request, rds_url, view=None, pval=None):
try:
rds = RawDataSet.objects.get(widget=widget, url=rds_url)
except RawDataSet.DoesNotExist:
return HttpResponseNotFound("This Raw Data Set does not exist")
pval = resolve_pval(rds.widget.parametisation, view=view, pval=pval)
if request.GET.get("format", "csv") != "csv":
return rds.json(pval=pval)
response = HttpResponse()
response['content-type'] = 'application/csv'
response['content-disposition'] = 'attachment; filename=%s' % rds.filename
rds.csv(response, view=view)
return response
def data_last_updated(self, update=False, view=None, pval=None):
pval = resolve_pval(self.widget().parametisation, view=view, pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
self._lud_cache[pval.id] = GraphData.objects.filter(graph=self,param_value=pval).aggregate(lud=models.Max("last_updated"))["lud"]
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
self._lud_cache = GraphData.objects.filter(graph=self,param_value__isnull=True).aggregate(lud=models.Max("last_updated"))["lud"]
return self._lud_cache
def widget_data(self, view=None, pval=None):
try:
pval = resolve_pval(self.parametisation, view=view, pval=pval)
except ParametisationException:
pval = None
if pval:
try:
return WidgetData.objects.get(widget=self, param_value=pval)
except WidgetData.DoesNotExist:
pass
try:
return WidgetData.objects.get(widget=self, param_value__isnull=True)
except WidgetData.DoesNotExist:
return None
def get_data(self, view=None, pval=None):
pval=resolve_pval(self.tile.widget.parametisation,view=view,pval=pval)
if self.is_data_list():
data = StatisticListItem.objects.filter(statistic=self)
if pval:
return data.filter(param_value=pval)
else:
return data.filter(param_value__isnull=True)
else:
try:
if pval:
return StatisticData.objects.get(statistic=self, param_value=pval)
else:
return StatisticData.objects.get(statistic=self, param_value__isnull=True)
except StatisticData.DoesNotExist:
return None
def data_last_updated(self, update=False, view=None, pval=None):
"""
Return when the data for this graph was last updated (with parametisation if necessary).
update: If true and the last_updated value is cached, then the cached value is dropped and recalculated.
"""
pval = resolve_pval(self.widget().parametisation, view=view, pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
self._lud_cache[pval.id] = GraphData.objects.filter(graph=self,param_value=pval).aggregate(lud=models.Max("last_updated"))["lud"]
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
self._lud_cache = GraphData.objects.filter(graph=self,param_value__isnull=True).aggregate(lud=models.Max("last_updated"))["lud"]
return self._lud_cache
def data_last_updated(self, update=False, view=None, pval=None):
"""
Return when the data for this graph was last updated (with parametisation if necessary).
update: If true and the last_updated value is cached, then the cached value is dropped and recalculated.
"""
pval = resolve_pval(self.widget().parametisation, view=view, pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
self._lud_cache[pval.id] = GraphData.objects.filter(graph=self,param_value=pval).aggregate(lud=models.Max("last_updated"))["lud"]
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
self._lud_cache = GraphData.objects.filter(graph=self,param_value__isnull=True).aggregate(lud=models.Max("last_updated"))["lud"]
return self._lud_cache
def widget_data(self, view=None, pval=None):
"""
Return the :model:`widget_data.WidgetData` object for this widget.
view, pval: One of these must be supplied for a parametised widget.
"""
try:
pval = resolve_pval(self.parametisation, view=view, pval=pval)
except ParametisationException:
pval = None
if pval:
try:
return WidgetData.objects.get(widget=self, param_value=pval)
except WidgetData.DoesNotExist:
pass
try:
return WidgetData.objects.get(widget=self, param_value=pval)
except WidgetData.DoesNotExist:
return None
def data_last_updated(self, update=False, view=None, pval=None):
"""
Return the date the data for this widget was last updated.
update: If true, the objects last-updated cache is flushed and recalculated.
view, pval: One of these must be supplied for a parametised widget (unless a non-None wd has been passed in)
"""
pval = resolve_pval(self.parametisation, view=view, pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
latest = None
Statistic = apps.get_app_config("widget_def").get_model(
"Statistic")
for s in Statistic.objects.filter(tile__widget=self):
slu = s.data_last_updated(update, view, pval)
if latest is None:
latest = slu
elif slu and slu > latest:
latest = slu
self._lud_cache[pval.id] = latest
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
lud_statdata = StatisticData.objects.filter(
statistic__tile__widget=self).aggregate(
lud=models.Max('last_updated'))['lud']
lud_listdata = StatisticListItem.objects.filter(
statistic__tile__widget=self).aggregate(
lud=models.Max('last_updated'))['lud']
lud_graphdata = GraphData.objects.filter(
graph__tile__widget=self).aggregate(
lud=models.Max("last_updated"))["lud"]
luds_mapdata = [None]
for t in self.tiles.all():
for ds in t.geo_datasets.all():
luds_mapdata.append(ds.data_last_updated(update))
self._lud_cache = max_with_nulls(lud_statdata, lud_listdata,
lud_graphdata, *luds_mapdata)
return self._lud_cache
def widget_data(self, view=None, pval=None):
"""
Return the :model:`widget_data.WidgetData` object for this widget.
view, pval: One of these must be supplied for a parametised widget.
"""
try:
pval = resolve_pval(self.parametisation, view=view, pval=pval)
except ParametisationException:
pval = None
if pval:
try:
return WidgetData.objects.get(widget=self, param_value=pval)
except WidgetData.DoesNotExist:
pass
try:
return WidgetData.objects.get(widget=self, param_value=pval)
except WidgetData.DoesNotExist:
return None
def get_data(self, view=None, pval=None):
"""
Return the data for this widget (with parametisation if necessary).
Data returned as a single :model:`widget_data.StatisticData` object or a :model:`widget_data.StatisticListItem` query result if is_data_list() returns True.
"""
pval=resolve_pval(self.tile.widget.parametisation,view=view,pval=pval)
if self.is_data_list():
data = StatisticListItem.objects.filter(statistic=self)
if pval:
return data.filter(param_value=pval)
else:
return data.filter(param_value__isnull=True)
else:
try:
if pval:
return StatisticData.objects.get(statistic=self, param_value=pval)
else:
return StatisticData.objects.get(statistic=self, param_value__isnull=True)
except StatisticData.DoesNotExist:
return None
def data_last_updated(self, update=False, view=None, pval=None):
"""
Return when the data for this statistic was last updated (with parametisation if necessary).
update: If true and the last_updated value is cached, then the cached value is dropped and recalculated.
"""
pval = resolve_pval(self.widget().parametisation, view=view, pval=pval)
if pval:
if self._lud_cache and self._lud_cache.get(pval.id) and not update:
return self._lud_cache[pval.id]
if not self._lud_cache:
self._lud_cache = {}
if self.is_data_list():
self._lud_cache[pval.id] = StatisticListItem.objects.filter(
statistic=self, param_value=pval).aggregate(
lud=models.Max('last_updated'))['lud']
else:
try:
self._lud_cache[pval.id] = StatisticData.objects.get(
statistic=self, param_value=pval).last_updated
except StatisticData.DoesNotExist:
self._lud_cache[pval.id] = None
return self._lud_cache[pval.id]
else:
if self._lud_cache and not update:
return self._lud_cache
if self.is_data_list():
self._lud_cache = StatisticListItem.objects.filter(
statistic=self).aggregate(
lud=models.Max('last_updated'))['lud']
else:
try:
self._lud_cache = StatisticData.objects.get(
statistic=self).last_updated
except StatisticData.DoesNotExist:
self._lud_cache = None
return self._lud_cache
return state
def get_data(self, view=None, pval=None):
"""
Return the data for this widget (with parametisation if necessary).
Data returned as a single :model:`widget_data.StatisticData` object or a :model:`widget_data.StatisticListItem` query result if is_data_list() returns True.
"""
pval = resolve_pval(self.widget().parametisation, view=view, pval=pval)
if self.is_data_list():
data = StatisticListItem.objects.filter(statistic=self)
if pval:
return data.filter(param_value=pval)
else:
return data.filter(param_value__isnull=True)
else:
try:
if pval:
return StatisticData.objects.get(statistic=self,
param_value=pval)
else:
return StatisticData.objects.get(statistic=self,
param_value__isnull=True)
except StatisticData.DoesNotExist:
return None
def api_get_single_graph_data(graph, view, pval=None, verbose=False):
pval = resolve_pval(graph.widget().parametisation, view=view, pval=pval)
graph_json = {"data": {}}
if verbose:
graph_json["data"] = []
else:
if graph.use_clusters():
for cluster in graph.clusters(pval):
graph_json["data"][cluster.url] = {}
else:
for dataset in graph.datasets.all():
graph_json["data"][dataset.url] = []
numeric_min = None
numeric_max = None
numeric2_min = None
numeric2_max = None
horiz_min = None
horiz_max = None
for gd in graph.get_data(pval=pval):
if graph.use_numeric_axes():
if graph.use_secondary_numeric_axis and gd.dataset.use_secondary_numeric_axis:
(numeric2_min,
numeric2_max) = update_graph_maxmin(gd, numeric2_min,
numeric2_max)
else:
(numeric_min,
numeric_max) = update_graph_maxmin(gd, numeric_min,
numeric_max)
if not graph.use_clusters():
(horiz_min, horiz_max) = update_maxmin(gd.horiz_value(), horiz_min,
horiz_max)
if verbose:
if graph.use_numeric_axes():
if gd.dataset.use_secondary_numeric_axis:
data_label = graph.secondary_numeric_axis_label
else:
data_label = graph.numeric_axis_label
data_label = parametise_label(graph.widget(), view, data_label)
else:
data_label = "value"
graph_datum = {
parametise_label(graph.widget(), view, graph.dataset_label):
parametise_label(
graph.widget(), view,
get_graph_subset_displayname(gd.dataset, pval)),
data_label:
gd.value
}
if graph.use_clusters():
graph_datum[parametise_label(
graph.widget(), view,
graph.cluster_label)] = parametise_label(
graph.widget(), view,
gd.get_cluster().label)
else:
graph_datum[parametise_label(
graph.widget(), view,
graph.horiz_axis_label)] = gd.horiz_json_value()
if gd.dataset.use_error_bars:
graph_datum[data_label + "_min"] = gd.err_valmin
graph_datum[data_label + "_max"] = gd.err_valmax
graph_json["data"].append(graph_datum)
else:
if gd.dataset.use_error_bars:
json_val = {
"value": gd.value,
"min": gd.err_valmin,
"max": gd.err_valmax,
}
else:
json_val = gd.value
if graph.use_clusters():
graph_json["data"][gd.get_cluster().url][
gd.dataset.url] = json_val
else:
if gd.dataset.use_error_bars:
json_val["horizontal_value"] = gd.horiz_json_value()
else:
json_val = (gd.horiz_json_value(), json_val)
graph_json["data"][gd.dataset.url].append(json_val)
if graph.use_numeric_axes():
numeric_min, numeric_max = apply_vertical_axis_buffer(
graph, numeric_min, numeric_max)
graph_json["%s_scale" % graph.numeric_axis_name()] = {
"min": numeric_min,
"max": numeric_max
}
if graph.use_secondary_numeric_axis:
numeric2_min, numeric2_max = apply_vertical_axis_buffer(
graph, numeric2_min, numeric2_max)
graph_json["%s_2_scale" % graph.numeric_axis_name()] = {
"min": numeric2_min,
"max": numeric2_max
}
if not graph.use_clusters():
graph_json["horizontal_axis_scale"] = {
"min": graph.jsonise_horiz_value(horiz_min),
"max": graph.jsonise_horiz_value(horiz_max)
}
if graph.use_clusters():
if graph.is_histogram():
clusters_attrib = "clusters"
else:
clusters_attrib = "pies"
graph_json[clusters_attrib] = [
c.__getstate__(view=view) for c in graph.clusters(pval)
]
overrides = get_graph_overrides(graph.datasets, GraphDatasetData,
"dataset", pval)
datasets = {}
for ds in graph.datasets.all():
datasets[ds.url] = ds.__getstate__(view=view)
del datasets[ds.url]["dynamic_name_display"]
if ds.url in overrides:
datasets[ds.url]["name"] = overrides[ds.url]
if graph.is_histogram():
datasets_attrib = "datasets"
else:
datasets_attrib = "sectors"
graph_json[datasets_attrib] = datasets
if overrides:
graph_json["dataset_name_overrides"] = overrides
return graph_json
def api_get_single_graph_data(graph, view, pval=None, verbose=False):
pval = resolve_pval(graph.widget().parametisation, view=view, pval=pval)
graph_json = { "data": {} }
if verbose:
graph_json["data"] = []
else:
if graph.use_clusters():
for cluster in graph.clusters(pval):
graph_json["data"][cluster.url] = {}
else:
for dataset in graph.graphdataset_set.all():
graph_json["data"][dataset.url] = []
numeric_min = None
numeric_max = None
numeric2_min = None
numeric2_max = None
horiz_min = None
horiz_max = None
for gd in graph.get_data(pval=pval):
if graph.use_numeric_axes():
if graph.use_secondary_numeric_axis and gd.dataset.use_secondary_numeric_axis:
(numeric2_min, numeric2_max)=update_maxmin(gd.value,
numeric2_min, numeric2_max)
else:
(numeric_min, numeric_max)=update_maxmin(gd.value,
numeric_min, numeric_max)
if not graph.use_clusters():
(horiz_min, horiz_max) = update_maxmin(gd.horiz_value(),
horiz_min, horiz_max)
if verbose:
if graph.use_numeric_axes():
if gd.dataset.use_secondary_numeric_axis:
data_label = graph.secondary_numeric_axis_label
else:
data_label = graph.numeric_axis_label
data_label = parametise_label(graph.widget(), view, data_label)
else:
data_label = "value"
graph_datum = {
parametise_label(graph.widget(), view, graph.dataset_label): parametise_label(graph.widget(), view, get_graph_subset_displayname(gd.dataset,pval)),
data_label: gd.value
}
if graph.use_clusters():
graph_datum[parametise_label(graph.widget(), view, graph.cluster_label)] = parametise_label(graph.widget(), view, gd.get_cluster().label)
else:
graph_datum[parametise_label(graph.widget(), view, graph.horiz_axis_label)] = gd.horiz_json_value()
if gd.dataset.use_error_bars:
graph_datum[data_label + "_min"] = gd.err_valmin
graph_datum[data_label + "_max"] = gd.err_valmax
graph_json["data"].append(graph_datum)
else:
if gd.dataset.use_error_bars:
json_val = {
"value": gd.value,
"min": gd.err_valmin,
"max": gd.err_valmax,
}
else:
json_val = gd.value
if graph.use_clusters():
graph_json["data"][gd.get_cluster().url][gd.dataset.url] = json_val
else:
if gd.dataset.use_error_bars:
json_val["horizontal_value"] = gd.horiz_json_value()
else:
json_val = ( gd.horiz_json_value(), json_val )
graph_json["data"][gd.dataset.url].append(json_val)
if graph.use_numeric_axes():
graph_json["%s_scale" % graph.numeric_axis_name()] = {
"min": numeric_min,
"max": numeric_max
}
if graph.use_secondary_numeric_axis:
graph_json["%s_2_scale" % graph.numeric_axis_name()] = {
"min": numeric2_min,
"max": numeric2_max
}
if not graph.use_clusters():
graph_json["horizontal_axis_scale"] = {
"min": graph.jsonise_horiz_value(horiz_min),
"max": graph.jsonise_horiz_value(horiz_max)
}
if graph.use_clusters() and graph.dynamic_clusters:
if graph.is_histogram():
graph_json["clusters"] = [ c.__getstate__(view) for c in graph.clusters(pval) ]
else:
graph_json["pies"] = [ c.__getstate__(view) for c in graph.clusters(pval) ]
overrides = get_graph_overrides(graph.graphdataset_set, GraphDatasetData, "dataset", pval)
if overrides:
graph_json["dataset_name_overrides"] = overrides
return graph_json
def api_get_graph_data(widget, view=None, pval=None, verbose=False):
pval = resolve_pval(widget.parametisation, view=view, pval=pval)
graph_json = {}
for graph in GraphDefinition.objects.filter(tile__widget=widget):
graph_json[graph.tile.url] = api_get_single_graph_data(graph, view, pval=pval, verbose=verbose)
return graph_json
def get_data(self, view=None, pval=None):
"""Get the data for this graph (parametised if necessary)"""
pval = resolve_pval(self.widget().parametisation, view=view, pval=pval)
return GraphData.objects.filter(graph=self,param_value=pval).natural_order(self)
def api_get_single_graph_data(graph, view, pval=None, verbose=False):
pval = resolve_pval(graph.widget().parametisation, view=view, pval=pval)
graph_json = { "data": {} }
if verbose:
graph_json["data"] = []
else:
if graph.use_clusters():
for cluster in graph.graphcluster_set.all():
graph_json["data"][cluster.url] = {}
else:
for dataset in graph.graphdataset_set.all():
graph_json["data"][dataset.url] = []
numeric_min = None
numeric_max = None
numeric2_min = None
numeric2_max = None
horiz_min = None
horiz_max = None
for gd in graph.get_data(pval=pval):
if graph.use_numeric_axes():
if graph.use_secondary_numeric_axis and gd.dataset.use_secondary_numeric_axis:
(numeric2_min, numeric2_max)=update_maxmin(gd.value,
numeric2_min, numeric2_max)
else:
(numeric_min, numeric_max)=update_maxmin(gd.value,
numeric_min, numeric_max)
if not graph.use_clusters():
(horiz_min, horiz_max) = update_maxmin(gd.horiz_value(),
horiz_min, horiz_max)
if verbose:
if graph.use_clusters():
if gd.dataset.use_secondary_numeric_axis:
data_label = graph.secondary_numeric_axis_label
else:
data_label = graph.numeric_axis_label
data_label = parametise_label(graph.widget(), view, data_label)
graph_json["data"].append({
parametise_label(graph.widget(), view, graph.cluster_label): parametise_label(graph.widget(), view, get_graph_subset_displayname(gd.cluster,pval)),
parametise_label(graph.widget(), view, graph.dataset_label): parametise_label(graph.widget(), view, get_graph_subset_displayname(gd.dataset,pval)),
data_label: gd.value
})
else:
graph_json["data"].append({
parametise_label(graph.widget(), view, graph.horiz_axis_label): gd.horiz_json_value(),
parametise_label(graph.widget(), view, graph.dataset_label): parametise_label(graph.widget(), view, get_graph_subset_displayname(gd.dataset,pval)),
data_label: gd.value
})
else:
if graph.use_clusters():
graph_json["data"][gd.cluster.url][gd.dataset.url] = gd.value
else:
graph_json["data"][gd.dataset.url].append([
gd.horiz_json_value(),
gd.value
])
if graph.use_numeric_axes():
graph_json["%s_scale" % graph.numeric_axis_name()] = {
"min": numeric_min,
"max": numeric_max
}
if graph.use_secondary_numeric_axis:
graph_json["%s_2_scale" % graph.numeric_axis_name()] = {
"min": numeric2_min,
"max": numeric2_max
}
if not graph.use_clusters():
graph_json["horizontal_axis_scale"] = {
"min": graph.jsonise_horiz_value(horiz_min),
"max": graph.jsonise_horiz_value(horiz_max)
}
overrides = get_graph_overrides(graph.graphcluster_set, GraphClusterData, "cluster", pval)
if overrides:
graph_json["cluster_name_overrides"] = overrides
overrides = get_graph_overrides(graph.graphdataset_set, GraphDatasetData, "dataset", pval)
if overrides:
graph_json["dataset_name_overrides"] = overrides
return graph_json
def get_data(self, view=None, pval=None):
pval = resolve_pval(self.widget().parametisation, view=view, pval=pval)
return GraphData.objects.filter(graph=self,param_value=pval).natural_order(self)
def get_data(self, view=None, pval=None):
"""Get the data for this graph (parametised if necessary)"""
pval = resolve_pval(self.widget().parametisation, view=view, pval=pval)
return GraphData.objects.filter(graph=self,param_value=pval).natural_order(self)
