def results(request):
get_histogram = True if 'get_histogram' in request.POST.keys() else False
get_time_series = True if 'get_time_series' in request.POST.keys() else False
log_y = True if 'log_y' in request.POST.keys() else False
hist_log_y = True if 'hist_log_y' in request.POST.keys() else False
hist_log_x = True if 'hist_log_x' in request.POST.keys() else False
show_errors = True if 'show_errors' in request.POST.keys() else False
hist_show_errors = True if 'hist_show_errors' in request.POST.keys() else False
select_stat = request.POST['select_stat']
select_span = request.POST['select_span']
num_bins = int(request.POST['num_bins'])
align_start = True if 'align_start' in request.POST.keys() else False
bio_or_npp = request.POST['bio_or_npp']
table_dict = {
'bio': 'piedata',
'gro': 'piedata',
'npp_wet': 'kelp_grow_npp',
'bio_all': 'hja_ws1_test',
'anpp': 'hja_ws1_test',
}
#if dataset == 'bio' or dataset == 'gro':
# data_label = 'PIE' # Plum Island Ecosystem: estuary (Spartina spp.)
#elif dataset == 'bio_all':
# data_label = 'HJA' # HJ Andrews: old-growth forest (Psuedotsuga menziesii)
#else:
# data_label = 'SBC' # Santa Barbara Coastal: sea vegetation (Macrocystis spp.)
P = Plotter(bins=num_bins, align=align_start)
P.summary_stats()
P.fetch_data()
P.make_plots()
if select_span == 'year':
time_series = P.time_series
field_list = ['bio', 'gro', 'bio_all', 'npp_wet', 'anpp']
else:
time_series = P.monthly_time_series
field_list = ['bio', 'gro', 'npp_wet']
keep_fields = ['gro', 'npp_wet', 'anpp'] if bio_or_npp == 'npp' \
else ['bio', 'bio_all']
field_list = filter(
None, [f if f in keep_fields else None for f in field_list]
)
# Create prettier labels for the plots...
field_labels = {
'bio': 'PIE',
'gro': 'PIE',
'bio_all': 'HJA',
'npp_wet': 'SBC',
'anpp': 'HJA',
}
stat_labels = {
'max': 'Maximum',
'mean': 'Mean',
'median': 'Median',
'min': 'Minimum',
'quartile_1': '1st quartile',
'quartile_3': '3rd quartile',
}
json_time_series = {}
json_histogram = {}
total_summary, total_labels = [], []
for field in field_list:
# Get standard errors and zip time-series data into JSON-like dict
# (for Flot)
time_key = 'yearly' if select_span == 'year' else 'aggregate'
this_summary = P.summary[time_key][table_dict[field]][field]
values = time_series[field][select_stat]
if show_errors:
N = [this_summary[j]['N'] for j in this_summary.keys()]
error_bars = [j/sqrt(N[i]-1) \
for i, j in enumerate(time_series[field]['std'])]
period = time_series[field][select_span]
data = zip(period, values, error_bars)
else:
period = time_series[field][select_span]
data = zip(period, values)
data = [list(j) for j in data]
json_time_series[field] = {
'label': field_labels[field],
'data': data,
}
# Zip histogram data into JSON-like dict (for Flot)
hist_x = P.hist['bin'][field]
bar_width = P.hist['bin'][field][1] - P.hist['bin'][field][0]
hist_bar_width = [bar_width for j in hist_x]
if hist_log_y:
hist_y = [None if j == 0 else j for j in P.hist['percent'][field]]
else:
hist_y = P.hist['percent'][field]
if hist_show_errors:
hist_errors = [0 if isnan(j) else j for j in P.hist['std'][field]]
hist_data = zip(hist_x, hist_y, hist_errors)
else:
hist_errors = [0 for j in hist_y]
hist_data = zip(hist_x, hist_y, hist_errors, hist_bar_width)
hist_data = [list(j) for j in hist_data]
json_histogram[field] = {
'label': field_labels[field],
'data': hist_data,
}
this_total = P.summary['total'][time_key][table_dict[field]][field]
total_labels.append(field_labels[field])
total_summary.append([
[
#field_labels[field],
stat_labels[key],
repr(round(this_total[key]['mean']*1000.0)/1000.0),
repr(round(this_total[key]['std']*1000.0)/1000.0)
]
for key in this_total.keys()
])
summary = zip(total_labels, total_summary)
bar_width = P.hist['bin']['npp_wet'][1] - P.hist['bin']['npp_wet'][0]
bio_or_npp_dict = {
'biomass': '<strong>Biomass</strong> (g/m<sup>2</sup>)',
'npp': '<strong>NPP</strong> (g/m<sup>2</sup>/year)',
}
bio_or_npp_label = bio_or_npp_dict[bio_or_npp]
if bio_or_npp == 'biomass':
json_histogram_1 = json_histogram['bio']
json_histogram_2 = json_histogram['bio_all']
json_histogram_3 = None
else:
json_histogram_1 = json_histogram['gro']
json_histogram_2 = json_histogram['npp_wet']
json_histogram_3 = json_histogram['anpp']
return render(request, 'visual/results.html', {
#'dataset': dataset,
#'table': table,
#'get_summary': get_summary,
#'get_histogram': get_histogram,
#'get_time_series': get_time_series,
'select_stat': select_stat,
'select_span': select_span,
'show_errors': show_errors,
'hist_show_errors': hist_show_errors,
'log_y': log_y,
'bar_width': bar_width,
'hist_log_y': hist_log_y,
'hist_log_x': hist_log_x,
#'bin_sizes': bin_sizes,
'summary': summary,
'num_bins': P.num_bins,
'bio_or_npp': bio_or_npp,
'bio_or_npp_label': bio_or_npp_label,
#'histogram': histogram,
#'time_series': time_series,
'json_time_series': json.dumps(json_time_series),
'json_histogram': json.dumps(json_histogram),
'json_histogram_1': json.dumps(json_histogram_1),
'json_histogram_2': json.dumps(json_histogram_2),
'json_histogram_3': json.dumps(json_histogram_3),
})
