# colormap = get_cmap('gist_yarg_r')

colormap = get_cmap('gist_earth')

density_maxes = []

total_counts = []

all_t = []

for delta_minutes in minute_intervals:

time_delta = DateTimeDelta(0, 0, delta_minutes, 0)

n_frames = int(ceil((end_time - start_time) / time_delta))

n_cols = 6

n_rows = int(ceil( float(n_frames) / n_cols ))

w, h = figaspect(float(n_rows)/n_cols)

xedge=np.arange(b.x[0], b.x[1]+dx, dx)

yedge=np.arange(b.y[0], b.y[1]+dy, dy)

x_range = b.x[1] - b.x[0]

y_range = b.y[1] - b.y[0]

min_count, max_count = 1, max_count_baseline*delta_minutes

f = figure(figsize=(w,h))

p = small_multiples_plot(fig=f, rows=n_rows, columns=n_cols)

p.label_edges(True)

for ax in p.multiples.flat:

ax.yaxis.set_major_formatter(kilo_formatter)

ax.xaxis.set_major_formatter(kilo_formatter)

for i in range(n_frames):

frame_start = start_time + i*time_delta

frame_end = frame_start + time_delta

b.sec_of_day = (frame_start.abstime, frame_end.abstime)

b.t = (frame_start, frame_end)

do_plot = False

flash_extent_density = True

density = None

if source_density==True:

lmaManager.refresh(b)

lma_view.transformed.cache_is_old()

x,y,t=lma_view.transformed['x','y','t']

density,edges = np.histogramdd((x,y), bins=(xedge,yedge))

do_plot=True

else:

for lmaManager in HDFmanagers:

# yes, loop through every file every time and reselect data.

# so wrong, yet so convenient.

h5 = lmaManager.h5file

if flash_extent_density == False:

lmaManager.refresh(b)

lma_view = AcuityView(DataSelection(lmaManager.data, b), mapProj, bounds=b)

# lma_view.transformed.cache_is_old()

x,y,t=lma_view.transformed['x','y','t']

if x.shape[0] > 1: do_plot = True

break

else:

# assume here that the bounds sec_of_day day is the same as

# the dataset day

t0, t1 = b.sec_of_day

# events = getattr(h5.root.events, lmaManager.table.name)[:]

# flashes = getattr(h5.root.flashes, lmaManager.table.name)[:]

event_dtype = getattr(h5.root.events, lmaManager.table.name)[0].dtype

events_all = getattr(h5.root.events, lmaManager.table.name)[:]

flashes = getattr(h5.root.flashes, lmaManager.table.name)

def event_yielder(evs, fls):

these_events = []

for fl in fls:

if ( (fl['n_points']>9) &

(t0 < fl['start']) &

(fl['start'] <= t1)

):

these_events = evs[evs['flash_id'] == fl['flash_id']]

if len(these_events) <> fl['n_points']:

print 'not giving all ', fl['n_points'], ' events? ', these_events.shape

for an_ev in these_events:

yield an_ev

# events = np.fromiter((an_ev for an_ev in ( events_all[events_all['flash_id'] == fl['flash_id']]

# for fl in flashes if (

# (fl['n_points']>9) & (t0 < fl['start']) & (fl['start'] <= t1)

# )

# ) ), dtype=event_dtype)

events = np.fromiter(event_yielder(events_all, flashes), dtype=event_dtype)

# print events['flash_id'].shape

### Flash extent density ###

x,y,z = mapProj.fromECEF(

*geoProj.toECEF(events['lon'], events['lat'], events['alt'])

)

# Convert to integer grid coordinate bins

# 0 1 2 3

# | | | | |

# -1.5 0.0 1.5 3.0 4.5

if x.shape[0] > 1:

density, edges = extent_density(x,y,events['flash_id'].astype('int32'),

b.x[0], b.y[0], dx, dy, xedge, yedge)

do_plot = True

break

# print 'density values: ', density.min(), density.max()

if do_plot == True: # need some data

# density,edges = np.histogramdd((x,y), bins=(xedge,yedge))

density_plot = p.multiples.flat[i].pcolormesh(xedge,yedge,

np.log10(density.transpose()),

vmin=-0.2,

vmax=np.log10(max_count),

cmap=colormap)

label_string = frame_start.strftime('%H%M:%S')

text_label = p.multiples.flat[i].text(b.x[0]-pad+x_range*.01, b.y[0]-pad+y_range*.01, label_string, color=(0.5,)*3, size=6)

density_plot.set_rasterized(True)

density_maxes.append(density.max())

total_counts.append(density.sum())

all_t.append(frame_start)

print label_string, x.shape, density.max(), density.sum()

color_scale = ColorbarBase(p.colorbar_ax, cmap=density_plot.cmap,

norm=density_plot.norm,

orientation='horizontal')

# color_scale.set_label('count per pixel')

color_scale.set_label('log10(count per pixel)')

# moving reference frame correction. all panels will have same limits, based on time of last frame

view_dt = 0.0 # (frame_start - t0).seconds

x_ctr = x0 + view_dt*u

y_ctr = y0 + view_dt*v

view_x = (x_ctr - view_dx/2.0 - pad, x_ctr + view_dx/2.0 + pad)

view_y = (y_ctr - view_dy/2.0 - pad, y_ctr + view_dy/2.0 + pad)

# view_x = (b.x[0]+view_dt*u, b.x[1]+view_dt*u)

# view_y = (b.y[0]+view_dt*v, b.y[1]+view_dt*v)

# print 'making timeseries',

# time_series = figure(figsize=(16,9))

# ts_ax = time_series.add_subplot(111)

# ts_ax.plot_date(mx2num(all_t),total_counts,'-', label='total sources', tz=tz)

# ts_ax.plot_date(mx2num(all_t),density_maxes,'-', label='max pixel', tz=tz)

# ts_ax.xaxis.set_major_formatter(time_series_x_fmt)

# ts_ax.legend()

# time_filename = 'out/LMA-timeseries_%s_%5.2fkm_%5.1fs.pdf' % (start_time.strftime('%Y%m%d_%H%M%S'), dx/1000.0, time_delta.seconds)

# time_series.savefig(time_filename)

# print ' ... done'

print 'making multiples',

p.multiples.flat[0].axis(view_x+view_y)

filename = 'out/LMA-density_%s_%5.2fkm_%5.1fs.pdf' % (start_time.strftime('%Y%m%d_%H%M%S'), dx/1000.0, time_delta.seconds)

f.savefig(filename, dpi=150)

print ' ... done'

f.clf()