def animateImages(imglist, datetimelist, mask, settings, logger, duration, fps,
resolution, fformat):
if len(imglist) == 0:
return False
mask, pgs, th = mask
(duration, fps, resolution) = map(float, (duration, fps, resolution[:-1]))
resolution = int(resolution)
if fps == 0 and duration != 0:
fps = len(datetimelist) / duration
if fps < 1:
fps = 1.0
if fps != 0 and duration == 0:
duration = len(datetimelist) / fps
if fps == 0 and duration == 0:
logger.set("Either duration or frames per second should not be zero.")
return False
logger.set('Generating animation...')
logger.set('Number of images:' + str(len(imglist)))
logger.set('Animation duration: ' +
str(datetime.timedelta(seconds=duration)))
logger.set('Frames per second: ' + str(fps))
logger.set('Resolution ' + str(resolution) + 'p')
logger.set('Format: ' + str(fformat))
(sdate, edate) = (datetimelist[0], datetimelist[-1])
dateratio = (edate - sdate).total_seconds() / float(duration)
animfname = str(uuid4()) + '.' + fformat.lower()
while os.path.isfile(os.path.join(TmpDir, animfname)):
animfname = str(uuid4()) + '.' + fformat.lower()
animfname = os.path.join(TmpDir, animfname)
datetimelist = np.array(datetimelist)
toy_frame_ratio = 100
year_total_secs = abs(
datetime.datetime(1971, 1, 1, 0, 0, 0) -
datetime.datetime(1970, 1, 1, 0, 0, 0)).total_seconds()
def make_frame(t):
try:
frame_for_time_t = mahotas.imread(imglist[np.argmin(
np.abs(datetimelist - sdate -
datetime.timedelta(seconds=dateratio * t)))])
#print np.argmin(np.abs(datetimelist-sdate-datetime.timedelta(seconds=dateratio*t)))
#print imglist[np.argmin(np.abs(datetimelist-sdate-datetime.timedelta(seconds=dateratio*t)))]
except:
frame_for_time_t = mahotas.imread(imglist[0]) * 0
if len(frame_for_time_t.shape) != 3:
frame_for_time_t = mahotas.imread(imglist[0]) * 0
img_date = datetimelist[np.argmin(
np.abs(datetimelist - sdate -
datetime.timedelta(seconds=dateratio * t)))]
vid_date = sdate + datetime.timedelta(seconds=dateratio * t)
img_toy = abs(
datetime.datetime(img_date.year, 1, 1, 0, 0, 0) -
img_date).total_seconds() / float(year_total_secs)
vid_toy = abs(
datetime.datetime(vid_date.year, 1, 1, 0, 0, 0) -
vid_date).total_seconds() / float(year_total_secs)
toyframe = np.zeros(
(int(round(frame_for_time_t.shape[0] / toy_frame_ratio)),
frame_for_time_t.shape[1]),
dtype='uint8')
img_toy = [
int(round(toyframe.shape[1] * img_toy)) -
int(round(frame_for_time_t.shape[0] / toy_frame_ratio)),
int(round(toyframe.shape[1] * img_toy)) +
int(round(frame_for_time_t.shape[0] / toy_frame_ratio))
]
vid_toy = [
int(round(toyframe.shape[1] * vid_toy)) -
int(round(frame_for_time_t.shape[0] / toy_frame_ratio)),
int(round(toyframe.shape[1] * vid_toy)) +
int(round(frame_for_time_t.shape[0] / toy_frame_ratio))
]
if img_toy[0] < 0:
img_toy[0] = 0
if img_toy[1] > toyframe.shape[1]:
img_toy[1] = toyframe.shape[1]
if vid_toy[0] < 0:
vid_toy[0] = 0
if vid_toy[1] > toyframe.shape[1]:
vid_toy[1] = toyframe.shape[1]
toyframe[:int(round(toyframe.shape[0] / 2)),
img_toy[0]:img_toy[1]] = 127
toyframe[int(round(toyframe.shape[0] / 2)):,
vid_toy[0]:vid_toy[1]] = 255
toyframe = np.dstack((toyframe, toyframe, toyframe))
frame_for_time_t = np.vstack((frame_for_time_t, toyframe))
logger.set('Frame time: |progress:4|queue:' + str(t + 1 / fps) +
'|total:' + str(round(int(duration))))
return frame_for_time_t # (Height x Width x 3) Numpy array
animation = VideoClip(make_frame, duration=duration)
if resolution != 0:
animation = animation.resize(height=resolution)
logger.set("Writing animation...")
if fformat == "MP4":
animation.write_videofile(animfname, fps=fps)
if fformat == "GIF":
animation.write_gif(animfname, fps=fps)
output = ["filename", animfname]
output = [["Time series animation", output]]
return output
def animateImagesFromResults(imglist, datetimelist, mask, settings, logger,
temporalmode, temporalrange, temporalthreshold,
replaceimages, varstoplot, barwidth, barlocation,
duration, fps, resolution, fformat, resdata):
if len(imglist) == 0:
return False
if mask is not None:
mask, pgs, th = mask
(duration, fps, resolution,
barwidth) = map(float, (duration, fps, resolution[:-1], barwidth))
barwidth = barwidth / 100.0
resolution = int(resolution)
temporalthreshold = datetime.timedelta(hours=float(temporalthreshold))
logger.set('Generating animation...')
res_captions = []
res_data = []
for i, v in enumerate(resdata):
if i % 2 == 0:
res_captions.append(v)
else:
res_data.append(v)
resdata = None
# if temporalmode == 'Date interval':
if True:
sdate = min([
datetime.datetime.strptime(temporalrange[0], '%d.%m.%Y'),
datetime.datetime.strptime(temporalrange[1], '%d.%m.%Y')
])
edate = max([
datetime.datetime.strptime(temporalrange[0], '%d.%m.%Y'),
datetime.datetime.strptime(temporalrange[1], '%d.%m.%Y')
])
logger.set('Number of images:' + str(
np.sum((np.array(datetimelist) <= edate) *
(np.array(datetimelist) >= sdate))))
if fps == 0:
fps = np.sum((np.array(datetimelist) <= edate) *
(np.array(datetimelist) >= sdate)) / duration
if fps < 1:
fps = 1.0
else: #range in data
sdate = min(res_data[res_captions.index('Time')])
edate = max(res_data[res_captions.index('Time')])
logger.set('Number of images:' + str(len(imglist)))
if fps == 0:
fps = len(datetimelist) / duration
if fps < 1:
fps = 1.0
logger.set('Animation duration: ' +
str(datetime.timedelta(seconds=duration)))
logger.set('Frames per second: ' + str(fps))
logger.set('Number of frames: ' + str(fps * duration))
logger.set('Resolution ' + str(resolution) + 'p')
logger.set('Format: ' + str(fformat))
dateratio = (edate - sdate).total_seconds() / float(duration)
animfname = str(uuid4()) + '.' + fformat.lower()
while os.path.isfile(os.path.join(TmpDir, animfname)):
animfname = str(uuid4()) + '.' + fformat.lower()
animfname = os.path.join(TmpDir, animfname)
datetimelist = np.array(datetimelist)
range_total_secs = abs(edate - sdate).total_seconds()
for i, v in enumerate(varstoplot):
if v[1] != 'Time':
if v[4] == '':
varstoplot[i][4] = np.nanmin(res_data[res_captions.index(
v[1])])
else:
varstoplot[i][4] = float(v[4])
if v[5] == '':
varstoplot[i][5] = np.nanmax(res_data[res_captions.index(
v[1])])
else:
varstoplot[i][5] = float(v[5])
def make_frame(t):
res_date = res_data[res_captions.index('Time')][np.argmin(
np.abs(res_data[res_captions.index('Time')] - sdate -
datetime.timedelta(seconds=dateratio * t)))]
if abs(res_date - sdate -
datetime.timedelta(seconds=dateratio * t)) > temporalthreshold:
img_file = False
else:
if res_date in datetimelist:
img_date = res_date
img_file = imglist[datetimelist.tolist().index(img_date)]
try:
img = mahotas.imread(img_file)
except:
img_file = False
if res_date not in datetimelist or img_file is False: #'Closest image','Blank (Black)','Blank (White)','Monochromatic Noise'
if replaceimages == 'Closest image': #xxcheck later again
img_date = datetimelist[np.argmin(
np.abs(datetimelist - res_date))]
img_file = imglist[np.argmin(np.abs(datetimelist - res_date))]
img = mahotas.imread(img_file)
else:
img_date = res_date
if replaceimages == 'Blank (Black)':
img = mahotas.imread(imglist[0]) * 0
if replaceimages == 'Blank (White)':
img = mahotas.imread(imglist[0]) * 0 + 255
if replaceimages == 'Monochromatic Noise':
img = (
np.random.rand(*mahotas.imread(imglist[0]).shape[:2]) *
255).astype('uint8')
img = np.dstack((img, img, img))
vid_date = sdate + datetime.timedelta(seconds=dateratio * t)
res_toy = abs(
datetime.datetime(res_date.year, 1, 1, 0, 0, 0) -
res_date).total_seconds() / float(
abs(
datetime.datetime(res_date.year, 12, 31, 23, 59, 59) -
datetime.datetime(res_date.year, 1, 1, 0, 0, 0)).
total_seconds())
if img_file == False:
res_toy = 0.0
vid_toy = datetime.timedelta(
seconds=dateratio * t).total_seconds() / float(range_total_secs)
if barlocation == 'Right' or barlocation == 'Left':
barshape = (img.shape[0], int(round(img.shape[1] * barwidth)))
for v in varstoplot:
if bool(int(v[0])):
barframe = np.zeros(barshape, dtype='uint8')
if v[1] == 'Time':
barvalue = vid_toy
barvalue = int(round(barshape[0] * barvalue))
barvalue2 = res_toy
barvalue2 = int(round(barshape[0] * barvalue2))
barframe[-barvalue:, :int(round(barshape[1] /
2.0))] = 1
barframe[-barvalue2:,
int(round(barshape[1] / 2.0)):] = 1
barframe = np.dstack(
((barframe == 0) * int(v[2][1:3], 16) +
(barframe == 1) * int(v[3][1:3], 16),
(barframe == 0) * int(v[2][3:5], 16) +
(barframe == 1) * int(v[3][3:5], 16),
(barframe == 0) * int(v[2][5:7], 16) +
(barframe == 1) * int(v[3][5:7], 16)))
img = np.hstack((img, barframe))
else:
if img_file == False:
barframe = (np.random.rand(*barframe.shape[:2]) *
255).astype('uint8')
barframe = np.dstack(
(barframe, barframe, barframe))
else:
barvalue = res_data[res_captions.index(
v[1])][res_data[res_captions.index(
'Time')].tolist().index(res_date)]
barvalue = abs(
(barvalue /
float(abs(float(v[5]) - float(v[4])))))
barvalue = int(round(barshape[0] * barvalue))
if np.isnan(barvalue):
barvalue = 0
barframe[-barvalue:, :] = 1
barframe = barframe.transpose(1,
0)[::-1].transpose(
1, 0)
barframe = np.dstack(
((barframe == 0) * int(v[2][1:3], 16) +
(barframe == 1) * int(v[3][1:3], 16),
(barframe == 0) * int(v[2][3:5], 16) +
(barframe == 1) * int(v[3][3:5], 16),
(barframe == 0) * int(v[2][5:7], 16) +
(barframe == 1) * int(v[3][5:7], 16)))
img = np.hstack((img, barframe))
else:
barshape = (int(round(img.shape[0] * barwidth)), img.shape[1])
for v in varstoplot:
if bool(int(v[0])):
barframe = np.zeros(barshape, dtype='uint8')
if v[1] == 'Time':
barvalue = vid_toy
barvalue = int(round(barshape[1] * barvalue))
barvalue2 = res_toy
barvalue2 = int(round(barshape[1] * barvalue2))
barframe[:int(round(barshape[0] / 2.0)), :barvalue] = 1
barframe[int(round(barshape[0] /
2.0)):, :barvalue2] = 1
barframe = np.dstack(
((barframe == 0) * int(v[2][1:3], 16) +
(barframe == 1) * int(v[3][1:3], 16),
(barframe == 0) * int(v[2][3:5], 16) +
(barframe == 1) * int(v[3][3:5], 16),
(barframe == 0) * int(v[2][5:7], 16) +
(barframe == 1) * int(v[3][5:7], 16)))
img = np.vstack((img, barframe))
else:
if img_file == False:
barframe = (np.random.rand(*barframe.shape[:2]) *
255).astype('uint8')
barframe = np.dstack(
(barframe, barframe, barframe))
else:
barvalue = res_data[res_captions.index(
v[1])][res_data[res_captions.index(
'Time')].tolist().index(res_date)]
barvalue = barvalue / float(
abs(float(v[5]) - float(v[4])))
barvalue = int(round(barshape[1] * barvalue))
if np.isnan(barvalue):
barvalue = 0
barframe[:, :barvalue] = 1
barframe = np.dstack(
((barframe == 0) * int(v[2][1:3], 16) +
(barframe == 1) * int(v[3][1:3], 16),
(barframe == 0) * int(v[2][3:5], 16) +
(barframe == 1) * int(v[3][3:5], 16),
(barframe == 0) * int(v[2][5:7], 16) +
(barframe == 1) * int(v[3][5:7], 16)))
img = np.vstack((img, barframe))
logger.set('Frame time: |progress:4|queue:' + str(t + 1 / fps) +
'|total:' + str(round(int(duration))))
return img # (Height x Width x 3) Numpy array
animation = VideoClip(make_frame, duration=duration)
if resolution != 0:
animation = animation.resize(height=resolution)
logger.set("Writing animation...")
if fformat == "MP4":
animation.write_videofile(animfname, fps=fps)
if fformat == "GIF":
animation.write_gif(animfname, fps=fps)
output = ["filename", animfname]
output = [["Time series animation", output]]
return output
