pos1 = ax1[ii].get_position()
pos2 = [pos1.x0+0.008+(ii-1)*0.008, pos1.y0, pos1.width, pos1.height]
ax1[ii].set_position(pos2)
plt.show()
if __name__ == "__main__":
args = parser.parse_args()
if args.filename.rstrip()[-5:] == '.json':
args.filename = args.filename[:-5]
elif args.filename.rstrip()[-4:] == '.npz':
args.filename = args.filename[:-4]
# load parameters
params = Run.Params()
params.file_read_chg(args.filename)
dom_len = params.domain_info[1]*2 + 1
# load model result
modelsol = []
with np.load(args.filename+'.npz') as npz_obj:
days = npz_obj['days']
# some code here to make loading robust to both COO and CSR.
CSR = False
for day in days:
V = npz_obj[str(day)+'_data']
if CSR:
indices = npz_obj[str(day)+'_ind']
indptr = npz_obj[str(day)+'_indptr']
modelsol.append(sparse.csr_matrix((V,indices,indptr),
def main(argv):
'''Function for plotting a previous result.
The first argument in the list should be the location of a simulation file.
'''
try:
filename = argv[0]
except IndexError:
print(
'Please pass the filename you wish to load as an argument, e.g.:')
print('python Plot_Result.py output/filename')
return
if filename.rstrip()[-5:] == '.json':
filename = filename[:-5]
elif filename.rstrip()[-4:] == '.npz':
filename = filename[:-4]
# load parameters
params = Run.Params()
params.file_read_chg(filename)
dom_len = params.domain_info[1] * 2 + 1
# load data
modelsol = []
with np.load(filename + '.npz') as npz_obj:
days = npz_obj['days']
for day in days:
V = npz_obj[str(day) + '_data']
# Solution should be reconstructed as CSR sparse
indices = npz_obj[str(day) + '_ind']
indptr = npz_obj[str(day) + '_indptr']
modelsol.append(
sparse.csr_matrix((V, indices, indptr),
shape=(dom_len, dom_len)))
LOCINFO_LOADED = False
print('----------------Model result visualizations----------------')
while True:
val = input(
'\nEnter a day number to plot, ' + 'or "all" to plot all.\n' +
'"save" or "s" and then a number will save that day to file.\n' +
'? will provide a list of plottable day numbers.\n' +
'"vid" will output a video (requires FFmpeg or menconder).\n' +
'"fields" will load data for plotting sentinel field outlines.\n' +
'Or enter q to quit:')
val = val.strip()
if val == '':
continue
elif val == '?':
print(*list(range(1, len(days) + 1)))
elif val.lower() == 'q' or val.lower() == 'quit':
break
elif val.lower() == 'a' or val.lower() == 'all':
# plot_all wants a list of values. pass a view into ordered dict
if LOCINFO_LOADED:
plot_all(modelsol, params, locinfo=locinfo)
else:
plot_all(modelsol, params)
elif val.lower() == 'vid':
if LOCINFO_LOADED:
create_mp4(modelsol, params, filename, locinfo=locinfo)
else:
create_mp4(modelsol, params, filename)
elif val.lower() == 'fields':
try:
from Data_Import import LocInfo
locinfo = LocInfo(params.dataset, params.coord,
params.domain_info)
LOCINFO_LOADED = True
print('\nSentinel field locations loaded.')
except:
print('\nCould not load sentinel field data.')
print(sys.exc_info()[0])
continue
elif val[0] == 's':
try:
if val[:4] == 'save':
val = int(val[4:].strip())
else:
val = int(val[1:].strip())
except ValueError:
print('\nCould not convert {} to an integer.'.format(val))
continue
try:
if LOCINFO_LOADED:
plot(modelsol[val - 1],
val,
params,
saveonly=filename,
locinfo=locinfo)
else:
plot(modelsol[val - 1], val, params, saveonly=filename)
except IndexError:
print("\n{} is out of the simulation's range.".format(val))
print("Possible entries are: " +
str(list(range(1,
len(days) + 1)))[1:-1] + '.')
continue
else:
try:
if LOCINFO_LOADED:
plot(modelsol[int(val) - 1], val, params, locinfo=locinfo)
else:
plot(modelsol[int(val) - 1], val, params)
except KeyError:
print('\nDay {0} not found.'.format(val))
except ValueError:
print('\nInput {} not understood.'.format(val))
continue
except IndexError:
print("\n{} is out of the simulation's range.".format(val))
print("Possible entries are: " +
str(list(range(1,
len(days) + 1)))[1:-1] + '.')
continue
