def __init__(self, filename):
self.filename = filename
self.plot_rect = VOAAreaRect()
self.lat_step_size, self.lon_step_size, self.plot_title, self.data_format_dict = self.parse_global_params()
self.datasets = self.build_dataset_list()
print ("Found ",len(self.datasets), " datasets")
self.itr_ctr = -1
class REC533Out:
'''
A small class to encapsulate files produced by the ITURHFProp
application. These file may contain a number of sets of plot data.
These may be accessed directly or via an iterator.
Plots sets for different values of hour and frequency may be contained
in a single REC533 Out file.
Each entry starts with the month, hour, frequency. User defined values
follow.
'''
filename = ""
def __init__(self, filename):
self.filename = filename
self.plot_rect = VOAAreaRect()
self.lat_step_size, self.lon_step_size, self.plot_title, self.data_format_dict = self.parse_global_params()
self.datasets = self.build_dataset_list()
print ("Found ",len(self.datasets), " datasets")
self.itr_ctr = -1
def consume(self, iterator, n):
"Advance the iterator n-steps ahead. If n is none, consume entirely."
# Use functions that consume iterators at C speed.
if n is None:
# feed the entire iterator into a zero-length deque
collections.deque(iterator, maxlen=0)
else:
# advance to the empty slice starting at position n
next(itertools.islice(iterator, n, n), None)
def parse_global_params(self):
data_format_dict = {}
title = ""
pathname_pattern = re.compile("\** P533 Input Parameters")
lat_inc_pattern = re.compile("^\s*Latitude increment\s*= ([\d.]+) \(deg\)")
lon_inc_pattern = re.compile("^\s*Longitude increment\s*= ([\d.]+) \(deg\)")
col_rel_pattern = re.compile("Column (\d+): BSR - Basic circuit reliability")
col_snr_pattern = re.compile("Column (\d+): SNR - Median signal-to-noise ratio")
title_line_ptr = False
with open(self.filename) as f:
for line in f:
m = pathname_pattern.match(line)
if m:
self.consume(f,1)
title_line_ptr = True
continue
if title_line_ptr:
title = line.strip()
title_line_ptr = False
continue
m = lat_inc_pattern.match(line)
if m:
lat_inc = float(m.group(1))
continue
m = lon_inc_pattern.match(line)
if m:
lon_inc = float(m.group(1))
continue
m = col_rel_pattern.match(line)
if m:
data_format_dict['REL'] = int(m.group(1)) - 1
continue
m = col_snr_pattern.match(line)
if m:
data_format_dict['SNR'] = int(m.group(1)) - 1
continue
if '*** Calculated Parameters ***' in line:
break
return (lat_inc, lon_inc, title, data_format_dict)
def get_datasets(self):
return [(plot_dt, freq, title) for plot_dt, title, freq, idx in self.datasets]
def build_dataset_list(self):
datasets = []
#todo remove hardcoded year
year = '2015'
month = ''
hour = ''
freq = ''
idx = 0
calculated_parameters_section = False
with open(self.filename) as f:
for line in f:
if "**** Calculated Parameters ****" in line:
calculated_parameters_section = True
elif calculated_parameters_section:
params = line.split(',')
if len(params) > 3:
if (month != params[0]) or (hour != params[1]) or (freq != params[2]):
month = params[0]
hour = params[1]
freq =params[2]
h = int(hour) if (int(hour) < 24) else int(hour) % 24
plot_dt = datetime.datetime(int(year), int(month), 15, hour=h)
datasets.append((plot_dt, self.plot_title, freq.strip(), idx))
#print (month, hour, freq, idx)
idx += len(line)+1
return datasets
def __iter__(self):
return self
def __next__(self):
self.itr_ctr += 1
if self.itr_ctr < (len(self.datasets)):
return self.get_plot_data(self.datasets[self.itr_ctr])
else:
raise StopIteration
def get_plot_data(self, dataset_id, plot_type):
try:
data_column = self.data_format_dict[plot_type]
except KeyError:
print("Error: Specified data set {:s} not found in file {:s}".format(plot_type, self.filename))
quit()
plot_dt, title, freq, idx = self.datasets[dataset_id]
num_pts_lat = ((self.plot_rect.get_ne_lat() - self.plot_rect.get_sw_lat()) / self.lat_step_size) + 1
num_pts_lon = ((self.plot_rect.get_ne_lon() - self.plot_rect.get_sw_lon()) / self.lon_step_size) + 1
points = np.zeros([num_pts_lat, num_pts_lon], float)
lons = np.arange(self.plot_rect.get_sw_lon(),
self.plot_rect.get_ne_lon()+1,
self.lon_step_size)
lats = np.arange(self.plot_rect.get_sw_lat(),
self.plot_rect.get_ne_lat()+1,
self.lat_step_size)
f = open(self.filename, 'rt')
freq=freq.strip()
formatted_hour_str = '{0:02d}'.format(plot_dt.hour)
try:
reader = csv.reader(f)
for row in reader:
if len(row) > 3:
#print("looking in +", row[1].strip(), "+ for +", formatted_hour_str, ": looking in +", row[2].strip(), "+ for +", freq,"+")
if row[1].strip()==formatted_hour_str and row[2].strip()==freq:
#print (row)
lat_grid_pos = (int(float(row[3])-self.plot_rect.get_sw_lat()) / self.lat_step_size)
lon_grid_pos = (int(float(row[4])-self.plot_rect.get_sw_lon()) / self.lon_step_size)
points[lat_grid_pos][lon_grid_pos] = float(row[data_column])
finally:
f.close()
# todo don't return the full self.datasets params
return (points, plot_type, lons, lats, num_pts_lon, num_pts_lat, self.datasets[dataset_id])
