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forkoziforkozi
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deleted certain print statements and changed version number before release v2.2.0
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+7
-248
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2 files changed

+7
-248
lines changed

‎Tpu.py‎

Lines changed: 6 additions & 232 deletions
Original file line numberDiff line numberDiff line change
@@ -50,8 +50,6 @@
5050
import datetime
5151
import cProfile
5252

53-
import matplotlib.pyplot as plt
54-
5553

5654
class Tpu:
5755
"""
@@ -121,191 +119,11 @@ def update_fl_stats(self, fl, num_fl_points, fl_tpu_data):
121119
fl_tpu_stddev[ind])
122120

123121
fl_stats_str = '{}: {:6.3f}{:6.3f}{:6.3f}{:6.3f}'.format(*fl_stats_vals)
124-
#fl_stats_str = '{}: {:6d}{:6d}{:6.0f}{:6.0f}'.format(*fl_stats_vals)
125122
fl_stats_strs.append(fl_stats_str)
126123

127124
fl_header_str = f'{fl} ({fl_tpu_count}/{num_fl_points} points with TPU)'
128125
self.flight_line_stats.update({fl_header_str: fl_stats_strs})
129126

130-
def export_diag_data(self, las_base_name, diag_dfs):
131-
diag_data_fields = {
132-
'las_data': [
133-
'las_name',
134-
'flight_line',
135-
'raw_class',
136-
'las_t',
137-
'las_x',
138-
'las_y',
139-
'las_z'],
140-
'sbet_data': [
141-
'sbet_t',
142-
'sbet_x',
143-
'sbet_y',
144-
'sbet_z',
145-
'r',
146-
'p',
147-
'h',
148-
'std_r',
149-
'std_p',
150-
'std_h',
151-
'stdx_sbet',
152-
'stdy_sbet',
153-
'stdz_sbet'],
154-
'subaerial_data': [
155-
'rho_est',
156-
'a_est',
157-
'b_est',
158-
'std_a',
159-
'std_b',
160-
'std_rho',
161-
'aer_x_pre_poly',
162-
'aer_y_pre_poly',
163-
'aer_z_pre_poly',
164-
'dx',
165-
'dy',
166-
'dz'],
167-
'cblue_position': [
168-
'cblue_aer_x',
169-
'cblue_aer_y',
170-
'cblue_aer_z',
171-
'cblue_aer_err_x',
172-
'cblue_aer_err_y',
173-
'cblue_aer_err_z'],
174-
'subaer_comp_uncertainties': [
175-
'x_subaer_a',
176-
'x_subaer_b',
177-
'x_subaer_r',
178-
'x_subaer_p',
179-
'x_subaer_h',
180-
'x_subaer_x',
181-
'x_subaer_y',
182-
'x_subaer_z',
183-
'x_subaer_rho',
184-
'y_subaer_a',
185-
'y_subaer_b',
186-
'y_subaer_r',
187-
'y_subaer_p',
188-
'y_subaer_h',
189-
'y_subaer_x',
190-
'y_subaer_y',
191-
'y_subaer_z',
192-
'y_subaer_rho',
193-
'z_subaer_a',
194-
'z_subaer_b',
195-
'z_subaer_r',
196-
'z_subaer_p',
197-
'z_subaer_h',
198-
'z_subaer_x',
199-
'z_subaer_y',
200-
'z_subaer_z',
201-
'z_subaer_rho'],
202-
'tpu_data': [
203-
'subaerial_thu',
204-
'subaerial_tvu',
205-
'subaqueous_thu',
206-
'subaqueous_tvu',
207-
'total_thu',
208-
'total_tvu']
209-
}
210-
211-
for k, v in diag_data_fields.items():
212-
data = {}
213-
for field in v:
214-
print(f'adding {field} data to array...')
215-
data[field] = []
216-
for fl_df in diag_dfs:
217-
data[field].extend(fl_df[field].to_list())
218-
219-
df = pd.DataFrame(data)
220-
out_path = Path(self.tpu_output) / f'{las_base_name}_{k}.pkl'
221-
print(f'pickling {out_path}...')
222-
df.to_pickle(str(out_path))
223-
224-
def output_diagnostic_data(self, las_short_name, fl, merged_data,
225-
stddev, subaer_obj, subaqu_obj,
226-
total_thu, total_tvu, raw_class):
227-
228-
print(f'outputting diagnostic data - {las_short_name}, flight line {fl}...')
229-
230-
las_pos_xyz = (merged_data[2], merged_data[3], merged_data[4], )
231-
sensor_model_diag_data = subaer_obj.jacobian.sensor_model.get_sensor_model_diagnostic_data(las_pos_xyz)
232-
233-
diag_data = {
234-
'las_name': las_short_name,
235-
'flight_line': fl,
236-
'raw_class': raw_class,
237-
'las_t': merged_data[1],
238-
'las_x': merged_data[2],
239-
'las_y': merged_data[3],
240-
'las_z': merged_data[4],
241-
'sbet_t': merged_data[0],
242-
'sbet_x': merged_data[5],
243-
'sbet_y': merged_data[6],
244-
'sbet_z': merged_data[7],
245-
'r': merged_data[8],
246-
'p': merged_data[9],
247-
'h': merged_data[10],
248-
'std_a': stddev[0],
249-
'std_b': stddev[1],
250-
'std_r': stddev[2],
251-
'std_p': stddev[3],
252-
'std_h': stddev[4],
253-
'stdx_sbet': stddev[5],
254-
'stdy_sbet': stddev[6],
255-
'stdz_sbet': stddev[7],
256-
'std_rho': stddev[8],
257-
'rho_est': sensor_model_diag_data[0],
258-
'a_est': sensor_model_diag_data[1],
259-
'b_est': sensor_model_diag_data[2],
260-
'aer_x_pre_poly': sensor_model_diag_data[3],
261-
'aer_y_pre_poly': sensor_model_diag_data[4],
262-
'aer_z_pre_poly': sensor_model_diag_data[5],
263-
'dx': sensor_model_diag_data[6],
264-
'dy': sensor_model_diag_data[7],
265-
'dz': sensor_model_diag_data[8],
266-
'cblue_aer_x': sensor_model_diag_data[9], # np.round_(total_thu * 100).astype('int')
267-
'cblue_aer_y': sensor_model_diag_data[10],
268-
'cblue_aer_z': sensor_model_diag_data[11],
269-
'cblue_aer_err_x': sensor_model_diag_data[12],
270-
'cblue_aer_err_y': sensor_model_diag_data[13],
271-
'cblue_aer_err_z': sensor_model_diag_data[14],
272-
'x_subaer_a': np.round_(subaer_obj.x_comp_uncertainties[0] * 1000).astype('uint16'),
273-
'x_subaer_b': np.round_(subaer_obj.x_comp_uncertainties[1] * 1000).astype('uint16'),
274-
'x_subaer_r': np.round_(subaer_obj.x_comp_uncertainties[2] * 1000).astype('uint16'),
275-
'x_subaer_p': np.round_(subaer_obj.x_comp_uncertainties[3] * 1000).astype('uint16'),
276-
'x_subaer_h': np.round_(subaer_obj.x_comp_uncertainties[4] * 1000).astype('uint16'),
277-
'x_subaer_x': np.round_(subaer_obj.x_comp_uncertainties[5] * 1000).astype('uint16'),
278-
'x_subaer_y': None,
279-
'x_subaer_z': None,
280-
'x_subaer_rho': np.round_(subaer_obj.x_comp_uncertainties[6] * 1000).astype('uint16'),
281-
'y_subaer_a': np.round_(subaer_obj.y_comp_uncertainties[0] * 1000).astype('uint16'),
282-
'y_subaer_b': np.round_(subaer_obj.y_comp_uncertainties[1] * 1000).astype('uint16'),
283-
'y_subaer_r': np.round_(subaer_obj.y_comp_uncertainties[2] * 1000).astype('uint16'),
284-
'y_subaer_p': np.round_(subaer_obj.y_comp_uncertainties[3] * 1000).astype('uint16'),
285-
'y_subaer_h': np.round_(subaer_obj.y_comp_uncertainties[4] * 1000).astype('uint16'),
286-
'y_subaer_x': None,
287-
'y_subaer_y': np.round_(subaer_obj.y_comp_uncertainties[5] * 1000).astype('uint16'),
288-
'y_subaer_z': None,
289-
'y_subaer_rho': np.round_(subaer_obj.y_comp_uncertainties[6] * 1000).astype('uint16'),
290-
'z_subaer_a': np.round_(subaer_obj.z_comp_uncertainties[0] * 1000).astype('uint16'),
291-
'z_subaer_b': np.round_(subaer_obj.z_comp_uncertainties[1] * 1000).astype('uint16'),
292-
'z_subaer_r': np.round_(subaer_obj.z_comp_uncertainties[2] * 1000).astype('uint16'),
293-
'z_subaer_p': np.round_(subaer_obj.z_comp_uncertainties[3] * 1000).astype('uint16'),
294-
'z_subaer_h': None,
295-
'z_subaer_x': None,
296-
'z_subaer_y': None,
297-
'z_subaer_z': np.round_(subaer_obj.z_comp_uncertainties[4] * 1000).astype('uint16'),
298-
'z_subaer_rho': np.round_(subaer_obj.z_comp_uncertainties[5] * 1000).astype('uint16'),
299-
'subaerial_thu': subaer_obj.thu,
300-
'subaerial_tvu': subaer_obj.tvu,
301-
'subaqueous_thu': subaqu_obj.thu,
302-
'subaqueous_tvu': subaqu_obj.tvu,
303-
'total_thu': total_thu,
304-
'total_tvu': total_tvu,
305-
}
306-
307-
return pd.DataFrame(diag_data)
308-
309127
def calc_tpu(self, sbet_las_files):
310128
"""
311129
@@ -367,28 +185,15 @@ def calc_tpu(self, sbet_las_files):
367185
total_tvu = ne.evaluate('sqrt(subaer_tvu**2 + subaqu_tvu**2 + vdatum_mcu**2)')
368186

369187
fl_tpu_data = np.vstack((
370-
#np.round_(total_thu * 1000).astype('uint16'),
371-
#np.round_(total_tvu * 1000).astype('uint16'),
372188
total_thu,
373189
total_tvu,
374-
merged_data[1],
375-
merged_data[2],
376-
merged_data[3],
377-
merged_data[4],
378-
raw_class,
379190
unsort_idx
380191
)).T
381192

382-
print(fl_tpu_data)
383193
data_to_output.append(fl_tpu_data)
384194

385195
self.update_fl_stats(fl, num_fl_points, fl_tpu_data)
386196

387-
#diag_dfs.append(self.output_diagnostic_data(las.las_short_name, fl,
388-
# merged_data, stddev,
389-
# subaer_obj, subaqu_obj,
390-
# total_thu, total_tvu, raw_class))
391-
392197
else:
393198
logging.warning('SBET and LAS not merged because max delta '
394199
'time exceeded acceptable threshold of {} '
@@ -400,9 +205,6 @@ def calc_tpu(self, sbet_las_files):
400205
self.write_metadata(las) # TODO: include as VLR?
401206
self.output_tpu_to_las_extra_bytes(las, data_to_output)
402207

403-
## merge fl diagnostic dataframes
404-
#self.export_diag_data(las.las_base_name, diag_dfs)
405-
406208
else:
407209
logging.warning('WARNING: {} has no data points'.format(las.las_short_name))
408210

@@ -446,17 +248,11 @@ def output_tpu_to_las_extra_bytes(self, las, data_to_output):
446248
in_las = laspy.file.File(las.las, mode="r") # las is Las object
447249
out_las = laspy.file.File(out_las_name, mode="w", header=in_las.header)
448250

449-
tpu_data_type = 9 # 3 = laspy unsigned short (2 bytes)
251+
tpu_data_type = 9 # float
450252

451253
extra_byte_dimensions = OrderedDict([
452254
('total_thu', tpu_data_type),
453-
('total_tvu', tpu_data_type),
454-
('t', tpu_data_type),
455-
('x', tpu_data_type),
456-
('y', tpu_data_type),
457-
('z', tpu_data_type),
458-
('raw_class', tpu_data_type),
459-
('unsort_idx', tpu_data_type)
255+
('total_tvu', tpu_data_type)
460256
])
461257

462258
num_extra_bytes = len(extra_byte_dimensions.keys())
@@ -470,12 +266,10 @@ def output_tpu_to_las_extra_bytes(self, las, data_to_output):
470266

471267
if len(data_to_output) != 0:
472268
tpu_data = np.vstack(data_to_output)
473-
print(tpu_data)
474-
extra_byte_df = pd.DataFrame(tpu_data,
475-
index=tpu_data[:, -1],
269+
extra_byte_df = pd.DataFrame(tpu_data[:, 0:num_extra_bytes],
270+
index=tpu_data[:, num_extra_bytes],
476271
columns=extra_byte_dimensions.keys())
477-
print(extra_byte_df)
478-
272+
479273
if extra_byte_df.shape[0] == las.num_file_points:
480274
extra_byte_df = extra_byte_df.sort_index()
481275
else:
@@ -490,27 +284,7 @@ def output_tpu_to_las_extra_bytes(self, las, data_to_output):
490284

491285
logging.debug('populating extra byte data for total_tvu...')
492286
out_las.total_tvu = extra_byte_df['total_tvu']
493-
494-
logging.debug('populating extra byte data for t...')
495-
out_las.t = extra_byte_df['t']
496-
497-
logging.debug('populating extra byte data for x...')
498-
out_las.x = extra_byte_df['x']
499-
500-
logging.debug('populating extra byte data for y...')
501-
out_las.y = extra_byte_df['y']
502287

503-
logging.debug('populating extra byte data for z...')
504-
out_las.z = extra_byte_df['z']
505-
506-
logging.debug('populating extra byte data for raw_class...')
507-
out_las.raw_class = extra_byte_df['raw_class']
508-
509-
logging.debug('populating extra byte data for unsort_idx...')
510-
out_las.unsort_idx = extra_byte_df['unsort_idx']
511-
512-
#logging.debug('populating extra byte data for masked_fl_t_idx...')
513-
#out_las.masked_fl_t_idx = extra_byte_df['masked_fl_t_idx']
514288
else:
515289
logging.debug('populating extra byte data for total_thu...')
516290
out_las.total_thu = np.zeros(las.num_file_points)
@@ -575,7 +349,7 @@ def run_tpu_multiprocess(self, num_las, sbet_las_generator):
575349
"""
576350

577351
print('Calculating TPU (multi-processing)...')
578-
p = pp.ProcessPool(4)
352+
p = pp.ProcessPool(2)
579353

580354
for _ in tqdm(p.imap(self.calc_tpu, sbet_las_generator), total=num_las, ascii=True):
581355
pass

‎cblue_configuration.json‎

Lines changed: 1 addition & 16 deletions
Original file line numberDiff line numberDiff line change
@@ -1,16 +1 @@
1-
{
2-
"directories": {
3-
"tpu": "D:/JeromesCreek/AllPoints",
4-
"sbet": "D:/JeromesCreek",
5-
"las": "D:/JeromesCreek"
6-
},
7-
"subaqueous_LUTs": {
8-
"RIEGL": "./lookup_tables/Riegl_look_up_fit_HG0995_1sig.csv",
9-
"ECKV": "./lookup_tables/ECKV_LUT_HG0995_1sig.csv"
10-
},
11-
"multiprocess": true,
12-
"number_cores": 4,
13-
"cBLUE_version": "v2.1.1",
14-
"sensor_model": "Riegl VQ-880-G",
15-
"water_surface_ellipsoid_height": 45.9
16-
}
1+
{"directories": {"tpu": "D:/JeromesCreek/tpu_dir", "sbet": "D:/JeromesCreek", "las": "D:/JeromesCreek"}, "subaqueous_LUTs": {"RIEGL": "./lookup_tables/Riegl_look_up_fit_HG0995_1sig.csv", "ECKV": "./lookup_tables/ECKV_LUT_HG0995_1sig.csv"}, "multiprocess": true, "number_cores": 4, "cBLUE_version": "v2.1.1", "sensor_model": "Riegl VQ-880-G", "water_surface_ellipsoid_height": 5.55}

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