def test_Defaults(self):
"""
Default tested: array_size = 32
"""
expected = tools.txt2np(filepath=EXPECTED_TXT_FP, array_size=32)
result = tools.txt2np(filepath=EXPECTED_TXT_FP)
expected_frames, _ = expected
frames, _ = result
self.assertTrue(np.array_equal(frames, expected_frames))
def test_array_size(self):
expected_frames_shape = (3, 16, 16)
expected_timestamps = [170.093, 170.218, 170.343]
result = tools.txt2np(filepath=EXPECTED_TXT_FP, array_size=16)
frames, timestamps = result
self.assertEqual(timestamps, expected_timestamps)
self.assertEqual(frames.shape, expected_frames_shape)
def test_Result(self):
expected_frames_shape = (3, 32, 32)
expected_timestamps = [170.093, 170.218, 170.343]
result = tools.txt2np(filepath=EXPECTED_TXT_FP, array_size=32)
frames, timestamps = result
self.assertEqual(timestamps, expected_timestamps)
self.assertEqual(frames.shape, expected_frames_shape)
expected_frames = np.load(EXPECTED_NP_FP)
self.assertTrue(np.array_equal(frames, expected_frames))
def txtFunctions(txt_fp,
gif=False,
csv=False,
bmp=False,
crop=-1,
overwrite=False,
**args):
def init(txt_fp, ext):
parent, txt_fn = os.path.split(txt_fp)
fn = txt_fn.split(".TXT")[0]
txt_fn = fn + ".TXT"
ext_fn = fn + ext
ext_fp = os.path.join(parent, ext_fn)
if os.path.exists(ext_fp):
if not overwrite:
print("{} already exists, aborting conversion".format(
ext_fn))
return None
print("Converting {} to {}".format(txt_fn, ext_fn))
return ext_fp
array, timestamps = tools.txt2np(txt_fp)
# NO CROPPING HERE! CSV SHOULD NOT BE CROPPED!
if csv:
csv_fp = init(txt_fp, ".csv")
if csv_fp:
tools.write_np2csv(csv_fp, array, timestamps)
cropped_array = tools.crop_center(array, crop, crop)
if gif:
gif_fp = init(txt_fp, ".gif")
if gif_fp:
pc = tools.np2pc(cropped_array)
tools.write_pc2gif(
pc,
gif_fp,
duration=tools.timestamps2frame_durations(timestamps))
if bmp:
parent, txt_fn = os.path.split(txt_fp)
fn = txt_fn.split(".TXT")[0]
dest = fn
if init(txt_fp, ""):
print("Extracting frames...")
tools.save_frames(tools.np2pc(cropped_array),
os.path.join(parent, dest))
return
def create(self):
"""
Convert *.TXT and write *.CSV files preserving directory structure
"""
dataset_path = os.path.join(self.destination_path, self.dataset_name)
if not os.path.exists(dataset_path):
os.mkdir(dataset_path)
for file_path in tqdm(self._text_files):
new_relative_path = os.path.relpath(
file_path, self._directory_path).replace(
'.{}'.format(self._file_extension),
'.{}'.format(self._new_file_extension))
new_file_path = os.path.join(self.destination_path,
self.dataset_name, new_relative_path)
if not os.path.exists(os.path.dirname(new_file_path)):
os.mkdir(os.path.dirname(new_file_path))
data = tools.txt2np(file_path)
tools.write_np2csv(new_file_path, *data)
def txtFunctions(txt_fp,
bmp=False,
histogram=False,
crop=-1,
overwrite=False,
bins=None,
mu=True,
sigma=True,
**args):
def init(txt_fp, ext, suffix=None):
parent, txt_fn = os.path.split(txt_fp)
if not suffix:
suffix = ""
fn = txt_fn.split(".TXT")[0] + suffix
txt_fn = fn + ".TXT"
ext_fn = fn + ext
ext_fp = os.path.join(parent, ext_fn)
if os.path.exists(ext_fp):
if not overwrite:
print("{} already exists, aborting conversion".format(
ext_fn))
return None
print("Converting {} to {}".format(txt_fn, ext_fn))
return ext_fp
array, timestamps = tools.txt2np(txt_fp)
cropped_array = tools.crop_center(array, crop, crop)
if bmp:
bmp_fp = init(txt_fp, ".bmp")
if bmp_fp:
pc_img = tools.np2pc(cropped_array)[0]
cv2.imwrite(bmp_fp, pc_img)
if histogram:
hist_fp = init(txt_fp, ".png", suffix="_histogram")
if hist_fp:
tools.save_temperature_histogram(array,
fp=hist_fp,
bins=bins,
mu=mu,
sigma=sigma)
return
def test_DTYPE(self):
expected_dtype = np.dtype(tools.DTYPE)
result = tools.txt2np(filepath=EXPECTED_TXT_FP)
frames, _ = result
self.assertEqual(frames.dtype, expected_dtype)