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import numpy as np
from igor2.packed import load as loadpxp
from helper import data_dir
def tostr(data):
if isinstance(data, bytes):
data = data.decode("utf-8")
return data
def test_pxp():
data = loadpxp(data_dir / 'polar-graphs-demo.pxp')
records = data[0]
assert len(records) == 51
assert records[30].variables == {'version': 1,
'variables': {
'var_header': {'numSysVars': 21,
'numUserVars': 0,
'numUserStrs': 0},
'sysVars': {'K0': 0.0,
'K1': 0.0,
'K2': 0.0,
'K3': 0.0,
'K4': 0.0,
'K5': 0.0,
'K6': 0.0,
'K7': 0.0,
'K8': 0.0,
'K9': 0.0,
'K10': 0.0,
'K11': 0.0,
'K12': 0.0,
'K13': 0.0,
'K14': 0.0,
'K15': 0.0,
'K16': 0.0,
'K17': 0.0,
'K18': 0.0,
'K19': 0.0,
'K20': 128.0},
'userVars': {},
'userStrs': {}}}
wave = data[1]["root"]
wkeys = [tostr(st) for st in wave.keys()]
assert sorted(wkeys) == sorted(
['K0', 'K1', 'K2', 'K3', 'K4', 'K5', 'K6', 'K7', 'K8', 'K9', 'K10',
'K11', 'K12', 'K13', 'K14', 'K15', 'K16', 'K17', 'K18', 'K19', 'K20',
'radiusData', 'angleData', 'W_plrX5', 'W_plrY5', 'angleQ1',
'radiusQ1', 'W_plrX6', 'W_plrY6', 'Packages']
)
assert np.allclose(records[32].wave["wave"]["wData"], np.array(
[0.3, 0.5448544, 0.77480197, 0.9758435, 1.1357394, 1.2447554,
1.2962544, 1.287101, 1.2178528, 1.0927255, 0.91933674,
0.7082426, 0.47229454, 0.22585714, -0.01606643,
-0.23874778, -0.42862982, -0.574153, -0.6664573, -0.6999235,
-0.6725141, -0.5858976, -0.44534767, -0.25942117, -0.03943586,
0.20121357, 0.44787762, 0.6855388, 0.8997279, 1.0774051,
1.2077546, 1.2828392, 1.2980883, 1.2525737, 1.1490659,
0.99386656, 0.7964253, 0.5687607, 0.32473388, 0.07920124,
-0.15288824, -0.35740662, -0.5219018, -0.636359, -0.69381076,
-0.69075894, -0.62739, -0.5075599, -0.3385666, -0.13069656,
0.10339352, 0.34945396, 0.5925036, 0.8177455, 1.0114669,
1.1618733, 1.2598093, 1.2993116, 1.277976, 1.1971004,
1.061609, 0.8797508, 0.6625979, 0.4233691, 0.17663053,
-0.06259823, -0.2797519, -0.46160996, -0.597101, -0.6779761,
-0.6993116, -0.6598092, -0.56187314, -0.41146588, -0.21774435,
0.00749773, 0.25054744, 0.49660596, 0.7306987, 0.9385669,
1.1075606, 1.2273898, 1.2907591, 1.2938106, 1.2363585,
1.1219027, 0.95740634, 0.7528879, 0.5207975, 0.2752648,
0.03123802, -0.19642642, -0.39386547, -0.54906607, -0.6525743,
-0.6980884, -0.682839, -0.607754, -0.47740453, -0.29972947,
-0.08553842, 0.15212469, 0.39878684, 0.6394367, 0.85942155,
1.0453486, 1.1858985, 1.2725141, 1.2999234, 1.2664578,
1.1741526, 1.0286293, 0.83874667, 0.6160649, 0.37414294,
0.12770344, -0.1082412, -0.3193372, -0.49272597, -0.6178533,
-0.6871013, -0.6962544, -0.6447547, -0.5357403, -0.37584305,
-0.17479956, 0.05514668, 0.30000135],
dtype=np.float32))
assert np.allclose(records[33].wave["wave"]["wData"], np.array([
0., 0.0494739, 0.0989478, 0.1484217, 0.1978956,
0.24736951, 0.29684341, 0.34631732, 0.3957912, 0.44526511,
0.49473903, 0.54421294, 0.59368682, 0.6431607, 0.69263464,
0.74210852, 0.79158241, 0.84105635, 0.89053023, 0.94000411,
0.98947805, 1.03895199, 1.08842587, 1.13789964, 1.18737364,
1.23684752, 1.2863214, 1.3357954, 1.38526928, 1.43474305,
1.48421705, 1.53369093, 1.58316481, 1.63263881, 1.68211269,
1.73158658, 1.78106046, 1.83053434, 1.88000822, 1.92948222,
1.9789561, 2.02842999, 2.07790399, 2.12737775, 2.17685175,
2.22632551, 2.27579927, 2.32527351, 2.37474728, 2.42422128,
2.47369504, 2.52316904, 2.5726428, 2.6221168, 2.67159081,
2.72106457, 2.77053857, 2.82001233, 2.86948609, 2.91896009,
2.9684341, 3.0179081, 3.06738186, 3.11685586, 3.16632962,
3.21580338, 3.26527762, 3.31475139, 3.36422539, 3.41369915,
3.46317315, 3.51264691, 3.56212091, 3.61159492, 3.66106868,
3.71054268, 3.76001644, 3.8094902, 3.85896444, 3.90843821,
3.95791221, 4.00738621, 4.05685997, 4.10633373, 4.15580797,
4.20528126, 4.2547555, 4.30422926, 4.3537035, 4.40317726,
4.45265102, 4.50212526, 4.55159855, 4.60107279, 4.65054703,
4.70002079, 4.74949455, 4.79896832, 4.84844255, 4.89791584,
4.94739008, 4.99686432, 5.04633808, 5.09581184, 5.14528561,
5.19475985, 5.24423361, 5.29370737, 5.34318161, 5.3926549,
5.44212914, 5.4916029, 5.54107714, 5.5905509, 5.64002466,
5.6894989, 5.73897219, 5.78844643, 5.83792019, 5.88739443,
5.93686819, 5.98634195, 6.03581619, 6.08528948, 6.13476372,
6.18423796, 6.23371172, 6.28318548], dtype=np.float32))
assert np.allclose(records[39].wave["wave"]["wData"], np.array([
8.19404411, 8.88563347, 9.70543861, 10.17177773,
10.11173058, 9.73756695, 9.25513077, 8.8788929,
9.16085339, 10.56489944, 12.75579453, 14.90572262,
16.46352959, 17.33401871, 17.68511391, 17.74635315,
17.70048141, 17.79942513, 18.36241531, 19.38741684,
20.41767311, 21.02259827, 21.09260368, 20.4905529,
18.95538521, 16.9299469, 15.94969368, 17.14490509,
19.78741264, 22.33615875, 23.96352196, 24.04369545,
21.92454147, 18.79150391, 17.77407646, 20.32803917,
24.37140465, 27.24079132, 28.40307808, 28.67787933,
28.70550728, 28.50283432, 27.68538666, 26.36607552,
25.73583984, 26.78374672, 28.8236084, 30.36226463,
30.91939545, 31.22146797, 31.97431755, 32.95656204,
33.4611969, 33.23248672, 32.3250885, 30.64473915,
28.72983551, 28.05199242, 29.29024887, 31.3501091,
32.7331543, 32.87995529, 32.28799438, 31.99738503],
dtype=np.float32))
def test_pxt():
data = loadpxp(data_dir / 'packed-byteorder.pxt', initial_byte_order='>')
records = data[0]
assert len(records) == 2
assert records[0].variables == {'version': 2,
'variables': {
'var_header': {'numSysVars': 0,
'numUserVars': 0,
'numUserStrs': 0,
'numDependentVars': 0,
'numDependentStrs': 0},
'sysVars': {},
'userVars': {},
'userStrs': {},
'dependentVars': [],
'dependentStrs': []}}
assert np.allclose(records[1].wave['wave']["wData"][:30, 0], np.array(
[14603., 13701., 14907., 13795., 14339., 14942., 14984., 14261.,
12647., 14242., 14470., 13913., 14158., 14754., 14462., 14346.,
14219., 13467., 13595., 14331., 13960., 12934., 12897., 13557.,
13105., 12797., 13234., 13053., 13455., 12825.], dtype='>f8'))
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