improve plots
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@ -10,8 +10,13 @@ import threading
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from sklearn.model_selection import train_test_split
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from teng_ml.util.transform import Multiply
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# groups: date, name, n_object, voltage, distance, index
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# re_filename = r"(\d{4}-\d{2}-\d{2})_([a-zA-Z_]+)_(\d{1,2}(?:\.\d*)?)V_(\d+(?:\.\d*)?)mm(\d+).csv"
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# for teng_1
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# re_filename = r"(\d{4}-\d{2}-\d{2})_([a-zA-Z_]+)_()(\d{1,2}(?:\.\d*)?)V_(\d+(?:\.\d*)?)mm(\d+).csv"
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# for teng_2
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re_filename = r"(\d{4}-\d{2}-\d{2})_([a-zA-Z0-9_]+)_(\d+)_(\d{1,2}(?:\.\d*)?)V_(\d+(?:\.\d*)?)mm(\d+).csv"
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class LabelConverter:
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@ -51,7 +56,7 @@ class Datasample:
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def __init__(self, date: str, label: str, n_object: str, voltage: str, distance: str, index: str, label_vec, datapath: str, init_data=False):
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self.date = date
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self.label = label
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self.n_object = int(n_object)
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self.n_object = 0 if n_object == "" else int(n_object)
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self.voltage = float(voltage)
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self.distance = float(distance)
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self.index = int(index)
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@ -86,6 +91,19 @@ class Dataset:
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"""
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self.transforms = transforms
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self.data = [] # (data, label)
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# NORMALIZE ALL DATA WITH THE SAME FACTOR
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# sup = 0
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# inf = 0
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# for sample in datasamples:
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# data = sample.get_data()
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# max_ = np.max(data[:,2])
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# min_ = np.min(data[:,2])
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# if max_ > sup: sup = max_
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# if min_ < inf: inf = min_
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# multiplier = 1 / max(sup, abs(inf))
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# self.transforms.append(Multiply(multiplier))
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for sample in datasamples:
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data = self.apply_transforms(sample.get_data())
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if split_function is None:
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@ -128,7 +146,7 @@ def get_datafiles(datadir, labels: LabelConverter, exclude_n_object=None, filter
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label = match.groups()[1]
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if label not in labels: continue
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sample_n_object = float(match.groups()[2])
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sample_n_object = 0 if match.groups()[2] == "" else int(match.groups()[2])
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if exclude_n_object and exclude_n_object == sample_n_object: continue
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sample_voltage = float(match.groups()[3])
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if filter_voltage and filter_voltage != sample_voltage: continue
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