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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def sample(self, label):
 """ generate random cropping boxes according to parameters if satifactory crops generated, apply to ground-truth as well Parameters: label : numpy.array (n x 5 matrix) ground-truths Returns: list of (crop_box, label) tuples, if failed, return empty list [] """

        samples = []
        count = 0
        for trial in range(self.max_trials):
            if count >= self.max_sample:
                return samples
            scale = np.random.uniform(self.min_scale, self.max_scale)
            min_ratio = max(self.min_aspect_ratio, scale * scale)
            max_ratio = min(self.max_aspect_ratio, 1. / scale / scale)
            ratio = math.sqrt(np.random.uniform(min_ratio, max_ratio))
            width = scale * ratio
            height = scale / ratio
            left = np.random.uniform(0., 1 - width)
            top = np.random.uniform(0., 1 - height)
            rand_box = (left, top, left + width, top + height)
            valid_mask = np.where(label[:, 0] > -1)[0]
            gt = label[valid_mask, :]
            ious = self._check_satisfy(rand_box, gt)
            if ious is not None:
                # transform gt labels after crop, discard bad ones
                l, t, r, b = rand_box
                new_gt_boxes = []
                new_width = r - l
                new_height = b - t
                for i in range(valid_mask.size):
                    if ious[i] > 0:
                        xmin = max(0., (gt[i, 1] - l) / new_width)
                        ymin = max(0., (gt[i, 2] - t) / new_height)
                        xmax = min(1., (gt[i, 3] - l) / new_width)
                        ymax = min(1., (gt[i, 4] - t) / new_height)
                        new_gt_boxes.append([gt[i, 0], xmin, ymin, xmax, ymax])
                if not new_gt_boxes:
                    continue
                new_gt_boxes = np.array(new_gt_boxes)
                label = np.lib.pad(new_gt_boxes,
                    ((0, label.shape[0]-new_gt_boxes.shape[0]), (0,0)), \
                    'constant', constant_values=(-1, -1))
                samples.append((rand_box, label))
                count += 1
        return samples