"""NEO nodes implementation in ngclib repository""" from pathlib import Path import numpy as np from codecs import encode def _cmap_hex_to_rgb(hex_list): res = [] for hex_data in hex_list: r = int(hex_data[1: 3], 16) g = int(hex_data[3: 5], 16) b = int(hex_data[5: 7], 16) res.append([r, g, b]) return np.array(res) def _act_to_cmap(act_file: Path) -> np.ndarray: """converts the .act file to a matplotlib cmap representation""" with open(act_file, "rb") as act: raw_data = act.read() # Read binary data hex_data = encode(raw_data, "hex") # Convert it to hexadecimal values total_colors_count = int(hex_data[-7:-4], 16) # Get last 3 digits to get number of colors total total_colors_count = 256 # Decode colors from hex to string and split it by 6 (because colors are #1c1c1c) colors = [hex_data[i: i + 6].decode() for i in range(0, total_colors_count * 6, 6)] # Add # to each item and filter empty items if there is a corrupted total_colors_count bit hex_colors = [f"#{i}" for i in colors if len(i)] rgb_colors = _cmap_hex_to_rgb(hex_colors) return rgb_colors class NEONode: """NEO nodes implementation in ngclib repository""" def __init__(self, node_type: str, name: str): # all neo nodes have 1 dimension. valid_node_types = ["AerosolOpticalDepth", "Albedo", "CarbonMonoxide", "Chlorophyll", "CloudFraction", "CloudOpticalThickness", "CloudParticleRadius", "CloudWaterContent", "Fire", "LeafAreaIndex", "NetRadiation", "NitrogenDioxide", "OutgoingLongwaveRadiation", "Ozone", "ReflectedShortwaveRadiation", "SeaSurfaceTemperature", "SnowCover", "SolarInsolation", "Temperature", "TemperatureAnomaly", "Vegetation", "WaterVapor"] assert node_type in valid_node_types, f"Node type '{node_type}' not in {valid_node_types}" self.node_type = node_type self.name = name self.cmap = _act_to_cmap(Path(__file__).absolute().parent / "cmaps" / f"{self.node_type}.act") def load_from_disk(self, x: np.ndarray) -> np.ndarray: y: np.ndarray = np.float32(x) if y.shape[0] == 1: # pylint: disable=unsubscriptable-object y = y[0] # pylint: disable=unsubscriptable-object if len(y.shape) == 2: y = np.expand_dims(y, axis=-1) y[np.isnan(y)] = 0 return y.astype(np.float32) def save_to_disk(self, x: np.ndarray) -> np.ndarray: return x.clip(0, 1) def plot_fn(self, x: np.ndarray | None) -> np.ndarray | None: if x is None: return x y = np.clip(x, 0, 1) y = y * 255 y[y == 0] = 255 y = y.astype(np.uint).squeeze() y_rgb = self.cmap[y].astype(np.uint8) return y_rgb def __repr__(self): return self.name def __str__(self): return f"NEONode({self.name})"