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| 1 | +# Copyright Iris contributors |
| 2 | +# |
| 3 | +# This file is part of Iris and is released under the BSD license. |
| 4 | +# See LICENSE in the root of the repository for full licensing details. |
| 5 | +"""Module providing to netcdf datasets with automatic character encoding. |
| 6 | +
|
| 7 | +The requirement is to convert numpy fixed-width unicode arrays on writing to a variable |
| 8 | +which is declared as a byte (character) array with a fixed-length string dimension. |
| 9 | +
|
| 10 | +Numpy unicode string arrays are ones with dtypes of the form "U<character-width>". |
| 11 | +Numpy character variables have the dtype "S1", and map to a fixed-length "string |
| 12 | +dimension". |
| 13 | +
|
| 14 | +In principle, netCDF4 already performs these translations, but in practice current |
| 15 | +releases are not functional for anything other than "ascii" encoding -- including UTF-8, |
| 16 | +which is the most obvious and desirable "general" solution. |
| 17 | +
|
| 18 | +There is also the question of whether we should like to implement UTF-8 as our default. |
| 19 | +Current discussions on this are inconclusive and neither CF conventions nor the NetCDF |
| 20 | +User Guide are definite on what possible values of "_Encoding" are, or what the effective |
| 21 | +default is, even though they do both mention the "_Encoding" attribute as a potential |
| 22 | +way to handle the issue. |
| 23 | +
|
| 24 | +Because of this, we interpret as follows: |
| 25 | + * in the absence of an "_Encoding" attribute, we will attempt to decode bytes as UTF-8 |
| 26 | + * when writing string data, in the absence of an "_Encoding" attribute (on the Iris |
| 27 | + cube or coord object), we will attempt to encode data with "ascii" : If this succeeds, |
| 28 | + we will save as is (with no "_Encoding" attribute), but if it fails we will encode |
| 29 | + as UTF-8 **and** add an "_Encoding='UTF-8'" attribute. |
| 30 | +
|
| 31 | +Where an "_Encoding" attribute is provided to Iris, we will honour it where possible, |
| 32 | +identifying with "codecs.lookup" : This means we support the encodings in the Python |
| 33 | +Standard Library, and name aliases which it recognises. |
| 34 | +
|
| 35 | +See: |
| 36 | +
|
| 37 | +* known problems https://github.com/Unidata/netcdf4-python/issues/1440 |
| 38 | +* suggestions for how this "ought" to work, discussed in the netcdf-c library |
| 39 | + * https://github.com/Unidata/netcdf-c/issues/402 |
| 40 | +
|
| 41 | +""" |
| 42 | + |
| 43 | +import codecs |
| 44 | + |
| 45 | +import numpy as np |
| 46 | + |
| 47 | +from iris.fileformats.netcdf._thread_safe_nc import DatasetWrapper, VariableWrapper |
| 48 | + |
| 49 | + |
| 50 | +def decode_bytesarray_to_stringarray( |
| 51 | + byte_array, encoding="utf-8", string_width: int | None = None |
| 52 | +): |
| 53 | + """Convert an array of bytes to an array of strings, with one less dimension. |
| 54 | +
|
| 55 | + N.B. for now at least, we assume the string dim is **always the last one**. |
| 56 | + If 'string_width' is not given, it is set to the final dimension of 'byte_array'. |
| 57 | + """ |
| 58 | + bytes_shape = byte_array.shape |
| 59 | + var_shape = bytes_shape[:-1] |
| 60 | + if string_width is None: |
| 61 | + string_width = bytes_shape[-1] |
| 62 | + string_dtype = f"U{string_width}" |
| 63 | + result = np.empty(var_shape, dtype=string_dtype) |
| 64 | + for ndindex in np.ndindex(var_shape): |
| 65 | + element_bytes = byte_array[ndindex] |
| 66 | + bytes = b"".join([b if b else b"\0" for b in element_bytes]) |
| 67 | + string = bytes.decode(encoding) |
| 68 | + result[ndindex] = string |
| 69 | + return result |
| 70 | + |
| 71 | + |
| 72 | +def encode_stringarray_as_bytearray( |
| 73 | + data: np.ndarray, encoding=None, string_dimension_length: int | None = None |
| 74 | +) -> np.ndarray: |
| 75 | + """Encode strings as bytearray. |
| 76 | +
|
| 77 | + Note: if 'string_dimension_length' is not given (None), it is set to the longest |
| 78 | + encoded bytes element. If 'string_dimension_length' is specified, the last array |
| 79 | + dimension is set to this and content strings are truncated or extended as required. |
| 80 | + """ |
| 81 | + element_shape = data.shape |
| 82 | + max_length = 1 # this is a MINIMUM - i.e. not zero! |
| 83 | + data_elements = np.zeros(element_shape, dtype=object) |
| 84 | + for index in np.ndindex(element_shape): |
| 85 | + data_element = data[index].encode(encoding=encoding) |
| 86 | + element_length = len(data_element) |
| 87 | + data_elements[index] = data_element |
| 88 | + if element_length > max_length: |
| 89 | + max_length = element_length |
| 90 | + |
| 91 | + if string_dimension_length is None: |
| 92 | + string_dimension_length = max_length |
| 93 | + |
| 94 | + # We already encoded all the strings, but stored them in an object-array as |
| 95 | + # we didn't yet know the fixed byte-length to convert to. |
| 96 | + # Now convert to a fixed-width byte array with an extra string-length dimension |
| 97 | + result = np.zeros(element_shape + (string_dimension_length,), dtype="S1") |
| 98 | + right_pad = b"\0" * string_dimension_length |
| 99 | + for index in np.ndindex(element_shape): |
| 100 | + bytes = data_elements[index] |
| 101 | + bytes = (bytes + right_pad)[:string_dimension_length] |
| 102 | + result[index] = [bytes[i : i + 1] for i in range(string_dimension_length)] |
| 103 | + |
| 104 | + return result |
| 105 | + |
| 106 | + |
| 107 | +class EncodedVariable(VariableWrapper): |
| 108 | + """A variable wrapper that translates variable data according to byte encodings.""" |
| 109 | + |
| 110 | + def __getitem__(self, keys): |
| 111 | + if self.is_chardata(): |
| 112 | + super().set_auto_chartostring(False) |
| 113 | + |
| 114 | + data = super().__getitem__(keys) |
| 115 | + |
| 116 | + if self.is_chardata(): |
| 117 | + encoding = self.get_byte_encoding() |
| 118 | + strlen = self.get_string_length() |
| 119 | + data = decode_bytesarray_to_stringarray(data, encoding, strlen) |
| 120 | + |
| 121 | + return data |
| 122 | + |
| 123 | + def __setitem__(self, keys, data): |
| 124 | + if self.is_chardata(): |
| 125 | + encoding = self.get_byte_encoding() |
| 126 | + strlen = self.get_string_length() |
| 127 | + data = encode_stringarray_as_bytearray(data, encoding, strlen) |
| 128 | + super().set_auto_chartostring(False) |
| 129 | + |
| 130 | + super().__setitem__(keys, data) |
| 131 | + |
| 132 | + def is_chardata(self): |
| 133 | + return np.issubdtype(self.dtype, np.bytes_) |
| 134 | + |
| 135 | + def get_encoding(self): |
| 136 | + """Get the effective byte encoding to be used for this variable.""" |
| 137 | + # utf-8 is a reasonable "safe" default, equivalent to 'ascii' for ascii data |
| 138 | + default_encoding = "utf-8" |
| 139 | + encoding = getattr(self, "_Encoding", None) |
| 140 | + if encoding is None: |
| 141 | + encoding = default_encoding |
| 142 | + else: |
| 143 | + try: |
| 144 | + # Accept + normalise naming of encodings |
| 145 | + encoding = codecs.lookup(encoding).name |
| 146 | + # NOTE: if encoding does not suit data, errors can occur. |
| 147 | + # For example, _Encoding = "ascii", with non-ascii content. |
| 148 | + except LookupError: |
| 149 | + # Replace some invalid setting with "safe"(ish) fallback. |
| 150 | + encoding = default_encoding |
| 151 | + |
| 152 | + def get_string_length(self): |
| 153 | + """Return the string-length defined for this variable (or None).""" |
| 154 | + return getattr(self, "iris_string_length", None) |
| 155 | + |
| 156 | + |
| 157 | +class EncodedDataset(DatasetWrapper): |
| 158 | + """A specialised DatasetWrapper whose variables perform byte encodings.""" |
| 159 | + |
| 160 | + VAR_WRAPPER_CLS = EncodedVariable |
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