| 1 | """ |
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| 2 | This is the base file reader class most file readers should inherit from. |
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| 3 | All generic functionality required for a file loader/reader is built into this |
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| 4 | class |
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| 5 | """ |
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| 6 | |
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| 7 | import os |
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| 8 | import sys |
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| 9 | import math |
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| 10 | import logging |
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| 11 | from abc import abstractmethod |
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| 12 | |
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| 13 | import numpy as np |
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| 14 | from .loader_exceptions import NoKnownLoaderException, FileContentsException,\ |
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| 15 | DataReaderException, DefaultReaderException |
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| 16 | from .data_info import Data1D, Data2D, DataInfo, plottable_1D, plottable_2D,\ |
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| 17 | combine_data_info_with_plottable |
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| 18 | from sas.sascalc.data_util.nxsunit import Converter |
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| 19 | |
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| 20 | logger = logging.getLogger(__name__) |
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| 21 | |
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| 22 | if sys.version_info[0] < 3: |
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| 23 | def decode(s): |
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| 24 | return s |
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| 25 | else: |
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| 26 | def decode(s): |
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| 27 | return s.decode() if isinstance(s, bytes) else s |
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| 28 | |
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| 29 | # Data 1D fields for iterative purposes |
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| 30 | FIELDS_1D = ('x', 'y', 'dx', 'dy', 'dxl', 'dxw') |
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| 31 | # Data 2D fields for iterative purposes |
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| 32 | FIELDS_2D = ('data', 'qx_data', 'qy_data', 'q_data', 'err_data', |
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| 33 | 'dqx_data', 'dqy_data', 'mask') |
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| 34 | DEPRECATION_MESSAGE = ("\rThe extension of this file suggests the data set migh" |
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| 35 | "t not be fully reduced. Support for the reader associat" |
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| 36 | "ed with this file type has been removed. An attempt to " |
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| 37 | "load the file was made, but, should it be successful, " |
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| 38 | "SasView cannot guarantee the accuracy of the data.") |
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| 39 | |
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| 40 | |
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| 41 | class FileReader(object): |
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| 42 | # String to describe the type of data this reader can load |
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| 43 | type_name = "ASCII" |
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| 44 | # Wildcards to display |
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| 45 | type = ["Text files (*.txt|*.TXT)"] |
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| 46 | # List of allowed extensions |
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| 47 | ext = ['.txt'] |
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| 48 | # Deprecated extensions |
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| 49 | deprecated_extensions = ['.asc', '.nxs'] |
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| 50 | # Bypass extension check and try to load anyway |
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| 51 | allow_all = False |
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| 52 | # Able to import the unit converter |
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| 53 | has_converter = True |
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| 54 | # Default value of zero |
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| 55 | _ZERO = 1e-16 |
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| 56 | |
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| 57 | def __init__(self): |
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| 58 | # List of Data1D and Data2D objects to be sent back to data_loader |
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| 59 | self.output = [] |
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| 60 | # Current plottable_(1D/2D) object being loaded in |
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| 61 | self.current_dataset = None |
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| 62 | # Current DataInfo object being loaded in |
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| 63 | self.current_datainfo = None |
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| 64 | # File path sent to reader |
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| 65 | self.filepath = None |
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| 66 | # Open file handle |
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| 67 | self.f_open = None |
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| 68 | |
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| 69 | def read(self, filepath): |
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| 70 | """ |
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| 71 | Basic file reader |
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| 72 | |
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| 73 | :param filepath: The full or relative path to a file to be loaded |
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| 74 | """ |
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| 75 | self.filepath = filepath |
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| 76 | if os.path.isfile(filepath): |
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| 77 | basename, extension = os.path.splitext(os.path.basename(filepath)) |
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| 78 | self.extension = extension.lower() |
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| 79 | # If the file type is not allowed, return nothing |
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| 80 | if self.extension in self.ext or self.allow_all: |
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| 81 | # Try to load the file, but raise an error if unable to. |
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| 82 | try: |
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| 83 | self.f_open = open(filepath, 'rb') |
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| 84 | self.get_file_contents() |
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| 85 | |
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| 86 | except DataReaderException as e: |
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| 87 | self.handle_error_message(e.message) |
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| 88 | except OSError as e: |
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| 89 | # If the file cannot be opened |
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| 90 | msg = "Unable to open file: {}\n".format(filepath) |
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| 91 | msg += e.message |
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| 92 | self.handle_error_message(msg) |
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| 93 | finally: |
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| 94 | # Close the file handle if it is open |
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| 95 | if not self.f_open.closed: |
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| 96 | self.f_open.close() |
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| 97 | if any(filepath.lower().endswith(ext) for ext in |
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| 98 | self.deprecated_extensions): |
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| 99 | self.handle_error_message(DEPRECATION_MESSAGE) |
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| 100 | if len(self.output) > 0: |
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| 101 | # Sort the data that's been loaded |
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| 102 | self.convert_data_units() |
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| 103 | self.sort_data() |
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| 104 | else: |
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| 105 | msg = "Unable to find file at: {}\n".format(filepath) |
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| 106 | msg += "Please check your file path and try again." |
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| 107 | self.handle_error_message(msg) |
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| 108 | |
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| 109 | # Return a list of parsed entries that data_loader can manage |
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| 110 | final_data = self.output |
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| 111 | self.reset_state() |
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| 112 | return final_data |
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| 113 | |
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| 114 | def reset_state(self): |
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| 115 | """ |
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| 116 | Resets the class state to a base case when loading a new data file so previous |
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| 117 | data files do not appear a second time |
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| 118 | """ |
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| 119 | self.current_datainfo = None |
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| 120 | self.current_dataset = None |
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| 121 | self.filepath = None |
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| 122 | self.ind = None |
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| 123 | self.output = [] |
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| 124 | |
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| 125 | def nextline(self): |
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| 126 | """ |
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| 127 | Returns the next line in the file as a string. |
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| 128 | """ |
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| 129 | #return self.f_open.readline() |
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| 130 | return decode(self.f_open.readline()) |
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| 131 | |
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| 132 | def nextlines(self): |
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| 133 | """ |
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| 134 | Returns the next line in the file as a string. |
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| 135 | """ |
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| 136 | for line in self.f_open: |
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| 137 | #yield line |
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| 138 | yield decode(line) |
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| 139 | |
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| 140 | def readall(self): |
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| 141 | """ |
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| 142 | Returns the entire file as a string. |
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| 143 | """ |
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| 144 | return decode(self.f_open.read()) |
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| 145 | |
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| 146 | def handle_error_message(self, msg): |
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| 147 | """ |
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| 148 | Generic error handler to add an error to the current datainfo to |
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| 149 | propagate the error up the error chain. |
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| 150 | :param msg: Error message |
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| 151 | """ |
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| 152 | if len(self.output) > 0: |
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| 153 | self.output[-1].errors.append(msg) |
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| 154 | elif isinstance(self.current_datainfo, DataInfo): |
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| 155 | self.current_datainfo.errors.append(msg) |
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| 156 | else: |
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| 157 | logger.warning(msg) |
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| 158 | raise NoKnownLoaderException(msg) |
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| 159 | |
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| 160 | def send_to_output(self): |
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| 161 | """ |
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| 162 | Helper that automatically combines the info and set and then appends it |
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| 163 | to output |
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| 164 | """ |
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| 165 | data_obj = combine_data_info_with_plottable(self.current_dataset, |
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| 166 | self.current_datainfo) |
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| 167 | self.output.append(data_obj) |
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| 168 | |
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| 169 | def sort_data(self): |
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| 170 | """ |
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| 171 | Sort 1D data along the X axis for consistency |
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| 172 | """ |
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| 173 | for data in self.output: |
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| 174 | if isinstance(data, Data1D): |
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| 175 | # Normalize the units for |
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| 176 | data.x_unit = self.format_unit(data.x_unit) |
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| 177 | data._xunit = data.x_unit |
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| 178 | data.y_unit = self.format_unit(data.y_unit) |
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| 179 | data._yunit = data.y_unit |
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| 180 | # Sort data by increasing x and remove 1st point |
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| 181 | ind = np.lexsort((data.y, data.x)) |
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| 182 | data.x = self._reorder_1d_array(data.x, ind) |
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| 183 | data.y = self._reorder_1d_array(data.y, ind) |
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| 184 | if data.dx is not None: |
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| 185 | if len(data.dx) == 0: |
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| 186 | data.dx = None |
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| 187 | continue |
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| 188 | data.dx = self._reorder_1d_array(data.dx, ind) |
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| 189 | if data.dxl is not None: |
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| 190 | data.dxl = self._reorder_1d_array(data.dxl, ind) |
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| 191 | if data.dxw is not None: |
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| 192 | data.dxw = self._reorder_1d_array(data.dxw, ind) |
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| 193 | if data.dy is not None: |
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| 194 | if len(data.dy) == 0: |
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| 195 | data.dy = None |
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| 196 | continue |
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| 197 | data.dy = self._reorder_1d_array(data.dy, ind) |
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| 198 | if data.lam is not None: |
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| 199 | data.lam = self._reorder_1d_array(data.lam, ind) |
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| 200 | if data.dlam is not None: |
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| 201 | data.dlam = self._reorder_1d_array(data.dlam, ind) |
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| 202 | data = self._remove_nans_in_data(data) |
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| 203 | if len(data.x) > 0: |
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| 204 | data.xmin = np.min(data.x) |
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| 205 | data.xmax = np.max(data.x) |
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| 206 | data.ymin = np.min(data.y) |
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| 207 | data.ymax = np.max(data.y) |
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| 208 | elif isinstance(data, Data2D): |
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| 209 | # Normalize the units for |
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| 210 | data.Q_unit = self.format_unit(data.Q_unit) |
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| 211 | data.I_unit = self.format_unit(data.I_unit) |
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| 212 | data._xunit = data.Q_unit |
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| 213 | data._yunit = data.Q_unit |
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| 214 | data._zunit = data.I_unit |
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| 215 | data.data = data.data.astype(np.float64) |
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| 216 | data.qx_data = data.qx_data.astype(np.float64) |
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| 217 | data.xmin = np.min(data.qx_data) |
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| 218 | data.xmax = np.max(data.qx_data) |
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| 219 | data.qy_data = data.qy_data.astype(np.float64) |
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| 220 | data.ymin = np.min(data.qy_data) |
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| 221 | data.ymax = np.max(data.qy_data) |
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| 222 | data.q_data = np.sqrt(data.qx_data * data.qx_data |
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| 223 | + data.qy_data * data.qy_data) |
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| 224 | if data.err_data is not None: |
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| 225 | data.err_data = data.err_data.astype(np.float64) |
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| 226 | if data.dqx_data is not None: |
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| 227 | data.dqx_data = data.dqx_data.astype(np.float64) |
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| 228 | if data.dqy_data is not None: |
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| 229 | data.dqy_data = data.dqy_data.astype(np.float64) |
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| 230 | if data.mask is not None: |
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| 231 | data.mask = data.mask.astype(dtype=bool) |
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| 232 | |
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| 233 | if len(data.data.shape) == 2: |
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| 234 | n_rows, n_cols = data.data.shape |
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| 235 | data.y_bins = data.qy_data[0::int(n_cols)] |
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| 236 | data.x_bins = data.qx_data[:int(n_cols)] |
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| 237 | data.data = data.data.flatten() |
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| 238 | data = self._remove_nans_in_data(data) |
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| 239 | if len(data.data) > 0: |
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| 240 | data.xmin = np.min(data.qx_data) |
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| 241 | data.xmax = np.max(data.qx_data) |
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| 242 | data.ymin = np.min(data.qy_data) |
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| 243 | data.ymax = np.max(data.qx_data) |
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| 244 | |
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| 245 | @staticmethod |
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| 246 | def _reorder_1d_array(array, ind): |
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| 247 | """ |
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| 248 | Reorders a 1D array based on the indices passed as ind |
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| 249 | :param array: Array to be reordered |
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| 250 | :param ind: Indices used to reorder array |
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| 251 | :return: reordered array |
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| 252 | """ |
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| 253 | array = np.asarray(array, dtype=np.float64) |
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| 254 | return array[ind] |
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| 255 | |
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| 256 | @staticmethod |
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| 257 | def _remove_nans_in_data(data): |
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| 258 | """ |
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| 259 | Remove data points where nan is loaded |
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| 260 | :param data: 1D or 2D data object |
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| 261 | :return: data with nan points removed |
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| 262 | """ |
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| 263 | if isinstance(data, Data1D): |
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| 264 | fields = FIELDS_1D |
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| 265 | elif isinstance(data, Data2D): |
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| 266 | fields = FIELDS_2D |
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| 267 | else: |
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| 268 | return data |
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| 269 | # Make array of good points - all others will be removed |
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| 270 | good = np.isfinite(getattr(data, fields[0])) |
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| 271 | for name in fields[1:]: |
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| 272 | array = getattr(data, name) |
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| 273 | if array is not None: |
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| 274 | # Update good points only if not already changed |
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| 275 | good &= np.isfinite(array) |
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| 276 | if not np.all(good): |
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| 277 | for name in fields: |
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| 278 | array = getattr(data, name) |
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| 279 | if array is not None: |
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| 280 | setattr(data, name, array[good]) |
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| 281 | return data |
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| 282 | |
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| 283 | @staticmethod |
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| 284 | def set_default_1d_units(data): |
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| 285 | """ |
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| 286 | Set the x and y axes to the default 1D units |
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| 287 | :param data: 1D data set |
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| 288 | :return: |
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| 289 | """ |
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| 290 | data.xaxis("\\rm{Q}", '1/A') |
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| 291 | data.yaxis("\\rm{Intensity}", "1/cm") |
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| 292 | return data |
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| 293 | |
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| 294 | @staticmethod |
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| 295 | def set_default_2d_units(data): |
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| 296 | """ |
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| 297 | Set the x and y axes to the default 2D units |
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| 298 | :param data: 2D data set |
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| 299 | :return: |
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| 300 | """ |
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| 301 | data.xaxis("\\rm{Q_{x}}", '1/A') |
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| 302 | data.yaxis("\\rm{Q_{y}}", '1/A') |
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| 303 | data.zaxis("\\rm{Intensity}", "1/cm") |
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| 304 | return data |
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| 305 | |
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| 306 | def convert_data_units(self, default_q_unit="1/A", default_i_unit="1/cm"): |
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| 307 | """ |
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| 308 | Converts al; data to the sasview default of units of A^{-1} for Q and |
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| 309 | cm^{-1} for I. |
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| 310 | :param default_q_unit: The default Q unit used by Sasview |
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| 311 | :param default_i_unit: The default I unit used by Sasview |
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| 312 | """ |
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| 313 | new_output = [] |
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| 314 | for data in self.output: |
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| 315 | if data.isSesans: |
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| 316 | new_output.append(data) |
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| 317 | continue |
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| 318 | file_x_unit = data._xunit |
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| 319 | data_conv_x = Converter(file_x_unit) |
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| 320 | file_y_unit = data._yunit |
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| 321 | data_conv_y = Converter(file_y_unit) |
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| 322 | if isinstance(data, Data1D): |
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| 323 | try: |
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| 324 | data.x = data_conv_x(data.x, units=default_q_unit) |
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| 325 | data._xunit = default_q_unit |
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| 326 | data.x_unit = default_q_unit |
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| 327 | if data.dx is not None: |
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| 328 | data.dx = data_conv_x(data.dx, units=default_q_unit) |
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| 329 | if data.dxl is not None: |
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| 330 | data.dxl = data_conv_x(data.dxl, units=default_q_unit) |
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| 331 | if data.dxw is not None: |
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| 332 | data.dxw = data_conv_x(data.dxw, units=default_q_unit) |
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| 333 | except KeyError: |
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| 334 | message = "Unable to convert Q units from {0} to 1/A." |
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| 335 | message.format(default_q_unit) |
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| 336 | data.errors.append(message) |
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| 337 | try: |
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| 338 | data.y = data_conv_y(data.y, units=default_i_unit) |
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| 339 | data._yunit = default_i_unit |
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| 340 | data.y_unit = default_i_unit |
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| 341 | if data.dy is not None: |
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| 342 | data.dy = data_conv_y(data.dy, units=default_i_unit) |
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| 343 | except KeyError: |
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| 344 | message = "Unable to convert I units from {0} to 1/cm." |
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| 345 | message.format(default_q_unit) |
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| 346 | data.errors.append(message) |
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| 347 | elif isinstance(data, Data2D): |
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| 348 | try: |
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| 349 | data.qx_data = data_conv_x(data.qx_data, |
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| 350 | units=default_q_unit) |
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| 351 | if data.dqx_data is not None: |
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| 352 | data.dqx_data = data_conv_x(data.dqx_data, |
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| 353 | units=default_q_unit) |
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| 354 | data.qy_data = data_conv_y(data.qy_data, |
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| 355 | units=default_q_unit) |
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| 356 | if data.dqy_data is not None: |
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| 357 | data.dqy_data = data_conv_y(data.dqy_data, |
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| 358 | units=default_q_unit) |
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| 359 | except KeyError: |
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| 360 | message = "Unable to convert Q units from {0} to 1/A." |
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| 361 | message.format(default_q_unit) |
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| 362 | data.errors.append(message) |
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| 363 | try: |
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| 364 | file_z_unit = data._zunit |
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| 365 | data_conv_z = Converter(file_z_unit) |
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| 366 | data.data = data_conv_z(data.data, units=default_i_unit) |
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| 367 | if data.err_data is not None: |
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| 368 | data.err_data = data_conv_z(data.err_data, |
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| 369 | units=default_i_unit) |
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| 370 | except KeyError: |
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| 371 | message = "Unable to convert I units from {0} to 1/cm." |
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| 372 | message.format(default_q_unit) |
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| 373 | data.errors.append(message) |
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| 374 | else: |
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| 375 | # TODO: Throw error of some sort... |
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| 376 | pass |
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| 377 | new_output.append(data) |
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| 378 | self.output = new_output |
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| 379 | |
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| 380 | def format_unit(self, unit=None): |
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| 381 | """ |
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| 382 | Format units a common way |
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| 383 | :param unit: |
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| 384 | :return: |
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| 385 | """ |
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| 386 | if unit: |
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| 387 | split = unit.split("/") |
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| 388 | if len(split) == 1: |
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| 389 | return unit |
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| 390 | elif split[0] == '1': |
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| 391 | return "{0}^".format(split[1]) + "{-1}" |
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| 392 | else: |
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| 393 | return "{0}*{1}^".format(split[0], split[1]) + "{-1}" |
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| 394 | |
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| 395 | def set_all_to_none(self): |
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| 396 | """ |
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| 397 | Set all mutable values to None for error handling purposes |
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| 398 | """ |
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| 399 | self.current_dataset = None |
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| 400 | self.current_datainfo = None |
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| 401 | self.output = [] |
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| 402 | |
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| 403 | def data_cleanup(self): |
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| 404 | """ |
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| 405 | Clean up the data sets and refresh everything |
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| 406 | :return: None |
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| 407 | """ |
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| 408 | self.remove_empty_q_values() |
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| 409 | self.send_to_output() # Combine datasets with DataInfo |
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| 410 | self.current_datainfo = DataInfo() # Reset DataInfo |
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| 411 | |
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| 412 | def remove_empty_q_values(self): |
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| 413 | """ |
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| 414 | Remove any point where Q == 0 |
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| 415 | """ |
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| 416 | if isinstance(self.current_dataset, plottable_1D): |
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| 417 | # Booleans for resolutions |
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| 418 | has_error_dx = self.current_dataset.dx is not None |
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| 419 | has_error_dxl = self.current_dataset.dxl is not None |
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| 420 | has_error_dxw = self.current_dataset.dxw is not None |
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| 421 | has_error_dy = self.current_dataset.dy is not None |
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| 422 | # Create arrays of zeros for non-existent resolutions |
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| 423 | if has_error_dxw and not has_error_dxl: |
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| 424 | array_size = self.current_dataset.dxw.size - 1 |
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| 425 | self.current_dataset.dxl = np.append(self.current_dataset.dxl, |
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| 426 | np.zeros([array_size])) |
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| 427 | has_error_dxl = True |
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| 428 | elif has_error_dxl and not has_error_dxw: |
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| 429 | array_size = self.current_dataset.dxl.size - 1 |
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| 430 | self.current_dataset.dxw = np.append(self.current_dataset.dxw, |
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| 431 | np.zeros([array_size])) |
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| 432 | has_error_dxw = True |
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| 433 | elif not has_error_dxl and not has_error_dxw and not has_error_dx: |
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| 434 | array_size = self.current_dataset.x.size - 1 |
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| 435 | self.current_dataset.dx = np.append(self.current_dataset.dx, |
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| 436 | np.zeros([array_size])) |
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| 437 | has_error_dx = True |
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| 438 | if not has_error_dy: |
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| 439 | array_size = self.current_dataset.y.size - 1 |
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| 440 | self.current_dataset.dy = np.append(self.current_dataset.dy, |
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| 441 | np.zeros([array_size])) |
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| 442 | has_error_dy = True |
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| 443 | |
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| 444 | # Remove points where q = 0 |
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| 445 | x = self.current_dataset.x |
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| 446 | self.current_dataset.x = self.current_dataset.x[x != 0] |
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| 447 | self.current_dataset.y = self.current_dataset.y[x != 0] |
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| 448 | if has_error_dy: |
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| 449 | self.current_dataset.dy = self.current_dataset.dy[x != 0] |
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| 450 | if has_error_dx: |
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| 451 | self.current_dataset.dx = self.current_dataset.dx[x != 0] |
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| 452 | if has_error_dxl: |
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| 453 | self.current_dataset.dxl = self.current_dataset.dxl[x != 0] |
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| 454 | if has_error_dxw: |
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| 455 | self.current_dataset.dxw = self.current_dataset.dxw[x != 0] |
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| 456 | elif isinstance(self.current_dataset, plottable_2D): |
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| 457 | has_error_dqx = self.current_dataset.dqx_data is not None |
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| 458 | has_error_dqy = self.current_dataset.dqy_data is not None |
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| 459 | has_error_dy = self.current_dataset.err_data is not None |
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| 460 | has_mask = self.current_dataset.mask is not None |
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| 461 | x = self.current_dataset.qx_data |
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| 462 | self.current_dataset.data = self.current_dataset.data[x != 0] |
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| 463 | self.current_dataset.qx_data = self.current_dataset.qx_data[x != 0] |
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| 464 | self.current_dataset.qy_data = self.current_dataset.qy_data[x != 0] |
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| 465 | self.current_dataset.q_data = np.sqrt( |
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| 466 | np.square(self.current_dataset.qx_data) + np.square( |
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| 467 | self.current_dataset.qy_data)) |
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| 468 | if has_error_dy: |
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| 469 | self.current_dataset.err_data = self.current_dataset.err_data[ |
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| 470 | x != 0] |
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| 471 | if has_error_dqx: |
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| 472 | self.current_dataset.dqx_data = self.current_dataset.dqx_data[ |
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| 473 | x != 0] |
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| 474 | if has_error_dqy: |
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| 475 | self.current_dataset.dqy_data = self.current_dataset.dqy_data[ |
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| 476 | x != 0] |
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| 477 | if has_mask: |
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| 478 | self.current_dataset.mask = self.current_dataset.mask[x != 0] |
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| 479 | |
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| 480 | def reset_data_list(self, no_lines=0): |
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| 481 | """ |
|---|
| 482 | Reset the plottable_1D object |
|---|
| 483 | """ |
|---|
| 484 | # Initialize data sets with arrays the maximum possible size |
|---|
| 485 | x = np.zeros(no_lines) |
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| 486 | y = np.zeros(no_lines) |
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| 487 | dx = np.zeros(no_lines) |
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| 488 | dy = np.zeros(no_lines) |
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| 489 | self.current_dataset = plottable_1D(x, y, dx, dy) |
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| 490 | |
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| 491 | @staticmethod |
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| 492 | def splitline(line): |
|---|
| 493 | """ |
|---|
| 494 | Splits a line into pieces based on common delimiters |
|---|
| 495 | :param line: A single line of text |
|---|
| 496 | :return: list of values |
|---|
| 497 | """ |
|---|
| 498 | # Initial try for CSV (split on ,) |
|---|
| 499 | toks = line.split(',') |
|---|
| 500 | # Now try SCSV (split on ;) |
|---|
| 501 | if len(toks) < 2: |
|---|
| 502 | toks = line.split(';') |
|---|
| 503 | # Now go for whitespace |
|---|
| 504 | if len(toks) < 2: |
|---|
| 505 | toks = line.split() |
|---|
| 506 | return toks |
|---|
| 507 | |
|---|
| 508 | @abstractmethod |
|---|
| 509 | def get_file_contents(self): |
|---|
| 510 | """ |
|---|
| 511 | Reader specific class to access the contents of the file |
|---|
| 512 | All reader classes that inherit from FileReader must implement |
|---|
| 513 | """ |
|---|
| 514 | pass |
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