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 logging |
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9 | import numpy as np |
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10 | from abc import abstractmethod |
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11 | from loader_exceptions import NoKnownLoaderException, FileContentsException,\ |
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12 | DataReaderException, DefaultReaderException |
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13 | from data_info import Data1D, Data2D, DataInfo, plottable_1D, plottable_2D,\ |
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14 | combine_data_info_with_plottable |
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15 | |
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16 | logger = logging.getLogger(__name__) |
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17 | |
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18 | |
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19 | class FileReader(object): |
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20 | # List of Data1D and Data2D objects to be sent back to data_loader |
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21 | output = [] |
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22 | # Current plottable_(1D/2D) object being loaded in |
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23 | current_dataset = None |
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24 | # Current DataInfo object being loaded in |
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25 | current_datainfo = None |
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26 | # String to describe the type of data this reader can load |
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27 | type_name = "ASCII" |
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28 | # Wildcards to display |
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29 | type = ["Text files (*.txt|*.TXT)"] |
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30 | # List of allowed extensions |
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31 | ext = ['.txt'] |
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32 | # Bypass extension check and try to load anyway |
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33 | allow_all = False |
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34 | # Able to import the unit converter |
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35 | has_converter = True |
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36 | # Open file handle |
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37 | f_open = None |
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38 | # Default value of zero |
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39 | _ZERO = 1e-16 |
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40 | |
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41 | def read(self, filepath): |
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42 | """ |
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43 | Basic file reader |
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44 | |
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45 | :param filepath: The full or relative path to a file to be loaded |
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46 | """ |
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47 | if os.path.isfile(filepath): |
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48 | basename, extension = os.path.splitext(os.path.basename(filepath)) |
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49 | self.extension = extension.lower() |
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50 | # If the file type is not allowed, return nothing |
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51 | if self.extension in self.ext or self.allow_all: |
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52 | # Try to load the file, but raise an error if unable to. |
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53 | try: |
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54 | self.f_open = open(filepath, 'rb') |
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55 | self.get_file_contents() |
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56 | |
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57 | except DataReaderException as e: |
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58 | self.handle_error_message(e.message) |
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59 | except OSError as e: |
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60 | # If the file cannot be opened |
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61 | msg = "Unable to open file: {}\n".format(filepath) |
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62 | msg += e.message |
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63 | self.handle_error_message(msg) |
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64 | finally: |
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65 | # Close the file handle if it is open |
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66 | if not self.f_open.closed: |
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67 | self.f_open.close() |
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68 | if len(self.output) > 0: |
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69 | # Sort the data that's been loaded |
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70 | self.sort_one_d_data() |
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71 | self.sort_two_d_data() |
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72 | else: |
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73 | msg = "Unable to find file at: {}\n".format(filepath) |
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74 | msg += "Please check your file path and try again." |
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75 | self.handle_error_message(msg) |
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76 | |
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77 | # Return a list of parsed entries that data_loader can manage |
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78 | return self.output |
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79 | |
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80 | def handle_error_message(self, msg): |
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81 | """ |
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82 | Generic error handler to add an error to the current datainfo to |
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83 | propogate the error up the error chain. |
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84 | :param msg: Error message |
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85 | """ |
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86 | if isinstance(self.current_datainfo, DataInfo): |
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87 | self.current_datainfo.errors.append(msg) |
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88 | else: |
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89 | logger.warning(msg) |
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90 | |
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91 | def send_to_output(self): |
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92 | """ |
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93 | Helper that automatically combines the info and set and then appends it |
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94 | to output |
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95 | """ |
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96 | data_obj = combine_data_info_with_plottable(self.current_dataset, |
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97 | self.current_datainfo) |
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98 | self.output.append(data_obj) |
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99 | |
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100 | def sort_one_d_data(self): |
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101 | """ |
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102 | Sort 1D data along the X axis for consistency |
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103 | """ |
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104 | for data in self.output: |
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105 | if isinstance(data, Data1D): |
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106 | # Sort data by increasing x and remove 1st point |
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107 | ind = np.lexsort((data.y, data.x)) |
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108 | data.x = np.asarray([data.x[i] for i in ind]).astype(np.float64) |
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109 | data.y = np.asarray([data.y[i] for i in ind]).astype(np.float64) |
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110 | if data.dx is not None: |
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111 | data.dx = np.asarray([data.dx[i] for i in ind]).astype(np.float64) |
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112 | if data.dxl is not None: |
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113 | data.dxl = np.asarray([data.dxl[i] for i in ind]).astype(np.float64) |
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114 | if data.dxw is not None: |
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115 | data.dxw = np.asarray([data.dxw[i] for i in ind]).astype(np.float64) |
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116 | if data.dy is not None: |
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117 | data.dy = np.asarray([data.dy[i] for i in ind]).astype(np.float64) |
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118 | if data.lam is not None: |
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119 | data.lam = np.asarray([data.lam[i] for i in ind]).astype(np.float64) |
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120 | if data.dlam is not None: |
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121 | data.dlam = np.asarray([data.dlam[i] for i in ind]).astype(np.float64) |
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122 | if len(data.x > 0): |
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123 | data.xmin = np.min(data.x) |
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124 | data.xmax = np.max(data.x) |
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125 | data.ymin = np.min(data.y) |
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126 | data.ymax = np.max(data.y) |
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127 | |
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128 | def sort_two_d_data(self): |
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129 | for dataset in self.output: |
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130 | if isinstance(dataset, Data2D): |
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131 | dataset.data = dataset.data.astype(np.float64) |
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132 | dataset.qx_data = dataset.qx_data.astype(np.float64) |
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133 | dataset.xmin = np.min(dataset.qx_data) |
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134 | dataset.xmax = np.max(dataset.qx_data) |
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135 | dataset.qy_data = dataset.qy_data.astype(np.float64) |
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136 | dataset.ymin = np.min(dataset.qy_data) |
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137 | dataset.ymax = np.max(dataset.qy_data) |
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138 | dataset.q_data = np.sqrt(dataset.qx_data * dataset.qx_data |
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139 | + dataset.qy_data * dataset.qy_data) |
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140 | if dataset.err_data is not None: |
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141 | dataset.err_data = dataset.err_data.astype(np.float64) |
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142 | if dataset.dqx_data is not None: |
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143 | dataset.dqx_data = dataset.dqx_data.astype(np.float64) |
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144 | if dataset.dqy_data is not None: |
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145 | dataset.dqy_data = dataset.dqy_data.astype(np.float64) |
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146 | if dataset.mask is not None: |
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147 | dataset.mask = dataset.mask.astype(dtype=bool) |
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148 | |
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149 | if len(dataset.data.shape) == 2: |
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150 | n_rows, n_cols = dataset.data.shape |
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151 | dataset.y_bins = dataset.qy_data[0::int(n_cols)] |
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152 | dataset.x_bins = dataset.qx_data[:int(n_cols)] |
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153 | dataset.data = dataset.data.flatten() |
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154 | |
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155 | def set_all_to_none(self): |
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156 | """ |
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157 | Set all mutable values to None for error handling purposes |
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158 | """ |
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159 | self.current_dataset = None |
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160 | self.current_datainfo = None |
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161 | self.output = [] |
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162 | |
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163 | def remove_empty_q_values(self, has_error_dx=False, has_error_dy=False): |
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164 | """ |
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165 | Remove any point where Q == 0 |
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166 | """ |
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167 | x = self.current_dataset.x |
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168 | self.current_dataset.x = self.current_dataset.x[x != 0] |
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169 | self.current_dataset.y = self.current_dataset.y[x != 0] |
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170 | self.current_dataset.dy = self.current_dataset.dy[x != 0] if \ |
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171 | has_error_dy else np.zeros(len(self.current_dataset.y)) |
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172 | self.current_dataset.dx = self.current_dataset.dx[x != 0] if \ |
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173 | has_error_dx else np.zeros(len(self.current_dataset.x)) |
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174 | |
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175 | def reset_data_list(self, no_lines=0): |
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176 | """ |
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177 | Reset the plottable_1D object |
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178 | """ |
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179 | # Initialize data sets with arrays the maximum possible size |
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180 | x = np.zeros(no_lines) |
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181 | y = np.zeros(no_lines) |
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182 | dy = np.zeros(no_lines) |
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183 | dx = np.zeros(no_lines) |
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184 | self.current_dataset = plottable_1D(x, y, dx, dy) |
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185 | |
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186 | @staticmethod |
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187 | def splitline(line): |
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188 | """ |
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189 | Splits a line into pieces based on common delimeters |
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190 | :param line: A single line of text |
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191 | :return: list of values |
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192 | """ |
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193 | # Initial try for CSV (split on ,) |
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194 | toks = line.split(',') |
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195 | # Now try SCSV (split on ;) |
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196 | if len(toks) < 2: |
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197 | toks = line.split(';') |
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198 | # Now go for whitespace |
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199 | if len(toks) < 2: |
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200 | toks = line.split() |
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201 | return toks |
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202 | |
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203 | @abstractmethod |
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204 | def get_file_contents(self): |
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205 | """ |
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206 | Reader specific class to access the contents of the file |
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207 | All reader classes that inherit from FileReader must implement |
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208 | """ |
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209 | pass |
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