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1 """
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2 Author: Timothy Tickle
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3 Description: Base class for ordination plots.
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4 """
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5
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6 #####################################################################################
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7 #Copyright (C) <2012>
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8 #
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9 #Permission is hereby granted, free of charge, to any person obtaining a copy of
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10 #this software and associated documentation files (the "Software"), to deal in the
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11 #Software without restriction, including without limitation the rights to use, copy,
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12 #modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
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13 #and to permit persons to whom the Software is furnished to do so, subject to
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14 #the following conditions:
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15 #
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16 #The above copyright notice and this permission notice shall be included in all copies
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17 #or substantial portions of the Software.
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18 #
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19 #THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
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20 #INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
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21 #PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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22 #HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
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23 #OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
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24 #SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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25 #####################################################################################
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26
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27 __author__ = "Timothy Tickle"
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28 __copyright__ = "Copyright 2013"
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29 __credits__ = ["Timothy Tickle"]
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30 __license__ = "MIT"
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31 __maintainer__ = "Timothy Tickle"
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32 __email__ = "ttickle@sph.harvard.edu"
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33 __status__ = "Development"
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34
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35 #External libraries
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36 import AbundanceTable
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37 from ConstantsFiguresBreadCrumbs import ConstantsFiguresBreadCrumbs
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38 import matplotlib.cm as cm
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39 from matplotlib import pyplot as plt
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40 from UtilityMath import UtilityMath
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41 from ValidateData import ValidateData
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42
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43 class Ordination:
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44 """
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45 Base class for ordination methods and plots.
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46 """
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47
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48 def __init__(self):
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49 # Rows = Samples
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50 self.dataMatrix = None
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51 self.isRawData = None
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52 self.lsIDs = []
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53 self.dataProcessed = None
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54
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55 #Happy path tested
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56 def loadData(self, xData, fIsRawData):
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57 """
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58 Loads data into the object (given a matrix or an abundance table)
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59 Data can be the Abundance Table to be converted to a distance matrix or a distance matrix
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60 If it is the AbundanceTable, indicate that it is rawData (tempIsRawData=True)
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61 If it is the distance matrix already generated indicate (tempIsRawData=False)
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62 and no conversion will occur in subsequent methods.
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63
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64 :params xData: AbundanceTable or Distance matrix . Taxa (columns) by samples (rows)(lists)
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65 :type: AbundanceTable or DistanceMatrix
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66 :param fIsRawData: Indicates if the xData is an AbudanceTable (True) or distance matrix (False; numpy array)
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67 :type: boolean
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68 :return boolean: indicator of success (True=Was able to load data)
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69 """
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70
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71 if fIsRawData:
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72 #Read in the file data to a numpy array.
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73 #Samples (column) by Taxa (rows)(lists) without the column
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74 data = xData.funcToArray()
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75 if data==None:
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76 print("Ordination:loadData::Error when converting AbundanceTable to Array, did not perform ordination.")
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77 return False
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78
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79 #Transpose data to be Taxa (columns) by samples (rows)(lists)
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80 data = UtilityMath.funcTransposeDataMatrix(data,fRemoveAdornments=False)
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81 if(ValidateData.funcIsFalse(data)):
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82 print("Ordination:loadData::Error when transposing data file, did not perform ordination.")
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83 return False
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84 else:
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85 self.dataMatrix=data
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86 self.isRawData=fIsRawData
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87 self.lsIDs=xData.funcGetMetadata(xData.funcGetIDMetadataName())
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88
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89 #Otherwise load the data directly as passed.
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90 else:
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91 self.dataMatrix=xData
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92 self.isRawData=fIsRawData
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93 return True
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94
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