diff src/breadcrumbs/src/Ordination.py @ 0:2f4f6f08c8c4 draft

Uploaded

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/src/breadcrumbs/src/Ordination.py	Tue May 13 21:58:57 2014 -0400
@@ -0,0 +1,94 @@
+"""
+Author: Timothy Tickle
+Description: Base class for ordination plots.
+"""
+
+#####################################################################################
+#Copyright (C) <2012>
+#
+#Permission is hereby granted, free of charge, to any person obtaining a copy of
+#this software and associated documentation files (the "Software"), to deal in the
+#Software without restriction, including without limitation the rights to use, copy,
+#modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
+#and to permit persons to whom the Software is furnished to do so, subject to
+#the following conditions:
+#
+#The above copyright notice and this permission notice shall be included in all copies
+#or substantial portions of the Software.
+#
+#THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
+#INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A
+#PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+#HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
+#OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+#SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+#####################################################################################
+
+__author__ = "Timothy Tickle"
+__copyright__ = "Copyright 2013"
+__credits__ = ["Timothy Tickle"]
+__license__ = "MIT"
+__maintainer__ = "Timothy Tickle"
+__email__ = "[e-mail]"
+__status__ = "Development"
+
+#External libraries
+import AbundanceTable
+from ConstantsFiguresBreadCrumbs import ConstantsFiguresBreadCrumbs
+import matplotlib.cm as cm
+from matplotlib import pyplot as plt
+from UtilityMath import UtilityMath
+from ValidateData import ValidateData
+
+class Ordination:
+    """
+    Base class for ordination methods and plots.
+    """
+
+    def __init__(self):
+      # Rows = Samples
+      self.dataMatrix = None
+      self.isRawData = None
+      self.lsIDs = []
+      self.dataProcessed = None
+
+    #Happy path tested
+    def loadData(self, xData, fIsRawData):
+        """
+        Loads data into the object (given a matrix or an abundance table)
+        Data can be the Abundance Table to be converted to a distance matrix or a distance matrix
+        If it is the AbundanceTable, indicate that it is rawData (tempIsRawData=True)
+        If it is the distance matrix already generated indicate (tempIsRawData=False)
+        and no conversion will occur in subsequent methods.
+
+        :params xData: AbundanceTable or Distance matrix . Taxa (columns) by samples (rows)(lists)
+        :type: AbundanceTable or DistanceMatrix
+        :param fIsRawData: Indicates if the xData is an AbudanceTable (True) or distance matrix (False; numpy array)
+        :type: boolean
+        :return boolean: indicator of success (True=Was able to load data)
+        """
+
+        if fIsRawData:
+            #Read in the file data to a numpy array.
+            #Samples (column) by Taxa (rows)(lists) without the column
+            data = xData.funcToArray()
+            if data==None:
+                print("Ordination:loadData::Error when converting AbundanceTable to Array, did not perform ordination.")
+                return False
+
+            #Transpose data to be Taxa (columns) by samples (rows)(lists)
+            data = UtilityMath.funcTransposeDataMatrix(data,fRemoveAdornments=False)
+            if(ValidateData.funcIsFalse(data)):
+                print("Ordination:loadData::Error when transposing data file, did not perform ordination.")
+                return False
+            else:
+                self.dataMatrix=data
+                self.isRawData=fIsRawData
+                self.lsIDs=xData.funcGetMetadata(xData.funcGetIDMetadataName())
+
+        #Otherwise load the data directly as passed.
+        else:
+            self.dataMatrix=xData
+            self.isRawData=fIsRawData
+        return True
+