def to_dynamic_productlevelexportsystem(self, verbose=True):
"""
Method to construct a Product Level Export System from the dataset
"""
#-Prepare Names-#
data = self.data.copy(deep=True) #Don't Alter Dataset, Should this be the default behaviour of the data attribute?
data = data.reset_index()
data.rename(columns={'eiso3c' : 'country', 'value' : 'export'}, inplace=True)
data.set_index(['year'], inplace=True)
#-Construct Object-#
from pyeconlab.trade.systems import DynamicProductLevelExportSystem
system = DynamicProductLevelExportSystem()
system.from_df(df=data)
return system
def test_simple_data(self):
"""
Test Simple Networks
"""
A = DynamicProductLevelExportSystem()
A.from_csv(self.fn, dtypes=['DataFrame', 'BiPartiteGraph'], verbose=True) # - Funtions Tested: from_csv, from_df
for year in [2000, 2001]:
assert_frame_equal(self.odata_yeardict[year], A[year].data.reset_index())
# print "Object A[2000] Network Nodes:" # These features will be migrated to DynamicProductLevelExportNetwork Class
# print A[2000].network.nodes()
# print "Object A[2000] Network Edges:"
# print A[2000].network.edges()
#-WORKING HERE-#
#-Itegrate these into the test-#
# ################
# #Test Functions#
# ################
# print "Test .data property"
# print A.data
# print "Test get_data() Extended method"
# print "Default Settings"
# print A.get_data()
# print "Specific Year Data"
# print A.get_data(year=2000)
# print "Long Panel of Data"
# print A.get_data(rtype='long')
# print "Wide Panel of Data"
# print A.get_data(rtype='wide')
# print "Panel of Data"
# print A.get_data(rtype='panel')
# print "Test as_cp_matrices()"
# A.as_cp_matrices(verbose=True)
# print A[2000].cp_matrix
# print A[2001].cp_matrix
# print "Testing .cp_matrix Property"
# print A.cp_matrix
# print "Testing rca_matrices()"
# A.complete_trade_network = True
# A.rca_matrices(verbose=True)
# print A[2000].rca
# print A[2001].rca
# print "Testing .rca Property"
# print A.rca
# print "Testing Mcp_matrices()"
# A.mcp_matrices(fillna=True, verbose=True)
# print A[2000].mcp
# print A[2001].mcp
# print "Testing .mcp Property"
# print A.mcp
# print "Testing proximity_matrices()"
# A.proximity_matrices(verbose=True)
# print A[2000].proximity
# print A[2001].proximity
# print "Testing .proximity Property"
# print A.proximity
# print "Testing proximity_matrices(matrix_type='asymmetric')"
# A.proximity_matrices(matrix_type='asymmetric', verbose=True)
# print A[2000].proximity
# print A[2001].proximity
# print "Testing .proximity Property"
# print A.proximity
# print "Testing Product Ubiquity Method"
# A.compute_ubiquity(verbose=True)
# print A[2000].ubiquity
# print A[2001].ubiquity
# print "Testing .ubiquity Property"
# print A.ubiquity
# print "Testing Country Diversity Method"
# A.compute_diversity(verbose=True)
# print A[2000].diversity
# print A[2001].diversity
# print "Testing .diversity Property"
# print A.diversity
# print "--------"
# print "TESTING COMPLETED SUCCESFULLY!"
# print "--------"
# sys.exit()
# #################################################
# ## Alternative Ways of Working with the Object ##
# #################################################
# print "\nObject B:"
# B = DynProductLevelExportSystem()
# # - Import Test Data - #
# B.from_csv(data, dtypes=['DataFrame'], verbose=True)
# B.construct_bipartite(verbose=True)
# print B[2000].network.nodes()
# if graphics: B[2000].draw_network()
# ####################################
# ### --- Test Object Networks --- ###
# ####################################
# # - Country Data from WDI - #
# W = wdi.WDI('WDI_Data.csv',source_ds='d1352f394ef8e7519797214f52ccd7cc', hash_file_sep=r' ', verbose=True)
# C = Countries() #Investigate a Pickle Here
# C.build_from_wdi(W)
# A = DynProductLevelExportSystem()
# # - Import Test Data - #
# # - Funtions Tested: from_csv, from_df
# A.from_csv(data, cntry_obj=C, dtypes=['DataFrame', 'BiPartiteGraph'], verbose=True)
# print "Object A:"
# print A
# print "Object A.data => Should be the Same due to __repr__"
# print A.ples
# print "Object A[2000] Data:"
# print A[2000].data
# print "Object A[2000] Network Nodes:"
# print A[2000].network.nodes()
# print "Object A[2000] Network Edges:"
# print A[2000].network.edges()
# ################
# #Test Functions#
# ################
# if graphics:
# print "\nDrawing Network"
# A[2000].draw_network()
# print "\nTest to_cp_matrices()"
# A.as_cp_matrices(verbose=True)
# print A[2000].cp_matrix
# print A[2001].cp_matrix
# print "\nTesting cp_matrices() Getter Method"
# print A.cp_matrices()
def test_simple_data(self):
"""
Test Simple Networks
"""
A = DynamicProductLevelExportSystem()
A.from_csv(self.fn,
dtypes=['DataFrame', 'BiPartiteGraph'],
verbose=True) # - Funtions Tested: from_csv, from_df
for year in [2000, 2001]:
assert_frame_equal(self.odata_yeardict[year],
A[year].data.reset_index())
# print "Object A[2000] Network Nodes:" # These features will be migrated to DynamicProductLevelExportNetwork Class
# print A[2000].network.nodes()
# print "Object A[2000] Network Edges:"
# print A[2000].network.edges()
#-WORKING HERE-#
#-Itegrate these into the test-#
# ################
# #Test Functions#
# ################
# print "Test .data property"
# print A.data
# print "Test get_data() Extended method"
# print "Default Settings"
# print A.get_data()
# print "Specific Year Data"
# print A.get_data(year=2000)
# print "Long Panel of Data"
# print A.get_data(rtype='long')
# print "Wide Panel of Data"
# print A.get_data(rtype='wide')
# print "Panel of Data"
# print A.get_data(rtype='panel')
# print "Test as_cp_matrices()"
# A.as_cp_matrices(verbose=True)
# print A[2000].cp_matrix
# print A[2001].cp_matrix
# print "Testing .cp_matrix Property"
# print A.cp_matrix
# print "Testing rca_matrices()"
# A.complete_trade_network = True
# A.rca_matrices(verbose=True)
# print A[2000].rca
# print A[2001].rca
# print "Testing .rca Property"
# print A.rca
# print "Testing Mcp_matrices()"
# A.mcp_matrices(fillna=True, verbose=True)
# print A[2000].mcp
# print A[2001].mcp
# print "Testing .mcp Property"
# print A.mcp
# print "Testing proximity_matrices()"
# A.proximity_matrices(verbose=True)
# print A[2000].proximity
# print A[2001].proximity
# print "Testing .proximity Property"
# print A.proximity
# print "Testing proximity_matrices(matrix_type='asymmetric')"
# A.proximity_matrices(matrix_type='asymmetric', verbose=True)
# print A[2000].proximity
# print A[2001].proximity
# print "Testing .proximity Property"
# print A.proximity
# print "Testing Product Ubiquity Method"
# A.compute_ubiquity(verbose=True)
# print A[2000].ubiquity
# print A[2001].ubiquity
# print "Testing .ubiquity Property"
# print A.ubiquity
# print "Testing Country Diversity Method"
# A.compute_diversity(verbose=True)
# print A[2000].diversity
# print A[2001].diversity
# print "Testing .diversity Property"
# print A.diversity
# print "--------"
# print "TESTING COMPLETED SUCCESFULLY!"
# print "--------"
# sys.exit()
# #################################################
# ## Alternative Ways of Working with the Object ##
# #################################################
# print "\nObject B:"
# B = DynProductLevelExportSystem()
# # - Import Test Data - #
# B.from_csv(data, dtypes=['DataFrame'], verbose=True)
# B.construct_bipartite(verbose=True)
# print B[2000].network.nodes()
# if graphics: B[2000].draw_network()
# ####################################
# ### --- Test Object Networks --- ###
# ####################################
# # - Country Data from WDI - #
# W = wdi.WDI('WDI_Data.csv',source_ds='d1352f394ef8e7519797214f52ccd7cc', hash_file_sep=r' ', verbose=True)
# C = Countries() #Investigate a Pickle Here
# C.build_from_wdi(W)
# A = DynProductLevelExportSystem()
# # - Import Test Data - #
# # - Funtions Tested: from_csv, from_df
# A.from_csv(data, cntry_obj=C, dtypes=['DataFrame', 'BiPartiteGraph'], verbose=True)
# print "Object A:"
# print A
# print "Object A.data => Should be the Same due to __repr__"
# print A.ples
# print "Object A[2000] Data:"
# print A[2000].data
# print "Object A[2000] Network Nodes:"
# print A[2000].network.nodes()
# print "Object A[2000] Network Edges:"
# print A[2000].network.edges()
# ################
# #Test Functions#
# ################
# if graphics:
# print "\nDrawing Network"
# A[2000].draw_network()
# print "\nTest to_cp_matrices()"
# A.as_cp_matrices(verbose=True)
# print A[2000].cp_matrix
# print A[2001].cp_matrix
# print "\nTesting cp_matrices() Getter Method"
# print A.cp_matrices()
