def adjacency_rcm_ordered(data_matrix, threshold, countries, file_prefix, ordered=True):
'''
r = [1 2 3 4 5 6 7 8 9 10]
allowedR = [1 2 3 4 5 6]
orderedVector = {'Argentina', 'Brazil', 'Fm USSR', 'Peru', 'Libya', 'Israel', 'UK', 'USA', 'Denmark', 'Portugal', 'Norway', 'Sweden'};
filteredLabels = {};
filteredR = []
r_size = size(r)
r_size = r_size(2)
filteredRIndex = 1
for i=1:r_size
if ismember(r(i), allowedR)
filteredR = [filteredR r(i)]
filteredLabels{filteredRIndex} = char(orderedVector(r(i)));
filteredRIndex = filteredRIndex + 1
end
end
'''
assert len(data_matrix) == len(data_matrix[0])
all_countries = countries[0]
allowed_countries = countries[1]
lines = []
lines.append(matrix_py_matlab_with_name('c0', transform_pn_to_01(data_matrix, threshold)))
lines.append(matrix_py_matlab_with_name('datamatrix', data_matrix))
lines.append("r = symrcm(c0);")
lines.append(
"allowedR = %s;" % (str([all_countries.index(country) + 1 for country in allowed_countries]).replace(",", "")))
lines.append("countriesVectorRow={%s};" % (str(all_countries)[1:-1]))
lines.append("filteredLabels = {};")
lines.append("filteredR = []")
lines.append("r_size = size(r)")
lines.append("r_size = r_size(2)")
lines.append("filteredRIndex = 1")
lines.append("for i=1:r_size")
lines.append("\tif ismember(r(i), allowedR)")
lines.append("\t\tfilteredR = [filteredR r(i)]")
lines.append("\t\tfilteredLabels{filteredRIndex} = char(countriesVectorRow(r(i)));")
lines.append("\t\tfilteredRIndex = filteredRIndex + 1")
lines.append("\tend")
lines.append("end")
lines.append("x=redgreencmap(200);")
vectorName = 'filteredLabels' if ordered else 'countriesVectorRow'
lines.append(
"hm = HeatMap(datamatrix%s,'RowLabels',%s,'ColumnLabels',%s, 'Colormap', horzcat(horzcat(x(:,2),x(:,1)),x(:,3)));"
% ('(filteredR,filteredR)' if ordered else '', vectorName, vectorName)
)
lines.append("plot(hm);")
lines.append(
"saveas(gcf,'%s-%d-%s','png');" % (file_prefix, threshold * 100, 'ordered' if ordered else 'unordered'))
lines.append("close all force;")
return lines
def write_matlab_code_for_corrmatrix(data, years, definition, def_args, file_prefix,
countries=DEFAULT_COUNTRIES_LIST,
country_study=False):
for year in years:
corrcoef_mat = corrcoef(adjacency_matrix(data, definition, def_args, year, countries))
print matrix_py_matlab_with_name('corrmatrix%d' % year, corrcoef_mat, country_study)
print "corrmatrix=[%s]" % (';'.join(['corrmatrix%d' % year for year in years]))
print list_as_matlab_vector('countriesVectorColumn', countries)
if country_study:
print "countriesVectorRow={%s};" % (str(concat_countries([countries[0]], years))[1:-1])
else:
print "countriesVectorRow={%s};" % (str(concat_countries(countries, years))[1:-1])
print "x=redgreencmap(200);"
print "HeatMap(corrmatrix,'RowLabels',countriesVectorRow,'ColumnLabels',countriesVectorColumn, 'Colormap', horzcat(horzcat(x(:,2),x(:,1)),x(:,3)));"
print "saveas(gcf,'%s','png');" % (file_prefix)
def matlab_code_for_rcm_ordered_corr_coef_for_export_volume_matrix(data, normalize_row_or_column):
f = open(OUT_DIR.RCM_MATRIC + 'iraniraqexport.m', 'w')
all_countries = DEFAULT_COUNTRIES_LIST
allowed_countries = iran_iraq_countries
# all_countries = ['USA', 'UK', 'Australia', 'Greece']
# allowed_countries = ['Australia', 'Greece']
for year in data.all_years:
pn_matrix = export_volume_matrix(data, year, all_countries, normalize_row_or_column)
f.write(matrix_py_matlab_with_name('exportvolume', pn_matrix))
data_matrix = corrcoef(pn_matrix)
for threshold in [0]:
for line in adjacency_rcm_ordered(data_matrix, threshold, [all_countries, allowed_countries],
'%s' % (year)):
f.write("%s\n" % line)
f.close()
def matlab_code_for_rcm_ordered_corr_coef_for_sliding_window_degree_matrix(data, definition, def_args,
normalize_row_or_column):
f = open(OUT_DIR.RCM_MATRIC + 'iraniraqpn.m', 'w')
all_countries = DEFAULT_COUNTRIES_LIST
allowed_countries = iran_iraq_countries
# all_countries = ['USA', 'UK', 'Australia', 'Greece']
# allowed_countries = ['Australia', 'Greece']
window_size = 5
for window_start_year in data.all_years:
sliding_window = range(window_start_year, window_start_year + window_size)
window_end_year = sliding_window[-1:][0]
if window_end_year > 2000: break
pn_matrix = positives_and_negatives_matrix(data, definition, def_args, sliding_window, all_countries,
normalize_row_or_column)
f.write(matrix_py_matlab_with_name('pnmatrix', pn_matrix))
data_matrix = corrcoef(pn_matrix)
for threshold in [0]:
for line in adjacency_rcm_ordered(data_matrix, threshold, [all_countries, allowed_countries],
'%s-%s' % (window_start_year, window_end_year)):
f.write("%s\n" % line)
f.close()
