def test_create_dir(self):
"""create_dir creates dir and fails meaningful."""
tmp_dir_path = get_random_directory_name()
tmp_dir_path2 = get_random_directory_name(suppress_mkdir=True)
tmp_dir_path3 = get_random_directory_name(suppress_mkdir=True)
self.dirs_to_remove.append(tmp_dir_path)
self.dirs_to_remove.append(tmp_dir_path2)
self.dirs_to_remove.append(tmp_dir_path3)
# create on existing dir raises OSError if fail_on_exist=True
self.assertRaises(OSError,
create_dir,
tmp_dir_path,
fail_on_exist=True)
self.assertEquals(
create_dir(tmp_dir_path,
fail_on_exist=True,
handle_errors_externally=True), 1)
# return should be 1 if dir exist and fail_on_exist=False
self.assertEqual(create_dir(tmp_dir_path, fail_on_exist=False), 1)
# if dir not there make it and return always 0
self.assertEqual(create_dir(tmp_dir_path2), 0)
self.assertEqual(create_dir(tmp_dir_path3, fail_on_exist=True), 0)
def test_make_table_file(self):
random_dir_name = get_random_directory_name(output_dir='/tmp')
foldername = random_dir_name
self._dir_to_clean_up = foldername
try:
os.mkdir(foldername)
except OSError:
pass
obs = foldername
try:
os.mkdir(os.path.join(obs, "otu_network"))
except OSError:
pass
obs = os.path.join(obs, "otu_network")
make_table_file(self.edge_file_str, self.labels, obs,
"real_edge_table.txt")
self.assertTrue(
exists(foldername + "/otu_network/real_edge_table.txt"),
'The file was not created in \
the appropriate location')
def setUp(self):
"""define some top-level data"""
qiime_dir = get_qiime_project_dir()
self.key = 'qiime_test'
self.project_id = 'qiime_test'
self.sample_id = 'qiime_sample1'
self.params=[('key', self.key), ('sample', self.sample_id), \
('project', self.project_id)]
test_dir = path.dirname(path.abspath(__file__))
self.seq_file=path.join(test_dir,'test_support_files',\
'qiime_tutorial_split_lib_seqs_subset.fna')
self.output_dir = get_random_directory_name(output_dir='/tmp/')
self.sample_file = [('file', 'qiime_test.fna', fasta_example)]
self._paths_to_clean_up = []
self._dirs_to_clean_up = []
#make the webfile directory
try:
mkdir(self.output_dir)
except OSError:
pass
#define directory to clean up
self._dirs_to_clean_up = [self.output_dir]
def test_make_table_file(self):
random_dir_name = get_random_directory_name(output_dir='/tmp')
foldername = random_dir_name
self._dir_to_clean_up = foldername
try:
os.mkdir(foldername)
except OSError:
pass
obs = foldername
try:
os.mkdir(os.path.join(obs, "otu_network"))
except OSError:
pass
obs = os.path.join(obs, "otu_network")
make_table_file(
self.edge_file_str,
self.labels,
obs,
"real_edge_table.txt")
self.assertTrue(exists(foldername + "/otu_network/real_edge_table.txt"), 'The file was not created in \
the appropriate location')
def setUp(self):
# create the temporary input files that will be used
self.iupac = {
'A': 'A',
'T': 'T',
'G': 'G',
'C': 'C',
'R': '[AG]',
'Y': '[CT]',
'S': '[GC]',
'W': '[AT]',
'K': '[GT]',
'M': '[AC]',
'B': '[CGT]',
'D': '[AGT]',
'H': '[ACT]',
'V': '[ACG]',
'N': '[ACGT]'
}
self.output_dir = get_random_directory_name(prefix='/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
def setUp(self):
"""define some top-level data"""
qiime_dir = get_qiime_project_dir()
self.key='qiime_test'
self.project_id='qiime_test'
self.sample_id='qiime_sample1'
self.params=[('key', self.key), ('sample', self.sample_id), \
('project', self.project_id)]
test_dir = path.dirname(path.abspath(__file__))
self.seq_file=path.join(test_dir,'test_support_files',\
'qiime_tutorial_split_lib_seqs_subset.fna')
self.output_dir=get_random_directory_name(output_dir='/tmp/')
self.sample_file=[('file','qiime_test.fna',fasta_example)]
self._paths_to_clean_up = []
self._dirs_to_clean_up = []
#make the webfile directory
try:
mkdir(self.output_dir)
except OSError:
pass
#define directory to clean up
self._dirs_to_clean_up = [self.output_dir]
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
if not opts.counts_fname:
parser.error("An otu table file must be specified")
if not opts.map_fname:
parser.error("A Map file must be specified")
prefs,data,background_color,label_color, ball_scale, arrow_colors= \
sample_color_prefs_and_map_data_from_options(opts)
dir_path = opts.dir_path
if dir_path==None or dir_path=='':
dir_path = get_random_directory_name()
create_dir(dir_path)
create_dir(os.path.join(dir_path,"otu_network"))
create_dir(os.path.join(dir_path,"otu_network/props"))
create_dir(os.path.join(dir_path,"otu_network/stats"))
map_lines = open(opts.map_fname,'U').readlines()
otu_sample_lines = open(opts.counts_fname, 'U').readlines()
create_network_and_stats(dir_path,map_lines,otu_sample_lines,prefs,data,background_color,label_color)
def test_make_props_files(self):
random_dir_name=get_random_directory_name(output_dir='/tmp')
foldername = random_dir_name
self._dir_to_clean_up = foldername
try:
os.mkdir(foldername)
except OSError:
pass
obs=foldername
try:
os.mkdir(os.path.join(obs,"otu_network"))
except OSError:
pass
try:
os.mkdir(os.path.join(obs,"otu_network/props"))
except OSError:
pass
obs = os.path.join(obs,"otu_network")
self.assertTrue(exists(foldername+"/otu_network/props/"),'The file was not created in \
the appropriate location')
self.assertTrue(exists(foldername+"/otu_network/props"),'The file was not created in \
the appropriate location')
def test_mothur_supported_version(self):
"""mothur is in path and version is supported """
acceptable_version = (1,6,0)
self.assertTrue(app_path('mothur'),
"mothur not found. This may or may not be a problem depending on "+\
"which components of QIIME you plan to use.")
# mothur creates a log file in cwd, so create a tmp and cd there first
tmp_dir = get_random_directory_name(output_dir='/tmp/')
command = "cd %s ; mothur -v | grep ^mothur" % tmp_dir
proc = Popen(command,shell=True,universal_newlines=True,\
stdout=PIPE,stderr=STDOUT)
stdout, stderr = proc.communicate()
version_string = stdout.strip().split(' ')[1].strip('v.')
try:
version = tuple(map(int,version_string.split('.')))
pass_test = version == acceptable_version
except ValueError:
pass_test = False
version_string = stdout
self.assertTrue(pass_test,\
"Unsupported mothur version. %s is required, but running %s." \
% ('.'.join(map(str,acceptable_version)), version_string))
# remove the directory and the log file
rmtree(tmp_dir)
def test_make_props_files(self):
random_dir_name = get_random_directory_name(output_dir='/tmp')
foldername = random_dir_name
self._dir_to_clean_up = foldername
try:
os.mkdir(foldername)
except OSError:
pass
obs = foldername
try:
os.mkdir(os.path.join(obs, "otu_network"))
except OSError:
pass
try:
os.mkdir(os.path.join(obs, "otu_network/props"))
except OSError:
pass
obs = os.path.join(obs, "otu_network")
self.assertTrue(
exists(foldername + "/otu_network/props/"),
'The file was not created in \
the appropriate location')
self.assertTrue(
exists(foldername + "/otu_network/props"),
'The file was not created in \
the appropriate location')
def setUp(self):
# create the temporary input files that will be used
self.iupac = {'A':'A', 'T':'T', 'G':'G', 'C':'C', 'R':'[AG]',
'Y':'[CT]', 'S':'[GC]', 'W':'[AT]', 'K':'[GT]', 'M':'[AC]',
'B':'[CGT]','D':'[AGT]', 'H':'[ACT]', 'V':'[ACG]', 'N':'[ACGT]'}
self.output_dir = get_random_directory_name(prefix = '/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
def test_make_stats_files(self):
random_dir_name = get_random_directory_name(output_dir='/tmp')
foldername = random_dir_name
self._dir_to_clean_up = foldername
try:
os.mkdir(foldername)
except OSError:
pass
obs = foldername
try:
os.mkdir(os.path.join(obs, "otu_network"))
except OSError:
pass
try:
os.mkdir(os.path.join(obs, "otu_network/stats"))
except OSError:
pass
obs = os.path.join(obs, "otu_network")
make_stats_files(self.sample_dc, self.otu_dc, self.degree_counts,
self.num_con_cat, self.num_con, self.num_cat,
self.cat_by_sample, obs)
self.assertTrue(
exists(foldername + "/otu_network/stats/real_dc_otu_degree.txt"),
'The file was not created in \
the appropriate location')
self.assertTrue(
exists(foldername +
"/otu_network/stats/real_dc_sample_degree.txt"),
'The file was not created in \
the appropriate location')
self.assertTrue(
exists(foldername +
"/otu_network/stats/real_dc_sample_otu_degree.txt"),
'The file was not created in \
the appropriate location')
self.assertTrue(
exists(foldername + "/otu_network/stats/real_cat_stats_Day.txt"),
'The file was not created in \
the appropriate location')
self.assertTrue(
exists(foldername + "/otu_network/stats/real_cat_stats_time.txt"),
'The file was not created in \
the appropriate location')
def setUp(self):
# create the temporary input files that will be used
self._files_to_remove = []
# Need an empty input directory to control fasta files present
self.input_dir = get_random_directory_name(prefix = '/tmp/') + "/"
# Input data
self.sample_fasta1 = sample_fasta1
self.sample_fasta2 = sample_fasta2
self.sample_fasta3 = sample_fasta3
self.fasta1_fp = join(self.input_dir, "fasta1.fasta")
map_file = open(self.fasta1_fp, 'w')
map_file.write(self.sample_fasta1)
map_file.close()
self.fasta2_fp = join(self.input_dir, "fasta2.fna")
map_file = open(self.fasta2_fp, 'w')
map_file.write(self.sample_fasta2)
map_file.close()
self.fasta3_fp = join(self.input_dir, "fasta3.fa")
map_file = open(self.fasta3_fp, 'w')
map_file.write(self.sample_fasta3)
map_file.close()
# Output data
self.output_dir = get_random_directory_name(prefix = '/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
self._files_to_remove =\
[self.fasta1_fp, self.fasta2_fp, self.fasta3_fp]
def setUp(self):
# create the temporary input files that will be used
self._files_to_remove = []
# Need an empty input directory to control fasta files present
self.input_dir = get_random_directory_name(prefix='/tmp/') + "/"
# Input data
self.sample_fasta1 = sample_fasta1
self.sample_fasta2 = sample_fasta2
self.sample_fasta3 = sample_fasta3
self.fasta1_fp = join(self.input_dir, "fasta1.fasta")
map_file = open(self.fasta1_fp, 'w')
map_file.write(self.sample_fasta1)
map_file.close()
self.fasta2_fp = join(self.input_dir, "fasta2.fna")
map_file = open(self.fasta2_fp, 'w')
map_file.write(self.sample_fasta2)
map_file.close()
self.fasta3_fp = join(self.input_dir, "fasta3.fa")
map_file = open(self.fasta3_fp, 'w')
map_file.write(self.sample_fasta3)
map_file.close()
# Output data
self.output_dir = get_random_directory_name(prefix='/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
self._files_to_remove =\
[self.fasta1_fp, self.fasta2_fp, self.fasta3_fp]
def test_create_dir(self):
"""create_dir creates dir and fails meaningful."""
tmp_dir_path = get_random_directory_name()
tmp_dir_path2 = get_random_directory_name(suppress_mkdir=True)
tmp_dir_path3 = get_random_directory_name(suppress_mkdir=True)
self.dirs_to_remove.append(tmp_dir_path)
self.dirs_to_remove.append(tmp_dir_path2)
self.dirs_to_remove.append(tmp_dir_path3)
# create on existing dir raises OSError if fail_on_exist=True
self.assertRaises(OSError, create_dir, tmp_dir_path,
fail_on_exist=True)
self.assertEquals(create_dir(tmp_dir_path,
fail_on_exist=True,
handle_errors_externally=True), 1)
# return should be 1 if dir exist and fail_on_exist=False
self.assertEqual(create_dir(tmp_dir_path, fail_on_exist=False), 1)
# if dir not there make it and return always 0
self.assertEqual(create_dir(tmp_dir_path2), 0)
self.assertEqual(create_dir(tmp_dir_path3, fail_on_exist=True), 0)
def test_make_stats_files(self):
random_dir_name = get_random_directory_name(output_dir='/tmp')
foldername = random_dir_name
self._dir_to_clean_up = foldername
try:
os.mkdir(foldername)
except OSError:
pass
obs = foldername
try:
os.mkdir(os.path.join(obs, "otu_network"))
except OSError:
pass
try:
os.mkdir(os.path.join(obs, "otu_network/stats"))
except OSError:
pass
obs = os.path.join(obs, "otu_network")
make_stats_files(
self.sample_dc,
self.otu_dc,
self.degree_counts,
self.num_con_cat,
self.num_con,
self.num_cat,
self.cat_by_sample,
obs)
self.assertTrue(exists(foldername + "/otu_network/stats/real_dc_otu_degree.txt"), 'The file was not created in \
the appropriate location')
self.assertTrue(exists(foldername + "/otu_network/stats/real_dc_sample_degree.txt"), 'The file was not created in \
the appropriate location')
self.assertTrue(exists(foldername + "/otu_network/stats/real_dc_sample_otu_degree.txt"), 'The file was not created in \
the appropriate location')
self.assertTrue(exists(foldername + "/otu_network/stats/real_cat_stats_Day.txt"), 'The file was not created in \
the appropriate location')
self.assertTrue(exists(foldername + "/otu_network/stats/real_cat_stats_time.txt"), 'The file was not created in \
the appropriate location')
def setUp(self):
# create the temporary input files that will be used
self._files_to_remove = []
self.qual_fp = get_tmp_filename(
prefix='qual_scores_',
suffix='.qual')
seq_file = open(self.qual_fp, 'w')
seq_file.write(qual_scores)
seq_file.close()
self.output_dir = get_random_directory_name(prefix='/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
self.expected_output_text_file = expected_output_text_file
self._files_to_remove =\
[self.qual_fp]
def test_get_taxa(self):
rand_fname = get_random_directory_name(suppress_mkdir=True)
rand_fname += '_tmp.txt'
fout = open(rand_fname,'w')
lines = ['#Full OTU Counts', \
'Taxon\tA\tB\tC', \
'Root;Bacteria;Acidobacteria\t0.1\t0.2\t0.3', \
'Root;Bacteria;TM7\t0.05\t0.0\t0.3' \
]
fout.write('\n'.join(lines))
fout.close()
otu_ids = ['Root;Bacteria;Acidobacteria','Root;Bacteria;TM7']
otu_table = np.array([[0.1,0.3],[0.05,0.3]])
res = bp.get_taxa(rand_fname,sample_ids_kept=['A','C'])
self.assertEqual(res[0],otu_ids)
self.assertEqual(res[1],otu_table)
# remove temporary file
system('rm %s' %(rand_fname))
pass
def setUp(self):
# create the temporary input files that will be used
self._files_to_remove = []
self.qual_fp = get_tmp_filename(\
prefix = 'qual_scores_',
suffix = '.qual')
seq_file = open(self.qual_fp, 'w')
seq_file.write(qual_scores)
seq_file.close()
self.output_dir = get_random_directory_name(prefix='/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
self.expected_output_text_file = expected_output_text_file
self._files_to_remove =\
[self.qual_fp]
def setUp(self):
"""define some top-level data"""
qiime_dir = get_qiime_project_dir()
self.key = "qiime_test"
self.project_id = "qiime_test"
self.sample_id = "qiime_sample1"
self.params = [("key", self.key), ("sample", self.sample_id), ("project", self.project_id)]
test_dir = path.dirname(path.abspath(__file__))
self.seq_file = path.join(test_dir, "test_support_files", "qiime_tutorial_split_lib_seqs_subset.fna")
self.output_dir = get_random_directory_name(output_dir="/tmp/")
self.sample_file = [("file", "qiime_test.fna", fasta_example)]
self._paths_to_clean_up = []
self._dirs_to_clean_up = []
# make the webfile directory
try:
mkdir(self.output_dir)
except OSError:
pass
# define directory to clean up
self._dirs_to_clean_up = [self.output_dir]
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
# Some code for error checking of input args:
# Check if distance_matrix_file is valid:
try:
d_header, d_mat = parse_distmat(open(opts.distance_matrix_file, "U"))
except:
option_parser.error(
"This does not look like a valid distance matrix file. Please supply a valid distance matrix file using the -d option."
)
if not is_symmetric_and_hollow(d_mat):
option_parser.error("The distance matrix must be symmetric and " "hollow.")
# Check if map_fname is valid:
try:
mapping, m_header, m_comments = parse_mapping_file(open(opts.map_fname, "U"))
except QiimeParseError:
option_parser.error(
"This does not look like a valid metadata mapping file. Please supply a valid mapping file using the -m option."
)
# make sure background_color is valid
if opts.background_color not in ["black", "white"]:
option_parser.error(
"'%s' is not a valid background color. Please pass in either 'black' or 'white' using the -k option."
% (opts.background_color)
)
# make sure prefs file is valid if it exists
if opts.prefs_path is not None:
try:
prefs_file = open(opts.prefs_path, "U").read()
except IOError:
option_parser.error(
"Provided prefs file, '%s', does not exist. Please pass in a valid prefs file with the -p option."
% (opts.prefs_path)
)
if opts.prefs_path is not None:
prefs = parse_prefs_file(prefs_file)
else:
prefs = None
color_prefs, color_data, background_color, label_color, ball_scale, arrow_colors = sample_color_prefs_and_map_data_from_options(
opts
)
# list of labelname, groups, colors, data_colors, data_color_order
groups_and_colors = list(iter_color_groups(mapping=color_data["map"], prefs=color_prefs))
# dict mapping labelname to list of: [groups, colors, data_colors,
# data_color_order]
field_to_colors = {}
for color_info in groups_and_colors:
field_to_colors[color_info[0]] = color_info[1:]
qiime_dir = get_qiime_project_dir() + "/qiime/support_files/"
fields = opts.fields
if fields is not None:
fields = map(strip, fields.split(","))
fields = [i.strip('"').strip("'") for i in fields]
elif prefs is not None:
fields = prefs.get("FIELDS", None)
else:
fields = get_interesting_mapping_fields(mapping, m_header)
# Check that all provided fields are valid:
if fields is not None:
for f in fields:
if f not in m_header:
option_parser.error(
"The field, %s, is not in the provided mapping file. Please supply correct fields (using the -f option or providing a 'FIELDS' list in the prefs file) corresponding to fields in mapping file."
% (f)
)
within_distances, between_distances, dmat = group_distances(
mapping_file=opts.map_fname,
dmatrix_file=opts.distance_matrix_file,
fields=fields,
dir_prefix=get_random_directory_name(output_dir=opts.dir_path, prefix="distances"),
)
if not opts.suppress_html_output:
# histograms output path
histograms_path = path.join(opts.dir_path, "histograms")
try:
mkdir(histograms_path)
except OSError: # raised if dir exists
pass
# draw all histograms
distances_dict, label_to_histogram_filename = draw_all_histograms(
single_field=within_distances,
paired_field=between_distances,
dmat=dmat,
histogram_dir=histograms_path,
field_to_color_prefs=field_to_colors,
background_color=background_color,
)
# Get relative path to histogram files.
label_to_histogram_filename_relative = _make_relative_paths(label_to_histogram_filename, opts.dir_path)
dm_fname = path.split(opts.distance_matrix_file)[-1]
basename = path.splitext(dm_fname)[0]
outfile_name = basename + "_distance_histograms.html"
make_main_html(
distances_dict=distances_dict,
label_to_histogram_filename=label_to_histogram_filename_relative,
root_outdir=opts.dir_path,
outfile_name=outfile_name,
title="Distance Histograms",
)
# Handle saving web resources locally.
# javascript file
javascript_path = path.join(opts.dir_path, "js")
try:
mkdir(javascript_path)
except OSError: # raised if dir exists
pass
js_out = open(javascript_path + "/histograms.js", "w")
js_out.write(open(qiime_dir + "js/histograms.js").read())
js_out.close()
monte_carlo_iters = opts.monte_carlo_iters
if monte_carlo_iters > 0:
# Do Monte Carlo for all fields
monte_carlo_group_distances(
mapping_file=opts.map_fname,
dmatrix_file=opts.distance_matrix_file,
prefs=prefs,
dir_prefix=opts.dir_path,
fields=fields,
default_iters=monte_carlo_iters,
)
# Do Monte Carlo for within and between fields
monte_carlo_group_distances_within_between(
single_field=within_distances,
paired_field=between_distances,
dmat=dmat,
dir_prefix=opts.dir_path,
num_iters=monte_carlo_iters,
)
def generate_2d_plots(prefs, data, html_dir_path, data_dir_path, filename,
background_color, label_color, generate_scree):
"""Generate interactive 2D scatterplots"""
coord_tups = [("1", "2"), ("3", "2"), ("1", "3")]
mapping = data['map']
out_table = ''
#Iterate through prefs and generate html files for each colorby option
#Sort by the column name first
sample_location = {}
groups_and_colors = iter_color_groups(mapping, prefs)
groups_and_colors = list(groups_and_colors)
for i in range(len(groups_and_colors)):
labelname = groups_and_colors[i][0]
groups = groups_and_colors[i][1]
colors = groups_and_colors[i][2]
data_colors = groups_and_colors[i][3]
data_color_order = groups_and_colors[i][4]
data_file_dir_path = get_random_directory_name(
output_dir=data_dir_path)
new_link = os.path.split(data_file_dir_path)
data_file_link=os.path.join('.', os.path.split(new_link[-2])[-1], \
new_link[-1])
new_col_name = labelname
img_data = {}
plot_label = labelname
if data.has_key('support_pcoas'):
matrix_average, matrix_low, matrix_high, eigval_average, m_names = \
summarize_pcoas(data['coord'], data['support_pcoas'],
method=data['ellipsoid_method'])
data['coord'] = \
(m_names,matrix_average,data['coord'][2],data['coord'][3])
for i in range(len(m_names)):
sample_location[m_names[i]] = i
else:
matrix_average = None
matrix_low = None
matrix_high = None
eigval_average = None
m_names = None
iterator = 0
for coord_tup in coord_tups:
if isarray(matrix_low) and isarray(matrix_high) and \
isarray(matrix_average):
coord_1r = asarray(matrix_low)
coord_2r = asarray(matrix_high)
mat_ave = asarray(matrix_average)
else:
coord_1r = None
coord_2r = None
mat_ave = None
sample_location = None
coord_1, coord_2 = coord_tup
img_data[coord_tup] = draw_pcoa_graph(plot_label,data_file_dir_path,
data_file_link,coord_1,coord_2,
coord_1r, coord_2r, mat_ave,\
sample_location,
data,prefs,groups,colors,
background_color,label_color,
data_colors,data_color_order,
generate_eps=True)
out_table += TABLE_HTML % (labelname, "<br>".join(
img_data[("1", "2")]), "<br>".join(
img_data[("3", "2")]), "<br>".join(img_data[("1", "3")]))
if generate_scree:
data_file_dir_path = get_random_directory_name(
output_dir=data_dir_path)
new_link = os.path.split(data_file_dir_path)
data_file_link = os.path.join('.',
os.path.split(new_link[-2])[-1],
new_link[-1])
img_src, download_link = draw_scree_graph(data_file_dir_path,
data_file_link,
background_color,
label_color,
generate_eps=True,
data=data)
out_table += SCREE_TABLE_HTML % ("<br>".join((img_src, download_link)))
outfile = create_html_filename(filename, '.html')
outfile = os.path.join(html_dir_path, outfile)
write_html_file(out_table, outfile)
def main():
print "\nWarning: make_3d_plots.py is being deprecated in favor of make_emperor.py, and will no longer be available in QIIME 1.8.0-dev.\n"
option_parser, opts, args = parse_command_line_parameters(**script_info)
prefs, data, background_color, label_color, ball_scale, arrow_colors= \
sample_color_prefs_and_map_data_from_options(opts)
plot_scaled= 'scaled' in opts.scaling_method
plot_unscaled= 'unscaled' in opts.scaling_method
if opts.output_format == 'invue':
# validating the number of points for interpolation
if (opts.interpolation_points<0):
option_parser.error('The --interpolation_points should be ' +\
'greater or equal to 0.')
# make sure that coord file has internally consistent # of columns
coord_files_valid = validate_coord_files(opts.coord_fname)
if not coord_files_valid:
option_parser.error('Every line of every coord file must ' +\
'have the same number of columns.')
#Open and get coord data
data['coord'] = get_coord(opts.coord_fname, opts.ellipsoid_method)
# remove any samples not present in mapping file
remove_unmapped_samples(data['map'],data['coord'])
# if no samples overlapped between mapping file and otu table, exit
if len(data['coord'][0]) == 0:
print "\nError: OTU table and mapping file had no samples in common\n"
exit(1)
if opts.output_dir:
create_dir(opts.output_dir,False)
dir_path=opts.output_dir
else:
dir_path='./'
filepath=opts.coord_fname
if os.path.isdir(filepath):
coord_files = [fname for fname in os.listdir(filepath) if not \
fname.startswith('.')]
filename = os.path.split(coord_files[0])[-1]
else:
filename = os.path.split(filepath)[-1]
generate_3d_plots_invue(prefs, data, dir_path, filename, \
opts.interpolation_points, opts.polyhedron_points, \
opts.polyhedron_offset)
#finish script
return
# Potential conflicts
if not opts.custom_axes is None and os.path.isdir(opts.coord_fname):
# can't do averaged pcoa plots _and_ custom axes in the same plot
option_parser.error("Please supply either custom axes or multiple coordinate \
files, but not both.")
# check that smoothness is an integer between 0 and 3
try:
ellipsoid_smoothness = int(opts.ellipsoid_smoothness)
except:
option_parser.error("Please supply an integer ellipsoid smoothness \
value.")
if ellipsoid_smoothness < 0 or ellipsoid_smoothness > 3:
option_parser.error("Please supply an ellipsoid smoothness value \
between 0 and 3.")
# check that opacity is a float between 0 and 1
try:
ellipsoid_alpha = float(opts.ellipsoid_opacity)
except:
option_parser.error("Please supply a number for ellipsoid opacity.")
if ellipsoid_alpha < 0 or ellipsoid_alpha > 1:
option_parser.error("Please supply an ellipsoid opacity value \
between 0 and 1.")
# check that ellipsoid method is valid
ellipsoid_methods = ['IQR','sdev']
if not opts.ellipsoid_method in ellipsoid_methods:
option_parser.error("Please supply a valid ellipsoid method. \
Valid methods are: " + ', '.join(ellipsoid_methods) + ".")
# gather ellipsoid drawing preferences
ellipsoid_prefs = {}
ellipsoid_prefs["smoothness"] = ellipsoid_smoothness
ellipsoid_prefs["alpha"] = ellipsoid_alpha
# make sure that coord file has internally consistent # of columns
coord_files_valid = validate_coord_files(opts.coord_fname)
if not coord_files_valid:
option_parser.error('Every line of every coord file must ' +\
'have the same number of columns.')
#Open and get coord data
data['coord'] = get_coord(opts.coord_fname, opts.ellipsoid_method)
# remove any samples not present in mapping file
remove_unmapped_samples(data['map'],data['coord'])
# if no samples overlapped between mapping file and otu table, exit
if len(data['coord'][0]) == 0:
print "\nError: OTU table and mapping file had no samples in common\n"
exit(1)
# process custom axes, if present.
custom_axes = None
if opts.custom_axes:
custom_axes = process_custom_axes(opts.custom_axes)
get_custom_coords(custom_axes, data['map'], data['coord'])
remove_nans(data['coord'])
scale_custom_coords(custom_axes,data['coord'])
# process vectors if requested
if opts.add_vectors:
add_vectors={}
add_vectors['vectors'] = opts.add_vectors.split(',')
add_vectors['weight_by_vector'] = opts.weight_by_vector
if len(add_vectors)>3:
raise ValueError, 'You must add maximum 3 columns but %s' % opts.add_vectors
# Validating Vectors values
if opts.vectors_algorithm:
axes_number = len(data['coord'][1][1])
if opts.vectors_axes<0 or opts.vectors_axes>axes_number:
raise ValueError, 'vectors_algorithm should be between 0 and the max number' +\
'of samples/pcoa-axes: %d' % len(data['coord'][1][1])
if opts.vectors_axes == 0:
opts.vectors_axes = axes_number
add_vectors['vectors_axes'] = opts.vectors_axes
valid_chars = '_.abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789'
for c in opts.vectors_path:
if c not in valid_chars:
raise ValueError, 'vectors_path (%s) has invalid chars' % opts.vectors_path
add_vectors['vectors_output'] = {}
add_vectors['vectors_algorithm']=opts.vectors_algorithm
add_vectors['eigvals'] = data['coord'][3]
add_vectors['window_size'] = None
# checks specific for the modified first difference algorithm
if add_vectors['vectors_algorithm'] == 'wdiff':
try:
add_vectors['window_size'] = int(opts.window_size)
except TypeError:
raise TypeError, 'Specify --window_size as an integer'
# sanity check as the value can only be greater or equal to one
if add_vectors['window_size'] < 1:
raise ValueError, 'The value of window_size is invalid, '+\
'the value must be greater than zero, not %d' % add_vectors['window_size']
else:
add_vectors['vectors_algorithm'] = None
add_vectors['vectors_path'] = opts.vectors_path
else:
add_vectors = None
if opts.taxa_fname != None:
# get taxonomy counts
# get list of sample_ids that haven't been removed
sample_ids = data['coord'][0]
# get taxa summaries for all sample_ids
lineages, taxa_counts = get_taxa(opts.taxa_fname, sample_ids)
data['taxa'] = {}
data['taxa']['lineages'] = lineages
data['taxa']['counts'] = taxa_counts
# get average relative abundance of taxa
data['taxa']['prevalence'] = get_taxa_prevalence(data['taxa']['counts'])
# get coordinates of taxa (weighted mean of sample scores)
data['taxa']['coord'] = get_taxa_coords(data['taxa']['counts'],
data['coord'][1])
# trim results, do NOT change order
# check: https://github.com/qiime/qiime/issues/677
remove_rare_taxa(data['taxa'],nkeep=opts.n_taxa_keep)
# write taxa coords if requested
if not opts.biplot_output_file is None:
output = make_biplot_scores_output(data['taxa'])
fout = open(opts.biplot_output_file,'w')
fout.write('\n'.join(output))
fout.close()
if opts.output_dir:
create_dir(opts.output_dir,False)
dir_path=opts.output_dir
else:
dir_path='./'
qiime_dir=get_qiime_project_dir()
jar_path=os.path.join(qiime_dir,'qiime/support_files/jar/')
data_dir_path = get_random_directory_name(output_dir=dir_path,
return_absolute_path=False)
try:
os.mkdir(data_dir_path)
except OSError:
pass
data_file_path=data_dir_path
jar_dir_path = os.path.join(dir_path,'jar')
try:
os.mkdir(jar_dir_path)
except OSError:
pass
shutil.copyfile(os.path.join(jar_path,'king.jar'), os.path.join(jar_dir_path,'king.jar'))
filepath=opts.coord_fname
if os.path.isdir(filepath):
coord_files = [fname for fname in os.listdir(filepath) if not \
fname.startswith('.')]
filename = os.path.split(coord_files[0])[-1]
else:
filename = os.path.split(filepath)[-1]
try:
action = generate_3d_plots
except NameError:
action = None
#Place this outside try/except so we don't mask NameError in action
if action:
action(prefs,data,custom_axes,background_color,label_color,dir_path, \
data_file_path,filename,ellipsoid_prefs=ellipsoid_prefs, \
add_vectors=add_vectors, plot_scaled=plot_scaled, \
plot_unscaled=plot_unscaled)
def generate_2d_plots(prefs,data,html_dir_path,data_dir_path,filename,
background_color,label_color,generate_scree):
"""Generate interactive 2D scatterplots"""
coord_tups = [("1", "2"), ("3", "2"), ("1", "3")]
mapping=data['map']
out_table=''
#Iterate through prefs and generate html files for each colorby option
#Sort by the column name first
sample_location={}
groups_and_colors=iter_color_groups(mapping,prefs)
groups_and_colors=list(groups_and_colors)
radiobuttons = []
for i in range(len(groups_and_colors)):
labelname=groups_and_colors[i][0] #'EnvoID'
groups=groups_and_colors[i][1] #defaultdict(<type 'list'>, {'mangrove biome/marine habitat/ocean water': ['BBA.number1.filt..660397', 'BBA.number2.filt..660380', ...}
colors=groups_and_colors[i][2] #{'mangrove biome/marine habitat/ocean water': 'red5', 'Small lake biome/marine habitat/saline lake sediment': 'cyan1',
data_colors=groups_and_colors[i][3]#{'orange1': <qiime.colors.Color object at 0x25f1210>, 'orange3':
data_color_order=groups_and_colors[i][4]#['red1', 'blue1', 'orange1', 'green1', 'purple1', 'yellow1', 'cyan1', 'pink1', 'teal1', ...]
data_file_dir_path = get_random_directory_name(output_dir=data_dir_path)
new_link=os.path.split(data_file_dir_path)
data_file_link=os.path.join('.', os.path.split(new_link[-2])[-1], \
new_link[-1])
new_col_name=labelname
img_data = {}
plot_label=labelname
if data.has_key('support_pcoas'):
matrix_average, matrix_low, matrix_high, eigval_average, m_names = \
summarize_pcoas(data['coord'], data['support_pcoas'],
method=data['ellipsoid_method'])
data['coord'] = \
(m_names,matrix_average,data['coord'][2],data['coord'][3])
for i in range(len(m_names)):
sample_location[m_names[i]]=i
else:
matrix_average = None
matrix_low = None
matrix_high = None
eigval_average = None
m_names = None
iterator=0
for coord_tup in coord_tups: # change, if you want more thatn one PCoA plot! (i.e involving PC3)
if isarray(matrix_low) and isarray(matrix_high) and \
isarray(matrix_average):
coord_1r=asarray(matrix_low)
coord_2r=asarray(matrix_high)
mat_ave=asarray(matrix_average)
else:
coord_1r=None
coord_2r=None
mat_ave=None
sample_location=None
coord_1, coord_2 = coord_tup
img_data[coord_tup] = draw_pcoa_graph(plot_label,data_file_dir_path,
data_file_link,coord_1,coord_2,
coord_1r, coord_2r, mat_ave,\
sample_location,
data,prefs,groups,colors,
background_color,label_color,
data_colors,data_color_order,
generate_eps=True)
radiobuttons.append(RADIO % (data_file_link, labelname))
if i == 0: ## only create first table!
out_table += TABLE_HTML % (labelname,
"<br>".join(img_data[("1", "2")]),
"<br>".join(img_data[("3", "2")]),
"<br>".join(img_data[("1", "3")]))
if generate_scree:
data_file_dir_path = get_random_directory_name(output_dir = data_dir_path)
new_link = os.path.split(data_file_dir_path)
data_file_link = os.path.join('.', os.path.split(new_link[-2])[-1], new_link[-1])
img_src, download_link = draw_scree_graph(data_file_dir_path, data_file_link, background_color,
label_color, generate_eps = True, data = data)
out_table += SCREE_TABLE_HTML % ("<br>".join((img_src, download_link)))
out_table = "\n".join(radiobuttons) + out_table
outfile = create_html_filename(filename,'.html')
outfile = os.path.join(html_dir_path,outfile)
write_html_file(out_table,outfile)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
data = {}
prefs,data,background_color,label_color,ball_scale, arrow_colors= \
sample_color_prefs_and_map_data_from_options(opts)
data['ellipsoid_method'] = opts.ellipsoid_method
if 0.00 <= opts.ellipsoid_opacity <= 1.00:
data['alpha'] = opts.ellipsoid_opacity
else:
raise ValueError, 'The opacity must be a value between 0 and 1!'
#Open and get coord data
if os.path.isdir(opts.coord_fname) and opts.master_pcoa:
data['coord'], data['support_pcoas'] = load_pcoa_files(
opts.coord_fname)
data['coord'] = get_coord(opts.master_pcoa)
elif os.path.isdir(opts.coord_fname):
data['coord'], data['support_pcoas'] = load_pcoa_files(
opts.coord_fname)
else:
data['coord'] = get_coord(opts.coord_fname)
filepath = opts.coord_fname
basename, extension = os.path.splitext(filepath)
filename = '%s_2D_PCoA_plots' % (basename)
qiime_dir = get_qiime_project_dir()
js_path = os.path.join(qiime_dir, 'qiime', 'support_files', 'js')
if opts.output_dir:
if os.path.exists(opts.output_dir):
dir_path = opts.output_dir
else:
try:
os.mkdir(opts.output_dir)
dir_path = opts.output_dir
except OSError:
pass
else:
dir_path = './'
html_dir_path = dir_path
data_dir_path = get_random_directory_name(output_dir=dir_path)
try:
os.mkdir(data_dir_path)
except OSError:
pass
js_dir_path = os.path.join(html_dir_path, 'js')
try:
os.mkdir(js_dir_path)
except OSError:
pass
shutil.copyfile(os.path.join(js_path,'overlib.js'), \
os.path.join(js_dir_path,'overlib.js'))
try:
action = generate_2d_plots
except NameError:
action = None
#Place this outside try/except so we don't mask NameError in action
if action:
action(prefs, data, html_dir_path, data_dir_path, filename,
background_color, label_color, opts.scree)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
#Some code for error checking of input args:
#Check if distance_matrix_file is valid:
try:
d_header, d_mat = parse_distmat(open(opts.distance_matrix_file, 'U'))
except:
option_parser.error(
"This does not look like a valid distance matrix file. Please supply a valid distance matrix file using the -d option."
)
if not is_symmetric_and_hollow(d_mat):
option_parser.error("The distance matrix must be symmetric and "
"hollow.")
#Check if map_fname is valid:
try:
mapping, m_header, m_comments = \
parse_mapping_file(open(opts.map_fname,'U'))
except QiimeParseError:
option_parser.error(
"This does not look like a valid metadata mapping file. Please supply a valid mapping file using the -m option."
)
#make sure background_color is valid
if opts.background_color not in ['black', 'white']:
option_parser.error(
"'%s' is not a valid background color. Please pass in either 'black' or 'white' using the -k option."
% (opts.background_color))
#make sure prefs file is valid if it exists
if opts.prefs_path is not None:
try:
prefs_file = open(opts.prefs_path, 'U').read()
except IOError:
option_parser.error(
"Provided prefs file, '%s', does not exist. Please pass in a valid prefs file with the -p option."
% (opts.prefs_path))
if opts.prefs_path is not None:
prefs = parse_prefs_file(prefs_file)
else:
prefs = None
color_prefs, color_data, background_color, label_color, ball_scale,\
arrow_colors=sample_color_prefs_and_map_data_from_options(opts)
#list of labelname, groups, colors, data_colors, data_color_order
groups_and_colors=list(iter_color_groups(mapping=color_data['map'],\
prefs=color_prefs))
#dict mapping labelname to list of: [groups, colors, data_colors,
# data_color_order]
field_to_colors = {}
for color_info in groups_and_colors:
field_to_colors[color_info[0]] = color_info[1:]
qiime_dir = get_qiime_project_dir() + '/qiime/support_files/'
fields = opts.fields
if fields is not None:
fields = map(strip, fields.split(','))
fields = [i.strip('"').strip("'") for i in fields]
elif prefs is not None:
fields = prefs.get('FIELDS', None)
else:
fields = get_interesting_mapping_fields(mapping, m_header)
#Check that all provided fields are valid:
if fields is not None:
for f in fields:
if f not in m_header:
option_parser.error(
"The field, %s, is not in the provided mapping file. Please supply correct fields (using the -f option or providing a 'FIELDS' list in the prefs file) corresponding to fields in mapping file."
% (f))
within_distances, between_distances, dmat = \
group_distances(mapping_file=opts.map_fname,\
dmatrix_file=opts.distance_matrix_file,\
fields=fields,\
dir_prefix=get_random_directory_name(output_dir=opts.dir_path,\
prefix='distances'))
if not opts.suppress_html_output:
#histograms output path
histograms_path = path.join(opts.dir_path, 'histograms')
try:
mkdir(histograms_path)
except OSError: #raised if dir exists
pass
#draw all histograms
distances_dict, label_to_histogram_filename = \
draw_all_histograms(single_field=within_distances, \
paired_field=between_distances, \
dmat=dmat,\
histogram_dir=histograms_path,\
field_to_color_prefs=field_to_colors,\
background_color=background_color)
#Get relative path to histogram files.
label_to_histogram_filename_relative = \
_make_relative_paths(label_to_histogram_filename, opts.dir_path)
dm_fname = path.split(opts.distance_matrix_file)[-1]
basename = path.splitext(dm_fname)[0]
outfile_name = basename + '_distance_histograms.html'
make_main_html(distances_dict=distances_dict,\
label_to_histogram_filename=label_to_histogram_filename_relative,\
root_outdir=opts.dir_path, \
outfile_name = outfile_name, \
title='Distance Histograms')
#Handle saving web resources locally.
#javascript file
javascript_path = path.join(opts.dir_path, 'js')
try:
mkdir(javascript_path)
except OSError: #raised if dir exists
pass
js_out = open(javascript_path + '/histograms.js', 'w')
js_out.write(open(qiime_dir + 'js/histograms.js').read())
js_out.close()
monte_carlo_iters = opts.monte_carlo_iters
if monte_carlo_iters > 0:
#Do Monte Carlo for all fields
monte_carlo_group_distances(mapping_file=opts.map_fname,\
dmatrix_file=opts.distance_matrix_file,\
prefs=prefs, \
dir_prefix = opts.dir_path,\
fields=fields,\
default_iters=monte_carlo_iters)
#Do Monte Carlo for within and between fields
monte_carlo_group_distances_within_between(\
single_field=within_distances,\
paired_field=between_distances, dmat=dmat, \
dir_prefix = opts.dir_path,\
num_iters=monte_carlo_iters)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
input_dir = opts.input_dir
imagetype = opts.imagetype
resolution = opts.resolution
output_dir = opts.output_dir
ymax = opts.ymax
std_type = opts.std_type
suppress_webpage = opts.suppress_html_output
output_type = opts.output_type
generate_per_sample_plots = opts.generate_per_sample_plots
generate_average_tables = opts.generate_average_tables
# Get the command-line options.
prefs, data, background_color, label_color, ball_scale, arrow_colors = \
sample_color_prefs_and_map_data_from_options(opts)
rares = {}
if isdir(input_dir):
rarenames = listdir(input_dir)
rarenames = [r for r in rarenames if not r.startswith('.')]
for r in rarenames:
try:
rarefl = open(path.join(input_dir, r), 'U').readlines()
rares[r] = parse_rarefaction(rarefl)
except(IOError):
option_parser.error('Problem with rarefaction file. %s' %
exc_info()[1])
exit(0)
else:
try:
input_file = input_dir.split(',')
for i in range(len(input_file)):
input_path = split(input_file[i])[-1]
rarefl = open(input_file[i], 'U').readlines()
rares[input_path] = parse_rarefaction(rarefl)
except(IOError):
option_parser.error('Problem with rarefaction file. %s' %
exc_info()[1])
exit(0)
if imagetype not in ['png', 'svg', 'pdf']:
option_parser.error('Supplied extension not supported.')
exit(0)
try:
resolution = int(resolution)
except(ValueError):
option_parser.error('Inavlid resolution.')
exit(0)
# output directory check
if isinstance(output_dir, str) and output_dir != '.':
if exists(output_dir):
output_dir = output_dir
else:
try:
create_dir(output_dir, False)
output_dir = output_dir
except(ValueError):
option_parser.error('Could not create output directory.')
exit(0)
else:
output_dir = get_random_directory_name()
# Generate the plots and html text
html_output = make_averages(prefs, data, background_color, label_color,
rares, output_dir, resolution, imagetype, ymax,
suppress_webpage, std_type, output_type,
generate_per_sample_plots=generate_per_sample_plots,
generate_average_tables=generate_average_tables)
if html_output:
# Write the html file.
outfile = open(path.join(output_dir, 'rarefaction_plots.html'), 'w')
outfile.write(html_output)
outfile.close()
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
prefs, data, background_color, label_color, ball_scale, arrow_colors = sample_color_prefs_and_map_data_from_options(
opts
)
scaling_methods = opts.scaling_method.split(",")
plot_scaled = False
plot_unscaled = False
for i in scaling_methods:
if i.lower() == "scaled":
plot_scaled = True
elif i.lower() == "unscaled":
plot_unscaled = True
if not (plot_scaled or plot_unscaled):
raise ValueError, "You must choose a valid scaling method (scaled or unscaled)"
if opts.output_format == "invue":
# validating the number of points for interpolation
if opts.interpolation_points < 0:
option_parser.error("The --interpolation_points should be " + "greater or equal to 0.")
# make sure that coord file has internally consistent # of columns
coord_files_valid = validate_coord_files(opts.coord_fname)
if not coord_files_valid:
option_parser.error("Every line of every coord file must " + "have the same number of columns.")
# Open and get coord data
data["coord"] = get_coord(opts.coord_fname, opts.ellipsoid_method)
# remove any samples not present in mapping file
remove_unmapped_samples(data["map"], data["coord"])
# if no samples overlapped between mapping file and otu table, exit
if len(data["coord"][0]) == 0:
print "\nError: OTU table and mapping file had no samples in common\n"
exit(1)
if opts.output_dir:
create_dir(opts.output_dir, False)
dir_path = opts.output_dir
else:
dir_path = "./"
filepath = opts.coord_fname
if os.path.isdir(filepath):
coord_files = [fname for fname in os.listdir(filepath) if not fname.startswith(".")]
filename = os.path.split(coord_files[0])[-1]
else:
filename = os.path.split(filepath)[-1]
generate_3d_plots_invue(
prefs, data, dir_path, filename, opts.interpolation_points, opts.polyhedron_points, opts.polyhedron_offset
)
# finish script
return
# Potential conflicts
if not opts.custom_axes is None and os.path.isdir(opts.coord_fname):
# can't do averaged pcoa plots _and_ custom axes in the same plot
option_parser.error(
"Please supply either custom axes or multiple coordinate \
files, but not both."
)
# check that smoothness is an integer between 0 and 3
try:
ellipsoid_smoothness = int(opts.ellipsoid_smoothness)
except:
option_parser.error(
"Please supply an integer ellipsoid smoothness \
value."
)
if ellipsoid_smoothness < 0 or ellipsoid_smoothness > 3:
option_parser.error(
"Please supply an ellipsoid smoothness value \
between 0 and 3."
)
# check that opacity is a float between 0 and 1
try:
ellipsoid_alpha = float(opts.ellipsoid_opacity)
except:
option_parser.error("Please supply a number for ellipsoid opacity.")
if ellipsoid_alpha < 0 or ellipsoid_alpha > 1:
option_parser.error(
"Please supply an ellipsoid opacity value \
between 0 and 1."
)
# check that ellipsoid method is valid
ellipsoid_methods = ["IQR", "sdev"]
if not opts.ellipsoid_method in ellipsoid_methods:
option_parser.error(
"Please supply a valid ellipsoid method. \
Valid methods are: "
+ ", ".join(ellipsoid_methods)
+ "."
)
# gather ellipsoid drawing preferences
ellipsoid_prefs = {}
ellipsoid_prefs["smoothness"] = ellipsoid_smoothness
ellipsoid_prefs["alpha"] = ellipsoid_alpha
# make sure that coord file has internally consistent # of columns
coord_files_valid = validate_coord_files(opts.coord_fname)
if not coord_files_valid:
option_parser.error("Every line of every coord file must " + "have the same number of columns.")
# Open and get coord data
data["coord"] = get_coord(opts.coord_fname, opts.ellipsoid_method)
# remove any samples not present in mapping file
remove_unmapped_samples(data["map"], data["coord"])
# if no samples overlapped between mapping file and otu table, exit
if len(data["coord"][0]) == 0:
print "\nError: OTU table and mapping file had no samples in common\n"
exit(1)
# process custom axes, if present.
custom_axes = None
if opts.custom_axes:
custom_axes = process_custom_axes(opts.custom_axes)
get_custom_coords(custom_axes, data["map"], data["coord"])
remove_nans(data["coord"])
scale_custom_coords(custom_axes, data["coord"])
# process vectors if requested
if opts.add_vectors:
add_vectors = {}
add_vectors["vectors"] = opts.add_vectors.split(",")
add_vectors["weight_by_vector"] = opts.weight_by_vector
if len(add_vectors) > 3:
raise ValueError, "You must add maximum 3 columns but %s" % opts.add_vectors
# Validating Vectors values
if opts.vectors_algorithm:
axes_number = len(data["coord"][1][1])
if opts.vectors_axes < 0 or opts.vectors_axes > axes_number:
raise ValueError, "vectors_algorithm should be between 0 and the max number" + "of samples/pcoa-axes: %d" % len(
data["coord"][1][1]
)
if opts.vectors_axes == 0:
opts.vectors_axes = axes_number
add_vectors["vectors_axes"] = opts.vectors_axes
valid_chars = "_.abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789"
for c in opts.vectors_path:
if c not in valid_chars:
raise ValueError, "vectors_path (%s) has invalid chars" % opts.vectors_path
add_vectors["vectors_output"] = {}
add_vectors["vectors_algorithm"] = opts.vectors_algorithm
add_vectors["eigvals"] = data["coord"][3]
add_vectors["window_size"] = None
# checks specific for the modified first difference algorithm
if add_vectors["vectors_algorithm"] == "wdiff":
try:
add_vectors["window_size"] = int(opts.window_size)
except TypeError:
raise TypeError, "Specify --window_size as an integer"
# sanity check as the value can only be greater or equal to one
if add_vectors["window_size"] < 1:
raise ValueError, "The value of window_size is invalid, " + "the value must be greater than zero, not %d" % add_vectors[
"window_size"
]
else:
add_vectors["vectors_algorithm"] = None
add_vectors["vectors_path"] = opts.vectors_path
else:
add_vectors = None
if opts.taxa_fname != None:
# get taxonomy counts
# get list of sample_ids that haven't been removed
sample_ids = data["coord"][0]
# get taxa summaries for all sample_ids
lineages, taxa_counts = get_taxa(opts.taxa_fname, sample_ids)
data["taxa"] = {}
data["taxa"]["lineages"] = lineages
data["taxa"]["counts"] = taxa_counts
# get average relative abundance of taxa
data["taxa"]["prevalence"] = get_taxa_prevalence(data["taxa"]["counts"])
remove_rare_taxa(data["taxa"], nkeep=opts.n_taxa_keep)
# get coordinates of taxa (weighted mean of sample scores)
data["taxa"]["coord"] = get_taxa_coords(data["taxa"]["counts"], data["coord"][1])
data["taxa"]["coord"]
# write taxa coords if requested
if not opts.biplot_output_file is None:
output = make_biplot_scores_output(data["taxa"])
fout = open(opts.biplot_output_file, "w")
fout.write("\n".join(output))
fout.close()
if opts.output_dir:
create_dir(opts.output_dir, False)
dir_path = opts.output_dir
else:
dir_path = "./"
qiime_dir = get_qiime_project_dir()
jar_path = os.path.join(qiime_dir, "qiime/support_files/jar/")
data_dir_path = get_random_directory_name(output_dir=dir_path, return_absolute_path=False)
try:
os.mkdir(data_dir_path)
except OSError:
pass
data_file_path = data_dir_path
jar_dir_path = os.path.join(dir_path, "jar")
try:
os.mkdir(jar_dir_path)
except OSError:
pass
shutil.copyfile(os.path.join(jar_path, "king.jar"), os.path.join(jar_dir_path, "king.jar"))
filepath = opts.coord_fname
if os.path.isdir(filepath):
coord_files = [fname for fname in os.listdir(filepath) if not fname.startswith(".")]
filename = os.path.split(coord_files[0])[-1]
else:
filename = os.path.split(filepath)[-1]
try:
action = generate_3d_plots
except NameError:
action = None
# Place this outside try/except so we don't mask NameError in action
if action:
action(
prefs,
data,
custom_axes,
background_color,
label_color,
dir_path,
data_file_path,
filename,
ellipsoid_prefs=ellipsoid_prefs,
add_vectors=add_vectors,
plot_scaled=plot_scaled,
plot_unscaled=plot_unscaled,
)
def main():
print "\nWarning: compare_3d_plots.py is being deprecated in favor of make_emperor.py, and will no longer be available in QIIME 1.8.0-dev.\n"
option_parser, opts, args = parse_command_line_parameters(**script_info)
prefs, data, background_color, label_color, ball_scale, arrow_colors = sample_color_prefs_and_map_data_from_options(
opts
)
if len(opts.coord_fnames) < 2 and opts.edges_file is None:
option_parser.error("Please provide at least two " + "coordinate files or a custom edges file")
# Open and get coord data (for multiple coords files)
coord_files = opts.coord_fnames
coord_files_valid = validate_coord_files(coord_files)
if not coord_files_valid:
option_parser.error("Every line of every coord file must " + "have the same number of columns.")
num_coord_files = len(coord_files)
data["edges"], data["coord"] = get_multiple_coords(coord_files, opts.edges_file, opts.serial)
# if the edges file wasn't supplied, we appended _i to each file's samples
# therefore we now add duplicated samples with _0, _1,... to mapping file
if opts.edges_file is None:
newmap = [data["map"][0]]
for i in xrange(len(coord_files)):
for sample in data["map"][1:]:
newsample = ["%s_%d" % (sample[0], i)]
newsample.extend(sample[1:])
newmap.append(newsample)
data["map"] = newmap
# remove any samples not present in mapping file
remove_unmapped_samples(data["map"], data["coord"], data["edges"])
if len(data["coord"][1]) == 0:
raise ValueError, "\n\nError: None of the sample IDs in the coordinates files were present in the mapping file.\n"
# process custom axes, if present.
custom_axes = None
if opts.custom_axes:
custom_axes = process_custom_axes(opts.custom_axes)
get_custom_coords(custom_axes, data["map"], data["coord"])
remove_nans(data["coord"])
scale_custom_coords(custom_axes, data["coord"])
# Generate random output file name and create directories
if opts.output_dir:
create_dir(opts.output_dir)
dir_path = opts.output_dir
else:
dir_path = "./"
qiime_dir = get_qiime_project_dir()
jar_path = os.path.join(qiime_dir, "qiime/support_files/jar/")
data_dir_path = get_random_directory_name(output_dir=dir_path, return_absolute_path=False)
try:
os.mkdir(data_dir_path)
except OSError:
pass
jar_dir_path = os.path.join(dir_path, "jar")
try:
os.mkdir(jar_dir_path)
except OSError:
pass
shutil.copyfile(os.path.join(jar_path, "king.jar"), os.path.join(jar_dir_path, "king.jar"))
filepath = coord_files[0]
filename = filepath.strip().split("/")[-1]
try:
action = generate_3d_plots
except NameError:
action = None
# Place this outside try/except so we don't mask NameError in action
if action:
generate_3d_plots(
prefs,
data,
custom_axes,
background_color,
label_color,
dir_path,
data_dir_path,
filename,
ball_scale=ball_scale,
arrow_colors=arrow_colors,
user_supplied_edges=not (opts.edges_file is None),
)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
matplotlib_version = re.split("[^\d]", matplotlib.__version__)
matplotlib_version_info = tuple([int(i) for i in matplotlib_version if \
i.isdigit()])
if matplotlib_version_info != (1,1,0):
print "This code was only tested with Matplotlib-1.1.0"
data = {}
prefs,data,background_color,label_color,ball_scale, arrow_colors= \
sample_color_prefs_and_map_data_from_options(opts)
data['ellipsoid_method']=opts.ellipsoid_method
if 0.00 <= opts.ellipsoid_opacity <= 1.00:
data['alpha']=opts.ellipsoid_opacity
else:
raise ValueError, 'The opacity must be a value between 0 and 1!'
#Open and get coord data
if os.path.isdir(opts.coord_fname) and opts.master_pcoa:
data['coord'],data['support_pcoas'] = load_pcoa_files(opts.coord_fname)
data['coord']=get_coord(opts.master_pcoa)
elif os.path.isdir(opts.coord_fname):
data['coord'],data['support_pcoas'] = load_pcoa_files(opts.coord_fname)
else:
data['coord'] = get_coord(opts.coord_fname)
filepath=opts.coord_fname
basename,extension=os.path.splitext(filepath)
filename='%s_2D_PCoA_plots' % (basename)
qiime_dir=get_qiime_project_dir()
js_path=os.path.join(qiime_dir,'qiime','support_files','js')
if opts.output_dir:
if os.path.exists(opts.output_dir):
dir_path=opts.output_dir
else:
try:
os.mkdir(opts.output_dir)
dir_path=opts.output_dir
except OSError:
pass
else:
dir_path='./'
html_dir_path=dir_path
data_dir_path = get_random_directory_name(output_dir=dir_path)
try:
os.mkdir(data_dir_path)
except OSError:
pass
js_dir_path = os.path.join(html_dir_path,'js')
try:
os.mkdir(js_dir_path)
except OSError:
pass
shutil.copyfile(os.path.join(js_path,'overlib.js'), \
os.path.join(js_dir_path,'overlib.js'))
try:
action = generate_2d_plots
except NameError:
action = None
#Place this outside try/except so we don't mask NameError in action
if action:
action(prefs,data,html_dir_path,data_dir_path,filename,background_color,
label_color,opts.scree)
def setUp(self):
# create the temporary input files that will be used
self._files_to_remove = []
self.sample_fasta_file1_data = sample_fasta_file1
self.sample_fasta_file_bad_labels_data =\
sample_fasta_file_bad_labels
self.sample_mapping_file1_data = sample_mapping_file1
self.sample_mapping_file_no_revprimer_header =\
sample_mapping_file_no_revprimer_header
self.sample_mapping_file_bad_revprimer =\
sample_mapping_file_bad_revprimer
self.expected_truncation_default_settings =\
expected_truncation_default_settings
self.expected_truncation_zero_mismatches =\
expected_truncation_zero_mismatches
self.expected_truncation_zero_mismatches_truncate_remove =\
expected_truncation_zero_mismatches_truncate_remove
self.fasta_fp = get_tmp_filename(\
prefix = 'fasta_seqs_',
suffix = '.fna')
seq_file = open(self.fasta_fp, 'w')
seq_file.write(self.sample_fasta_file1_data)
seq_file.close()
self.fasta_badlabels_fp = get_tmp_filename(\
prefix = "fasta_seqs_badlabels_",
suffix = ".fna")
seq_file = open(self.fasta_badlabels_fp, "w")
seq_file.write(self.sample_fasta_file_bad_labels_data)
seq_file.close()
self.mapping_fp = get_tmp_filename(\
prefix = 'sample_mapping_',
suffix = '.txt')
mapping_file = open(self.mapping_fp, "w")
mapping_file.write(self.sample_mapping_file1_data)
mapping_file.close()
self.mapping_bad_header_fp = get_tmp_filename(\
prefix = 'sample_mapping_badheader_',
suffix = ".txt")
mapping_file = open(self.mapping_bad_header_fp, "w")
mapping_file.write(self.sample_mapping_file_no_revprimer_header)
mapping_file.close()
self.mapping_bad_primer_fp = get_tmp_filename(\
prefix = 'sample_mapping_badprimer_',
suffix = ".txt")
mapping_file = open(self.mapping_bad_primer_fp, "w")
mapping_file.write(self.sample_mapping_file_bad_revprimer)
mapping_file.close()
self.output_dir = get_random_directory_name(prefix='/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
self._files_to_remove =\
[self.fasta_fp, self.mapping_fp, self.mapping_bad_header_fp,
self.mapping_bad_primer_fp, self.fasta_badlabels_fp]
def generate_2d_plots(prefs,data,html_dir_path,data_dir_path,filename,
background_color,label_color,generate_scree):
"""Generate interactive 2D scatterplots"""
coord_tups = [("1", "2"), ("3", "2"), ("1", "3")]
mapping=data['map']
out_table=''
#Iterate through prefs and generate html files for each colorby option
#Sort by the column name first
sample_location={}
groups_and_colors=iter_color_groups(mapping,prefs)
groups_and_colors=list(groups_and_colors)
for i in range(len(groups_and_colors)):
labelname=groups_and_colors[i][0]
groups=groups_and_colors[i][1]
colors=groups_and_colors[i][2]
data_colors=groups_and_colors[i][3]
data_color_order=groups_and_colors[i][4]
data_file_dir_path = get_random_directory_name(output_dir=data_dir_path)
new_link=os.path.split(data_file_dir_path)
data_file_link=os.path.join('.', os.path.split(new_link[-2])[-1], \
new_link[-1])
new_col_name=labelname
img_data = {}
plot_label=labelname
if data.has_key('support_pcoas'):
matrix_average, matrix_low, matrix_high, eigval_average, m_names = \
summarize_pcoas(data['coord'], data['support_pcoas'],
method=data['ellipsoid_method'])
data['coord'] = \
(m_names,matrix_average,data['coord'][2],data['coord'][3])
for i in range(len(m_names)):
sample_location[m_names[i]]=i
else:
matrix_average = None
matrix_low = None
matrix_high = None
eigval_average = None
m_names = None
iterator=0
for coord_tup in coord_tups:
if isarray(matrix_low) and isarray(matrix_high) and \
isarray(matrix_average):
coord_1r=asarray(matrix_low)
coord_2r=asarray(matrix_high)
mat_ave=asarray(matrix_average)
else:
coord_1r=None
coord_2r=None
mat_ave=None
sample_location=None
coord_1, coord_2 = coord_tup
img_data[coord_tup] = draw_pcoa_graph(plot_label,data_file_dir_path,
data_file_link,coord_1,coord_2,
coord_1r, coord_2r, mat_ave,\
sample_location,
data,prefs,groups,colors,
background_color,label_color,
data_colors,data_color_order,
generate_eps=True)
out_table += TABLE_HTML % (labelname,
"<br>".join(img_data[("1", "2")]),
"<br>".join(img_data[("3", "2")]),
"<br>".join(img_data[("1", "3")]))
if generate_scree:
data_file_dir_path = get_random_directory_name(output_dir = data_dir_path)
new_link = os.path.split(data_file_dir_path)
data_file_link = os.path.join('.', os.path.split(new_link[-2])[-1], new_link[-1])
img_src, download_link = draw_scree_graph(data_file_dir_path, data_file_link, background_color,
label_color, generate_eps = True, data = data)
out_table += SCREE_TABLE_HTML % ("<br>".join((img_src, download_link)))
outfile = create_html_filename(filename,'.html')
outfile = os.path.join(html_dir_path,outfile)
write_html_file(out_table,outfile)
def generate_2d_plots(prefs,data,html_dir_path,data_dir_path,filename,
background_color,label_color,generate_scree):
"""Generate interactive 2D scatterplots"""
coord_tups = [("1", "2"), ("3", "2"), ("1", "3")]
mapping=data['map']
out_table=''
#Iterate through prefs and generate html files for each colorby option
#Sort by the column name first
sample_location={}
groups_and_colors=iter_color_groups(mapping,prefs)
groups_and_colors=list(groups_and_colors)
radiobuttons = []
for i in range(len(groups_and_colors)):
labelname=groups_and_colors[i][0] #'EnvoID'
groups=groups_and_colors[i][1] #defaultdict(<type 'list'>, {'mangrove biome/marine habitat/ocean water': ['BBA.number1.filt..660397', 'BBA.number2.filt..660380', ...}
colors=groups_and_colors[i][2] #{'mangrove biome/marine habitat/ocean water': 'red5', 'Small lake biome/marine habitat/saline lake sediment': 'cyan1',
data_colors=groups_and_colors[i][3]#{'orange1': <qiime.colors.Color object at 0x25f1210>, 'orange3':
data_color_order=groups_and_colors[i][4]#['red1', 'blue1', 'orange1', 'green1', 'purple1', 'yellow1', 'cyan1', 'pink1', 'teal1', ...]
data_file_dir_path = get_random_directory_name(output_dir=data_dir_path)
new_link=os.path.split(data_file_dir_path)
data_file_link=os.path.join('.', os.path.split(new_link[-2])[-1], \
new_link[-1])
new_col_name=labelname
img_data = {}
plot_label=labelname
if data.has_key('support_pcoas'):
matrix_average, matrix_low, matrix_high, eigval_average, m_names = \
summarize_pcoas(data['coord'], data['support_pcoas'],
method=data['ellipsoid_method'])
data['coord'] = \
(m_names,matrix_average,data['coord'][2],data['coord'][3])
for i in range(len(m_names)):
sample_location[m_names[i]]=i
else:
matrix_average = None
matrix_low = None
matrix_high = None
eigval_average = None
m_names = None
iterator=0
for coord_tup in coord_tups: # change, if you want more thatn one PCoA plot! (i.e involving PC3)
if isarray(matrix_low) and isarray(matrix_high) and \
isarray(matrix_average):
coord_1r=asarray(matrix_low)
coord_2r=asarray(matrix_high)
mat_ave=asarray(matrix_average)
else:
coord_1r=None
coord_2r=None
mat_ave=None
sample_location=None
coord_1, coord_2 = coord_tup
img_data[coord_tup] = draw_pcoa_graph(plot_label,data_file_dir_path,
data_file_link,coord_1,coord_2,
coord_1r, coord_2r, mat_ave,\
sample_location,
data,prefs,groups,colors,
background_color,label_color,
data_colors,data_color_order,
generate_eps=True)
radiobuttons.append(RADIO % (data_file_link, labelname))
if i == 0: ## only create first table!
out_table += TABLE_HTML % (labelname,
"<br>".join(img_data[("1", "2")]),
"<br>".join(img_data[("3", "2")]),
"<br>".join(img_data[("1", "3")]))
if generate_scree:
data_file_dir_path = get_random_directory_name(output_dir = data_dir_path)
new_link = os.path.split(data_file_dir_path)
data_file_link = os.path.join('.', os.path.split(new_link[-2])[-1], new_link[-1])
img_src, download_link = draw_scree_graph(data_file_dir_path, data_file_link, background_color,
label_color, generate_eps = True, data = data)
out_table += SCREE_TABLE_HTML % ("<br>".join((img_src, download_link)))
out_table = "\n".join(radiobuttons) + out_table
outfile = create_html_filename(filename,'.html')
outfile = os.path.join(html_dir_path,outfile)
write_html_file(out_table,outfile)
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
prefs, data, background_color, label_color, ball_scale, arrow_colors = \
sample_color_prefs_and_map_data_from_options(opts)
if len(opts.coord_fnames) < 2 and opts.edges_file is None:
option_parser.error('Please provide at least two ' +\
'coordinate files or a custom edges file')
#Open and get coord data (for multiple coords files)
coord_files = opts.coord_fnames
coord_files_valid = validate_coord_files(coord_files)
if not coord_files_valid:
option_parser.error('Every line of every coord file must ' +\
'have the same number of columns.')
num_coord_files = len(coord_files)
data['edges'], data['coord'] = \
get_multiple_coords(coord_files, opts.edges_file, opts.serial)
# if the edges file wasn't supplied, we appended _i to each file's samples
# therefore we now add duplicated samples with _0, _1,... to mapping file
if opts.edges_file is None:
newmap = [data['map'][0]]
for i in xrange(len(coord_files)):
for sample in data['map'][1:]:
newsample = ['%s_%d' %(sample[0],i)]
newsample.extend(sample[1:])
newmap.append(newsample)
data['map'] = newmap
# remove any samples not present in mapping file
remove_unmapped_samples(data['map'],data['coord'],data['edges'])
if(len(data['coord'][1]) == 0):
raise ValueError, '\n\nError: None of the sample IDs in the coordinates files were present in the mapping file.\n'
# process custom axes, if present.
custom_axes = None
if opts.custom_axes:
custom_axes = process_custom_axes(opts.custom_axes)
get_custom_coords(custom_axes, data['map'], data['coord'])
remove_nans(data['coord'])
scale_custom_coords(custom_axes,data['coord'])
# Generate random output file name and create directories
if opts.output_dir:
create_dir(opts.output_dir)
dir_path = opts.output_dir
else:
dir_path='./'
qiime_dir=get_qiime_project_dir()
jar_path=os.path.join(qiime_dir,'qiime/support_files/jar/')
data_dir_path = get_random_directory_name(output_dir=dir_path,
return_absolute_path=False)
try:
os.mkdir(data_dir_path)
except OSError:
pass
jar_dir_path = os.path.join(dir_path,'jar')
try:
os.mkdir(jar_dir_path)
except OSError:
pass
shutil.copyfile(os.path.join(jar_path,'king.jar'), os.path.join(jar_dir_path,'king.jar'))
filepath=coord_files[0]
filename=filepath.strip().split('/')[-1]
try:
action = generate_3d_plots
except NameError:
action = None
#Place this outside try/except so we don't mask NameError in action
if action:
generate_3d_plots(prefs, data, custom_axes,
background_color, label_color,
dir_path, data_dir_path, filename,
ball_scale=ball_scale, arrow_colors=arrow_colors,
user_supplied_edges=not(opts.edges_file is None))
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
prefs, data, background_color, label_color, ball_scale, arrow_colors = \
sample_color_prefs_and_map_data_from_options(opts)
if len(opts.coord_fnames.split(',')) < 2 and opts.edges_file is None:
option_parser.error('Please provide at least two ' +\
'coordinate files or a custom edges file')
#Open and get coord data (for multiple coords files)
coord_files = process_coord_filenames(opts.coord_fnames)
coord_files_valid = validate_coord_files(coord_files)
if not coord_files_valid:
option_parser.error('Every line of every coord file must ' +\
'have the same number of columns.')
num_coord_files = len(coord_files)
data['edges'], data['coord'] = \
get_multiple_coords(coord_files, opts.edges_file, opts.serial)
# if the edges file wasn't supplied, we appended _i to each file's samples
# therefore we now add duplicated samples with _0, _1,... to mapping file
if opts.edges_file is None:
newmap = [data['map'][0]]
for i in xrange(len(coord_files)):
for sample in data['map'][1:]:
newsample = ['%s_%d' %(sample[0],i)]
newsample.extend(sample[1:])
newmap.append(newsample)
data['map'] = newmap
# remove any samples not present in mapping file
remove_unmapped_samples(data['map'],data['coord'],data['edges'])
if(len(data['coord'][1]) == 0):
raise ValueError, '\n\nError: None of the sample IDs in the coordinates files were present in the mapping file.\n'
# process custom axes, if present.
custom_axes = None
if opts.custom_axes:
custom_axes = process_custom_axes(opts.custom_axes)
get_custom_coords(custom_axes, data['map'], data['coord'])
remove_nans(data['coord'])
scale_custom_coords(custom_axes,data['coord'])
# Generate random output file name and create directories
if opts.output_dir:
create_dir(opts.output_dir)
dir_path = opts.output_dir
else:
dir_path='./'
qiime_dir=get_qiime_project_dir()
jar_path=os.path.join(qiime_dir,'qiime/support_files/jar/')
data_dir_path = get_random_directory_name(output_dir=dir_path,
return_absolute_path=False)
try:
os.mkdir(data_dir_path)
except OSError:
pass
jar_dir_path = os.path.join(dir_path,'jar')
try:
os.mkdir(jar_dir_path)
except OSError:
pass
shutil.copyfile(os.path.join(jar_path,'king.jar'), os.path.join(jar_dir_path,'king.jar'))
filepath=coord_files[0]
filename=filepath.strip().split('/')[-1]
try:
action = generate_3d_plots
except NameError:
action = None
#Place this outside try/except so we don't mask NameError in action
if action:
generate_3d_plots(prefs, data, custom_axes,
background_color, label_color,
dir_path, data_dir_path, filename,
ball_scale=ball_scale, arrow_colors=arrow_colors,
user_supplied_edges=not(opts.edges_file is None))
def main():
option_parser, options, args = parse_command_line_parameters(**script_info)
ops = {}
input_dir = options.input_dir
rares = {}
if isdir(input_dir):
rarenames = listdir(input_dir)
rarenames = [r for r in rarenames if not r.startswith(".")]
for r in rarenames:
try:
rarefl = open(path.join(input_dir, r), "U").readlines()
rares[r] = parse_rarefaction(rarefl)
except (IOError):
option_parser.error("Problem with rarefaction file. %s" % exc_info()[1])
exit(0)
else:
try:
input_file = input_dir.split(",")
for i in range(len(input_file)):
input_path = split(input_file[i])[-1]
rarefl = open(input_file[i], "U").readlines()
rares[input_path] = parse_rarefaction(rarefl)
except (IOError):
option_parser.error("Problem with rarefaction file. %s" % exc_info()[1])
exit(0)
if options.imagetype not in ["png", "svg", "pdf"]:
option_parser.error("Supplied extension not supported.")
exit(0)
else:
imagetype = options.imagetype
try:
resolution = int(options.resolution)
except (ValueError):
option_parser.error("Inavlid resolution.")
exit(0)
# Get the command-line options.
prefs, data, background_color, label_color, ball_scale, arrow_colors = sample_color_prefs_and_map_data_from_options(
options
)
# output directory check
if isinstance(options.output_dir, str) and options.output_dir != ".":
if exists(options.output_dir):
output_dir = options.output_dir
else:
try:
create_dir(options.output_dir, False)
output_dir = options.output_dir
except (ValueError):
option_parser.error("Could not create output directory.")
exit(0)
else:
output_dir = get_random_directory_name()
# Generate the plots and html text
ymax = options.ymax
suppress_webpage = options.suppress_html_output
html_output = make_averages(
prefs, data, background_color, label_color, rares, output_dir, resolution, imagetype, ymax, suppress_webpage
)
if html_output:
# Write the html file.
outfile = open(path.join(output_dir, "rarefaction_plots.html"), "w")
outfile.write(html_output)
outfile.close()
def main():
option_parser, opts, args = parse_command_line_parameters(**script_info)
prefs, data, background_color, label_color, ball_scale, arrow_colors= \
sample_color_prefs_and_map_data_from_options(opts)
if opts.output_format == 'invue':
# validating the number of points for interpolation
if (opts.interpolation_points<0):
option_parser.error('The --interpolation_points should be ' +\
'greater or equal to 0.')
# make sure that coord file has internally consistent # of columns
coord_files_valid = validate_coord_files(opts.coord_fname)
if not coord_files_valid:
option_parser.error('Every line of every coord file must ' +\
'have the same number of columns.')
coord_files_valid = validate_coord_files(opts.coord_fname)
if not coord_files_valid:
option_parser.error('Every line of every coord file must ' +\
'have the same number of columns.')
#Open and get coord data
data['coord'] = get_coord(opts.coord_fname, opts.ellipsoid_method)
# remove any samples not present in mapping file
remove_unmapped_samples(data['map'],data['coord'])
# if no samples overlapped between mapping file and otu table, exit
if len(data['coord'][0]) == 0:
print "\nError: OTU table and mapping file had no samples in common\n"
exit(1)
if opts.output_dir:
create_dir(opts.output_dir,False)
dir_path=opts.output_dir
else:
dir_path='./'
filepath=opts.coord_fname
if os.path.isdir(filepath):
coord_files = [fname for fname in os.listdir(filepath) if not \
fname.startswith('.')]
filename = os.path.split(coord_files[0])[-1]
else:
filename = os.path.split(filepath)[-1]
generate_3d_plots_invue(prefs, data, dir_path, filename, \
opts.interpolation_points, opts.polyhedron_points, \
opts.polyhedron_offset)
#finish script
return
# Potential conflicts
if not opts.custom_axes is None and os.path.isdir(opts.coord_fname):
# can't do averaged pcoa plots _and_ custom axes in the same plot
option_parser.error("Please supply either custom axes or multiple coordinate \
files, but not both.")
# check that smoothness is an integer between 0 and 3
try:
ellipsoid_smoothness = int(opts.ellipsoid_smoothness)
except:
option_parser.error("Please supply an integer ellipsoid smoothness \
value.")
if ellipsoid_smoothness < 0 or ellipsoid_smoothness > 3:
option_parser.error("Please supply an ellipsoid smoothness value \
between 0 and 3.")
# check that opacity is a float between 0 and 1
try:
ellipsoid_alpha = float(opts.ellipsoid_opacity)
except:
option_parser.error("Please supply a number for ellipsoid opacity.")
if ellipsoid_alpha < 0 or ellipsoid_alpha > 1:
option_parser.error("Please supply an ellipsoid opacity value \
between 0 and 1.")
# check that ellipsoid method is valid
ellipsoid_methods = ['IQR','sdev']
if not opts.ellipsoid_method in ellipsoid_methods:
option_parser.error("Please supply a valid ellipsoid method. \
Valid methods are: " + ', '.join(ellipsoid_methods) + ".")
# gather ellipsoid drawing preferences
ellipsoid_prefs = {}
ellipsoid_prefs["smoothness"] = ellipsoid_smoothness
ellipsoid_prefs["alpha"] = ellipsoid_alpha
# make sure that coord file has internally consistent # of columns
coord_files_valid = validate_coord_files(opts.coord_fname)
if not coord_files_valid:
option_parser.error('Every line of every coord file must ' +\
'have the same number of columns.')
#Open and get coord data
data['coord'] = get_coord(opts.coord_fname, opts.ellipsoid_method)
# remove any samples not present in mapping file
remove_unmapped_samples(data['map'],data['coord'])
# if no samples overlapped between mapping file and otu table, exit
if len(data['coord'][0]) == 0:
print "\nError: OTU table and mapping file had no samples in common\n"
exit(1)
if opts.taxa_fname != None:
# get taxonomy counts
# get list of sample_ids that haven't been removed
sample_ids = data['coord'][0]
# get taxa summaries for all sample_ids
lineages, taxa_counts = get_taxa(opts.taxa_fname, sample_ids)
data['taxa'] = {}
data['taxa']['lineages'] = lineages
data['taxa']['counts'] = taxa_counts
# get average relative abundance of taxa
data['taxa']['prevalence'] = get_taxa_prevalence(data['taxa']['counts'])
remove_rare_taxa(data['taxa'],nkeep=opts.n_taxa_keep)
# get coordinates of taxa (weighted mean of sample scores)
data['taxa']['coord'] = get_taxa_coords(data['taxa']['counts'],
data['coord'][1])
data['taxa']['coord']
# write taxa coords if requested
if not opts.biplot_output_file is None:
output = make_biplot_scores_output(data['taxa'])
fout = open(opts.biplot_output_file,'w')
fout.write('\n'.join(output))
fout.close()
# process custom axes, if present.
custom_axes = None
if opts.custom_axes:
custom_axes = process_custom_axes(opts.custom_axes)
get_custom_coords(custom_axes, data['map'], data['coord'])
remove_nans(data['coord'])
scale_custom_coords(custom_axes,data['coord'])
if opts.output_dir:
create_dir(opts.output_dir,False)
dir_path=opts.output_dir
else:
dir_path='./'
qiime_dir=get_qiime_project_dir()
jar_path=os.path.join(qiime_dir,'qiime/support_files/jar/')
data_dir_path = get_random_directory_name(output_dir=dir_path,
return_absolute_path=False)
try:
os.mkdir(data_dir_path)
except OSError:
pass
data_file_path=data_dir_path
jar_dir_path = os.path.join(dir_path,'jar')
try:
os.mkdir(jar_dir_path)
except OSError:
pass
shutil.copyfile(os.path.join(jar_path,'king.jar'), os.path.join(jar_dir_path,'king.jar'))
filepath=opts.coord_fname
if os.path.isdir(filepath):
coord_files = [fname for fname in os.listdir(filepath) if not \
fname.startswith('.')]
filename = os.path.split(coord_files[0])[-1]
else:
filename = os.path.split(filepath)[-1]
try:
action = generate_3d_plots
except NameError:
action = None
#Place this outside try/except so we don't mask NameError in action
if action:
action(prefs,data,custom_axes,background_color,label_color,dir_path, \
data_file_path,filename,ellipsoid_prefs=ellipsoid_prefs)
def setUp(self):
# create the temporary input files that will be used
self._files_to_remove = []
self.sample_fasta_file1_data = sample_fasta_file1
self.sample_fasta_file_bad_labels_data =\
sample_fasta_file_bad_labels
self.sample_mapping_file1_data = sample_mapping_file1
self.sample_mapping_file_no_revprimer_header =\
sample_mapping_file_no_revprimer_header
self.sample_mapping_file_bad_revprimer =\
sample_mapping_file_bad_revprimer
self.expected_truncation_default_settings =\
expected_truncation_default_settings
self.expected_truncation_zero_mismatches =\
expected_truncation_zero_mismatches
self.expected_truncation_zero_mismatches_truncate_remove =\
expected_truncation_zero_mismatches_truncate_remove
self.fasta_fp = get_tmp_filename(\
prefix = 'fasta_seqs_',
suffix = '.fna')
seq_file = open(self.fasta_fp, 'w')
seq_file.write(self.sample_fasta_file1_data)
seq_file.close()
self.fasta_badlabels_fp = get_tmp_filename(\
prefix = "fasta_seqs_badlabels_",
suffix = ".fna")
seq_file = open(self.fasta_badlabels_fp, "w")
seq_file.write(self.sample_fasta_file_bad_labels_data)
seq_file.close()
self.mapping_fp = get_tmp_filename(\
prefix = 'sample_mapping_',
suffix = '.txt')
mapping_file = open(self.mapping_fp, "w")
mapping_file.write(self.sample_mapping_file1_data)
mapping_file.close()
self.mapping_bad_header_fp = get_tmp_filename(\
prefix = 'sample_mapping_badheader_',
suffix = ".txt")
mapping_file = open(self.mapping_bad_header_fp, "w")
mapping_file.write(self.sample_mapping_file_no_revprimer_header)
mapping_file.close()
self.mapping_bad_primer_fp = get_tmp_filename(\
prefix = 'sample_mapping_badprimer_',
suffix = ".txt")
mapping_file = open(self.mapping_bad_primer_fp, "w")
mapping_file.write(self.sample_mapping_file_bad_revprimer)
mapping_file.close()
self.output_dir = get_random_directory_name(prefix = '/tmp/')
self.output_dir += '/'
create_dir(self.output_dir)
self._files_to_remove =\
[self.fasta_fp, self.mapping_fp, self.mapping_bad_header_fp,
self.mapping_bad_primer_fp, self.fasta_badlabels_fp]