def genes_list(colmun, colmun_f, colmun_id, funcs, id_list, config):
import paplot.subcode.tools as tools
import paplot.convert as convert
sept = tools.config_getstr(config, "result_format_mutation", "sept_gene")
genes_di = {}
ids_di = {}
for i in range(len(colmun)):
if (colmun_f[i] in funcs) is False:
continue
row = colmun[i].replace('"', '')
splt = []
if sept == "":
splt.append(row)
else:
splt = row.split(sept)
for gene in splt:
if gene == "":
continue
if gene in ids_di.keys():
if (colmun_id[i] in ids_di[gene]) is True:
continue
else:
ids_di[gene].append(colmun_id[i])
else:
ids_di.update({gene: [colmun_id[i]]})
value = 1
if gene in genes_di.keys():
value = genes_di[gene] + 1
genes_di.update({gene: value})
# gene list
use_gene_rate = config.getfloat("mutation", "use_gene_rate")
limited_list = convert.text_to_list(
tools.config_getstr(config, "mutation", "limited_gene"), ",")
nouse_list = convert.text_to_list(
tools.config_getstr(config, "mutation", "nouse_gene"), ",")
genes = []
for key in genes_di:
if len(limited_list) > 0 and convert.fnmatch_list(
key, limited_list) is False:
continue
if convert.fnmatch_list(key, nouse_list):
continue
if genes_di[key] < float(len(id_list)) * use_gene_rate:
continue
genes.append(key)
genes.sort()
return genes
def genes_list(colmun, colmun_f, colmun_id, funcs, Ids, config):
import paplot.subcode.tools as tools
import paplot.convert as convert
sept = tools.config_getstr(config, "result_format_mutation", "sept_gene")
use_gene_rate = config.getfloat("mut", "use_gene_rate")
limited_list = convert.text_to_list(tools.config_getstr(config, "mut", "limited_genes"), ",")
nouse_list = convert.text_to_list(tools.config_getstr(config, "mut", "nouse_genes"), ",")
genes_di = {}
ids_di = {}
for i in range(len(colmun)):
if (colmun_f[i] in funcs) == False: continue
row = colmun[i].replace('"', '')
splt = []
if sept == "": splt.append(row)
else: splt = row.split(sept)
for gene in splt:
if gene == "": continue
if gene in ids_di.keys():
if (colmun_id[i] in ids_di[gene]) == True: continue
else: ids_di[gene].append(colmun_id[i])
else:
ids_di.update({gene: [colmun_id[i]]})
value = 1
if gene in genes_di.keys():
value = genes_di[gene] + 1
genes_di.update({gene: value})
# gene list
genes = []
for key in genes_di:
if len(limited_list) > 0:
if (key in limited_list) == False: continue
if key in nouse_list: continue
if genes_di[key] < float(len(Ids))*use_gene_rate: continue
genes.append(key)
genes.sort()
return genes
def load_subdata(ids, sec, config):
import os
import paplot.subcode.tools as tools
import paplot.convert as convert
import paplot.color as color
input_file = tools.config_getpath(config, sec, "path", default = "")
if os.path.exists(input_file) == False:
print ("[ERROR] file is not exist. %s" % input_file)
return None
sept = tools.config_getstr(config, sec, "sept").replace("\\t", "\t").replace("\\n", "\n").replace("\\r", "\r")
mode = tools.config_getstr(config, sec, "mode")
comment = tools.config_getstr(config, sec, "comment")
title = tools.config_getstr(config, sec, "title")
label = []
item = []
colors_n_di = {}
colors_h_di = {}
for name_set in tools.config_getstr(config, sec, "name_set").split(","):
name_set_split = convert.text_to_list(name_set, ":")
for i in range(len(name_set_split)):
text = name_set_split[i]
if i == 0:
item.append(text)
if len(name_set_split) == 1:
label.append(text)
elif i == 1:
label.append(text)
elif i == 2:
colors_n_di[name_set_split[0]] = color.name_to_value(text)
elif i == 3:
colors_h_di[name_set_split[0]] = color.name_to_value(text)
# fill in undefined items
colors_n_di = color.create_color_dict(item, colors_n_di, color.osaka_subway_colors)
colors_h_di2 = {}
for key in colors_n_di:
if key in colors_h_di: continue
colors_h_di2[key] = color.saturation_down(colors_n_di[key])
# dict to value
colors_n = []
for key in item:
colors_n.append(colors_n_di[key])
if mode == "range":
item.remove(item[0])
header = []
if tools.config_getboolean(config, sec, "header") == True:
pos_value = -1
pos_id = -1
else:
pos_value = tools.config_getint(config, sec, "col_value")-1
pos_id = tools.config_getint(config, sec, "col_ID")-1
header = ["",""]
# copy id_list for find check
unlookup = []
for iid in ids:
unlookup.append(iid)
# read
data_text = ""
values = []
for line in open(input_file):
line = line.strip()
if len(line.replace(sept, "")) == 0:
continue
if comment != "" and line.find(comment) == 0:
continue
if len(header) == 0:
header = convert.text_to_list(line,sept)
try:
colname = tools.config_getstr(config, sec, "col_value")
pos_value = header.index(colname)
colname = tools.config_getstr(config, sec, "col_ID")
pos_id = header.index(colname)
except Exception as e:
print(e.message)
return None
continue
cols = convert.text_to_list(line,sept)
if (cols[pos_id] in ids) == False: continue
else: unlookup.remove(cols[pos_id])
id_pos = ids.index(cols[pos_id])
if mode == "fix":
if cols[pos_value] in item:
data_text += subdata_data_template.format(id = id_pos, item = item.index(cols[pos_value]))
else:
print("[" + sec + "] name_set: data is undefined." + cols[pos_value] + "\n")
continue
elif mode == "range" or mode == "gradient":
try:
values.append(float(cols[pos_value]))
except Exception as e:
print(colname + ": data type is invalid.\n" + e.message)
continue
data_text += subdata_data_template.format(id = id_pos, item = cols[pos_value])
if len(unlookup) > 0:
print("[WARNING] can't find IDs subplot data.")
print(unlookup)
if mode == "gradient" and len(values) > 0:
item[0] = min(values)
item[1] = max(values)
return [data_text, item, colors_n, label, title]
def convert_tojs(input_file, output_file, positions, config):
import os
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "result_format_mutation", "sept"), \
comment = tools.config_getstr(config, "result_format_mutation", "comment") \
)
except Exception as e:
print ("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print ("no data %s" % input_file)
return None
# func replace
for f in range(len(df.data)):
func_pos = df.name_to_index(cols_di["group"])
if df.data[f][func_pos] == "":
df.data[f][func_pos] = "_blank_"
[funcs, colors_n] = convert.group_list(df.column(cols_di["group"]), "mutation", "group", config)
# ID list
id_list = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": id_list.append(iid)
id_list = list(set(id_list))
id_list.sort()
# gene list
genes = genes_list(df.column(cols_di["gene"]), \
df.column(cols_di["group"]), \
df.column(cols_di["id"]), \
funcs, id_list, config)
option_keys = tools.dict_keys(cols_di)
option_keys.remove("id")
option_keys.remove("group")
option_keys.remove("gene")
# mutation list
f = open(output_file, "w")
f.write(js_header)
f.write(js_mutations_1)
mutations = {}
tooltips = {}
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
if (iid in mutations) == False:
mutations[iid] = {}
tooltips[iid] = {}
func_split = convert.text_to_list(row[df.name_to_index(cols_di["group"])], \
tools.config_getstr(config, "result_format_mutation", "sept_group"))
tooltip_items = []
for k in range(len(option_keys)):
key = option_keys[k]
if cols_di[key] == "": continue
tooltip_items.append(row[df.name_to_index(cols_di[key])])
for func in func_split:
if (func in mutations[iid]) == False:
mutations[iid][func] = {}
tooltips[iid][func] = {}
gene_split = convert.text_to_list(row[df.name_to_index(cols_di["gene"])], \
tools.config_getstr(config, "result_format_mutation", "sept_gene"))
for gene in gene_split:
if (gene in mutations[iid][func]) == False:
mutations[iid][func][gene] = 1
tooltips[iid][func][gene] = []
else:
mutations[iid][func][gene] += 1
tooltips[iid][func][gene].append(tooltip_items)
mutations_sum = 0
for iid in tools.dict_keys(mutations):
for func in tools.dict_keys(mutations[iid]):
for gene in tools.dict_keys(mutations[iid][func]):
idx_i = convert.value_to_index(id_list, iid, -1)
idx_f = convert.value_to_index(funcs, func, -1)
idx_g = convert.value_to_index(genes, gene, -1)
if idx_i >= 0 and idx_f >= 0 and idx_g >= 0:
tooltip_items = ""
for tips in tooltips[iid][func][gene]:
tooltip_items += "[" + convert.list_to_text(tips) + "],"
f.write(mu_mutations_template.format(ID = idx_i, \
func = idx_f , \
gene = idx_g, \
num = mutations[iid][func][gene],
tooltip = tooltip_items))
mutations_sum += mutations[iid][func][gene]
f.write(js_mutations_2.format(mutations_sum = mutations_sum))
# write id, func, gene ... list
f.write(js_dataset.format(
Ids = convert.list_to_text(id_list), \
genes = convert.list_to_text(convert.list_prohibition(genes)), \
funcs = convert.list_to_text(convert.list_prohibition(funcs)), \
func_colors_n = convert.list_to_text(colors_n), \
mutation_header = convert.list_to_text(option_keys), \
checker_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_checker_title"), \
checker_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_checker_partial"), \
gene_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_gene_title"), \
gene_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_gene_partial"), \
id_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_id_title"), \
id_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_id_partial"), \
))
dataset = {}
##### subdata #####
f.write(js_subdata_1)
subdata = []
counter = 0
for sec in config.sections():
if sec.startswith("mutation_subplot_type1_"):
ret_val = load_subdata(id_list, sec, config)
if ret_val == None: continue
[data_text, item, colors_n, label, title] = ret_val
name = "sub%d" % (counter)
pos = 1
counter += 1
elif sec.startswith("mutation_subplot_type2_"):
ret_val = load_subdata(id_list, sec, config)
if ret_val == None: continue
[data_text, item, colors_n, label, title] = ret_val
name = "sub%d" % (counter)
pos = 2
counter += 1
else: continue
f.write(subdata_template.format(name = name, \
title = title, \
type = tools.config_getstr(config, sec, "mode"), \
item = convert.list_to_text(item), \
label = convert.list_to_text(label), \
colors_n = convert.list_to_text(colors_n), \
data = data_text ))
subdata.append({"pos":pos, "label":label, "color":colors_n, "title": title})
f.write(js_subdata_2)
##### functions #####
f_template = open(os.path.dirname(os.path.abspath(__file__)) + "/templates/data_mutation.js")
js_function = f_template.read()
f_template.close()
f.write(js_function)
f.write(js_footer)
f.close()
dataset["subdata"] = subdata
return dataset
def convert_tojs(input_file, output_file, positions, config):
import os
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
import paplot.color as color
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "result_format_qc", "sept"), \
comment = tools.config_getstr(config, "result_format_qc", "comment") \
)
except Exception as e:
print("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print("no data %s" % input_file)
return None
# chart list
plots_text = ""
plots_option = []
config_sections = config.sections()
config_sections.sort()
if "qc_chart_brush" in config_sections:
config_sections.remove("qc_chart_brush")
config_sections.insert(0, "qc_chart_brush")
for sec in config.sections():
if not sec.startswith("qc_chart_"):
continue
chart_id = sec.replace("qc_chart_", "chart_")
stack_id = []
label = []
colors_di = {}
counter = 0
for name_set in tools.config_getstr(config, sec,
"name_set").split(","):
name_set_split = convert.text_to_list(name_set, ":")
if len(name_set_split) == 0:
continue
stack_id.append("stack" + str(counter))
label.append(name_set_split[0])
if len(name_set_split) > 1:
colors_di[name_set_split[0]] = color.name_to_value(
name_set_split[1])
counter += 1
# fill in undefined items
colors_di = color.create_color_dict(label, colors_di,
color.metro_colors)
# dict to value
colors_li = []
for key in label:
colors_li.append(colors_di[key])
plots_text += plot_template.format(
chart_id = chart_id, \
title = tools.config_getstr(config, sec, "title"), \
title_y = tools.config_getstr(config, sec, "title_y"), \
stack = convert.pyformat_to_jstooltip_text(cols_di, config, sec, "result_format_qc", "stack"), \
stack_id = convert.list_to_text(stack_id), \
label = convert.list_to_text(label), \
color = convert.list_to_text(colors_li), \
tooltip = convert.pyformat_to_jstooltip_text(cols_di, config, sec, "result_format_qc", "tooltip_format"), \
)
plots_option.append(chart_id)
# ID list
id_list = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": id_list.append(iid)
id_list = list(set(id_list))
id_list.sort()
# header
headers = tools.dict_keys(cols_di)
f = open(output_file, "w")
f.write(js_header)
f.write(js_dataset.format(IDs = convert.list_to_text(id_list), \
header = convert.list_to_text(headers), \
plots = plots_text))
f.write(js_data1)
# values
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
values = ""
for item in headers:
if len(values) > 0:
values += ","
val = row[df.name_to_index(cols_di[item])]
if type(val) == type(""):
values += "'" + val + "'"
elif type(val) == type(0.0):
values += str('%.2f' % val)
else:
values += str(val)
f.write("[" + values + "],")
f.write(js_data2)
f_template = open(
os.path.dirname(os.path.abspath(__file__)) + "/templates/data_qc.js")
js_function = f_template.read()
f_template.close()
f.write(js_function)
f.write(js_footer)
f.close()
return {"plots": plots_option}
def convert_tojs(input_file, output_file, positions, config):
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
import paplot.color as color
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "merge_format_qc", "sept"), \
comment = tools.config_getstr(config, "result_format_qc", "comment") \
)
except Exception as e:
print ("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print ("no data %s" % input_file)
return None
# chart list
plots_text = ""
plots_option = []
config_sections = config.sections()
config_sections.sort()
if "qc_chart_brush" in config_sections:
config_sections.remove("qc_chart_brush")
config_sections.insert(0, "qc_chart_brush")
for sec in config.sections():
if not sec.startswith("qc_chart_"):
continue
chart_id = sec.replace("qc_chart_", "chart_")
stack_id = []
label = []
colors_di = {}
counter = 0
for name_set in tools.config_getstr(config, sec, "name_set").split(","):
name_set_split = convert.text_to_list(name_set, ":")
if len(name_set_split) == 0:
continue
stack_id.append("stack" + str(counter))
label.append(name_set_split[0])
if len(name_set_split) > 1:
colors_di[name_set_split[0]] = color.name_to_value(name_set_split[1])
counter += 1
# fill in undefined items
colors_di = color.create_color_dict(label, colors_di, color.metro_colors)
# dict to value
colors_li = []
for key in label:
colors_li.append(colors_di[key])
plots_text += plot_template.format(
chart_id = chart_id, \
title = tools.config_getstr(config, sec, "title"), \
title_y = tools.config_getstr(config, sec, "title_y"), \
stack = convert.pyformat_to_jstooltip_text(cols_di, config, sec, "result_format_qc", "stack"), \
stack_id = convert.list_to_text(stack_id), \
label = convert.list_to_text(label), \
color = convert.list_to_text(colors_li), \
tooltip = convert.pyformat_to_jstooltip_text(cols_di, config, sec, "result_format_qc", "tooltip_format"), \
)
plots_option.append(chart_id)
# ID list
Ids = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": Ids.append(iid)
Ids = list(set(Ids))
Ids.sort()
# header
headers = cols_di.keys()
headers.sort()
f = open(output_file, "w")
f.write(js_header)
f.write(js_dataset.format(IDs = convert.list_to_text(Ids), \
header = convert.list_to_text(headers), \
plots = plots_text))
f.write(js_data1)
# values
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
values = ""
for item in headers:
if len(values) > 0:
values += ","
val = row[df.name_to_index(cols_di[item])]
if type(val) == type(""):
values += "'" + val + "'"
elif type(val) == type(0.0):
values += str('%.2f' % val)
else:
values += str(val)
f.write("[" + values + "],")
f.write(js_data2)
f.write(js_function)
f.close()
return {"plots": plots_option}
def load_subdata(ids, sec, config):
import os
import paplot.subcode.tools as tools
import paplot.convert as convert
import paplot.color as color
input_file = tools.config_getpath(config, sec, "path", default = "../../example/sample_summary.csv")
if os.path.exists(input_file) == False:
print ("[ERROR] file is not exist. %s" % input_file)
return None
sept = tools.config_getstr(config, sec, "sept")
mode = tools.config_getstr(config, sec, "mode")
comment = tools.config_getstr(config, sec, "comment")
title = tools.config_getstr(config, sec, "title")
label = []
item = []
colors_n_di = {}
colors_h_di = {}
for name_set in tools.config_getstr(config, sec, "name_set").split(","):
name_set_split = convert.text_to_list(name_set, ":")
for i in range(len(name_set_split)):
text = name_set_split[i]
if i == 0:
item.append(text)
if len(name_set_split) == 1:
label.append(text)
elif i == 1:
label.append(text)
elif i == 2:
colors_n_di[name_set_split[0]] = color.name_to_value(text)
elif i == 3:
colors_h_di[name_set_split[0]] = color.name_to_value(text)
# fill in undefined items
colors_n_di = color.create_color_dict(item, colors_n_di, color.osaka_subway_colors)
colors_h_di2 = {}
for key in colors_n_di:
if colors_h_di.has_key(key): continue
colors_h_di2[key] = color.Saturation_down(colors_n_di[key])
# dict to value
colors_n = []
for key in item:
colors_n.append(colors_n_di[key])
if mode == "range":
item.remove(item[0])
header = []
if tools.config_getboolean(config, sec, "header") == True:
pos_value = -1
pos_ID = -1
else:
pos_value = tools.config_getint(config, sec, "col_value")
pos_ID = tools.config_getint(config, sec, "col_ID")
header = ["",""]
# copy Ids for find check
unlookup = []
for iid in ids:
unlookup.append(iid)
# read
data_text = ""
values = []
for line in open(input_file):
line = line.strip()
if len(line.replace(sept, "")) == 0:
continue
if comment != "" and line.find(comment) == 0:
continue
if len(header) == 0:
header = convert.text_to_list(line,sept)
try:
colname = tools.config_getstr(config, sec, "col_value")
pos_value = header.index(colname)
colname = tools.config_getstr(config, sec, "col_ID")
pos_ID = header.index(colname)
except Exception as e:
print(e.message)
return None
continue
cols = convert.text_to_list(line,sept)
if (cols[pos_ID] in ids) == False: continue
else: unlookup.remove(cols[pos_ID])
id_pos = ids.index(cols[pos_ID])
if mode == "fix":
if cols[pos_value] in item:
data_text += subdata_data_template.format(id = id_pos, item = item.index(cols[pos_value]))
else:
print("[" + sec + "] name_set: data is undefined." + cols[pos_value] + "\n")
continue
elif mode == "range":
try:
values.append(float(cols[pos_value]))
except Exception as e:
print(colname + ": data type is invalid.\n" + e.message)
continue
data_text += subdata_data_template.format(id = id_pos, item = cols[pos_value])
elif mode == "gradient":
try:
values.append(float(cols[pos_value]))
except Exception as e:
print(colname + ": data type is invalid.\n" + e.message)
continue
data_text += subdata_data_template.format(id = id_pos, item = cols[pos_value])
if len(unlookup) > 0:
print("[WARNING] can't find IDs subplot data.")
print(unlookup)
if mode == "gradient" and len(values) > 0:
item[0] = min(values)
item[1] = max(values)
return [data_text, item, colors_n, label, title]
def convert_tojs(input_file, output_file, positions, config):
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "merge_format_mutation", "sept"), \
comment = tools.config_getstr(config, "result_format_mutation", "comment") \
)
except Exception as e:
print ("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print ("no data %s" % input_file)
return None
# func replace
for f in range(len(df.data)):
func_pos = df.name_to_index(cols_di["func"])
func = df.data[f][func_pos]
df.data[f][func_pos] = func.replace(" ", "_")
if func == "":
df.data[f][func_pos] = "_blank_"
[funcs, colors_n] = convert.group_list(df.column(cols_di["func"]), "mut", "func", config)
# ID list
Ids = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": Ids.append(iid)
Ids = list(set(Ids))
Ids.sort()
genes = genes_list(df.column(cols_di["gene"]), \
df.column(cols_di["func"]), \
df.column(cols_di["id"]), \
funcs, Ids, config)
option_keys = cols_di.keys()
option_keys.remove("id")
option_keys.remove("func")
option_keys.remove("gene")
f = open(output_file, "w")
f.write(js_header \
+ js_dataset.format(Ids = convert.list_to_text(Ids), \
genes = convert.list_to_text(genes), \
funcs = convert.list_to_text(funcs), \
func_colors_n = convert.list_to_text(colors_n), \
mutation_header = convert.list_to_text(option_keys), \
checker_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_checker_title"), \
checker_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_checker_partial"), \
gene_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_gene_title"), \
gene_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_gene_partial"), \
id_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_id_title"), \
id_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_id_partial"), \
))
# mutation list
f.write(js_mutations_1)
mutations = {}
tooltips = {}
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
if (iid in mutations) == False:
mutations[iid] = {}
tooltips[iid] = {}
func_split = convert.text_to_list(row[df.name_to_index(cols_di["func"])], \
tools.config_getstr(config, "result_format_mutation", "sept_func"))
tooltip_items = []
for k in range(len(option_keys)):
key = option_keys[k]
if cols_di[key] == "": continue
tooltip_items.append(row[df.name_to_index(cols_di[key])])
for func in func_split:
if (func in mutations[iid]) == False:
mutations[iid][func] = {}
tooltips[iid][func] = {}
gene_split = convert.text_to_list(row[df.name_to_index(cols_di["gene"])], \
tools.config_getstr(config, "result_format_mutation", "sept_gene"))
for gene in gene_split:
if (gene in mutations[iid][func]) == False:
mutations[iid][func][gene] = 1
tooltips[iid][func][gene] = []
else:
mutations[iid][func][gene] += 1
tooltips[iid][func][gene].append(tooltip_items)
mutations_sum = 0
for iid in mutations:
for func in mutations[iid]:
for gene in mutations[iid][func]:
idx_i = convert.value_to_index(Ids, iid, -1)
idx_f = convert.value_to_index(funcs, func, -1)
idx_g = convert.value_to_index(genes, gene, -1)
if idx_i >= 0 and idx_f >= 0 and idx_g >= 0:
tooltip_items = ""
for tips in tooltips[iid][func][gene]:
tooltip_items += "[" + convert.list_to_text(tips) + "],"
f.write(mu_mutations_template.format(ID = idx_i, \
func = idx_f , \
gene = idx_g, \
num = mutations[iid][func][gene],
tooltip = tooltip_items))
mutations_sum += mutations[iid][func][gene]
f.write(js_mutations_2.format(mutations_sum = mutations_sum))
dataset = {"func":funcs, "color":colors_n}
##### subdata #####
f.write(js_subdata_1)
subdata = []
counter = 0
for sec in config.sections():
if sec.startswith("mut_subplot_type1_"):
ret_val = load_subdata(Ids, sec, config)
if ret_val == None: continue
[data_text, item, colors_n, label, title] = ret_val
name = "sub%d" % (counter)
pos = 1
counter += 1
elif sec.startswith("mut_subplot_type2_"):
ret_val = load_subdata(Ids, sec, config)
if ret_val == None: continue
[data_text, item, colors_n, label, title] = ret_val
name = "sub%d" % (counter)
pos = 2
counter += 1
else: continue
f.write(subdata_template.format(name = name, \
title = title, \
type = tools.config_getstr(config, sec, "mode"), \
item = convert.list_to_text(item), \
label = convert.list_to_text(label), \
colors_n = convert.list_to_text(colors_n), \
data = data_text ))
subdata.append({"pos":pos, "label":label, "color":colors_n, "title": title})
f.write(js_subdata_2)
##### functions #####
f.write(js_function)
f.close()
dataset["subdata"] = subdata
return dataset
