def update_output(alpha_limit, node_name, dropdown_path, network_layout):
# Change input variables
if alpha_limit=='': alpha_limit=0
if alpha_limit==None: alpha_limit=0
if network_layout=='': network_layout='fruchterman_reingold'
if network_layout==None: network_layout='fruchterman_reingold'
if dropdown_path==None: dropdown_path=''
alpha_limit=np.int(alpha_limit)
ALPHA_SCORE = np.int(alpha_limit)
NODE_NAME = node_name
NETWORK_LAYOUT = network_layout
HNET_OUT = None
# edge1=None
# node1=None
# Print selection dropdownbox
# print(get_d3path(dropdown_path))
# print(get_pklpath(dropdown_path))
print('Dropdown_path path: %s\n' %(dropdown_path))
print('Node name selected : %s\n' %(node_name))
print('Node layout selected : %s\n' %(network_layout))
# Load data
if os.path.isfile(get_pklpath(dropdown_path)):
print('Load picke file')
HNET_OUT=pypickle.load(get_pklpath(dropdown_path))
# HNET_OUT=hnet_out
#print(df['simmatLogP'])
df_edges=HNET_OUT['simmatLogP'].stack().reset_index()
df_edges.columns=['Source', 'Target', 'Weight']
df_edges['Weight']=df_edges['Weight'].astype(float)
edge1 = df_edges.loc[df_edges['Weight']>0,:]
node1 = pd.DataFrame(np.unique(df_edges[['Source','Target']].values.reshape(-1)), columns=['NodeName'])
node1['Label']=node1['NodeName']
node1['Type']=''
# Write to disk
edge1.to_csv(os.path.join(TMP_DIRECTORY+'edge1.csv'), index=False)
node1.to_csv(os.path.join(TMP_DIRECTORY+'node1.csv'), index=False)
# ALPHA_SCORE=[0,np.max(edge1['Weight'].values)]
# Make graph
# if (not isinstance(edge1, type(None))) and (not isinstance(node1, type(None))):
hnet_graph=network_graph(alpha_limit, node_name, network_layout, HNET_OUT=HNET_OUT)
# else:
# print('Select one first in dropdown!')
# Return to screen
return(hnet_graph)
def test_load():
data = [1, 2, 3, 4, 5]
assert pypickle.save('test.pkl', data, overwrite=True)
data_load = pypickle.load('test.pkl')
assert data_load == data
#%%
#out['df_method_comparison']
#%%
dagtype = 'alarm'
#dagtype='asia'
#scoretype='MCC'
columns = ['hnet', 'bayes', 'golden', 'random', 'n_sampling', 'DAG']
df = pd.DataFrame()
df_score = pd.DataFrame()
dfScore = pd.DataFrame(columns=columns)
for n_sampling in arg['n_sampling']:
loadname = 'hnet_' + dagtype + '_' + str(n_sampling) + '.pkl'
d = pypickle.load(os.path.join('../PROJECTS/hnet/results/', loadname))
# F1-score
tmpdf = d['df_method_comparison_scores']
# tmpdf=d['df_method_comparison']
tmpdf['n_sampling'] = d['arg']['n_sampling']
tmpdf['DAG'] = d['arg']['DAG']
df = df.append(tmpdf)
# F1-score
# dfScore=pd.DataFrame(columns=columns)
# score=[]
# score.append([d['hnet_undirected']['f1'], d['bayes_undirected']['f1'], d['golden_truth_undirected']['f1'], d['random_undirected']['f1'], d['arg']['n_sampling'], d['arg']['DAG']])
# dfScore=pd.concat([dfScore, pd.DataFrame(index=['f1_undirected'], data=np.array(score).reshape(1,-1), columns=columns)], axis=0)
# score=[]
# score.append([d['hnet_directed']['f1'], d['bayes_directed']['f1'], d['golden_truth_directed']['f1'], d['random_directed']['f1'], d['arg']['n_sampling'], d['arg']['DAG']])
def process_csv_file(uploaded_filenames, uploaded_file_contents, y_min, alpha, k, excl_background, perc_min_num, specificity, multtest):
"""Save uploaded files and regenerate the file list."""
# Check input parameters
[args, runOK, runtxt]=check_input(uploaded_filenames, uploaded_file_contents, y_min, alpha, k, excl_background, perc_min_num, specificity, multtest)
if runOK==False:
for txt in runtxt: print('[HNET-GUI] %s' %txt)
return(runtxt)
print('alpha:%s' %args['alpha'])
print('y_min:%s' %args['y_min'])
print('k:%s' %args['k'])
print('multtest:%s' %args['multtest'])
print('excl_background:%s' %args['excl_background'])
print('perc_min_num:%s' %args['perc_min_num'])
print('specificity:%s' %args['specificity'])
print('dropna:%s' %args['dropna'])
print('File input: %s' %(args['uploaded_filenames']))
# if uploaded_filenames is not None and uploaded_file_contents is not None:
filepath = save_file(args['uploaded_filenames'], args['uploaded_file_contents'], TMP_DIRECTORY)
[_,filename, _] = hnet.hnet.path_split(args['uploaded_filenames'])
savepath = os.path.join(HNET_DIR_STABLE,filename+'_'+str(args['y_min'])+'_'+str(args['k'])+'_'+str(args['multtest'])+'_'+str(args['specificity'])+'_'+str(args['perc_min_num'])+'_'+str(args['excl_background'])+'/')
d3path = get_d3path(savepath)
pklpath = get_pklpath(savepath)
print('filepath %s' %(filepath))
print('savepath %s' %(savepath))
print('d3path %s' %(d3path))
print('pklpath %s' %(pklpath))
# Progressbar
# mGUI=tk.Tk()
# mGUI.title('HNET '+ filename)
# progressbar = ttk.Progressbar(mGUI, orient='horizontal', length=300)
# progressbar.pack(side=tk.TOP)
# progressbar.config(mode='determinate')
# progressbar.update()
# progressbar['value']=0
# progressbar['maximum']=5
# # Set starting position
# progressbar['value']=progressbar['value']+1 # update bar
# progressbar.update() # update gui
# Make directory
if not os.path.isdir(savepath):
os.mkdir(savepath)
# Make D3js path
if not os.path.isfile(d3path):
# Read file
df = pd.read_csv(filepath)
# Run HNet
# progressbar['value']=progressbar['value']+1 # update bar
# progressbar.update() # update gui
HNET_OUT = hnet.fit(df, alpha=args['alpha'], y_min=args['y_min'], k=args['k'], multtest=args['multtest'], dtypes='pandas', specificity=args['specificity'], perc_min_num=args['perc_min_num'], dropna=args['dropna'], excl_background=args['excl_background'], verbose=3)
# Save pickle file
print('SAVING NETWORK FIGURE: %s' %(savepath))
# progressbar['value']=progressbar['value']+1 # update bar
# progressbar.update() # update gui
HNET_OUT['G'] = hnet.plot_network(HNET_OUT, dist_between_nodes=0.4, scale=2, dpi=250, figsize=[30,20], showfig=False, savepath=os.path.join(savepath,'hnet_network.png'))
# Store pickle file
print('STORE PICKLE')
# progressbar['value']=progressbar['value']+1 # update bar
# progressbar.update() # update gui
pypickle.save(pklpath, HNET_OUT)
#print('MAKE D3GRAPH')
_ = hnet.plot_d3graph(HNET_OUT, savepath=savepath, showfig=False)
else:
print('dir exists, load stuff')
HNET_OUT=pypickle.load(pklpath)
# Open in browser
if os.path.isfile(d3path):
print('OPEN BROWSER')
webbrowser.open(os.path.abspath(d3path), new=2)
print('HNET_DIR_STABLE: %s!' %(HNET_DIR_STABLE))
print('%s done!' %(filename))
print('-----------------------Done!-----------------------')
# progressbar['value']=progressbar['maximum'] # update bar
# progressbar.update() # update gui
# try:
# mGUI.destroy()
# except:
# pass
return(filename)
# %% import pypickle print(dir(pypickle)) print(pypickle.__version__) # %% filepath = 'tes1t.pkl' data = [1, 2, 3, 4, 5] status = pypickle.save(filepath, data, fix_imports=True, overwrite=True) #%% Load file data = pypickle.load(filepath, encoding="latin1") # %%