def make_file(n_clicks, fig: dict, filename: str):
if n_clicks:
fig = go.Figure(fig)
if not filename:
filename = fig.layout.title.text
if not filename:
filename = 'DashFigure'
fname = filename + f'.{file_type}'
bytes_ = False
if file_type == 'html':
data = fig.to_html()
mtype = 'text/html'
elif file_type == 'jpg':
fig.write_image('temp/dash_temp.jpg', format='jpg')
return send_file('temp/dash_temp.jpg',
filename=fname,
mime_type='image/jpg')
elif file_type == 'svg':
fig.write_image('temp/dash_temp.svg', format='svg')
return send_file('temp/dash_temp.svg', fname,
'image/svg+xml')
else:
raise ValueError(f'{file_type} not supported')
return dict(content=data,
filename=fname,
mimetype=mtype,
byte=bytes_)
else:
raise PreventUpdate
def test_result(n_clicks, test_data, co, nox, hc, val_number):
ctx = dash.callback_context
changed_id = ctx.triggered[0]['prop_id'].split('.')[0]
if changed_id =='submit_button':
layout, rules_st, puc_st = result_layout(test_data, co, nox, hc)
if rules_st == 'Passed' and puc_st == 'Passed':
make_certificate(val_number)
upload_test_result(val_number, True)
return layout, send_file(val_number + '.pdf')
else:
upload_test_result(val_number, False)
return layout, send_file('failed_certi.pdf')
def download_results(n_clicks, n_clicks_peakmax, wdir):
if (n_clicks is None) and (n_clicks_peakmax is None):
raise PreventUpdate
ctx = dash.callback_context
prop_id = ctx.triggered[0]['prop_id']
if prop_id == 'res-download.n_clicks':
fn = T.get_results_fn(wdir)
workspace = os.path.basename(wdir)
return [
send_file(fn,
filename=f'{T.today()}-{workspace}_MINT-results.csv')
]
elif prop_id == 'res-download-peakmax.n_clicks':
workspace = os.path.basename(wdir)
results = T.get_results(wdir)
df = results.pivot_table('peak_max', 'peak_label', 'ms_file')
df.columns = [P(x).with_suffix('') for x in df.columns]
buffer = T.df_to_in_memory_excel_file(df)
return [
send_bytes(
buffer,
filename=f'{T.today()}-{workspace}_MINT-peak-max.xlsx')
]
def cb_downloadspdx(button, spdxfile):
if button is None:
raise dash.exceptions.PreventUpdate
filepath = os.path.join('SPDX', spdxfile)
return send_file(filepath)
def download_nodes_csv(n_clicks, json_df):
if n_clicks:
downloads_dir = os.path.join(os.getcwd(), 'downloads')
if not os.path.exists(downloads_dir):
os.mkdir(downloads_dir)
nodes_df = pd.read_json(json_df)
abs_filename = os.path.join(downloads_dir, 'node_details.csv')
nodes_df.to_csv(abs_filename, index=False)
return send_file(abs_filename)
def download_graphml(n_clicks, json_str_sub_network):
if n_clicks:
downloads_dir = os.path.join(os.getcwd(), 'downloads')
if not os.path.exists(downloads_dir):
os.mkdir(downloads_dir)
rel_filename = os.path.join('downloads', 'network.graphml')
abs_filename = os.path.join(os.getcwd(), rel_filename)
sub_network = nx.node_link_graph(json.loads(json_str_sub_network))
nx.write_graphml(sub_network, path=abs_filename)
return send_file(abs_filename)
def download_file(n_clicks, data, rows):
if n_clicks == 0:
raise dash.exceptions.PreventUpdate
directory = os.getcwd() + "/data/"
files = [data[r]['Filename'] for r in rows]
if len(files) == 1:
return send_file(directory + files[0]), ''
else:
# create a ZipFile object
zip_obj = ZipFile(directory + 'measurements.zip', 'w')
# Add multiple files to the zip
for f in files:
zip_obj.write(directory + f, arcname=f)
# close the Zip File
zip_obj.close()
return send_file(directory + "measurements.zip",
mime_type='application/zip'), ''
def download_enrichment_results(n_clicks, filename, enrichment_results):
"""Generates and sends a csv file of enrichment results for download."""
if n_clicks:
# Create downloads directory if there isn't one
downloads_dir = os.path.join(os.getcwd(), 'downloads')
if not os.path.exists(downloads_dir):
os.mkdir(downloads_dir)
rel_filename = os.path.join('downloads',
'{}_enrichment.csv'.format(filename[:-4]))
abs_filename = os.path.join(os.getcwd(), rel_filename)
enrichment = pd.read_json(enrichment_results)
enrichment.to_csv(abs_filename, index=False)
return send_file(abs_filename)
def func(n_clicks):
return send_file("./protein_coding_genes_novel_predictions.csv",
filename='protein coding.csv')
def func(n_clicks):
return send_file("./bioembeds_nonsmote_pos_preds.csv",
filename='bioembed preds.csv')
def download_file(n, uploaded_filename):
"""Save uploaded files and regenerate the file list."""
if n > 0:
file_in_question = 'new_{}'.format(uploaded_filename[0])
# print(file_in_question)
return send_file('uploaded_img/{}'.format(file_in_question))
def generate_raw_csv(clicks, table_data):
print("GENERATE RAW CSV")
if table_data:
return send_file("data/recent_query.csv")
def func(n_clicks):
if n_clicks is None:
raise PreventUpdate
else:
return send_file("assets/data_apls.csv")
def func(n_clicks):
return send_file("/home/emher/Documents/Untitled.png")
def func(n_clicks):
return send_file("results/hgv1_mouse_hormone_src_tgt_genes.json", filename = 'hgv1_mouse_hormone_src_tgt_genes.json')
def func(n_clicks):
return send_file("./lncRNA_novel_predictions.csv", filename='lncRNA.csv')
def func(n_clicks):
return send_file(
"results/protein_coding_genes_novel_predictions_threshold.csv",
filename='protein coding.csv')
def func(n_clicks):
return send_file("results/lncRNA_novel_predictions_threshold.csv",
filename='lncRNA.csv')
def generate_raw_csv(clicks, table_data):
print("GENERATE ANALYSIS CSV")
if table_data:
return send_file("data/recent_analysis.csv")
def func(n_clicks):
return send_file("./hgv1_hormone_src_tgt_genes.json",
filename='HGv1_Gene.json')
def func(n_clicks):
return send_file("./download/endereços.json")
def func(n_clicks):
return send_file("./source_target_tissue.json",
filename='HGv1_Tissue.json')
def update_link(n_clicks, wdir):
if n_clicks is None:
raise PreventUpdate
fn = T.get_results_fn(wdir)
workspace = os.path.basename( wdir )
return [send_file(fn, filename=f'{T.today()}-{workspace}_MINT-results.csv')]
def return_pdf(n_clicks):
return send_file("./samples/template.xlsx")
