diff --git a/logic/page_logic.py b/logic/page_logic.py index 2f7e5df17d44833d1a13755f1347189913732fd0..1e8a569af3837cd6f9b57ccf3dd50ee3712c60cf 100644 --- a/logic/page_logic.py +++ b/logic/page_logic.py @@ -32,6 +32,7 @@ def generate_page(md, widget): st.table(make_spec_df(md.measurement_series_types)) if widget == 'Raw Data': + st.markdown('## Index') st.write(md.index_frame) if widget == 'Overview': @@ -51,43 +52,12 @@ def generate_page(md, widget): object_selection = c3.selectbox('Object Selection', object_list) - df = md.measurement_series[selected_measurement_type].df - - downsample_to = 15_000 - should_downsample = False - if len(df) > downsample_to: - st.text('will have to downsample ☹️') - should_downsample = True - from tsdownsample import MinMaxLTTBDownsampler - sampler = MinMaxLTTBDownsampler() - - df = df.loc[df.object == object_selection, ['time'] + measurement_feature_selection] - - fig = make_subplots(rows=2, cols=1, row_heights=[0.9, 0.1], shared_xaxes=True, vertical_spacing=0.05) - - for f in measurement_feature_selection: - # go.scatter.Line() - x, y = df.time, df[f] - if should_downsample: - x = x.values - y = y.values - sidx = sampler.downsample(x, y, n_out=downsample_to) - x = x[sidx] # .iloc[sidx, 'time'] - y = y[sidx] # .iloc[sidx, f] - - fig.add_trace(go.Scattergl(name=f, x=x, y=y, mode='lines'), row=1, col=1) - for e in event_selection: - edf = md.event_series[e].df - edf = edf.loc[edf.object == object_selection] - fig.add_trace( - go.Scatter(name=e, x=edf.time, y=np.zeros_like(edf.time), mode='markers', - marker=dict(size=10, line_width=4, symbol='line-ns-open')), row=2, col=1) - - fig.update_yaxes(row=2, col=1, visible=False) - fig.update_layout(title_text='Timeseries', showlegend=True, - legend=dict(x=0, y=-0.2, orientation='h')) - - st.plotly_chart(fig, use_container_width=True) + selection = plotting.Selection(measurement=selected_measurement_type, events=event_selection, + object=object_selection, features=measurement_feature_selection) + + f = plotting.create_timeseries_plot(md, selection, split_into_subplots=False) + + st.plotly_chart(f, use_container_width=True) def make_spec_df(spec_types): diff --git a/pages/conversion_page.py b/pages/conversion_page.py deleted file mode 100644 index 071a925694478fc77214b3800950763d3316d0b2..0000000000000000000000000000000000000000 --- a/pages/conversion_page.py +++ /dev/null @@ -1,3 +0,0 @@ -import streamlit as st - -st.title('Machine Data File Conversions') diff --git a/pages/export_page.py b/pages/export_page.py new file mode 100644 index 0000000000000000000000000000000000000000..918d8502ba5d5de437ea7032c471704e9a7ba2a4 --- /dev/null +++ b/pages/export_page.py @@ -0,0 +1,56 @@ +import os + +import mdata.core.machine_data_def as mdd +import streamlit as st +from mdata.file_formats.csv import write_machine_data +from mdata.file_formats.hdf import write_machine_data_h5 + +st.title('Machine Data File Export & Conversions') + +if 'uploaded_md' not in st.session_state: + st.write('No data has been uploaded yet') +else: + md: mdd.MachineData = st.session_state['uploaded_md'] + + with st.container(): + st.header('File Format Exports') + + st.subheader('CSV') + c1, c2 = st.columns(2) + with c1: + c11, c12 = st.columns(2) + with c11: + do_csv_export = st.button('Export as CSV') + with c12: + ht = st.selectbox('Header file type', ['json', 'csv']) + with c2: + c21, c22 = st.columns(2) + header_download = c21.empty() + csv_download = c22.empty() + + st.subheader('HDF') + + c1, c2 = st.columns(2) + with c1: + do_hdf_export = st.button('Export as HDF') + with c2: + hdf_download = st.empty() + + if do_csv_export: + write_machine_data('temp/temp', md, header_type=ht) + st.session_state['did_csv_export'] = True + elif do_hdf_export: + write_machine_data_h5('temp/temp.h5', md) + + hf = f'temp/temp_header.{ht}' + df = 'temp/temp_data.csv' + if os.path.exists(hf) and os.path.exists(df): + with open(hf, 'r') as header_file: + header_download.download_button('download header', header_file, f'converted_header.{ht}') + with open(df, 'r') as csv_file: + csv_download.download_button('download csv file', csv_file, 'converted_data.csv') + + h5f = 'temp/temp.h5' + if os.path.exists(h5f): + with open(h5f, 'rb') as hdf_file: + hdf_download.download_button('download h5 file', hdf_file, 'converted.h5') diff --git a/pages/upload_page.py b/pages/upload_page.py index 9a4a4ba2c433d56272275ab1614251612b5d5abe..241805587ccaf25b0dce32fe0bb17dab027f9597 100644 --- a/pages/upload_page.py +++ b/pages/upload_page.py @@ -33,10 +33,12 @@ def import_hdf(f): # @st.experimental_memo def import_csv(hf, df): + header_type = None if 'csv' in hf.type: header_type = 'csv' elif 'json' in hf.type: header_type = 'json' + assert header_type is not None return read_machine_data(hf, df, validity_checking=False, header_type=header_type) @@ -50,10 +52,10 @@ def attempt_import(import_type, **files): hdf_upload = files['hdf_upload'] return 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path = "C:/Users/Leah/PycharmProjects/mdata", develop = true } +# mdata = { git = "git@git-ce.rwth-aachen.de:leah.tgu/mdata.git", branch = "master" } seaborn = "^0.12.2" plotly = "^5.14.1" tsdownsample = "^0.1.2" diff --git a/streamlit_app.py b/streamlit_app.py index 97be24143326ec0c122f0cefc8a8be65e2c73727..c5fbc3122c489a5b18e5986a712f2915d9a3e8ec 100644 --- a/streamlit_app.py +++ b/streamlit_app.py @@ -8,7 +8,10 @@ st.title('Welcome to the Machine Data Demo Website') got_to_demo = st.button('Got to Demo') go_to_file_viewer = st.button('Got to File Viewer') +go_to_exporter = st.button('Got to Exporter') if got_to_demo: switch_page('demo_page') elif go_to_file_viewer: switch_page('upload_page') +elif go_to_exporter: + switch_page('export_page')