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fixing make sure runing everything smooth #3

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140f4a8
fix dependencies
Arslan-Siraj Aug 1, 2025
ef4e95c
pyopenms from pip
Arslan-Siraj Aug 1, 2025
7c372b3
fix plotting
Arslan-Siraj Aug 1, 2025
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6 changes: 3 additions & 3 deletions Dockerfile
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Original file line number Diff line number Diff line change
Expand Up @@ -79,9 +79,9 @@ RUN make -j4 TOPP
RUN rm -rf src doc CMakeFiles

# Build pyOpenMS wheels and install via pip.
RUN make -j4 pyopenms
WORKDIR /openms-build/pyOpenMS
RUN pip install dist/*.whl
#RUN make -j4 pyopenms
#WORKDIR /openms-build/pyOpenMS
#RUN pip install dist/*.whl


WORKDIR /
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211 changes: 95 additions & 116 deletions content/Result_2.py
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Expand Up @@ -6,6 +6,7 @@
from st_aggrid import GridOptionsBuilder, AgGrid, GridUpdateMode, ColumnsAutoSizeMode
from src.common.captcha_ import *
from pyopenms import *
from scipy.spatial import cKDTree

params = page_setup()

Expand Down Expand Up @@ -106,141 +107,119 @@ def remove_substrings(original_string, substrings_to_remove):

#with View Results tab
with tabs[0]:
#make sure load all example result files
load_example_result_files()

tabs_ = st.tabs(["Sage Output Table", "PTMs Table"])
# take all .idXML files in current session files; .idXML is CSMs
session_files = [f.name for f in Path(st.session_state.workspace,"result-files").iterdir() if (f.name.endswith(".idXML"))]

# select box to select .idXML file to see the results
selected_file = st.selectbox("choose a currently protocol file to view",session_files)

#current workspace session path
workspace_path = Path(st.session_state.workspace)

## selected .idXML file
tabs_ = st.tabs(["Sage Output Table", "PTMs Table"])

#with CSMs Table
with tabs_[0]:
load_example_result_files()
# take all .idXML files in current session files; .idXML is CSMs
session_files = [f.name for f in Path(st.session_state.workspace,"result-files").iterdir() if (f.name.endswith(".idXML"))]
mzML_files = [f2.name for f2 in Path(st.session_state.workspace,"mzML-files").iterdir() if (f2.name.endswith(".mzML"))]
# select box to select .idXML file to see the results
selected_file = st.selectbox("choose an output idXML file to view",session_files)
selected_mzML_file = st.selectbox("choose the corresponding mzML file for annotation",mzML_files)

#current workspace session path
workspace_path = Path(st.session_state.workspace)
#tabs on page to show different results

if selected_file:
#st.write("CSMs Table")
#take all CSMs as dataframe
if selected_file:

with tabs_[0]:

CSM_= readAndProcessIdXML(workspace_path / "result-files" /f"{selected_file}")
#st.write(selected_file)

##TODO setup more better/effiecient
# Remove the out pattern of idxml
#file_name_wout_out = remove_substrings(selected_file, nuxl_out_pattern)

if (selected_file.find("Example") != -1):
file_name_wout_out = "Example_RNA_UV_XL"
file_name_wout_out = "Example"
else:
file_name_wout_out = selected_file.replace(".idXML", "")


if selected_mzML_file:
MS2 = process_mzML_file(os.path.join(Path.cwd().parent , str(st.session_state.workspace)[3:] , "mzML-files" ,selected_mzML_file))
if MS2 is None:
st.warning("The corresponding " + ".mzML file could not be found. Please re-upload the mzML file to visualize all peaks.")
MS2 = process_mzML_file(os.path.join(Path.cwd().parent , str(st.session_state.workspace)[3:] , "mzML-files" ,f"{file_name_wout_out}.mzML"))
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@coderabbitai coderabbitai bot Aug 1, 2025

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⚠️ Potential issue

Improve path construction for robustness

The path construction using Path.cwd().parent and string slicing [3:] is fragile and could break if the directory structure changes.

-            MS2 = process_mzML_file(os.path.join(Path.cwd().parent ,  str(st.session_state.workspace)[3:] , "mzML-files" ,f"{file_name_wout_out}.mzML"))
+            mzml_path = Path(st.session_state.workspace) / "mzML-files" / f"{file_name_wout_out}.mzML"
+            MS2 = process_mzML_file(str(mzml_path))
📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change
MS2 = process_mzML_file(os.path.join(Path.cwd().parent , str(st.session_state.workspace)[3:] , "mzML-files" ,f"{file_name_wout_out}.mzML"))
mzml_path = Path(st.session_state.workspace) / "mzML-files" / f"{file_name_wout_out}.mzML"
MS2 = process_mzML_file(str(mzml_path))
🧰 Tools
🪛 Ruff (0.12.2)

139-139: os may be undefined, or defined from star imports

(F405)

139-139: Path may be undefined, or defined from star imports

(F405)

🤖 Prompt for AI Agents 
In content/Result_2.py at line 139, the current path construction uses
Path.cwd().parent combined with string slicing [3:], which is fragile and
error-prone. Replace this with a more robust approach by using pathlib's Path
methods to join paths without manual string slicing. Construct the full path by
properly joining Path.cwd().parent with the workspace directory and other
subdirectories using Path objects and the / operator or Path.joinpath to ensure
platform-independent and reliable path handling.

if MS2 is None:
st.warning("The corresponding " + ".mzML file could not be found. Please re-upload the mzML file to visualize all peaks.")

if CSM_ is None:
st.warning("No CSMs found in selected idXML file")
else:

#if CSM_['NuXL:NA'].str.contains('none').any():
# st.warning("nonXL CSMs found")
#else:

# provide dataframe
#st.write(list(CSM_.columns.values))

gb = GridOptionsBuilder.from_dataframe(CSM_[list(CSM_.columns.values)])

# configure selection
gb.configure_selection(selection_mode="single", use_checkbox=True)
gb.configure_side_bar()
gb.configure_pagination(enabled=True, paginationAutoPageSize=False, paginationPageSize=10)
gridOptions = gb.build()



data = AgGrid(CSM_,
gridOptions=gridOptions,
enable_enterprise_modules=True,
allow_unsafe_jscode=True,
update_mode=GridUpdateMode.SELECTION_CHANGED,
columns_auto_size_mode=ColumnsAutoSizeMode.FIT_CONTENTS)

#download table
#show_table(CSM_, f"{os.path.splitext(selected_file)[0]}")
#select row by user
selected_row = data["selected_rows"]

if CSM_ is None:
st.warning("No CSMs found in selected idXML file")
else:

gb = GridOptionsBuilder.from_dataframe(CSM_[list(CSM_.columns.values)])

# configure selection
gb.configure_selection(selection_mode="single", use_checkbox=True)
gb.configure_side_bar()
gb.configure_pagination(enabled=True, paginationAutoPageSize=False, paginationPageSize=10)
gridOptions = gb.build()

data = AgGrid(CSM_,
gridOptions=gridOptions,
enable_enterprise_modules=True,
allow_unsafe_jscode=True,
update_mode=GridUpdateMode.SELECTION_CHANGED,
columns_auto_size_mode=ColumnsAutoSizeMode.FIT_CONTENTS)

selected_row = data.get("selected_rows")
if selected_row:
row = selected_row[0]


if not(selected_row is None):
# Create a dictionary of annotation features
annotation_data_idxml = {'intarray': [float(value) for value in {selected_row['intensities'][0]}.pop().split(',')],
'mzarray': [float(value) for value in {selected_row['mz_values'][0]}.pop().split(',')],
'anotarray': [str(value) for value in {selected_row['ions'][0]}.pop().split(',')]
}




if MS2 is not None:
# Extract m/z and intensity data from the selected MS2 spectrum
mz_full, inten_full = get_mz_intensities_from_ms2(MS2_spectras=MS2, native_id=selected_row['SpecId'][0])

scaled = []
for i in annotation_data_idxml['intarray']:
scaled.append(i/max(annotation_data_idxml['intarray']))


# Convert annotation_data into a dictionary for efficient matching
annotation_dict = {(round(mz, 2)): (anot, i) for i, mz, anot in zip(scaled, annotation_data_idxml['mzarray'], annotation_data_idxml['anotarray'])}


# Annotate the data
annotation_data = []
for intensity, mz in zip(inten_full, mz_full):
mz_r = round(float(mz), 2)
int_r = round(float(intensity), 2)
#st.write(mz_r)
annotation = annotation_dict.get(mz_r, (' ', int_r))
#st.write(annotation)
annotation_data.append({
'mzarray': mz_r,
'intarray': annotation[1],
'anotarray': annotation[0]
})

if MS2 is None:
annotation_data = annotation_data_idxml # just provide the annotated peaks
st.write("MS2 was none")

# Check if the lists are not empty
if annotation_data:
#st.write("Gets to annotation data")
# Create the DataFrame
annotation_df = pd.DataFrame(annotation_data)
#st.write(annotation_df)
# title of spectra #Maybe remove NuXL:na
spectra_name = os.path.splitext(selected_file)[0] +" Scan# " + str({selected_row['ScanNr'][0]}).strip('{}') + " Pep: " + str({selected_row['Peptide'][0]}).strip('{}\'')
# generate ms2 spectra
fig = plot_ms2_spectrum_full(annotation_df, spectra_name, "black")
#show figure
show_fig(fig, f"{os.path.splitext(selected_file)[0]}_scan_{str({selected_row['ScanNr'][0]}).strip('{}')}")

# Parse annotation arrays
intensities = list(map(float, row['intensities'].split(',')))
mz_values = list(map(float, row['mz_values'].split(',')))
ions = row['ions'].split(',')

annotation_data_idxml = {
'intarray': intensities,
'mzarray': mz_values,
'anotarray': ions
}

# Build annotation data based on MS2 availability
if MS2 is not None:
mz_full, inten_full = get_mz_intensities_from_ms2(MS2_spectras=MS2, native_id=row['SpecId'])

# Create a KDTree from annotation m/z values
annotation_mz = np.array(annotation_data_idxml['mzarray'])
tree = cKDTree(annotation_mz.reshape(-1, 1))

# Tolerance for m/z matching
tolerance = 0.001
mz_full = np.array(mz_full)
inten_full = np.array(inten_full)

# Perform tolerant matching
matches = tree.query_ball_point(mz_full.reshape(-1, 1), r=tolerance)

annotation_data = []
for i, (mz, intensity) in enumerate(zip(mz_full, inten_full)):
match_indices = matches[i]
if match_indices:
matched_idx = min(match_indices, key=lambda j: abs(annotation_mz[j] - mz))
annotation = annotation_data_idxml['anotarray'][matched_idx]
else:
# if any list empty
st.warning("Annotation not available for this peptide")
annotation = ' '
annotation_data.append({
'mzarray': mz,
'intarray': intensity,
'anotarray': annotation
})
else:
# Use IDXML annotations directly if MS2 is missing
annotation_data = [
{'mzarray': mz, 'intarray': i, 'anotarray': anot}
for i, mz, anot in zip(intensities, mz_values, ions)
]

# Display annotated spectrum
if annotation_data:
annotation_df = pd.DataFrame(annotation_data)
scan_nr = str(row['ScanNr'])
peptide = row['Peptide']
spectra_name = f"{os.path.splitext(selected_file)[0]} Scan# {scan_nr} Pep: {peptide}"
fig = plot_ms2_spectrum_full(annotation_df, spectra_name, "black")
show_fig(fig, f"{os.path.splitext(selected_file)[0]}_scan_{scan_nr}")
else:
st.warning("Annotation not available for this peptide")

#with PRTs Table
with tabs_[1]:
Expand Down
1 change: 1 addition & 0 deletions environment.yml
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Expand Up @@ -15,3 +15,4 @@ dependencies:
- streamlit-plotly-events
- streamlit-aggrid
- pyopenms_viz>=0.1.2
- scipy==1.16.1
12 changes: 8 additions & 4 deletions requirements.txt
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@@ -1,9 +1,13 @@
# the requirements.txt file is intended for deployment on streamlit cloud and if the simple container is built
# note that it is much more restricted in terms of installing third-parties / etc.
# preferably use the batteries included or simple docker file for local hosting
streamlit>=1.38.0
pyopenms==3.2.0
numpy==1.26.4 # pandas and numpy are dependencies of pyopenms, however, pyopenms needs numpy<=1.26.4
streamlit==1.38.0
streamlit-plotly-events==0.0.6
streamlit-aggrid==0.3.4.post3
pandas==2.0.3
numpy==1.26.4
plotly==5.22.0
pyopenms==3.2.0
captcha==0.5.0
pyopenms_viz>=0.1.2
pyopenms_viz>=0.1.2
scipy==1.16.1
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