def main():
st.set_option("deprecation.showfileUploaderEncoding", False)
uploaded_file_buffer_list = st.file_uploader(
"Files to pseudonymise, refresh page after downloading zip(s)",
["dcm"],
accept_multiple_files=True,
)
if st.button("Pseudonymise", key="PseudonymiseButton"):
pseudonymise_buffer_list(uploaded_file_buffer_list)
uploaded_file_buffer_list.clear()
def main():
st.write("## Parameters")
number_of_images = st.number_input("Number of Images", 10)
width = st.number_input("Width (mm)", 20)
length = st.number_input("Length (mm)", 24)
edge_lengths = [width, length]
# initial_rotation = 0
bb_diameter = st.number_input("BB Diameter (mm)", 8)
penumbra = st.number_input("Penumbra (mm)", 2)
# files = sorted(IMAGES_DIR.glob("*.jpg"), key=lambda t: -os.stat(t).st_mtime)
# most_recent = files[0:5]
# most_recent
files = get_file_list()
most_recent = sorted(
files, key=lambda t: -os.stat(t).st_mtime)[0:number_of_images]
image_path = st.radio("Image to select", options=most_recent)
plt.imshow(read_image(image_path))
st.pyplot()
if st.button("Calculate"):
img = read_image(image_path)
x, y, img = iview.iview_image_transform(img)
field = imginterp.create_interpolated_field(x, y, img)
initial_centre = findfield.get_centre_of_mass(x, y, img)
(field_centre,
field_rotation) = findfield.field_centre_and_rotation_refining(
field, edge_lengths, penumbra, initial_centre, fixed_rotation=0)
bb_centre = findbb.optimise_bb_centre(field, bb_diameter, edge_lengths,
penumbra, field_centre,
field_rotation)
fig = reporting.image_analysis_figure(
x,
y,
img,
bb_centre,
field_centre,
field_rotation,
bb_diameter,
edge_lengths,
penumbra,
)
st.write(fig)
st.pyplot()
def main():
config = get_config()
st.sidebar.markdown("""
# Overview
""")
st.sidebar.markdown("""
## Reference
""")
set_reference_overview = sidebar_overview()
st.sidebar.markdown("""
## Evaluation
""")
set_evaluation_overview = sidebar_overview()
overview_updater_map = {
"reference": set_reference_overview,
"evaluation": set_evaluation_overview,
}
st.sidebar.markdown("""
# Status indicators
""")
show_status_indicators()
st.sidebar.markdown("""
# Advanced options
Enable advanced functionality by ticking the below.
""")
advanced_mode = st.sidebar.checkbox("Run in Advanced Mode")
gamma_options = get_gamma_options(advanced_mode)
data_option_functions = {
"monaco": monaco_input_method,
"dicom": dicom_input_method,
"icom": icom_input_method,
"trf": trf_input_method,
"mosaiq": mosaiq_input_method,
}
default_reference_id = config["data_methods"]["default_reference"]
default_evaluation_id = config["data_methods"]["default_evaluation"]
available_data_methods = config["data_methods"]["available"]
default_reference = DATA_OPTION_LABELS[default_reference_id]
default_evaluation = DATA_OPTION_LABELS[default_evaluation_id]
data_method_map = {}
for method in available_data_methods:
data_method_map[
DATA_OPTION_LABELS[method]] = data_option_functions[method]
"""
### Reference
"""
reference_results = get_input_data_ui(
overview_updater_map,
data_method_map,
default_reference,
"reference",
advanced_mode,
)
"""
### Evaluation
"""
evaluation_results = get_input_data_ui(
overview_updater_map,
data_method_map,
default_evaluation,
"evaluation",
advanced_mode,
**reference_results,
)
"""
## Output Locations
"""
"""
### eSCAN Directory
The location to save the produced pdf report.
"""
site_directories = get_site_directories()
site_options = list(site_directories.keys())
escan_site = st.radio("eScan Site", site_options)
escan_directory = site_directories[escan_site]["escan"]
if advanced_mode:
st.write(escan_directory.resolve())
default_png_output_directory = config["output"]["png_directory"]
if advanced_mode:
"""
### Image record
Path to save the image of the results for posterity
"""
png_output_directory = pathlib.Path(
st.text_input("png output directory",
default_png_output_directory))
st.write(png_output_directory.resolve())
else:
png_output_directory = pathlib.Path(default_png_output_directory)
"""
## Calculation
"""
if st.button("Run Calculation"):
run_calculation(
reference_results,
evaluation_results,
gamma_options,
escan_directory,
png_output_directory,
)
if advanced_mode:
advanced_debugging()
def main():
st.write("# Anonymise Monaco Files")
st.write("## Select Patient")
(
monaco_site,
_,
patient_id,
_,
patient_directory,
) = st_monaco.monaco_patient_directory_picker(advanced_mode_local=True)
st.write(f"Directory to anonymise: `{patient_directory}`")
st.write("## Select Export Location")
_, export_directory = st_misc.get_site_and_directory(
"Site to save anonymised zip file",
"anonymised_monaco",
default=monaco_site,
key="export_site",
)
st.write(f"Export directory: `{export_directory}`")
zip_path = pathlib.Path(export_directory).joinpath(f"{patient_id}.zip")
st.write(f"Zip file to be created: `{zip_path}`")
if zip_path.exists():
st.write(FileExistsError("This zip file already exists."))
if st.button("Delete zip file"):
zip_path.unlink()
st_rerun.rerun()
st.stop()
if st.button("Copy and Anonymise"):
with tempfile.TemporaryDirectory() as temp_dir:
pl_temp_dir = pathlib.Path(temp_dir)
new_temp_location = pl_temp_dir.joinpath(patient_directory.name)
st.write("Copying to temp directory, skipping DICOM files...")
shutil.copytree(
patient_directory,
new_temp_location,
ignore=shutil.ignore_patterns("*.DCM", "demographic.*"),
)
st.write("Creating anonymised demographic file...")
new_demographic_file = new_temp_location.joinpath(
f"demographic.{patient_id}"
)
shutil.copy2(ANON_DEMOGRAPHIC_FILE, new_demographic_file)
with open(new_demographic_file, "r") as f:
demographic_data = f.readlines()
demographic_data[3] = demographic_data[3].replace("000000", patient_id)
with open(new_demographic_file, "w") as f:
f.writelines(demographic_data)
st.write("Creating zip file...")
shutil.make_archive(
str(zip_path.with_suffix("")),
"zip",
root_dir=str(pl_temp_dir.resolve()),
base_dir=f"{patient_directory.name}",
)
st.write("Complete!")
def main():
st.write("""
# MU Density comparison tool
Tool to compare the MU Density between planned and delivery.
""")
config = st_config.get_config()
st.sidebar.markdown("""
# MU Density Overview
""")
st.sidebar.markdown("""
## Reference
""")
set_reference_overview = sidebar_overview()
st.sidebar.markdown("""
## Evaluation
""")
set_evaluation_overview = sidebar_overview()
overview_updater_map = {
"reference": set_reference_overview,
"evaluation": set_evaluation_overview,
}
st.sidebar.markdown("""
# Status indicators
""")
show_status_indicators()
st.sidebar.markdown("""
# Advanced options
Enable advanced functionality by ticking the below.
""")
advanced_mode = st.sidebar.checkbox("Run in Advanced Mode")
gamma_options = _config.get_gamma_options(advanced_mode)
data_option_functions = {
"monaco": _monaco.monaco_input_method,
"dicom": _dicom.dicom_input_method,
"icom": _icom.icom_input_method,
"trf": _trf.trf_input_method,
"mosaiq": _mosaiq.mosaiq_input_method,
}
default_reference_id = config["data_methods"]["default_reference"]
default_evaluation_id = config["data_methods"]["default_evaluation"]
available_data_methods = config["data_methods"]["available"]
default_reference = DATA_OPTION_LABELS[default_reference_id]
default_evaluation = DATA_OPTION_LABELS[default_evaluation_id]
data_method_map = {}
for method in available_data_methods:
data_method_map[
DATA_OPTION_LABELS[method]] = data_option_functions[method]
st.write("""
## Selection of data to compare
""")
st.write("""
### Reference
""")
reference_results = get_input_data_ui(
overview_updater_map,
data_method_map,
default_reference,
"reference",
advanced_mode,
)
st.write("""
### Evaluation
""")
evaluation_results = get_input_data_ui(
overview_updater_map,
data_method_map,
default_evaluation,
"evaluation",
advanced_mode,
**reference_results,
)
st.write("""
## Output Locations
""")
st.write("""
### eSCAN Directory
The location to save the produced pdf report.
""")
default_site = evaluation_results.get("site", None)
if default_site is None:
default_site = reference_results.get("site", None)
_, escan_directory = st_misc.get_site_and_directory(
"eScan Site",
"escan",
default=default_site,
key="escan_export_site_picker")
escan_directory = pathlib.Path(
os.path.expanduser(escan_directory)).resolve()
if advanced_mode:
st.write(escan_directory)
default_png_output_directory = config["output"]["png_directory"]
if advanced_mode:
st.write("""
### Image record
Path to save the image of the results for posterity
""")
png_output_directory = pathlib.Path(
st.text_input("png output directory",
default_png_output_directory))
st.write(png_output_directory.resolve())
else:
png_output_directory = pathlib.Path(default_png_output_directory)
png_output_directory = pathlib.Path(
os.path.expanduser(png_output_directory)).resolve()
st.write("""
## Calculation
""")
if st.button("Run Calculation"):
st.write("""
### MU Density usage warning
""")
st.warning(pymedphys.mudensity.WARNING_MESSAGE)
st.write("""
### Calculation status
""")
run_calculation(
reference_results,
evaluation_results,
gamma_options,
escan_directory,
png_output_directory,
)
if advanced_mode:
advanced_debugging()
def main():
centres = ["rccc", "nbcc", "sash"]
servers = {
"rccc": "msqsql",
"nbcc": "physics-server:31433",
"sash": "physics-server",
}
physics_locations = {
"rccc": "Physics_Check",
"nbcc": "Physics",
"sash": "Physics_Check",
}
cursors = {
centre: st_mosaiq.get_mosaiq_cursor_in_bucket(servers[centre])
for centre in centres
}
st.write("# Mosaiq QCLs")
if st.button("Refresh"):
st.experimental_rerun()
for centre in centres:
st.write(f"## {centre.upper()}")
cursor_bucket = cursors[centre]
physics_location = physics_locations[centre]
try:
table = msq_helpers.get_incomplete_qcls(cursor_bucket["cursor"],
physics_location)
except (pymssql.InterfaceError, pymssql.OperationalError) as e:
st.write(e)
cursor_bucket["cursor"] = st_mosaiq.uncached_get_mosaiq_cursor(
servers[centre])
table = msq_helpers.get_incomplete_qcls(cursor_bucket["cursor"],
physics_location)
table_dict = collections.OrderedDict()
for index, row in table.iterrows():
patient_name = f"{str(row.last_name).upper()}, {str(row.first_name).lower().capitalize()}"
table_dict[index] = collections.OrderedDict({
"Due":
row.due.strftime("%Y-%m-%d"),
"Patient":
f"{row.patient_id} {patient_name}",
"Instructions":
row.instructions,
"Comment":
row.comment,
"Task":
row.task,
})
formated_table = pd.DataFrame.from_dict(table_dict).T
formated_table = formated_table.reindex(
["Due", "Patient", "Instructions", "Comment", "Task"], axis=1)
st.write(formated_table)