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rewritten with xlsxwriter
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@vedina
vedina committed Apr 2, 2024
1 parent fdcf156 commit cd69a04
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Showing 2 changed files with 91 additions and 44 deletions.
135 changes: 91 additions & 44 deletions src/pynanomapper/datamodel/templates/blueprint.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@ def json2frame(json_data,sortby=None):
def get_method_metadata(json_blueprint):

_header = {
"Project Work Package" : json_blueprint.get("provenance_workpackage",""),
"Project Work Package" : json_blueprint.get("provenance_project",""),
"Partner conducting test/assay" : json_blueprint.get("provenance_workpackage",""),
"Test facility - Laboratory name" : json_blueprint.get("provenance_provider",""),
"Lead Scientist & contact for test" : json_blueprint.get("provenance_contact",""),
Expand Down Expand Up @@ -175,20 +175,39 @@ def autofit_columns(sheet,cols=None):
sheet.cell(row=1, column=col_num+1).fill = pf
#break


def autofit_multilevel(df,worksheet):
for idx, col in enumerate(df.columns):
# Find the maximum length of the column header (using the last level of multi-index)
max_length = max(len(str(level)) for level in col) + 1
# Set the column width based on the length of the column header
worksheet.set_column(idx, idx, max_length)

def pchem_format_2excel(file_path_xlsx,json_blueprint):
_SHEET_INFO = "Provider_informations"
_SHEET_RAW = "Raw_data_TABLE"
_SHEET_RESULT = "Results_TABLE"
_SHEET_MATERIAL = "Materials"
current_script_directory = os.path.dirname(os.path.abspath(__file__))
resource_file = os.path.join(current_script_directory, "../../resource/nmparser","template_pchem.xlsx")
shutil.copy2(resource_file, file_path_xlsx)
with pd.ExcelWriter(file_path_xlsx, engine='openpyxl', mode='a') as writer:
sheet = writer.book["Provider_informations"]
sheet["E7"] = json_blueprint.get("METHOD","")
sheet["C2"] = json_blueprint.get("EXPERIMENT","")
sheet["B10"] = json_blueprint.get("template_name","")
sheet["B11"] = json_blueprint.get("template_status","")
sheet["B12"] = json_blueprint.get("template_author","")
sheet["B13"] = json_blueprint.get("template_acknowledgment","")
sheet["B15"] = datetime.now().strftime("%Y-%m-%d")
#resource_file = os.path.join(current_script_directory, "../../resource/nmparser","template_pchem.xlsx")
#shutil.copy2(resource_file, file_path_xlsx)
with pd.ExcelWriter(file_path_xlsx, engine='xlsxwriter', mode='w') as writer:
#sheet = writer.book["Provider_informations"]
worksheet = writer.book.add_worksheet(_SHEET_INFO)
bold_format = writer.book.add_format({'bold': True})
orange_bg_format = writer.book.add_format({'bg_color': '#FFF2CC'})
material_format = writer.book.add_format({'bg_color': '#00B0F0'})
position_format = writer.book.add_format({'bg_color': '#FFC000'})
#_colors = { "top" : '#002060' , "orange" : '#FFC000', 'skyblue' : '#00B0F0' , 'grey' : '#C0C0C0', 'input' : '#FFF2CC'}
for t in [("A2","General information"),
("A10","Template name"),("A11","Template version "), ("A12","Template authors"),("A13","Template acknowledgment"),
("A6","Project"),("A7","Workpackage"),("A8","Partner"),("D7","Study"),("A15","Template downloaded"),("B15",datetime.now().strftime("%Y-%m-%d"))]:
worksheet.write(t[0],t[1], bold_format)
for t in [("E7","METHOD"),("C2","EXPERIMENT"), ("B10","template_name"),("B11","template_status"),
("B12","template_author"),("B13","template_acknowledgment"),
("B6","provenance_project"),("B7","provenance_workpackage"),("B8","provenance_provider")]:
worksheet.write(t[0],json_blueprint.get(t[1],""),orange_bg_format)

worksheet = writer.book.add_worksheet(_SHEET_RESULT)
df = create_nested_headers_dataframe(json_blueprint,keys=
{"raw_data_report" : {'name' : 'raw_endpoint','type' : 'raw_aggregate', 'unit' : 'raw_unit'},
"question3" : {'name' : 'result_name','type' : 'result_aggregate','unit' : 'result_unit'}},
Expand All @@ -197,32 +216,59 @@ def pchem_format_2excel(file_path_xlsx,json_blueprint):
)
#df.insert(0, 'Material ID',None)
df.insert(0, 'Position_ID',None)
df.to_excel(writer,sheet_name="Results_TABLE")
sheet = writer.book["Results_TABLE"]
sheet["A1"] = "Material ID"
sheet["A2"] = ""
sheet["A3"] = ""
sheet["A4"] = ""
autofit_columns(writer.book["Results_TABLE"],df.columns)
df.to_excel(writer,sheet_name=_SHEET_RESULT)
worksheet = writer.book.get_worksheet_by_name(_SHEET_RESULT)
worksheet.write('A1', 'Material ID',material_format)
worksheet.write('A2', ' ',material_format)
worksheet.write('A3', ' ',material_format)
worksheet.write('A4', ' ',material_format)
worksheet.write('B1', 'Position_ID',position_format)
worksheet.write('B2', ' ',position_format)
worksheet.write('B3', ' ',position_format)
worksheet.write('B4', ' ',position_format)
autofit_multilevel(df,worksheet)

df = create_nested_headers_dataframe(json_blueprint,keys={"METADATA_PARAMETERS" : {'group' : 'param_group', 'name' : 'param_name', 'unit' : 'param_unit'}})
#df.insert(0, 'Position_ID',None)
df.to_excel(writer,sheet_name="Measuring_conditions")
sheet = writer.book["Measuring_conditions"]
sheet["A1"] = "Position_ID"
sheet["A2"] = ""
sheet["A3"] = ""
sheet["A4"] = ""
autofit_columns(writer.book["Measuring_conditions"],df.columns)

df = create_nested_headers_dataframe(json_blueprint,keys=
{"METADATA_SAMPLE_INFO" : {'group' : 'param_sample_group', 'name' : 'param_sample_name'},
_SHEET_MEASUREMENT = "Measuring_conditions"
df.to_excel(writer,sheet_name=_SHEET_MEASUREMENT)
worksheet = writer.book.get_worksheet_by_name(_SHEET_MEASUREMENT)
worksheet.write('A1', 'Position_ID',position_format)
worksheet.write('A2', ' ',position_format)
worksheet.write('A3', ' ',position_format)
worksheet.write('A4', ' ',position_format)
worksheet.write('A5', '1',position_format)
worksheet.write('A6', '2',position_format)
position_identifiers_range = "{}!$A5:$A1048576".format(_SHEET_MEASUREMENT) # Entire column A
writer.book.define_name('Position_Identifiers', position_identifiers_range)
autofit_multilevel(df,worksheet)
validation = {
'validate': 'list',
'source': '=Position_Identifiers'
}
writer.book.get_worksheet_by_name(_SHEET_RESULT).data_validation("B5:B1048576", validation)

df = create_nested_headers_dataframe(json_blueprint,keys={
#"METADATA_SAMPLE_INFO" : {'group' : 'param_sample_group', 'name' : 'param_sample_name'},
"METADATA_SAMPLE_PREP" : {'group' : 'param_sampleprep_group', 'name' : 'param_sampleprep_name'}},
levels = ['group','name'],
lookup = {'METADATA_SAMPLE_INFO' : "Sample", "METADATA_SAMPLE_PREP" : "Sample preparation", "group" : ""})
df.insert(0, 'Material ID',None)
df.to_excel(writer,sheet_name="SAMPLES")
autofit_columns(writer.book["SAMPLES"],df.columns)
worksheet = writer.book.get_worksheet_by_name("SAMPLES")
worksheet.write('A1', 'Material ID',material_format)
worksheet.write('A2', ' ',material_format)
worksheet.write('A3', ' ',material_format)

validation = {
'validate': 'list',
'source': '=ERM_Identifiers'
}
writer.book.get_worksheet_by_name("SAMPLES").data_validation("A4:A1048576", validation)
autofit_multilevel(df,worksheet)


materials_sheet = create_materials_sheet(writer.book,writer,
materials=_SHEET_MATERIAL,
info=None,results=[_SHEET_RESULT],material_column="A5:A1048576")
add_hidden_jsondef(file_path_xlsx,json_blueprint)

def add_hidden_jsondef(file_path_xlsx,json_blueprint):
Expand All @@ -240,7 +286,6 @@ def add_hidden_jsondef(file_path_xlsx,json_blueprint):
print(err)

def add_plate_layout(file_path_xlsx,json_blueprint):
print(json_blueprint.get("data_sheets"))
if "data_platelayout" in json_blueprint.get("data_sheets",[]):
platexlsx = "platelayout_{}well.xlsx".format(json_blueprint.get("data_platelayout",96) )
current_script_directory = os.path.dirname(os.path.abspath(__file__))
Expand Down Expand Up @@ -473,8 +518,8 @@ def iom_format_2excel(file_path, df_info,df_result,df_raw=None,df_conditions=Non
info=_SHEET_INFO,results=linksheets)


def create_materials_sheet(workbook,writer,materials,info,results):
info_sheet = writer.sheets[info]
def create_materials_sheet(workbook,writer,materials,info=None,results=[],material_column="A3:A1048576"):
info_sheet = None if info is None else writer.sheets[info]
materials_sheet = workbook.add_worksheet(materials)
column_headers = get_materials_columns()
table = pd.DataFrame(columns=column_headers)
Expand All @@ -486,19 +531,21 @@ def create_materials_sheet(workbook,writer,materials,info,results):
'validate': 'list',
'source': '=ERM_Identifiers'
}
info_sheet.data_validation(validation_cell, validation)
vlookup = [('B26',3),('B27',9),('B28',4),('B29',6),('B31',8)]
for v in vlookup:
formula = '=VLOOKUP($B$25,Materials!B:J,"{}",FALSE)'.format(v[1])
info_sheet.write_formula(v[0], formula)
readonly_format = workbook.add_format({'locked': True})
if not info_sheet is None:
info_sheet.data_validation(validation_cell, validation)
vlookup = [('B26',3),('B27',9),('B28',4),('B29',6),('B31',8)]
for v in vlookup:
formula = '=VLOOKUP($B$25,Materials!B:J,"{}",FALSE)'.format(v[1])
info_sheet.write_formula(v[0], formula)
readonly_format = workbook.add_format({'locked': True})

for result in results:
try:
result_sheet = writer.sheets[result]
result_sheet.data_validation("A3:A1048576", validation)
result_sheet.data_validation(material_column, validation)
#protect_headers(result_sheet,readonly_format)
except:
except Exception as err:
print(err)
pass
return materials_sheet

Expand Down
Binary file modified src/pynanomapper/resource/nmparser/template_pchem.xlsx
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