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Update ProcessMultipleExcelTables_FromAivia.py
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v1.60
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@pmascalchi
pmascalchi committed Aug 11, 2023
1 parent 5e14795 commit 8fecbf3
Showing 1 changed file with 70 additions and 27 deletions.
97 changes: 70 additions & 27 deletions Recipes/ProcessMeasurementTables/ProcessMultipleExcelTables_FromAivia.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,6 +12,7 @@ def search_activation_path():
return ''

activate_path = search_activation_path()

if os.path.exists(activate_path):
exec(open(activate_path).read(), {'__file__': activate_path})
print(f'Aivia virtual environment activated\nUsing python: {activate_path}')
Expand All @@ -33,7 +34,7 @@ def search_activation_path():
from datetime import datetime

# Folder to quickly run the script on all Excel files in it
DEFAULT_FOLDER = r''
DEFAULT_FOLDER = ''

# Collect scenario
scenario_descriptions = ['A: Select multiple xlsx tables to create a combined table.\n'
Expand Down Expand Up @@ -64,16 +65,28 @@ def search_activation_path():
'Not compatible with timelapses.'
]

# Relationship definitions (Warning: names should be the sheets in the spreadsheets)
# Example: 'Set': ['Obj1', 'Obj2']
relationships = {'Neuron Set': ['Soma Set', 'Dendrite Set', 'Dendrite Segments'],
'Dendrite Set': ['Dendrite Segments']}
relationship_ID_headers = {'Neuron Set': 'Neuron ID', 'Dendrite Set': 'Tree ID'}
'Dendrite Set': ['Dendrite Segments'],
'Cells': ['Cell Membranes', 'Cytoplasm', 'Nucleus', 'Vesicles - ']}

# Due to discrepancy between object name and ID header, we can provide the correspondence below
relationship_ID_headers = {'Neuron Set': 'Neuron ID', 'Dendrite Set': 'Tree ID', 'Cells': 'Cell ID'}

# Measurements to extract, to avoid too many columns in the final table
relationship_measurements = {'Soma Set': ['Volume (µm³)'],
'Dendrite Set': ['Mean Diameter (µm)'],
'Dendrite Segments': ['Mean Diameter (µm)', 'Total Path Length (µm)', 'Branch Angle']
}
'Dendrite Segments': ['Mean Diameter (µm)', 'Total Path Length (µm)', 'Branch Angle'],
'Cell Membranes': [],
'Cytoplasm': [],
'Nucleus': [],
'Vesicles - ': ['Relation Count']}

relationships_with_stats = ['Dendrite Set', 'Dendrite Segments']
# Selection of secondary relationships for which statistics are calculated: 'Total', 'Average'.
relationships_with_stats = ['Dendrite Set', 'Dendrite Segments', 'Vesicles - ']

# Some statistics do not make any sense, so below are the ones to avoid
relationship_measurements_stats_todrop = {'Branch Angle': 'Total',
'Mean Diameter (µm)': 'Total'}

Expand Down Expand Up @@ -301,8 +314,8 @@ def run(params):
if do_multiple_files_as_cols:
output_basename = 'Analysis_All results.xlsx'
else:
output_basename = '{}_grouped.xlsx'.format(os.path.basename(indiv_path_list[0]).split('.')[0])
output_file = os.path.join(output_folder, output_basename)
output_basename = '{}_grouped.xlsx'.format(''.join(os.path.basename(indiv_path_list[0]).split('.')[:-1]))
output_file = os.path.join(output_folder, output_basename.replace('.aivia', ''))

df_grouped = {} # init

Expand All @@ -317,7 +330,7 @@ def run(params):
do_combine_meas_tabs = False # not possible as columns = measurements

# Detect multiwell batch
process_wells = is_multiwell(well_ref_for_tables[0])
process_wells = is_multiwell(well_ref_for_tables[0]) # TODO: Remove summary tab if True?

# First table in final table
df_grouped = df_raw_1
Expand Down Expand Up @@ -434,6 +447,12 @@ def run(params):
if do_combine_meas_tabs:
df_grouped = combine_tabs(df_grouped)

# Collecting all measurements exact names
all_meas_names = []
for tmp_df in df_grouped.values():
if not 'summary' in str(tmp_df.columns[0]).lower():
all_meas_names.extend(tmp_df.columns[1:])

# Specific to neurons: split dendrite trees from segments
if 'Dendrite Set' in df_grouped.keys():
df_grouped_to_add = {}
Expand All @@ -457,22 +476,32 @@ def run(params):
else:
df_grouped[n] = df_grouped_tmp[n]

# Process relationships between object sets (see definition before this code)
for rel_k in relationships.keys():
# Check presence of primary object
# Process relationships between object sets (see definition before the def run)
for rel_k in relationships.keys(): # E.g. 'Cells'
# Select all tabs where the primary object is # E.g. 'Cells.Cell_Cytoplasm Volume ...'
for k in [it_k for it_k in df_grouped.keys() if rel_k in it_k]:
k_suffix = k.replace(rel_k, '')
k_suffix = k.replace(rel_k, '') # Important when multiple object sets existed (' (2)')

# Check presence of secondary object defined by relationships
for rel_s in relationships[rel_k]:
s = rel_s + k_suffix
# Check presence of secondary object
if s in df_grouped.keys():
# Check presence of correct ID header in measurements in order to associate objects
id_header = relationship_ID_headers[rel_k]
if id_header in df_grouped[s].columns:
prefix = s + '.'
selected_meas = relationship_measurements[rel_s]
df_grouped[k] = calculate_relation_stats(df_grouped[k], df_grouped[s], id_header,
prefix, rel_s, selected_meas)
# v1.60 gives the ability to provide only the beginning of the object name ('Vesicles - ')
# It also provides relationships of multiple secondary objects beginning with the same name

for s in [it_s for it_s in df_grouped.keys() if is_same_object_set(it_s, k_suffix)]:

if rel_s in s: # positive match for secondary object
# Check presence of correct ID header in measurements in order to associate objects
id_header = relationship_ID_headers[rel_k]
if id_header in df_grouped[s].columns:
prefix = s + '.'
selected_meas_prefixes = relationship_measurements[rel_s]

# See if prefixes exists in exact names of measurements (columns)
for meas_prefix in selected_meas_prefixes:
meas = [col for col in df_grouped[s].columns if meas_prefix in col]
print('Collecting statistics ({}) from [{}] to be reported for [{}]'.format(meas, s, k))
df_grouped[k] = calculate_relation_stats(df_grouped[k], df_grouped[s],
id_header, prefix, rel_s, meas)

# Collecting summary values
for k in df_grouped.keys():
Expand Down Expand Up @@ -567,7 +596,7 @@ def run(params):
t += 1

# Adding percentages of objects if multiple object sets exists
if do_combine_meas_tabs:
if do_combine_meas_tabs: # TODO: for do_multiple_files_as_cols too??
if len(total_counts) > 1:
# Collect tab names without summary
df_grouped_keys_nosum = [k for k in df_grouped.keys() if not k.endswith('Summary')]
Expand Down Expand Up @@ -596,7 +625,7 @@ def run(params):
# Writing sheets to excel
with pd.ExcelWriter(output_file, engine="openpyxl") as writer:
# Write Summary first
df_grouped[summary_lbl].to_excel(writer, sheet_name='Summary', index=False)
df_grouped[summary_lbl].to_excel(writer, sheet_name=summary_lbl, index=False)

# Resizing columns
for c in range(0, len(df_grouped[summary_lbl].columns)):
Expand All @@ -605,14 +634,14 @@ def run(params):
len_longest_text = df_grouped[summary_lbl].iloc[:, c].map(str).str.len().max()
writer.sheets[summary_lbl].column_dimensions[col_letter].width = len_longest_text * 1.5

for sh in [d for d in df_grouped.keys() if d != 'Summary']:
for sh in [d for d in df_grouped.keys() if d != summary_lbl]:
df_grouped[sh].to_excel(writer, sheet_name=sh, index=False)

# Resizing columns
for c in range(0, len(df_grouped[sh].columns)):
col_letter = openpyxl.utils.cell.get_column_letter(c + 1)
len_longest_text = len(str(df_grouped[sh].columns[c]))
if c == 0: # First column with measurement name and object names
if c == 0 and df_grouped[sh].shape[0] > 1: # First column with measurement name and object names
if len(str(df_grouped[sh].iloc[1, 0])) > len_longest_text:
len_longest_text = len(str(df_grouped[sh].iloc[1, 0]))
if len_longest_text < 10:
Expand Down Expand Up @@ -806,6 +835,8 @@ def combine_tabs(df_raw):
def calculate_relation_stats(df_i, df_ii, id_header, meas_prefix, obj_ii_type, measurements):
global relationships_with_stats, relationship_measurements_stats_todrop

# Measurements input needs to be a list

df_to_add = pd.DataFrame()

if set(df_ii.columns) & set(measurements):
Expand Down Expand Up @@ -870,6 +901,15 @@ def split_dendrite_set_and_segments(df):
return dendrite_set_df, dendrite_seg_df


# Function to distinguish 'Cells' from 'Cells (2)' and 'Cells (3)'. Used in relationship detection.
def is_same_object_set(name, suffix):
if suffix == '':
ans = True if not name.endswith(')') else False
else:
ans = True if name.endswith(suffix) else False
return ans


def get_split_name(txt: str):
# Check if previous object set name is present in txt
# prev_obj_name = '' if it is for the first measurement tab or if there is only one object set with no child objects
Expand Down Expand Up @@ -978,3 +1018,6 @@ def Mbox(title, text, style):
# Also fixing a bug with formatting of 'Analysis_Summary' when not multiwell
# Fixed wrong sorting of subfolders such as 'Job 9', 'Job 10', etc.
# v1.55: - New virtual env code for auto-activation
# v1.56: - Bug fix since Aivia 12.0 (r38705) security release for scenario F where only the summary tab is output
# v1.60: - Add Cell Analysis support for relationship grouping. Better recognition of object sets with numbers '(1)'
# - Bug fixed at line 660 (if result table is empty)

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