# HG changeset patch
# User iuc
# Date 1566073537 14400
# Node ID 1b0f96ed73f20919dd6ecc73f4101efa5f7b6f01
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/table_compute commit 1ee75135483d5db22c540bc043746cd986f85762"
diff -r 000000000000 -r 1b0f96ed73f2 allowed_functions.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/allowed_functions.xml Sat Aug 17 16:25:37 2019 -0400
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diff -r 000000000000 -r 1b0f96ed73f2 scripts/safety.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/scripts/safety.py Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,211 @@
+import re
+
+
+class Safety():
+ """
+ Class to safely evaluate mathematical expression on single
+ or table data
+ """
+
+ __allowed_tokens = (
+ '(', ')', 'if', 'else', 'or', 'and', 'not', 'in',
+ '+', '-', '*', '/', '%', ',', '!=', '==', '>', '>=', '<', '<=',
+ 'min', 'max', 'sum',
+ )
+ __allowed_ref_types = {
+ 'pd.DataFrame': {
+ 'abs', 'add', 'agg', 'aggregate', 'align', 'all', 'any', 'append',
+ 'apply', 'applymap', 'as_matrix', 'asfreq', 'at', 'axes', 'bool',
+ 'clip', 'clip_lower', 'clip_upper', 'columns', 'combine',
+ 'compound', 'corr', 'count', 'cov', 'cummax', 'cummin', 'cumprod',
+ 'cumsum', 'describe', 'div', 'divide', 'dot', 'drop',
+ 'drop_duplicates', 'droplevel', 'dropna', 'duplicated', 'empty',
+ 'eq', 'equals', 'expanding', 'ffill', 'fillna', 'filter', 'first',
+ 'first_valid_index', 'floordiv', 'ge', 'groupby', 'gt', 'head',
+ 'iat', 'iloc', 'index', 'insert', 'interpolate', 'isin', 'isna',
+ 'isnull', 'items', 'iteritems', 'iterrows', 'itertuples', 'ix',
+ 'join', 'keys', 'kurt', 'kurtosis', 'last', 'last_valid_index',
+ 'le', 'loc', 'lookup', 'lt', 'mad', 'mask', 'max', 'mean',
+ 'median', 'melt', 'merge', 'min', 'mod', 'mode', 'mul', 'multiply',
+ 'ndim', 'ne', 'nlargest', 'notna', 'notnull', 'nsmallest',
+ 'nunique', 'pct_change', 'pivot', 'pivot_table', 'pop', 'pow',
+ 'prod', 'product', 'quantile', 'radd', 'rank', 'rdiv', 'replace',
+ 'resample', 'rfloordiv', 'rmod', 'rmul', 'rolling', 'round',
+ 'rpow', 'rsub', 'rtruediv', 'sample', 'select',
+ 'sem', 'shape', 'shift', 'size', 'skew', 'slice_shift',
+ 'squeeze', 'stack', 'std', 'sub', 'subtract', 'sum', 'swapaxes',
+ 'swaplevel', 'T', 'tail', 'take', 'transform', 'transpose',
+ 'truediv', 'truncate', 'tshift', 'unstack', 'var', 'where',
+ },
+ 'pd.Series': {
+ 'abs', 'add', 'agg', 'aggregate', 'align', 'all', 'any', 'append',
+ 'apply', 'argsort', 'as_matrix', 'asfreq', 'asof', 'astype', 'at',
+ 'at_time', 'autocorr', 'axes', 'between', 'between_time', 'bfill',
+ 'bool', 'cat', 'clip', 'clip_lower', 'clip_upper', 'combine',
+ 'combine_first', 'compound', 'corr', 'count', 'cov', 'cummax',
+ 'cummin', 'cumprod', 'cumsum', 'describe', 'diff', 'div', 'divide',
+ 'divmod', 'dot', 'drop', 'drop_duplicates', 'droplevel', 'dropna',
+ 'dt', 'dtype', 'dtypes', 'duplicated', 'empty', 'eq', 'equals',
+ 'ewm', 'expanding', 'factorize', 'ffill', 'fillna', 'filter',
+ 'first', 'first_valid_index', 'flags', 'floordiv', 'ge', 'groupby',
+ 'gt', 'hasnans', 'head', 'iat', 'idxmax', 'idxmin', 'iloc', 'imag',
+ 'index', 'interpolate', 'is_monotonic', 'is_monotonic_decreasing',
+ 'is_monotonic_increasing', 'is_unique', 'isin', 'isna', 'isnull',
+ 'item', 'items', 'iteritems', 'ix', 'keys', 'kurt', 'kurtosis',
+ 'last', 'last_valid_index', 'le', 'loc', 'lt', 'mad', 'map',
+ 'mask', 'max', 'mean', 'median', 'min', 'mod', 'mode', 'mul',
+ 'multiply', 'name', 'ndim', 'ne', 'nlargest', 'nonzero', 'notna',
+ 'notnull', 'nsmallest', 'nunique', 'pct_change', 'pop', 'pow',
+ 'prod', 'product', 'ptp', 'quantile', 'radd', 'rank', 'rdiv',
+ 'rdivmod', 'real', 'repeat', 'replace', 'resample', 'rfloordiv',
+ 'rmod', 'rmul', 'rolling', 'round', 'rpow', 'rsub', 'rtruediv',
+ 'sample', 'searchsorted', 'select', 'sem', 'shape', 'shift',
+ 'size', 'skew', 'slice_shift', 'sort_index', 'sort_values',
+ 'squeeze', 'std', 'sub', 'subtract', 'sum', 'swapaxes',
+ 'swaplevel', 'T', 'tail', 'take', 'transform', 'transpose',
+ 'truediv', 'truncate', 'tshift', 'unique', 'unstack',
+ 'value_counts', 'var', 'where', 'xs',
+ },
+ }
+
+ __allowed_qualified = {
+ # allowed numpy functionality
+ 'np': {
+ 'abs', 'add', 'all', 'any', 'append', 'array', 'bool', 'ceil',
+ 'complex', 'cos', 'cosh', 'cov', 'cumprod', 'cumsum', 'degrees',
+ 'divide', 'divmod', 'dot', 'e', 'empty', 'exp', 'float', 'floor',
+ 'hypot', 'inf', 'int', 'isfinite', 'isin', 'isinf', 'isnan', 'log',
+ 'log10', 'log2', 'max', 'mean', 'median', 'min', 'mod', 'multiply',
+ 'nan', 'ndim', 'pi', 'product', 'quantile', 'radians', 'rank',
+ 'remainder', 'round', 'sin', 'sinh', 'size', 'sqrt', 'squeeze',
+ 'stack', 'std', 'str', 'subtract', 'sum', 'swapaxes', 'take',
+ 'tan', 'tanh', 'transpose', 'unique', 'var', 'where',
+ },
+ # allowed math functionality
+ 'math': {
+ 'acos', 'acosh', 'asin', 'asinh', 'atan', 'atan2', 'atanh', 'ceil',
+ 'copysign', 'cos', 'cosh', 'degrees', 'e', 'erf', 'erfc', 'exp',
+ 'expm1', 'fabs', 'factorial', 'floor', 'fmod', 'frexp', 'fsum',
+ 'gamma', 'gcd', 'hypot', 'inf', 'isclose', 'isfinite', 'isinf',
+ 'isnan', 'ldexp', 'lgamma', 'log', 'log10', 'log1p', 'log2',
+ 'modf', 'nan', 'pi', 'pow', 'radians', 'remainder', 'sin', 'sinh',
+ 'sqrt', 'tan', 'tanh', 'tau', 'trunc',
+ },
+ # allowed pd functionality
+ 'pd': {
+ 'DataFrame', 'array', 'concat', 'cut', 'date_range', 'factorize',
+ 'interval_range', 'isna', 'isnull', 'melt', 'merge', 'notna',
+ 'notnull', 'period_range', 'pivot', 'pivot_table', 'unique',
+ 'value_counts', 'wide_to_long',
+ },
+ }
+
+ def __init__(self, expression,
+ ref_whitelist=None, ref_type=None,
+ custom_qualified=None):
+ self.allowed_qualified = self.__allowed_qualified.copy()
+ if ref_whitelist is None:
+ self.these = []
+ else:
+ self.these = ref_whitelist
+ if ref_type is None or ref_type not in self.__allowed_ref_types:
+ self.allowed_qualified['_this'] = set()
+ else:
+ self.allowed_qualified[
+ '_this'
+ ] = self.__allowed_ref_types[ref_type]
+ if custom_qualified is not None:
+ self.allowed_qualified.update(custom_qualified)
+ self.expr = expression
+ self.__assertSafe()
+
+ def generateFunction(self):
+ "Generates a function to be evaluated outside the class"
+ cust_fun = "def fun(%s):\n\treturn(%s)" % (self.these[0], self.expr)
+ return cust_fun
+
+ def __assertSafe(self):
+ indeed, problematic_token = self.__isSafeStatement()
+ if not indeed:
+ self.detailedExcuse(problematic_token)
+ raise ValueError("Custom Expression is not safe.")
+
+ @staticmethod
+ def detailedExcuse(word):
+ "Gives a verbose statement for why users should not use some specific operators."
+ mess = None
+ if word == "for":
+ mess = "for loops and comprehensions are not allowed. Use numpy or pandas table operations instead."
+ elif word == ":":
+ mess = "Colons are not allowed. Use inline Python if/else statements."
+ elif word == "=":
+ mess = "Variable assignment is not allowed. Use object methods to substitute values."
+ elif word in ("[", "]"):
+ mess = "Direct indexing of arrays is not allowed. Use numpy or pandas functions/methods to address specific parts of tables."
+ else:
+ mess = "Not an allowed token in this operation"
+ print("( '%s' ) %s" % (word, mess))
+
+ def __isSafeStatement(self):
+ """
+ Determines if a user-expression is safe to evaluate.
+
+ To be considered safe an expression may contain only:
+ - standard Python operators and numbers
+ - inline conditional expressions
+ - select functions and objects
+ by default, these come from the math, numpy and pandas
+ libraries, and must be qualified with the modules' conventional
+ names math, np, pd; can be overridden at the instance level
+ - references to a whitelist of objects (pd.DataFrames by default)
+ and their methods
+ """
+
+ safe = True
+ # examples of user-expressions
+ # '-math.log(1 - elem/4096) * 4096 if elem != bn else elem - 0.5'
+ # 'vec.median() + vec.sum()'
+
+ # 1. Break expressions into tokens
+ # e.g.,
+ # [
+ # '-', 'math.log', '(', '1', '-', 'elem', '/', '4096', ')', '*',
+ # '4096', 'if', 'elem', '!=', 'bn', 'else', 'elem', '-', '0.5'
+ # ]
+ # or
+ # ['vec.median', '(', ')', '+', 'vec.sum', '(', ')']
+ tokens = [
+ e for e in re.split(
+ r'([a-zA-Z0-9_.]+|[^a-zA-Z0-9_.() ]+|[()])', self.expr
+ ) if e.strip()
+ ]
+
+ # 2. Subtract allowed standard tokens
+ rem = [e for e in tokens if e not in self.__allowed_tokens]
+
+ # 3. Subtract allowed qualified objects from allowed modules
+ # and whitelisted references and their attributes
+ rem2 = []
+ for e in rem:
+ parts = e.split('.')
+ if len(parts) == 1:
+ if parts[0] in self.these:
+ continue
+ if len(parts) == 2:
+ if parts[0] in self.these:
+ parts[0] = '_this'
+ if parts[0] in self.allowed_qualified:
+ if parts[1] in self.allowed_qualified[parts[0]]:
+ continue
+ rem2.append(e)
+
+ # 4. Assert that rest are real numbers
+ e = ''
+ for e in rem2:
+ try:
+ _ = float(e)
+ except ValueError:
+ safe = False
+ break
+
+ return safe, e
diff -r 000000000000 -r 1b0f96ed73f2 scripts/table_compute.py
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/scripts/table_compute.py Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,310 @@
+#!/usr/bin/env python3
+"""
+Table Compute tool - a wrapper around pandas with parameter input validation.
+"""
+
+__version__ = "0.8"
+
+import csv
+import math
+from sys import argv
+
+import numpy as np
+import pandas as pd
+import userconfig as uc
+from safety import Safety
+# This should be generated in the same directory
+
+# Version command should not need to copy the config
+if len(argv) == 2 and argv[1] == "--version":
+ print(__version__)
+ exit(-1)
+
+
+class Utils:
+ @staticmethod
+ def getOneValueMathOp(op_name):
+ "Returns a simple one value math operator such as log, sqrt, etc"
+ return getattr(math, op_name)
+
+ @staticmethod
+ def getVectorPandaOp(op_name):
+ "Returns a valid DataFrame vector operator"
+ return getattr(pd.DataFrame, op_name)
+
+ @staticmethod
+ def getTwoValuePandaOp(op_name, pd_obj):
+ "Returns a valid two value DataFrame or Series operator"
+ return getattr(type(pd_obj), "__" + op_name + "__")
+
+
+# Math is imported but not directly used because users
+# may specify a "math." when inserting a custom
+# function. To remove linting errors, which break CI testing
+# we will just use an arbitrary math statement here.
+__ = math.log
+
+
+# Set decimal precision
+pd.options.display.precision = uc.Default["precision"]
+
+user_mode = uc.Default["user_mode"]
+user_mode_single = None
+out_table = None
+params = uc.Data["params"]
+
+if user_mode == "single":
+ # Read in TSV file
+ data = pd.read_csv(
+ uc.Data["tables"][0]["reader_file"],
+ header=uc.Data["tables"][0]["reader_header"],
+ index_col=uc.Data["tables"][0]["reader_row_col"],
+ keep_default_na=uc.Default["narm"],
+ sep='\t'
+ )
+ # Fix whitespace issues in index or column names
+ data.columns = [col.strip() if type(col) is str else col
+ for col in data.columns]
+ data.index = [row.strip() if type(row) is str else row
+ for row in data.index]
+
+ user_mode_single = params["user_mode_single"]
+
+ if user_mode_single == "precision":
+ # Useful for changing decimal precision on write out
+ out_table = data
+
+ elif user_mode_single == "select":
+ cols_specified = params["select_cols_wanted"]
+ rows_specified = params["select_rows_wanted"]
+
+ # Select all indexes if empty array of values
+ if not cols_specified:
+ cols_specified = range(len(data.columns))
+ if not rows_specified:
+ rows_specified = range(len(data))
+
+ # do not use duplicate indexes
+ # e.g. [2,3,2,5,5,4,2] to [2,3,5,4]
+ nodupes_col = not params["select_cols_unique"]
+ nodupes_row = not params["select_rows_unique"]
+
+ if nodupes_col:
+ cols_specified = [x for i, x in enumerate(cols_specified)
+ if x not in cols_specified[:i]]
+ if nodupes_row:
+ rows_specified = [x for i, x in enumerate(rows_specified)
+ if x not in rows_specified[:i]]
+
+ out_table = data.iloc[rows_specified, cols_specified]
+
+ elif user_mode_single == "filtersumval":
+ mode = params["filtersumval_mode"]
+ axis = params["filtersumval_axis"]
+ operation = params["filtersumval_op"]
+ compare_operation = params["filtersumval_compare"]
+ value = params["filtersumval_against"]
+ minmatch = params["filtersumval_minmatch"]
+
+ if mode == "operation":
+ # Perform axis operation
+ summary_op = Utils.getVectorPandaOp(operation)
+ axis_summary = summary_op(data, axis=axis)
+ # Perform vector comparison
+ compare_op = Utils.getTwoValuePandaOp(
+ compare_operation, axis_summary
+ )
+ axis_bool = compare_op(axis_summary, value)
+
+ elif mode == "element":
+ if operation.startswith("str_"):
+ data = data.astype("str")
+ value = str(value)
+ # Convert str_eq to eq
+ operation = operation[4:]
+ else:
+ value = float(value)
+
+ op = Utils.getTwoValuePandaOp(operation, data)
+ bool_mat = op(data, value)
+ axis_bool = np.sum(bool_mat, axis=axis) >= minmatch
+
+ out_table = data.loc[:, axis_bool] if axis == 0 else data.loc[axis_bool, :]
+
+ elif user_mode_single == "matrixapply":
+ # 0 - column, 1 - row
+ axis = params["matrixapply_dimension"]
+ # sd, mean, max, min, sum, median, summary
+ operation = params["matrixapply_op"]
+
+ if operation is None:
+ use_custom = params["matrixapply_custom"]
+ if use_custom:
+ custom_func = params["matrixapply_custom_func"]
+
+ def fun(vec):
+ """Dummy Function"""
+ return vec
+
+ ss = Safety(custom_func, ['vec'], 'pd.Series')
+ fun_string = ss.generateFunction()
+ exec(fun_string) # SUPER DUPER SAFE...
+
+ out_table = data.apply(fun, axis)
+ else:
+ print("No operation given")
+ exit(-1)
+ else:
+ op = getattr(pd.DataFrame, operation)
+ out_table = op(data, axis)
+
+ elif user_mode_single == "element":
+ # lt, gt, ge, etc.
+ operation = params["element_op"]
+ if operation is not None:
+ op = Utils.getTwoValuePandaOp(operation, data)
+ value = params["element_value"]
+ try:
+ # Could be numeric
+ value = float(value)
+ except ValueError:
+ pass
+ # generate filter matrix of True/False values
+ bool_mat = op(data, value)
+ else:
+ # implement no filtering through a filter matrix filled with
+ # True values.
+ bool_mat = np.full(data.shape, True)
+
+ # Get the main processing mode
+ mode = params["element_mode"]
+ if mode == "replace":
+ replacement_val = params["element_replace"]
+ out_table = data.mask(bool_mat, replacement_val)
+ elif mode == "modify":
+ mod_op = Utils.getOneValueMathOp(params["element_modify_op"])
+ out_table = data.mask(
+ bool_mat, data.where(bool_mat).applymap(mod_op)
+ )
+ elif mode == "scale":
+ scale_op = Utils.getTwoValuePandaOp(
+ params["element_scale_op"], data
+ )
+ scale_value = params["element_scale_value"]
+ out_table = data.mask(
+ bool_mat, scale_op(data.where(bool_mat), scale_value)
+ )
+ elif mode == "custom":
+ element_customop = params["element_customop"]
+
+ def fun(elem):
+ """Dummy Function"""
+ return elem
+
+ ss = Safety(element_customop, ['elem'])
+ fun_string = ss.generateFunction()
+ exec(fun_string) # SUPER DUPER SAFE...
+
+ out_table = data.mask(
+ bool_mat, data.where(bool_mat).applymap(fun)
+ )
+ else:
+ print("No such element mode!", mode)
+ exit(-1)
+
+ elif user_mode_single == "fulltable":
+ general_mode = params["mode"]
+
+ if general_mode == "melt":
+ melt_ids = params["MELT"]["melt_ids"]
+ melt_values = params["MELT"]["melt_values"]
+
+ out_table = pd.melt(data, id_vars=melt_ids, value_vars=melt_values)
+ elif general_mode == "pivot":
+ pivot_index = params["PIVOT"]["pivot_index"]
+ pivot_column = params["PIVOT"]["pivot_column"]
+ pivot_values = params["PIVOT"]["pivot_values"]
+
+ out_table = data.pivot(
+ index=pivot_index, columns=pivot_column, values=pivot_values
+ )
+ elif general_mode == "custom":
+ custom_func = params["fulltable_customop"]
+
+ def fun(tableau):
+ """Dummy Function"""
+ return tableau
+
+ ss = Safety(custom_func, ['table'], 'pd.DataFrame')
+ fun_string = ss.generateFunction()
+ exec(fun_string) # SUPER DUPER SAFE...
+
+ out_table = fun(data)
+
+ else:
+ print("No such mode!", user_mode_single)
+ exit(-1)
+
+
+elif user_mode == "multiple":
+
+ table_sections = uc.Data["tables"]
+
+ if not table_sections:
+ print("Multiple table sets not given!")
+ exit(-1)
+
+ reader_skip = uc.Default["reader_skip"]
+
+ # Data
+ table = []
+ # 1-based handlers for users "table1", "table2", etc.
+ table_names = []
+ # Actual 0-based references "table[0]", "table[1]", etc.
+ table_names_real = []
+
+ # Read and populate tables
+ for x, t_sect in enumerate(table_sections):
+ tmp = pd.read_csv(
+ t_sect["file"],
+ header=t_sect["header"],
+ index_col=t_sect["row_names"],
+ keep_default_na=uc.Default["narm"],
+ sep="\t"
+ )
+ table.append(tmp)
+ table_names.append("table" + str(x + 1))
+ table_names_real.append("table[" + str(x) + "]")
+
+ custom_op = params["fulltable_customop"]
+ ss = Safety(custom_op, table_names, 'pd.DataFrame')
+ fun_string = ss.generateFunction()
+ # Change the argument to table
+ fun_string = fun_string.replace("fun(table1):", "fun():")
+ # table1 to table[1]
+ for name, name_real in zip(table_names, table_names_real):
+ fun_string = fun_string.replace(name, name_real)
+
+ fun_string = fun_string.replace("fun():", "fun(table):")
+ exec(fun_string) # SUPER DUPER SAFE...
+ out_table = fun(table)
+
+else:
+ print("No such mode!", user_mode)
+ exit(-1)
+
+if not isinstance(out_table, (pd.DataFrame, pd.Series)):
+ print('The specified operation did not result in a table to return.')
+ raise RuntimeError(
+ 'The operation did not generate a pd.DataFrame or pd.Series to return.'
+ )
+out_parameters = {
+ "sep": "\t",
+ "float_format": "%%.%df" % pd.options.display.precision,
+ "header": uc.Default["out_headers_col"],
+ "index": uc.Default["out_headers_row"]
+}
+if user_mode_single not in ('matrixapply', None):
+ out_parameters["quoting"] = csv.QUOTE_NONE
+
+out_table.to_csv(uc.Default["outtable"], **out_parameters)
diff -r 000000000000 -r 1b0f96ed73f2 table_compute.xml
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/table_compute.xml Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,1441 @@
+
+ computes operations on table data
+
+ 0.8
+ ]]>
+ ]]>
+ allowed_functions.xml
+
+
+ ^(?:\w+)?$
+
+
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+ ^(?:\w+)?$
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+ ^(?:\w+(?:, *\w+)*)?$
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+ ^(?:\d+(?::\d)*(?:, *\d+(?::\d)*)*)?$
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+ ^[\w !\-+=/*%,.<>()]+$
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+
+ 5) else 1
+
+ * *Operate on elements* → **All**
+
+
+Example 5: Perform a Full table operation
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+We have the following table:
+
+ === === === ===
+ . c1 c2 c3
+ === === === ===
+ g1 10 20 30
+ g2 3 10 9
+ g3 4 8 10
+ g4 81 10 10
+ === === === ===
+
+and we want to subtract from each column the mean of that column divided by the standard deviation of it to yield:
+
+
+ === ========= ========= =========
+ . c1 c2 c3
+ === ========= ========= =========
+ g1 9.351737 17.784353 28.550737
+ g2 2.351737 7.784353 7.550737
+ g3 3.351737 5.784353 8.550737
+ g4 80.351737 7.784353 8.550737
+ === ========= ========= =========
+
+In Galaxy we would select the following:
+
+ * *Input Single or Multiple Tables* → **Single Table**
+ * *Column names on first row?* → **Yes**
+ * *Row names on first column?* → **Yes**
+ * *Type of table operation* → **Perform a Full Table Operation**
+
+ * *Operation* → **Custom**
+
+ * *Custom Expression on 'table' along axis (0 or 1)* → ::
+
+ table - table.mean(0)/table.std(0)
+
+
+Example 6: Perform operations on multiple tables
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+We have the following three input tables:
+
+Table 1
+
+ === === === ===
+ . c1 c2 c3
+ === === === ===
+ g1 10 20 30
+ g2 3 10 9
+ g3 4 8 10
+ === === === ===
+
+Table 2
+
+ === === ===
+ . c1 c2
+ === === ===
+ g1 1 2
+ g2 3 4
+ g3 6 5
+ === === ===
+
+Table 3
+
+ === === === ===
+ . c1 c2 c3
+ === === === ===
+ g1 1 2 3
+ g2 1 2 3
+ === === === ===
+
+
+*Note that the dimensions of these tables do not match.*
+
+Dimensions:
+ * Table1 [3,3]
+ * Table2 [3,2]
+ * Table3 [2,3]
+
+In order to perform simple operations between Tables, they must be of the same dimensions.
+
+To add Table2 to Table3 we would have to transpose one of the tables using the in-built `T` method::
+
+ table2 + table3.T
+
+or::
+
+ table2.T + table3
+
+We can also perform more general operations using all 3 tables, such as taking the minimum value of
+the maximum values of Table2 and Table3, and dividing the Table1 values by it::
+
+ table1 / min(table2.values.max(), table3.values.max())
+
+
+To perform these types of operations in Galaxy we would select the following:
+
+ * *Input Single or Multiple Tables* → **Multiple Tables**
+ * *(For each inserted table)*
+ * *Column names on first row?* → **Yes**
+ * *Row names on first column?* → **Yes**
+ * *Custom Expression* → ::
+
+
+
+Please note that the last example shown above was chosen to illustrate the
+limitations of the tool. Nested attributes like `table2.values.max` are
+disallowed in expressions in the tool so the above would have to be replaced
+with the harder to read workaround::
+
+ table1 / min(np.max(np.max(table2)), np.max(np.max(table3)))
+
+Also note that, currently `min()`, `max()` and `sum()` are the only built-in
+Python functions that can be used inside expressions. If you want to use
+additional functions, these have to be qualified functions from the `math`,
+`np` or `pd` libraries.
+
+
+Example 7: Melt
+~~~~~~~~~~~~~~~
+
+We have the following table
+
+ === === === ===
+ . A B C
+ === === === ===
+ 0 a B 1
+ 1 b B 3
+ 2 c B 5
+ === === === ===
+
+and we want:
+
+ === === ======== =====
+ . A variable value
+ === === ======== =====
+ 0 a B B
+ 1 b B B
+ 2 c B B
+ 3 a C 1
+ 4 b C 3
+ 5 c C 5
+ === === ======== =====
+
+
+In Galaxy we would select the following:
+
+ * *Input Single or Multiple Tables* → **Single Table**
+ * *Column names on first row?* → **Yes**
+ * *Row names on first column?* → **Yes**
+ * *Type of table operation* → **Perform a Full Table Operation**
+
+ * *Operation* → **Melt**
+ * *Variable IDs* → "A"
+ * *Unpivoted IDs* → "B,C"
+
+This converts the "B" and "C" columns into variables.
+
+
+Example 8: Pivot
+~~~~~~~~~~~~~~~~
+
+We have the following table
+
+ === === === === ===
+ . foo bar baz zoo
+ === === === === ===
+ 0 one A 1 x
+ 1 one B 2 y
+ 2 one C 3 z
+ 3 two A 4 q
+ 4 two B 5 w
+ 5 two C 6 t
+ === === === === ===
+
+and we want:
+
+ === === === ===
+ . A B C
+ === === === ===
+ one 1 2 3
+ two 4 5 6
+ === === === ===
+
+In Galaxy we would select the following:
+
+ * *Input Single or Multiple Tables* → **Single Table**
+ * *Column names on first row?* → **Yes**
+ * *Row names on first column?* → **Yes**
+ * *Type of table operation* → **Perform a Full Table Operation**
+
+ * *Operation* → **Pivot**
+ * *Index* → "foo"
+ * *Column* → "bar"
+ * *Values* → "baz"
+
+This splits the matrix using "foo" and "bar" using only the values from "baz". Header values may contain extra information.
+
+]]>
+
+
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.1.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,5 @@
+ c1 c2 c3
+g1 10 20 30
+g2 3 6 9
+g3 4 8 12
+g4 81 6 3
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.2.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.2.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,5 @@
+ c1 c2 c3
+g1 10 20 30
+g2 3 6 9
+g3 4 8 12
+g4 81 6 3
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.3p1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.3p1.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,5 @@
+ c1 c2 c3
+g1 10 20 30
+g2 3 6 9
+g3 4 8 12
+g4 81 6 3
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.3p2.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.3p2.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,5 @@
+ c1 c2 c3
+g1 False False False
+g2 True True True
+g3 True True False
+g4 False True True
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.4.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.4.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,5 @@
+ c1 c2 c3
+g1 0 20 30
+g2 3 0 9
+g3 4 8 0
+g4 81 0 0
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.5.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.5.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,5 @@
+ c1 c2 c3
+g1 10 20 30
+g2 3 10 9
+g3 4 8 10
+g4 81 10 10
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.6p1.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.6p1.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,4 @@
+ c1 c2 c3
+g1 10 20 30
+g2 3 10 9
+g3 4 8 10
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.6p2.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.6p2.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,4 @@
+ c1 c2
+g1 1 2
+g2 3 4
+g3 6 5
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.6p3.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.6p3.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,3 @@
+ c1 c2 c3
+g1 1 2 3
+g2 1 2 3
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.7.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.7.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,4 @@
+ A B C
+0 a B 1
+1 b B 3
+2 c B 5
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/examples.8.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/examples.8.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,7 @@
+ foo bar baz zoo
+0 one A 1 x
+1 one B 2 y
+2 one C 3 z
+3 two A 4 q
+4 two B 5 w
+5 two C 6 t
\ No newline at end of file
diff -r 000000000000 -r 1b0f96ed73f2 test-data/mat1.trans.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mat1.trans.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,22 @@
+ CTTCGA GAAGAC GAAGGA GAATCC GAATGG GACAAC GACAGA GACGAA GAGCAA GAGGTA GAGTGA GAGTTG GATACG GATCGA GATCTG GATTGC GCAACA GCAATG GCAGAA GCATGA GCATTC
+ENSDARG00000087616 -0.000000 1.000122 0 6.004399 -0.000000 0 -0.000000 10.012227 1.000122 -0.000000 -0.000000 -0.000000 1.000122 -0.000000 -0.000000 0 4.001954 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000036044 5.003054 -0.000000 0 -0.000000 -0.000000 0 -0.000000 31.117905 -0.000000 -0.000000 -0.000000 -0.000000 1.000122 -0.000000 -0.000000 0 -0.000000 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000036816 -0.000000 1.000122 0 12.017613 -0.000000 0 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 0 5.003054 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000102632 1.000122 -0.000000 0 10.012227 1.000122 0 -0.000000 8.007823 -0.000000 -0.000000 1.000122 -0.000000 1.000122 1.000122 -0.000000 0 1.000122 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000056722 -0.000000 1.000122 0 2.000488 -0.000000 0 -0.000000 17.035376 -0.000000 -0.000000 2.000488 -0.000000 1.000122 -0.000000 -0.000000 0 2.000488 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000098591 -0.000000 -0.000000 0 9.009902 3.001099 0 1.000122 30.110403 -0.000000 -0.000000 1.000122 -0.000000 -0.000000 -0.000000 -0.000000 0 2.000488 -0.000000 0 1.000122 -0.000000
+ENSDARG00000044212 -0.000000 -0.000000 0 -0.000000 -0.000000 0 -0.000000 33.133653 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 4.001954 -0.000000 0 3.001099 -0.000000 0 -0.000000 1.000122
+ENSDARG00000010516 2.000488 -0.000000 0 3.001099 2.000488 0 -0.000000 13.020674 -0.000000 -0.000000 -0.000000 -0.000000 1.000122 -0.000000 -0.000000 0 -0.000000 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000021143 4.001954 -0.000000 0 14.023980 2.000488 0 -0.000000 8.007823 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 0 3.001099 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000042905 1.000122 -0.000000 0 -0.000000 -0.000000 0 -0.000000 22.059294 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 0 1.000122 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000041435 1.000122 -0.000000 0 6.004399 1.000122 0 -0.000000 15.027533 -0.000000 -0.000000 -0.000000 2.000488 -0.000000 -0.000000 -0.000000 0 1.000122 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000034897 2.000488 -0.000000 0 5.003054 1.000122 0 -0.000000 21.054018 1.000122 -0.000000 -0.000000 1.000122 -0.000000 -0.000000 -0.000000 0 1.000122 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000040287 2.000488 2.000488 0 1.000122 -0.000000 0 -0.000000 11.014797 -0.000000 -0.000000 1.000122 -0.000000 -0.000000 -0.000000 -0.000000 0 1.000122 1.000122 0 -0.000000 -0.000000
+ENSDARG00000007320 3.001099 -0.000000 0 1.000122 -0.000000 0 -0.000000 26.082870 -0.000000 -0.000000 1.000122 2.000488 -0.000000 1.000122 -0.000000 0 -0.000000 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000003599 -0.000000 -0.000000 0 2.000488 2.000488 0 -0.000000 27.089382 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 1.000122 0 -0.000000 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000099104 4.001954 -0.000000 0 3.001099 1.000122 0 -0.000000 14.023980 -0.000000 1.000122 -0.000000 -0.000000 -0.000000 2.000488 -0.000000 0 -0.000000 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000071658 -0.000000 1.000122 0 3.001099 -0.000000 0 -0.000000 8.007823 -0.000000 -0.000000 3.001099 -0.000000 -0.000000 -0.000000 -0.000000 0 5.003054 -0.000000 0 -0.000000 1.000122
+ENSDARG00000030408 1.000122 1.000122 0 1.000122 1.000122 0 -0.000000 25.076606 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 0 1.000122 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000039647 -0.000000 -0.000000 0 26.082870 1.000122 0 -0.000000 5.003054 -0.000000 -0.000000 1.000122 -0.000000 -0.000000 -0.000000 -0.000000 0 -0.000000 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000043509 -0.000000 -0.000000 0 -0.000000 1.000122 0 1.000122 27.089382 1.000122 -0.000000 -0.000000 -0.000000 -0.000000 1.000122 -0.000000 0 3.001099 -0.000000 0 -0.000000 -0.000000
+ENSDARG00000017235 1.000122 -0.000000 0 3.001099 1.000122 0 -0.000000 15.027533 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 -0.000000 0 -0.000000 -0.000000 0 -0.000000 -0.000000
diff -r 000000000000 -r 1b0f96ed73f2 test-data/mat1.umi.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mat1.umi.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,22 @@
+ CTTCGA GAAGAC GAAGGA GAATCC GAATGG GACAAC GACAGA GACGAA GAGCAA GAGGTA GAGTGA GAGTTG GATACG GATCGA GATCTG GATTGC GCAACA GCAATG GCAGAA GCATGA GCATTC
+ENSDARG00000087616 0 1 0 6 0 0 0 10 1 0 0 0 1 0 0 0 4 0 0 0 0
+ENSDARG00000036044 5 0 0 0 0 0 0 31 0 0 0 0 1 0 0 0 0 0 0 0 0
+ENSDARG00000036816 0 1 0 12 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 0 0
+ENSDARG00000102632 1 0 0 10 1 0 0 8 0 0 1 0 1 1 0 0 1 0 0 0 0
+ENSDARG00000056722 0 1 0 2 0 0 0 17 0 0 2 0 1 0 0 0 2 0 0 0 0
+ENSDARG00000098591 0 0 0 9 3 0 1 30 0 0 1 0 0 0 0 0 2 0 0 1 0
+ENSDARG00000044212 0 0 0 0 0 0 0 33 0 0 0 0 0 4 0 0 3 0 0 0 1
+ENSDARG00000010516 2 0 0 3 2 0 0 13 0 0 0 0 1 0 0 0 0 0 0 0 0
+ENSDARG00000021143 4 0 0 14 2 0 0 8 0 0 0 0 0 0 0 0 3 0 0 0 0
+ENSDARG00000042905 1 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 1 0 0 0 0
+ENSDARG00000041435 1 0 0 6 1 0 0 15 0 0 0 2 0 0 0 0 1 0 0 0 0
+ENSDARG00000034897 2 0 0 5 1 0 0 21 1 0 0 1 0 0 0 0 1 0 0 0 0
+ENSDARG00000040287 2 2 0 1 0 0 0 11 0 0 1 0 0 0 0 0 1 1 0 0 0
+ENSDARG00000007320 3 0 0 1 0 0 0 26 0 0 1 2 0 1 0 0 0 0 0 0 0
+ENSDARG00000003599 0 0 0 2 2 0 0 27 0 0 0 0 0 0 1 0 0 0 0 0 0
+ENSDARG00000099104 4 0 0 3 1 0 0 14 0 1 0 0 0 2 0 0 0 0 0 0 0
+ENSDARG00000071658 0 1 0 3 0 0 0 8 0 0 3 0 0 0 0 0 5 0 0 0 1
+ENSDARG00000030408 1 1 0 1 1 0 0 25 0 0 0 0 0 0 0 0 1 0 0 0 0
+ENSDARG00000039647 0 0 0 26 1 0 0 5 0 0 1 0 0 0 0 0 0 0 0 0 0
+ENSDARG00000043509 0 0 0 0 1 0 1 27 1 0 0 0 0 1 0 0 3 0 0 0 0
+ENSDARG00000017235 1 0 0 3 1 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0
diff -r 000000000000 -r 1b0f96ed73f2 test-data/mat2.trans.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mat2.trans.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,31 @@
+ AACACC AACCTC AACGAG AACTGG AAGCAC AAGCCA AAGGTG AAGTGC ACAAGC ACAGAC ACAGGA ACAGTG ACATGG ACCAAC ACCAGA ACCATG ACGGTA ACGTAC ACGTGA ACGTTG ACTCAC ACTCGA ACTCTG ACTTCG AGAACG AGACAG AGACCA AGACTC AGATGC AGCGAA AGCTAG AGCTCA AGCTTC AGGAAG AGGACA AGGATC AGGCTA AGTACC AGTAGG AGTGCA AGTGTC ATACGG ATCACG ATCAGC ATCCAC ATCCGA ATCGCA ATCGTG ATCTCC ATGACC ATGAGG ATGCAG ATGCTC ATGGAC ATGTCG ATTCGC ATTGCG CAATGC CACCAA CACGTA CACTCA CACTTC CAGAAG CAGGAA CATGCA CATGTC CATTGG CCAATC CCACAA CCAGTA CCATAG CCATCA CCGATA CCGTAA CCTACA CCTATG CCTGAA CCTTGA CGAACA CGATGA CGATTG CGCATA CGCTAA CGGTTA CGTAAG CGTCTA CGTTAC CGTTCA CTAACG CTAAGC CTAGAC CTAGGA CTAGTG CTATCC CTCAGA CTCATG CTCGAA CTGCTA CTGTTG CTTCGA GAAGAC GAAGGA GAATCC GAATGG GACAAC GACAGA GACGAA GAGCAA GAGGTA GAGTGA GAGTTG GATACG GATCGA GATCTG GATTGC GCAACA GCAATG GCAGAA GCATGA GCATTC GCCATA GCGTTA GCTAAG GCTCTA GCTTAC GCTTCA GGAATC GGACAA GGATAC GGATCA GGCTTA GGTAAC GGTAGA GGTATG GGTGTA GGTTAG GTAACC GTACAG GTACCA GTACTC GTATCG GTATGC GTCTCA GTGAAG GTGACA GTGATC GTGGAA GTTAGG GTTGAG TAACGG TACAGG TACCAC TACCGA TACGCA TACTCC TAGCTC TAGGAC TAGTGG TATCCG TATCGC TCAACG TCACAG TCATCC TCCGAA TCTAGG TCTTGC TGAACC TGAAGG TGAGGA TGATCG TGCAAC TGCAGA TGGTGA TGGTTG TGTACG TGTAGC TGTCGA TGTCTG TGTTCC TGTTGG TTACGC TTCACC TTCCAG TTCGAC TTCTCG TTGCAC TTGCGA TTGCTG TTGGAG TTGGCA TTGGTC TTGTGC
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diff -r 000000000000 -r 1b0f96ed73f2 test-data/mat2.umi.tsv
--- /dev/null Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/mat2.umi.tsv Sat Aug 17 16:25:37 2019 -0400
@@ -0,0 +1,31 @@
+ AACACC AACCTC AACGAG AACTGG AAGCAC AAGCCA AAGGTG AAGTGC ACAAGC ACAGAC ACAGGA ACAGTG ACATGG ACCAAC ACCAGA ACCATG ACGGTA ACGTAC ACGTGA ACGTTG ACTCAC ACTCGA ACTCTG ACTTCG AGAACG AGACAG AGACCA AGACTC AGATGC AGCGAA AGCTAG AGCTCA AGCTTC AGGAAG AGGACA AGGATC AGGCTA AGTACC AGTAGG AGTGCA AGTGTC ATACGG ATCACG ATCAGC ATCCAC ATCCGA ATCGCA ATCGTG ATCTCC ATGACC ATGAGG ATGCAG ATGCTC ATGGAC ATGTCG ATTCGC ATTGCG CAATGC CACCAA CACGTA CACTCA CACTTC CAGAAG CAGGAA CATGCA CATGTC CATTGG CCAATC CCACAA CCAGTA CCATAG CCATCA CCGATA CCGTAA CCTACA CCTATG CCTGAA CCTTGA CGAACA CGATGA CGATTG CGCATA CGCTAA CGGTTA CGTAAG CGTCTA CGTTAC CGTTCA CTAACG CTAAGC CTAGAC CTAGGA CTAGTG CTATCC CTCAGA CTCATG CTCGAA CTGCTA CTGTTG CTTCGA GAAGAC GAAGGA GAATCC GAATGG GACAAC GACAGA GACGAA GAGCAA GAGGTA GAGTGA GAGTTG GATACG GATCGA GATCTG GATTGC GCAACA GCAATG GCAGAA GCATGA GCATTC GCCATA GCGTTA GCTAAG GCTCTA GCTTAC GCTTCA GGAATC GGACAA GGATAC GGATCA GGCTTA GGTAAC GGTAGA GGTATG GGTGTA GGTTAG GTAACC GTACAG GTACCA GTACTC GTATCG GTATGC GTCTCA GTGAAG GTGACA GTGATC GTGGAA GTTAGG GTTGAG TAACGG TACAGG TACCAC TACCGA TACGCA TACTCC TAGCTC TAGGAC TAGTGG TATCCG TATCGC TCAACG TCACAG TCATCC TCCGAA TCTAGG TCTTGC TGAACC TGAAGG TGAGGA TGATCG TGCAAC TGCAGA TGGTGA TGGTTG TGTACG TGTAGC TGTCGA TGTCTG TGTTCC TGTTGG TTACGC TTCACC TTCCAG TTCGAC TTCTCG TTGCAC TTGCGA TTGCTG TTGGAG TTGGCA TTGGTC TTGTGC
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diff -r 000000000000 -r 1b0f96ed73f2 test-data/small.element.scalerem5.tsv
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000
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