def array_filter_yield(array, match, inverse=False):
'''
Description: yields filtered array, match may either be an individual object or an array
'''
if (inverse):
for i in array:
if (__check__.array_test(match)):
if (i not in match):
continue
else:
yield i
else:
if (i != match):
continue
else:
yield i
else:
for i in array:
if (__check__.array_test(match)):
if (i in match):
continue
else:
yield i
else:
if (i == match):
continue
else:
yield i
def str_filter(string, filtre, inverse=False, print_bool=True):
'''
Description: Filters 'filtre' string out of 'string' string, if
'inverse' then the instances of 'filtre' are returned
else the entries not equivalent to 'filtre' are returned
'''
if (not isinstance(string, str)):
try:
string = str(string)
except:
if (print_bool):
print(
"[str_filter] Error: 'string' input could not be cast as a string object"
)
out_list = []
if (inverse):
for i in string:
if (__check__.array_test(filtre)):
if (i in filtre):
out_list.append(i)
else:
if (i == filtre):
out_list.append(i)
else:
for i in string:
if (__check__.array_test(filtre)):
if (i not in filtre):
out_list.append(i)
else:
if (i != filtre):
out_list.append(i)
out_str = array_to_str(out_list, spc='', print_bool=print_bool)
return out_str
def ismatrix(n, numeric=False):
p1 = 'Below is invalid content found in the '
p2 = " entry of 'n'"
if (not __check__.array_test(n)):
return __func_eprint__(
"[ismatrix] Error: input 'n' is not a python array")
index_err = []
err = False
length_err = False
lang = 0
for i in range(len(n)):
if (not __check__.array_test(n[i])):
print("[ismatrix] Error: the " + __strl__.print_ordinal(i + 1) +
" entry in 'n' is not a python array")
err = True
else:
if (i == 0):
lang = len(n[i])
if (numeric):
err_arr = [j for j in n[i] if not __check__.numeric_test(j)]
else:
err_arr = [
j for j in n[i] if not __check__.numeric_test(j)
and not isinstance(j, str)
]
if (len(err_arr) > 0):
err = True
__strl__.format_fancy(err_arr,
header=p1 +
__strl__.print_ordinal(i + 1) + p2)
if (len(n[i]) != lang):
err = True
length_err = True
if (err):
if (length_err):
print(
"[ismatrix] Error: lengths of the enteries of 'n' are not all equal"
)
return False
else:
return True
def coerce_to_matrix(n, fill='NULL'):
if (not __check__.array_test(n)):
text = "[coerce_to_matrix] Error: input 'n' is not a python array; could not coerce to matrix"
return __func_eprint__(text)
newn = list(n)
maxl = 0
for i in range(len(newn)):
if (not __check__.array_test(newn[i])):
text = "[coerce_to_matrix] Error: the " + __strl__.print_ordinal(
i + 1) + " entry in 'n' is not a python array"
return __func_eprint__(text)
if (len(newn[i]) > maxl):
maxl = len(newn[i])
for i in range(len(newn)):
if (len(newn[i]) < maxl):
while (len(newn[i]) < maxl):
newn[i].append(fill)
return newn
def line_nan_check(array, nan=True, inf=True, null=True):
if (not __check__.array_test(array)):
print("[line_nan_check] TypeError: 'array' is not a python array")
return False
check = (nan, inf, null)
check_type = __nan_func__(check)
index_list = []
for i in range(len(array)):
if (__bool_tester__(array[i], check_type)):
index_list.append(i)
else:
pass
if (len(index_list) > 0):
return index_list
else:
return False
def format_fancy(obj,
header=None,
newln=True,
indt=4,
err=True,
list_return=False):
if (newln):
nl = '\n'
else:
nl = ''
spc = indt * ' '
stylized_list = []
if (__check__.array_test(obj)):
if (list_return):
stylized_list.append(' \n')
else:
print(' ')
if (isinstance(header, str)):
out_val = header + nl
if (list_return):
stylized_list.append(out_val)
else:
print(out_val)
for i in obj:
out_val = spc + str(i) + nl
if (list_return):
stylized_list.append(out_val)
else:
print(out_val)
if (list_return):
stylized_list.append(' \n')
return stylized_list
else:
print(' ')
return None
elif (isinstance(obj, str)):
if (list_return):
stylized_list.append(' \n')
else:
print(' ')
if (isinstance(header, str)):
out_val = spc + header + nl
if (list_return):
stylized_list.append(out_val)
else:
print(out_val)
out_val = obj + nl
if (list_return):
stylized_list.append(out_val)
return stylized_list
else:
print(out_val)
return None
else:
print(
"TypeError: 'obj' input object must be either an 'array' or a 'string'"
)
def table_str_to_fill_numeric(line_list,
space=' ',
fill='NULL',
nval=False,
header=False,
entete=True,
columns=True,
nanopt=True,
nantup=(True, True, True),
spc=' ',
genre=float,
debug=True):
'''
Input Variables:
line_list : A array (list or tuple) of strings which form a numeric table (header option allowed)
space : A string of spaces, corrosponds to the number of spaces required for an empty entry
fill : A string, corrosponds to the value which will be added in the place of an empty entry
nval : An integer, corrosponds to the number of values in a row, to which the table will be coerced
If False, the table is read according to parsed spaces
header : If True, treats the first line in the input array as a header and not with the data
entete : If header is True, attempts to return the header with the output numeric table
columns : If True, attempts to return lists of each columns of data, rather than each rows as found in 'line_list'
nanopt : If True, NaN style strings values do not return error values as specified in nantup
nantup : A tuple in the form (nan,inf,null), each value is true if it is allowed
sep : A string, seperator for numeric values in the input table (',' for CSV, space ' ' is default)
genre : A python object function: attempts to coerce object type to 'genre', float is default
debug : If True, checks performs dummy-check on input data, returns printing of point or location of failure
Purpose:
Takes a list of strings and attempts to convert into a table of numeric values
Useful if working with formatted data tables
'''
nan, inf, null = nantup
null = True
if (debug):
fail_test = not __check__.array_test(
line_list) # True if failed array test
if (fail_test):
print(
"[table_str_to_numeric] TypeError: input 'line_list' is not a python array"
)
return False
for i in range(len(line_list)
): # checking if each object in 'line_list' is a string
fail_test = not isinstance(line_list[i],
str) # True if failed string test
if (fail_test):
print(
"[table_str_to_numeric] TypeError: non-string object at line "
+ str(i + 1) + "of 'line_list'")
return False
if (header):
head = line_list[0]
op_list = line_list[1:-1]
n = len(op_list)
try:
head = __strl__.str_to_list(head, spc=spc, filtre=True)
nhead = len(head)
except:
print(
"[table_str_to_fill_numeric] Warning: header could not be parsed"
)
header = False
else:
op_list = list(line_list)
# Parsing list of lines
for i in range(len(op_list)):
string = op_list[i]
temp = __strl__.str_to_fill_list(string,
lngspc=space,
fill=fill,
nval=nval,
spc=spc,
numeric=False)
# Parsing numeric values found in each list
if (nanopt):
nan_list = line_nan_check(temp, nan=nan, inf=inf, null=null)
if (nan_list > 0):
for j in range(len(temp)):
if (temp[j] not in nan_list and temp[j] != fill):
try:
temp[j] = genre(temp[j])
except:
temp[j] = float(temp[j])
else:
nan_list = line_nan_check(temp, False, False, True)
if (nan_list > 0):
for j in range(len(temp)):
if (temp[j] not in nan_list and temp[j] != fill):
try:
temp[j] = genre(temp[j])
except:
temp[j] = float(temp[j])
op_list[i] = temp
if (header and entete):
op_list.insert(0, head)
if (columns):
output = table_trans(op_list, coerce=True, fill=fill)
if (output == False):
print(
"[table_str_to_numeric] Warning: could not transpose table; returning as is"
)
return op_list
else:
return output
else:
return op_list
def table_str_to_numeric(line_list,
header=False,
entete=False,
columns=True,
nanopt=True,
nantup=(True, True, True),
sep=' ',
genre=float,
debug=True):
'''
Input Variables:
line_list : A python array (list or tuple) of strings which form a numeric table (header option allowed)
header : If True, treats the first line in the input array as a header and not with the data
entete : If header, attempts to return the header with the output numeric table
columns : If True, attempts to return each columns of data, rather than input rows found in 'line_list'
nanopt : If True, 'NaN' values do not return error values
nantup : A tuple in the form (nan,inf,null), each value is true if it is allowed
sep : string, seperator for numeric values in the input table (',' for CSV, space ' ' is default)
genre : A python object function: attempts to coerce object type to 'genre', float is default (str, int)
debug : If True, checks performs dummy-check on input data, returns printing of point or location of failure
Purpose:
Takes a list of strings and attempts to convert into a table of numeric values
Useful if working with formatted data tables
'''
nan, inf, null = nantup
if (debug):
fail_test = not __check__.array_test(
line_list) # True if failed array test
if (fail_test):
print(
"[table_str_to_numeric] TypeError: input 'line_list' is not a python array"
)
return False
for i in range(len(line_list)
): # checking if each object in 'line_list' is a string
fail_test = not isinstance(line_list[i],
str) # True if failed string test
if (fail_test):
print(
"[table_str_to_numeric] TypeError: non-string object at line "
+ str(i + 1) + "of 'line_list'")
return False
new_line_list = __strl__.array_filter_spaces(list(line_list))
n = len(new_line_list)
if (header):
head = new_line_list[0]
new_line_list = new_line_list[1:-1]
n = len(new_line_list)
try:
head = __strl__.str_to_list(head, spc=sep, filtre=True)
nhead = len(head)
except:
print("[table_str_to_numeric] Error: header could not be parsed]")
return False
nanopt_test = False
for i in range(n):
new_line_list[i] = __strl__.str_to_list(new_line_list[i],
spc=sep,
filtre=True)
for j in range(len(new_line_list[i])):
try:
if (nanopt):
nanopt_test = nan_check(new_line_list[i][j], nan, inf,
null)
if ((genre == int or genre == long) and nanopt_test == False):
new_line_list[i][j] = genre(float(new_line_list[i][j]))
if ((genre == float or genre == str) and nanopt_test == False):
new_line_list[i][j] = genre(new_line_list[i][j])
except:
print(
"[table_str_to_numeric] Error: failed attempting to parsing table as numeric array"
)
return False
if (header and entete):
try:
new_line_list.insert(0, head)
except:
print(
"[table_str_to_numeric] Warning: error occured when adding header, returning table without it"
)
pass
if (columns):
output = table_trans(new_line_list)
if (output == False):
print(
"[table_str_to_numeric] Warning: could not translate table, returning as is"
)
return new_line_list
else:
return output
else:
return new_line_list
def __ecc_plot__(x,
y,
label=None,
lims=None,
fontsize=20,
save=False,
save_name='plot.jpg'):
'''
__ecc_plot__ : Error correction code plot
return tuple: (xarray, yarray ,labre, limre, fontsize, save, save_name)
'''
# ECC
# Dummy Check for 'x' and 'y'
if (not __check__.array_test(x)):
print("[__ecc_plot__] Error: 'x' must be an array")
return False
if (not __check__.array_test(y)):
print("[__ecc_plot__] Error: 'y' must be an array")
return False
# Checking 'x' for proper formating
xnumeric = True
xarray = True
for i in x:
if (__check__.numeric_test(i)):
xarray = False
elif (__check__.array_test(i)):
xnumeric = False
for j in i:
if (not __check__.numeric_test(j)):
xarray = False
else:
xnumeric, xarray = False, False
if (xarray == False and xnumeric == False):
print(
"[__ecc_plot__] Error: input 'x' must either be a numeric array or an array of numeric arrays"
)
return False
# Checking 'y' for proper formating
ynumeric = True
yarray = True
for i in y:
if (__check__.numeric_test(i)):
yarray = False
elif (__check__.array_test(i)):
ynumeric = False
for j in i:
if (not __check__.numeric_test(j)):
yarray = False
else:
ynumeric, yarray = False, False
if (yarray == False and ynumeric == False):
print(
"[__ecc_plot__] Error: input 'y' must either be a numeric array or an array of numeric arrays"
)
return False
# Special check for a set of y arrays
if (yarray and not xarray):
for i in xrange(len(y)):
if (len(x) != len(y[i])):
print(
"[__ecc_plot__] Error: 'x' should corrospond 1-to-1 for each array in 'y'"
)
return False
if (xarray and not yarray):
print(
"[__ecc_plot__] Error: if 'x' is an array of arrays, then 'y' must be as well"
)
return False
if (xarray):
if (len(x) != len(y)):
print(
"[__ecc_plot__] Error: if 'x' is an array of arrays, then it must have the same length as 'y'"
)
return False
else:
for i in xrange(len(x)):
if (len(x[i]) != len(y[i])):
errmsg = "[__ecc_plot__] Warning: each respective entry of 'x' "
errmsg = errmsg + "should corrospond 1-to-1 to the 'y' entry"
print(errmsg)
return False
# Label checks
labre = False
if (not __check__.array_test(label)):
if (label != None):
print(
"[__ecc_plot__] Warning: input 'label' is not an array and has been deprecated"
)
labre = True
else:
if (len(label) < 2):
print(
"[__ecc_plot__] Warning: input 'label' has a length less than 2 and has been deprecated"
)
labre = True
else:
xlabel, ylabel = label[0], label[1]
if (not isinstance(xlabel, str)):
print(
"[__ecc_plot__] Warning: input 'xlabel' is not string so 'label and has been deprecated"
)
labre = True
if (not isinstance(ylabel, str)):
print(
"[__ecc_plot__] Warning: input 'ylabel' is not string so 'label and has been deprecated"
)
labre = True
# Limit checks
limre = False
if (not __check__.array_test(lims)):
if (lims != None):
print(
"[__ecc_plot__] Warning: input 'lims' is not an array and has been deprecated"
)
limre = True
else:
if (len(lims) < 2):
print(
"[__ecc_plot__] Warning: input 'lims' has a length less than 2 and has been deprecated"
)
limre = True
else:
xlims, ylims = lims[0], lims[1]
if (__check__.array_test(xlims)):
if (not __check__.numeric_test(xlims[0])
or not __check__.numeric_test(xlims[1])):
print(
"[__ecc_plot__] Warning: input 'xlims' is not string so 'lims and has been deprecated"
)
limre = True
else:
limre = True
if (__check__.array_test(ylims)):
if (not __check__.numeric_test(ylims[0])
or not __check__.numeric_test(ylims[1])):
print(
"[__ecc_plot__] Warning: input 'ylims' is not string so 'lims and has been deprecated"
)
limre = True
else:
limre = True
# Checking the rest of the input variables
if (__check__.numeric_test(fontsize)):
fontsize = int(fontsize)
else:
fontsize = 30
if (not isinstance(save, bool)):
save = False
if (not isinstance(save_name, str)):
save_name = 'plot.jpg'
output = (xarray, yarray, labre, limre, fontsize, save, save_name)
return output
def new_four_plot(tl_data,
tr_data,
bl_data,
br_data,
fontsize=20,
lwd=2.5,
label=None,
lims=None,
namelab=None,
smooth=False,
smoothness=300,
save=False,
save_name=None):
fig, axs = __plt__.subplots(2, 2, sharex=False, sharey=False)
tl_xysep, tl_ysep, tl_sep = False, False, False
tr_xysep, tr_ysep, tr_sep = False, False, False
bl_xysep, bl_ysep, bl_sep = False, False, False
br_xysep, br_ysep, br_sep = False, False, False
if (smooth):
spln_inst = __mops__.spline()
if (not __check__.array_test(label)):
tl_label, tr_label, bl_label, br_label = [[' ', ' '], [' ', ' '],
[' ', ' '], [' ', ' ']]
else:
if (len(label) != 4):
tl_label, tr_label, bl_label, br_label = [[' ', ' '], [' ', ' '],
[' ', ' '], [' ', ' ']]
else:
tl_label = label[0]
tr_label = label[1]
bl_label = label[2]
br_label = label[3]
try:
x, y = tl_data
except:
print(
"Error: input data 'tl_data' must be a python array of length two")
test = __ecc_plot__(x, y, tl_label, lims, fontsize, save, save_name)
if (test == False):
print(
"[new_plot] Error: 'tl_data' (top-left) data test failed, see preceding error msg for details"
)
return False
else:
tl_xarray, tl_yarray, tl_labre, tl_limre, tl_fontsize, save, save_name = test
if (tl_xarray and tl_yarray):
tl_xysep = True
elif (tl_yarray):
tl_ysep = True
else:
tl_sep = True
if (tl_labre):
tl_label = (None, None)
if (tl_limre):
tl_lims = (None, None)
try:
x, y = tr_data
except:
print(
"Error: input data 'tr_data' must be a python array of length two")
test = __ecc_plot__(x, y, tr_label, lims, fontsize, save, save_name)
if (test == False):
print(
"[new_plot] Error: 'tr_data' (top-right) data test failed, see preceding error msg for details"
)
return False
else:
tr_xarray, tr_yarray, tr_labre, tr_limre, tr_fontsize, save, save_name = test
if (tr_xarray and tr_yarray):
tr_xysep = True
elif (tr_yarray):
tr_ysep = True
else:
tr_sep = True
if (tr_labre):
tr_label = (None, None)
if (tr_limre):
tr_lims = (None, None)
try:
x, y = bl_data
except:
print(
"Error: input data 'bl_data' must be a python array of length two")
test = __ecc_plot__(x, y, bl_label, lims, fontsize, save, save_name)
if (test == False):
print(
"[new_plot] Error: 'bl_data' (bottom-left) data test failed, see preceding error msg for details"
)
return False
else:
bl_xarray, bl_yarray, bl_labre, bl_limre, bl_fontsize, save, save_name = test
if (bl_xarray and bl_yarray):
bl_xysep = True
elif (bl_yarray):
bl_ysep = True
else:
bl_sep = True
if (bl_labre):
bl_label = (None, None)
if (bl_limre):
bl_lims = (None, None)
try:
x, y = br_data
except:
print(
"Error: input data 'br_data' must be a python array of length two")
test = __ecc_plot__(x, y, br_label, lims, fontsize, save, save_name)
if (test == False):
print(
"[new_plot] Error: 'br_data' (bottom-right) data test failed, see preceding error msg for details"
)
return False
else:
br_xarray, br_yarray, br_labre, br_limre, br_fontsize, save, save_name = test
if (br_xarray and br_yarray):
br_xysep = True
elif (br_yarray):
br_ysep = True
else:
br_sep = True
if (br_labre):
br_label = (None, None)
if (br_limre):
br_lims = (None, None)
# Top-Left plot
x, y = tl_data
if (tl_sep):
if (smooth):
xsmooth = __mops__.span_vec(x, smoothness)
spln_inst.pass_vecs(x, y, xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x
tempy = y
axs[0, 0].plot(tempx, tempy, linewidth=lwd)
elif (tl_ysep):
for i in y:
if (smooth):
xsmooth = __mops__.span_vec(x, smoothness)
spln_inst.pass_vecs(x, i, xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x
tempy = i
axs[0, 0].plot(tempx, tempy, linewidth=lwd)
elif (tl_xysep):
for i in xrange(len(x)):
if (smooth):
xsmooth = __mops__.span_vec(x[i], smoothness)
spln_inst.pass_vecs(x[i], y[i], xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x[i]
tempy = y[i]
axs[0, 0].plot(tempx, tempy, linewidth=lwd)
if (namelab != None):
try:
axs[0, 0].set_title(str(namelab[0]))
except:
pass
if (tl_label != (None, None)):
axs[0, 0].set(xlabel=tl_label[0], ylabel=tl_label[1])
# Top-Right plot
x, y = tr_data
if (tr_sep):
if (smooth):
xsmooth = __mops__.span_vec(x, smoothness)
spln_inst.pass_vecs(x, y, xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x
tempy = y
axs[0, 1].plot(tempx, tempy, linewidth=lwd)
elif (tr_ysep):
for i in y:
if (smooth):
xsmooth = __mops__.span_vec(x, smoothness)
spln_inst.pass_vecs(x, i, xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x
tempy = i
axs[0, 1].plot(tempx, tempy, linewidth=lwd)
elif (tr_xysep):
for i in xrange(len(x)):
if (smooth):
xsmooth = __mops__.span_vec(x[i], smoothness)
spln_inst.pass_vecs(x[i], y[i], xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x[i]
tempy = y[i]
axs[0, 1].plot(tempx, tempy, linewidth=lwd)
if (namelab != None):
try:
axs[0, 1].set_title(str(namelab[1]))
except:
pass
if (tr_label != (None, None)):
axs[0, 1].set(xlabel=tr_label[0], ylabel=tr_label[1])
# Bottom-Left plot
x, y = bl_data
if (bl_sep):
if (smooth):
xsmooth = __mops__.span_vec(x, smoothness)
spln_inst.pass_vecs(x, y, xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x
tempy = y
axs[1, 0].plot(tempx, tempy, linewidth=lwd)
elif (bl_ysep):
for i in y:
if (smooth):
xsmooth = __mops__.span_vec(x, smoothness)
spln_inst.pass_vecs(x, i, xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x
tempy = i
axs[1, 0].plot(tempx, tempy, linewidth=lwd)
elif (bl_xysep):
for i in xrange(len(x)):
if (smooth):
xsmooth = __mops__.span_vec(x[i], smoothness)
spln_inst.pass_vecs(x[i], y[i], xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x[i]
tempy = y[i]
axs[1, 0].plot(tempx, tempy, linewidth=lwd)
if (namelab != None):
try:
axs[1, 0].set_title(str(namelab[2]))
except:
pass
if (bl_label != (None, None)):
axs[1, 0].set(xlabel=bl_label[0], ylabel=bl_label[1])
# Bottom-Right plot
x, y = br_data
if (br_sep):
if (smooth):
xsmooth = __mops__.span_vec(x, smoothness)
spln_inst.pass_vecs(x, y, xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x
tempy = y
axs[1, 1].plot(tempx, tempy, linewidth=lwd)
elif (br_ysep):
for i in y:
if (smooth):
xsmooth = __mops__.span_vec(x, smoothness)
spln_inst.pass_vecs(x, i, xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x
tempy = i
axs[1, 1].plot(tempx, tempy, linewidth=lwd)
elif (br_xysep):
for i in xrange(len(x)):
if (smooth):
xsmooth = __mops__.span_vec(x[i], smoothness)
spln_inst.pass_vecs(x[i], y[i], xsmooth)
spln_inst.pass_spline()
ysmooth = spln_inst.get_spline()
tempx = xsmooth
tempy = ysmooth
else:
tempx = x[i]
tempy = y[i]
axs[1, 1].plot(tempx, tempy, linewidth=lwd)
if (namelab != None):
try:
axs[1, 1].set_title(str(namelab[3]))
except:
pass
if (br_label != (None, None)):
axs[1, 1].set(xlabel=br_label[0], ylabel=br_label[1])
__plt__.tight_layout()
__plt__.show()
if (save):
try:
fig.savefig(save_name)
except:
print("Error: attempted and failed to print graph as " +
str(save_name))
return True