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Vasudevan, Rama K
pycroscopy
Commits
cfac8e18
Commit
cfac8e18
authored
May 19, 2017
by
Somnath, Suhas
Browse files
Removed many instances of python 2 print statements
parent
0bcd5e40
Changes
7
Hide whitespace changes
Inline
Side-by-side
pycroscopy/analysis/be_loop_model.py
View file @
cfac8e18
...
...
@@ -580,8 +580,8 @@ class BELoopModel(Model):
warn
(
'Error - could not reshape provided raw data chunk...'
)
return
None
if
verbose
:
print
'Shape of N dimensional dataset:'
,
fit_nd
.
shape
print
'Dimensions of order:'
,
dim_names_orig
print
(
'Shape of N dimensional dataset:'
,
fit_nd
.
shape
)
print
(
'Dimensions of order:'
,
dim_names_orig
)
# order_dc_outside_nd = np.roll(range(fit_nd.ndim), -self._dc_offset_index)
# order_dc_offset_reverse = np.roll(range(fit_nd.ndim), self._dc_offset_index)
...
...
@@ -594,13 +594,13 @@ class BELoopModel(Model):
fit_nd2
=
np
.
transpose
(
fit_nd
,
tuple
(
order_dc_outside_nd
))
dim_names_dc_out
=
dim_names_orig
[
order_dc_outside_nd
]
if
verbose
:
print
'originally:'
,
fit_nd
.
shape
,
', after moving DC offset outside:'
,
fit_nd2
.
shape
print
'new dim names:'
,
dim_names_dc_out
print
(
'originally:'
,
fit_nd
.
shape
,
', after moving DC offset outside:'
,
fit_nd2
.
shape
)
print
(
'new dim names:'
,
dim_names_dc_out
)
# step 6: reshape the ND data to 2D arrays
loops_2d
=
np
.
reshape
(
fit_nd2
,
(
fit_nd2
.
shape
[
0
],
-
1
))
if
verbose
:
print
'Loops ready to be projected of shape (Vdc, all other dims besides FORC):'
,
loops_2d
.
shape
print
(
'Loops ready to be projected of shape (Vdc, all other dims besides FORC):'
,
loops_2d
.
shape
)
return
loops_2d
,
order_dc_offset_reverse
,
fit_nd2
.
shape
...
...
@@ -628,15 +628,15 @@ class BELoopModel(Model):
Projected loops reshaped to the original chronological order in which the data was acquired
"""
if
verbose
:
print
'Projected loops of shape:'
,
projected_loops_2d
.
shape
,
', need to bring to:'
,
nd_mat_shape_dc_first
print
(
'Projected loops of shape:'
,
projected_loops_2d
.
shape
,
', need to bring to:'
,
nd_mat_shape_dc_first
)
# Step 9: Reshape back to same shape as fit_Nd2:
projected_loops_nd
=
np
.
reshape
(
projected_loops_2d
,
nd_mat_shape_dc_first
)
if
verbose
:
print
'Projected loops reshaped to N dimensions :'
,
projected_loops_nd
.
shape
print
(
'Projected loops reshaped to N dimensions :'
,
projected_loops_nd
.
shape
)
# Step 10: Move Vdc back inwards. Only for projected loop
projected_loops_nd_2
=
np
.
transpose
(
projected_loops_nd
,
order_dc_offset_reverse
)
if
verbose
:
print
'Projected loops after moving DC offset inwards:'
,
projected_loops_nd_2
.
shape
print
(
'Projected loops after moving DC offset inwards:'
,
projected_loops_nd_2
.
shape
)
# step 11: reshape back to 2D
proj_loops_2d
,
success
=
reshape_from_Ndims
(
projected_loops_nd_2
,
h5_pos
=
None
,
...
...
@@ -646,7 +646,7 @@ class BELoopModel(Model):
warn
(
'unable to reshape projected loops'
)
return
None
if
verbose
:
print
'loops shape after collapsing dimensions:'
,
proj_loops_2d
.
shape
print
(
'loops shape after collapsing dimensions:'
,
proj_loops_2d
.
shape
)
return
proj_loops_2d
...
...
@@ -671,7 +671,7 @@ class BELoopModel(Model):
Loop metrics reshaped to the original chronological order in which the data was acquired
"""
if
verbose
:
print
'Loop metrics of shape:'
,
raw_results
.
shape
print
(
'Loop metrics of shape:'
,
raw_results
.
shape
)
# Step 9: Reshape back to same shape as fit_Nd2:
if
not
self
.
_met_all_but_forc_inds
:
spec_inds
=
None
...
...
@@ -681,7 +681,7 @@ class BELoopModel(Model):
loop_metrics_nd
=
np
.
reshape
(
raw_results
,
nd_mat_shape_dc_first
[
1
:])
if
verbose
:
print
'Loop metrics reshaped to N dimensions :'
,
loop_metrics_nd
.
shape
print
(
'Loop metrics reshaped to N dimensions :'
,
loop_metrics_nd
.
shape
)
# step 11: reshape back to 2D
metrics_2d
,
success
=
reshape_from_Ndims
(
loop_metrics_nd
,
...
...
@@ -691,7 +691,7 @@ class BELoopModel(Model):
warn
(
'unable to reshape ND results back to 2D'
)
return
None
if
verbose
:
print
'metrics shape after collapsing dimensions:'
,
metrics_2d
.
shape
print
(
'metrics shape after collapsing dimensions:'
,
metrics_2d
.
shape
)
return
metrics_2d
...
...
pycroscopy/io/parse_dm3.py
View file @
cfac8e18
...
...
@@ -3,6 +3,7 @@ import array
import
StringIO
import
logging
import
re
# mfm 2013-05-21 do we need the numpy array stuff? The python array module
# allows us to store arrays easily and efficiently. How do we deal
# with arrays of complex data? We could use numpy arrays with custom dtypes
...
...
@@ -23,7 +24,7 @@ verbose = False
treat_as_string_names
=
[
'.*Name'
]
def
get_from_file
(
f
,
stype
):
#print
"reading", stype, "size", struct.calcsize(stype)
#
print
(
"reading", stype, "size", struct.calcsize(stype)
)
src
=
f
.
read
(
struct
.
calcsize
(
stype
))
assert
(
len
(
src
)
==
struct
.
calcsize
(
stype
))
d
=
struct
.
unpack
(
stype
,
src
)
...
...
@@ -103,7 +104,7 @@ def parse_dm_header(f, outdata=None):
start
=
f
.
tell
()
ret
=
parse_dm_tag_root
(
f
,
outdata
)
end
=
f
.
tell
()
# print
"fs", file_size, end - start, (end-start)%8
# print
(
"fs", file_size, end - start, (end-start)%8
)
# mfm 2013-07-11 the file_size value is not always
# end-start, sometimes there seems to be an extra 4 bytes,
# other times not. Let's just ignore it for the moment
...
...
@@ -120,28 +121,28 @@ def parse_dm_tag_root(f, outdata=None):
put_into_file
(
f
,
"> b b l"
,
is_dict
,
_open
,
num_tags
)
if
not
is_dict
:
if
verbose
:
print
"list:"
,
outdata
print
(
"list:"
,
outdata
)
for
subdata
in
outdata
:
parse_dm_tag_entry
(
f
,
subdata
,
None
)
else
:
if
verbose
:
print
"dict:"
,
outdata
print
(
"dict:"
,
outdata
)
for
key
in
outdata
:
if
verbose
:
print
"Writing"
,
key
,
outdata
[
key
]
print
(
"Writing"
,
key
,
outdata
[
key
]
)
assert
(
key
is
not
None
)
parse_dm_tag_entry
(
f
,
outdata
[
key
],
key
)
else
:
is_dict
,
_open
,
num_tags
=
get_from_file
(
f
,
"> b b l"
)
if
verbose
:
print
"New tag root"
,
is_dict
,
_open
,
num_tags
print
(
"New tag root"
,
is_dict
,
_open
,
num_tags
)
if
is_dict
:
new_obj
=
{}
for
i
in
range
(
num_tags
):
name
,
data
=
parse_dm_tag_entry
(
f
)
assert
(
name
is
not
None
)
if
verbose
:
print
"Read name"
,
name
,
"at"
,
f
.
tell
()
print
(
"Read name"
,
name
,
"at"
,
f
.
tell
()
)
new_obj
[
name
]
=
data
else
:
new_obj
=
[]
...
...
@@ -149,7 +150,7 @@ def parse_dm_tag_root(f, outdata=None):
name
,
data
=
parse_dm_tag_entry
(
f
)
assert
(
name
is
None
)
if
verbose
:
print
"appending..."
,
i
,
"at"
,
f
.
tell
()
print
(
"appending..."
,
i
,
"at"
,
f
.
tell
()
)
new_obj
.
append
(
data
)
return
new_obj
...
...
@@ -206,7 +207,7 @@ def parse_dm_tag_data(f, outdata=None):
# ie can all numbers be doubles or ints, and we have lists
_
,
data_type
=
get_structdmtypes_for_python_typeorobject
(
outdata
)
if
verbose
:
print
"treating {} as {}"
.
format
(
outdata
,
data_type
)
print
(
"treating {} as {}"
.
format
(
outdata
,
data_type
)
)
if
not
data_type
:
raise
Exception
(
"Unsupported type: {}"
.
format
(
type
(
outdata
)))
_delim
=
"%%%%"
...
...
@@ -349,7 +350,7 @@ def dm_read_string(f, outdata=None):
slen
=
get_from_file
(
f
,
">L"
)
raws
=
get_from_file
(
f
,
">"
+
str
(
slen
)
+
"s"
)
if
verbose
:
print
"Got String"
,
unicode
(
raws
,
"utf_16_le"
),
"at"
,
f
.
tell
()
print
(
"Got String"
,
unicode
(
raws
,
"utf_16_le"
),
"at"
,
f
.
tell
()
)
return
unicode
(
raws
,
"utf_16_le"
),
header_size
dm_types
[
get_dmtype_for_name
(
'string'
)]
=
dm_read_string
...
...
@@ -400,7 +401,7 @@ def dm_read_struct(f, outdata=None):
else
:
types
,
header
=
dm_read_struct_types
(
f
)
if
verbose
:
print
"Found struct with types"
,
types
,
"at"
,
f
.
tell
()
print
(
"Found struct with types"
,
types
,
"at"
,
f
.
tell
()
)
ret
=
[]
for
t
in
types
:
...
...
@@ -453,8 +454,8 @@ def dm_read_array(f, outdata=None):
types
,
struct_header
=
dm_read_struct_types
(
f
)
alen
=
get_from_file
(
f
,
"> L"
)
if
verbose
:
print
types
print
"Array of structs! types %s, len %d"
%
(
","
.
join
(
map
(
str
,
types
)),
alen
),
"at"
,
f
.
tell
()
print
(
types
)
print
(
"Array of structs! types %s, len %d"
%
(
","
.
join
(
map
(
str
,
types
)),
alen
),
"at"
,
f
.
tell
()
)
ret
=
structarray
([
get_structchar_for_dmtype
(
d
)
for
d
in
types
])
ret
.
from_file
(
f
,
alen
)
return
ret
,
array_header
+
struct_header
...
...
@@ -467,15 +468,15 @@ def dm_read_array(f, outdata=None):
ret
=
array
.
array
(
struct_char
)
alen
=
get_from_file
(
f
,
"> L"
)
if
verbose
:
print
"Array type %d len %d struct %c size %d"
%
(
dtype
,
alen
,
struct_char
,
struct
.
calcsize
(
struct_char
)),
"at"
,
f
.
tell
()
print
(
"Array type %d len %d struct %c size %d"
%
(
dtype
,
alen
,
struct_char
,
struct
.
calcsize
(
struct_char
)),
"at"
,
f
.
tell
()
)
if
alen
:
# faster to read <1024f than <f 1024 times. probly
# stype = "<" + str(alen) + dm_simple_names[dtype][1]
# ret = get_from_file(f, stype)
read_array
(
f
,
ret
,
alen
)
if
verbose
:
print
"Done Array type %d len %d"
%
(
dtype
,
alen
),
"at"
,
f
.
tell
()
print
(
"Done Array type %d len %d"
%
(
dtype
,
alen
),
"at"
,
f
.
tell
()
)
return
ret
,
array_header
dm_types
[
get_dmtype_for_name
(
'array'
)]
=
dm_read_array
pycroscopy/io/translators/be_utils.py
View file @
cfac8e18
...
...
@@ -288,8 +288,8 @@ def normalizeBEresponse(spectrogram_mat, FFT_BE_wave, harmonic):
scaling_factor
=
np
.
fft
.
fftshift
(
np
.
fft
.
fft
(
BE_wave
**
2
))
/
(
2
*
np
.
exp
(
1j
*
3
*
np
.
pi
*
0.5
))
elif
harmonic
==
3
:
scaling_factor
=
np
.
fft
.
fftshift
(
np
.
fft
.
fft
(
BE_wave
**
3
))
/
(
4
*
np
.
exp
(
1j
*
np
.
pi
))
elif
harmonic
>=
4
:
print
"Warning these high harmonics are not supported in translator."
elif
harmonic
>=
4
:
print
(
"Warning these high harmonics are not supported in translator."
)
# Generate transfer functions
F_AO_spectrogram
=
np
.
transpose
(
np
.
tile
(
FFT_BE_wave
/
scaling_factor
,
[
spectrogram_mat
.
shape
[
1
],
1
]))
...
...
@@ -1287,7 +1287,7 @@ class BEHistogram():
max_resp
=
[]
min_resp
=
[]
print
'Creating BEHistogram for Plot Group {}'
.
format
(
p_group
.
name
)
print
(
'Creating BEHistogram for Plot Group {}'
.
format
(
p_group
.
name
)
)
udvs_lab
=
p_group
.
attrs
[
'Name'
]
udvs_col
=
h5_udvs
[
im
][
h5_udvs
[
im
].
attrs
[
udvs_lab
]]
actual_udvs_steps
=
np
.
where
(
np
.
isnan
(
udvs_col
)
==
False
)[
0
]
...
...
@@ -1337,7 +1337,7 @@ class BEHistogram():
"""
free_mem
=
getAvailableMem
()
if
debug
:
print
'We have {} bytes of memory available'
.
format
(
free_mem
)
if
debug
:
print
(
'We have {} bytes of memory available'
.
format
(
free_mem
)
)
self
.
max_mem
=
min
(
max_mem_mb
*
1024
**
2
,
0.75
*
free_mem
)
"""
...
...
@@ -1372,17 +1372,17 @@ class BEHistogram():
self
.
N_bins
=
np
.
size
(
freqs_mat
)
self
.
N_freqs
=
np
.
size
(
np
.
unique
(
freqs_mat
))
# print
'There are {} total frequencies in this dataset'.format(self.N_bins)
# print
(
'There are {} total frequencies in this dataset'.format(self.N_bins)
)
del
freqs_mat
,
spec_ind_mat
self
.
N_pixels
=
np
.
shape
(
h5_main
)[
1
]
# print
'There are {} pixels in this dataset'.format(self.N_pixels)
# print
(
'There are {} pixels in this dataset'.format(self.N_pixels)
)
self
.
N_y_bins
=
np
.
int
(
np
.
min
(
(
max_bins
,
np
.
rint
(
np
.
sqrt
(
self
.
N_pixels
*
self
.
N_spectral_steps
)))))
# self.N_y_bins = np.min( (max_bins, np.rint(2*(self.N_pixels*self.N_spectral_steps)**(1.0/3.0))))
# print
'{} bins will be used'.format(self.N_y_bins)
# print
(
'{} bins will be used'.format(self.N_y_bins)
)
ds_hist
=
self
.
__datasetHist
(
h5_main
,
active_udvs_steps
,
x_hist
,
debug
)
ds_hist
=
self
.
__datasetHist
(
h5_main
,
active_udvs_steps
,
x_hist
,
debug
)
return
ds_hist
...
...
@@ -1557,9 +1557,9 @@ class BEHistogram():
loop over pixels
"""
for
ichunk
in
range
(
len
(
pix_chunks
)
-
1
):
if
debug
:
print
'pixel chunk'
,
ichunk
if
debug
:
print
(
'pixel chunk'
,
ichunk
)
chunk
=
range
(
pix_chunks
[
ichunk
],
pix_chunks
[
ichunk
+
1
])
chunk
=
range
(
pix_chunks
[
ichunk
],
pix_chunks
[
ichunk
+
1
])
"""
Loop over active UDVS steps
...
...
pycroscopy/processing/proc_utils.py
View file @
cfac8e18
...
...
@@ -49,7 +49,7 @@ def buildHistogram(x_hist, data_mat, N_x_bins, N_y_bins, weighting_vec=1, min_re
min_resp
=
np
.
minb
(
y_hist
)
if
max_resp
is
None
:
max_resp
=
np
.
max
(
y_hist
)
if
debug
:
print
'min_resp'
,
min_resp
,
'max_resp'
,
max_resp
if
debug
:
print
(
'min_resp'
,
min_resp
,
'max_resp'
,
max_resp
)
y_hist
=
__scale_and_descritize
(
y_hist
,
N_y_bins
,
max_resp
,
min_resp
,
debug
)
...
...
@@ -57,8 +57,8 @@ def buildHistogram(x_hist, data_mat, N_x_bins, N_y_bins, weighting_vec=1, min_re
Combine x_hist and y_hist into one matrix
'''
if
debug
:
print
np
.
shape
(
x_hist
)
print
np
.
shape
(
y_hist
)
print
(
np
.
shape
(
x_hist
)
)
print
(
np
.
shape
(
y_hist
)
)
try
:
group_idx
=
np
.
zeros
((
2
,
x_hist
.
size
),
dtype
=
np
.
int32
)
...
...
@@ -71,9 +71,9 @@ def buildHistogram(x_hist, data_mat, N_x_bins, N_y_bins, weighting_vec=1, min_re
Aggregate matrix for histogram of current chunk
'''
if
debug
:
print
np
.
shape
(
group_idx
)
print
np
.
shape
(
weighting_vec
)
print
N_x_bins
,
N_y_bins
print
(
np
.
shape
(
group_idx
)
)
print
(
np
.
shape
(
weighting_vec
)
)
print
(
N_x_bins
,
N_y_bins
)
try
:
pixel_hist
=
aggregate_np
(
group_idx
,
weighting_vec
,
func
=
'sum'
,
size
=
(
N_x_bins
,
N_y_bins
),
dtype
=
np
.
int32
)
...
...
@@ -108,6 +108,6 @@ def __scale_and_discretize(y_hist, N_y_bins, max_resp, min_resp, debug=False):
'''
y_hist
=
np
.
rint
(
y_hist
*
(
N_y_bins
-
1
))
if
debug
:
print
'ymin'
,
min
(
y_hist
),
'ymax'
,
max
(
y_hist
)
print
(
'ymin'
,
min
(
y_hist
),
'ymax'
,
max
(
y_hist
)
)
return
y_hist
pycroscopy/processing/svd_utils.py
View file @
cfac8e18
...
...
@@ -62,14 +62,14 @@ def doSVD(h5_main, num_comps=None):
C.Smith -- We might need to put a lower limit on num_comps in the future. I don't
know enough about svd to be sure.
'''
print
'Performing SVD decomposition'
print
(
'Performing SVD decomposition'
)
U
,
S
,
V
=
randomized_svd
(
func
(
h5_main
),
num_comps
,
n_iter
=
3
)
svd_type
=
'sklearn-randomized'
print
'SVD took {} seconds. Writing results to file.'
.
format
((
time
.
time
()
-
t1
))
print
(
'SVD took {} seconds. Writing results to file.'
.
format
((
time
.
time
()
-
t1
))
)
'''
Create datasets for V and S, deleting original arrays afterward to save
...
...
@@ -249,7 +249,7 @@ def rebuild_svd(h5_main, components=None, cores=None, max_RAM_mb=1024):
# Ensuring that at least one core is available for use / 2 cores are available for other use
max_cores
=
max
(
1
,
cpu_count
()
-
2
)
# print
'max_cores',max_cores
# print
(
'max_cores',max_cores
)
if
cores
is
not
None
:
cores
=
min
(
round
(
abs
(
cores
)),
max_cores
)
else
:
...
...
pycroscopy/versioner.py
View file @
cfac8e18
...
...
@@ -6,11 +6,12 @@ Created on Mar 14, 2016
import
os
import
datetime
import
argparse
if
__name__
==
'__main__'
:
parser
=
argparse
.
ArgumentParser
(
prog
=
'PySPM Versioner'
,
description
=
'Increments the version number for PySPM'
)
parser
.
add_argument
(
'--manual'
,
type
=
str
,
default
=
None
)
parser
.
add_argument
(
'--minor'
,
default
=
False
,
action
=
'store_true'
)
parser
.
add_argument
(
'--major'
,
default
=
False
,
action
=
'store_true'
)
parser
.
add_argument
(
'--manual'
,
type
=
str
,
default
=
None
)
parser
.
add_argument
(
'--minor'
,
default
=
False
,
action
=
'store_true'
)
parser
.
add_argument
(
'--major'
,
default
=
False
,
action
=
'store_true'
)
args
=
parser
.
parse_args
()
new_minor
=
args
.
minor
new_major
=
args
.
major
...
...
@@ -28,17 +29,17 @@ if __name__ == '__main__':
vc_time
=
0
vm_time
=
0
v_time
=
0
dir_version
=
[
0
,
0
,
0
]
#
print
root, 'contains'
#
print
'directories', dirs
#
print
'files', files
dir_version
=
[
0
,
0
,
0
]
#
print
(
root, 'contains'
)
#
print
(
'directories', dirs
)
#
print
(
'files', files
)
f_time
=
0
for
file
in
files
:
if
file
.
split
(
'.'
)[
1
]
==
'pyc'
:
continue
elif
file
==
self_name
:
continue
file_path
=
os
.
path
.
join
(
root
,
file
)
file_path
=
os
.
path
.
join
(
root
,
file
)
f_stats
=
os
.
stat
(
file_path
)
if
file
==
'__version__.py'
:
vc_time
=
f_stats
[
9
]
...
...
@@ -46,18 +47,18 @@ if __name__ == '__main__':
v_time
=
max
([
vc_time
,
vm_time
])
fc_time
=
f_stats
[
9
]
fm_time
=
f_stats
[
8
]
f_time
=
max
([
fc_time
,
fm_time
,
f_time
])
#
print
'{} was created {} and modified {}.'.format(file, fc_time, fm_time)
f_time
=
max
([
fc_time
,
fm_time
,
f_time
])
#
print
(
'{} was created {} and modified {}.'.format(file, fc_time, fm_time)
if
v_time
==
0
:
#
print
'No version file found. Will create new at version 0.0.1'
v_file
=
open
(
os
.
path
.
join
(
root
,
'__version__.py'
),
'w'
)
#
print
(
'No version file found. Will create new at version 0.0.1'
)
v_file
=
open
(
os
.
path
.
join
(
root
,
'__version__.py'
),
'w'
)
new_version
=
True
elif
root
==
main_dir
:
continue
else
:
#
print
'Version file found. Reading old version number.'
v_file
=
open
(
os
.
path
.
join
(
root
,
'__version__.py'
),
'r+'
)
#
print
(
'Version file found. Reading old version number.'
))
v_file
=
open
(
os
.
path
.
join
(
root
,
'__version__.py'
),
'r+'
)
for
iline
,
line
in
enumerate
(
v_file
.
readlines
()):
line
=
line
.
split
()
if
line
==
[]:
...
...
@@ -73,36 +74,36 @@ if __name__ == '__main__':
new_version
=
f_time
<
v_time
if
dir_version
==
[
0
,
0
,
0
]:
#
print
'Blank version file.'
if
dir_version
==
[
0
,
0
,
0
]:
#
print
(
'Blank version file.'
)
new_version
=
True
#
print
'Old version was {}.{}.{}'.format(*dir_version)
#
print
(
'Old version was {}.{}.{}'.format(*dir_version)
)
if
new_version
:
print
'Files have been modified since last version.'
print
(
'Files have been modified since last version.'
)
new_main_version
=
True
dir_version
[
2
]
+=
1
dir_version
[
2
]
+=
1
if
new_minor
:
dir_version
[
1
]
+=
1
dir_version
[
1
]
+=
1
dir_version
[
2
]
=
0
if
new_major
:
dir_version
[
0
]
+=
1
dir_version
[
0
]
+=
1
dir_version
[
1
]
=
0
dir_version
[
2
]
=
0
v_file
.
seek
(
0
)
v_file
.
write
(
'major
\t
=
\t
{}
\n
'
.
format
(
dir_version
[
0
]))
v_file
.
write
(
'minor
\t
=
\t
{}
\n
'
.
format
(
dir_version
[
1
]))
v_file
.
write
(
'micro
\t
=
\t
{}
\n
'
.
format
(
dir_version
[
2
]))
print
'New version is {}.{}.{}'
.
format
(
*
dir_version
)
print
(
'New version is {}.{}.{}'
.
format
(
*
dir_version
)
)
v_file
.
close
()
if
new_main_version
:
mv_file
=
open
(
os
.
path
.
join
(
main_dir
,
'__version__.py'
),
'r+'
)
mv_file
=
open
(
os
.
path
.
join
(
main_dir
,
'__version__.py'
),
'r+'
)
mv_version
=
'0.0.1'
ver_date
=
datetime
.
datetime
.
now
()
mv_date
=
'{}/{}/{}'
.
format
(
ver_date
.
month
,
ver_date
.
day
,
ver_date
.
year
)
mv_date
=
'{}/{}/{}'
.
format
(
ver_date
.
month
,
ver_date
.
day
,
ver_date
.
year
)
for
line
in
mv_file
.
readlines
():
print
line
print
(
line
)
if
line
.
strip
()
==
''
:
continue
field
,
value
=
line
.
split
(
'='
)
...
...
@@ -113,29 +114,29 @@ if __name__ == '__main__':
elif
field
==
'time'
:
mv_time
=
value
.
strip
[
'
\'
'
]
mv_major
,
mv_minor
,
mv_micro
=
mv_version
.
split
(
'.'
)
mv_major
,
mv_minor
,
mv_micro
=
mv_version
.
split
(
'.'
)
mv_micro
=
str
(
int
(
mv_micro
)
+
1
)
if
new_minor
:
mv_minor
+=
1
mv_minor
+=
1
mv_micro
=
0
if
new_major
:
mv_major
+=
1
mv_major
+=
1
mv_minor
=
0
mv_micro
=
0
if
args
.
manual
:
mv_version
=
args
.
manual
else
:
mv_version
=
'.'
.
join
([
mv_major
,
mv_minor
,
mv_micro
])
mv_time
=
'{}:{}:{}'
.
format
(
ver_date
.
hour
,
ver_date
.
minute
,
ver_date
.
second
)
mv_version
=
'.'
.
join
([
mv_major
,
mv_minor
,
mv_micro
])
mv_time
=
'{}:{}:{}'
.
format
(
ver_date
.
hour
,
ver_date
.
minute
,
ver_date
.
second
)
mv_file
.
seek
(
0
)
mv_file
.
truncate
()
mv_file
.
write
(
'version = {}
\n
'
.
format
(
mv_version
))
mv_file
.
write
(
'date = {}
\n
'
.
format
(
mv_date
))
mv_file
.
write
(
'time = {}
\n
'
.
format
(
mv_time
))
print
'New main version is {}'
.
format
(
mv_version
)
print
'Vesion date is {}'
.
format
(
mv_date
)
print
(
'New main version is {}'
.
format
(
mv_version
)
)
print
(
'Vesion date is {}'
.
format
(
mv_date
)
)
pass
\ No newline at end of file
pycroscopy/viz/plot_utils.py
View file @
cfac8e18
...
...
@@ -437,7 +437,7 @@ def plot_loops(excit_wfm, datasets, line_colors=[], dataset_names=[], evenly_spa
for
dataset
,
col_val
in
zip
(
datasets
,
line_colors
):
axes_lin
[
count
].
plot
(
excit_wfm
[
l_resp_ind
:
r_resp_ind
],
dataset
[
posn
,
l_resp_ind
:
r_resp_ind
],
color
=
col_val
)
if
h5_pos
is
not
None
:
# print
'Row ' + str(h5_pos[posn,1]) + ' Col ' + str(h5_pos[posn,0])
# print
(
'Row ' + str(h5_pos[posn,1]) + ' Col ' + str(h5_pos[posn,0])
)
axes_lin
[
count
].
set_title
(
'Row '
+
str
(
h5_pos
[
posn
,
1
])
+
' Col '
+
str
(
h5_pos
[
posn
,
0
]),
fontsize
=
12
)
else
:
axes_lin
[
count
].
set_title
(
subtitles
+
' '
+
str
(
posn
),
fontsize
=
12
)
...
...
@@ -1005,10 +1005,10 @@ def plot_cluster_dendrogram(label_mat, e_vals, num_comp, num_cluster, mode='Full
mode
=
'Full'
if
mode
==
'Full'
:
print
'Creating full dendrogram from clusters'
print
(
'Creating full dendrogram from clusters'
)
mode
=
None
elif
mode
==
'Truncated'
:
print
'Creating truncated dendrogram from clusters. Will stop at {}.'
.
format
(
last
)
print
(
'Creating truncated dendrogram from clusters. Will stop at {}.'
.
format
(
last
)
)
mode
=
'lastp'
else
:
raise
ValueError
(
'Error: Unknown mode requested for plotting dendrograms. mode={}'
.
format
(
mode
))
...
...
@@ -1127,8 +1127,8 @@ def plot_2d_spectrogram(mean_spectrogram, freq, title, cmap=None, figure_path=No
freq
*=
1E-3
# to kHz
fig
,
ax
=
plt
.
subplots
(
nrows
=
2
,
ncols
=
1
,
sharex
=
True
)
# print
mean_spectrogram.shape
# print
freq.shape
# print
(
mean_spectrogram.shape
)
# print
(
freq.shape
)
ax
[
0
].
imshow
(
np
.
abs
(
mean_spectrogram
),
interpolation
=
'nearest'
,
cmap
=
col_map
,
extent
=
[
freq
[
0
],
freq
[
-
1
],
mean_spectrogram
.
shape
[
0
],
0
],
**
kwargs
)
ax
[
0
].
set_title
(
'Amplitude'
)
...
...
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