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1 import traceback
1 import traceback
2 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
2 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
3 import numpy as np
3 import numpy as np
4 from spwc.cache import _cache
4 from speasy.cache import _cache
5 from spwc.common.datetime_range import DateTimeRange
5 from speasy.common.datetime_range import DateTimeRange
6 from datetime import datetime, timedelta, timezone
6 from datetime import datetime, timedelta, timezone
7 from spwc.common.variable import SpwcVariable
7 from speasy.common.variable import SpeasyVariable
8 from spwc.amda import AMDA
8 from speasy.amda import AMDA
9
9
10 amda = AMDA()
10 amda = AMDA()
11
11
12
12
13 def vp_make_scalar(var=None):
13 def vp_make_scalar(var=None):
14 if var is None:
14 if var is None:
15 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SCALAR)
15 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SCALAR)
16 else:
16 else:
17 return (((var.time, np.array([])), var.data), DataSeriesType.SCALAR)
17 return (((var.time, np.array([])), var.data), DataSeriesType.SCALAR)
18
18
19 class DemoVP(PyDataProvider):
19 class DemoVP(PyDataProvider):
20 def __init__(self):
20 def __init__(self):
21 super().__init__()
21 super().__init__()
22 self.register_products([Product("/VP/thb_fgm_gse_mod",[],{"type":"scalar"})])
22 self.register_products([Product("/VP/thb_fgm_gse_mod",[],{"type":"scalar"})])
23
23
24 def get_data(self,metadata,start,stop):
24 def get_data(self,metadata,start,stop):
25 try:
25 try:
26 tstart = datetime.fromtimestamp(start, tz=timezone.utc)
26 tstart = datetime.fromtimestamp(start, tz=timezone.utc)
27 tend = datetime.fromtimestamp(stop, tz=timezone.utc)
27 tend = datetime.fromtimestamp(stop, tz=timezone.utc)
28 thb_bs = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id='thb_bs', method="REST")
28 thb_bs = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id='thb_bs', method="REST")
29 thb_bs.data = np.sqrt((thb_bs.data*thb_bs.data).sum(axis=1))
29 thb_bs.data = np.sqrt((thb_bs.data*thb_bs.data).sum(axis=1))
30 return vp_make_scalar(thb_bs)
30 return vp_make_scalar(thb_bs)
31 except Exception as e:
31 except Exception as e:
32 print(traceback.format_exc())
32 print(traceback.format_exc())
33 print(f"Error in {__file__} ",str(e))
33 print(f"Error in {__file__} ",str(e))
34 return (((np.array([]), np.array([])), np.array([])), ts_type)
34 return (((np.array([]), np.array([])), np.array([])), ts_type)
35
35
36
36
37 t=DemoVP()
37 t=DemoVP()
38
38
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@@ -1,128 +1,128
1 import traceback
1 import traceback
2 import os
2 import os
3 from datetime import datetime, timedelta, timezone
3 from datetime import datetime, timedelta, timezone
4 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
4 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
5 import numpy as np
5 import numpy as np
6 import requests
6 import requests
7 import copy
7 import copy
8 from spwc.amda import AMDA
8 from speasy.amda import AMDA
9
9
10 amda = AMDA()
10 amda = AMDA()
11
11
12
12
13 def amda_make_scalar(var=None):
13 def amda_make_scalar(var=None):
14 if var is None:
14 if var is None:
15 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SCALAR)
15 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SCALAR)
16 else:
16 else:
17 return (((var.time, np.array([])), var.data), DataSeriesType.SCALAR)
17 return (((var.time, np.array([])), var.data), DataSeriesType.SCALAR)
18
18
19
19
20 def amda_make_vector(var=None):
20 def amda_make_vector(var=None):
21 if var is None:
21 if var is None:
22 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.VECTOR)
22 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.VECTOR)
23 else:
23 else:
24 return (((var.time, np.array([])), var.data), DataSeriesType.VECTOR)
24 return (((var.time, np.array([])), var.data), DataSeriesType.VECTOR)
25
25
26
26
27 def amda_make_multi_comp(var=None):
27 def amda_make_multi_comp(var=None):
28 if var is None:
28 if var is None:
29 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.MULTICOMPONENT)
29 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.MULTICOMPONENT)
30 else:
30 else:
31 return (((var.time, np.array([])), var.data), DataSeriesType.MULTICOMPONENT)
31 return (((var.time, np.array([])), var.data), DataSeriesType.MULTICOMPONENT)
32
32
33
33
34 def amda_make_spectro(var=None):
34 def amda_make_spectro(var=None):
35 if var is None:
35 if var is None:
36 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SPECTROGRAM)
36 return (((np.array([]), np.array([])), np.array([])), DataSeriesType.SPECTROGRAM)
37 else:
37 else:
38 min_sampling = float(var.meta.get("DATASET_MIN_SAMPLING", "nan"))
38 min_sampling = float(var.meta.get("DATASET_MIN_SAMPLING", "nan"))
39 max_sampling = float(var.meta.get("DATASET_MAX_SAMPLING", "nan"))
39 max_sampling = float(var.meta.get("DATASET_MAX_SAMPLING", "nan"))
40 if var.y is None and len(var.data):
40 if var.y is None and len(var.data):
41 var.y = np.logspace(1, 3, var.data.shape[1])[::-1]
41 var.y = np.logspace(1, 3, var.data.shape[1])[::-1]
42 return (((var.time, var.y), var.data), DataSeriesType.SPECTROGRAM)
42 return (((var.time, var.y), var.data), DataSeriesType.SPECTROGRAM)
43 #return pysciqlopcore.SpectrogramTimeSerie(var.time,y,var.data,min_sampling,max_sampling,True)
43 #return pysciqlopcore.SpectrogramTimeSerie(var.time,y,var.data,min_sampling,max_sampling,True)
44
44
45
45
46 def amda_get_sample(metadata, start, stop):
46 def amda_get_sample(metadata, start, stop):
47 ts_type = amda_make_scalar
47 ts_type = amda_make_scalar
48 try:
48 try:
49 param_id = None
49 param_id = None
50 for key, value in metadata:
50 for key, value in metadata:
51 if key == 'xml:id':
51 if key == 'xml:id':
52 param_id = value
52 param_id = value
53 elif key == 'type':
53 elif key == 'type':
54 if value == 'vector':
54 if value == 'vector':
55 ts_type = amda_make_vector
55 ts_type = amda_make_vector
56 elif value == 'multicomponent':
56 elif value == 'multicomponent':
57 ts_type = amda_make_multi_comp
57 ts_type = amda_make_multi_comp
58 elif value == 'spectrogram':
58 elif value == 'spectrogram':
59 ts_type = amda_make_spectro
59 ts_type = amda_make_spectro
60 tstart = datetime.fromtimestamp(start, tz=timezone.utc)
60 tstart = datetime.fromtimestamp(start, tz=timezone.utc)
61 tend = datetime.fromtimestamp(stop, tz=timezone.utc)
61 tend = datetime.fromtimestamp(stop, tz=timezone.utc)
62 var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
62 var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
63 return ts_type(var)
63 return ts_type(var)
64 except Exception as e:
64 except Exception as e:
65 print(traceback.format_exc())
65 print(traceback.format_exc())
66 print("Error in amda.py ", str(e))
66 print("Error in amda.py ", str(e))
67 return ts_type()
67 return ts_type()
68
68
69
69
70 class AmdaProvider(PyDataProvider):
70 class AmdaProvider(PyDataProvider):
71 def __init__(self):
71 def __init__(self):
72 super(AmdaProvider, self).__init__()
72 super(AmdaProvider, self).__init__()
73 if len(amda.component) is 0:
73 if len(amda.component) is 0:
74 amda.update_inventory()
74 amda.update_inventory()
75 parameters = copy.deepcopy(amda.parameter)
75 parameters = copy.deepcopy(amda.parameter)
76 for name, component in amda.component.items():
76 for name, component in amda.component.items():
77 if 'components' in parameters[component['parameter']]:
77 if 'components' in parameters[component['parameter']]:
78 parameters[component['parameter']]['components'].append(component)
78 parameters[component['parameter']]['components'].append(component)
79 else:
79 else:
80 parameters[component['parameter']]['components']=[component]
80 parameters[component['parameter']]['components']=[component]
81
81
82 products = []
82 products = []
83 for key, parameter in parameters.items():
83 for key, parameter in parameters.items():
84 mission_name = amda.mission[parameter['mission']]['name']
84 mission_name = amda.mission[parameter['mission']]['name']
85 observatory_name = parameter.get('observatory','')
85 observatory_name = parameter.get('observatory','')
86 if observatory_name != '':
86 if observatory_name != '':
87 observatory_name = amda.observatory[observatory_name]['name']
87 observatory_name = amda.observatory[observatory_name]['name']
88 instrument_name = amda.instrument[parameter['instrument']]['name']
88 instrument_name = amda.instrument[parameter['instrument']]['name']
89 dataset_name = amda.dataset[parameter['dataset']]['name']
89 dataset_name = amda.dataset[parameter['dataset']]['name']
90 path = f"/AMDA/{mission_name}/{observatory_name}/{instrument_name}/{dataset_name}/{parameter['name']}"
90 path = f"/AMDA/{mission_name}/{observatory_name}/{instrument_name}/{dataset_name}/{parameter['name']}"
91 components = [component['name'] for component in parameter.get('components',[])]
91 components = [component['name'] for component in parameter.get('components',[])]
92 metadata = {key: item for key, item in parameter.items() if key is not 'components'}
92 metadata = {key: item for key, item in parameter.items() if key is not 'components'}
93 n_components = parameter.get('size', 0)
93 n_components = parameter.get('size', 0)
94 if n_components == '3':
94 if n_components == '3':
95 metadata["type"] = "vector"
95 metadata["type"] = "vector"
96 elif parameter.get('display_type', '')=="spectrogram":
96 elif parameter.get('display_type', '')=="spectrogram":
97 metadata["type"] = "spectrogram"
97 metadata["type"] = "spectrogram"
98 elif n_components != 0:
98 elif n_components != 0:
99 metadata["type"] = "multicomponent"
99 metadata["type"] = "multicomponent"
100 else:
100 else:
101 metadata["type"] = "scalar"
101 metadata["type"] = "scalar"
102 products.append(Product(path, components, metadata))
102 products.append(Product(path, components, metadata))
103 self.register_products(products)
103 self.register_products(products)
104 for _,mission in amda.mission.items():
104 for _,mission in amda.mission.items():
105 if ('target' in mission) and (mission['xml:id'] != 'Ephemerides') and (mission['target'] != 'Earth'):
105 if ('target' in mission) and (mission['xml:id'] != 'Ephemerides') and (mission['target'] != 'Earth'):
106 self.set_icon(f'/AMDA/{mission["name"]}','satellite')
106 self.set_icon(f'/AMDA/{mission["name"]}','satellite')
107
107
108 def get_data(self, metadata, start, stop):
108 def get_data(self, metadata, start, stop):
109 ts_type = amda_make_scalar
109 ts_type = amda_make_scalar
110 try:
110 try:
111 param_id = metadata['xml:id']
111 param_id = metadata['xml:id']
112 ts_type_str = metadata['type']
112 ts_type_str = metadata['type']
113 if ts_type_str == 'vector':
113 if ts_type_str == 'vector':
114 ts_type = amda_make_vector
114 ts_type = amda_make_vector
115 elif ts_type_str == 'multicomponent':
115 elif ts_type_str == 'multicomponent':
116 ts_type = amda_make_multi_comp
116 ts_type = amda_make_multi_comp
117 elif ts_type_str == 'spectrogram':
117 elif ts_type_str == 'spectrogram':
118 ts_type = amda_make_spectro
118 ts_type = amda_make_spectro
119 tstart = datetime.fromtimestamp(start, tz=timezone.utc)
119 tstart = datetime.fromtimestamp(start, tz=timezone.utc)
120 tend = datetime.fromtimestamp(stop, tz=timezone.utc)
120 tend = datetime.fromtimestamp(stop, tz=timezone.utc)
121 var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
121 var = amda.get_parameter(start_time=tstart, stop_time=tend, parameter_id=param_id, method="REST")
122 return ts_type(var)
122 return ts_type(var)
123 except Exception as e:
123 except Exception as e:
124 print(traceback.format_exc())
124 print(traceback.format_exc())
125 print("Error in amda.py ", str(e))
125 print("Error in amda.py ", str(e))
126 return ts_type()
126 return ts_type()
127
127
128 _amda = AmdaProvider()
128 _amda = AmdaProvider()
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@@ -1,93 +1,93
1 import traceback
1 import traceback
2 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
2 from SciQLopBindings import PyDataProvider, Product, VectorTimeSerie, ScalarTimeSerie, DataSeriesType
3 import numpy as np
3 import numpy as np
4 import math
4 import math
5 from spwc.cache import _cache
5 from speasy.cache import _cache
6 from spwc.common.datetime_range import DateTimeRange
6 from speasy.common.datetime_range import DateTimeRange
7 from functools import partial
7 from functools import partial
8 from datetime import datetime, timedelta, timezone
8 from datetime import datetime, timedelta, timezone
9 from spwc.common.variable import SpwcVariable
9 from speasy.common.variable import SpeasyVariable
10
10
11
11
12 def make_scalar(x):
12 def make_scalar(x):
13 y = np.cos(x/10.)
13 y = np.cos(x/10.)
14 return SpwcVariable(time=x, data=y)
14 return SpeasyVariable(time=x, data=y)
15
15
16 def make_vector(x):
16 def make_vector(x):
17 v=np.ones((len(x),3))
17 v=np.ones((len(x),3))
18 for i in range(3):
18 for i in range(3):
19 v.transpose()[:][i] = np.cos(x/10. + float(i)) + (100. * np.cos(x/10000. + float(i)))
19 v.transpose()[:][i] = np.cos(x/10. + float(i)) + (100. * np.cos(x/10000. + float(i)))
20 return SpwcVariable(time=x, data=v)
20 return SpeasyVariable(time=x, data=v)
21
21
22
22
23 def make_multicomponent(x):
23 def make_multicomponent(x):
24 v=np.ones((len(x),4))
24 v=np.ones((len(x),4))
25 for i in range(4):
25 for i in range(4):
26 v.transpose()[:][i] = float(i+1) * np.cos(x/10. + float(i))
26 v.transpose()[:][i] = float(i+1) * np.cos(x/10. + float(i))
27 return SpwcVariable(time=x, data=v)
27 return SpeasyVariable(time=x, data=v)
28
28
29 def make_spectrogram(x):
29 def make_spectrogram(x):
30 v=np.ones((len(x),32))
30 v=np.ones((len(x),32))
31 for i in range(32):
31 for i in range(32):
32 v.transpose()[:][i] = 100.*(2.+ float(i+1) * np.cos(x/1024. + float(i)))
32 v.transpose()[:][i] = 100.*(2.+ float(i+1) * np.cos(x/1024. + float(i)))
33 return SpwcVariable(time=x, data=v)
33 return SpeasyVariable(time=x, data=v)
34
34
35
35
36 def _get_data(p_type, start, stop):
36 def _get_data(p_type, start, stop):
37 if type(start) is datetime:
37 if type(start) is datetime:
38 start = start.timestamp()
38 start = start.timestamp()
39 stop = stop.timestamp()
39 stop = stop.timestamp()
40 x = np.arange(math.ceil(start), math.floor(stop))*1.
40 x = np.arange(math.ceil(start), math.floor(stop))*1.
41 if p_type == 'scalar':
41 if p_type == 'scalar':
42 return make_scalar(x)
42 return make_scalar(x)
43 if p_type == 'vector':
43 if p_type == 'vector':
44 return make_vector(x)
44 return make_vector(x)
45 if p_type == 'multicomponent':
45 if p_type == 'multicomponent':
46 return make_multicomponent(x)
46 return make_multicomponent(x)
47 if p_type == 'spectrogram':
47 if p_type == 'spectrogram':
48 return make_spectrogram(np.arange(math.ceil(start), math.floor(stop),15.))
48 return make_spectrogram(np.arange(math.ceil(start), math.floor(stop),15.))
49 return None
49 return None
50
50
51 class MyProvider(PyDataProvider):
51 class MyProvider(PyDataProvider):
52 def __init__(self):
52 def __init__(self):
53 super(MyProvider,self).__init__()
53 super(MyProvider,self).__init__()
54 self.register_products([Product("/tests/without_cache/scalar",[],{"type":"scalar"}),
54 self.register_products([Product("/tests/without_cache/scalar",[],{"type":"scalar"}),
55 Product("/tests/without_cache/vector",[],{"type":"vector"}),
55 Product("/tests/without_cache/vector",[],{"type":"vector"}),
56 Product("/tests/without_cache/multicomponent",[],{"type":"multicomponent",'size':'4'}),
56 Product("/tests/without_cache/multicomponent",[],{"type":"multicomponent",'size':'4'}),
57 Product("/tests/without_cache/spectrogram",[],{"type":"spectrogram",'size':'32'}),
57 Product("/tests/without_cache/spectrogram",[],{"type":"spectrogram",'size':'32'}),
58 Product("/tests/with_cache/scalar",[],{"type":"scalar", "cache":"true"}),
58 Product("/tests/with_cache/scalar",[],{"type":"scalar", "cache":"true"}),
59 Product("/tests/with_cache/vector",[],{"type":"vector", "cache":"true"}),
59 Product("/tests/with_cache/vector",[],{"type":"vector", "cache":"true"}),
60 Product("/tests/with_cache/multicomponent",[],{"type":"multicomponent",'size':'4', "cache":"true"})
60 Product("/tests/with_cache/multicomponent",[],{"type":"multicomponent",'size':'4', "cache":"true"})
61 ])
61 ])
62
62
63 def get_data(self,metadata,start,stop):
63 def get_data(self,metadata,start,stop):
64 ts_type = DataSeriesType.SCALAR
64 ts_type = DataSeriesType.SCALAR
65 default_ctor_args = 1
65 default_ctor_args = 1
66 use_cache = False
66 use_cache = False
67 p_type = 'scalar'
67 p_type = 'scalar'
68 try:
68 try:
69 for key,value in metadata.items():
69 for key,value in metadata.items():
70 if key == 'type':
70 if key == 'type':
71 p_type = value
71 p_type = value
72 if value == 'vector':
72 if value == 'vector':
73 ts_type = DataSeriesType.VECTOR
73 ts_type = DataSeriesType.VECTOR
74 elif value == 'multicomponent':
74 elif value == 'multicomponent':
75 ts_type = DataSeriesType.MULTICOMPONENT
75 ts_type = DataSeriesType.MULTICOMPONENT
76 elif value == 'spectrogram':
76 elif value == 'spectrogram':
77 ts_type = DataSeriesType.SPECTROGRAM
77 ts_type = DataSeriesType.SPECTROGRAM
78 if key == 'cache' and value == 'true':
78 if key == 'cache' and value == 'true':
79 use_cache = True
79 use_cache = True
80 if use_cache:
80 if use_cache:
81 cache_product = f"tests/{p_type}"
81 cache_product = f"tests/{p_type}"
82 var = _cache.get_data(cache_product, DateTimeRange(datetime.fromtimestamp(start, tz=timezone.utc), datetime.fromtimestamp(stop, tz=timezone.utc)), partial(_get_data, p_type), fragment_hours=24)
82 var = _cache.get_data(cache_product, DateTimeRange(datetime.fromtimestamp(start, tz=timezone.utc), datetime.fromtimestamp(stop, tz=timezone.utc)), partial(_get_data, p_type), fragment_hours=24)
83 else:
83 else:
84 var = _get_data(p_type, start, stop)
84 var = _get_data(p_type, start, stop)
85 return (((var.time, np.array([])),var.data), ts_type)
85 return (((var.time, np.array([])),var.data), ts_type)
86 except Exception as e:
86 except Exception as e:
87 print(traceback.format_exc())
87 print(traceback.format_exc())
88 print("Error in test.py ",str(e))
88 print("Error in test.py ",str(e))
89 return (((np.array([]), np.array([])), np.array([])), ts_type)
89 return (((np.array([]), np.array([])), np.array([])), ts_type)
90
90
91
91
92 t=MyProvider()
92 t=MyProvider()
93
93
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@@ -1,31 +1,31
1 #!/bin/bash
1 #!/bin/bash
2 # guess using centos 7 as build host
2 # guess using centos 7 as build host
3 yum install -y gtk3 openssl-devel.x86_64 ncurses-devel.x86_64 sqlite-devel.x86_64 tkinter.x86_64 readline-devel.x86_64 xz-devel.x86_64 gdbm-devel.x86_64 bzip2-devel.x86_64 tk-devel.x86_64 libffi-devel.x86_64 make
3 yum install -y gtk3 openssl-devel.x86_64 ncurses-devel.x86_64 sqlite-devel.x86_64 tkinter.x86_64 readline-devel.x86_64 xz-devel.x86_64 gdbm-devel.x86_64 bzip2-devel.x86_64 tk-devel.x86_64 libffi-devel.x86_64 make
4 HERE="$(dirname "$(readlink -f "${0}")")"
4 HERE="$(dirname "$(readlink -f "${0}")")"
5 SCIQLOP_SCR=$HERE/../../
5 SCIQLOP_SCR=$HERE/../../
6 SCIQLOP_BUILD=$SCIQLOP_SCR/build/
6 SCIQLOP_BUILD=$SCIQLOP_SCR/build/
7 SCIQLOP_APPDIR=$SCIQLOP_BUILD/AppDir
7 SCIQLOP_APPDIR=$SCIQLOP_BUILD/AppDir
8 mkdir $SCIQLOP_BUILD
8 mkdir $SCIQLOP_BUILD
9 cd $SCIQLOP_BUILD
9 cd $SCIQLOP_BUILD
10 # need to build python to easily install/relocate in AppImage
10 # need to build python to easily install/relocate in AppImage
11 wget https://www.python.org/ftp/python/3.7.3/Python-3.7.3.tgz
11 wget https://www.python.org/ftp/python/3.7.3/Python-3.7.3.tgz
12 tar -xf Python-3.7.3.tgz
12 tar -xf Python-3.7.3.tgz
13 cd Python-3.7.3
13 cd Python-3.7.3
14 # Optimisation is damn slow maybe enabled later
14 # Optimisation is damn slow maybe enabled later
15 ./configure --enable-shared --prefix=/usr
15 ./configure --enable-shared --prefix=/usr
16 make -j
16 make -j
17 DESTDIR=$SCIQLOP_BUILD/AppDir make install
17 DESTDIR=$SCIQLOP_BUILD/AppDir make install
18 cd ..
18 cd ..
19 cp $HERE/AppRun $SCIQLOP_APPDIR/
19 cp $HERE/AppRun $SCIQLOP_APPDIR/
20 chmod +x $SCIQLOP_APPDIR/AppRun
20 chmod +x $SCIQLOP_APPDIR/AppRun
21 # Tweak to find custom python from build dir
21 # Tweak to find custom python from build dir
22 sed "s|/usr|$SCIQLOP_APPDIR/usr|" -i $SCIQLOP_APPDIR/usr/lib/pkgconfig/python3.pc
22 sed "s|/usr|$SCIQLOP_APPDIR/usr|" -i $SCIQLOP_APPDIR/usr/lib/pkgconfig/python3.pc
23 LD_PRELOAD=$SCIQLOP_APPDIR/usr/lib/libpython3.7m.so.1.0 PATH=$SCIQLOP_APPDIR/usr/bin/:/usr/bin/ LD_LIBRARY_PATH=AppDir/usr/lib/:AppDir/usr/lib/python3.7/ $SCIQLOP_APPDIR/usr/bin/python3 $SCIQLOP_APPDIR/usr/bin/pip3 install git+https://github.com/jeandet/spwc
23 LD_PRELOAD=$SCIQLOP_APPDIR/usr/lib/libpython3.7m.so.1.0 PATH=$SCIQLOP_APPDIR/usr/bin/:/usr/bin/ LD_LIBRARY_PATH=AppDir/usr/lib/:AppDir/usr/lib/python3.7/ $SCIQLOP_APPDIR/usr/bin/python3 $SCIQLOP_APPDIR/usr/bin/pip3 install speasy
24 LD_LIBRARY_PATH=$SCIQLOP_APPDIR/usr/lib/ PKG_CONFIG_PATH=$SCIQLOP_APPDIR/usr/lib/pkgconfig/:$PKG_CONFIG_PATH PATH=$SCIQLOP_APPDIR/usr/bin/:$PATH meson --prefix=/usr ..
24 LD_LIBRARY_PATH=$SCIQLOP_APPDIR/usr/lib/ PKG_CONFIG_PATH=$SCIQLOP_APPDIR/usr/lib/pkgconfig/:$PKG_CONFIG_PATH PATH=$SCIQLOP_APPDIR/usr/bin/:$PATH meson --prefix=/usr ..
25 ninja
25 ninja
26 DESTDIR=$SCIQLOP_APPDIR ninja install
26 DESTDIR=$SCIQLOP_APPDIR ninja install
27 cp -rf $SCIQLOP_APPDIR/usr/lib64/* $SCIQLOP_APPDIR/usr/lib/
27 cp -rf $SCIQLOP_APPDIR/usr/lib64/* $SCIQLOP_APPDIR/usr/lib/
28 rm -rf $SCIQLOP_APPDIR/usr/lib64/
28 rm -rf $SCIQLOP_APPDIR/usr/lib64/
29 wget https://github.com/probonopd/linuxdeployqt/releases/download/continuous/linuxdeployqt-continuous-x86_64.AppImage
29 wget https://github.com/probonopd/linuxdeployqt/releases/download/continuous/linuxdeployqt-continuous-x86_64.AppImage
30 chmod +x linuxdeployqt-continuous-x86_64.AppImage && ./linuxdeployqt-continuous-x86_64.AppImage --appimage-extract
30 chmod +x linuxdeployqt-continuous-x86_64.AppImage && ./linuxdeployqt-continuous-x86_64.AppImage --appimage-extract
31 LD_LIBRARY_PATH=$SCIQLOP_APPDIR/usr/lib:$SCIQLOP_APPDIR/usr/lib/SciQLop/:$SCIQLOP_APPDIR/usr/lib/python3.7/site-packages/numpy/.libs/ ./squashfs-root/AppRun $SCIQLOP_APPDIR/usr/share/applications/*.desktop -appimage -extra-plugins=iconengines,platformthemes/libqgtk3.so
31 LD_LIBRARY_PATH=$SCIQLOP_APPDIR/usr/lib:$SCIQLOP_APPDIR/usr/lib/SciQLop/:$SCIQLOP_APPDIR/usr/lib/python3.7/site-packages/numpy/.libs/ ./squashfs-root/AppRun $SCIQLOP_APPDIR/usr/share/applications/*.desktop -appimage -extra-plugins=iconengines,platformthemes/libqgtk3.so
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@@ -1,15 +1,15
1 #!/bin/bash
1 #!/bin/bash
2 # On OS X only 0.49.1 works :(
2 # On OS X only 0.49.1 works :(
3 pip3 install --upgrade --user meson==0.49.1
3 pip3 install --upgrade --user meson==0.49.1
4 HERE=$( cd "$(dirname "$0")" ; pwd -P )
4 HERE=$( cd "$(dirname "$0")" ; pwd -P )
5 mkdir build
5 mkdir build
6 ~/Library/Python/3.7/bin/meson -Dcpp_args='-DQT_STATICPLUGIN' -Ddefault_library=static --prefix=/tmp/SciQLOP.app --bindir=Contents/MacOS build
6 ~/Library/Python/3.7/bin/meson -Dcpp_args='-DQT_STATICPLUGIN' -Ddefault_library=static --prefix=/tmp/SciQLOP.app --bindir=Contents/MacOS build
7 cd build
7 cd build
8 ninja
8 ninja
9 ninja install
9 ninja install
10 ~/Library/Python/3.7/bin/virtualenv --always-copy /tmp/SciQLOP.app
10 ~/Library/Python/3.7/bin/virtualenv --always-copy /tmp/SciQLOP.app
11 ~/Library/Python/3.7/bin/virtualenv --relocatable /tmp/SciQLOP.app
11 ~/Library/Python/3.7/bin/virtualenv --relocatable /tmp/SciQLOP.app
12 source /tmp/SciQLOP.app/bin/activate
12 source /tmp/SciQLOP.app/bin/activate
13 /tmp/SciQLOP.app/bin/pip install git+https://github.com/jeandet/spwc
13 /tmp/SciQLOP.app/bin/pip install speasy
14 cp $HERE/SciQLOP_wrapper /tmp/SciQLOP.app/Contents/MacOS/
14 cp $HERE/SciQLOP_wrapper /tmp/SciQLOP.app/Contents/MacOS/
15 chmod +x /tmp/SciQLOP.app/Contents/MacOS/SciQLOP_wrapper
15 chmod +x /tmp/SciQLOP.app/Contents/MacOS/SciQLOP_wrapper
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