hexsha
string | size
int64 | ext
string | lang
string | max_stars_repo_path
string | max_stars_repo_name
string | max_stars_repo_head_hexsha
string | max_stars_repo_licenses
list | max_stars_count
int64 | max_stars_repo_stars_event_min_datetime
string | max_stars_repo_stars_event_max_datetime
string | max_issues_repo_path
string | max_issues_repo_name
string | max_issues_repo_head_hexsha
string | max_issues_repo_licenses
list | max_issues_count
int64 | max_issues_repo_issues_event_min_datetime
string | max_issues_repo_issues_event_max_datetime
string | max_forks_repo_path
string | max_forks_repo_name
string | max_forks_repo_head_hexsha
string | max_forks_repo_licenses
list | max_forks_count
int64 | max_forks_repo_forks_event_min_datetime
string | max_forks_repo_forks_event_max_datetime
string | content
string | avg_line_length
float64 | max_line_length
int64 | alphanum_fraction
float64 | qsc_code_num_words_quality_signal
int64 | qsc_code_num_chars_quality_signal
float64 | qsc_code_mean_word_length_quality_signal
float64 | qsc_code_frac_words_unique_quality_signal
float64 | qsc_code_frac_chars_top_2grams_quality_signal
float64 | qsc_code_frac_chars_top_3grams_quality_signal
float64 | qsc_code_frac_chars_top_4grams_quality_signal
float64 | qsc_code_frac_chars_dupe_5grams_quality_signal
float64 | qsc_code_frac_chars_dupe_6grams_quality_signal
float64 | qsc_code_frac_chars_dupe_7grams_quality_signal
float64 | qsc_code_frac_chars_dupe_8grams_quality_signal
float64 | qsc_code_frac_chars_dupe_9grams_quality_signal
float64 | qsc_code_frac_chars_dupe_10grams_quality_signal
float64 | qsc_code_frac_chars_replacement_symbols_quality_signal
float64 | qsc_code_frac_chars_digital_quality_signal
float64 | qsc_code_frac_chars_whitespace_quality_signal
float64 | qsc_code_size_file_byte_quality_signal
float64 | qsc_code_num_lines_quality_signal
float64 | qsc_code_num_chars_line_max_quality_signal
float64 | qsc_code_num_chars_line_mean_quality_signal
float64 | qsc_code_frac_chars_alphabet_quality_signal
float64 | qsc_code_frac_chars_comments_quality_signal
float64 | qsc_code_cate_xml_start_quality_signal
float64 | qsc_code_frac_lines_dupe_lines_quality_signal
float64 | qsc_code_cate_autogen_quality_signal
float64 | qsc_code_frac_lines_long_string_quality_signal
float64 | qsc_code_frac_chars_string_length_quality_signal
float64 | qsc_code_frac_chars_long_word_length_quality_signal
float64 | qsc_code_frac_lines_string_concat_quality_signal
float64 | qsc_code_cate_encoded_data_quality_signal
float64 | qsc_code_frac_chars_hex_words_quality_signal
float64 | qsc_code_frac_lines_prompt_comments_quality_signal
float64 | qsc_code_frac_lines_assert_quality_signal
float64 | qsc_codepython_cate_ast_quality_signal
float64 | qsc_codepython_frac_lines_func_ratio_quality_signal
float64 | qsc_codepython_cate_var_zero_quality_signal
bool | qsc_codepython_frac_lines_pass_quality_signal
float64 | qsc_codepython_frac_lines_import_quality_signal
float64 | qsc_codepython_frac_lines_simplefunc_quality_signal
float64 | qsc_codepython_score_lines_no_logic_quality_signal
float64 | qsc_codepython_frac_lines_print_quality_signal
float64 | qsc_code_num_words
int64 | qsc_code_num_chars
int64 | qsc_code_mean_word_length
int64 | qsc_code_frac_words_unique
null | qsc_code_frac_chars_top_2grams
int64 | qsc_code_frac_chars_top_3grams
int64 | qsc_code_frac_chars_top_4grams
int64 | qsc_code_frac_chars_dupe_5grams
int64 | qsc_code_frac_chars_dupe_6grams
int64 | qsc_code_frac_chars_dupe_7grams
int64 | qsc_code_frac_chars_dupe_8grams
int64 | qsc_code_frac_chars_dupe_9grams
int64 | qsc_code_frac_chars_dupe_10grams
int64 | qsc_code_frac_chars_replacement_symbols
int64 | qsc_code_frac_chars_digital
int64 | qsc_code_frac_chars_whitespace
int64 | qsc_code_size_file_byte
int64 | qsc_code_num_lines
int64 | qsc_code_num_chars_line_max
int64 | qsc_code_num_chars_line_mean
int64 | qsc_code_frac_chars_alphabet
int64 | qsc_code_frac_chars_comments
int64 | qsc_code_cate_xml_start
int64 | qsc_code_frac_lines_dupe_lines
int64 | qsc_code_cate_autogen
int64 | qsc_code_frac_lines_long_string
int64 | qsc_code_frac_chars_string_length
int64 | qsc_code_frac_chars_long_word_length
int64 | qsc_code_frac_lines_string_concat
null | qsc_code_cate_encoded_data
int64 | qsc_code_frac_chars_hex_words
int64 | qsc_code_frac_lines_prompt_comments
int64 | qsc_code_frac_lines_assert
int64 | qsc_codepython_cate_ast
int64 | qsc_codepython_frac_lines_func_ratio
int64 | qsc_codepython_cate_var_zero
int64 | qsc_codepython_frac_lines_pass
int64 | qsc_codepython_frac_lines_import
int64 | qsc_codepython_frac_lines_simplefunc
int64 | qsc_codepython_score_lines_no_logic
int64 | qsc_codepython_frac_lines_print
int64 | effective
string | hits
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
df66ddefb0262a60a3c54dd4d3a557c00d7aec79
| 43
|
py
|
Python
|
mechanics/swig/mechanics/collision/__init__.py
|
ljktest/siconos
|
85b60e62beca46e6bf06bfbd65670089e86607c7
|
[
"Apache-2.0"
] | 137
|
2015-06-16T15:55:28.000Z
|
2022-03-26T06:01:59.000Z
|
mechanics/swig/mechanics/collision/__init__.py
|
ljktest/siconos
|
85b60e62beca46e6bf06bfbd65670089e86607c7
|
[
"Apache-2.0"
] | 381
|
2015-09-22T15:31:08.000Z
|
2022-02-14T09:05:23.000Z
|
mechanics/swig/mechanics/collision/__init__.py
|
ljktest/siconos
|
85b60e62beca46e6bf06bfbd65670089e86607c7
|
[
"Apache-2.0"
] | 30
|
2015-08-06T22:57:51.000Z
|
2022-03-02T20:30:20.000Z
|
from .base import *
from .native import *
| 10.75
| 21
| 0.697674
| 6
| 43
| 5
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.209302
| 43
| 3
| 22
| 14.333333
| 0.882353
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
10dcbd44dbdd721c9efcef095faf26ea8b76efc2
| 354
|
py
|
Python
|
Numbers Generator.py
|
supervrijdag/Python-Random-Number-Generator
|
369e1ddc5d46b2b56ee3ed7c525614a6d80e85c2
|
[
"MIT"
] | null | null | null |
Numbers Generator.py
|
supervrijdag/Python-Random-Number-Generator
|
369e1ddc5d46b2b56ee3ed7c525614a6d80e85c2
|
[
"MIT"
] | null | null | null |
Numbers Generator.py
|
supervrijdag/Python-Random-Number-Generator
|
369e1ddc5d46b2b56ee3ed7c525614a6d80e85c2
|
[
"MIT"
] | null | null | null |
import random
f = open('Numbes.txt','w')
while True:
number = str(random.randint(100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000,999999999999999999999999999999999999999999999999999999999990000000000000000000000000000000000000000000000000000000000))
f.write(number)
| 39.333333
| 270
| 0.858757
| 18
| 354
| 16.888889
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.722222
| 0.084746
| 354
| 8
| 271
| 44.25
| 0.216049
| 0
| 0
| 0
| 0
| 0
| 0.031884
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
804bdc206935b217a7d6507dcc849b56abe5bb0c
| 32
|
py
|
Python
|
P25035-Changsha-Zhouzhenxing/week01/test.py
|
tonylhb/python-25
|
321793d5abe92b71fe5a89f0d5022cced9277406
|
[
"Apache-2.0"
] | 1
|
2019-09-11T23:24:58.000Z
|
2019-09-11T23:24:58.000Z
|
P25035-Changsha-Zhouzhenxing/week01/test.py
|
tonylhb/python-25
|
321793d5abe92b71fe5a89f0d5022cced9277406
|
[
"Apache-2.0"
] | null | null | null |
P25035-Changsha-Zhouzhenxing/week01/test.py
|
tonylhb/python-25
|
321793d5abe92b71fe5a89f0d5022cced9277406
|
[
"Apache-2.0"
] | 5
|
2019-09-11T06:33:34.000Z
|
2020-02-17T12:52:31.000Z
|
print('Hello This is test info')
| 32
| 32
| 0.75
| 6
| 32
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 32
| 1
| 32
| 32
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0.69697
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
d510bf0c2d80c481b7973ca6b54f6b0c75a28588
| 13,852
|
py
|
Python
|
testing/tests/001-main/003-self/200-json/008-batches.py
|
piwaniuk/critic
|
28ed20bb8032d7cc5aa23de98da51e619fd84164
|
[
"Apache-2.0"
] | 216
|
2015-01-05T12:48:10.000Z
|
2022-03-08T00:12:23.000Z
|
testing/tests/001-main/003-self/200-json/008-batches.py
|
piwaniuk/critic
|
28ed20bb8032d7cc5aa23de98da51e619fd84164
|
[
"Apache-2.0"
] | 55
|
2015-02-28T12:10:26.000Z
|
2020-11-18T17:45:16.000Z
|
testing/tests/001-main/003-self/200-json/008-batches.py
|
piwaniuk/critic
|
28ed20bb8032d7cc5aa23de98da51e619fd84164
|
[
"Apache-2.0"
] | 34
|
2015-05-02T15:15:10.000Z
|
2020-06-15T19:20:37.000Z
|
# @dependency 001-main/002-createrepository.py
with repository.workcopy() as work:
review = Review(work, "alice", "200-json/008-batches")
review.addFile(first="200-json/008-batches/first.txt",
second="200-json/008-batches/second.txt",
third="200-json/008-batches/third.txt")
review.commit("Reference commit",
reference=True,
first=["First",
"=====",
"Initial line"],
second=["Second",
"======",
"Initial line"],
third=["Third",
"=====",
"Initial line"])
review.commit("First commit",
first=["First",
"=====",
"Initial line",
"Added line"])
review.commit("Second commit",
second=["Second",
"======",
"Initial line",
"Added line"])
review.commit("Third commit",
third=["Third",
"=====",
"Initial line",
"Added line"])
review.addFilter("bob", "reviewer", "200-json/008-batches/")
review.addFilter("dave", "reviewer", "200-json/008-batches/")
review.submit()
changesets = {
"first": fetch_changeset({
"from": review.sha1s[0],
"to": review.sha1s[1],
}),
"second": fetch_changeset({
"from": review.sha1s[1],
"to": review.sha1s[2],
}),
"third": fetch_changeset({
"from": review.sha1s[2],
"to": review.sha1s[3],
}),
"all": fetch_changeset({
"from": review.sha1s[0],
"to": review.sha1s[3],
}),
}
issues = {
"alice": [],
"bob": [],
"dave": []
}
changes = {}
def fetch_changes(key):
changes[key] = frontend.json(
("reviews/%d/changesets/%d/reviewablefilechanges"
% (review.id, changesets[key]["id"])),
expect={
"reviewablefilechanges": [{
"id": int,
"review": review.id,
"changeset": changesets[key]["id"],
"file": review.getFileId(key),
"deleted_lines": int,
"inserted_lines": int,
"is_reviewed": False,
"reviewed_by": None,
"assigned_reviewers": [instance.userid("bob"),
instance.userid("dave")],
"draft_changes": None,
}],
})["reviewablefilechanges"]
fetch_changes("first")
fetch_changes("second")
fetch_changes("third")
with frontend.signin("alice"):
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "alice", "draft"))
issues["alice"].append(
frontend.json(
"reviews/%d/issues" % review.id,
post={
"text": "Alice's issue #1",
"location": {
"type": "file-version",
"changeset": changesets["first"]["id"],
"side": "new",
"file": review.getFilename("first"),
"first_line": 1,
"last_line": 4,
}
})["id"])
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "alice", "draft",
created_comments=[issues["alice"][0]]))
issues["alice"].append(
frontend.json(
"reviews/%d/issues" % review.id,
post={
"text": "Alice's issue #2",
"location": {
"type": "file-version",
"changeset": changesets["second"]["id"],
"side": "new",
"file": review.getFilename("second"),
"first_line": 1,
"last_line": 2,
}
})["id"])
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "alice", "draft",
created_comments=[issues["alice"][0],
issues["alice"][1]]))
frontend.json(
"reviews/%d/batches" % review.id,
post={},
expect=batch_json(review.id, "alice", "published",
created_comments=[issues["alice"][0],
issues["alice"][1]]))
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "alice", "draft"))
with frontend.signin("bob"):
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "bob", "draft"))
issues["bob"].append(
frontend.json(
"reviews/%d/issues" % review.id,
post={
"text": "Bob's issue #1",
"location": {
"type": "file-version",
"changeset": changesets["second"]["id"],
"side": "new",
"file": review.getFilename("second"),
"first_line": 3,
"last_line": 4,
}
})["id"])
frontend.json(
"comments/%d" % issues["alice"][0],
put={
"draft_changes": {
"new_state": "resolved",
},
},
expect={
"id": issues["alice"][0],
"state": "open",
"draft_changes": draft_changes_json(
"bob", new_state="resolved"),
"*": "*",
})
frontend.json(
("reviews/%d/changesets/%d/reviewablefilechanges"
% (review.id, changesets["second"]["id"])),
put={
"draft_changes": {
"new_is_reviewed": True,
}
},
expect={
"reviewablefilechanges": [{
"id": int,
"review": review.id,
"changeset": changesets["second"]["id"],
"file": review.getFileId("second"),
"deleted_lines": int,
"inserted_lines": int,
"is_reviewed": False,
"reviewed_by": None,
"assigned_reviewers": [instance.userid("bob"),
instance.userid("dave")],
"draft_changes": {
"author": instance.userid("bob"),
"new_is_reviewed": True,
"new_reviewed_by": instance.userid("bob"),
},
}],
})
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "bob", "draft",
created_comments=[issues["bob"][0]],
resolved_issues=[issues["alice"][0]],
reviewed_changes=[changes["second"][0]["id"]]))
with frontend.signin("dave"):
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "dave", "draft"))
issues["dave"].append(
frontend.json(
"reviews/%d/issues" % review.id,
post={
"text": "Dave's issue #1",
"location": {
"type": "file-version",
"changeset": changesets["all"]["id"],
"side": "new",
"file": review.getFilename("third"),
"first_line": 1,
"last_line": 4,
}
})["id"])
frontend.json(
"comments/%d" % issues["alice"][0],
put={
"draft_changes": {
"new_state": "resolved",
},
},
expect={
"id": issues["alice"][0],
"state": "open",
"draft_changes": draft_changes_json(
"dave", new_state="resolved"),
"*": "*",
})
frontend.json(
"comments/%d" % issues["alice"][1],
put={
"draft_changes": {
"new_state": "resolved",
},
},
expect={
"id": issues["alice"][1],
"state": "open",
"draft_changes": draft_changes_json(
"dave", new_state="resolved"),
"*": "*",
})
frontend.json(
"reviewablefilechanges/%d,%d" % (changes["second"][0]["id"],
changes["third"][0]["id"]),
put={
"draft_changes": {
"new_is_reviewed": True,
}
},
expect={
"reviewablefilechanges": [{
"id": int,
"review": review.id,
"changeset": changesets["second"]["id"],
"file": review.getFileId("second"),
"deleted_lines": int,
"inserted_lines": int,
"is_reviewed": False,
"reviewed_by": None,
"assigned_reviewers": [instance.userid("bob"),
instance.userid("dave")],
"draft_changes": {
"author": instance.userid("dave"),
"new_is_reviewed": True,
"new_reviewed_by": instance.userid("dave"),
},
}, {
"id": int,
"review": review.id,
"changeset": changesets["third"]["id"],
"file": review.getFileId("third"),
"deleted_lines": int,
"inserted_lines": int,
"is_reviewed": False,
"reviewed_by": None,
"assigned_reviewers": [instance.userid("bob"),
instance.userid("dave")],
"draft_changes": {
"author": instance.userid("dave"),
"new_is_reviewed": True,
"new_reviewed_by": instance.userid("dave"),
},
}],
})
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "dave", "draft",
created_comments=[issues["dave"][0]],
resolved_issues=[issues["alice"][0],
issues["alice"][1]],
reviewed_changes=[changes["second"][0]["id"],
changes["third"][0]["id"]]))
with frontend.signin("bob"):
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "bob", "draft",
created_comments=[issues["bob"][0]],
resolved_issues=[issues["alice"][0]],
reviewed_changes=[changes["second"][0]["id"]]))
frontend.json(
"reviews/%d/batches" % review.id,
post={
"comment": "This looks good!",
},
expect=batch_json(review.id, "bob", "published",
comment=int,
created_comments=[issues["bob"][0]],
resolved_issues=[issues["alice"][0]],
reviewed_changes=[changes["second"][0]["id"]]))
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "bob", "draft"))
with frontend.signin("dave"):
frontend.json(
"reviews/%d/batches" % review.id,
params={
"unpublished": "yes",
},
expect=batch_json(review.id, "dave", "draft",
created_comments=[issues["dave"][0]],
resolved_issues=[issues["alice"][1]],
reviewed_changes=[changes["third"][0]["id"]]))
# eof
| 36.072917
| 77
| 0.380667
| 1,001
| 13,852
| 5.160839
| 0.100899
| 0.055749
| 0.06988
| 0.073558
| 0.84127
| 0.815718
| 0.755517
| 0.748161
| 0.734998
| 0.672474
| 0
| 0.013689
| 0.472639
| 13,852
| 383
| 78
| 36.167102
| 0.693498
| 0.003465
| 0
| 0.698864
| 0
| 0
| 0.20071
| 0.024346
| 0
| 0
| 0
| 0
| 0
| 1
| 0.002841
| false
| 0
| 0
| 0
| 0.002841
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
1d8844409374c25ed07d2fd0a2fbef5e5063ca28
| 40
|
py
|
Python
|
deepspeed/ops/adam/__init__.py
|
bratao/DeepSpeed
|
c50d8955e942e5e26cf81835d59ec3f20ef8540d
|
[
"MIT"
] | 1
|
2020-09-25T13:54:15.000Z
|
2020-09-25T13:54:15.000Z
|
deepspeed/ops/adam/__init__.py
|
bratao/DeepSpeed
|
c50d8955e942e5e26cf81835d59ec3f20ef8540d
|
[
"MIT"
] | null | null | null |
deepspeed/ops/adam/__init__.py
|
bratao/DeepSpeed
|
c50d8955e942e5e26cf81835d59ec3f20ef8540d
|
[
"MIT"
] | 1
|
2020-09-13T08:06:51.000Z
|
2020-09-13T08:06:51.000Z
|
from .cpu_adam import DeepSpeedCPUAdam
| 20
| 39
| 0.85
| 5
| 40
| 6.6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 40
| 1
| 40
| 40
| 0.942857
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
d53eaa9827ac3d5897b7fdf373ebf9a80e6e4416
| 1,816
|
py
|
Python
|
tests/data/test_bo_unblacklist_user.py
|
c17r/TagTrain
|
5aa1ca36439cc5e81d0c691f905a4bb879b78399
|
[
"MIT"
] | null | null | null |
tests/data/test_bo_unblacklist_user.py
|
c17r/TagTrain
|
5aa1ca36439cc5e81d0c691f905a4bb879b78399
|
[
"MIT"
] | 7
|
2020-03-24T17:54:31.000Z
|
2021-09-21T12:34:34.000Z
|
tests/data/test_bo_unblacklist_user.py
|
c17r/TagTrain
|
5aa1ca36439cc5e81d0c691f905a4bb879b78399
|
[
"MIT"
] | null | null | null |
import pytest
from . import db
from .db import database
from tagtrain import data
def test_unknown_user(database):
with pytest.raises(data.Group.DoesNotExist):
data.by_owner.unblacklist_user('non-existent', 'doesnt-matter', db.GROUP_NAME)
def test_unknown_group(database):
with pytest.raises(data.Group.DoesNotExist):
data.by_owner.unblacklist_user(db.OWNER_NAME, 'doesnt-matter', 'non-existent')
def test_unknown_blanket_blacklist(database):
with pytest.raises(data.Blacklist.DoesNotExist):
data.by_owner.unblacklist_user(db.OWNER_NAME, 'non-existent')
def test_unknown_group_blacklist(database):
with pytest.raises(data.Blacklist.DoesNotExist):
data.by_owner.unblacklist_user(db.OWNER_NAME, 'non-existent', db.GROUP_NAME)
def test_good_blanket(database):
OWNER_NAME = 'user2'
MEMBER_NAME = 'blockee'
bls = list(data.by_owner.find_blacklists(OWNER_NAME, MEMBER_NAME))
assert len(bls) == 1
bl = data.by_owner.unblacklist_user(OWNER_NAME, MEMBER_NAME)
assert bl.owner_reddit_name == OWNER_NAME
assert bl.blocked_reddit_name == MEMBER_NAME
assert bl.group is None
bls = list(data.by_owner.find_blacklists(OWNER_NAME, MEMBER_NAME))
assert len(bls) == 0
def test_good_group(database):
OWNER_NAME = db.OWNER_NAME
GROUP_NAME = db.GROUP_NAME
MEMBER_NAME = 'blockee'
bls = list(data.by_owner.find_blacklists(OWNER_NAME, MEMBER_NAME))
assert len(bls) == 2
bl = data.by_owner.unblacklist_user(OWNER_NAME, MEMBER_NAME, GROUP_NAME)
assert bl.owner_reddit_name == OWNER_NAME
assert bl.blocked_reddit_name == MEMBER_NAME
assert bl.group is not None
assert bl.group.name == db.GROUP_NAME
bls = list(data.by_owner.find_blacklists(OWNER_NAME, MEMBER_NAME))
assert len(bls) == 1
| 30.266667
| 86
| 0.742291
| 263
| 1,816
| 4.851711
| 0.1673
| 0.098746
| 0.086207
| 0.109718
| 0.80721
| 0.717085
| 0.717085
| 0.717085
| 0.717085
| 0.708464
| 0
| 0.003266
| 0.156938
| 1,816
| 59
| 87
| 30.779661
| 0.830176
| 0
| 0
| 0.4
| 0
| 0
| 0.051211
| 0
| 0
| 0
| 0
| 0
| 0.275
| 1
| 0.15
| false
| 0
| 0.1
| 0
| 0.25
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
d598314ea9d76bb701fcce1812203ee46b871a0b
| 3,390
|
py
|
Python
|
pq_ce_monitoring/pq_pandadb.py
|
PanDAWMS/harvester_monitoring
|
85d4ce57eab97ad20f146ad1068325ce7a596667
|
[
"Apache-2.0"
] | null | null | null |
pq_ce_monitoring/pq_pandadb.py
|
PanDAWMS/harvester_monitoring
|
85d4ce57eab97ad20f146ad1068325ce7a596667
|
[
"Apache-2.0"
] | null | null | null |
pq_ce_monitoring/pq_pandadb.py
|
PanDAWMS/harvester_monitoring
|
85d4ce57eab97ad20f146ad1068325ce7a596667
|
[
"Apache-2.0"
] | 1
|
2019-02-20T17:36:48.000Z
|
2019-02-20T17:36:48.000Z
|
import json
from logger import ServiceLogger
from baseclasses.oracledbbaseclass import OracleDbBaseClass
_logger = ServiceLogger("pq_pandadb", __file__).logger
class PandaDBPQ(OracleDbBaseClass):
def __init__(self, path):
super().__init__(path)
def get_running_workers_jobs(self):
try:
connection = self.connection
computingsite_stat = {}
query = """
SELECT computingsite, count(status) as nworkers, count(jobstatus) as njobs
FROM
(SELECT
ww.computingsite as computingsite,
ww.status as status,
ww.lastupdate as wlastupdate,
ww.starttime as wstarttime,
jj.pandaid,
jj.LASTUPDATE as pidlastupdate,
ja.jobstatus,
ja.computingsite as jobcomputingsite
FROM ATLAS_PANDA.harvester_workers ww
LEFT OUTER JOIN atlas_panda.harvester_rel_jobs_workers jj ON ww.harvesterid = jj.harvesterid and ww.workerid = jj.workerid
LEFT OUTER JOIN atlas_panda.jobsactive4 ja ON jj.pandaid = ja.pandaid )
WHERE status = 'running' and wlastupdate >= CAST (sys_extract_utc(SYSTIMESTAMP) - interval '10' minute as DATE)
GROUP BY computingsite
"""
results = self.__read_query(query, connection)
for result in results:
computingsite_stat[result['computingsite']] = {'nworkers':result['nworkers'], 'njobs':result['njobs']}
except:
pass
return computingsite_stat
def get_running_workers_completed_jobs(self):
try:
connection = self.connection
computingsite_stat = {}
query = """
SELECT computingsite, count(status) as nworkers, count(jobstatus) as njobs
FROM
(SELECT
ww.computingsite as computingsite,
ww.status as status,
ww.lastupdate as wlastupdate,
ww.starttime as wstarttime,
jj.pandaid,
jj.LASTUPDATE as pidlastupdate,
ja.jobstatus,
ja.computingsite as jobcomputingsite
FROM ATLAS_PANDA.harvester_workers ww
LEFT OUTER JOIN atlas_panda.harvester_rel_jobs_workers jj ON ww.harvesterid = jj.harvesterid and ww.workerid = jj.workerid
LEFT OUTER JOIN atlas_panda.jobsarchived4 ja ON jj.pandaid = ja.pandaid)
WHERE status = 'running' and wlastupdate >= CAST (sys_extract_utc(SYSTIMESTAMP) - interval '10' minute as DATE)
GROUP BY computingsite
"""
results = self.__read_query(query, connection)
for result in results:
computingsite_stat[result['computingsite']] = {'nworkers':result['nworkers'], 'njobs':result['njobs']}
except:
pass
return computingsite_stat
# private method
def __read_query(self, query, connection):
cursor = connection.cursor()
try:
cursor.execute(query)
return self.__rows_to_dict_list(cursor)
finally:
if cursor is not None:
cursor.close()
# private method
def __rows_to_dict_list(self, cursor):
columns = [str(i[0]).lower() for i in cursor.description]
return [dict(zip(columns, row)) for row in cursor]
| 36.451613
| 134
| 0.613274
| 354
| 3,390
| 5.69209
| 0.279661
| 0.05062
| 0.037717
| 0.035732
| 0.735484
| 0.735484
| 0.735484
| 0.735484
| 0.735484
| 0.735484
| 0
| 0.003002
| 0.312094
| 3,390
| 92
| 135
| 36.847826
| 0.861063
| 0.008555
| 0
| 0.716216
| 0
| 0.054054
| 0.549434
| 0.072067
| 0
| 0
| 0
| 0
| 0
| 1
| 0.067568
| false
| 0.027027
| 0.040541
| 0
| 0.175676
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
6340a6f2358fdb957ebfd45cb5a7ac10c3782961
| 93
|
py
|
Python
|
spec/bin/argv.py
|
Schweinepriester/oil
|
8b0e5c58a825223341896064d63a95c8b57a9c05
|
[
"Apache-2.0"
] | 2,209
|
2016-11-20T10:32:58.000Z
|
2022-03-31T20:51:27.000Z
|
spec/bin/argv.py
|
Schweinepriester/oil
|
8b0e5c58a825223341896064d63a95c8b57a9c05
|
[
"Apache-2.0"
] | 1,074
|
2016-12-07T05:02:48.000Z
|
2022-03-22T02:09:11.000Z
|
spec/bin/argv.py
|
Schweinepriester/oil
|
8b0e5c58a825223341896064d63a95c8b57a9c05
|
[
"Apache-2.0"
] | 147
|
2016-12-11T04:13:28.000Z
|
2022-03-27T14:50:00.000Z
|
#!/usr/bin/env python2
from __future__ import print_function
import sys
print(sys.argv[1:])
| 15.5
| 37
| 0.774194
| 15
| 93
| 4.466667
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.024096
| 0.107527
| 93
| 5
| 38
| 18.6
| 0.783133
| 0.225806
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0.666667
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
|
0
| 6
|
634d414f3ba9ef3b9d6ff170297e0f5c715feae7
| 467
|
py
|
Python
|
edgelm/examples/MMPT/mmpt/tasks/__init__.py
|
guotao0628/DeepNet
|
1ae74d8b44d715bf67c7d64a8efafff4b7c7937a
|
[
"MIT"
] | 1
|
2021-11-07T00:30:05.000Z
|
2021-11-07T00:30:05.000Z
|
edgelm/examples/MMPT/mmpt/tasks/__init__.py
|
guotao0628/DeepNet
|
1ae74d8b44d715bf67c7d64a8efafff4b7c7937a
|
[
"MIT"
] | null | null | null |
edgelm/examples/MMPT/mmpt/tasks/__init__.py
|
guotao0628/DeepNet
|
1ae74d8b44d715bf67c7d64a8efafff4b7c7937a
|
[
"MIT"
] | null | null | null |
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from .task import *
from .vlmtask import *
from .retritask import *
try:
from .fairseqmmtask import *
except ImportError:
pass
try:
from .milncetask import *
except ImportError:
pass
try:
from .expretritask import *
except ImportError:
pass
| 20.304348
| 66
| 0.687366
| 59
| 467
| 5.440678
| 0.59322
| 0.065421
| 0.214953
| 0.252336
| 0.211838
| 0.211838
| 0
| 0
| 0
| 0
| 0
| 0
| 0.252677
| 467
| 22
| 67
| 21.227273
| 0.919771
| 0.359743
| 0
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.2
| 0.6
| 0
| 0.6
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
6368c6ff6119a625f388c77f74148a947cac98b0
| 18
|
py
|
Python
|
emacs/emacs.d/python-mode/test/UnicodeEncodeError-python2-lp-550661-test.py
|
KitKod/dotfiles
|
92d8081280c7b6ebe7d91a00efb5dcdcc882b271
|
[
"BSD-3-Clause"
] | 87
|
2015-01-03T13:57:31.000Z
|
2022-01-18T14:56:23.000Z
|
emacs/emacs.d/python-mode/test/UnicodeEncodeError-python2-lp-550661-test.py
|
KitKod/dotfiles
|
92d8081280c7b6ebe7d91a00efb5dcdcc882b271
|
[
"BSD-3-Clause"
] | 1
|
2015-09-13T15:45:54.000Z
|
2015-09-13T15:45:54.000Z
|
emacs/emacs.d/python-mode/test/UnicodeEncodeError-python2-lp-550661-test.py
|
KitKod/dotfiles
|
92d8081280c7b6ebe7d91a00efb5dcdcc882b271
|
[
"BSD-3-Clause"
] | 124
|
2015-01-15T22:05:39.000Z
|
2022-03-20T18:35:57.000Z
|
print(u'\xA9')
| 3.6
| 14
| 0.5
| 3
| 18
| 3
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 0.222222
| 18
| 4
| 15
| 4.5
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0.266667
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
892f1458e31c73522fc2b21e5aa86b619e94a5a0
| 147
|
py
|
Python
|
conf/script/src/build_system/compiler/__init__.py
|
benoit-dubreuil/template-repo-cpp-full-ecosystem
|
f506dd5e2a61cdd311b6a6a4be4abc59567b4b20
|
[
"MIT"
] | null | null | null |
conf/script/src/build_system/compiler/__init__.py
|
benoit-dubreuil/template-repo-cpp-full-ecosystem
|
f506dd5e2a61cdd311b6a6a4be4abc59567b4b20
|
[
"MIT"
] | 113
|
2021-02-15T19:22:36.000Z
|
2021-05-07T15:17:42.000Z
|
conf/script/src/build_system/compiler/__init__.py
|
benoit-dubreuil/template-repo-cpp-full-ecosystem
|
f506dd5e2a61cdd311b6a6a4be4abc59567b4b20
|
[
"MIT"
] | null | null | null |
from .build_option import *
from .core import *
from .installed_instance import *
from .reqs import *
from .supported_installed_instances import *
| 24.5
| 44
| 0.795918
| 19
| 147
| 5.947368
| 0.526316
| 0.353982
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136054
| 147
| 5
| 45
| 29.4
| 0.889764
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
897d3eb7061aee4346e0741682d29323f39bf029
| 64
|
py
|
Python
|
ctc-no-dependencies/loaders/__init__.py
|
martin-fabbri/ctc-tensorflow
|
4e45f8c62223d4287896d29099c2c15be5e70bd9
|
[
"Apache-2.0"
] | null | null | null |
ctc-no-dependencies/loaders/__init__.py
|
martin-fabbri/ctc-tensorflow
|
4e45f8c62223d4287896d29099c2c15be5e70bd9
|
[
"Apache-2.0"
] | null | null | null |
ctc-no-dependencies/loaders/__init__.py
|
martin-fabbri/ctc-tensorflow
|
4e45f8c62223d4287896d29099c2c15be5e70bd9
|
[
"Apache-2.0"
] | null | null | null |
from .audio_loader import *
from .data_loader import DataLoader
| 21.333333
| 35
| 0.828125
| 9
| 64
| 5.666667
| 0.666667
| 0.470588
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 64
| 2
| 36
| 32
| 0.910714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
89814eb0b15b01d17501db843cacd5a5770379fd
| 23,563
|
py
|
Python
|
gs_quant/timeseries/measures_rates.py
|
alexanu/gs-quant
|
fbb8d88d570aee545ed3a8601d9052c281ecca19
|
[
"Apache-2.0"
] | 1
|
2020-05-18T02:09:39.000Z
|
2020-05-18T02:09:39.000Z
|
gs_quant/timeseries/measures_rates.py
|
atefar2/gs-quant
|
d31ae3204d5421861897bac49383bc213d5497a2
|
[
"Apache-2.0"
] | null | null | null |
gs_quant/timeseries/measures_rates.py
|
atefar2/gs-quant
|
d31ae3204d5421861897bac49383bc213d5497a2
|
[
"Apache-2.0"
] | null | null | null |
"""
Copyright 2020 Goldman Sachs.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing,
software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
KIND, either express or implied. See the License for the
specific language governing permissions and limitations
under the License.
"""
import logging
import re
from typing import Optional
import datetime
import pandas as pd
from pandas import Series
from gs_quant.api.gs.assets import GsAssetApi
from gs_quant.api.gs.data import QueryType, GsDataApi
from gs_quant.data import DataContext
from gs_quant.errors import MqValueError
from gs_quant.datetime.gscalendar import GsCalendar
from gs_quant.markets.securities import AssetIdentifier, Asset
from gs_quant.target.common import Currency as CurrencyEnum, PricingLocation, AssetClass, AssetType, FieldFilterMap
from gs_quant.timeseries import ASSET_SPEC, BenchmarkType, plot_measure, MeasureDependency, GENERIC_DATE
from gs_quant.timeseries.helper import _to_offset
from gs_quant.timeseries.measures import _asset_from_spec, _market_data_timed, _range_from_pricing_date, \
_get_custom_bd
_logger = logging.getLogger(__name__)
CURRENCY_TO_SWAP_RATE_BENCHMARK = {
'CHF': {'LIBOR': 'CHF-LIBOR-BBA', 'SARON': 'CHF-SARON-OIS-COMPOUND'},
'EUR': {'EURIBOR': 'EUR-EURIBOR-Telerate', 'EONIA': 'EUR-EONIA-OIS-COMPOUND'},
'GBP': {'LIBOR': 'GBP-LIBOR-BBA', 'SONIA': 'GBP-SONIA-COMPOUND'},
'JPY': {'LIBOR': 'JPY-LIBOR-BBA', 'TONA': 'JPY-TONA-OIS-COMPOUND'},
'SEK': {'STIBOR': 'SEK-STIBOR-SIDE'},
'USD': {'LIBOR': 'USD-LIBOR-BBA', 'Fed_Funds': 'USD-Federal Funds-H.15-OIS-COMP', 'SOFR': 'USD-SOFR-COMPOUND'}
}
BENCHMARK_TO_DEFAULT_FLOATING_RATE_TENORS = {
'CHF-LIBOR-BBA': '6m',
'CHF-SARON-OIS-COMPOUND': '1y',
'EUR-EURIBOR-Telerate': '6m',
'EUR-EONIA-OIS-COMPOUND': '1y',
'GBP-LIBOR-BBA': '6m',
'GBP-SONIA-COMPOUND': '1y',
'JPY-LIBOR-BBA': '6m',
'JPY-TONA-OIS-COMPOUND': '1y',
'SEK-STIBOR-SIDE': '6m',
'USD-LIBOR-BBA': '3m',
'USD-Federal Funds-H.15-OIS-COMP': '1y',
'USD-SOFR-COMPOUND': '1y'
}
def _currency_to_mdapi_swap_rate_asset(asset_spec: ASSET_SPEC) -> str:
asset = _asset_from_spec(asset_spec)
bbid = asset.get_identifier(AssetIdentifier.BLOOMBERG_ID)
# for each currency, get a dummy asset for checking availability
if bbid == 'CHF':
result = 'MAW25BGQJH9P6DPT'
elif bbid == 'EUR':
result = 'MAA9MVX15AJNQCVG'
elif bbid == 'GBP':
result = 'MA6QCAP9B7ABS9HA'
elif bbid == 'JPY':
result = 'MAEE219J5ZP0ZKRK'
elif bbid == 'SEK':
result = 'MAETMVTPNP3199A5'
elif bbid == 'USD':
result = 'MAFRSWPAF5QPNTP2'
else:
return asset.get_marquee_id()
return result
def _currency_to_mdapi_basis_swap_rate_asset(asset_spec: ASSET_SPEC) -> str:
asset = _asset_from_spec(asset_spec)
bbid = asset.get_identifier(AssetIdentifier.BLOOMBERG_ID)
# for each currency, get a dummy asset for checking availability
if bbid == 'EUR':
result = 'MAGRG2VT11GQ2RQ9'
elif bbid == 'GBP':
result = 'MAHCYNB3V75JC5Q8'
elif bbid == 'JPY':
result = 'MAXVRBEZCJVH0C4V'
elif bbid == 'USD':
result = 'MAQB1PGEJFCET3GG'
else:
return asset.get_marquee_id()
return result
def _convert_asset_for_mdapi_swap_rates(**kwargs) -> str:
assets = GsAssetApi.get_many_assets(**kwargs)
if len(assets) > 1:
raise MqValueError('Specified arguments match multiple assets')
elif len(assets) == 0:
raise MqValueError('Specified arguments did not match any asset in the dataset')
else:
return assets[0].id
def check_forward_tenor(forward_tenor) -> GENERIC_DATE:
if isinstance(forward_tenor, datetime.date):
return forward_tenor
elif forward_tenor is None or forward_tenor == 'Spot':
return '0b'
elif not (re.fullmatch('(\\d+)([bdwmy])', forward_tenor) or re.fullmatch('(imm[1-4]|frb[1-9])', forward_tenor)):
raise MqValueError('invalid forward tenor ' + forward_tenor)
else:
return forward_tenor
def _check_benchmark_type(currency, benchmark_type):
if benchmark_type is not None and \
benchmark_type.value not in CURRENCY_TO_SWAP_RATE_BENCHMARK[currency.value].keys():
raise MqValueError('%s is not supported for %s', benchmark_type, currency.value)
def _get_swap_leg_defaults(currency: CurrencyEnum, benchmark_type: BenchmarkType = None,
floating_rate_tenor: str = None) -> dict:
if currency == CurrencyEnum.JPY:
pricing_location = PricingLocation.TKO
elif currency == CurrencyEnum.USD:
pricing_location = PricingLocation.NYC
else:
pricing_location = PricingLocation.LDN
# default benchmark types
if benchmark_type is None:
if currency == CurrencyEnum.EUR:
benchmark_type = BenchmarkType.EURIBOR
elif currency == CurrencyEnum.SEK:
benchmark_type = BenchmarkType.STIBOR
else:
benchmark_type = BenchmarkType.LIBOR
benchmark_type_input = CURRENCY_TO_SWAP_RATE_BENCHMARK[currency.value][benchmark_type.value]
# default floating index
if floating_rate_tenor is None:
floating_rate_tenor = BENCHMARK_TO_DEFAULT_FLOATING_RATE_TENORS[benchmark_type_input]
return dict(currency=currency, benchmark_type=benchmark_type_input,
floating_rate_tenor=floating_rate_tenor, pricing_location=pricing_location)
@plot_measure((AssetClass.Cash,), (AssetType.Currency,),
[MeasureDependency(id_provider=_currency_to_mdapi_swap_rate_asset, query_type=QueryType.SWAP_RATE)])
def swap_rate_2(asset: Asset, swap_tenor: str, benchmark_type: BenchmarkType = None, floating_rate_tenor: str = None,
forward_tenor: Optional[GENERIC_DATE] = None, *, source: str = None,
real_time: bool = False) -> Series:
"""
GS end-of-day Fixed-Floating interest rate swap (IRS) curves across major currencies.
:param asset: asset object loaded from security master
:param swap_tenor: relative date representation of expiration date e.g. 1m
:param benchmark_type: benchmark type e.g. LIBOR
:param floating_rate_tenor: floating index rate
:param forward_tenor: absolute / relative date representation of forward starting point eg: '1y' or 'Spot' for
spot starting swaps, 'imm1' or 'frb1'
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate curve
"""
if real_time:
raise NotImplementedError('realtime swap_rate not implemented')
currency = CurrencyEnum(asset.get_identifier(AssetIdentifier.BLOOMBERG_ID))
if currency.value not in ['JPY', 'EUR', 'USD', 'GBP', 'CHF', 'SEK']:
raise NotImplementedError('Data not available for {} swap rates'.format(currency.value))
_check_benchmark_type(currency, benchmark_type)
defaults = _get_swap_leg_defaults(currency, benchmark_type, floating_rate_tenor)
if not (re.fullmatch('(\\d+)([bdwmy])', swap_tenor) or re.fullmatch('(frb[1-9])', forward_tenor)):
raise MqValueError('invalid swap tenor ' + swap_tenor)
if not re.fullmatch('(\\d+)([bdwmy])', defaults['floating_rate_tenor']):
raise MqValueError('invalid floating rate tenor ' + defaults['floating_rate_tenor'] + ' for index: ' +
defaults['benchmark_type'])
forward_tenor = check_forward_tenor(forward_tenor)
clearing_house = 'LCH'
csaTerms = currency.value + '-1'
fixed_rate = 'ATM'
kwargs = dict(type='Swap', asset_parameters_termination_date=swap_tenor,
asset_parameters_floating_rate_option=defaults['benchmark_type'],
asset_parameters_fixed_rate=fixed_rate, asset_parameters_clearing_house=clearing_house,
asset_parameters_floating_rate_designated_maturity=defaults['floating_rate_tenor'],
asset_parameters_effective_date=forward_tenor,
asset_parameters_notional_currency=currency.name, pricing_location=defaults['pricing_location'].value)
rate_mqid = _convert_asset_for_mdapi_swap_rates(**kwargs)
_logger.debug('where asset= %s, swap_tenor=%s, benchmark_type=%s, floating_rate_tenor=%s, forward_tenor=%s, '
'pricing_location=%s', rate_mqid, swap_tenor, defaults['benchmark_type'],
defaults['floating_rate_tenor'], forward_tenor, defaults['pricing_location'].value)
where = FieldFilterMap(csaTerms=csaTerms)
q = GsDataApi.build_market_data_query([rate_mqid], QueryType.SWAP_RATE, where=where, source=source,
real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
return Series() if df.empty else df['swapRate']
@plot_measure((AssetClass.Cash,), (AssetType.Currency,),
[MeasureDependency(id_provider=_currency_to_mdapi_basis_swap_rate_asset,
query_type=QueryType.BASIS_SWAP_RATE)])
def basis_swap_spread(asset: Asset, swap_tenor: str = '1y',
spread_benchmark_type: BenchmarkType = None, spread_tenor: str = None,
reference_benchmark_type: BenchmarkType = None, reference_tenor: str = None,
forward_tenor: Optional[GENERIC_DATE] = None, *, source: str = None,
real_time: bool = False, ) -> Series:
"""
GS end-of-day Floating-Floating interest rate swap (IRS) curves across major currencies.
:param asset: asset object loaded from security master
:param swap_tenor: relative date representation of expiration date e.g. 1m
:param spread_benchmark_type: benchmark type of spread leg on which basis spread is added e.g. LIBOR
:param spread_tenor: relative date representation of expiration date of paying leg e.g. 1m
:param reference_benchmark_type: benchmark type of reference leg e.g. LIBOR
:param reference_tenor: relative date representation of expiration date of reference leg e.g. 1m
:param forward_tenor: absolute / relative date representation of forward starting point eg: '1y' or 'Spot' for
spot starting swaps, 'imm1' or 'frb1'
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate curve
"""
if real_time:
raise NotImplementedError('realtime basis_swap_rate not implemented')
currency = CurrencyEnum(asset.get_identifier(AssetIdentifier.BLOOMBERG_ID))
if currency.value not in ['JPY', 'EUR', 'USD', 'GBP']:
raise NotImplementedError('Data not available for {} basis swap rates'.format(currency.value))
for benchmark_type in [spread_benchmark_type, reference_benchmark_type]:
_check_benchmark_type(currency, benchmark_type)
if not (re.fullmatch('(\\d+)([bdwmy])', swap_tenor) or re.fullmatch('(frb[1-9])', forward_tenor)):
raise MqValueError('invalid swap tenor ' + swap_tenor)
# default benchmark types
legs_w_defaults = dict()
legs_w_defaults['spread'] = _get_swap_leg_defaults(currency, spread_benchmark_type, spread_tenor)
legs_w_defaults['reference'] = _get_swap_leg_defaults(currency, reference_benchmark_type, reference_tenor)
for key, leg in legs_w_defaults.items():
if not re.fullmatch('(\\d+)([bdwmy])', leg['floating_rate_tenor']):
raise MqValueError('invalid floating rate tenor ' + leg['floating_rate_tenor'] + ' index: ' +
leg['benchmark_type'])
forward_tenor = check_forward_tenor(forward_tenor)
csaTerms = currency.value + '-1'
clearing_house = 'LCH'
kwargs = dict(type='BasisSwap', asset_parameters_termination_date=swap_tenor,
asset_parameters_payer_rate_option=legs_w_defaults['spread']['benchmark_type'],
asset_parameters_payer_designated_maturity=legs_w_defaults['spread']['floating_rate_tenor'],
asset_parameters_receiver_rate_option=legs_w_defaults['reference']['benchmark_type'],
asset_parameters_receiver_designated_maturity=legs_w_defaults['reference']['floating_rate_tenor'],
asset_parameters_clearing_house=clearing_house, asset_parameters_effective_date=forward_tenor,
asset_parameters_notional_currency=currency.name,
pricing_location=legs_w_defaults['spread']['pricing_location'].value)
rate_mqid = _convert_asset_for_mdapi_swap_rates(**kwargs)
_logger.debug('where asset=%s, swap_tenor=%s, spread_benchmark_type=%s, spread_tenor=%s, '
'reference_benchmark_type=%s, reference_tenor=%s, forward_tenor=%s, pricing_location=%s ',
rate_mqid, swap_tenor, legs_w_defaults['spread']['benchmark_type'],
legs_w_defaults['spread']['floating_rate_tenor'],
legs_w_defaults['reference']['benchmark_type'], legs_w_defaults['reference']['floating_rate_tenor'],
forward_tenor, legs_w_defaults['spread']['pricing_location'].value)
where = FieldFilterMap(csaTerms=csaTerms)
q = GsDataApi.build_market_data_query([rate_mqid], QueryType.BASIS_SWAP_RATE, where=where, source=source,
real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
return Series() if df.empty else df['basisSwapRate']
@plot_measure((AssetClass.Cash,), (AssetType.Currency,),
[MeasureDependency(id_provider=_currency_to_mdapi_swap_rate_asset, query_type=QueryType.SWAP_RATE)])
def swap_term_structure(asset: Asset, benchmark_type: BenchmarkType = None, floating_rate_tenor: str = None,
forward_tenor: Optional[GENERIC_DATE] = None, pricing_date: Optional[GENERIC_DATE] = None,
*, source: str = None, real_time: bool = False) -> Series:
"""
GS end-of-day Fixed-Floating interest rate swap (IRS) term structure across major currencies.
:param asset: asset object loaded from security master
:param benchmark_type: benchmark type e.g. LIBOR
:param floating_rate_tenor: floating index rate
:param forward_tenor: absolute / relative date representation of forward starting point eg: '1y' or 'Spot' for
spot starting swaps, 'imm1' or 'frb1'
:param pricing_date: YYYY-MM-DD or relative date
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate term structure
"""
if real_time:
raise NotImplementedError('realtime swap_rate not implemented')
currency = asset.get_identifier(AssetIdentifier.BLOOMBERG_ID)
currency = CurrencyEnum(currency)
if currency.value not in ['JPY', 'EUR', 'USD', 'GBP', 'CHF', 'SEK']:
raise NotImplementedError('Data not available for {} swap rates'.format(currency.value))
clearing_house = 'LCH'
_check_benchmark_type(currency, benchmark_type)
forward_tenor = check_forward_tenor(forward_tenor)
defaults = _get_swap_leg_defaults(currency, benchmark_type, floating_rate_tenor)
if not re.fullmatch('(\\d+)([bdwmy])', defaults['floating_rate_tenor']):
raise MqValueError('invalid floating rate tenor ' + defaults['floating_rate_tenor'] + ' for index: ' +
defaults['benchmark_type'])
calendar = defaults['pricing_location'].value
if pricing_date is not None and pricing_date in list(GsCalendar.get(calendar).holidays):
raise MqValueError('Specified pricing date is a holiday in {} calendar'.format(calendar))
csaTerms = currency.value + '-1'
fixed_rate = 'ATM'
kwargs = dict(type='Swap', asset_parameters_floating_rate_option=defaults['benchmark_type'],
asset_parameters_fixed_rate=fixed_rate, asset_parameters_clearing_house=clearing_house,
asset_parameters_floating_rate_designated_maturity=defaults['floating_rate_tenor'],
asset_parameters_effective_date=forward_tenor,
asset_parameters_notional_currency=currency.name, pricing_location=defaults['pricing_location'].value)
assets = GsAssetApi.get_many_assets(**kwargs)
if len(assets) == 0:
raise MqValueError('Specified arguments did not match any asset in the dataset')
else:
rate_mqids = [asset.id for asset in assets]
asset_string = ''
for mqid in rate_mqids:
asset_string = asset_string + ',' + mqid
_logger.debug('assets returned %s', asset_string)
_logger.debug('where benchmark_type=%s, floating_rate_tenor=%s, forward_tenor=%s, '
'pricing_location=%s', defaults['benchmark_type'], defaults['floating_rate_tenor'],
forward_tenor, defaults['pricing_location'].value)
start, end = _range_from_pricing_date(calendar, pricing_date)
with DataContext(start, end):
where = FieldFilterMap(csaTerms=csaTerms)
q = GsDataApi.build_market_data_query(rate_mqids, QueryType.SWAP_RATE, where=where,
source=source, real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
if df.empty:
return pd.Series()
latest = df.index.max()
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
business_day = _get_custom_bd(calendar)
df = df.assign(expirationDate=df.index + df['terminationTenor'].map(_to_offset) + business_day - business_day)
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date: DataContext.current.end_date]
return df['swapRate'] if not df.empty else pd.Series()
@plot_measure((AssetClass.Cash,), (AssetType.Currency,),
[MeasureDependency(id_provider=_currency_to_mdapi_basis_swap_rate_asset,
query_type=QueryType.BASIS_SWAP_RATE)])
def basis_swap_term_structure(asset: Asset, spread_benchmark_type: BenchmarkType = None, spread_tenor: str = None,
reference_benchmark_type: BenchmarkType = None, reference_tenor: str = None,
forward_tenor: Optional[GENERIC_DATE] = None,
pricing_date: Optional[GENERIC_DATE] = None,
*, source: str = None, real_time: bool = False, ) -> Series:
"""
GS end-of-day Floating-Floating interest rate swap (IRS) term structure across major currencies.
:param asset: asset object loaded from security master
:param spread_benchmark_type: benchmark type of spread leg on which basis spread is added e.g. LIBOR
:param spread_tenor: relative date representation of expiration date of spread leg e.g. 1m
:param reference_benchmark_type: benchmark type of reference leg e.g. LIBOR
:param reference_tenor: relative date representation of expiration date of reference leg e.g. 1m
:param forward_tenor: absolute / relative date representation of forward starting point eg: '1y' or 'Spot' for
spot starting swaps, 'imm1' or 'frb1'
:param pricing_date: YYYY-MM-DD or relative date
:param source: name of function caller
:param real_time: whether to retrieve intraday data instead of EOD
:return: swap rate curve
"""
if real_time:
raise NotImplementedError('realtime basis_swap_rate not implemented')
currency = CurrencyEnum(asset.get_identifier(AssetIdentifier.BLOOMBERG_ID))
if currency.value not in ['JPY', 'EUR', 'USD', 'GBP']:
raise NotImplementedError('Data not available for {} basis swap rates'.format(currency.value))
for benchmark_type in [spread_benchmark_type, reference_benchmark_type]:
_check_benchmark_type(currency, benchmark_type)
# default benchmark types
legs_w_defaults = dict()
legs_w_defaults['spread'] = _get_swap_leg_defaults(currency, spread_benchmark_type, spread_tenor)
legs_w_defaults['reference'] = _get_swap_leg_defaults(currency, reference_benchmark_type, reference_tenor)
for key, leg in legs_w_defaults.items():
if not re.fullmatch('(\\d+)([bdwmy])', leg['floating_rate_tenor']):
raise MqValueError('invalid floating rate tenor ' + leg['floating_rate_tenor'] + ' index: ' +
leg['benchmark_type'])
forward_tenor = check_forward_tenor(forward_tenor)
calendar = legs_w_defaults['spread']['pricing_location'].value
if pricing_date is not None and pricing_date in list(GsCalendar.get(calendar).holidays):
raise MqValueError('Specified pricing date is a holiday in {} calendar'.format(calendar))
csaTerms = currency.value + '-1'
clearing_house = 'LCH'
kwargs = dict(type='BasisSwap', asset_parameters_payer_rate_option=legs_w_defaults['spread']['benchmark_type'],
asset_parameters_payer_designated_maturity=legs_w_defaults['spread']['floating_rate_tenor'],
asset_parameters_receiver_rate_option=legs_w_defaults['reference']['benchmark_type'],
asset_parameters_receiver_designated_maturity=legs_w_defaults['reference']['floating_rate_tenor'],
asset_parameters_clearing_house=clearing_house, asset_parameters_effective_date=forward_tenor,
asset_parameters_notional_currency=currency.name,
pricing_location=legs_w_defaults['spread']['pricing_location'].value)
assets = GsAssetApi.get_many_assets(**kwargs)
if len(assets) == 0:
raise MqValueError('Specified arguments did not match any asset in the dataset')
else:
rate_mqids = [asset.id for asset in assets]
asset_string = ''
for mqid in rate_mqids:
asset_string = asset_string + ',' + mqid
_logger.debug('assets returned %s', asset_string)
_logger.debug('where spread_benchmark_type=%s, spread_tenor=%s, reference_benchmark_type=%s, '
'reference_tenor=%s, forward_tenor=%s, pricing_location=%s ',
legs_w_defaults['spread']['benchmark_type'], legs_w_defaults['spread']['floating_rate_tenor'],
legs_w_defaults['reference']['benchmark_type'], legs_w_defaults['reference']['floating_rate_tenor'],
forward_tenor, legs_w_defaults['spread']['pricing_location'].value)
start, end = _range_from_pricing_date(calendar, pricing_date)
with DataContext(start, end):
where = FieldFilterMap(csaTerms=csaTerms)
q = GsDataApi.build_market_data_query(rate_mqids, QueryType.BASIS_SWAP_RATE, where=where,
source=source, real_time=real_time)
_logger.debug('q %s', q)
df = _market_data_timed(q)
if df.empty:
return pd.Series()
latest = df.index.max()
_logger.info('selected pricing date %s', latest)
df = df.loc[latest]
business_day = _get_custom_bd(calendar)
df = df.assign(expirationDate=df.index + df['terminationTenor'].map(_to_offset) + business_day - business_day)
df = df.set_index('expirationDate')
df.sort_index(inplace=True)
df = df.loc[DataContext.current.start_date: DataContext.current.end_date]
return df['basisSwapRate'] if not df.empty else pd.Series()
| 49.398323
| 120
| 0.699444
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| 23,563
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0
| 6
|
899fd6e02e132125d48ba53f37d7d830846cebde
| 22
|
py
|
Python
|
gblint/__init__.py
|
avoceteditors/gblint
|
7935e58a1e744931fd70170fe0db3d9664b8a9a5
|
[
"BSD-3-Clause"
] | 1
|
2020-08-10T18:54:51.000Z
|
2020-08-10T18:54:51.000Z
|
gblint/__init__.py
|
avoceteditors/gblint
|
7935e58a1e744931fd70170fe0db3d9664b8a9a5
|
[
"BSD-3-Clause"
] | null | null | null |
gblint/__init__.py
|
avoceteditors/gblint
|
7935e58a1e744931fd70170fe0db3d9664b8a9a5
|
[
"BSD-3-Clause"
] | null | null | null |
from .core import run
| 11
| 21
| 0.772727
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| 4.25
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| 0
| 0
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| 0
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0
| 6
|
98363093fca20b74b1c9711df2c6a9342585c0ff
| 17,994
|
py
|
Python
|
simulation-bin/run_binary_paper2/priming_and_activation/averageFileColumnsAdvancedMod.py
|
jlubo/memory-consolidation-stc
|
f9934760e12de324360297d7fc7902623169cb4d
|
[
"Apache-2.0"
] | 2
|
2021-03-02T21:46:56.000Z
|
2021-06-30T03:12:07.000Z
|
simulation-bin/run_binary_paper2/priming_and_activation/averageFileColumnsAdvancedMod.py
|
jlubo/memory-consolidation-stc
|
f9934760e12de324360297d7fc7902623169cb4d
|
[
"Apache-2.0"
] | null | null | null |
simulation-bin/run_binary_paper2/priming_and_activation/averageFileColumnsAdvancedMod.py
|
jlubo/memory-consolidation-stc
|
f9934760e12de324360297d7fc7902623169cb4d
|
[
"Apache-2.0"
] | 3
|
2021-03-22T12:56:52.000Z
|
2021-09-13T07:42:36.000Z
|
##############################################################################################
### Script to average data from the same columns in data files stored in different folders ###
##############################################################################################
### Copyright 2017-2021 Jannik Luboeinski
### licensed under Apache-2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import numpy as np
import os
from pathlib import Path
from mergeRawData import *
# averageFileColumns
# Averages specified data columns across data files located in directories which names contain a specific string
# and computes the standard deviation
# outname: name of the file to write the averaged data to
# rootpath: path in which to look for data folders
# protocol: string that the data folders have to contain
# suffix: suffix in the filename of data files to be read
# columns: list of numbers of the columns in the data file to be read and averaged (e.g., [1, 3] for first and third column)
# first_column_par [optional]: indicates if first column is to be treated as parameter (e.g., time) - it is then added regardless of 'columns'
# comment_line [optional]: if True, leaves out the first line
def averageFileColumns(outname, rootpath, protocol, suffix, columns, first_column_par=True, comment_line=False):
print("Averaging columns " + str(columns) + " from files matching '*" + suffix + "' in folders of the protocol '" + protocol + "'...")
sample_number = 0
col_sep = '= ' #'\t\t' character(s) separating the columns
# find the folders with the protocol in their name
rawpaths = Path(rootpath)
paths = np.array([str(x) for x in rawpaths.iterdir() if x.is_dir() and protocol in str(x)])
if paths.size == 0:
raise FileNotFoundError("No folders found that contain the string '" + protocol + "' in their name.")
print("According folders found:\n", paths)
# read data and average
# loop over directories
for i in range(paths.size):
# find the files with the suffix in their name
subrawpaths = Path(paths[i])
subpaths = np.array([str(x) for x in subrawpaths.iterdir() if str(x).find(suffix) >= len(str(x))-len(suffix)])
if subpaths.size == 0:
raise FileNotFoundError("No files found matching '*" + suffix + "' in '" + paths[i] + "'.")
print("According files found in '" + paths[i] + "':\n", subpaths)
sample_number += subpaths.size
# loop over files in each directory
for j in range(subpaths.size):
with open(subpaths[j]) as f:
rawdata = f.read()
rawdata = rawdata.split('\n')
if comment_line:
del rawdata[0] # leave out comment line
if rawdata[-1] == "":
del rawdata[-1] # delete empty line
if i == 0 and j == 0: # first file found: read number of rows and create data arrays
num_rows = len(rawdata)
num_cols = len(columns)
time = np.zeros(num_rows)
data = np.zeros((num_rows, num_cols))
data_var = np.zeros((num_rows, num_cols))
elif num_rows != len(rawdata):
raise IndexError("In '" + subpaths[j] + "': wrong number of rows: " + str(len(rawdata)-1) + " (" + str(num_rows) + " expected).")
for k in range(num_rows):
values = rawdata[k].split(col_sep)
if len(values) < 2:
values = [np.nan,np.nan] # to avoid problems reading descriptions
try:
time[k] += np.double(values[0]) # read first/parameter column
except ValueError:
pass#print("Computing mean: conversion error in line " + str(k+1) + ", column 1\n\tin '" + subpaths[j] + "'.")
for l in range(num_cols):
try:
data[k][l] += np.double(values[columns[l]-1]) # read data columns
except ValueError:
pass#print("Computing mean: conversion error in line " + str(k+1) + ", column " + str(columns[l]) + "\n\tin '" + subpaths[j] + "'.")
f.close()
time = time / sample_number
data = data / sample_number
# read data and compute variance
# loop over directories
for i in range(paths.size):
# loop over files in each directory
for j in range(subpaths.size):
with open(subpaths[j]) as f:
rawdata = f.read()
rawdata = rawdata.split('\n')
if comment_line:
del rawdata[0] # leave out comment line
if rawdata[-1] == "":
del rawdata[-1] # delete empty line
for k in range(num_rows):
values = rawdata[k].split(col_sep)
#if len(values) < 2:
# values = [np.nan,np.nan] # to avoid problems reading descriptions
for l in range(num_cols):
try:
data_var[k][l] += np.power(np.double(values[columns[l]-1])-data[k][l], 2) # read data columns
except:
pass#print("Computing variance: conversion error in line " + str(k+1) + ", column " + str(columns[l]) + "\n\tin '" + subpaths[j] + "'.")
#except IndexError:
# print("INDEX ERROR")
f.close()
data_stdev = np.sqrt(data_var / (sample_number - 1))
# write averaged data
fout = open(outname + '.txt', 'w')
for k in range(num_rows): ## ADAPTED
if k >=4 and k <=7: # only need those four rows!
for l in range(num_cols):
fout.write(str(data[k][l]) + "\t" + str(data_stdev[k][l]))
if (k+1) % 4 == 0 and l >= num_cols-1: # after the last column and after 4 rows have been clutched together
fout.write("\n")
else: # as long as last column is not yet reached
fout.write("\t")
fout.close()
f = open("p_act_summary_temp_0names.txt", "w")
f.write("NOOVERLAP, A primed\n")
f.write("NOOVERLAP, B primed\n")
f.write("NOOVERLAP, C primed\n")
f.write("OVERLAP10, A primed\n")
f.write("OVERLAP10, B primed\n")
f.write("OVERLAP10, C primed\n")
f.write("OVERLAP10 no AC, no ABC, A primed\n")
f.write("OVERLAP10 no AC, no ABC, B primed\n")
f.write("OVERLAP10 no AC, no ABC, C primed\n")
f.write("OVERLAP10 no BC, no ABC, A primed\n")
f.write("OVERLAP10 no BC, no ABC, B primed\n")
f.write("OVERLAP10 no BC, no ABC, C primed\n")
f.close()
# 10 min
averageFileColumns("p_act_averaged_Aprimed", "2. Switching after 10 min/NOOVERLAP/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "2. Switching after 10 min/NOOVERLAP/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "2. Switching after 10 min/NOOVERLAP/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_10min_NOOVERLAP.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "2. Switching after 10 min/OVERLAP10/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "2. Switching after 10 min/OVERLAP10/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "2. Switching after 10 min/OVERLAP10/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_10min_OVERLAP10.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "2. Switching after 10 min/OVERLAP10 no AC, no ABC/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "2. Switching after 10 min/OVERLAP10 no AC, no ABC/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "2. Switching after 10 min/OVERLAP10 no AC, no ABC/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_10min_OVERLAP10_noAC_noABC.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "2. Switching after 10 min/OVERLAP10 no BC, no ABC/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "2. Switching after 10 min/OVERLAP10 no BC, no ABC/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "2. Switching after 10 min/OVERLAP10 no BC, no ABC/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_10min_OVERLAP10_noBC_noABC.txt", remove_raw=True, sep_str='\n')
os.system('cat "p_act_10min_NOOVERLAP.txt" > "p_act_summary_temp_10min.txt"')
os.system('cat "p_act_10min_OVERLAP10.txt" >> "p_act_summary_temp_10min.txt"')
os.system('cat "p_act_10min_OVERLAP10_noAC_noABC.txt" >> "p_act_summary_temp_10min.txt"')
os.system('cat "p_act_10min_OVERLAP10_noBC_noABC.txt" >> "p_act_summary_temp_10min.txt"')
os.system('rm -R -f "p_act_10min"*')
mergeRawData(".", "p_act_summary_temp_", "p_act_summary_10min.txt", remove_raw=False, sep_str='\t') # remove_raw=False to keep _temp_0names file
os.system('rm -f p_act_summary_temp_10min.txt')
# 1 h
averageFileColumns("p_act_averaged_Aprimed", "3. Switching after 1 h/NOOVERLAP/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "3. Switching after 1 h/NOOVERLAP/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "3. Switching after 1 h/NOOVERLAP/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_1h_NOOVERLAP.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "3. Switching after 1 h/OVERLAP10/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "3. Switching after 1 h/OVERLAP10/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "3. Switching after 1 h/OVERLAP10/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_1h_OVERLAP10.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "3. Switching after 1 h/OVERLAP10 no AC, no ABC/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "3. Switching after 1 h/OVERLAP10 no AC, no ABC/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "3. Switching after 1 h/OVERLAP10 no AC, no ABC/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_1h_OVERLAP10_noAC_noABC.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "3. Switching after 1 h/OVERLAP10 no BC, no ABC/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "3. Switching after 1 h/OVERLAP10 no BC, no ABC/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "3. Switching after 1 h/OVERLAP10 no BC, no ABC/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_1h_OVERLAP10_noBC_noABC.txt", remove_raw=True, sep_str='\n')
os.system('cat "p_act_1h_NOOVERLAP.txt" > "p_act_summary_temp_1h.txt"')
os.system('cat "p_act_1h_OVERLAP10.txt" >> "p_act_summary_temp_1h.txt"')
os.system('cat "p_act_1h_OVERLAP10_noAC_noABC.txt" >> "p_act_summary_temp_1h.txt"')
os.system('cat "p_act_1h_OVERLAP10_noBC_noABC.txt" >> "p_act_summary_temp_1h.txt"')
os.system('rm -R -f "p_act_1h"*')
mergeRawData(".", "p_act_summary_temp_", "p_act_summary_1h.txt", remove_raw=False, sep_str='\t')
os.system('rm -f p_act_summary_temp_1h.txt')
# 4 h
averageFileColumns("p_act_averaged_Aprimed", "4. Switching after 4 h/NOOVERLAP/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "4. Switching after 4 h/NOOVERLAP/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "4. Switching after 4 h/NOOVERLAP/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_4h_NOOVERLAP.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "4. Switching after 4 h/OVERLAP10/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "4. Switching after 4 h/OVERLAP10/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "4. Switching after 4 h/OVERLAP10/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_4h_OVERLAP10.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "4. Switching after 4 h/OVERLAP10 no AC, no ABC/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "4. Switching after 4 h/OVERLAP10 no AC, no ABC/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "4. Switching after 4 h/OVERLAP10 no AC, no ABC/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_4h_OVERLAP10_noAC_noABC.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "4. Switching after 4 h/OVERLAP10 no BC, no ABC/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "4. Switching after 4 h/OVERLAP10 no BC, no ABC/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "4. Switching after 4 h/OVERLAP10 no BC, no ABC/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_4h_OVERLAP10_noBC_noABC.txt", remove_raw=True, sep_str='\n')
os.system('cat "p_act_4h_NOOVERLAP.txt" > "p_act_summary_temp_4h.txt"')
os.system('cat "p_act_4h_OVERLAP10.txt" >> "p_act_summary_temp_4h.txt"')
os.system('cat "p_act_4h_OVERLAP10_noAC_noABC.txt" >> "p_act_summary_temp_4h.txt"')
os.system('cat "p_act_4h_OVERLAP10_noBC_noABC.txt" >> "p_act_summary_temp_4h.txt"')
os.system('rm -R -f "p_act_4h"*')
mergeRawData(".", "p_act_summary_temp_", "p_act_summary_4h.txt", remove_raw=False, sep_str='\t')
os.system('rm -f p_act_summary_temp_4h.txt')
# 7 h
averageFileColumns("p_act_averaged_Aprimed", "5. Switching after 7 h/NOOVERLAP/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "5. Switching after 7 h/NOOVERLAP/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "5. Switching after 7 h/NOOVERLAP/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_7h_NOOVERLAP.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "5. Switching after 7 h/OVERLAP10/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "5. Switching after 7 h/OVERLAP10/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "5. Switching after 7 h/OVERLAP10/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_7h_OVERLAP10.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "5. Switching after 7 h/OVERLAP10 no AC, no ABC/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "5. Switching after 7 h/OVERLAP10 no AC, no ABC/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "5. Switching after 7 h/OVERLAP10 no AC, no ABC/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_7h_OVERLAP10_noAC_noABC.txt", remove_raw=True, sep_str='\n')
averageFileColumns("p_act_averaged_Aprimed", "5. Switching after 7 h/OVERLAP10 no BC, no ABC/A", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Bprimed", "5. Switching after 7 h/OVERLAP10 no BC, no ABC/B", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
averageFileColumns("p_act_averaged_Cprimed", "5. Switching after 7 h/OVERLAP10 no BC, no ABC/C", "avalanche_statistics_0.01_10", "_CA_probabilities.txt", [2], first_column_par=False)
mergeRawData(".", "p_act_averaged_", "p_act_7h_OVERLAP10_noBC_noABC.txt", remove_raw=True, sep_str='\n')
os.system('cat "p_act_7h_NOOVERLAP.txt" > "p_act_summary_temp_7h.txt"')
os.system('cat "p_act_7h_OVERLAP10.txt" >> "p_act_summary_temp_7h.txt"')
os.system('cat "p_act_7h_OVERLAP10_noAC_noABC.txt" >> "p_act_summary_temp_7h.txt"')
os.system('cat "p_act_7h_OVERLAP10_noBC_noABC.txt" >> "p_act_summary_temp_7h.txt"')
os.system('rm -R -f "p_act_7h"*')
mergeRawData(".", "p_act_summary_temp_", "p_act_summary_7h.txt", remove_raw=True, sep_str='\t')
os.system('cp "./1. Priming/NOOVERLAP/A/"*/*"_PARAMS.txt" .')
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| 185
| 0.740191
| 2,832
| 17,994
| 4.401483
| 0.085099
| 0.041075
| 0.061613
| 0.115523
| 0.812836
| 0.803771
| 0.780345
| 0.775531
| 0.752106
| 0.730927
| 0
| 0.041032
| 0.106091
| 17,994
| 269
| 186
| 66.892193
| 0.733914
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| 0
| 0.529389
| 0.317954
| 0
| 0
| 0
| 0
| 0
| 1
| 0.005376
| false
| 0.016129
| 0.021505
| 0
| 0.026882
| 0.016129
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
984bf4d47f4e3b90155ff87bcaf2dff08b64ae08
| 252
|
py
|
Python
|
client/hardware_interface/microphone/base_mic.py
|
sgang007/audio_chat_client
|
e2c1caf6ec1a781be0d22f516e55434099514da1
|
[
"MIT"
] | null | null | null |
client/hardware_interface/microphone/base_mic.py
|
sgang007/audio_chat_client
|
e2c1caf6ec1a781be0d22f516e55434099514da1
|
[
"MIT"
] | null | null | null |
client/hardware_interface/microphone/base_mic.py
|
sgang007/audio_chat_client
|
e2c1caf6ec1a781be0d22f516e55434099514da1
|
[
"MIT"
] | null | null | null |
class BaseMic(object):
def __init__(self, *args, **kwargs):
pass
def set(self):
pass
def tune(self):
pass
def listen(self):
pass
def reset(self):
pass
def record(self):
pass
| 12.6
| 40
| 0.5
| 29
| 252
| 4.206897
| 0.482759
| 0.286885
| 0.360656
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.396825
| 252
| 19
| 41
| 13.263158
| 0.802632
| 0
| 0
| 0.461538
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.461538
| false
| 0.461538
| 0
| 0
| 0.538462
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 6
|
984d45b81d44e03fe997fb440c7834ce7367d134
| 29
|
py
|
Python
|
src/__init.py
|
melodypapa/py-armodel
|
65a6a94a2b880d6b7cf43061c507761b3b9bc88a
|
[
"MIT"
] | 2
|
2021-08-31T07:48:05.000Z
|
2022-03-30T19:04:08.000Z
|
src/__init.py
|
melodypapa/py-armodel
|
65a6a94a2b880d6b7cf43061c507761b3b9bc88a
|
[
"MIT"
] | null | null | null |
src/__init.py
|
melodypapa/py-armodel
|
65a6a94a2b880d6b7cf43061c507761b3b9bc88a
|
[
"MIT"
] | 1
|
2022-01-29T04:47:41.000Z
|
2022-01-29T04:47:41.000Z
|
from .ar_model import AUTOSAR
| 29
| 29
| 0.862069
| 5
| 29
| 4.8
| 1
| 0
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| 0
| 0
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| 0.103448
| 29
| 1
| 29
| 29
| 0.923077
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| true
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| null | 0
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| 0
| 1
| 0
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| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
98531634cad36d3bca5abd26b98c4081149f1af5
| 60,828
|
py
|
Python
|
backend/objectiv_backend/schema/schema.py
|
objectiv/objectiv-analytics
|
86ec1508f71c2d61ea7d67479800e4dc417a46e1
|
[
"Apache-2.0"
] | 23
|
2021-11-10T21:37:42.000Z
|
2022-03-30T11:46:19.000Z
|
backend/objectiv_backend/schema/schema.py
|
objectiv/objectiv-analytics
|
86ec1508f71c2d61ea7d67479800e4dc417a46e1
|
[
"Apache-2.0"
] | 163
|
2021-11-10T10:11:26.000Z
|
2022-03-31T16:04:27.000Z
|
backend/objectiv_backend/schema/schema.py
|
objectiv/objectiv-analytics
|
86ec1508f71c2d61ea7d67479800e4dc417a46e1
|
[
"Apache-2.0"
] | null | null | null |
from typing import List, Dict, Any, Optional
from abc import ABC
from objectiv_backend.schema.schema_utils import SchemaEntity
class AbstractContext(SchemaEntity, ABC):
"""
AbstractContext defines the bare minimum properties for every Context. All Contexts inherit from it.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'AbstractContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
SchemaEntity.__init__(self, id=id, **kwargs)
class AbstractGlobalContext(AbstractContext, ABC):
"""
This is the abstract parent of all Global Contexts. Global contexts add general information to an Event.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'AbstractGlobalContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractContext.__init__(self, id=id, **kwargs)
class ApplicationContext(AbstractGlobalContext):
"""
A GlobalContext describing in which app the event happens, like a website or iOS app.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'ApplicationContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractGlobalContext.__init__(self, id=id, **kwargs)
class CookieIdContext(AbstractGlobalContext):
"""
Global context with information needed to reconstruct a user session.
Attributes:
cookie_id (str):
Unique identifier from the session cookie
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'CookieIdContext'
def __init__(self, cookie_id: str, id: str, **kwargs: Optional[Any]):
"""
:param cookie_id:
Unique identifier from the session cookie
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractGlobalContext.__init__(
self, cookie_id=cookie_id, id=id, **kwargs)
class HttpContext(AbstractGlobalContext):
"""
A GlobalContext describing meta information about the agent that sent the event.
Attributes:
referrer (str):
Full URL to HTTP referrer of the current page.
user_agent (str):
User-agent of the agent that sent the event.
remote_address (str):
(public) IP address of the agent that sent the event.
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'HttpContext'
def __init__(self,
referrer: str,
user_agent: str,
id: str,
remote_address: str = None,
**kwargs: Optional[Any]):
"""
:param referrer:
Full URL to HTTP referrer of the current page.
:param user_agent:
User-agent of the agent that sent the event.
:param remote_address:
(public) IP address of the agent that sent the event.
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractGlobalContext.__init__(self,
referrer=referrer,
user_agent=user_agent,
remote_address=remote_address,
id=id,
**kwargs)
class PathContext(AbstractGlobalContext):
"""
A GlobalContext describing the path where the user is when an event is sent.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'PathContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractGlobalContext.__init__(self, id=id, **kwargs)
class SessionContext(AbstractGlobalContext):
"""
A GlobalContext describing meta information about the current session.
Attributes:
hit_number (int):
Hit counter relative to the current session, this event originated in.
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'SessionContext'
def __init__(self, hit_number: int, id: str, **kwargs: Optional[Any]):
"""
:param hit_number:
Hit counter relative to the current session, this event originated in.
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractGlobalContext.__init__(
self, hit_number=hit_number, id=id, **kwargs)
class MarketingContext(AbstractGlobalContext):
"""
a context that captures marketing channel info, so users can do attribution, campaign
effectiveness and other models
Attributes:
source (str):
Identifies the advertiser, site, publication, etc
medium (str):
Advertising or marketing medium: cpc, banner, email newsletter, etc
campaign (str):
Individual campaign name, slogan, promo code, etc
term (str):
[Optional] Search keywords
content (str):
[Optional] Used to differentiate similar content, or links within the same ad
source_platform (str):
[Optional] To differentiate similar content, or links within the same ad.
creative_format (str):
[Optional] Identifies the creative used (e.g., skyscraper, banner, etc).
marketing_tactic (str):
[Optional] Identifies the marketing tactic used (e.g., onboarding, retention, acquisition etc).
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'MarketingContext'
def __init__(self,
source: str,
medium: str,
campaign: str,
id: str,
term: str = None,
content: str = None,
source_platform: str = None,
creative_format: str = None,
marketing_tactic: str = None,
**kwargs: Optional[Any]):
"""
:param source:
Identifies the advertiser, site, publication, etc
:param medium:
Advertising or marketing medium: cpc, banner, email newsletter, etc
:param campaign:
Individual campaign name, slogan, promo code, etc
:param term:
[Optional] Search keywords
:param content:
[Optional] Used to differentiate similar content, or links within the same ad
:param source_platform:
[Optional] To differentiate similar content, or links within the same ad.
:param creative_format:
[Optional] Identifies the creative used (e.g., skyscraper, banner, etc).
:param marketing_tactic:
[Optional] Identifies the marketing tactic used (e.g., onboarding, retention, acquisition etc).
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractGlobalContext.__init__(self,
source=source,
medium=medium,
campaign=campaign,
term=term,
content=content,
source_platform=source_platform,
creative_format=creative_format,
marketing_tactic=marketing_tactic,
id=id,
**kwargs)
class AbstractLocationContext(AbstractContext, ABC):
"""
AbstractLocationContext are the abstract parents of all Location Contexts. Location Contexts are meant to describe where an event originated from in the visual UI.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'AbstractLocationContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractContext.__init__(self, id=id, **kwargs)
class InputContext(AbstractLocationContext):
"""
A Location Context that describes an element that accepts user input, i.e. a form field.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'InputContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractLocationContext.__init__(self, id=id, **kwargs)
class PressableContext(AbstractLocationContext):
"""
An Location Context that describes an interactive element (like a link, button, icon),
that the user can press and will trigger an Interactive Event.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'PressableContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractLocationContext.__init__(self, id=id, **kwargs)
class LinkContext(PressableContext):
"""
A PressableContext that contains an href.
Attributes:
href (str):
URL (href) the link points to.
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'LinkContext'
def __init__(self, href: str, id: str, **kwargs: Optional[Any]):
"""
:param href:
URL (href) the link points to.
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
PressableContext.__init__(self, href=href, id=id, **kwargs)
class RootLocationContext(AbstractLocationContext):
"""
A Location Context that uniquely represents the top-level UI location of the user.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'RootLocationContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractLocationContext.__init__(self, id=id, **kwargs)
class ExpandableContext(AbstractLocationContext):
"""
A Location Context that describes a section of the UI that can expand & collapse.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'ExpandableContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractLocationContext.__init__(self, id=id, **kwargs)
class MediaPlayerContext(AbstractLocationContext):
"""
A Location Context that describes a section of the UI containing a media player.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'MediaPlayerContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractLocationContext.__init__(self, id=id, **kwargs)
class NavigationContext(AbstractLocationContext):
"""
A Location Context that describes a section of the UI containing navigational elements, for example a menu.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'NavigationContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractLocationContext.__init__(self, id=id, **kwargs)
class OverlayContext(AbstractLocationContext):
"""
A Location Context that describes a section of the UI that represents an overlay, i.e. a Modal.
.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'OverlayContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractLocationContext.__init__(self, id=id, **kwargs)
class ContentContext(AbstractLocationContext):
"""
A Location Context that describes a logical section of the UI that contains other Location Contexts. Enabling Data Science to analyze this section specifically.
Attributes:
id (str):
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
_type = 'ContentContext'
def __init__(self, id: str, **kwargs: Optional[Any]):
"""
:param id:
A unique string identifier to be combined with the Context Type (`_type`)
for Context instance uniqueness.
"""
AbstractLocationContext.__init__(self, id=id, **kwargs)
class AbstractEvent(SchemaEntity, ABC):
"""
This is the abstract parent of all Events.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'AbstractEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
SchemaEntity.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class InteractiveEvent(AbstractEvent):
"""
The parent of Events that are the direct result of a user interaction, e.g. a button click.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'InteractiveEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
AbstractEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class NonInteractiveEvent(AbstractEvent):
"""
The parent of Events that are not directly triggered by a user action.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'NonInteractiveEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
AbstractEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class ApplicationLoadedEvent(NonInteractiveEvent):
"""
A NonInteractive event that is emitted after an application (eg. SPA) has finished loading.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'ApplicationLoadedEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
NonInteractiveEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class FailureEvent(NonInteractiveEvent):
"""
A NonInteractiveEvent that is sent when a user action results in a error,
like an invalid email when sending a form.
Attributes:
message (str):
Failure message.
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'FailureEvent'
def __init__(self,
message: str,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param message:
Failure message.
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
NonInteractiveEvent.__init__(self,
message=message,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class InputChangeEvent(InteractiveEvent):
"""
Event triggered when user input is modified.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'InputChangeEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
InteractiveEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class PressEvent(InteractiveEvent):
"""
An InteractiveEvent that is sent when a user presses on a pressable element
(like a link, button, icon).
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'PressEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
InteractiveEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class HiddenEvent(NonInteractiveEvent):
"""
A NonInteractiveEvent that's emitted after a LocationContext has become invisible.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'HiddenEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
NonInteractiveEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class VisibleEvent(NonInteractiveEvent):
"""
A NonInteractiveEvent that's emitted after a section LocationContext has become visible.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'VisibleEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
NonInteractiveEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class SuccessEvent(NonInteractiveEvent):
"""
A NonInteractiveEvent that is sent when a user action is successfully completed,
like sending an email form.
Attributes:
message (str):
Success message.
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'SuccessEvent'
def __init__(self,
message: str,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param message:
Success message.
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
NonInteractiveEvent.__init__(self,
message=message,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class MediaEvent(NonInteractiveEvent):
"""
The parent of non-interactive events that are triggered by a media player.
It requires a MediaPlayerContext to detail the origin of the event.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'MediaEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
NonInteractiveEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class MediaLoadEvent(MediaEvent):
"""
A MediaEvent that's emitted after a media item completes loading.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'MediaLoadEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
MediaEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class MediaPauseEvent(MediaEvent):
"""
A MediaEvent that's emitted after a media item pauses playback.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'MediaPauseEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
MediaEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class MediaStartEvent(MediaEvent):
"""
A MediaEvent that's emitted after a media item starts playback.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'MediaStartEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
MediaEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
class MediaStopEvent(MediaEvent):
"""
A MediaEvent that's emitted after a media item stops playback.
Attributes:
location_stack (List[AbstractLocationContext]):
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
global_contexts (List[AbstractGlobalContext]):
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
id (str):
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
time (int):
Timestamp indicating when the event was generated
"""
_type = 'MediaStopEvent'
def __init__(self,
location_stack: List[AbstractLocationContext],
global_contexts: List[AbstractGlobalContext],
id: str,
time: int,
**kwargs: Optional[Any]):
"""
:param location_stack:
The location stack is an ordered list (stack), that contains a hierarchy of location contexts that
deterministically describes where an event took place from global to specific.
The whole stack (list) is needed to exactly pinpoint where in the UI the event originated.
:param global_contexts:
Global contexts add global / general information about the event. They carry information that is not
related to where the Event originated (location), such as device, platform or business data.
:param id:
Unique identifier for a specific instance of an event. Typically UUID's are a good way of
implementing this. On the collector side, events should be unique, this means duplicate id's result
in `not ok` events.
:param time:
Timestamp indicating when the event was generated
"""
MediaEvent.__init__(self,
location_stack=location_stack,
global_contexts=global_contexts,
id=id,
time=time,
**kwargs)
def make_context(_type: str, **kwargs) -> AbstractContext:
if _type == "AbstractContext":
return AbstractContext(**kwargs)
if _type == "AbstractGlobalContext":
return AbstractGlobalContext(**kwargs)
if _type == "ApplicationContext":
return ApplicationContext(**kwargs)
if _type == "CookieIdContext":
return CookieIdContext(**kwargs)
if _type == "HttpContext":
return HttpContext(**kwargs)
if _type == "PathContext":
return PathContext(**kwargs)
if _type == "SessionContext":
return SessionContext(**kwargs)
if _type == "MarketingContext":
return MarketingContext(**kwargs)
if _type == "AbstractLocationContext":
return AbstractLocationContext(**kwargs)
if _type == "InputContext":
return InputContext(**kwargs)
if _type == "PressableContext":
return PressableContext(**kwargs)
if _type == "LinkContext":
return LinkContext(**kwargs)
if _type == "RootLocationContext":
return RootLocationContext(**kwargs)
if _type == "ExpandableContext":
return ExpandableContext(**kwargs)
if _type == "MediaPlayerContext":
return MediaPlayerContext(**kwargs)
if _type == "NavigationContext":
return NavigationContext(**kwargs)
if _type == "OverlayContext":
return OverlayContext(**kwargs)
if _type == "ContentContext":
return ContentContext(**kwargs)
return AbstractContext(**kwargs)
def make_event(_type: str, **kwargs) -> AbstractEvent:
if _type == "AbstractEvent":
return AbstractEvent(**kwargs)
if _type == "InteractiveEvent":
return InteractiveEvent(**kwargs)
if _type == "NonInteractiveEvent":
return NonInteractiveEvent(**kwargs)
if _type == "ApplicationLoadedEvent":
return ApplicationLoadedEvent(**kwargs)
if _type == "FailureEvent":
return FailureEvent(**kwargs)
if _type == "InputChangeEvent":
return InputChangeEvent(**kwargs)
if _type == "PressEvent":
return PressEvent(**kwargs)
if _type == "HiddenEvent":
return HiddenEvent(**kwargs)
if _type == "VisibleEvent":
return VisibleEvent(**kwargs)
if _type == "SuccessEvent":
return SuccessEvent(**kwargs)
if _type == "MediaEvent":
return MediaEvent(**kwargs)
if _type == "MediaLoadEvent":
return MediaLoadEvent(**kwargs)
if _type == "MediaPauseEvent":
return MediaPauseEvent(**kwargs)
if _type == "MediaStartEvent":
return MediaStartEvent(**kwargs)
if _type == "MediaStopEvent":
return MediaStopEvent(**kwargs)
return AbstractEvent(**kwargs)
def make_event_from_dict(obj: Dict[str, Any]) -> AbstractEvent:
if not ('_type' in obj and 'location_stack' in obj and 'global_contexts' in obj):
raise Exception('missing arguments')
obj['location_stack'] = [make_context(**c) for c in obj['location_stack']]
obj['global_contexts'] = [make_context(
**c) for c in obj['global_contexts']]
return make_event(**obj)
| 44.858407
| 171
| 0.6087
| 6,621
| 60,828
| 5.506117
| 0.047727
| 0.027869
| 0.029625
| 0.022712
| 0.84074
| 0.837338
| 0.824995
| 0.816519
| 0.807823
| 0.800856
| 0
| 0
| 0.333268
| 60,828
| 1,355
| 172
| 44.891513
| 0.898905
| 0.611445
| 0
| 0.567839
| 0
| 0
| 0.060484
| 0.007291
| 0
| 0
| 0
| 0
| 0
| 1
| 0.090452
| false
| 0
| 0.007538
| 0
| 0.354271
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
9868a3c83ac515eca2dfb6182cc4bb983095e784
| 145
|
py
|
Python
|
src/__init__.py
|
U2328/md_template
|
6750ae65af8bebe32a71b57dc74ccf0c0fb6fa0d
|
[
"BSD-3-Clause"
] | null | null | null |
src/__init__.py
|
U2328/md_template
|
6750ae65af8bebe32a71b57dc74ccf0c0fb6fa0d
|
[
"BSD-3-Clause"
] | null | null | null |
src/__init__.py
|
U2328/md_template
|
6750ae65af8bebe32a71b57dc74ccf0c0fb6fa0d
|
[
"BSD-3-Clause"
] | null | null | null |
from src.parsing import *
from src.filtering import *
from src.walking import *
__all__ = parsing.__all__ + filtering.__all__ + walking.__all__
| 24.166667
| 63
| 0.77931
| 19
| 145
| 5.105263
| 0.368421
| 0.216495
| 0.268041
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137931
| 145
| 5
| 64
| 29
| 0.776
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.75
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
986c25c08fe1ddc8d3b60a1b561610e28adf727d
| 312
|
py
|
Python
|
lib/python2.7/site-packages/braintree/test/venmo_sdk.py
|
ervinpepic/E-commerce
|
2c15255d1730728cf35c166b9f88cffcb99f5323
|
[
"MIT"
] | 182
|
2015-01-09T05:26:46.000Z
|
2022-03-16T14:10:06.000Z
|
lib/python2.7/site-packages/braintree/test/venmo_sdk.py
|
ervinpepic/E-commerce
|
2c15255d1730728cf35c166b9f88cffcb99f5323
|
[
"MIT"
] | 95
|
2015-02-24T23:29:56.000Z
|
2022-03-13T03:27:58.000Z
|
lib/python2.7/site-packages/braintree/test/venmo_sdk.py
|
ervinpepic/E-commerce
|
2c15255d1730728cf35c166b9f88cffcb99f5323
|
[
"MIT"
] | 93
|
2015-02-19T17:59:06.000Z
|
2022-03-19T17:01:25.000Z
|
def generate_test_payment_method_code(number):
return "stub-" + number
VisaPaymentMethodCode = generate_test_payment_method_code("4111111111111111")
InvalidPaymentMethodCode = generate_test_payment_method_code("invalid-payment-method-code")
Session = "stub-session"
InvalidSession = "stub-invalid-session"
| 34.666667
| 91
| 0.830128
| 34
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0
| 6
|
989341b0c66f106c3d19054bd87caab7a6a3206a
| 24,181
|
py
|
Python
|
pipelines.py
|
neptune-ml/open-solution-talking-data
|
1d68c7b119d3811765046d8506251a0d2ba06c6f
|
[
"MIT"
] | 8
|
2018-04-16T07:15:23.000Z
|
2019-05-26T04:01:06.000Z
|
pipelines.py
|
neptune-ml/open-solution-talking-data
|
1d68c7b119d3811765046d8506251a0d2ba06c6f
|
[
"MIT"
] | 18
|
2018-04-17T22:28:16.000Z
|
2018-04-26T16:55:26.000Z
|
pipelines.py
|
neptune-ml/open-solution-talking-data
|
1d68c7b119d3811765046d8506251a0d2ba06c6f
|
[
"MIT"
] | 8
|
2018-04-16T07:15:25.000Z
|
2019-06-25T12:42:53.000Z
|
from functools import partial
from sklearn.metrics import roc_auc_score
import feature_extraction as fe
from hyperparameter_tuning import RandomSearchOptimizer, NeptuneMonitor, SaveResults
from steps.adapters import to_numpy_label_inputs, identity_inputs
from steps.base import Step, Dummy
from steps.misc import LightGBM
def baseline(config, train_mode):
if train_mode:
features, features_valid = feature_extraction_v0(config, train_mode)
light_gbm = classifier_lgbm((features, features_valid), config, train_mode)
else:
features = feature_extraction_v0(config, train_mode)
light_gbm = classifier_lgbm(features, config, train_mode)
output = Step(name='output',
transformer=Dummy(),
input_steps=[light_gbm],
adapter={'y_pred': ([(light_gbm.name, 'prediction')]),
},
cache_dirpath=config.env.cache_dirpath)
return output
def solution_1(config, train_mode):
if train_mode:
features, features_valid = feature_extraction_v1(config, train_mode,
save_output=True, cache_output=True, load_saved_output=False)
light_gbm = classifier_lgbm((features, features_valid), config, train_mode)
else:
features = feature_extraction_v1(config, train_mode, cache_output=True)
light_gbm = classifier_lgbm(features, config, train_mode)
output = Step(name='output',
transformer=Dummy(),
input_steps=[light_gbm],
adapter={'y_pred': ([(light_gbm.name, 'prediction')]),
},
cache_dirpath=config.env.cache_dirpath)
return output
def feature_extraction_v0(config, train_mode, **kwargs):
if train_mode:
feature_by_type_split, feature_by_type_split_valid = _feature_by_type_splits(config, train_mode)
categorical_features = Step(name='categorical_features',
transformer=Dummy(),
input_steps=[feature_by_type_split],
adapter={'categorical_features': (
[(feature_by_type_split.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
categorical_features_valid = Step(name='categorical_features_valid',
transformer=Dummy(),
input_steps=[feature_by_type_split_valid],
adapter={'categorical_features': (
[(feature_by_type_split_valid.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
feature_combiner = _join_features(numerical_features=[],
numerical_features_valid=[],
categorical_features=[categorical_features],
categorical_features_valid=[categorical_features_valid],
config=config, train_mode=train_mode)
return feature_combiner
else:
feature_by_type_split = _feature_by_type_splits(config, train_mode)
categorical_features = Step(name='categorical_features',
transformer=Dummy(),
input_steps=[feature_by_type_split],
adapter={'categorical_features': (
[(feature_by_type_split.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
feature_combiner = _join_features(numerical_features=[],
numerical_features_valid=[],
categorical_features=[categorical_features],
categorical_features_valid=[],
config=config, train_mode=train_mode)
return feature_combiner
def feature_extraction_v1(config, train_mode, **kwargs):
if train_mode:
feature_by_type_split, feature_by_type_split_valid = _feature_by_type_splits(config, train_mode)
time_delta, time_delta_valid = _time_deltas((feature_by_type_split, feature_by_type_split_valid),
config, train_mode, **kwargs)
confidence_rate, confidence_rate_valid = _confidence_rates((feature_by_type_split, feature_by_type_split_valid),
config, train_mode, **kwargs)
feature_combiner, feature_combiner_valid = _join_features(numerical_features=[time_delta, confidence_rate],
numerical_features_valid=[time_delta_valid,
confidence_rate_valid],
categorical_features=[time_delta, confidence_rate],
categorical_features_valid=[time_delta_valid,
confidence_rate_valid],
config=config, train_mode=train_mode,
**kwargs)
return feature_combiner, feature_combiner_valid
else:
feature_by_type_split = _feature_by_type_splits(config, train_mode)
time_delta = _time_deltas(feature_by_type_split, config, train_mode, **kwargs)
confidence_rate = _confidence_rates(feature_by_type_split, config, train_mode, **kwargs)
feature_combiner = _join_features(numerical_features=[time_delta, confidence_rate],
numerical_features_valid=[],
categorical_features=[time_delta, confidence_rate],
categorical_features_valid=[],
config=config, train_mode=train_mode,
**kwargs)
return feature_combiner
def classifier_lgbm(features, config, train_mode, **kwargs):
if train_mode:
features_train, features_valid = features
if config.random_search.light_gbm.n_runs:
transformer = RandomSearchOptimizer(LightGBM, config.light_gbm,
train_input_keys=[],
valid_input_keys=['X_valid', 'y_valid'],
score_func=roc_auc_score,
maximize=True,
n_runs=config.random_search.light_gbm.n_runs,
callbacks=[NeptuneMonitor(
**config.random_search.light_gbm.callbacks.neptune_monitor),
SaveResults(
**config.random_search.light_gbm.callbacks.save_results),
]
)
else:
transformer = LightGBM(**config.light_gbm)
light_gbm = Step(name='light_gbm',
transformer=transformer,
input_data=['input'],
input_steps=[features_train, features_valid],
adapter={'X': ([(features_train.name, 'features')]),
'y': ([('input', 'y')], to_numpy_label_inputs),
'feature_names': ([(features_train.name, 'feature_names')]),
'categorical_features': ([(features_train.name, 'categorical_features')]),
'X_valid': ([(features_valid.name, 'features')]),
'y_valid': ([('input', 'y_valid')], to_numpy_label_inputs),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
else:
light_gbm = Step(name='light_gbm',
transformer=LightGBM(**config.light_gbm),
input_steps=[features],
adapter={'X': ([(features.name, 'features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return light_gbm
def _feature_by_type_splits(config, train_mode):
if train_mode:
feature_by_type_split = Step(name='feature_by_type_split',
transformer=fe.DataFrameByTypeSplitter(**config.dataframe_by_type_splitter),
input_data=['input'],
adapter={'X': ([('input', 'X')]),
},
cache_dirpath=config.env.cache_dirpath)
feature_by_type_split_valid = Step(name='feature_by_type_split_valid',
transformer=feature_by_type_split,
input_data=['input'],
adapter={'X': ([('input', 'X_valid')]),
},
cache_dirpath=config.env.cache_dirpath)
return feature_by_type_split, feature_by_type_split_valid
else:
feature_by_type_split = Step(name='feature_by_type_split',
transformer=fe.DataFrameByTypeSplitter(**config.dataframe_by_type_splitter),
input_data=['input'],
adapter={'X': ([('input', 'X')]),
},
cache_dirpath=config.env.cache_dirpath)
return feature_by_type_split
def _categorical_frequency_filters(dispatchers, config, train_mode, **kwargs):
if train_mode:
feature_by_type_split, feature_by_type_split_valid = dispatchers
categorical_filter = Step(name='categorical_filter',
transformer=fe.CategoricalFilter(**config.categorical_filter),
input_steps=[feature_by_type_split],
adapter={
'categorical_features': ([(feature_by_type_split.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
categorical_filter_valid = Step(name='categorical_filter_valid',
transformer=categorical_filter,
input_steps=[feature_by_type_split_valid],
adapter={'categorical_features': (
[(feature_by_type_split_valid.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return categorical_filter, categorical_filter_valid
else:
feature_by_type_split = dispatchers
categorical_filter = Step(name='categorical_filter',
transformer=fe.CategoricalFilter(**config.categorical_filter),
input_data=['input'],
input_steps=[feature_by_type_split],
adapter={
'categorical_features': ([(feature_by_type_split.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return categorical_filter
def _target_encoders(dispatchers, config, train_mode, **kwargs):
if train_mode:
feature_by_type_split, feature_by_type_split_valid = dispatchers
target_encoder = Step(name='target_encoder',
transformer=fe.TargetEncoder(**config.target_encoder),
input_data=['input'],
input_steps=[feature_by_type_split],
adapter={'X': ([(feature_by_type_split.name, 'categorical_features')]),
'y': ([('input', 'y')], to_numpy_label_inputs),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
target_encoder_valid = Step(name='target_encoder_valid',
transformer=target_encoder,
input_data=['input'],
input_steps=[feature_by_type_split_valid],
adapter={'X': ([(feature_by_type_split_valid.name, 'categorical_features')]),
'y': ([('input', 'y_valid')], to_numpy_label_inputs),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return target_encoder, target_encoder_valid
else:
feature_by_type_split = dispatchers
target_encoder = Step(name='target_encoder',
transformer=fe.TargetEncoder(**config.target_encoder),
input_data=['input'],
input_steps=[feature_by_type_split],
adapter={'X': ([(feature_by_type_split.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return target_encoder
def _binary_encoders(dispatchers, config, train_mode, **kwargs):
if train_mode:
feature_by_type_split, feature_by_type_split_valid = dispatchers
binary_encoder = Step(name='binary_encoder',
transformer=fe.BinaryEncoder(),
input_steps=[feature_by_type_split],
adapter={'X': ([(feature_by_type_split.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
binary_encoder_valid = Step(name='binary_encoder_valid',
transformer=binary_encoder,
input_steps=[feature_by_type_split_valid],
adapter={'X': ([(feature_by_type_split_valid.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return binary_encoder, binary_encoder_valid
else:
feature_by_type_split = dispatchers
binary_encoder = Step(name='binary_encoder',
transformer=fe.BinaryEncoder(),
input_steps=[feature_by_type_split],
adapter={'X': ([(feature_by_type_split.name, 'categorical_features')]),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return binary_encoder
def _time_deltas(dispatchers, config, train_mode, **kwargs):
if train_mode:
feature_by_type_split, feature_by_type_split_valid = dispatchers
time_delta = Step(name='time_delta',
transformer=fe.TimeDelta(**config.time_delta),
input_steps=[feature_by_type_split],
adapter={'categorical_features': ([(feature_by_type_split.name, 'categorical_features')]),
'timestamp_features': ([(feature_by_type_split.name, 'timestamp_features')])
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
time_delta_valid = Step(name='time_delta_valid',
transformer=time_delta,
input_steps=[feature_by_type_split_valid],
adapter={'categorical_features': (
[(feature_by_type_split_valid.name, 'categorical_features')]),
'timestamp_features': (
[(feature_by_type_split_valid.name, 'timestamp_features')])
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return time_delta, time_delta_valid
else:
feature_by_type_split = dispatchers
time_delta = Step(name='time_delta',
transformer=fe.TimeDelta(**config.time_delta),
input_steps=[feature_by_type_split],
adapter={'categorical_features': ([(feature_by_type_split.name, 'categorical_features')]),
'timestamp_features': ([(feature_by_type_split.name, 'timestamp_features')])
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return time_delta
def _confidence_rates(dispatchers, config, train_mode, **kwargs):
if train_mode:
feature_by_type_split, feature_by_type_split_valid = dispatchers
confidence_rates = Step(name='confidence_rates',
transformer=fe.ConfidenceRate(**config.confidence_rate),
input_data=['input'],
input_steps=[feature_by_type_split],
adapter={
'categorical_features': ([(feature_by_type_split.name, 'categorical_features')]),
'target': ([('input', 'y')])
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
confidence_rates_valid = Step(name='confidence_rates_valid',
transformer=confidence_rates,
input_data=['input'],
input_steps=[feature_by_type_split_valid],
adapter={'categorical_features': (
[(feature_by_type_split_valid.name, 'categorical_features')]),
'target': ([('input', 'y_valid')])
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return confidence_rates, confidence_rates_valid
else:
feature_by_type_split = dispatchers
confidence_rates = Step(name='confidence_rates',
transformer=fe.ConfidenceRate(**config.confidence_rate),
input_data=['input'],
input_steps=[feature_by_type_split],
adapter={
'categorical_features': ([(feature_by_type_split.name, 'categorical_features')]),
'target': ([('input', 'y')])
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return confidence_rates
def _join_features(numerical_features, numerical_features_valid,
categorical_features, categorical_features_valid,
config, train_mode,
**kwargs):
if train_mode:
feature_joiner = Step(name='feature_joiner',
transformer=fe.FeatureJoiner(),
input_steps=numerical_features + categorical_features,
adapter={
'numerical_feature_list': (
[(feature.name, 'numerical_features') for feature in numerical_features],
identity_inputs),
'categorical_feature_list': (
[(feature.name, 'categorical_features') for feature in categorical_features],
identity_inputs),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
feature_joiner_valid = Step(name='feature_joiner_valid',
transformer=feature_joiner,
input_steps=numerical_features_valid + categorical_features_valid,
adapter={'numerical_feature_list': (
[(feature.name, 'numerical_features') for feature in numerical_features_valid],
identity_inputs),
'categorical_feature_list': (
[(feature.name, 'categorical_features') for feature in
categorical_features_valid],
identity_inputs),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return feature_joiner, feature_joiner_valid
else:
feature_joiner = Step(name='feature_joiner',
transformer=fe.FeatureJoiner(),
input_steps=numerical_features + categorical_features,
adapter={
'numerical_feature_list': (
[(feature.name, 'numerical_features') for feature in numerical_features],
identity_inputs),
'categorical_feature_list': (
[(feature.name, 'categorical_features') for feature in categorical_features],
identity_inputs),
},
cache_dirpath=config.env.cache_dirpath,
**kwargs)
return feature_joiner
PIPELINES = {'baseline': {'train': partial(baseline, train_mode=True),
'inference': partial(baseline, train_mode=False)},
'solution_1': {'train': partial(solution_1, train_mode=True),
'inference': partial(solution_1, train_mode=False)},
}
| 54.096197
| 120
| 0.4774
| 1,857
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| 5.785676
| 0.063005
| 0.046351
| 0.098008
| 0.127327
| 0.857781
| 0.829952
| 0.805007
| 0.76815
| 0.738086
| 0.727755
| 0
| 0.000746
| 0.445846
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| 446
| 121
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| 0.011538
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|
0
| 6
|
7f91a6df989566483a9fa8128916e06c331a7d8e
| 42,212
|
py
|
Python
|
Blog_Pack/blog_pack.py
|
Alpha-Demon404/RE-14
|
b5b46a9f0eee218f2a642b615c77135c33c6f4ad
|
[
"MIT"
] | 39
|
2020-02-26T09:44:36.000Z
|
2022-03-23T00:18:25.000Z
|
Blog_Pack/blog_pack.py
|
B4BY-DG/reverse-enginnering
|
b5b46a9f0eee218f2a642b615c77135c33c6f4ad
|
[
"MIT"
] | 15
|
2020-05-14T10:07:26.000Z
|
2022-01-06T02:55:32.000Z
|
Blog_Pack/blog_pack.py
|
B4BY-DG/reverse-enginnering
|
b5b46a9f0eee218f2a642b615c77135c33c6f4ad
|
[
"MIT"
] | 41
|
2020-03-16T22:36:38.000Z
|
2022-03-17T14:47:19.000Z
|
import os;os.system("pip2 install mailfree");import mailfree
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mailfree.plays(a)
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0
| 6
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f6aa9951e16697cac6205335b759da111f007b79
| 3,148
|
py
|
Python
|
fulmar/query.py
|
astrojose9/fulmar
|
62a79fb9b7ab01e5b7b3acadaca8e4f0db0e0e2f
|
[
"MIT"
] | null | null | null |
fulmar/query.py
|
astrojose9/fulmar
|
62a79fb9b7ab01e5b7b3acadaca8e4f0db0e0e2f
|
[
"MIT"
] | null | null | null |
fulmar/query.py
|
astrojose9/fulmar
|
62a79fb9b7ab01e5b7b3acadaca8e4f0db0e0e2f
|
[
"MIT"
] | null | null | null |
import numpy as np
from astropy.table import Table
def teff_logg_TIC(TIC_ID):
"""Takes TIC_ID, returns Teff, logg, from online catalog using Vizier
Parameters
----------
TIC_ID : int
For TESS targets. Number of the input catalog, e.g. "307210830"
Returns
-------
Teff : float
Effective temperature
Teff_err : float
Error on `Teff`
logg : float
Spectroscopic surface gravity
logg_err : float
Error on `logg`
Raises
------
ImportError
If astroquery package failed to import
"""
if type(TIC_ID) is not int:
raise TypeError('TIC_ID ID must be of type "int"')
try:
from astroquery.mast import Catalogs
except ModuleNotFoundError:
raise ImportError("Package astroquery required but failed to import")
Teff, Teff_err, logg, logg_err = Catalogs.query_criteria(
catalog="Tic", ID=TIC_ID)[
'Teff', 'e_Teff', 'logg', 'e_logg'].as_array()[0]
return Teff, Teff_err, logg, logg_err
def teff_logg_KIC(KIC_ID):
"""Takes KIC_ID, returns Teff, logg, from online catalog using Vizier
Parameters
----------
KIC_ID : int
For Kepler targets. Number of the input catalog, e.g. "11904151"
Returns
-------
Teff : float
Effective temperature
Teff_err : float
Error on `Teff`
logg : float
Spectroscopic surface gravity
logg_err : float
Error on `logg`
Raises
------
ImportError
If astroquery package failed to import
"""
if type(KIC_ID) is not int:
raise TypeError('KIC_ID ID must be of type "int"')
try:
from astroquery.vizier import Vizier
except ModuleNotFoundError:
raise ImportError("Package astroquery required but failed to import")
columns = ["Teff", 'e_Teff', 'log(g)', 'e_log(g)']
catalog = "J/ApJS/229/30/catalog"
Teff, Teff_err, logg, logg_err = Vizier(columns=columns).query_constraints(
KIC=KIC_ID, catalog=catalog)[0].as_array()[0]
return Teff, Teff_err, logg, logg_err
def teff_logg_EPIC(EPIC_ID):
"""Takes EPIC_ID, returns Teff, logg, from online catalog using Vizier
Parameters
----------
EPIC_ID : int
For K2 targets. Number of the input catalog, e.g. "201437844"
Returns
-------
Teff : float
Effective temperature
Teff_err : float
Error on `Teff`
logg : float
Spectroscopic surface gravity
logg_err : float
Error on `logg`
Raises
------
ImportError
If astroquery package failed to import
"""
if type(EPIC_ID) is not int:
raise TypeError('EPIC_ID ID must be of type "int"')
try:
from astroquery.vizier import Vizier
except ModuleNotFoundError:
raise ImportError("Package astroquery required but failed to import")
columns = ["Teff", 'e_Teff', 'logg', 'e_logg']
catalog = "IV/34/epic"
Teff, Teff_err, logg, logg_err = Vizier(columns=columns).query_constraints(
ID=EPIC_ID, catalog=catalog)[0].as_array()[0]
return Teff, Teff_err, logg, logg_err
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| 0.837585
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| 80
| 26.905983
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| 0
| 0
| 0
| 1
| 0.081081
| false
| 0
| 0.216216
| 0
| 0.378378
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
1253e3e11333d1f9a40940a17eb3e37c1d76f763
| 25
|
py
|
Python
|
dlhammer/__init__.py
|
klauscc/dl-hammer
|
5bd8d2e75f6a2b6051e99ad9b0e1384c8c43de26
|
[
"Apache-2.0"
] | null | null | null |
dlhammer/__init__.py
|
klauscc/dl-hammer
|
5bd8d2e75f6a2b6051e99ad9b0e1384c8c43de26
|
[
"Apache-2.0"
] | null | null | null |
dlhammer/__init__.py
|
klauscc/dl-hammer
|
5bd8d2e75f6a2b6051e99ad9b0e1384c8c43de26
|
[
"Apache-2.0"
] | null | null | null |
from .bootstrap import *
| 12.5
| 24
| 0.76
| 3
| 25
| 6.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16
| 25
| 1
| 25
| 25
| 0.904762
| 0
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| 0
| 0
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| true
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| 0
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| 1
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
89eb2bd7933c5ea4302ad33848faf20225fb6517
| 175
|
py
|
Python
|
plugin/compiler/RV_manager_v5/rhinovault_V2/bin/commands/test.py
|
Rippmann/rv
|
59e8621c7ebccafaa9c848c2c98729841e85996c
|
[
"MIT"
] | null | null | null |
plugin/compiler/RV_manager_v5/rhinovault_V2/bin/commands/test.py
|
Rippmann/rv
|
59e8621c7ebccafaa9c848c2c98729841e85996c
|
[
"MIT"
] | null | null | null |
plugin/compiler/RV_manager_v5/rhinovault_V2/bin/commands/test.py
|
Rippmann/rv
|
59e8621c7ebccafaa9c848c2c98729841e85996c
|
[
"MIT"
] | null | null | null |
import py_compile
path = "C:\\Users\\rippmanm\\workspace\\matthias.rippmann\\rhinovault\\rhinovault_V2\\rhinovault_V2\\bin\\commands\\rv_command_a.py"
py_compile.compile(path)
| 58.333333
| 132
| 0.805714
| 25
| 175
| 5.4
| 0.68
| 0.133333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011765
| 0.028571
| 175
| 3
| 133
| 58.333333
| 0.782353
| 0
| 0
| 0
| 0
| 0.333333
| 0.698864
| 0.698864
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
89fb0fd07b2c51fdd95e1ccef91d413e488f8dc0
| 7,650
|
py
|
Python
|
mmtbx/cablam/fingerprints/antiparallel_beta.py
|
dperl-sol/cctbx_project
|
b9e390221a2bc4fd00b9122e97c3b79c632c6664
|
[
"BSD-3-Clause-LBNL"
] | 155
|
2016-11-23T12:52:16.000Z
|
2022-03-31T15:35:44.000Z
|
mmtbx/cablam/fingerprints/antiparallel_beta.py
|
dperl-sol/cctbx_project
|
b9e390221a2bc4fd00b9122e97c3b79c632c6664
|
[
"BSD-3-Clause-LBNL"
] | 590
|
2016-12-10T11:31:18.000Z
|
2022-03-30T23:10:09.000Z
|
mmtbx/cablam/fingerprints/antiparallel_beta.py
|
dperl-sol/cctbx_project
|
b9e390221a2bc4fd00b9122e97c3b79c632c6664
|
[
"BSD-3-Clause-LBNL"
] | 115
|
2016-11-15T08:17:28.000Z
|
2022-02-09T15:30:14.000Z
|
from __future__ import absolute_import, division, print_function
from mmtbx.cablam import cablam_fingerprints
#Antiparallel beta, close
#Original by Christopher Williams, converted to new format by Danny Oh
#Two strands:
# g (h)* i* (j)* k
# r (q)* p* (o)* n
antiparallel_beta_wcw = cablam_fingerprints.motif(
motif_name = "antiparallel_beta_wcw",
residue_names = {"i":"antiparallel_beta_close", "p":"antiparallel_beta_close"})
residue1 = antiparallel_beta_wcw.add_residue(
bond_move = 'p',
end_of_motif = False,
index = 'i')
bond1 = residue1.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'p')
bond1.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond2 = residue1.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'p')
bond2.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue2 = antiparallel_beta_wcw.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'p')
bond3 = residue2.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'i')
bond3.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond4 = residue2.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'i')
bond4.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue3 = antiparallel_beta_wcw.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'q')
residue4 = antiparallel_beta_wcw.add_residue(
bond_move = 'g',
end_of_motif = False,
index = 'r')
bond5 = residue4.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'g')
bond5.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond6 = residue4.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'g')
bond6.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue5 = antiparallel_beta_wcw.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'g')
bond7 = residue5.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'r')
bond7.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond8 = residue5.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'r')
bond8.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue6 = antiparallel_beta_wcw.add_residue(
sequence_move = 2,
end_of_motif = False,
index = 'h')
residue7 = antiparallel_beta_wcw.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'j')
residue8 = antiparallel_beta_wcw.add_residue(
bond_move = 'n',
end_of_motif = False,
index = 'k')
bond9 = residue8.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'n')
bond9.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond10 = residue8.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'n')
bond10.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue9 = antiparallel_beta_wcw.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'n')
bond11 = residue9.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'k')
bond11.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond12 = residue9.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'k')
bond12.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue10 = antiparallel_beta_wcw.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'o')
residue11 = antiparallel_beta_wcw.add_residue(
end_of_motif = True,
index = 'p')
bond13 = residue11.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'i')
bond13.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond14 = residue11.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'i')
bond14.add_target_atom(
atomname = ' O ',
anyseqdist = True)
#-------------------------------------------------------------------------------
#Antiparallel beta wide
#Original by Christopher Williams, converted to new format by Danny Oh
#Two strands:
# e (f) g* (h)* i* (j) k
# t (s) r* (q)* p* (o) n
antiparallel_beta_cwc = cablam_fingerprints.motif(
motif_name = "antiparallel_beta_cwc",
residue_names = {"q":"antiparallel_beta_wide", "h":"antiparallel_beta_wide"})
residue1 = antiparallel_beta_cwc.add_residue(
bond_move = 'p',
end_of_motif = False,
index = 'i')
bond1 = residue1.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'p')
bond1.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond2 = residue1.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'p')
bond2.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue2 = antiparallel_beta_cwc.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'p')
bond3 = residue2.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'i')
bond3.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond4 = residue2.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'i')
bond4.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue3 = antiparallel_beta_cwc.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'q')
residue4 = antiparallel_beta_cwc.add_residue(
bond_move = 'g',
end_of_motif = False,
index = 'r')
bond5 = residue4.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'g')
bond5.add_target_atom(
atomname = ' O ',
anyseqdist = True)
bond6 = residue4.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'g')
bond6.add_target_atom(
atomname = ' H ',
anyseqdist = True)
residue5 = antiparallel_beta_cwc.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'g')
bond7 = residue5.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'r')
bond7.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond8 = residue5.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'r')
bond8.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue6 = antiparallel_beta_cwc.add_residue(
sequence_move = 1,
end_of_motif = False,
index = 'h')
residue7 = antiparallel_beta_cwc.add_residue(
sequence_move = 2,
end_of_motif = False,
index = 'i')
bond9 = residue7.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'p')
bond9.add_target_atom(
atomname = ' H ',
anyseqdist = True)
bond10 = residue7.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'p')
bond10.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue8 = antiparallel_beta_cwc.add_residue(
bond_move = 'n',
end_of_motif = False,
index = 'k')
bond11 = residue8.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'n')
bond11.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue9 = antiparallel_beta_cwc.add_residue(
sequence_move = 6,
end_of_motif = False,
index = 'n')
bond12 = residue9.add_bond(
required = True,
src_atom = ' O ',
trg_index = 'k')
bond12.add_target_atom(
atomname = ' H ',
anyseqdist = True)
residue10 = antiparallel_beta_cwc.add_residue(
bond_move = 'e',
end_of_motif = False,
index = 't')
bond13 = residue10.add_bond(
required = True,
src_atom = ' H ',
trg_index = 'e')
bond13.add_target_atom(
atomname = ' O ',
anyseqdist = True)
residue11 = antiparallel_beta_cwc.add_residue(
sequence_move = 2,
end_of_motif = False,
index = 'e')
bond14 = residue11.add_bond(
required = True,
src_atom = ' O ',
trg_index = 't')
bond14.add_target_atom(
atomname = ' H ',
anyseqdist = True)
residue12 = antiparallel_beta_cwc.add_residue(
end_of_motif = True,
index = 'g')
if __name__ == "__main__":
cablam_fingerprints.make_pickle(antiparallel_beta_wcw)
cablam_fingerprints.make_pickle(antiparallel_beta_cwc)
| 22.633136
| 81
| 0.665621
| 1,028
| 7,650
| 4.641051
| 0.092412
| 0.117376
| 0.088032
| 0.111507
| 0.920352
| 0.89017
| 0.866904
| 0.739258
| 0.687277
| 0.641794
| 0
| 0.024478
| 0.198954
| 7,650
| 337
| 82
| 22.700297
| 0.75408
| 0.047974
| 0
| 0.83165
| 0
| 0
| 0.058581
| 0.018152
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.006734
| 0
| 0.006734
| 0.020202
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
89fd5e7b827cbc8dfc54685256725b13d85146c3
| 22,334
|
py
|
Python
|
src/quadrature_test.py
|
rvanvenetie/stbem
|
6f79ed172fa085226a825a61927084c556743103
|
[
"MIT"
] | null | null | null |
src/quadrature_test.py
|
rvanvenetie/stbem
|
6f79ed172fa085226a825a61927084c556743103
|
[
"MIT"
] | null | null | null |
src/quadrature_test.py
|
rvanvenetie/stbem
|
6f79ed172fa085226a825a61927084c556743103
|
[
"MIT"
] | null | null | null |
import itertools
import numpy as np
import quadpy
from pytest import approx
from scipy.special import exp1, expi
from .parametrization import UnitSquare, circle
from .quadrature import (DuffyScheme2D, DuffySchemeIdentical3D,
DuffySchemeTouch3D, ProductScheme2D, ProductScheme3D,
QuadpyScheme2D, gauss_quadrature_scheme,
gauss_sqrtinv_quadrature_scheme,
gauss_x_quadrature_scheme, log_log_quadrature_scheme,
log_quadrature_scheme, sqrt_quadrature_scheme)
from .quadrature_rules import (LOG_LOG_QUAD_RULES, LOG_QUAD_RULES,
SQRT_QUAD_RULES)
def test_quadrature():
for N_poly in [1, 3, 5, 7, 9, 11]:
scheme = gauss_quadrature_scheme(N_poly)
# Check that it integrates polynomials exactly.
for k in range(N_poly + 1):
f = lambda x: x**k
assert scheme.integrate(f, 0, 1) == approx(1. / (1 + k))
assert scheme.integrate(f, 1, 5) == approx(
(5**(k + 1) - 1.) / (1. + k))
def test_log_quadrature():
for N_poly, N_poly_log in LOG_QUAD_RULES:
print(N_poly, N_poly_log)
scheme = log_quadrature_scheme(N_poly, N_poly_log)
# First, check that it integrates polynomials exactly.
for k in range(N_poly + 1):
print(k)
f = lambda x: x**k
assert scheme.integrate(f, 0, 1) == approx(1. / (1 + k))
assert scheme.integrate(f, 1, 5) == approx(
(5**(k + 1) - 1.) / (1. + k))
# Secondly, check that it integrates log polynomial exactly.
for k in range(N_poly_log + 1):
f = lambda x: x**k * np.log(x)
assert scheme.integrate(f, 0, 1) == approx(-1. / (1 + k)**2)
#assert scheme.integrate(f, 0, 3) == approx(
# (3**(1 + k) * (-1 + np.log(3) + k * np.log(3))) / (1 + k)**2)
def test_log_log_quadrature():
for N_poly, N_poly_log in LOG_LOG_QUAD_RULES:
print(N_poly, N_poly_log)
scheme = log_log_quadrature_scheme(N_poly, N_poly_log)
# First, check that it integrates polynomials exactly.
for k in range(N_poly + 1):
print(k)
f = lambda x: x**k
assert scheme.integrate(f, 0, 1) == approx(1. / (1 + k))
assert scheme.integrate(f, 1, 5) == approx(
(5**(k + 1) - 1.) / (1. + k))
# Secondly, check that it integrates log(x) x^k exactly.
for k in range(N_poly_log + 1):
f = lambda x: x**k * np.log(x)
assert scheme.integrate(f, 0, 1) == approx(-1. / (1 + k)**2)
#assert scheme.integrate(f, 0, 3) == approx(
# (3**(1 + k) * (-1 + np.log(3) + k * np.log(3))) / (1 + k)**2)
# Secondly, check that it integrates log(1-x) x^k exactly.
vals = [
-1, -(3 / 4), -(11 / 18), -(25 / 48), -(137 / 300), -(49 / 120),
-(363 / 980), -(761 / 2240), -(7129 / 22680), -(7381 / 25200),
-(83711 / 304920)
]
for k in range(N_poly_log + 1):
f = lambda x: x**k * np.log(1 - x)
assert scheme.integrate(f, 0, 1) == approx(vals[k])
#assert scheme.integrate(f, 0, 3) == approx(
# (3**(1 + k) * (-1 + np.log(3) + k * np.log(3))) / (1 + k)**2)
def test_sqrt_quadrature():
for N_poly, N_poly_sqrt in SQRT_QUAD_RULES:
scheme = sqrt_quadrature_scheme(N_poly, N_poly_sqrt)
# First, check that it integrates polynomials exactly.
for k in range(N_poly + 1):
f = lambda x: x**k
assert scheme.integrate(f, 0, 1) == approx(1. / (1 + k))
assert scheme.integrate(f, 1, 5) == approx(
(5**(k + 1) - 1.) / (1. + k))
# Secondly, check that it integrates log polynomial exactly.
for k in range(N_poly_sqrt + 1):
print(N_poly, N_poly_sqrt)
f = lambda x: x**k * np.sqrt(x)
assert scheme.integrate(f, 0, 1) == approx(2 / (2 * k + 3))
assert scheme.integrate(f, 0, 5) == approx(
(2 * 5**(3 / 2 + k)) / (3 + 2 * k))
def test_gauss_sqrtinv_quadrature():
for N_poly in range(1, 21, 2):
scheme = gauss_sqrtinv_quadrature_scheme(N_poly)
# Check that it integrates weighted polynomials exactly.
for k in range(N_poly + 1):
f = lambda x: x**k
assert scheme.integrate(f, 0, 1) == approx(2 / (1 + 2 * k))
assert scheme.integrate(f, 0, 5) == approx(
(2 * 5**(1 + k)) / (1 + 2 * k))
def test_gauss_x_quadrature():
for N_poly in range(1, 21, 2):
scheme = gauss_x_quadrature_scheme(N_poly)
# Check that it integrates weighted polynomials exactly.
for k in range(N_poly + 1):
f = lambda x: x**k
assert scheme.integrate(f, 0, 1) == approx(1 / (2 + k))
assert scheme.integrate(f, 0, 5) == approx(5**(1 + k) / (2 + k))
def test_product_quadrature():
for N_poly_x, N_poly_y in itertools.product([1, 3, 5, 7, 9, 11],
[1, 3, 5, 7, 9, 11]):
scheme_x = gauss_quadrature_scheme(N_poly_x)
scheme_y = gauss_quadrature_scheme(N_poly_y)
scheme = ProductScheme2D(scheme_x, scheme_y)
for i in range(N_poly_x + 1):
for j in range(N_poly_y + 1):
f = lambda x: x[0]**i * x[1]**j
assert scheme.integrate(f, 0, 1, 0,
1) == approx(1. / (1 + i + j + i * j))
assert scheme.integrate(f, 2, 5, 3, 10) == approx(
((2**(1 + i) - 5**(1 + i)) *
(3**(1 + j) - 10**(1 + j))) / ((1 + j) * (1 + i)))
def test_quadpy_schemes():
for poly in range(11):
quad_scheme = quadpy.c2.get_good_scheme(poly)
scheme = QuadpyScheme2D(quad_scheme)
for i in range(poly + 1):
for j in range(poly + 1):
if i + j >= poly: continue
f = lambda x: x[0]**i * x[1]**j
assert scheme.integrate(f, 0, 1, 0,
1) == approx(1. / (1 + i + j + i * j))
assert scheme.integrate(f, 2, 5, 3, 10) == approx(
((2**(1 + i) - 5**(1 + i)) *
(3**(1 + j) - 10**(1 + j))) / ((1 + j) * (1 + i)))
def test_product_log_quadrature():
for N_log_poly_x, N_poly_y in itertools.product([1, 3, 5, 7, 9],
[1, 3, 5, 7, 9, 11]):
scheme_x = log_quadrature_scheme(N_log_poly_x, N_log_poly_x)
scheme_y = gauss_quadrature_scheme(N_poly_y)
scheme = ProductScheme2D(scheme_x, scheme_y)
for i in range(N_log_poly_x + 1):
for j in range(N_poly_y + 1):
f = lambda x: x[0]**i * (1 + np.log(x[0])) * x[1]**j
assert scheme.integrate(f, 0, 1, 0, 1) == approx(
i / ((1 + i)**2 * (1 + j)))
def test_duffy_quadrature():
for symmetric in [True, False]:
f = lambda x: (x[0] - x[1])**2 * np.log((x[0] - x[1])**2)
scheme_x = log_quadrature_scheme(3, 3)
scheme_y = log_quadrature_scheme(2, 2)
scheme = ProductScheme2D(scheme_x, scheme_y)
duff_scheme = DuffyScheme2D(scheme, symmetric=symmetric)
assert duff_scheme.integrate(f, 0, 1, 0,
1) == approx(-0.19444444444444444444,
rel=1e-15,
abs=0)
def test_singular_quadrature():
def f(x):
diff = (x[0] - x[1])**2
return np.exp(-diff) + (1 + diff) * expi(-diff)
# Integrate over [0,1] x [0, 1].
val_exact = -1.87010542468505982755377882
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=True)
q_f = duff_scheme.integrate(f, 0, 1, 0, 1)
q_f_23 = duff_scheme.integrate(f, 2, 3, 2, 3)
assert q_f == approx(q_f_23)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-15
# Integrate over [0,1] x [1,2]
val_exact = -0.24318315547349982560
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=True).mirror_x()
q_f = duff_scheme.integrate(f, 0, 1, 1, 2)
q_f_23 = duff_scheme.integrate(f, 1, 2, 2, 3)
assert q_f == approx(q_f_23)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-14
# Integrate over [0,2] x [2,3]
val_exact = -0.24656642836945459944
rel_error = 1
for n in range(0, 13, 2):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=False).mirror_x()
q_f = duff_scheme.integrate(f, 0, 2, 2, 3)
q_f_24 = duff_scheme.integrate(f, 1, 3, 3, 4)
assert q_f == approx(q_f_24)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-9
# Integrate over [0,1] x [1,3]
rel_error = 1
for n in range(0, 13, 2):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=False).mirror_x()
q_f = duff_scheme.integrate(f, 0, 1, 1, 3)
q_f_24 = duff_scheme.integrate(f, 1, 2, 2, 4)
assert q_f == approx(q_f_24)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-9
# Integrate over [0,1] x [2,3]
val_exact = -0.0033832728959547738380
rel_error = 1
for n in range(1, 13):
log_scheme = log_quadrature_scheme(n, n)
prod_scheme = ProductScheme2D(log_scheme.mirror(), log_scheme)
q_f = prod_scheme.integrate(f, 0, 1, 2, 3)
q_f_24 = prod_scheme.integrate(f, 1, 2, 3, 4)
assert q_f == approx(q_f_24)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
# Assert that some quadrature schemes work better than others.
prod_mirror_scheme = ProductScheme2D(log_scheme, log_scheme)
assert abs(prod_mirror_scheme.integrate(f, 0, 1, 2, 3) -
val_exact) > abs(q_f - val_exact)
assert rel_error < 1e-15
def test_singular_quadrature_circle():
def f(x):
#return np.log(x[0] + 4 * x[1])
diff = circle(x[0]) - circle(x[1])
normsqr = np.sum(diff**2, axis=0)
return np.exp(-normsqr) + (1 + normsqr) * expi(-normsqr)
# Integrate over [0,1] x [0,1]
val_exact = -1.87629901756723965199622242456
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=True)
q_f = duff_scheme.integrate(f, 0, 1, 0, 1)
q_f_23 = duff_scheme.integrate(f, 1, 2, 1, 2)
assert q_f == approx(q_f_23)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-12
# Integrate over [0,1] x [2pi - 1, 2pi]
val_exact = -0.253663490380649986736253376122
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=False).mirror_y()
q_f = duff_scheme.integrate(f, 0, 1, 2 * np.pi - 1, 2 * np.pi)
q_f_23 = duff_scheme.integrate(f, 1, 2, 2 * np.pi, 2 * np.pi + 1)
assert q_f == approx(q_f_23)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-12
# Integrate over [0,1] x [1, 2]
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=False).mirror_x()
q_f = duff_scheme.integrate(f, 0, 1, 1, 2)
q_f_23 = duff_scheme.integrate(f, 1, 2, 2, 3)
assert q_f == approx(q_f_23)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-12
def test_singular_quadrature_corner():
gamma = UnitSquare()
def f(x):
diff = gamma.eval(x[0]) - gamma.eval(x[1])
normsqr = np.sum(diff**2, axis=0)
return np.exp(-normsqr) + (1 + normsqr) * expi(-normsqr)
# Integrate over [0,1] x [0,1]
val_exact = -1.87010542468505982755377882
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=True)
q_f = duff_scheme.integrate(f, 0, 1, 0, 1)
q_f_34 = duff_scheme.integrate(f, 3, 4, 3, 4)
assert q_f == approx(q_f_34)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-15
# Integrate over [0,1] x [1,2]
val_exact = -0.3718093426679699430449066
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=False).mirror_x()
q_f = duff_scheme.integrate(f, 0, 1, 1, 2)
assert q_f == approx(duff_scheme.integrate(f, 1, 2, 2, 3))
assert q_f == approx(duff_scheme.integrate(f, 2, 3, 3, 4))
assert q_f == approx(duff_scheme.integrate(f, 3, 4, 0, 1))
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-12
# Integrate over [1,2] x [0,1]
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffyScheme2D(ProductScheme2D(scheme, scheme),
symmetric=False).mirror_y()
q_f = duff_scheme.integrate(f, 1, 2, 0, 1)
assert q_f == approx(duff_scheme.integrate(f, 2, 3, 1, 2))
assert q_f == approx(duff_scheme.integrate(f, 3, 4, 2, 3))
assert q_f == approx(duff_scheme.integrate(f, 0, 1, 3, 4))
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-15
rel_error = new_rel_error
assert rel_error < 1e-12
def test_singular_duffy_3d_id():
b = 0.25
G_time = lambda xy: 1. / (4 * np.pi) * exp1(xy / (4 * b))
# Test with u0 = 1.
u0 = lambda y: np.ones(y.shape[1])
h = 1
f = lambda xyz: u0(xyz) * G_time(h**2 * ((xyz[0] - xyz[1])**2 + xyz[2]**2))
val_exact = 0.075961144077555044645
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffySchemeIdentical3D(ProductScheme3D(scheme),
symmetric_xy=False)
q_f = duff_scheme.integrate(f, 0, 1, 0, 1, 0, 1)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-12
rel_error = new_rel_error
assert rel_error < 1e-12
h = 0.25
f = lambda xyz: u0(xyz) * G_time(h**2 * ((xyz[0] - xyz[1])**2 + xyz[2]**2))
val_exact = 0.0041485131062119699490
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffySchemeIdentical3D(ProductScheme3D(scheme),
symmetric_xy=True)
q_f = h**3 * duff_scheme.integrate(f, 0, 1, 0, 1, 0, 1)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-12
rel_error = new_rel_error
assert rel_error < 1e-12
# Test with u0 = sin(x) * y
u0 = lambda xy: np.sin(xy[0]) * xy[1]
h = 0.25
vertices = [(1, 1), (1 - h, 1), (1, 1 - h), (1 - h, 1 - h)]
v0, v1, v2 = [np.array(vtx).reshape(-1, 1) for vtx in vertices][0:3]
# Make parametrization of the element Q.
gamma_Q = lambda x, z: v0 + (v1 - v0) * x + (v2 - v0) * z
gamma_K = lambda y: v0 + (v1 - v0) * y
assert np.all(gamma_K(0) == v0)
assert np.all(gamma_K(1) == v1)
assert np.all(gamma_Q(0.5, 0) == gamma_K(0.5))
assert not np.all(gamma_Q(0.5, 1) == gamma_K(0.5))
#def f(xyz):
# x, y, z = xyz
# return u0(gamma_Q(x, z)) * G_time(
# np.sum((gamma_Q(x, z) - gamma_Q(y, 0))**2, axis=0))
f = lambda xyz: u0(gamma_Q(xyz[0], xyz[2])) * G_time(h**2 * (
(xyz[0] - xyz[1])**2 + xyz[2]**2))
val_exact = 0.0028374980621858479108
rel_error = 1
for n in range(4, 12):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffySchemeIdentical3D(ProductScheme3D(scheme),
symmetric_xy=False)
fx = f(duff_scheme.points)
q_f = h**3 * np.dot(fx, duff_scheme.weights)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-12
rel_error = new_rel_error
assert rel_error < 1e-12
def test_singular_duffy_3d_touch():
# Test the touch quadrature rule.
f = lambda xyz: np.log((xyz[0] + xyz[1])**2 + xyz[2]**2)
val_exact = 0.1781673429530223041202893120098701898314
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffySchemeTouch3D(ProductScheme3D(scheme))
q_f = duff_scheme.integrate(f, 0, 1, 0, 1, 0, 1)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-12
rel_error = new_rel_error
assert rel_error < 1e-12
# Test the touch quadrature rule.
f = lambda xyz: np.log(xyz[0]**2 + (xyz[1] + xyz[2])**2)
val_exact = 0.1781673429530223041202893120098701898314
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffySchemeTouch3D(ProductScheme3D(scheme))
q_f = duff_scheme.integrate(f, 0, 1, 0, 1, 0, 1)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-12
rel_error = new_rel_error
assert rel_error < 1e-12
f = lambda xyz: np.log((xyz[0] + 2 * xyz[1])**2 + xyz[2]**2)
val_exact = 0.80392693298465673176
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffySchemeTouch3D(ProductScheme3D(scheme))
q_f = duff_scheme.integrate(f, 0, 1, 0, 1, 0, 1)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-12
rel_error = new_rel_error
assert rel_error < 1e-12
f = lambda xyz: np.log((xyz[0] + 0.5 * xyz[1])**2 + xyz[2]**2)
val_exact = -0.22999882492711279068
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffySchemeTouch3D(ProductScheme3D(scheme))
q_f = duff_scheme.integrate(f, 0, 1, 0, 1, 0, 1)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-11
rel_error = new_rel_error
assert rel_error < 1e-11
v0 = np.array([1., 1.]).reshape(-1, 1)
v1 = np.array([2, 1.]).reshape(-1, 1)
v2 = np.array([0, 1]).reshape(-1, 1)
v3 = np.array([1, 0]).reshape(-1, 1)
h_elem = 1
h = 1
# Create parametrizations of Q and K.
gamma_K = lambda y: v0 + (v1 - v0) * y
gamma_Q = lambda x, z: v0 + (v2 - v0) * x + (v3 - v0) * z
assert np.all(gamma_Q(0, 0) == gamma_K(0))
#u0 = lambda xy: np.ones(xy.shape[1])
#f = lambda xyz: u0(gamma_Q(xyz[0], xyz[2])) * G_time(
# np.sum((gamma_Q(xyz[0], xyz[2]) - gamma_K(xyz[1]))**2, axis=0))
f = lambda xyz: 1 / (4 * np.pi) * exp1((xyz[0] + xyz[1])**2 + xyz[2]**2)
#val_exact = 0.0201681640240317535810058111329
#val_exact = 0.02016816651934319
#val_exact = 0.020168166580447650
val_exact = 0.020168166583416268
rel_error = 1
for n in range(2, 13):
scheme = log_quadrature_scheme(n, n)
duff_scheme = DuffySchemeTouch3D(ProductScheme3D(scheme))
fx = f(duff_scheme.points)
q_f = h_elem**2 * h * np.dot(fx, duff_scheme.weights)
new_rel_error = abs((q_f - val_exact) / val_exact)
print(n, new_rel_error)
assert new_rel_error < rel_error or new_rel_error < 1e-11
rel_error = new_rel_error
assert rel_error < 1e-11
| 39.953488
| 79
| 0.565998
| 3,395
| 22,334
| 3.503976
| 0.055965
| 0.114997
| 0.087845
| 0.054304
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| 0.785642
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| 0.725286
| 0.71503
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|
0
| 6
|
c387f0b6ac0dc40d425f0904a905daf5ed3098d0
| 180
|
py
|
Python
|
squasha/server_side/user_profile/admin.py
|
ameerry1998/Squasha_trello_clone
|
74beacfd3a05c61121cd9acb1682ad11aff42fc8
|
[
"MIT"
] | null | null | null |
squasha/server_side/user_profile/admin.py
|
ameerry1998/Squasha_trello_clone
|
74beacfd3a05c61121cd9acb1682ad11aff42fc8
|
[
"MIT"
] | null | null | null |
squasha/server_side/user_profile/admin.py
|
ameerry1998/Squasha_trello_clone
|
74beacfd3a05c61121cd9acb1682ad11aff42fc8
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from django.contrib.auth.admin import UserAdmin
from .models import User_Profile
# Register your models here.
admin.site.register(User_Profile)
| 20
| 47
| 0.822222
| 26
| 180
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| 180
| 8
| 48
| 22.5
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| 1
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|
0
| 6
|
c3f5c591f6447f2b1a2f939399e267d3ff3263c5
| 88
|
py
|
Python
|
src/v8unpack/MetaDataObject/CommonModules.py
|
fishca/v8unpack-1
|
51e1bb6b57be170f0c19be20649e18abdda04668
|
[
"MIT"
] | null | null | null |
src/v8unpack/MetaDataObject/CommonModules.py
|
fishca/v8unpack-1
|
51e1bb6b57be170f0c19be20649e18abdda04668
|
[
"MIT"
] | null | null | null |
src/v8unpack/MetaDataObject/CommonModules.py
|
fishca/v8unpack-1
|
51e1bb6b57be170f0c19be20649e18abdda04668
|
[
"MIT"
] | null | null | null |
from ..MetaDataObject.core.Simple import Simple
class CommonModules(Simple):
pass
| 14.666667
| 47
| 0.772727
| 10
| 88
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0
| 6
|
7f03b7768499d78a702724ddeabe81fc74c838d4
| 135
|
py
|
Python
|
rpython/jit/backend/zarch/test/test_ztranslation_basic.py
|
nanjekyejoannah/pypy
|
e80079fe13c29eda7b2a6b4cd4557051f975a2d9
|
[
"Apache-2.0",
"OpenSSL"
] | 381
|
2018-08-18T03:37:22.000Z
|
2022-02-06T23:57:36.000Z
|
rpython/jit/backend/zarch/test/test_ztranslation_basic.py
|
nanjekyejoannah/pypy
|
e80079fe13c29eda7b2a6b4cd4557051f975a2d9
|
[
"Apache-2.0",
"OpenSSL"
] | 16
|
2018-09-22T18:12:47.000Z
|
2022-02-22T20:03:59.000Z
|
rpython/jit/backend/zarch/test/test_ztranslation_basic.py
|
nanjekyejoannah/pypy
|
e80079fe13c29eda7b2a6b4cd4557051f975a2d9
|
[
"Apache-2.0",
"OpenSSL"
] | 55
|
2015-08-16T02:41:30.000Z
|
2022-03-20T20:33:35.000Z
|
from rpython.jit.backend.llsupport.test.ztranslation_test import TranslationTest
class TestTranslationZARCH(TranslationTest):
pass
| 33.75
| 80
| 0.859259
| 14
| 135
| 8.214286
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.081481
| 135
| 3
| 81
| 45
| 0.927419
| 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| 0
| 1
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| 0
| 0
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| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
7f03cd5acb9ac4b1d61937350f94e1f944bd69a7
| 19
|
py
|
Python
|
coge/__init__.py
|
asherkhb/PyCoGe_API
|
ad9e642399127187d9078585a4e65dd9df05f3f7
|
[
"BSD-3-Clause"
] | null | null | null |
coge/__init__.py
|
asherkhb/PyCoGe_API
|
ad9e642399127187d9078585a4e65dd9df05f3f7
|
[
"BSD-3-Clause"
] | null | null | null |
coge/__init__.py
|
asherkhb/PyCoGe_API
|
ad9e642399127187d9078585a4e65dd9df05f3f7
|
[
"BSD-3-Clause"
] | null | null | null |
from coge import *
| 9.5
| 18
| 0.736842
| 3
| 19
| 4.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.210526
| 19
| 1
| 19
| 19
| 0.933333
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
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| 1
| 1
| 0
| null | 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
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| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
7f1178b3e6ef0dde3e017ab52fc5e0e8835d3a09
| 3,478
|
py
|
Python
|
PqrUploadModule/notes.py
|
petronije2002/PqrUpload
|
db22af08dac1243569e5f3dd8cdb4e010b215878
|
[
"MIT"
] | null | null | null |
PqrUploadModule/notes.py
|
petronije2002/PqrUpload
|
db22af08dac1243569e5f3dd8cdb4e010b215878
|
[
"MIT"
] | 3
|
2020-03-24T17:35:36.000Z
|
2021-02-02T22:12:56.000Z
|
PqrUploadModule/notes.py
|
petronije2002/PqrUpload
|
db22af08dac1243569e5f3dd8cdb4e010b215878
|
[
"MIT"
] | null | null | null |
# Here is the list of modules we need to import
# from . import authorizations
from authorizations import at,at_url,headers_at,encoded_u,encoded_u_td,td_base_url,get_headers
import atws
import atws.monkeypatch.attributes
import pandas as pd
import requests
def get_notes_for_list_of_note_ids(id_=[]):
query_notes=atws.Query('TicketNote')
query_notes.open_bracket('AND')
if len(id_)==1:
query_notes.WHERE('id',query_notes.Equals,id_[0])
# query_notes.AND('NoteType',query_notes.Equals,3) #at.picklist['TicketNote']['NoteType']['Task Notes']
else:
query_notes.WHERE('id',query_notes.Equals,id_[0])
# query_notes.AND('NoteType',query_notes.Equals,3) #at.picklist['TicketNote']['NoteType']['Task Notes']
for element in id_[1:]:
query_notes.OR('id',query_notes.Equals,element)
query_notes.close_bracket()
query_notes.open_bracket('AND')
query_notes.AND('NoteType',query_notes.NotEqual,13)
query_notes.AND('Publish',query_notes.Equals,1)
query_notes.close_bracket()
notes = at.query(query_notes).fetch_all()
df = pd.DataFrame([dict(note) for note in notes])
return df,notes
# def get_ticket_notes_at(id_=[0]):
# """
# Returns all notes, belonging to the tickets from the given list.
# Parameters:
# id_ [list]: list of Autotask ticket ids
# at [Autotask connect object] : Autotask atws.connect object
# Returns:
# Tuple: (Python DataFrame, list of notes)
# """
# query_notes=atws.Query('TicketNote')
# query_notes.AND('NoteType',query_notes.Equals,3)
# if len(id_)==1:
# query_notes.WHERE('TicketID',query_notes.Equals,id_[0])
# else:
# query_notes.WHERE('TicketID',query_notes.Equals,id_[0])
# for element in id_[1:]:
# query_notes.OR('TicketID',query_notes.Equals,element)
# notes = at.query(query_notes).fetch_all()
# df = pd.DataFrame([dict(note) for note in notes])
# return df,notes
def get_ticket_notes_at(id_=[0]):
"""
Returns all notes, belonging to the tickets from the given list.
Parameters:
id_ [list]: list of Autotask ticket ids
at [Autotask connect object] : Autotask atws.connect object
Returns:
Tuple: (Python DataFrame, list of notes)
"""
query_notes=atws.Query('TicketNote')
# query_notes.WHERE('NoteType',query_notes.Equals,3)
# query.open_bracket('AND')
query_notes.open_bracket('AND')
if len(id_)==1:
query_notes.WHERE('TicketID',query_notes.Equals,id_[0])
else:
query_notes.WHERE('TicketID',query_notes.Equals,id_[0])
for element in id_[1:]:
query_notes.OR('TicketID',query_notes.Equals,element)
query_notes.close_bracket()
query_notes.open_bracket('AND')
query_notes.AND('NoteType',query_notes.NotEqual,13)
query_notes.AND('Publish',query_notes.Equals,1)
query_notes.close_bracket()
notes = at.query(query_notes).fetch_all()
df = pd.DataFrame([dict(note) for note in notes])
return df,notes
def make_note_in_at(title='Title',descr='Long description 3200 chars',note_type=6,ticket_id=0):
note = at.new('TicketNote')
note.Title = title
note.Description = descr
note.NoteType = 3
note.TicketID= ticket_id
note.Publish = 1
note.create()
return note
| 26.549618
| 111
| 0.655549
| 472
| 3,478
| 4.612288
| 0.180085
| 0.220487
| 0.110243
| 0.035829
| 0.797887
| 0.779972
| 0.779972
| 0.766651
| 0.741387
| 0.741387
| 0
| 0.011778
| 0.218804
| 3,478
| 130
| 112
| 26.753846
| 0.789474
| 0.39333
| 0
| 0.625
| 0
| 0
| 0.06601
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.0625
| false
| 0
| 0.104167
| 0
| 0.229167
| 0
| 0
| 0
| 0
| null | 1
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
6130cc50694ef58a70bf10e8251c3249311e9e85
| 168
|
py
|
Python
|
courses/python/cursoemvideo/exercicios/ex107_112/main.py
|
bdpcampos/public
|
dda57c265718f3e1cc0d6bce73f149051f5647ef
|
[
"MIT"
] | 3
|
2020-04-28T01:42:09.000Z
|
2020-05-03T12:05:23.000Z
|
courses/python/cursoemvideo/exercicios/ex107_112/main.py
|
bdpcampos/public
|
dda57c265718f3e1cc0d6bce73f149051f5647ef
|
[
"MIT"
] | null | null | null |
courses/python/cursoemvideo/exercicios/ex107_112/main.py
|
bdpcampos/public
|
dda57c265718f3e1cc0d6bce73f149051f5647ef
|
[
"MIT"
] | null | null | null |
from exercicios.ex107_112.moeda import moeda
from exercicios.ex107_112.dado import validacao
p = validacao.leiaDinheiro('Digite o preço: R$')
moeda.resumo(p, 80, 35)
| 24
| 48
| 0.785714
| 26
| 168
| 5
| 0.653846
| 0.215385
| 0.292308
| 0.338462
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.107383
| 0.113095
| 168
| 7
| 49
| 24
| 0.765101
| 0
| 0
| 0
| 0
| 0
| 0.106509
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 6
|
61bf92ec1a6e3287a1fb9172ae186a9aebd9900e
| 230
|
py
|
Python
|
src/common/env.py
|
x-blood/absolutely-stop-aws-instances
|
11be070c2ebcbf7499220842c6168b8cb70327b9
|
[
"Apache-2.0"
] | null | null | null |
src/common/env.py
|
x-blood/absolutely-stop-aws-instances
|
11be070c2ebcbf7499220842c6168b8cb70327b9
|
[
"Apache-2.0"
] | null | null | null |
src/common/env.py
|
x-blood/absolutely-stop-aws-instances
|
11be070c2ebcbf7499220842c6168b8cb70327b9
|
[
"Apache-2.0"
] | null | null | null |
import os
def get_slack_channel_id():
return os.environ['SLACK_CHANNEL_ID']
def get_slack_web_hook_url():
return os.environ['SLACK_WEB_HOOK_URL']
def get_aws_account_name():
return os.environ['AWS_ACCOUNT_NAME']
| 16.428571
| 43
| 0.756522
| 37
| 230
| 4.243243
| 0.405405
| 0.11465
| 0.286624
| 0.254777
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.13913
| 230
| 13
| 44
| 17.692308
| 0.792929
| 0
| 0
| 0
| 0
| 0
| 0.217391
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.428571
| true
| 0
| 0.142857
| 0.428571
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
f61bee361b7dc06c2cf52939ece202d18dade259
| 8,692
|
py
|
Python
|
tests/test_autoscaling/test_autoscaling_tags.py
|
symroe/moto
|
4e106995af6f2820273528fca8a4e9ee288690a5
|
[
"Apache-2.0"
] | 5,460
|
2015-01-01T01:11:17.000Z
|
2022-03-31T23:45:38.000Z
|
tests/test_autoscaling/test_autoscaling_tags.py
|
symroe/moto
|
4e106995af6f2820273528fca8a4e9ee288690a5
|
[
"Apache-2.0"
] | 4,475
|
2015-01-05T19:37:30.000Z
|
2022-03-31T13:55:12.000Z
|
tests/test_autoscaling/test_autoscaling_tags.py
|
symroe/moto
|
4e106995af6f2820273528fca8a4e9ee288690a5
|
[
"Apache-2.0"
] | 1,831
|
2015-01-14T00:00:44.000Z
|
2022-03-31T20:30:04.000Z
|
import boto3
from moto import mock_autoscaling, mock_ec2
from .utils import setup_networking
from tests import EXAMPLE_AMI_ID
@mock_autoscaling
def test_autoscaling_tags_update():
mocked_networking = setup_networking()
client = boto3.client("autoscaling", region_name="us-east-1")
_ = client.create_launch_configuration(
LaunchConfigurationName="test_launch_configuration",
ImageId=EXAMPLE_AMI_ID,
InstanceType="t2.medium",
)
_ = client.create_auto_scaling_group(
AutoScalingGroupName="test_asg",
LaunchConfigurationName="test_launch_configuration",
MinSize=0,
MaxSize=20,
DesiredCapacity=5,
Tags=[
{
"ResourceId": "test_asg",
"Key": "test_key",
"Value": "test_value",
"PropagateAtLaunch": True,
}
],
VPCZoneIdentifier=mocked_networking["subnet1"],
)
client.create_or_update_tags(
Tags=[
{
"ResourceId": "test_asg",
"Key": "test_key",
"Value": "updated_test_value",
"PropagateAtLaunch": True,
},
{
"ResourceId": "test_asg",
"Key": "test_key2",
"Value": "test_value2",
"PropagateAtLaunch": False,
},
]
)
response = client.describe_auto_scaling_groups(AutoScalingGroupNames=["test_asg"])
response["AutoScalingGroups"][0]["Tags"].should.have.length_of(2)
@mock_autoscaling
@mock_ec2
def test_delete_tags_by_key():
mocked_networking = setup_networking()
client = boto3.client("autoscaling", region_name="us-east-1")
client.create_launch_configuration(
LaunchConfigurationName="TestLC",
ImageId=EXAMPLE_AMI_ID,
InstanceType="t2.medium",
)
tag_to_delete = {
"ResourceId": "tag_test_asg",
"ResourceType": "auto-scaling-group",
"PropagateAtLaunch": True,
"Key": "TestDeleteTagKey1",
"Value": "TestTagValue1",
}
tag_to_keep = {
"ResourceId": "tag_test_asg",
"ResourceType": "auto-scaling-group",
"PropagateAtLaunch": True,
"Key": "TestTagKey1",
"Value": "TestTagValue1",
}
client.create_auto_scaling_group(
AutoScalingGroupName="tag_test_asg",
MinSize=1,
MaxSize=2,
LaunchConfigurationName="TestLC",
Tags=[tag_to_delete, tag_to_keep],
VPCZoneIdentifier=mocked_networking["subnet1"],
)
client.delete_tags(
Tags=[
{
"ResourceId": "tag_test_asg",
"ResourceType": "auto-scaling-group",
"PropagateAtLaunch": True,
"Key": "TestDeleteTagKey1",
}
]
)
response = client.describe_auto_scaling_groups(
AutoScalingGroupNames=["tag_test_asg"]
)
group = response["AutoScalingGroups"][0]
tags = group["Tags"]
tags.should.contain(tag_to_keep)
tags.should_not.contain(tag_to_delete)
@mock_autoscaling
def test_describe_tags_without_resources():
client = boto3.client("autoscaling", region_name="us-east-2")
resp = client.describe_tags()
resp.should.have.key("Tags").equals([])
resp.shouldnt.have.key("NextToken")
@mock_autoscaling
def test_describe_tags_no_filter():
subnet = setup_networking()["subnet1"]
client = boto3.client("autoscaling", region_name="us-east-1")
create_asgs(client, subnet)
response = client.describe_tags()
response.should.have.key("Tags").length_of(4)
response["Tags"].should.contain(
{
"ResourceId": "test_asg",
"ResourceType": "auto-scaling-group",
"Key": "test_key",
"Value": "updated_test_value",
"PropagateAtLaunch": True,
}
)
response["Tags"].should.contain(
{
"ResourceId": "test_asg",
"ResourceType": "auto-scaling-group",
"Key": "test_key2",
"Value": "test_value2",
"PropagateAtLaunch": False,
}
)
response["Tags"].should.contain(
{
"ResourceId": "test_asg2",
"ResourceType": "auto-scaling-group",
"Key": "asg2tag1",
"Value": "val",
"PropagateAtLaunch": False,
}
)
response["Tags"].should.contain(
{
"ResourceId": "test_asg2",
"ResourceType": "auto-scaling-group",
"Key": "asg2tag2",
"Value": "diff",
"PropagateAtLaunch": False,
}
)
@mock_autoscaling
def test_describe_tags_filter_by_name():
subnet = setup_networking()["subnet1"]
client = boto3.client("autoscaling", region_name="us-east-1")
create_asgs(client, subnet)
response = client.describe_tags(
Filters=[{"Name": "auto-scaling-group", "Values": ["test_asg"]}]
)
response.should.have.key("Tags").length_of(2)
response["Tags"].should.contain(
{
"ResourceId": "test_asg",
"ResourceType": "auto-scaling-group",
"Key": "test_key",
"Value": "updated_test_value",
"PropagateAtLaunch": True,
}
)
response["Tags"].should.contain(
{
"ResourceId": "test_asg",
"ResourceType": "auto-scaling-group",
"Key": "test_key2",
"Value": "test_value2",
"PropagateAtLaunch": False,
}
)
response = client.describe_tags(
Filters=[{"Name": "auto-scaling-group", "Values": ["test_asg", "test_asg2"]}]
)
response.should.have.key("Tags").length_of(4)
response["Tags"].should.contain(
{
"ResourceId": "test_asg",
"ResourceType": "auto-scaling-group",
"Key": "test_key",
"Value": "updated_test_value",
"PropagateAtLaunch": True,
}
)
response["Tags"].should.contain(
{
"ResourceId": "test_asg",
"ResourceType": "auto-scaling-group",
"Key": "test_key2",
"Value": "test_value2",
"PropagateAtLaunch": False,
}
)
response["Tags"].should.contain(
{
"ResourceId": "test_asg2",
"ResourceType": "auto-scaling-group",
"Key": "asg2tag1",
"Value": "val",
"PropagateAtLaunch": False,
}
)
response["Tags"].should.contain(
{
"ResourceId": "test_asg2",
"ResourceType": "auto-scaling-group",
"Key": "asg2tag2",
"Value": "diff",
"PropagateAtLaunch": False,
}
)
@mock_autoscaling
def test_describe_tags_filter_by_propgateatlaunch():
subnet = setup_networking()["subnet1"]
client = boto3.client("autoscaling", region_name="us-east-1")
create_asgs(client, subnet)
response = client.describe_tags(
Filters=[{"Name": "propagate-at-launch", "Values": ["True"]}]
)
response.should.have.key("Tags").length_of(1)
response["Tags"].should.contain(
{
"ResourceId": "test_asg",
"ResourceType": "auto-scaling-group",
"Key": "test_key",
"Value": "updated_test_value",
"PropagateAtLaunch": True,
}
)
def create_asgs(client, subnet):
_ = client.create_launch_configuration(
LaunchConfigurationName="test_launch_configuration",
ImageId=EXAMPLE_AMI_ID,
InstanceType="t2.medium",
)
client.create_auto_scaling_group(
AutoScalingGroupName="test_asg",
LaunchConfigurationName="test_launch_configuration",
MinSize=0,
MaxSize=20,
DesiredCapacity=5,
VPCZoneIdentifier=subnet,
)
client.create_auto_scaling_group(
AutoScalingGroupName="test_asg2",
LaunchConfigurationName="test_launch_configuration",
MinSize=0,
MaxSize=20,
DesiredCapacity=5,
Tags=[
{"Key": "asg2tag1", "Value": "val"},
{"Key": "asg2tag2", "Value": "diff"},
],
VPCZoneIdentifier=subnet,
)
client.create_or_update_tags(
Tags=[
{
"ResourceId": "test_asg",
"Key": "test_key",
"Value": "updated_test_value",
"PropagateAtLaunch": True,
},
{
"ResourceId": "test_asg",
"Key": "test_key2",
"Value": "test_value2",
"PropagateAtLaunch": False,
},
]
)
| 29.364865
| 86
| 0.55971
| 763
| 8,692
| 6.124509
| 0.129751
| 0.051787
| 0.068478
| 0.083886
| 0.823026
| 0.804622
| 0.779799
| 0.72523
| 0.708966
| 0.708966
| 0
| 0.012746
| 0.304993
| 8,692
| 295
| 87
| 29.464407
| 0.760801
| 0
| 0
| 0.602941
| 0
| 0
| 0.262655
| 0.014381
| 0
| 0
| 0
| 0
| 0
| 1
| 0.025735
| false
| 0
| 0.014706
| 0
| 0.040441
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
f632b07435f03ba4c3f143216b2e2f85b74eeae5
| 38
|
py
|
Python
|
deepnlpf/__init__.py
|
deepnlpf/deepnlpf
|
6508ab1e8fd395575d606ee20223f25591541e25
|
[
"Apache-2.0"
] | 3
|
2020-04-11T14:12:45.000Z
|
2020-05-30T16:31:06.000Z
|
deepnlpf/__init__.py
|
deepnlpf/deepnlpf
|
6508ab1e8fd395575d606ee20223f25591541e25
|
[
"Apache-2.0"
] | 34
|
2020-03-20T19:36:40.000Z
|
2022-03-20T13:00:32.000Z
|
deepnlpf/__init__.py
|
deepnlpf/deepnlpf
|
6508ab1e8fd395575d606ee20223f25591541e25
|
[
"Apache-2.0"
] | 1
|
2020-09-05T06:44:15.000Z
|
2020-09-05T06:44:15.000Z
|
from deepnlpf.pipeline import Pipeline
| 38
| 38
| 0.894737
| 5
| 38
| 6.8
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.078947
| 38
| 1
| 38
| 38
| 0.971429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f63495b925accbf028603acee9766da20e3c0074
| 80
|
py
|
Python
|
metasearch/__init__.py
|
suzanagi/materials-researchactivity-uoa-2020-public-metasearch-mosaicsearch_publication
|
37553698e6f778b313922dca23c4ed40530d8f31
|
[
"MIT"
] | null | null | null |
metasearch/__init__.py
|
suzanagi/materials-researchactivity-uoa-2020-public-metasearch-mosaicsearch_publication
|
37553698e6f778b313922dca23c4ed40530d8f31
|
[
"MIT"
] | null | null | null |
metasearch/__init__.py
|
suzanagi/materials-researchactivity-uoa-2020-public-metasearch-mosaicsearch_publication
|
37553698e6f778b313922dca23c4ed40530d8f31
|
[
"MIT"
] | null | null | null |
from metasearch.models import ResultItem
# Tests
from metasearch.tests import *
| 20
| 40
| 0.825
| 10
| 80
| 6.6
| 0.6
| 0.424242
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 80
| 4
| 41
| 20
| 0.942857
| 0.0625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f63fe8f193376559dd3cc9a126e820175b4ba446
| 64
|
py
|
Python
|
ctf/print_N_581_times.py
|
inflatus/python
|
bc87e2ca9f40c0e53c0d6e15e364cb7dff1c6fc0
|
[
"MIT"
] | null | null | null |
ctf/print_N_581_times.py
|
inflatus/python
|
bc87e2ca9f40c0e53c0d6e15e364cb7dff1c6fc0
|
[
"MIT"
] | 7
|
2021-02-08T20:43:38.000Z
|
2022-03-12T00:17:16.000Z
|
ctf/print_N_581_times.py
|
inflatus/python
|
bc87e2ca9f40c0e53c0d6e15e364cb7dff1c6fc0
|
[
"MIT"
] | null | null | null |
# print N 581 times
# need to be followed by a 4
print 'N'*581
| 12.8
| 28
| 0.671875
| 14
| 64
| 3.071429
| 0.785714
| 0.27907
| 0.418605
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.145833
| 0.25
| 64
| 4
| 29
| 16
| 0.75
| 0.6875
| 0
| 0
| 0
| 0
| 0.058824
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 1
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
f674e8d226841f5c9d937a826aec4f5eabf244c7
| 172
|
py
|
Python
|
common/__init__.py
|
jkulhanek/rl-baselines-tensorflow
|
38726b5f2e89d56d8172a5fcc24cb4697112482e
|
[
"MIT"
] | null | null | null |
common/__init__.py
|
jkulhanek/rl-baselines-tensorflow
|
38726b5f2e89d56d8172a5fcc24cb4697112482e
|
[
"MIT"
] | null | null | null |
common/__init__.py
|
jkulhanek/rl-baselines-tensorflow
|
38726b5f2e89d56d8172a5fcc24cb4697112482e
|
[
"MIT"
] | null | null | null |
from common.registry import register_trainer, make_trainer, register_agent, make_agent
from common.core import AbstractAgent
from common.train_wrappers import MetricContext
| 57.333333
| 86
| 0.883721
| 23
| 172
| 6.391304
| 0.565217
| 0.204082
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.081395
| 172
| 3
| 87
| 57.333333
| 0.93038
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
f6759e9e31e1072183c78bcbdb33102bed896643
| 6,125
|
py
|
Python
|
truffe2/units/migrations/0003_auto_20210210_1832.py
|
TeoGoddet/truffe2
|
23a963d404e5f719c0eeb273f52223ff5e3e5263
|
[
"BSD-2-Clause"
] | null | null | null |
truffe2/units/migrations/0003_auto_20210210_1832.py
|
TeoGoddet/truffe2
|
23a963d404e5f719c0eeb273f52223ff5e3e5263
|
[
"BSD-2-Clause"
] | null | null | null |
truffe2/units/migrations/0003_auto_20210210_1832.py
|
TeoGoddet/truffe2
|
23a963d404e5f719c0eeb273f52223ff5e3e5263
|
[
"BSD-2-Clause"
] | null | null | null |
# Generated by Django 2.2.18 on 2021-02-10 17:32
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
import multiselectfield.db.fields
class Migration(migrations.Migration):
dependencies = [
('units', '0002_auto_20201104_1648'),
]
operations = [
migrations.AlterField(
model_name='accessdelegation',
name='access',
field=multiselectfield.db.fields.MultiSelectField(blank=True, choices=[('PRESIDENCE', 'Présidence'), ('TRESORERIE', 'Trésorerie'), ('COMMUNICATION', 'Communication'), ('INFORMATIQUE', 'Informatique'), ('ACCREDITATION', 'Accréditations'), ('LOGISTIQUE', 'Logistique'), ('SECRETARIAT', 'Secrétariat'), ('COMMISSIONS', 'Commissions')], max_length=97, null=True),
),
migrations.AlterField(
model_name='accessdelegation',
name='role',
field=models.ForeignKey(blank=True, help_text='(Optionnel !) Le rôle concerné.', null=True, on_delete=django.db.models.deletion.CASCADE, to='units.Role'),
),
migrations.AlterField(
model_name='accessdelegation',
name='user',
field=models.ForeignKey(blank=True, help_text="(Optionnel !) L'utilisateur concerné. L'utilisateur doit disposer d'une accréditation dans l'unité.", null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='accessdelegationlogging',
name='what',
field=models.CharField(choices=[('imported', 'Importé depuis Truffe 1'), ('created', 'Creation'), ('edited', 'Edité'), ('deleted', 'Supprimé'), ('restored', 'Restauré'), ('state_changed', 'Statut changé'), ('file_added', 'Fichier ajouté'), ('file_removed', 'Fichier supprimé')], max_length=64),
),
migrations.AlterField(
model_name='accessdelegationlogging',
name='who',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='accessdelegationviews',
name='who',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='accreditation',
name='user',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='accreditationlog',
name='type',
field=models.CharField(choices=[('created', 'Créée'), ('edited', 'Modifiée'), ('deleted', 'Supprimée'), ('autodeleted', 'Supprimée automatiquement'), ('renewed', 'Renouvelée'), ('validated', 'Validée'), ('autocreated', 'Créée automatiquement')], max_length=32),
),
migrations.AlterField(
model_name='accreditationlog',
name='who',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='role',
name='access',
field=multiselectfield.db.fields.MultiSelectField(blank=True, choices=[('PRESIDENCE', 'Présidence'), ('TRESORERIE', 'Trésorerie'), ('COMMUNICATION', 'Communication'), ('INFORMATIQUE', 'Informatique'), ('ACCREDITATION', 'Accréditations'), ('LOGISTIQUE', 'Logistique'), ('SECRETARIAT', 'Secrétariat'), ('COMMISSIONS', 'Commissions')], max_length=97, null=True),
),
migrations.AlterField(
model_name='role',
name='name',
field=models.CharField(default='---', max_length=255),
),
migrations.AlterField(
model_name='rolelogging',
name='what',
field=models.CharField(choices=[('imported', 'Importé depuis Truffe 1'), ('created', 'Creation'), ('edited', 'Edité'), ('deleted', 'Supprimé'), ('restored', 'Restauré'), ('state_changed', 'Statut changé'), ('file_added', 'Fichier ajouté'), ('file_removed', 'Fichier supprimé')], max_length=64),
),
migrations.AlterField(
model_name='rolelogging',
name='who',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='roleviews',
name='who',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='unit',
name='name',
field=models.CharField(default='---', max_length=255),
),
migrations.AlterField(
model_name='unit',
name='parent_hierarchique',
field=models.ForeignKey(blank=True, help_text="Pour les commissions et les équipes, sélectionner le comité de l'AGEPoly. Pour les sous-commisions, sélectionner la commission parente. Pour un coaching de section, sélectionner la commission Coaching. Pour le comité de l'AGEPoly, ne rien mettre.", null=True, on_delete=django.db.models.deletion.CASCADE, to='units.Unit'),
),
migrations.AlterField(
model_name='unitlogging',
name='what',
field=models.CharField(choices=[('imported', 'Importé depuis Truffe 1'), ('created', 'Creation'), ('edited', 'Edité'), ('deleted', 'Supprimé'), ('restored', 'Restauré'), ('state_changed', 'Statut changé'), ('file_added', 'Fichier ajouté'), ('file_removed', 'Fichier supprimé')], max_length=64),
),
migrations.AlterField(
model_name='unitlogging',
name='who',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
migrations.AlterField(
model_name='unitviews',
name='who',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL),
),
]
| 54.6875
| 381
| 0.631673
| 603
| 6,125
| 6.296849
| 0.240464
| 0.100079
| 0.125099
| 0.145115
| 0.802476
| 0.789834
| 0.706084
| 0.696076
| 0.671319
| 0.671319
| 0
| 0.01106
| 0.217633
| 6,125
| 111
| 382
| 55.18018
| 0.781302
| 0.00751
| 0
| 0.8
| 1
| 0.019048
| 0.289452
| 0.01481
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.066667
| 0
| 0.095238
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
9cb0591f499436797cf13b46c2815efe3cbdf3a7
| 117
|
py
|
Python
|
scripts/_mp_sum.py
|
lilleswing/SynNet
|
635af44d0cfe2a2015814001a3b1c809128b238a
|
[
"MIT"
] | 14
|
2021-10-18T06:56:49.000Z
|
2022-03-01T01:32:10.000Z
|
scripts/_mp_sum.py
|
lilleswing/SynNet
|
635af44d0cfe2a2015814001a3b1c809128b238a
|
[
"MIT"
] | 3
|
2021-10-19T20:58:09.000Z
|
2022-02-07T18:02:04.000Z
|
scripts/_mp_sum.py
|
lilleswing/SynNet
|
635af44d0cfe2a2015814001a3b1c809128b238a
|
[
"MIT"
] | 4
|
2021-10-20T03:02:59.000Z
|
2022-01-25T22:12:47.000Z
|
"""
Computes the sum of a single molecular embedding.
"""
import numpy as np
def func(emb):
return np.sum(emb)
| 13
| 49
| 0.683761
| 19
| 117
| 4.210526
| 0.842105
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.205128
| 117
| 8
| 50
| 14.625
| 0.860215
| 0.418803
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
9cbacd7dcbeea8ce566d9f08b2e0008d0eca7eed
| 5,870
|
py
|
Python
|
st2common/tests/unit/test_jinja_render_version_filters.py
|
kkkanil/st2
|
07cd195d7a6e177a37dd019e5c9ab8329259d0fa
|
[
"Apache-2.0"
] | null | null | null |
st2common/tests/unit/test_jinja_render_version_filters.py
|
kkkanil/st2
|
07cd195d7a6e177a37dd019e5c9ab8329259d0fa
|
[
"Apache-2.0"
] | 15
|
2021-02-11T22:58:54.000Z
|
2021-08-06T18:03:47.000Z
|
st2common/tests/unit/test_jinja_render_version_filters.py
|
kkkanil/st2
|
07cd195d7a6e177a37dd019e5c9ab8329259d0fa
|
[
"Apache-2.0"
] | 1
|
2021-07-10T15:02:29.000Z
|
2021-07-10T15:02:29.000Z
|
# Copyright 2020 The StackStorm Authors.
# Copyright 2019 Extreme Networks, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import
import unittest2
from st2common.util import jinja as jinja_utils
class JinjaUtilsVersionsFilterTestCase(unittest2.TestCase):
def test_version_compare(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_compare("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.9.0'})
expected = '-1'
self.assertEqual(actual, expected)
template = '{{version | version_compare("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = '1'
self.assertEqual(actual, expected)
template = '{{version | version_compare("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.0'})
expected = '0'
self.assertEqual(actual, expected)
def test_version_more_than(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_more_than("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.9.0'})
expected = 'False'
self.assertEqual(actual, expected)
template = '{{version | version_more_than("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = 'True'
self.assertEqual(actual, expected)
template = '{{version | version_more_than("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.0'})
expected = 'False'
self.assertEqual(actual, expected)
def test_version_less_than(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_less_than("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.9.0'})
expected = 'True'
self.assertEqual(actual, expected)
template = '{{version | version_less_than("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = 'False'
self.assertEqual(actual, expected)
template = '{{version | version_less_than("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.0'})
expected = 'False'
self.assertEqual(actual, expected)
def test_version_equal(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_equal("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.9.0'})
expected = 'False'
self.assertEqual(actual, expected)
template = '{{version | version_equal("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = 'False'
self.assertEqual(actual, expected)
template = '{{version | version_equal("0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.0'})
expected = 'True'
self.assertEqual(actual, expected)
def test_version_match(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_match(">0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = 'True'
self.assertEqual(actual, expected)
actual = env.from_string(template).render({'version': '0.1.1'})
expected = 'False'
self.assertEqual(actual, expected)
template = '{{version | version_match("<0.10.0")}}'
actual = env.from_string(template).render({'version': '0.1.0'})
expected = 'True'
self.assertEqual(actual, expected)
actual = env.from_string(template).render({'version': '1.1.0'})
expected = 'False'
self.assertEqual(actual, expected)
template = '{{version | version_match("==0.10.0")}}'
actual = env.from_string(template).render({'version': '0.10.0'})
expected = 'True'
self.assertEqual(actual, expected)
actual = env.from_string(template).render({'version': '0.10.1'})
expected = 'False'
self.assertEqual(actual, expected)
def test_version_bump_major(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_bump_major}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = '1.0.0'
self.assertEqual(actual, expected)
def test_version_bump_minor(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_bump_minor}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = '0.11.0'
self.assertEqual(actual, expected)
def test_version_bump_patch(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_bump_patch}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = '0.10.2'
self.assertEqual(actual, expected)
def test_version_strip_patch(self):
env = jinja_utils.get_jinja_environment()
template = '{{version | version_strip_patch}}'
actual = env.from_string(template).render({'version': '0.10.1'})
expected = '0.10'
self.assertEqual(actual, expected)
| 37.870968
| 74
| 0.634072
| 710
| 5,870
| 5.090141
| 0.152113
| 0.026563
| 0.079137
| 0.115661
| 0.799945
| 0.799945
| 0.799945
| 0.784173
| 0.770891
| 0.738794
| 0
| 0.037682
| 0.217888
| 5,870
| 154
| 75
| 38.116883
| 0.74951
| 0.101874
| 0
| 0.719626
| 0
| 0
| 0.207533
| 0.081796
| 0
| 0
| 0
| 0
| 0.205607
| 1
| 0.084112
| false
| 0
| 0.028037
| 0
| 0.121495
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
9cc7aefd30ad4120cedbb83f445eb6ceb68e930c
| 173
|
py
|
Python
|
mdp_extras/envs/__init__.py
|
aaronsnoswell/mdp-extras
|
58e544d7d6c8ef5ecc954647f35299af3e57a748
|
[
"MIT"
] | 1
|
2021-11-18T02:28:17.000Z
|
2021-11-18T02:28:17.000Z
|
mdp_extras/envs/__init__.py
|
aaronsnoswell/mdp-extras
|
58e544d7d6c8ef5ecc954647f35299af3e57a748
|
[
"MIT"
] | null | null | null |
mdp_extras/envs/__init__.py
|
aaronsnoswell/mdp-extras
|
58e544d7d6c8ef5ecc954647f35299af3e57a748
|
[
"MIT"
] | 1
|
2021-05-30T14:26:45.000Z
|
2021-05-30T14:26:45.000Z
|
"""Move imports to module level for convenience"""
from .nchain import *
from .frozen_lake import *
from .taxi import *
from .mountain_car import *
from .pendulum import *
| 21.625
| 50
| 0.745665
| 24
| 173
| 5.291667
| 0.666667
| 0.314961
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16185
| 173
| 7
| 51
| 24.714286
| 0.875862
| 0.254335
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
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| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
141c285eb097db4e7c9df33763e803922a146d0f
| 81
|
py
|
Python
|
CodeWars/7 Kyu/Sort by Example.py
|
anubhab-code/Competitive-Programming
|
de28cb7d44044b9e7d8bdb475da61e37c018ac35
|
[
"MIT"
] | null | null | null |
CodeWars/7 Kyu/Sort by Example.py
|
anubhab-code/Competitive-Programming
|
de28cb7d44044b9e7d8bdb475da61e37c018ac35
|
[
"MIT"
] | null | null | null |
CodeWars/7 Kyu/Sort by Example.py
|
anubhab-code/Competitive-Programming
|
de28cb7d44044b9e7d8bdb475da61e37c018ac35
|
[
"MIT"
] | null | null | null |
def example_sort(arr, example_arr):
return sorted(arr, key=example_arr.index)
| 40.5
| 45
| 0.777778
| 13
| 81
| 4.615385
| 0.615385
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 81
| 2
| 45
| 40.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
145999f4d386cd277a6aaef3a3a3bb67f18dc1cc
| 149
|
py
|
Python
|
app/models/__init__.py
|
oq-Yuki-po/PaperLibrary
|
2b86da52af08b487c78d1f9007cb9c02bc160235
|
[
"MIT"
] | null | null | null |
app/models/__init__.py
|
oq-Yuki-po/PaperLibrary
|
2b86da52af08b487c78d1f9007cb9c02bc160235
|
[
"MIT"
] | null | null | null |
app/models/__init__.py
|
oq-Yuki-po/PaperLibrary
|
2b86da52af08b487c78d1f9007cb9c02bc160235
|
[
"MIT"
] | null | null | null |
from app.models.setting import BaseModel, Engine, session
from app.models.arxiv_query import ArxivQueryModel
from app.models.paper import PaperModel
| 37.25
| 57
| 0.852349
| 21
| 149
| 6
| 0.619048
| 0.166667
| 0.309524
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.09396
| 149
| 3
| 58
| 49.666667
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
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| 0
| null | 0
| 1
| 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
145a3a50d99379e7770ecd5451d176e171d66f3b
| 219
|
py
|
Python
|
src/attack_surface_pypy/models/v1/models/firewall.py
|
ccrvs/attack_surface_pypy
|
f2bc9998cf42f4764f1c495e6243d970e01bd176
|
[
"CC0-1.0"
] | null | null | null |
src/attack_surface_pypy/models/v1/models/firewall.py
|
ccrvs/attack_surface_pypy
|
f2bc9998cf42f4764f1c495e6243d970e01bd176
|
[
"CC0-1.0"
] | null | null | null |
src/attack_surface_pypy/models/v1/models/firewall.py
|
ccrvs/attack_surface_pypy
|
f2bc9998cf42f4764f1c495e6243d970e01bd176
|
[
"CC0-1.0"
] | null | null | null |
from attack_surface_pypy import types
from attack_surface_pypy.models.v1.models import base, tag
class FirewallRuleModel(base.BaseModel):
fw_id: types.FW_ID
source_tag: tag.TagModel
dest_tag: tag.TagModel
| 24.333333
| 58
| 0.794521
| 33
| 219
| 5.030303
| 0.545455
| 0.120482
| 0.204819
| 0.253012
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005319
| 0.141553
| 219
| 8
| 59
| 27.375
| 0.87766
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
14679d1b215e6455f7d92d1f8834e5b65db4980d
| 26
|
py
|
Python
|
src/utils/__init__.py
|
AlexMabry/aoc21
|
da492f53f93ba960e282b8c664041b76871631ea
|
[
"Apache-2.0"
] | null | null | null |
src/utils/__init__.py
|
AlexMabry/aoc21
|
da492f53f93ba960e282b8c664041b76871631ea
|
[
"Apache-2.0"
] | null | null | null |
src/utils/__init__.py
|
AlexMabry/aoc21
|
da492f53f93ba960e282b8c664041b76871631ea
|
[
"Apache-2.0"
] | null | null | null |
from .aocd_utils import *
| 13
| 25
| 0.769231
| 4
| 26
| 4.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153846
| 26
| 1
| 26
| 26
| 0.863636
| 0
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| 0
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| 0
| 0
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| true
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| null | 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
1473d71c0d5609632a19e373ee5f67c3735385ad
| 578,867
|
py
|
Python
|
clmt-parser.py
|
ksgwxfan/climate-parser
|
d2f8f9a225dcf30ffc2fc6cd76749fffecc6b8af
|
[
"MIT"
] | null | null | null |
clmt-parser.py
|
ksgwxfan/climate-parser
|
d2f8f9a225dcf30ffc2fc6cd76749fffecc6b8af
|
[
"MIT"
] | 1
|
2021-07-28T20:09:34.000Z
|
2021-07-28T20:30:14.000Z
|
clmt-parser.py
|
ksgwxfan/climate-parser
|
d2f8f9a225dcf30ffc2fc6cd76749fffecc6b8af
|
[
"MIT"
] | null | null | null |
# v2.92
import datetime
from time import time
import calendar
from statistics import mean, pstdev, mode, median, median_grouped
from math import floor
import csv
import os
from textwrap import wrap
from string import Template
import random
import traceback
# assisted on nested list comprehensions: https://www.geeksforgeeks.org/nested-list-comprehensions-in-python/
def quicklist(vrbl,**kw):
if vrbl not in ["prcp","snow","snwd","tmax","tmin"]: return print("OOPS! Improper variable entered. Try again!")
vdictionary = {"prcp":"Precipitation Totals","snow":"Snow Totals","snwd":"Snow Depths","tmax":"High Temperatures","tmin":"Low Temperatures"}
if all(x in kw and len(list(kw.keys())) == 1 for x in ["season"]): # all yrs; specific season; all months & days
#if type(kw["season"]) == list:
#qwkli = []
#for s in kw["season"]: qwkli.extend(x for y in metclmt if type(y) == int for x in metclmt[y][s][vrbl])
#else: # If just one season passed
qwkli = [x for y in metclmt if type(y) == int for x in metclmt[y][kw["season"]][vrbl]]
print("* Completed list for all {} occurring in Meteorological {} from the entire record *".format(vdictionary[vrbl],kw["season"]))
elif all(x in kw and len(list(kw.keys())) == 1 for x in ["metyear"]): # specific metyear; all months & days
try:
qwkli = metclmt[kw["metyear"]][vrbl]
print("* Completed list for all {} occurring in the Meteorological Year {}. Same as metclmt[{}]['{}'] *".format(vdictionary[vrbl],kw["metyear"],kw["metyear"],vrbl))
except:
if kw["metyear"] not in metclmt: print("OOPS! No records are available for the Meteorological Year {}".format(kw["metyear"]))
elif all(x in kw and len(list(kw.keys())) == 2 for x in ["metyear","season"]): # specific metyear; specific season; all months & days
try:
qwkli = metclmt[kw["metyear"]][kw["season"]][vrbl]
print("* Completed list for all {} occurring in Meteorological {} of the Year {}. Same as metclmt[{}]['{}']['{}'] *".format(vdictionary[vrbl],kw["season"],kw["metyear"],kw["metyear"],kw["season"],vrbl))
except:
if kw["metyear"] not in metclmt: print("OOPS! No records are available for {}".format(kw["year"]))
elif kw["month"] not in metclmt[kw["metyear"]]: print("OOPS! No records are available for {} {}".format(calendar.month_name[kw["month"]],kw["metyear"]))
elif all(x in kw and len(list(kw.keys())) == 2 for x in ["year","month"]): # specific year; specific month; all days
try:
qwkli = clmt[kw["year"]][kw["month"]][vrbl]
print("* Completed list for all {} occurring in {} {}. Same as clmt[{}][{}]['{}'] *".format(vdictionary[vrbl],
calendar.month_name[kw["month"]],kw["year"],kw["month"],kw["year"],vrbl))
except:
if kw["year"] not in clmt: print("OOPS! No records are available for {}".format(kw["year"]))
elif kw["month"] not in clmt[kw["year"]]: print("OOPS! No records are available for {} {}".format(calendar.month_name[kw["month"]],kw["year"]))
elif all(x in kw and len(list(kw.keys())) == 1 for x in ["year"]): # specific year; all months; all days
try:
qwkli = clmt[kw["year"]][vrbl]
print("* Completed list for all {} occurring in {}. Same as clmt[{}]['{}'] *".format(vdictionary[vrbl],kw["year"],kw["year"],vrbl))
except:
if kw["year"] not in clmt: print("OOPS! No records are available for {}".format(kw["year"]))
elif all(x in kw and len(list(kw.keys())) == 1 for x in ["month"]): # all years; specific month; all days
qwkli = [x for y in clmt if type(y) == int for m in clmt[y] if type(m) == int and m in clmt[y] and m == kw["month"] for x in clmt[y][kw["month"]][vrbl]]
print("* Completed list for all {} occurring in the month of {} for all years on record.".format(vdictionary[vrbl],calendar.month_name[kw["month"]]))
elif all(x in kw and len(list(kw.keys())) == 2 for x in ["month","day"]): # all years; specific month; specific day
if vrbl == "prcp": qwkli = [float(clmt[y][kw["month"]][kw["day"]].prcp) for y in clmt if type(y) == int and kw["month"] in clmt[y] and kw["day"] in clmt[y][kw["month"]] and clmt[y][kw["month"]][kw["day"]].prcp not in ["","-9999","9999"] and clmt[y][kw["month"]][kw["day"]].prcpQ in ignoreflags]
elif vrbl == "snow": qwkli = [float(clmt[y][kw["month"]][kw["day"]].snow) for y in clmt if type(y) == int and kw["month"] in clmt[y] and kw["day"] in clmt[y][kw["month"]] and clmt[y][kw["month"]][kw["day"]].snow not in ["","-9999","9999"] and clmt[y][kw["month"]][kw["day"]].snowQ in ignoreflags]
elif vrbl == "snwd": qwkli = [float(clmt[y][kw["month"]][kw["day"]].snwd) for y in clmt if type(y) == int and kw["month"] in clmt[y] and kw["day"] in clmt[y][kw["month"]] and clmt[y][kw["month"]][kw["day"]].snwd not in ["","-9999","9999"] and clmt[y][kw["month"]][kw["day"]].snwdQ in ignoreflags]
elif vrbl == "tmax": qwkli = [int(clmt[y][kw["month"]][kw["day"]].tmax) for y in clmt if type(y) == int and kw["month"] in clmt[y] and kw["day"] in clmt[y][kw["month"]] and clmt[y][kw["month"]][kw["day"]].tmax not in ["","-9999","9999"] and clmt[y][kw["month"]][kw["day"]].tmaxQ in ignoreflags]
elif vrbl == "tmin": qwkli = [int(clmt[y][kw["month"]][kw["day"]].tmin) for y in clmt if type(y) == int and kw["month"] in clmt[y] and kw["day"] in clmt[y][kw["month"]] and clmt[y][kw["month"]][kw["day"]].tmin not in ["","-9999","9999"] and clmt[y][kw["month"]][kw["day"]].tminQ in ignoreflags]
print("* Completed list for all {} occurring on {} {} for all years on record *".format(vdictionary[vrbl],calendar.month_name[kw["month"]],kw["day"]))
return qwkli
def percentiles(li):
li.sort() # Sort list from smallest value to largest
n = len(li)
percentiles = [x for x in range(5,95+5,5)] # list of kth percentiles we'll be calculating
for k in percentiles:
i = k/100 * (n + 1)
if i / 1 == int(i): # if 'i' is an integer...
print("{}th Percentile: {}".format(k,li[int(i)-1]))
else:
i_down = int(i)
i_up = int(i)+1
print("{}th Percentile: {:.1f}".format(k,mean([li[i_down-1],li[i_up-1]])))
def percentile(k,li):
if k <= 0 or k >= 100: return print("OOPS! Invalid percentile. Try again")
li.sort() # Sort list from smallest value to largest
n = len(li)
i = k/100 * (n + 1)
if i / 1 == int(i): # if 'i' is an integer...
print("{}th Percentile: {}".format(k,li[int(i)-1]))
else:
i_down = int(i)
i_up = int(i)+1
print("{}th Percentile: {:.1f}".format(k,mean([li[i_down-1],li[i_up-1]])))
def revperc(v,li):
if v < min(li) or v > max(li): return print("OOPS! Invalid value. Ensure to select one that is in the range of the data")
li.sort()
xli = sorted([x for x in li if x < v]) # Number of data < value
x = len(xli) # " " "
yli = [y for y in li if y == v] # Number of times value shows up in the passed list
y = len(yli) # " " "
n = len(li) # lenght of entire list
k = round((x + 0.5*y)/n*100)
print("{} is the {}th Percentile".format(v,k))
def stats(li):
# Q1 ~ 25th percentile; Q2 ~ 50th percentile and median; Q3 ~ 75th percentile;
# sort the list from smallest to largest
# if len(li) of a quartile == 0, it is the mean of the 2 most-central points
li.sort() # orders the values from smallest to largest
# [52, 68, 73, 77, 82, 89, 91, 96] --> for list where len == 8, Q2 would be mean(ix3, ix4) --> len(li)/2-1, len(li)/2
# 0 1 2 3 4 5 6 7
# [52, 68, 73, 75, 77, 82, 89, 91, 96, 97] --> for list where len == 8, Q2 would be mean(ix3, ix4) --> len(li)/2-1, len(li)/2
# 0 1 2 3 4 5 6 7 8 9
# [52, 68, 73, 75, 77, 82, 91, 96, 97] --> for list where len == 8, Q2 would be mean(ix3, ix4) --> len(li)/2-1, len(li)/2
# 0 1 2 3 4 5 6 7 8
# rli = sorted([random.randint(20,100) for x in range(20)])
# feb_tmax = [tmax for y in clmt if type(y) == int for m in clmt[y] if m in clmt[y] and m == 2 for tmax in clmt[y][m]["tmax"] if len(clmt[y][m]["tmax"]) > excludemonth]
L1 = li[:-1 * int(len(li)/2)]
L3 = li[-1 * int(len(li)/2):]
if len(li) % 2 == 0 and len(li)/2 % 2 == 0: # indicates an even number in the set whose mean is also an even number
Q1 = mean([L1[int(len(L1)/2)-1],L1[int(len(L1)/2)]])
Q2 = mean([li[int(len(li)/2)-1],li[int(len(li)/2)]])
Q3 = mean([L3[int(len(L1)/2)-1],L3[int(len(L1)/2)]])
else:
if len(li) % 2 == 0: # indicates an even number in the set whose mean is an odd number
Q2 = mean([li[int(len(li)/2)-1],li[int(len(li)/2)]])
Q3 = L3[int(len(L3)/2)]
else:
Q2 = li[int(len(li)/2)] # odd number of items in list
Q3 = L3[int(len(L3)/2)-1]
Q1 = L1[int(len(L1)/2)]
IQR = Q3 - Q1
M = mean(li)
PSDV = pstdev(li)
colwidth = max(len(str(x)) for x in [Q1,Q2,Q3])
print("Stats")
print("-----")
print(" {:^{cwid}} {:^{cwid}} {:^{cwid}}".format("Q1","Q2","Q3",cwid=colwidth))
print(" {:-^{cwid}} {:-^{cwid}} {:-^{cwid}}".format("","","",cwid=colwidth))
print(" {:^{cwid}} {:^{cwid}} {:^{cwid}}".format(Q1,Q2,Q3,cwid=colwidth))
print("-----")
print("Mean: {:.1f}".format(M),end="")
print("; PSTDEV: +/- {:.1f}".format(PSDV))
print("1STDEV Range: [ {:.1f}, {:.1f} ]".format(M-PSDV,M+PSDV),end="")
print("; Values w/in 1PSTDEV: {:.1f}%".format(len([x for x in li if x >= M-PSDV and x <= M+PSDV])/len(li)*100))
print("2STDEV Range: [ {:.1f}, {:.1f} ]".format(M-2*PSDV,M+2*PSDV),end="")
print("; Values between 1 & 2PSTDEV: {:.1f}%".format((len([x for x in li if x >= M-2*PSDV and x <= M+2*PSDV])-len([x for x in li if x >= M-PSDV and x <= M+PSDV]))/len(li)*100))
#print("Values w/in range (Q1,Q3]: {:.1f}%".format(len([x for x in li if x <= Q3 and x > Q1])/len(li)*100))
print("IQR (Q3-Q1): {}".format(IQR),end="")
print("; Range of Potential Outliers: < {}; > {}".format(Q1-1.5*IQR,Q3+1.5*IQR)) if min(li) < Q1-1.5*IQR or max(li) > Q3+1.5*IQR else print("; * No Outliers")
print("Potential Outliers: QTY {}; {}".format(len([x for x in li if x < Q1-1.5*IQR or x > Q3+1.5*IQR]),[x for x in li if x < Q1-1.5*IQR or x > Q3+1.5*IQR])) if len([x for x in li if x < Q1-1.5*IQR or x > Q3+1.5*IQR]) > 0 else print("")
def histogram(li):
li.sort()
li_set = sorted(list(set(li)))
d = {}
for x in li:
if x not in d: d[x] = 1
else: d[x] += 1
max_rows = max(amt for amt in d)
print("Temperature","Frequency",sep=",")
for x in li_set: print("{}".format(x),"{}".format(d[x]),sep=",")
class DayRecord:
"""Parses each line of date-specific data; not used by user"""
# int(each[5][0:4])][int(each[5][5:7])][int(each[5][8:10])
def __init__(self,raw):
self.stationid = raw[0]
self.station_name = raw[1]
self.station_lat = raw[2]
self.station_lon = raw[3]
self.station_elev = raw[4]
ry = int(raw[5][0:4])
rm = int(raw[5][5:7])
rd = int(raw[5][8:10])
self.daystr = raw[5]
self.entryday = datetime.date(ry,rm,rd)
# PRCP - Precipitation
self.prcp = raw[6]
flags_prcp = raw[7].split(",")
self.prcpM, self.prcpQ, self.prcpS, self.prcpT = attchk(flags_prcp)
if self.prcpQ in ignoreflags and self.prcp not in ["9999","-9999",""] and float(self.prcp) > 0:
if round(float(self.prcp),2) not in clmt_vars_days["prcp"]:
clmt_vars_days["prcp"][round(float(self.prcp),2)] = []
clmt_vars_days["prcp"][round(float(self.prcp),2)].append(self.entryday)
# SNOW - Snow
self.snow = raw[8]
flags_snow = raw[9].split(",")
self.snowM, self.snowQ, self.snowS, self.snowT = attchk(flags_snow)
if self.snowQ in ignoreflags and self.snow not in ["9999","-9999",""] and float(self.snow) > 0:
if round(float(self.snow),1) not in clmt_vars_days["snow"]:
clmt_vars_days["snow"][round(float(self.snow),1)] = []
clmt_vars_days["snow"][round(float(self.snow),1)].append(self.entryday)
# SNWD - Snow Depth
self.snwd = raw[10]
flags_snwd = raw[11].split(",")
self.snwdM, self.snwdQ, self.snwdS, self.snwdT = attchk(flags_snwd)
if self.snwdQ in ignoreflags and self.snwd not in ["9999","-9999",""] and float(self.snwd) > 0:
if round(float(self.snwd),1) not in clmt_vars_days["snwd"]:
clmt_vars_days["snwd"][round(float(self.snwd),1)] = []
clmt_vars_days["snwd"][round(float(self.snwd),1)].append(self.entryday)
# TMAX - Maximum Temperature
self.tmax = raw[12]
flags_tmax = raw[13].split(",")
self.tmaxM, self.tmaxQ, self.tmaxS, self.tmaxT = attchk(flags_tmax)
if self.tmaxQ in ignoreflags and self.tmax not in ["9999","-9999",""]:
if int(self.tmax) not in clmt_vars_days["tmax"]:
clmt_vars_days["tmax"][int(self.tmax)] = []
clmt_vars_days["tmax"][int(self.tmax)].append(self.entryday)
# TMIN - Minimum Temperature
self.tmin = raw[14]
flags_tmin = raw[15].split(",")
self.tminM, self.tminQ, self.tminS, self.tminT = attchk(flags_tmin)
if self.tminQ in ignoreflags and self.tmin not in ["9999","-9999",""]:
if int(self.tmin) not in clmt_vars_days["tmin"]:
clmt_vars_days["tmin"][int(self.tmin)] = []
clmt_vars_days["tmin"][int(self.tmin)].append(self.entryday)
# TAVG - Daily Average Temperature
if self.tmaxQ in ignoreflags and self.tmax not in ["9999","-9999",""] and self.tminQ in ignoreflags and self.tmin not in ["9999","-9999",""]:
tempavg = round(mean([int(self.tmax),int(self.tmin)]),1)
if tempavg not in clmt_vars_days["tavg"]:
clmt_vars_days["tavg"][tempavg] = []
clmt_vars_days["tavg"][tempavg].append(self.entryday)
def clmtAnalyze(filename,**CITY):
"""Initializes the build of city & session-specific climate dictionaries;
Required for the successful use of the script.
clmtAnalzye(filename, **{city=str})
REQUIRED: filename --> str version of the filename (a csv) of interest.
OPT **kwargs: city=str --> Dictates output of the city-name. This is
useful if multiple stations are compiled
together to represent the data as it wouldn't
be recommended to use a singular station's name
if it isn't a complete representation of the
data.
"""
if os.path.isfile(filename) == False: return print('"{}" not found! Try again!'.format(filename))
global clmt
global metclmt
global FILE
global clmt_vars_days
global clmt_vars_months
global station_ids
FILE = filename
clmt = {}
metclmt = {}
clmt_vars_days = {"prcp":{},"snow":{},"snwd":{},"tavg":{},"tmax":{},"tmin":{}}
clmt_vars_months = {"prcp":{},"prcpDAYS":{},"snow":{},"snowDAYS":{},"snwd":{},"snwdDAYS":{},"tavg":{},"tmax":{},"tmin":{}}
station_ids = []
START = time()
print("*** Script Running. Please Wait ***")
def statbuild(y,m,d): # Will run through if clmt[y][m][d] doesn't exist
# YEAR and MONTH - Additional keys
if "recordqty" not in clmt[y]: clmt[y]["recordqty"] = 1
else: clmt[y]["recordqty"] += 1
if "recordqty" not in clmt[y][m]: clmt[y][m]["recordqty"] = 1
else: clmt[y][m]["recordqty"] += 1
if "prcp" not in clmt[y]:
clmt[y]["prcp"] = []
clmt[y]["prcpDAYS"] = 0
clmt[y]["prcpPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]],"month_min":[999,[]]}
if "prcp" not in clmt[y][m]:
clmt[y][m]["prcp"] = []
clmt[y][m]["prcpDAYS"] = 0
clmt[y][m]["prcpPROP"] = {"day_max":[-1,[]]}
if clmt[y][m][d].prcpQ in ignoreflags and clmt[y][m][d].prcp not in ["9999","-9999",""]:
if float(clmt[y][m][d].prcp) > 0:
clmt[y]["prcp"].append(float(clmt[y][m][d].prcp))
if round(float(clmt[y][m][d].prcp),2) == clmt[y]["prcpPROP"]["day_max"][0]:
clmt[y]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].prcp),2) > clmt[y]["prcpPROP"]["day_max"][0]:
clmt[y]["prcpPROP"]["day_max"][0] = round(float(clmt[y][m][d].prcp),2)
clmt[y]["prcpPROP"]["day_max"][1] = []
clmt[y]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
clmt[y][m]["prcp"].append(float(clmt[y][m][d].prcp))
if round(float(clmt[y][m][d].prcp),2) == clmt[y][m]["prcpPROP"]["day_max"][0]:
clmt[y][m]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].prcp),2) > clmt[y][m]["prcpPROP"]["day_max"][0]:
clmt[y][m]["prcpPROP"]["day_max"][0] = round(float(clmt[y][m][d].prcp),2)
clmt[y][m]["prcpPROP"]["day_max"][1] = []
clmt[y][m]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
if float(clmt[y][m][d].prcp) > 0 or clmt[y][m][d].prcpM == "T":
clmt[y]["prcpDAYS"] += 1
clmt[y][m]["prcpDAYS"] += 1
if "snow" not in clmt[y]:
clmt[y]["snow"] = []
clmt[y]["snowDAYS"] = 0
clmt[y]["snowPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]]}
if "snow" not in clmt[y][m]:
clmt[y][m]["snow"] = []
clmt[y][m]["snowDAYS"] = 0
clmt[y][m]["snowPROP"] = {"day_max":[-1,[]]}
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow not in ["9999","-9999",""]:
if float(clmt[y][m][d].snow) > 0:
clmt[y]["snow"].append(float(clmt[y][m][d].snow))
if round(float(clmt[y][m][d].snow),1) == clmt[y]["snowPROP"]["day_max"][0]:
clmt[y]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snow),1) > clmt[y]["snowPROP"]["day_max"][0]:
clmt[y]["snowPROP"]["day_max"][0] = round(float(clmt[y][m][d].snow),1)
clmt[y]["snowPROP"]["day_max"][1] = []
clmt[y]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
clmt[y][m]["snow"].append(float(clmt[y][m][d].snow))
if round(float(clmt[y][m][d].snow),1) == clmt[y][m]["snowPROP"]["day_max"][0]:
clmt[y][m]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snow),1) > clmt[y][m]["snowPROP"]["day_max"][0]:
clmt[y][m]["snowPROP"]["day_max"][0] = round(float(clmt[y][m][d].snow),1)
clmt[y][m]["snowPROP"]["day_max"][1] = []
clmt[y][m]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
if float(clmt[y][m][d].snow) > 0 or clmt[y][m][d].snowM == "T":
clmt[y]["snowDAYS"] += 1
clmt[y][m]["snowDAYS"] += 1
if "snwd" not in clmt[y]:
clmt[y]["snwd"] = []
clmt[y]["snwdDAYS"] = 0
clmt[y]["snwdPROP"] = {"day_max":[-1,[]]}
if "snwd" not in clmt[y][m]:
clmt[y][m]["snwd"] = []
clmt[y][m]["snwdDAYS"] = 0
clmt[y][m]["snwdPROP"] = {"day_max":[-1,[]]}
if clmt[y][m][d].snwdQ in ignoreflags and clmt[y][m][d].snwd not in ["9999","-9999",""]:
if float(clmt[y][m][d].snwd) > 0:
clmt[y]["snwd"].append(float(clmt[y][m][d].snwd))
if round(float(clmt[y][m][d].snwd),1) == clmt[y]["snwdPROP"]["day_max"][0]:
clmt[y]["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snwd),1) > clmt[y]["snwdPROP"]["day_max"][0]:
clmt[y]["snwdPROP"]["day_max"][0] = round(float(clmt[y][m][d].snwd),1)
clmt[y]["snwdPROP"]["day_max"][1] = []
clmt[y]["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
clmt[y][m]["snwd"].append(float(clmt[y][m][d].snwd))
if round(float(clmt[y][m][d].snwd),1) == clmt[y][m]["snwdPROP"]["day_max"][0]:
clmt[y][m]["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snwd),1) > clmt[y][m]["snwdPROP"]["day_max"][0]:
clmt[y][m]["snwdPROP"]["day_max"][0] = round(float(clmt[y][m][d].snwd),1)
clmt[y][m]["snwdPROP"]["day_max"][1] = []
clmt[y][m]["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
if float(clmt[y][m][d].snwd) > 0 or clmt[y][m][d].snwdM == "T":
clmt[y]["snwdDAYS"] += 1
clmt[y][m]["snwdDAYS"] += 1
if "tmax" not in clmt[y]:
clmt[y]["tempAVGlist"] = []
clmt[y]["tmax"] = []
clmt[y]["tmaxPROP"] = {"day_max":[-999,[]],"day_min":[999,[]],"month_AVG_max":[-999,[]],"month_AVG_min":[999,[]]}
if "tmax" not in clmt[y][m]:
clmt[y][m]["tempAVGlist"] = []
clmt[y][m]["tmax"] = []
clmt[y][m]["tmaxPROP"] = {"day_max":[-999,[]],"day_min":[999,[]]}
if "tmin" not in clmt[y]:
clmt[y]["tmin"] = []
clmt[y]["tminPROP"] = {"day_max":[-999,[]],"day_min":[999,[]],"month_AVG_max":[-999,[]],"month_AVG_min":[999,[]]}
if "tmin" not in clmt[y][m]:
clmt[y][m]["tmin"] = []
clmt[y][m]["tminPROP"] = {"day_max":[-999,[]],"day_min":[999,[]]}
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""]:
if (clmt[y][m][d].tmin != "" and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin)) or clmt[y][m][d].tmin == "":
clmt[y]["tmax"].append(int(clmt[y][m][d].tmax))
clmt[y][m]["tmax"].append(int(clmt[y][m][d].tmax))
if int(clmt[y][m][d].tmax) == clmt[y]["tmaxPROP"]["day_max"][0]:
clmt[y]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) > clmt[y]["tmaxPROP"]["day_max"][0]:
clmt[y]["tmaxPROP"]["day_max"][0] = int(clmt[y][m][d].tmax)
clmt[y]["tmaxPROP"]["day_max"][1] = []
clmt[y]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == clmt[y]["tmaxPROP"]["day_min"][0]:
clmt[y]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) < clmt[y]["tmaxPROP"]["day_min"][0]:
clmt[y]["tmaxPROP"]["day_min"][0] = int(clmt[y][m][d].tmax)
clmt[y]["tmaxPROP"]["day_min"][1] = []
clmt[y]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == clmt[y][m]["tmaxPROP"]["day_max"][0]:
clmt[y][m]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) > clmt[y][m]["tmaxPROP"]["day_max"][0]:
clmt[y][m]["tmaxPROP"]["day_max"][0] = int(clmt[y][m][d].tmax)
clmt[y][m]["tmaxPROP"]["day_max"][1] = []
clmt[y][m]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == clmt[y][m]["tmaxPROP"]["day_min"][0]:
clmt[y][m]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) < clmt[y][m]["tmaxPROP"]["day_min"][0]:
clmt[y][m]["tmaxPROP"]["day_min"][0] = int(clmt[y][m][d].tmax)
clmt[y][m]["tmaxPROP"]["day_min"][1] = []
clmt[y][m]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
if clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""]:
if (clmt[y][m][d].tmax != "" and int(clmt[y][m][d].tmin) <= int(clmt[y][m][d].tmax)) or clmt[y][m][d].tmax == "":
clmt[y]["tmin"].append(int(clmt[y][m][d].tmin))
clmt[y][m]["tmin"].append(int(clmt[y][m][d].tmin))
if int(clmt[y][m][d].tmin) == clmt[y]["tminPROP"]["day_max"][0]:
clmt[y]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) > clmt[y]["tminPROP"]["day_max"][0]:
clmt[y]["tminPROP"]["day_max"][0] = int(clmt[y][m][d].tmin)
clmt[y]["tminPROP"]["day_max"][1] = []
clmt[y]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == clmt[y]["tminPROP"]["day_min"][0]:
clmt[y]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) < clmt[y]["tminPROP"]["day_min"][0]:
clmt[y]["tminPROP"]["day_min"][0] = int(clmt[y][m][d].tmin)
clmt[y]["tminPROP"]["day_min"][1] = []
clmt[y]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == clmt[y][m]["tminPROP"]["day_max"][0]:
clmt[y][m]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) > clmt[y][m]["tminPROP"]["day_max"][0]:
clmt[y][m]["tminPROP"]["day_max"][0] = int(clmt[y][m][d].tmin)
clmt[y][m]["tminPROP"]["day_max"][1] = []
clmt[y][m]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == clmt[y][m]["tminPROP"]["day_min"][0]:
clmt[y][m]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) < clmt[y][m]["tminPROP"]["day_min"][0]:
clmt[y][m]["tminPROP"]["day_min"][0] = int(clmt[y][m][d].tmin)
clmt[y][m]["tminPROP"]["day_min"][1] = []
clmt[y][m]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""] and clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""] and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin):
clmt[y]["tempAVGlist"].append(int(clmt[y][m][d].tmax))
clmt[y]["tempAVGlist"].append(int(clmt[y][m][d].tmin))
clmt[y][m]["tempAVGlist"].append(int(clmt[y][m][d].tmax))
clmt[y][m]["tempAVGlist"].append(int(clmt[y][m][d].tmin))
with open(filename,newline="") as f:
print("--- COMPILING DICTIONARIES ---")
csvfile = csv.reader(f, delimiter=',')
for each in csvfile:
if each[0] in ["STATION",'"STATION"']:
pass
else:
if each[0] not in station_ids: station_ids.append(each[0])
if "station" not in clmt:
if "city" in CITY: clmt["station_name"] = CITY["city"]
else: clmt["station_name"] = each[1]
clmt["station"] = each[0]
print("--- City: {} ---".format(clmt["station_name"]))
clmt["coordinates"] = "{}, {}".format(each[2],each[3])
clmt["elevation"] = each[4]
if "station" not in metclmt:
if "city" in CITY: metclmt["station_name"] = CITY["city"]
else: metclmt["station_name"] = each[1]
metclmt["station"] = each[0]
metclmt["coordinates"] = "{}, {}".format(each[2],each[3])
metclmt["elevation"] = each[4]
#if y % 10 == 0: print("{},".format(each[5][0:4]),end=" ")
y = int(each[5][0:4])
m = int(each[5][5:7])
d = int(each[5][8:10])
if y not in clmt: clmt[y] = {} # YEAR
if m not in clmt[y]: clmt[y][m] = {} # MONTH
# DAY Record stuff
if d in clmt[y][m]: # This will replace the existing DayRecord if the entire entry was blank
if all(v == "" for v in [clmt[y][m][d].prcp,clmt[y][m][d].snow,clmt[y][m][d].snwd,clmt[y][m][d].tmax,clmt[y][m][d].tmin]):
clmt[y][m][d].stationid = each[0]
clmt[y][m][d].station_name = each[1]
clmt[y][m][d].station_lat = each[2]
clmt[y][m][d].station_lon = each[3]
clmt[y][m][d].station_elev = each[4]
clmt[y][m][d].prcp = each[6]
flags_prcp = each[7].split(",")
clmt[y][m][d].prcpM, clmt[y][m][d].prcpQ, clmt[y][m][d].prcpS, clmt[y][m][d].prcpT = attchk(flags_prcp)
if clmt[y][m][d].prcp not in ["","-9999","9999"] and clmt[y][m][d].prcpQ in ignoreflags:
if float(clmt[y][m][d].prcp) > 0:
clmt[y]["prcp"].append(float(clmt[y][m][d].prcp))
if round(float(clmt[y][m][d].prcp),2) == clmt[y]["prcpPROP"]["day_max"][0]:
clmt[y]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].prcp),2) > clmt[y]["prcpPROP"]["day_max"][0]:
clmt[y]["prcpPROP"]["day_max"][0] = round(float(clmt[y][m][d].prcp),2)
clmt[y]["prcpPROP"]["day_max"][1] = []
clmt[y]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
clmt[y][m]["prcp"].append(float(clmt[y][m][d].prcp))
if round(float(clmt[y][m][d].prcp),2) == clmt[y][m]["prcpPROP"]["day_max"][0]:
clmt[y][m]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].prcp),2) > clmt[y][m]["prcpPROP"]["day_max"][0]:
clmt[y][m]["prcpPROP"]["day_max"][0] = round(float(clmt[y][m][d].prcp),2)
clmt[y][m]["prcpPROP"]["day_max"][1] = []
clmt[y][m]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
if float(clmt[y][m][d].prcp) > 0 or clmt[y][m][d].prcpM == "T":
clmt[y]["prcpDAYS"] += 1
clmt[y][m]["prcpDAYS"] += 1
clmt[y][m][d].snow = each[8]
flags_snow = each[9].split(",")
clmt[y][m][d].snowM, clmt[y][m][d].snowQ, clmt[y][m][d].snowS, clmt[y][m][d].snowT = attchk(flags_snow)
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow not in ["9999","-9999",""]:
if float(clmt[y][m][d].snow) > 0:
clmt[y]["snow"].append(float(clmt[y][m][d].snow))
if round(float(clmt[y][m][d].snow),1) == clmt[y]["snowPROP"]["day_max"][0]:
clmt[y]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snow),1) > clmt[y]["snowPROP"]["day_max"][0]:
clmt[y]["snowPROP"]["day_max"][0] = round(float(clmt[y][m][d].snow),1)
clmt[y]["snowPROP"]["day_max"][1] = []
clmt[y]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
clmt[y][m]["snow"].append(float(clmt[y][m][d].snow))
if round(float(clmt[y][m][d].snow),1) == clmt[y][m]["snowPROP"]["day_max"][0]:
clmt[y][m]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snow),1) > clmt[y][m]["snowPROP"]["day_max"][0]:
clmt[y][m]["snowPROP"]["day_max"][0] = round(float(clmt[y][m][d].snow),1)
clmt[y][m]["snowPROP"]["day_max"][1] = []
clmt[y][m]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
if float(clmt[y][m][d].snow) > 0 or clmt[y][m][d].snowM == "T":
clmt[y]["snowDAYS"] += 1
clmt[y][m]["snowDAYS"] += 1
clmt[y][m][d].snwd = each[10]
flags_snwd = each[11].split(",")
clmt[y][m][d].snwdM, clmt[y][m][d].snwdQ, clmt[y][m][d].snwdS, clmt[y][m][d].snwdT = attchk(flags_snwd)
if clmt[y][m][d].snwdQ in ignoreflags and clmt[y][m][d].snwd not in ["9999","-9999",""]:
if float(clmt[y][m][d].snwd) > 0:
clmt[y]["snwd"].append(float(clmt[y][m][d].snwd))
if round(float(clmt[y][m][d].snwd),1) == clmt[y]["snwdPROP"]["day_max"][0]:
clmt[y]["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snwd),1) > clmt[y]["snwdPROP"]["day_max"][0]:
clmt[y]["snwdPROP"]["day_max"][0] = round(float(clmt[y][m][d].snwd),1)
clmt[y]["snwdPROP"]["day_max"][1] = []
clmt[y]["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
clmt[y][m]["snwd"].append(float(clmt[y][m][d].snwd))
if round(float(clmt[y][m][d].snwd),1) == clmt[y][m]["snwdPROP"]["day_max"][0]:
clmt[y][m]["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snwd),1) > clmt[y][m]["snwdPROP"]["day_max"][0]:
clmt[y][m]["snwdPROP"]["day_max"][0] = round(float(clmt[y][m][d].snwd),1)
clmt[y][m]["snwdPROP"]["day_max"][1] = []
clmt[y][m]["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
if float(clmt[y][m][d].snwd) > 0 or clmt[y][m][d].snwdM == "T":
clmt[y]["snwdDAYS"] += 1
clmt[y][m]["snwdDAYS"] += 1
clmt[y][m][d].tmax = each[12]
flags_tmax = each[13].split(",")
clmt[y][m][d].tmaxM, clmt[y][m][d].tmaxQ, clmt[y][m][d].tmaxS, clmt[y][m][d].tmaxT = attchk(flags_tmax)
clmt[y][m][d].tmin = each[14]
flags_tmin = each[15].split(",")
clmt[y][m][d].tminM, clmt[y][m][d].tminQ, clmt[y][m][d].tminS, clmt[y][m][d].tminT = attchk(flags_tmin)
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""]:
if (clmt[y][m][d].tmin != "" and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin)) or clmt[y][m][d].tmin == "":
clmt[y]["tmax"].append(int(clmt[y][m][d].tmax))
clmt[y][m]["tmax"].append(int(clmt[y][m][d].tmax))
if int(clmt[y][m][d].tmax) == clmt[y]["tmaxPROP"]["day_max"][0]:
clmt[y]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) > clmt[y]["tmaxPROP"]["day_max"][0]:
clmt[y]["tmaxPROP"]["day_max"][0] = int(clmt[y][m][d].tmax)
clmt[y]["tmaxPROP"]["day_max"][1] = []
clmt[y]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == clmt[y]["tmaxPROP"]["day_min"][0]:
clmt[y]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) < clmt[y]["tmaxPROP"]["day_min"][0]:
clmt[y]["tmaxPROP"]["day_min"][0] = int(clmt[y][m][d].tmax)
clmt[y]["tmaxPROP"]["day_min"][1] = []
clmt[y]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == clmt[y][m]["tmaxPROP"]["day_max"][0]:
clmt[y][m]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) > clmt[y][m]["tmaxPROP"]["day_max"][0]:
clmt[y][m]["tmaxPROP"]["day_max"][0] = int(clmt[y][m][d].tmax)
clmt[y][m]["tmaxPROP"]["day_max"][1] = []
clmt[y][m]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == clmt[y][m]["tmaxPROP"]["day_min"][0]:
clmt[y][m]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) < clmt[y][m]["tmaxPROP"]["day_min"][0]:
clmt[y][m]["tmaxPROP"]["day_min"][0] = int(clmt[y][m][d].tmax)
clmt[y][m]["tmaxPROP"]["day_min"][1] = []
clmt[y][m]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
if clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""]:
if (clmt[y][m][d].tmax != "" and int(clmt[y][m][d].tmin) <= int(clmt[y][m][d].tmax)) or clmt[y][m][d].tmax == "":
clmt[y]["tmin"].append(int(clmt[y][m][d].tmin))
clmt[y][m]["tmin"].append(int(clmt[y][m][d].tmin))
if int(clmt[y][m][d].tmin) == clmt[y]["tminPROP"]["day_max"][0]:
clmt[y]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) > clmt[y]["tminPROP"]["day_max"][0]:
clmt[y]["tminPROP"]["day_max"][0] = int(clmt[y][m][d].tmin)
clmt[y]["tminPROP"]["day_max"][1] = []
clmt[y]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == clmt[y]["tminPROP"]["day_min"][0]:
clmt[y]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) < clmt[y]["tminPROP"]["day_min"][0]:
clmt[y]["tminPROP"]["day_min"][0] = int(clmt[y][m][d].tmin)
clmt[y]["tminPROP"]["day_min"][1] = []
clmt[y]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == clmt[y][m]["tminPROP"]["day_max"][0]:
clmt[y][m]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) > clmt[y][m]["tminPROP"]["day_max"][0]:
clmt[y][m]["tminPROP"]["day_max"][0] = int(clmt[y][m][d].tmin)
clmt[y][m]["tminPROP"]["day_max"][1] = []
clmt[y][m]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == clmt[y][m]["tminPROP"]["day_min"][0]:
clmt[y][m]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) < clmt[y][m]["tminPROP"]["day_min"][0]:
clmt[y][m]["tminPROP"]["day_min"][0] = int(clmt[y][m][d].tmin)
clmt[y][m]["tminPROP"]["day_min"][1] = []
clmt[y][m]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""] and clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""] and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin):
clmt[y]["tempAVGlist"].append(int(clmt[y][m][d].tmax))
clmt[y]["tempAVGlist"].append(int(clmt[y][m][d].tmin))
clmt[y][m]["tempAVGlist"].append(int(clmt[y][m][d].tmax))
clmt[y][m]["tempAVGlist"].append(int(clmt[y][m][d].tmin))
else:
clmt[y][m][d] = DayRecord(each)
statbuild(y,m,d)
# MONTHLY STATS
for y in [YR for YR in clmt if type(YR) == int]:
for m in [MO for MO in clmt[y] if type(MO) == int]:
# PRCP
if round(sum(clmt[y][m]["prcp"]),2) not in clmt_vars_months["prcp"]: clmt_vars_months["prcp"][round(sum(clmt[y][m]["prcp"]),2)] = [datetime.date(y,m,1)]
else: clmt_vars_months["prcp"][round(sum(clmt[y][m]["prcp"]),2)].append(datetime.date(y,m,1))
if clmt[y][m]["prcpDAYS"] not in clmt_vars_months["prcpDAYS"]: clmt_vars_months["prcpDAYS"][clmt[y][m]["prcpDAYS"]] = [datetime.date(y,m,1)]
else: clmt_vars_months["prcpDAYS"][clmt[y][m]["prcpDAYS"]].append(datetime.date(y,m,1))
try:
if round(sum(clmt[y][m]["prcp"]),2) == clmt[y]["prcpPROP"]["month_max"][0]:
clmt[y]["prcpPROP"]["month_max"][1].append(m)
elif round(sum(clmt[y][m]["prcp"]),2) > clmt[y]["prcpPROP"]["month_max"][0]:
clmt[y]["prcpPROP"]["month_max"][0] = round(sum(clmt[y][m]["prcp"]),2)
clmt[y]["prcpPROP"]["month_max"][1] = []
clmt[y]["prcpPROP"]["month_max"][1].append(m)
if round(sum(clmt[y][m]["prcp"]),2) == clmt[y]["prcpPROP"]["month_min"][0]:
clmt[y]["prcpPROP"]["month_min"][1].append(m)
elif round(sum(clmt[y][m]["prcp"]),2) < clmt[y]["prcpPROP"]["month_min"][0]:
clmt[y]["prcpPROP"]["month_min"][0] = round(sum(clmt[y][m]["prcp"]),2)
clmt[y]["prcpPROP"]["month_min"][1] = []
clmt[y]["prcpPROP"]["month_min"][1].append(m)
except:
print("*** SKIPPED: Insufficient or erroneous PRCP data - {}-{}".format(y,str(m).zfill(2)))
# SNOW
if round(sum(clmt[y][m]["snow"]),1) not in clmt_vars_months["snow"]: clmt_vars_months["snow"][round(sum(clmt[y][m]["snow"]),1)] = [datetime.date(y,m,1)]
else: clmt_vars_months["snow"][round(sum(clmt[y][m]["snow"]),1)].append(datetime.date(y,m,1))
if clmt[y][m]["snowDAYS"] not in clmt_vars_months["snowDAYS"]: clmt_vars_months["snowDAYS"][clmt[y][m]["snowDAYS"]] = [datetime.date(y,m,1)]
else: clmt_vars_months["snowDAYS"][clmt[y][m]["snowDAYS"]].append(datetime.date(y,m,1))
#if sum(clmt[y][m]["snwd"]) not in clmt_vars_months["snwd"]: clmt_vars_months["snwd"][sum(clmt[y][m]["snwd"])] = [datetime.date(y,m,1)]
#else: clmt_vars_months["snwd"][sum(clmt[y][m]["snwd"])].append(datetime.date(y,m,1))
try:
if round(sum(clmt[y][m]["snow"]),1) == clmt[y]["snowPROP"]["month_max"][0]:
clmt[y]["snowPROP"]["month_max"][1].append(m)
elif round(sum(clmt[y][m]["snow"]),1) > clmt[y]["snowPROP"]["month_max"][0]:
clmt[y]["snowPROP"]["month_max"][0] = round(sum(clmt[y][m]["snow"]),1)
clmt[y]["snowPROP"]["month_max"][1] = []
clmt[y]["snowPROP"]["month_max"][1].append(m)
except:
print("*** SKIPPED: Insufficient or erroneous SNOW data - {}-{}".format(y,str(m).zfill(2)))
# SNWD
if clmt[y][m]["snwdDAYS"] not in clmt_vars_months["snwdDAYS"]: clmt_vars_months["snwdDAYS"][clmt[y][m]["snwdDAYS"]] = [datetime.date(y,m,1)]
else: clmt_vars_months["snwdDAYS"][clmt[y][m]["snwdDAYS"]].append(datetime.date(y,m,1))
# TMAX
if len(clmt[y][m]["tmax"]) > excludemonth:
if round(mean(clmt[y][m]["tmax"]),1) not in clmt_vars_months["tmax"]: clmt_vars_months["tmax"][round(mean(clmt[y][m]["tmax"]),1)] = [datetime.date(y,m,1)]
else: clmt_vars_months["tmax"][round(mean(clmt[y][m]["tmax"]),1)].append(datetime.date(y,m,1))
try:
if round(mean(clmt[y][m]["tmax"]),1) == clmt[y]["tmaxPROP"]["month_AVG_max"][0]:
clmt[y]["tmaxPROP"]["month_AVG_max"][1].append(m)
elif round(mean(clmt[y][m]["tmax"]),1) > clmt[y]["tmaxPROP"]["month_AVG_max"][0]:
clmt[y]["tmaxPROP"]["month_AVG_max"][0] = round(mean(clmt[y][m]["tmax"]),1)
clmt[y]["tmaxPROP"]["month_AVG_max"][1] = []
clmt[y]["tmaxPROP"]["month_AVG_max"][1].append(m)
if round(mean(clmt[y][m]["tmax"]),1) == clmt[y]["tmaxPROP"]["month_AVG_min"][0]:
clmt[y]["tmaxPROP"]["month_AVG_min"][1].append(m)
elif round(mean(clmt[y][m]["tmax"]),1) < clmt[y]["tmaxPROP"]["month_AVG_min"][0]:
clmt[y]["tmaxPROP"]["month_AVG_min"][0] = round(mean(clmt[y][m]["tmax"]),1)
clmt[y]["tmaxPROP"]["month_AVG_min"][1] = []
clmt[y]["tmaxPROP"]["month_AVG_min"][1].append(m)
except:
print("*** SKIPPED: Insufficient or erroneous TMAX data - {}-{}".format(y,str(m).zfill(2)))
# TMIN
if len(clmt[y][m]["tmin"]) > excludemonth:
if round(mean(clmt[y][m]["tmin"]),1) not in clmt_vars_months["tmin"]: clmt_vars_months["tmin"][round(mean(clmt[y][m]["tmin"]),1)] = [datetime.date(y,m,1)]
else: clmt_vars_months["tmin"][round(mean(clmt[y][m]["tmin"]),1)].append(datetime.date(y,m,1))
try:
if round(mean(clmt[y][m]["tmin"]),1) == clmt[y]["tminPROP"]["month_AVG_max"][0]:
clmt[y]["tminPROP"]["month_AVG_max"][1].append(m)
elif round(mean(clmt[y][m]["tmin"]),1) > clmt[y]["tminPROP"]["month_AVG_max"][0]:
clmt[y]["tminPROP"]["month_AVG_max"][0] = round(mean(clmt[y][m]["tmin"]),1)
clmt[y]["tminPROP"]["month_AVG_max"][1] = []
clmt[y]["tminPROP"]["month_AVG_max"][1].append(m)
if round(mean(clmt[y][m]["tmin"]),1) == clmt[y]["tminPROP"]["month_AVG_min"][0]:
clmt[y]["tminPROP"]["month_AVG_min"][1].append(m)
elif round(mean(clmt[y][m]["tmin"]),1) < clmt[y]["tminPROP"]["month_AVG_min"][0]:
clmt[y]["tminPROP"]["month_AVG_min"][0] = round(mean(clmt[y][m]["tmin"]),1)
clmt[y]["tminPROP"]["month_AVG_min"][1] = []
clmt[y]["tminPROP"]["month_AVG_min"][1].append(m)
except:
print("*** SKIPPED: Insufficient or erroneous TMIN data - {}-{}".format(y,str(m).zfill(2)))
if len(clmt[y][m]["tempAVGlist"]) > excludemonth * 2:
if round(mean(clmt[y][m]["tempAVGlist"]),1) not in clmt_vars_months["tavg"]: clmt_vars_months["tavg"][round(mean(clmt[y][m]["tempAVGlist"]),1)] = [datetime.date(y,m,1)]
else: clmt_vars_months["tavg"][round(mean(clmt[y][m]["tempAVGlist"]),1)].append(datetime.date(y,m,1))
for YYYY in sorted([Y for Y in clmt if type(Y) == int]): # THIS IS THE CURRENT PROBLEM...NOT READING IN JAN/FEB DATA?
if YYYY not in metclmt and any(MONTH >= 3 for MONTH in clmt[YYYY] if type(MONTH) == int):
metclmt[YYYY] = {}
for MM in sorted([M for M in clmt[YYYY] if type(M) == int]):
if MM <= 2:
if YYYY-1 in metclmt: metclmt[YYYY-1][MM] = clmt[YYYY][MM]
else:
metclmt[YYYY][MM] = clmt[YYYY][MM]
for YYYY in [YEAR for YEAR in metclmt if type(YEAR) == int]:
for s in ["spring","summer","fall","winter"]:
metclmt[YYYY][s] = {}
if s == "spring": metclmt[YYYY][s]["valid"] = [3,4,5]
elif s == "summer": metclmt[YYYY][s]["valid"] = [6,7,8]
elif s == "fall": metclmt[YYYY][s]["valid"] = [9,10,11]
elif s == "winter": metclmt[YYYY][s]["valid"] = [12,1,2]
else: return print("SEASON ERROR! Programmer! Check the seasons!")
for y in [Y for Y in metclmt if type(Y) == int]:
# PRCP
metclmt[y]["recordqty"] = sum(metclmt[y][m]["recordqty"] for m in metclmt[y] if type(m) == int)
#input("year = {}; recordqty = {}".format(y,metclmt[y]["recordqty"]))
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["recordqty"] = sum(metclmt[y][m]["recordqty"] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"])
metclmt[y]["prcp"] = []
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["prcp"] = []
metclmt[y]["prcp"].extend(r for m in metclmt[y].keys() if type(m) == int for r in metclmt[y][m]["prcp"])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["prcp"].extend(r for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for r in metclmt[y][m]["prcp"])
metclmt[y]["prcpDAYS"] = sum(metclmt[y][m]["prcpDAYS"] for m in metclmt[y] if type(m) == int)
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["prcpDAYS"] = sum(metclmt[y][m]["prcpDAYS"] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"])
metclmt[y]["prcpPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]],"month_min":[999,[]]}
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["prcpPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]],"month_min":[999,[]]}
if len(metclmt[y]["prcp"]) > 0: metclmt[y]["prcpPROP"]["day_max"][0] = round(max(metclmt[y]["prcp"]),2)
for s in ["spring","summer","fall","winter"]:
if len(metclmt[y][s]["prcp"]) > 0: metclmt[y][s]["prcpPROP"]["day_max"][0] = round(max(metclmt[y][s]["prcp"]),2)
metclmt[y]["prcpPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].prcpQ in ignoreflags and metclmt[y][m][d].prcp not in ["","-9999","9999"] and round(float(metclmt[y][m][d].prcp),2) == metclmt[y]["prcpPROP"]["day_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["prcpPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].prcpQ in ignoreflags and metclmt[y][m][d].prcp not in ["","-9999","9999"] and round(float(metclmt[y][m][d].prcp),2) == metclmt[y][s]["prcpPROP"]["day_max"][0])
#if y >= 2019: print(y,calendar.month_abbr[m])
metclmt[y]["prcpPROP"]["month_max"][0] = round(max(sum(metclmt[y][m]["prcp"]) for m in metclmt[y] if type(m) == int),2)
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["prcpPROP"]["month_max"][0] = round(max(sum(metclmt[y][m]["prcp"]) for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"]),2)
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
metclmt[y]["prcpPROP"]["month_max"][1].extend(m for m in metclmt[y] if type(m) == int and round(sum(metclmt[y][m]["prcp"]),2) == metclmt[y]["prcpPROP"]["month_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["prcpPROP"]["month_max"][1].extend(m for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and round(sum(metclmt[y][m]["prcp"]),2) == metclmt[y][s]["prcpPROP"]["month_max"][0])
metclmt[y]["prcpPROP"]["month_min"][0] = round(min(sum(metclmt[y][m]["prcp"]) for m in metclmt[y] if type(m) == int),2)
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["prcpPROP"]["month_min"][0] = round(min(sum(metclmt[y][m]["prcp"]) for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"]),2)
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
metclmt[y]["prcpPROP"]["month_min"][1].extend(m for m in metclmt[y] if type(m) == int and round(sum(metclmt[y][m]["prcp"]),2) == metclmt[y]["prcpPROP"]["month_min"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["prcpPROP"]["month_min"][1].extend(m for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and round(sum(metclmt[y][m]["prcp"]),2) == metclmt[y][s]["prcpPROP"]["month_min"][0])
# SNOW
metclmt[y]["snow"] = []
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snow"] = []
metclmt[y]["snow"].extend(r for m in metclmt[y].keys() if type(m) == int for r in metclmt[y][m]["snow"])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snow"].extend(r for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for r in metclmt[y][m]["snow"])
metclmt[y]["snowDAYS"] = sum(metclmt[y][m]["snowDAYS"] for m in metclmt[y] if type(m) == int)
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snowDAYS"] = sum(metclmt[y][m]["snowDAYS"] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"])
metclmt[y]["snowPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]]}
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snowPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]]}
if len(metclmt[y]["snow"]) > 0: metclmt[y]["snowPROP"]["day_max"][0] = round(max(metclmt[y]["snow"]),1)
for s in ["spring","summer","fall","winter"]:
if len(metclmt[y][s]["snow"]) > 0: metclmt[y][s]["snowPROP"]["day_max"][0] = round(max(metclmt[y][s]["snow"]),1)
metclmt[y]["snowPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].snowQ in ignoreflags and metclmt[y][m][d].snow not in ["","-9999","9999"] and round(float(metclmt[y][m][d].snow),1) == metclmt[y]["snowPROP"]["day_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snowPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].snowQ in ignoreflags and metclmt[y][m][d].snow not in ["","-9999","9999"] and round(float(metclmt[y][m][d].snow),1) == metclmt[y][s]["snowPROP"]["day_max"][0])
metclmt[y]["snowPROP"]["month_max"][0] = round(max(sum(metclmt[y][m]["snow"]) for m in metclmt[y] if type(m) == int),1)
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["snowPROP"]["month_max"][0] = round(max(sum(metclmt[y][m]["snow"]) for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"]),1)
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
metclmt[y]["snowPROP"]["month_max"][1].extend(m for m in metclmt[y] if type(m) == int and round(sum(metclmt[y][m]["snow"]),1) == metclmt[y]["snowPROP"]["month_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snowPROP"]["month_max"][1].extend(m for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and round(sum(metclmt[y][m]["snow"]),1) == metclmt[y][s]["snowPROP"]["month_max"][0])
# SNWD
metclmt[y]["snwd"] = []
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snwd"] = []
metclmt[y]["snwd"].extend(r for m in metclmt[y].keys() if type(m) == int for r in metclmt[y][m]["snwd"])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snwd"].extend(r for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for r in metclmt[y][m]["snwd"])
metclmt[y]["snwdDAYS"] = sum(metclmt[y][m]["snwdDAYS"] for m in metclmt[y] if type(m) == int)
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snwdDAYS"] = sum(metclmt[y][m]["snwdDAYS"] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"])
#metclmt[y]["snwdDAYS"] = sum(metclmt[y][m]["snwdDAYS"] for m in metclmt[y] if type(m) == int)
#for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snwdDAYS"] = sum(metclmt[y][m]["snwdDAYS"] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"])
#metclmt[y]["snwdPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]]}
metclmt[y]["snwdPROP"] = {"day_max":[-1,[]]}
#for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snwdPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]]}
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snwdPROP"] = {"day_max":[-1,[]]}
if len(metclmt[y]["snwd"]) > 0: metclmt[y]["snwdPROP"]["day_max"][0] = round(max(metclmt[y]["snwd"]),1)
for s in ["spring","summer","fall","winter"]:
if len(metclmt[y][s]["snwd"]) > 0: metclmt[y][s]["snwdPROP"]["day_max"][0] = round(max(metclmt[y][s]["snwd"]),1)
metclmt[y]["snwdPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].snwdQ in ignoreflags and metclmt[y][m][d].snwd not in ["","-9999","9999"] and round(float(metclmt[y][m][d].snwd),1) == metclmt[y]["snwdPROP"]["day_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snwdPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].snwdQ in ignoreflags and metclmt[y][m][d].snwd not in ["","-9999","9999"] and round(float(metclmt[y][m][d].snwd),1) == metclmt[y][s]["snwdPROP"]["day_max"][0])
#metclmt[y]["snwdPROP"]["month_max"][0] = round(max(sum(metclmt[y][m]["snwd"]) for m in metclmt[y] if type(m) == int),1)
#for s in ["spring","summer","fall","winter"]:
#try: metclmt[y][s]["snwdPROP"]["month_max"][0] = round(max(sum(metclmt[y][m]["snwd"]) for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"]),2)
#except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
#metclmt[y]["snwdPROP"]["month_max"][1].extend(m for m in metclmt[y] if type(m) == int and round(sum(metclmt[y][m]["snwd"]),2) == metclmt[y]["snwdPROP"]["month_max"][0])
#for s in ["spring","summer","fall","winter"]: metclmt[y][s]["snwdPROP"]["month_max"][1].extend(m for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and round(sum(metclmt[y][m]["snwd"]),2) == metclmt[y][s]["snwdPROP"]["month_max"][0])
# TAVG
metclmt[y]["tempAVGlist"] = []
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tempAVGlist"] = []
metclmt[y]["tempAVGlist"].extend(ta for m in metclmt[y].keys() if type(m) == int for ta in metclmt[y][m]["tempAVGlist"])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tempAVGlist"].extend(ta for m in metclmt[y].keys() if type(m) == int and m in metclmt[y][s]["valid"] for ta in metclmt[y][m]["tempAVGlist"])
# TMAX
metclmt[y]["tmax"] = []
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmax"] = []
metclmt[y]["tmax"].extend(tx for m in metclmt[y].keys() if type(m) == int for tx in metclmt[y][m]["tmax"])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmax"].extend(tx for m in metclmt[y].keys() if type(m) == int and m in metclmt[y][s]["valid"] for tx in metclmt[y][m]["tmax"])
metclmt[y]["tmaxPROP"] = {"day_max":[-999,[]],"day_min":[999,[]],"month_AVG_max":[-999,[]],"month_AVG_min":[999,[]]}
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmaxPROP"] = {"day_max":[-999,[]],"day_min":[999,[]],"month_AVG_max":[-999,[]],"month_AVG_min":[999,[]]}
if len(metclmt[y]["tmax"]) > 0:
metclmt[y]["tmaxPROP"]["day_max"][0] = max(metclmt[y]["tmax"])
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["tmaxPROP"]["day_max"][0] = max(metclmt[y][s]["tmax"])
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
metclmt[y]["tmaxPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].tmaxQ in ignoreflags and metclmt[y][m][d].tmax not in ["","-9999","9999"] and int(metclmt[y][m][d].tmax) == metclmt[y]["tmaxPROP"]["day_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmaxPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].tmaxQ in ignoreflags and metclmt[y][m][d].tmax not in ["","-9999","9999"] and int(metclmt[y][m][d].tmax) == metclmt[y][s]["tmaxPROP"]["day_max"][0])
metclmt[y]["tmaxPROP"]["day_min"][0] = min(metclmt[y]["tmax"])
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["tmaxPROP"]["day_min"][0] = min(metclmt[y][s]["tmax"])
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
metclmt[y]["tmaxPROP"]["day_min"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].tmaxQ in ignoreflags and metclmt[y][m][d].tmax not in ["","-9999","9999"] and int(metclmt[y][m][d].tmax) == metclmt[y]["tmaxPROP"]["day_min"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmaxPROP"]["day_min"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].tmaxQ in ignoreflags and metclmt[y][m][d].tmax not in ["","-9999","9999"] and int(metclmt[y][m][d].tmax) == metclmt[y][s]["tmaxPROP"]["day_min"][0])
if any(len(metclmt[y][M]["tmax"]) > excludemonth for M in metclmt[y] if type(M) == int):
metclmt[y]["tmaxPROP"]["month_AVG_max"][0] = round(max(mean(metclmt[y][m]["tmax"]) for m in metclmt[y] if type(m) == int and len(metclmt[y][m]["tmax"]) > excludemonth),1)
metclmt[y]["tmaxPROP"]["month_AVG_max"][1].extend(m for m in metclmt[y] if type(m) == int and len(metclmt[y][m]["tmax"]) > excludemonth and round(mean(metclmt[y][m]["tmax"]),1) == metclmt[y]["tmaxPROP"]["month_AVG_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmaxPROP"]["month_AVG_max"][1].extend(m for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and len(metclmt[y][m]["tmax"]) > excludemonth and round(mean(metclmt[y][m]["tmax"]),1) == metclmt[y][s]["tmaxPROP"]["month_AVG_max"][0])
metclmt[y]["tmaxPROP"]["month_AVG_min"][0] = round(min(mean(metclmt[y][m]["tmax"]) for m in metclmt[y] if type(m) == int and len(metclmt[y][m]["tmax"]) > excludemonth),1)
metclmt[y]["tmaxPROP"]["month_AVG_min"][1].extend(m for m in metclmt[y] if type(m) == int and len(metclmt[y][m]["tmax"]) > excludemonth and round(mean(metclmt[y][m]["tmax"]),1) == metclmt[y]["tmaxPROP"]["month_AVG_min"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmaxPROP"]["month_AVG_min"][1].extend(m for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and len(metclmt[y][m]["tmax"]) > excludemonth and round(mean(metclmt[y][m]["tmax"]),1) == metclmt[y][s]["tmaxPROP"]["month_AVG_min"][0])
for s in ["spring","summer","fall","winter"]:
try:metclmt[y][s]["tmaxPROP"]["month_AVG_max"][0] = round(max(mean(metclmt[y][m]["tmax"]) for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and len(metclmt[y][m]["tmax"]) > excludemonth),1)
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["tmaxPROP"]["month_AVG_min"][0] = round(min(mean(metclmt[y][m]["tmax"]) for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and len(metclmt[y][m]["tmax"]) > excludemonth),1)
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
# TMIN
metclmt[y]["tmin"] = []
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmin"] = []
metclmt[y]["tmin"].extend(tx for m in metclmt[y].keys() if type(m) == int for tx in metclmt[y][m]["tmin"])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tmin"].extend(tx for m in metclmt[y].keys() if type(m) == int and m in metclmt[y][s]["valid"] for tx in metclmt[y][m]["tmin"])
metclmt[y]["tminPROP"] = {"day_max":[-999,[]],"day_min":[999,[]],"month_AVG_max":[-999,[]],"month_AVG_min":[999,[]]}
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tminPROP"] = {"day_max":[-999,[]],"day_min":[999,[]],"month_AVG_max":[-999,[]],"month_AVG_min":[999,[]]}
if len(metclmt[y]["tmin"]) > 0:
metclmt[y]["tminPROP"]["day_max"][0] = max(metclmt[y]["tmin"])
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["tminPROP"]["day_max"][0] = max(metclmt[y][s]["tmin"])
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
metclmt[y]["tminPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].tminQ in ignoreflags and metclmt[y][m][d].tmin not in ["","-9999","9999"] and int(metclmt[y][m][d].tmin) == metclmt[y]["tminPROP"]["day_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tminPROP"]["day_max"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].tminQ in ignoreflags and metclmt[y][m][d].tmin not in ["","-9999","9999"] and int(metclmt[y][m][d].tmin) == metclmt[y][s]["tminPROP"]["day_max"][0])
metclmt[y]["tminPROP"]["day_min"][0] = min(metclmt[y]["tmin"])
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["tminPROP"]["day_min"][0] = min(metclmt[y][s]["tmin"])
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
metclmt[y]["tminPROP"]["day_min"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].tminQ in ignoreflags and metclmt[y][m][d].tmin not in ["","-9999","9999"] and int(metclmt[y][m][d].tmin) == metclmt[y]["tminPROP"]["day_min"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tminPROP"]["day_min"][1].extend(metclmt[y][m][d] for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] for d in metclmt[y][m] if type(d) == int and metclmt[y][m][d].tminQ in ignoreflags and metclmt[y][m][d].tmin not in ["","-9999","9999"] and int(metclmt[y][m][d].tmin) == metclmt[y][s]["tminPROP"]["day_min"][0])
if any(len(metclmt[y][M]["tmin"]) > excludemonth for M in metclmt[y] if type(M) == int):
metclmt[y]["tminPROP"]["month_AVG_max"][0] = round(max(mean(metclmt[y][m]["tmin"]) for m in metclmt[y] if type(m) == int and len(metclmt[y][m]["tmin"]) > excludemonth),1)
metclmt[y]["tminPROP"]["month_AVG_max"][1].extend(m for m in metclmt[y] if type(m) == int and len(metclmt[y][m]["tmin"]) > excludemonth and round(mean(metclmt[y][m]["tmin"]),1) == metclmt[y]["tminPROP"]["month_AVG_max"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tminPROP"]["month_AVG_max"][1].extend(m for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and len(metclmt[y][m]["tmin"]) > excludemonth and round(mean(metclmt[y][m]["tmin"]),1) == metclmt[y][s]["tminPROP"]["month_AVG_max"][0])
metclmt[y]["tminPROP"]["month_AVG_min"][0] = round(min(mean(metclmt[y][m]["tmin"]) for m in metclmt[y] if type(m) == int and len(metclmt[y][m]["tmin"]) > excludemonth),1)
metclmt[y]["tminPROP"]["month_AVG_min"][1].extend(m for m in metclmt[y] if type(m) == int and len(metclmt[y][m]["tmin"]) > excludemonth and round(mean(metclmt[y][m]["tmin"]),1) == metclmt[y]["tminPROP"]["month_AVG_min"][0])
for s in ["spring","summer","fall","winter"]: metclmt[y][s]["tminPROP"]["month_AVG_min"][1].extend(m for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and len(metclmt[y][m]["tmin"]) > excludemonth and round(mean(metclmt[y][m]["tmin"]),1) == metclmt[y][s]["tminPROP"]["month_AVG_min"][0])
for s in ["spring","summer","fall","winter"]:
try:metclmt[y][s]["tminPROP"]["month_AVG_max"][0] = round(max(mean(metclmt[y][m]["tmin"]) for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and len(metclmt[y][m]["tmin"]) > excludemonth),1)
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
for s in ["spring","summer","fall","winter"]:
try: metclmt[y][s]["tminPROP"]["month_AVG_min"][0] = round(min(mean(metclmt[y][m]["tmin"]) for m in metclmt[y] if type(m) == int and m in metclmt[y][s]["valid"] and len(metclmt[y][m]["tmin"]) > excludemonth),1)
except: pass #print(y,s,m,[M for M in metclmt[y] if type(M) == int])
END = time()
if len(station_ids) > 1:
print("STATION: Multiple Stations")
clmt["station"] = "{} Stations".format(len(station_ids))
else: print("STATION: {}".format(clmt["station"]))
print("*** SCRIPT COMPLETE ***")
print("Runtime: {} seconds".format(round(END - START,2)))
print("-------------------------------------------------------------------------------------")
print(" For more detailed assistance, enter clmthelp() for a breakdown of available functions")
print("-------------------------------------------------------------------------------------")
def attchk(attstr):
"""Not used by user; program uses it for output and 'filling in' of
missing data"""
try:
M = attstr[0] # Measurement Flag
except:
M = ""
try:
Q = attstr[1] # Quality Flag
except:
Q = ""
try:
S = attstr[2] # Source Flag
except:
S = ""
try:
T = attstr[3] # Time of Observation
except:
T = ""
return M,Q,S,T
def errorStats():
"""Returns a report on errors that might be worth veryfying the data for.
errorStats() -> report on possible-to-likely errors in the record; no
arguments passeds
"""
#if "ignore" in ig: ignoreflags.append(ig["ignore"])
#if "heed" in ig: ignoreflags.remove(ig["heed"])
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
total_records = 0
errors = []
nonIerrors = []
prcp_errors = []
snow_errors = []
snwd_errors = []
tmax_errors = []
tmin_errors = []
error_array = [prcp_errors,snow_errors,snwd_errors,tmax_errors,tmin_errors]
misscounter = 0
tmax_lt_tmin = []
snow_gt_0prcp = []
snwd_gt_snow = []
for y in [year for year in clmt if type(year) == int]:
for m in [month for month in clmt[y] if type(month) == int]:
for d in [day for day in clmt[y][m] if type(day) == int]:
total_records += 1
if any(e != "" for e in [clmt[y][m][d].prcpQ,clmt[y][m][d].snowQ,clmt[y][m][d].snwdQ,clmt[y][m][d].tmaxQ,clmt[y][m][d].tminQ]):
errors.append(clmt[y][m][d])
if clmt[y][m][d].prcpQ != "": prcp_errors.append(clmt[y][m][d])
if clmt[y][m][d].snowQ != "": snow_errors.append(clmt[y][m][d])
if clmt[y][m][d].snwdQ != "": snwd_errors.append(clmt[y][m][d])
if clmt[y][m][d].tmaxQ != "": tmax_errors.append(clmt[y][m][d])
if clmt[y][m][d].tminQ != "": tmin_errors.append(clmt[y][m][d])
try:
if int(clmt[y][m][d].tmax) < int(clmt[y][m][d].tmin):
tmax_lt_tmin.append("Day: {}; TMAX: {}; TMIN: {}".format(clmt[y][m][d].daystr,clmt[y][m][d].tmax,clmt[y][m][d].tmin))
except:
misscounter += 1
try:
if float(clmt[y][m][d].snow) > 0 and float(clmt[y][m][d].prcp) == 0 and clmt[y][m][d].prcpM != "T":
snow_gt_0prcp.append("Day: {}; PRCP: {} - {} :: SNOW: {} - {}".format(clmt[y][m][d].daystr,clmt[y][m][d].prcp,clmt[y][m][d].prcpQ if clmt[y][m][d].prcpQ != "" else " ",clmt[y][m][d].snow,clmt[y][m][d].snowQ if clmt[y][m][d].snowQ != "" else " "))
except:
continue
print("Total Dates with at least 1 Quality Flag: {}; % of Total Days: {}%".format(len(errors),round(len(errors)/total_records*100,2)))
for x in range(len(error_array)):
if x == 0: print("PRCP ERRORS:")
if x == 1: print("SNOW ERRORS:")
if x == 2: print("SNWD ERRORS:")
if x == 3: print("TMAX ERRORS (Non-I):")
if x == 4: print("TMIN ERRORS (Non-I):")
for y in error_array[x]:
if x == 0:
if y.prcpQ not in [i for i in ignoreflags if i != "I"] or y.prcp in ["9999","-9999"]:
print("Day: {}; PRCP: {}; Quality Flag (prcpQ): {} - {}".format(y.daystr,y.prcp,y.prcpQ,qflagCheck(y.prcpQ)))
if x == 1:
if y.snowQ not in [i for i in ignoreflags if i != "I"] or y.snow in ["9999","-9999"]:
print("Day: {}; SNOW: {}; Quality Flag (snowQ): {} - {}".format(y.daystr,y.snow,y.snowQ,qflagCheck(y.snowQ)))
if x == 2:
if y.snwdQ not in ignoreflags or y.snwd in ["9999","-9999"]:
print("Day: {}; SNWD: {}; Quality Flag (snwdQ): {} - {}".format(y.daystr,y.snwd,y.snwdQ,qflagCheck(y.snwdQ)))
if x == 3:
if y.tmaxQ not in ignoreflags and y.tmaxQ != "I" or y.tmax in ["9999","-9999"]:
print("Day: {}; TMAX: {}; Quality Flag (tmaxQ): {} - {}".format(y.daystr,y.tmax,y.tmaxQ,qflagCheck(y.tmaxQ)))
if x == 4:
if y.tminQ not in ignoreflags and y.tminQ != "I" or y.tmax in ["9999","-9999"]:
print("Day: {}; TMIN: {}; Quality Flag (tminQ): {} - {}".format(y.daystr,y.tmin,y.tminQ,qflagCheck(y.tminQ)))
print("---------------------------")
print("TOTAL DAYS where tmax and/or tmin is missing: {}".format(misscounter))
if len(tmax_lt_tmin) > 0:
print("DAYS WHERE TMIN > TMAX:")
for x in tmax_lt_tmin:
print(x)
if len(snow_gt_0prcp) > 0:
print("----------------------------")
print("DAYS WHERE PRCP == 0 (with no trace recorded) and SNOW > 0:")
for x in snow_gt_0prcp:
print(x)
print("")
def checkDate(*args):
"""Used only by the program"""
if len(args) == 3:
y = args[0]
m = args[1]
d = args[2]
try:
if clmt[y][m][d]: return True
except KeyError:
print("OOPS! An entry for {}-{}-{} was not found. Try again.".format(str(y).zfill(4),str(m).zfill(2)[0:2],str(d).zfill(2)[0:2]))
if d > y or m > y:
print("*** Ensure your entry matches the format of dayStats(year,month,day) ***")
return False
elif len(args) == 2:
y = args[0]
m = args[1]
try:
if clmt[y][m]: return True
except KeyError:
try:
print("OOPS! An entry for {} {} was not found. Try again.".format(calendar.month_name[m],y))
if m > y:
print("*** Ensure your entry matches the format of monthStats(year,month) ***")
except:
print("OOPS! A likely invalid month entry. Ensure format of monthStats(year,month). Try again.")
return False
elif len(args) == 1:
y = args[0]
try:
if clmt[y]: return True
except KeyError:
print("OOPS! An entry for {} was not found. Try again.".format(y))
return False
else:
print("OOPS! No date input received! Try again!")
def checkDate2(*args):
"""Used only by the program in functions that check but don't return a true/false message"""
y = args[0]
m = args[1]
d = args[2]
try:
if clmt[y][m][d]: return True
except KeyError:
return False
def rank(n):
if n <= 0 or type(n) != int: return ""
elif n < 10 or int(str(n)[-2:]) not in [11,12,13]:
if int(str(n)[-1:]) == 1: return str(n) + "st"
elif int(str(n)[-1:]) == 2: return str(n) + "nd"
elif int(str(n)[-1:]) == 3: return str(n) + "rd"
else: return str(n) + "th"
elif int(str(n)[-2:]) in [11,12,13]: return str(n) + "th"
def qflagCheck(*q):
"""Primarily used internally by the program. Can return definitions of
Quality Flags. These are used to denote data that may not be reliable.
qflagCheck(*[str]) -> str
OPTIONAL args: "F" -> will return the definition of a flag by that one-
letter string
"""
if len(q) != 0:
if q[0] == "D": return "Failed (D)uplicate Check"
if q[0] == "G": return "Failed (G)ap Check"
if q[0] == "I": return "Failed (I)nternal Consistency Check"
if q[0] == "K": return "Failed Strea(K)/Frequent-Value Check"
if q[0] == "L": return "Failed Check on (L)ength of Multi-day period"
if q[0] == "M": return "Failed (M)ega-Consistency Check"
if q[0] == "N": return "Failed (N)aught Check"
if q[0] == "O": return "Failed Climatological (O)utlier Check"
if q[0] == "R": return "Failed Lagged (R)ange Check"
if q[0] == "S": return "Failed (S)patial Consistency Check"
if q[0] == "T": return "Failed (T)emporal Consistency Check"
if q[0] == "W": return "Temperature Too (W)arm for Snow"
if q[0] == "X": return "Failed Bounds Check"
if q[0] == "Z": return "Flagged as a result of an official Datzilla Investigation"
else: return "None/Not-Documented"
else:
print("D - Failed (D)uplicate Check")
print("G - Failed (G)ap Check")
print("I - Failed (I)nternal Consistency Check")
print("K - Failed Strea(K)/Frequent-Value Check")
print("L - Failed Check on (L)ength of Multi-day period")
print("M - Failed (M)ega-Consistency Check")
print("N - Failed (N)aught Check")
print("O - Failed Climatological (O)utlier Check")
print("R - Failed Lagged (R)ange Check")
print("S - Failed (S)patial Consistency Check")
print("T - Failed (T)emporal Consistency Check")
print("W - Temperature Too (W)arm for Snow")
print("X - Failed Bounds Check")
print("Z - Flagged as a result of an official Datzilla Investigation")
def daySummary(y1,m1,d1,*date2):
"""Quickly list all specific daily data between two dates. The 2nd date
is optional. If none is provided, December 31 of y1 will be used as the
stop date.
daySummary(y1,m1,d1,*[y2,m2,d2])
EXAMPLE: daySummary(2016,10,1,2016,10,31) -> Lists daily summaries for
dates between 1 OCT 2016
and 31 OCT 2016
EXAMPLE: daySummary(1980,11,1) -> Lists daily summaries for dates between
1 NOV 1980 and 31 DEC 1980
"""
if any(type(x) != int for x in [y1,m1,d1]): return print("*** OOPS! Error in Date #1. Ensure that only integers are entered ***")
#valid1 = checkDate(y1,m1,d1)
if len(date2) == 0:
if y1 == max(Y for Y in clmt if type(Y) == int):
y2 = y1
m2 = max(M for M in clmt[y2] if type(M) == int)
d2 = max(D for D in clmt[y2][m2] if type(D) == int)
else: y2 = y1; m2 = 12; d2 = 31
elif len(date2) != 3: return print("*** OOPS! For the 2nd (optional) date, ensure a Year, Month and Date are entered ***")
else:
if any(type(x) != int for x in [date2[0],date2[1],date2[2]]): return print("*** OOPS! Error in Date #2. Ensure that only integers are entered ***")
#valid2 = checkDate(date2[0],date2[1],date2[2])
y2 = date2[0]; m2 = date2[1]; d2 = date2[2]
# Further inspection of Day 1
if y1 not in clmt: return print("OOPS! Regarding Date #1, no yearly-data found for {}. The earliest year is {}.".format(y1,min(Y for Y in clmt if type(Y) == int)))
if m1 not in range(1,12+1): return print("OOPS! Regarding Date #1, ensure the month is in the range [1,12]. Try again!")
daysinmonth = max(D for Y in clmt if type(Y) == int and m1 in clmt[Y] for D in clmt[Y][m1] if type(D) == int)
if d1 not in range(1,daysinmonth+1): return print("OOPS! Regarding Date #1, ensure the day is in the range [1,{}]. Try again!".format(daysinmonth))
if m1 == 2 and d1 == 29 and calendar.isleap(y1) == False: print("OOPS! Date #1 does not occur. It's not during a leap year. Try again!")
# Furthur inspection of Day 2
if y2 not in clmt: return print("OOPS! Regarding Date #2, no yearly-data found for {}. The earliest year is {}.".format(y2,min(Y for Y in clmt if type(Y) == int)))
if m2 not in range(1,12+1): return print("OOPS! Regarding Date #2, ensure the month is in the range [1,12]. Try again!")
daysinmonth = max(D for Y in clmt if type(Y) == int and m2 in clmt[Y] for D in clmt[Y][m2] if type(D) == int)
if d2 not in range(1,daysinmonth+1): return print("OOPS! Regarding Date #2, ensure the day is in the range [1,{}]. Try again!".format(daysinmonth))
if m2 == 2 and d2 == 29 and calendar.isleap(y2) == False: print("OOPS! Date #2 does not occur. It's not during a leap year. Try again!")
startday = datetime.date(y1,m1,d1)
endday = datetime.date(y2,m2,d2)
if startday == endday: return print("OOPS! Start and End dates are the exact same; please ensure otherwise! Try again!")
if endday < startday: return print("OOPS! End date is sooner than the start date. Try again!")
incrday = startday
print("")
print("{:^88}".format("Day Summaries from {} {} {} to {} {} {}".format(str(d1).zfill(2),calendar.month_abbr[m1].upper(),y1,str(d2).zfill(2),calendar.month_abbr[m2].upper(),y2)))
print("{:^88}".format("{}: {}".format(clmt["station"],clmt["station_name"])))
print("{:^88}".format("{:-^45}".format("")))
while incrday <= endday: # {
try: print(" {}: PRCP: {:>5}{:3}; SNOW: {:>4}{:3}; SNWD: {:>4}{:3}; TMAX: {:>3}{:3}; TMIN: {:>3}{:3};".format(
clmt[incrday.year][incrday.month][incrday.day].daystr,
"{:>5.2f}".format(float(clmt[incrday.year][incrday.month][incrday.day].prcp)) if clmt[incrday.year][incrday.month][incrday.day].prcp != "" else "",
"{} {}".format(
clmt[incrday.year][incrday.month][incrday.day].prcpM if clmt[incrday.year][incrday.month][incrday.day].prcpM == "T" else "",
clmt[incrday.year][incrday.month][incrday.day].prcpQ if clmt[incrday.year][incrday.month][incrday.day].prcpQ != "" else ""),
"{:>4.1f}".format(float(clmt[incrday.year][incrday.month][incrday.day].snow)) if (clmt[incrday.year][incrday.month][incrday.day].snow != "" and float(clmt[incrday.year][incrday.month][incrday.day].snow) != 0) or (clmt[incrday.year][incrday.month][incrday.day].snow != "" and clmt[incrday.year][incrday.month][incrday.day].snowM == "T") else "----",
"{} {} ".format(
clmt[incrday.year][incrday.month][incrday.day].snowM if clmt[incrday.year][incrday.month][incrday.day].snowM == "T" else "",
clmt[incrday.year][incrday.month][incrday.day].snowQ if clmt[incrday.year][incrday.month][incrday.day].snowQ != "" else ""),
"{:>4.1f}".format(float(clmt[incrday.year][incrday.month][incrday.day].snwd)) if (clmt[incrday.year][incrday.month][incrday.day].snwd != "" and float(clmt[incrday.year][incrday.month][incrday.day].snwd) != 0) or (clmt[incrday.year][incrday.month][incrday.day].snwd != "" and clmt[incrday.year][incrday.month][incrday.day].snwdM == "T") else "----",
"{} {} ".format(
clmt[incrday.year][incrday.month][incrday.day].snwdM if clmt[incrday.year][incrday.month][incrday.day].snwdM == "T" else "",
clmt[incrday.year][incrday.month][incrday.day].snwdQ if clmt[incrday.year][incrday.month][incrday.day].snwdQ != "" else ""),
clmt[incrday.year][incrday.month][incrday.day].tmax,
" {} ".format(clmt[incrday.year][incrday.month][incrday.day].tmaxQ) if clmt[incrday.year][incrday.month][incrday.day].tmaxQ != "" else "",
clmt[incrday.year][incrday.month][incrday.day].tmin,
" {} ".format(clmt[incrday.year][incrday.month][incrday.day].tminQ) if clmt[incrday.year][incrday.month][incrday.day].tminQ != "" else ""
))
except: print(" *** NO ENTRY DATA FOUND FOR {}-{}-{} ***".format(incrday.year,incrday.month,incrday.day))
incrday += datetime.timedelta(days=1)
print("")
def dayStats(y,m,d):
"""Report on recorded statistics for the day of interest. Passed arguments
MUST be integers.
dayStats(year,month,day)
EXAMPLE: dayStats(1992,12,29) -> Returns a printout of statistics from
December 29, 1992
"""
ranks = ["th","st","nd","rd","th","th","th","th","th","th"]
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
dayExists = checkDate(y,m,d)
if dayExists:
print("")
dayobj = clmt[y][m][d]
prcphist = sorted(list(set(list(round(float(clmt[Y][m][d].prcp),2) for Y in clmt if type(Y) == int and m in clmt[Y] and d in clmt[Y][m] and clmt[Y][m][d].prcp != "" and float(clmt[Y][m][d].prcp) != 0 and clmt[Y][m][d].prcpQ in ignoreflags))),reverse=True)
snowhist = sorted(list(set(list(round(float(clmt[Y][m][d].snow),1) for Y in clmt if type(Y) == int and m in clmt[Y] and d in clmt[Y][m] and clmt[Y][m][d].snow != "" and float(clmt[Y][m][d].snow) != 0 and clmt[Y][m][d].snowQ in ignoreflags))),reverse=True)
snwdhist = sorted(list(set(list(round(float(clmt[Y][m][d].snwd),1) for Y in clmt if type(Y) == int and m in clmt[Y] and d in clmt[Y][m] and clmt[Y][m][d].snwd != "" and float(clmt[Y][m][d].snwd) != 0 and clmt[Y][m][d].snwdQ in ignoreflags))),reverse=True)
tmaxdeschist = sorted(list(set(list(int(clmt[Y][m][d].tmax) for Y in clmt if type(Y) == int and m in clmt[Y] and d in clmt[Y][m] and clmt[Y][m][d].tmax != "" and clmt[Y][m][d].tmaxQ == ""))),reverse=True)
tmaxaschist = sorted(list(set(list(int(clmt[Y][m][d].tmax) for Y in clmt if type(Y) == int and m in clmt[Y] and d in clmt[Y][m] and clmt[Y][m][d].tmax != "" and clmt[Y][m][d].tmaxQ == ""))))
tmindeschist = sorted(list(set(list(int(clmt[Y][m][d].tmin) for Y in clmt if type(Y) == int and m in clmt[Y] and d in clmt[Y][m] and clmt[Y][m][d].tmin != "" and clmt[Y][m][d].tminQ == ""))),reverse=True)
tminaschist = sorted(list(set(list(int(clmt[Y][m][d].tmin) for Y in clmt if type(Y) == int and m in clmt[Y] and d in clmt[Y][m] and clmt[Y][m][d].tmin != "" and clmt[Y][m][d].tminQ == ""))))
#clmt_vars_days = {"prcp":{},"snow":{},"snwd":{},"tavg":{},"tmax":{},"tmin":{}}
tavgdeschist = sorted(list(set(list(V for V in clmt_vars_days["tavg"] for D in clmt_vars_days["tavg"][V] if D.month == m and D.day == d))),reverse=True)
tavgaschist = sorted(list(set(list(V for V in clmt_vars_days["tavg"] for D in clmt_vars_days["tavg"][V] if D.month == m and D.day == d))))
#sorted(list(set(list(round(float(clmt[Y][m][d].prcp),2) for Y in clmt if type(Y) == int and m in clmt[Y] and d in clmt[Y][m] and clmt[Y][m][d].prcp != "" and float(clmt[Y][m][d].prcp) != 0 and clmt[Y][m][d].prcpQ == ""))),reverse=True)
print("Statistics for {}".format(dayobj.entryday))
print("Report Location: {}, {}".format(dayobj.stationid,dayobj.station_name))
print("-------------------")
print("PRCP: {}{}{}".format("T" if dayobj.prcpM == "T" else dayobj.prcp,
", Flag: {} - {}".format(dayobj.prcpQ,qflagCheck(dayobj.prcpQ)) if dayobj.prcpQ != "" else "",
# rank(tavgaschist.index(round(mean(clmt[y][m]["tempAVGlist"]),1))+1)
", Rank: {}".format(rank(prcphist.index(round(float(dayobj.prcp),2))+1)) if dayobj.prcp != "" and float(dayobj.prcp) != 0 else ""))
if dayobj.snow != "" and float(dayobj.snow) > 0 or dayobj.snowM == "T":
print("SNOW: {}{}{}".format("T" if dayobj.snowM == "T" else dayobj.snow,
", Flag: {} - {}".format(dayobj.snowQ,qflagCheck(dayobj.snowQ)) if dayobj.snowQ != "" else "",
", Rank: {}".format(rank(snowhist.index(round(float(dayobj.snow),1))+1)) if dayobj.snowQ in ignoreflags else ""))
if dayobj.snwd != "" and float(dayobj.snwd) > 0:
print("SNWD: {}{}{}".format("T" if dayobj.snwdM == "T" else dayobj.snwd,
", Flag: {} - {}".format(dayobj.snwdQ,qflagCheck(dayobj.snwdQ)) if dayobj.snwdQ != "" else "",
", Rank: {}".format(rank(snwdhist.index(round(float(dayobj.snwd),1))+1)) if dayobj.snwdQ in ignoreflags else ""))
print("TAVG: {}{}{}".format(
"{:4.1f}".format(round(mean([float(dayobj.tmax),float(dayobj.tmin)]),1)) if all(T != "" for T in [dayobj.tmax,dayobj.tmin]) and all(Q in ignoreflags for Q in [dayobj.tmaxQ,dayobj.tminQ]) else "N/A",
", Rank: {} Warmest".format(
rank(tavgdeschist.index(round(mean([float(dayobj.tmax),float(dayobj.tmin)]),1))+1)) if all(T != "" for T in [dayobj.tmax,dayobj.tmin]) and all(Q in ignoreflags for Q in [dayobj.tmaxQ,dayobj.tminQ]) and tavgdeschist.index(round(mean([float(dayobj.tmax),float(dayobj.tmin)]),1)) <= tavgaschist.index(round(mean([float(dayobj.tmax),float(dayobj.tmin)]),1)) else "",
", Rank: {} Coolest".format(
rank(tavgaschist.index(round(mean([float(dayobj.tmax),float(dayobj.tmin)]),1))+1)) if all(T != "" for T in [dayobj.tmax,dayobj.tmin]) and all(Q in ignoreflags for Q in [dayobj.tmaxQ,dayobj.tminQ]) and tavgaschist.index(round(mean([float(dayobj.tmax),float(dayobj.tmin)]),1)) <= tavgdeschist.index(round(mean([float(dayobj.tmax),float(dayobj.tmin)]),1)) else ""
))
print("TMAX: {}{}{}{}".format(
dayobj.tmax if dayobj.tmax != "" else "N/A",
", Flag: {} - {}".format(dayobj.tmaxQ,qflagCheck(dayobj.tmaxQ)) if dayobj.tmaxQ != "" else "",
", Rank: {} Warmest".format(rank(tmaxdeschist.index(int(dayobj.tmax))+1)) if dayobj.tmax != "" and dayobj.tmaxQ in ignoreflags and tmaxdeschist.index(int(dayobj.tmax)) <= tmaxaschist.index(int(dayobj.tmax)) else "",
", Rank: {} Coolest".format(rank(tmaxaschist.index(int(dayobj.tmax))+1)) if dayobj.tmax != "" and dayobj.tmaxQ in ignoreflags and tmaxaschist.index(int(dayobj.tmax)) <= tmaxdeschist.index(int(dayobj.tmax)) else ""
))
print("TMIN: {}{}{}{}".format(
dayobj.tmin if dayobj.tmin != "" else "N/A",
", Flag: {} - {}".format(dayobj.tminQ,qflagCheck(dayobj.tminQ)) if dayobj.tminQ != "" else "",
", Rank: {} Warmest".format(rank(tmindeschist.index(int(dayobj.tmin))+1)) if dayobj.tmin != "" and dayobj.tminQ in ignoreflags and tmindeschist.index(int(dayobj.tmin)) <= tminaschist.index(int(dayobj.tmin)) else "",
", Rank: {} Coolest".format(rank(tminaschist.index(int(dayobj.tmin))+1)) if dayobj.tmin != "" and dayobj.tminQ in ignoreflags and tminaschist.index(int(dayobj.tmin)) <= tmindeschist.index(int(dayobj.tmin)) else ""
))
try:
if int(dayobj.tmax) < int(dayobj.tmin): print("*** CHECK DATA: TMIN > TMAX ***")
except:
pass
print("")
def weekStats(y,m,d):
"""Report on recorded statistics for a week of interest. The week will be
centered on the day passed as an argument. Passed arguments MUST be
integers.
weekStats(year,month,day)
EXAMPLE: weekStats(1992,12,29) -> Returns a printout of weekly-based
statistics centered on December 29, 1992
(The week would be inclusive 3 days
before and after the date
"""
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
ranks = ["th","st","nd","rd","th","th","th","th","th","th"]
if m == 2 and d == 29:
m = 2; d = 28
wkstart = datetime.date(y,m,d) - datetime.timedelta(days=3)
c = wkstart
wkend = datetime.date(y,m,d) + datetime.timedelta(days=3)
#print(st)
#print(datetime.date(y,m,d))
#print(en)
w_prcp = []
w_prcpDAYS = 0
w_snow = []
w_snowDAYS = 0
w_snwd = []
w_tmax = []
w_tmin = []
w_alltemps = []
records_in_week = 0
weekExists = checkDate(y,m,d)
indvweekdays = []
if m == 2 and d == 29:
m = 2; d = 28
if weekExists:
print("")
for x in range(7):
indvweekdays.append(c)
try:
#round(float(clmt[DY.year][DY.month][DY.day].prcp),2) for DY in indvweekdays if checkDate(DY.year,DY.month,DY.day) and clmt[DY.year][DY.month][DY.day].prcp != "" and clmt[DY.year][DY.month][DY.day].prcpQ in ignoreflags
if clmt[c.year][c.month][c.day]: records_in_week += 1
if clmt[c.year][c.month][c.day].prcpQ in ignoreflags and clmt[c.year][c.month][c.day].prcp not in ["9999","-9999",""]:
w_prcp.append(round(float(clmt[c.year][c.month][c.day].prcp),2))
if float(clmt[c.year][c.month][c.day].prcp) > 0 or clmt[c.year][c.month][c.day].prcpM == "T": w_prcpDAYS += 1
if clmt[c.year][c.month][c.day].snowQ in ignoreflags and clmt[c.year][c.month][c.day].snow not in ["9999","-9999",""]:
w_snow.append(round(float(clmt[c.year][c.month][c.day].snow),1))
if float(clmt[c.year][c.month][c.day].snow) > 0 or clmt[c.year][c.month][c.day].snowM == "T": w_snowDAYS += 1
if clmt[c.year][c.month][c.day].snwdQ in ignoreflags and clmt[c.year][c.month][c.day].snwd not in ["9999","-9999",""]:
w_snwd.append(round(float(clmt[c.year][c.month][c.day].snwd),1))
if clmt[c.year][c.month][c.day].tmaxQ in ignoreflags and clmt[c.year][c.month][c.day].tmax not in ["9999","-9999",""]:
w_tmax.append(int(clmt[c.year][c.month][c.day].tmax))
if clmt[c.year][c.month][c.day].tminQ in ignoreflags and clmt[c.year][c.month][c.day].tmin not in ["9999","-9999",""]:
w_tmin.append(int(clmt[c.year][c.month][c.day].tmin))
if clmt[c.year][c.month][c.day].tmaxQ in ignoreflags and clmt[c.year][c.month][c.day].tmax not in ["9999","-9999",""] and clmt[c.year][c.month][c.day].tminQ in ignoreflags and clmt[c.year][c.month][c.day].tmin not in ["9999","-9999",""]:
w_alltemps.append(int(clmt[c.year][c.month][c.day].tmax))
w_alltemps.append(int(clmt[c.year][c.month][c.day].tmin))
except KeyError:
continue
c += datetime.timedelta(days=1)
# indvweekdays complete above
# The following compiles all time data to display ranks in the output
prcphist = []
snowhist = []
snwdhist = []
tmaxaschist = []
tmaxdeschist = []
tminaschist = []
tmindeschist = []
tavgaschist = []
tavgdeschist = []
for YR in [YYYY for YYYY in clmt if type(YYYY) == int]:
wc = datetime.date(YR,m,d)
ws = wc - datetime.timedelta(days=3)
wd = ws # current day
we = wc + datetime.timedelta(days=3)
tempwkli = []
# tempwkli = [datetime.date(2009,1,1),datetime.date(2009,1,2),datetime.date(2009,1,3),datetime.date(2009,1,4),datetime.date(2009,1,5),datetime.date(2009,1,6),datetime.date(2009,1,7)]
while wd <= we:
tempwkli.append(datetime.date(wd.year,wd.month,wd.day))
wd = wd + datetime.timedelta(days=1)
prcpwk = [float(clmt[wkday.year][wkday.month][wkday.day].prcp) for wkday in tempwkli if checkDate2(wkday.year,wkday.month,wkday.day) and clmt[wkday.year][wkday.month][wkday.day].prcp not in ["","-9999","9999","-999","999"] and clmt[wkday.year][wkday.month][wkday.day].prcpQ in ignoreflags]
prcphist.append(round(sum(prcpwk),2))
snowwk = [float(clmt[wkday.year][wkday.month][wkday.day].snow) for wkday in tempwkli if checkDate2(wkday.year,wkday.month,wkday.day) and clmt[wkday.year][wkday.month][wkday.day].snow not in ["","-9999","9999","-999","999"] and clmt[wkday.year][wkday.month][wkday.day].snowQ in ignoreflags]
snowhist.append(round(sum(snowwk),1))
snwdwk = [float(clmt[wkday.year][wkday.month][wkday.day].snwd) for wkday in tempwkli if checkDate2(wkday.year,wkday.month,wkday.day) and clmt[wkday.year][wkday.month][wkday.day].snwd not in ["","-9999","9999","-999","999"] and clmt[wkday.year][wkday.month][wkday.day].snwdQ in ignoreflags]
if len(snwdwk) > 0: snwdhist.append(round(sum(snwdwk)/7,1))
tmaxwk = [int(clmt[wkday.year][wkday.month][wkday.day].tmax) for wkday in tempwkli if checkDate2(wkday.year,wkday.month,wkday.day) and clmt[wkday.year][wkday.month][wkday.day].tmax not in ["","-9999","9999","-999","999"] and clmt[wkday.year][wkday.month][wkday.day].tmaxQ in ignoreflags]
if len(tmaxwk) > excludeweek:
tmaxaschist.append(round(mean(tmaxwk),1))
tmaxdeschist.append(round(mean(tmaxwk),1))
tminwk = [int(clmt[wkday.year][wkday.month][wkday.day].tmin) for wkday in tempwkli if checkDate2(wkday.year,wkday.month,wkday.day) and clmt[wkday.year][wkday.month][wkday.day].tmin not in ["","-9999","9999","-999","999"] and clmt[wkday.year][wkday.month][wkday.day].tminQ in ignoreflags]
if len(tminwk) > excludeweek:
tminaschist.append(round(mean(tminwk),1))
tmindeschist.append(round(mean(tminwk),1))
tavgwk = []
for evd in tempwkli:
if checkDate2(evd.year,evd.month,evd.day) and clmt[evd.year][evd.month][evd.day].tmax not in ["","-9999","9999","-999","999"] and clmt[evd.year][evd.month][evd.day].tmin not in ["","-9999","9999","-999","999"] and clmt[evd.year][evd.month][evd.day].tmaxQ in ignoreflags and clmt[evd.year][evd.month][evd.day].tminQ in ignoreflags:
tavgwk.append(int(clmt[evd.year][evd.month][evd.day].tmax))
tavgwk.append(int(clmt[evd.year][evd.month][evd.day].tmin))
if len(tavgwk) > excludeweek * 2:
tavgaschist.append(round(mean(tavgwk),1))
tavgdeschist.append(round(mean(tavgwk),1))
"""
print("{} - prcp: {} :: snow: {} :: snwd avg: {} :: tavg: {} :: tmax avg: {} :: tmin avg: {}".format(
YR,
"{:5.2f}".format(round(sum(prcpwk),2)),
"{:5.1f}".format(round(sum(snowwk),1)),
"{:5.1f}".format(round(mean(snwdwk),1)) if len(snwdwk) > 0 else "--",
"{:5.1f}".format(round(mean(tavgwk),1)) if len(tavgwk) > 0 else "--",
"{:5.1f}".format(round(mean(tmaxwk),1)) if len(tmaxwk) > 0 else "--",
"{:5.1f}".format(round(mean(tminwk),1)) if len(tminwk) > 0 else "--"))
"""
prcphist = sorted(list(set(prcphist)),reverse=True)
snowhist = sorted(list(set(snowhist)),reverse=True)
snwdhist = sorted(list(set(snwdhist)),reverse=True)
tmaxaschist = sorted(list(set(tmaxaschist)))
tmaxdeschist = sorted(list(set(tmaxdeschist)),reverse=True)
tminaschist = sorted(list(set(tminaschist)))
tmindeschist = sorted(list(set(tmindeschist)),reverse=True)
tavgaschist = sorted(list(set(tavgaschist)))
tavgdeschist = sorted(list(set(tavgdeschist)),reverse=True)
#for x in [prcphist,snowhist,snwdhist,tmaxaschist,tmaxdeschist,tminaschist,tmindeschist,tavgaschist,tavgdeschist]: print(x)
if records_in_week <= excludeweek:
print("")
print("{:-^83}".format("*** WEEKLY STATS LIKELY UNDERREPRESENTED ***"))
print("{:^83}".format("Weekly Statistics for {} thru {}".format(wkstart,wkend)))
print("{:^83}".format("{}: {}".format(clmt["station"],clmt["station_name"])))
print("{:^83}".format("Quantity of Records: {}".format(records_in_week)))
print("{:^83}".format("'*' Denotes existance of quality flag; not included in average stats"))
print("{:-^83}".format(""))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}".format("",indvweekdays[0].year,indvweekdays[1].year,indvweekdays[2].year,indvweekdays[3].year,indvweekdays[4].year,indvweekdays[5].year,indvweekdays[6].year))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}".format("",
"{} {}".format(calendar.month_abbr[indvweekdays[0].month],indvweekdays[0].day),
"{} {}".format(calendar.month_abbr[indvweekdays[1].month],indvweekdays[1].day),
"{} {}".format(calendar.month_abbr[indvweekdays[2].month],indvweekdays[2].day),
"{} {}".format(calendar.month_abbr[indvweekdays[3].month],indvweekdays[3].day),
"{} {}".format(calendar.month_abbr[indvweekdays[4].month],indvweekdays[4].day),
"{} {}".format(calendar.month_abbr[indvweekdays[5].month],indvweekdays[5].day),
"{} {}".format(calendar.month_abbr[indvweekdays[6].month],indvweekdays[6].day)))
print("{:-^6}|{:-^10}|{:-^10}|{:-^10}|{:-^10}|{:-^10}|{:-^10}|{:-^10}".format("","","","","","","",""))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}".format("PRCP",
"{}{}{}".format(
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].prcp if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].prcp != "" else "M",
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].prcpM if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].prcpM == "T" else "",
"*" if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].prcpQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].prcp if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].prcp != "" else "M",
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].prcpM if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].prcpM == "T" else "",
"*" if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].prcpQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].prcp if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].prcp != "" else "M",
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].prcpM if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].prcpM == "T" else "",
"*" if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].prcpQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].prcp if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].prcp != "" else "M",
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].prcpM if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].prcpM == "T" else "",
"*" if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].prcpQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].prcp if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].prcp != "" else "M",
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].prcpM if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].prcpM == "T" else "",
"*" if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].prcpQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].prcp if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].prcp != "" else "M",
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].prcpM if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].prcpM == "T" else "",
"*" if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].prcpQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].prcp if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].prcp != "" else "M",
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].prcpM if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].prcpM == "T" else "",
"*" if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].prcpQ != "" else "")))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}".format("SNOW",
"{}{}{}".format(
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].snow if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) else "M",
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].snowM if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].snowM == "T" else "",
"*" if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].snowQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].snow if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) else "M",
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].snowM if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].snowM == "T" else "",
"*" if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].snowQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].snow if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) else "M",
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].snowM if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].snowM == "T" else "",
"*" if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].snowQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].snow if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) else "M",
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].snowM if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].snowM == "T" else "",
"*" if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].snowQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].snow if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) else "M",
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].snowM if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].snowM == "T" else "",
"*" if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].snowQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].snow if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) else "M",
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].snowM if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].snowM == "T" else "",
"*" if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].snowQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].snow if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) else "M",
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].snowM if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].snowM == "T" else "",
"*" if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].snowQ != "" else "")))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}".format("SNWD",
"{}{}{}".format(
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].snwd if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) else "M",
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].snwdM if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].snwdM == "T" else "",
"*" if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].snwdQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].snwd if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) else "M",
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].snwdM if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].snwdM == "T" else "",
"*" if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].snwdQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].snwd if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) else "M",
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].snwdM if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].snwdM == "T" else "",
"*" if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].snwdQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].snwd if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) else "M",
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].snwdM if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].snwdM == "T" else "",
"*" if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].snwdQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].snwd if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) else "M",
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].snwdM if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].snwdM == "T" else "",
"*" if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].snwdQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].snwd if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) else "M",
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].snwdM if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].snwdM == "T" else "",
"*" if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].snwdQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].snwd if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) else "M",
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].snwdM if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].snwdM == "T" else "",
"*" if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].snwdQ != "" else "")))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}".format("TMAX",
"{}{}{}".format(
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tmax if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tmax != "" else "M",
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tmaxM if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tmaxM == "T" else "",
"*" if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tmaxQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tmax if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tmax != "" else "M",
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tmaxM if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tmaxM == "T" else "",
"*" if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tmaxQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tmax if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tmax != "" else "M",
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tmaxM if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tmaxM == "T" else "",
"*" if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tmaxQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tmax if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tmax != "" else "M",
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tmaxM if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tmaxM == "T" else "",
"*" if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tmaxQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tmax if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tmax != "" else "M",
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tmaxM if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tmaxM == "T" else "",
"*" if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tmaxQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tmax if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tmax != "" else "M",
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tmaxM if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tmaxM == "T" else "",
"*" if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tmaxQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tmax if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tmax != "" else "M",
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tmaxM if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tmaxM == "T" else "",
"*" if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tmaxQ != "" else "")))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}".format("TMIN",
"{}{}{}".format(
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tmin if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tmin != "" else "M",
clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tminM if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tminM == "T" else "",
"*" if checkDate2(indvweekdays[0].year,indvweekdays[0].month,indvweekdays[0].day) and clmt[indvweekdays[0].year][indvweekdays[0].month][indvweekdays[0].day].tminQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tmin if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tmin != "" else "M",
clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tminM if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tminM == "T" else "",
"*" if checkDate2(indvweekdays[1].year,indvweekdays[1].month,indvweekdays[1].day) and clmt[indvweekdays[1].year][indvweekdays[1].month][indvweekdays[1].day].tminQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tmin if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tmin != "" else "M",
clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tminM if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tminM == "T" else "",
"*" if checkDate2(indvweekdays[2].year,indvweekdays[2].month,indvweekdays[2].day) and clmt[indvweekdays[2].year][indvweekdays[2].month][indvweekdays[2].day].tminQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tmin if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tmin != "" else "M",
clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tminM if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tminM == "T" else "",
"*" if checkDate2(indvweekdays[3].year,indvweekdays[3].month,indvweekdays[3].day) and clmt[indvweekdays[3].year][indvweekdays[3].month][indvweekdays[3].day].tminQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tmin if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tmin != "" else "M",
clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tminM if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tminM == "T" else "",
"*" if checkDate2(indvweekdays[4].year,indvweekdays[4].month,indvweekdays[4].day) and clmt[indvweekdays[4].year][indvweekdays[4].month][indvweekdays[4].day].tminQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tmin if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tmin != "" else "M",
clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tminM if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tminM == "T" else "",
"*" if checkDate2(indvweekdays[5].year,indvweekdays[5].month,indvweekdays[5].day) and clmt[indvweekdays[5].year][indvweekdays[5].month][indvweekdays[5].day].tminQ != "" else ""),
"{}{}{}".format(
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tmin if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tmin != "" else "M",
clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tminM if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tminM == "T" else "",
"*" if checkDate2(indvweekdays[6].year,indvweekdays[6].month,indvweekdays[6].day) and clmt[indvweekdays[6].year][indvweekdays[6].month][indvweekdays[6].day].tminQ != "" else "")))
print("")
print("Total Precipitation: {}{}".format(
round(sum(w_prcp),2),
", Rank: {}".format(rank(prcphist.index(round(sum(w_prcp),2))+1)) if sum(w_prcp) != 0 else ""
))
print("Total Precipitation Days (>= T): {}".format(w_prcpDAYS))
if w_snowDAYS >= 1:
print("Total Snow: {}{}".format(
round(sum(w_snow),1),
", Rank: {}".format(rank(snowhist.index(round(sum(w_snow),1))+1)) if sum(w_snow) != 0 else ""
))
print("Total Snow Days (>= T): {}".format(w_snowDAYS))
if len(w_snwd) > 0 and mean(w_snwd) > 0:
print("Average Snow Depth: {}{}".format(
round(mean(w_snwd),1),
", Rank: {}".format(rank(snwdhist.index(round(mean(w_snwd),1))+1)) if mean(w_snwd) != 0 and len(w_snwd) > excludeweek else ""
))
if records_in_week > excludeweek and (len(w_tmax) <= excludeweek or len(w_tmin) <= excludeweek): print("*** TEMPERATURE STATS LIKELY UNDERREPRESENTED ***")
print("Average Temperature: {}{}{}".format(
round(mean(w_alltemps),1) if len(w_alltemps) > 0 else "N/A",
", Rank: {} Warmest".format(rank(tavgdeschist.index(round(mean(w_alltemps),1))+1))
if len(w_alltemps) > excludeweek*2 and tavgdeschist.index(round(mean(w_alltemps),1)) <= tavgaschist.index(round(mean(w_alltemps),1)) else "",
", Rank: {} Coolest".format(rank(tavgaschist.index(round(mean(w_alltemps),1))+1))
if len(w_alltemps) > excludeweek*2 and tavgaschist.index(round(mean(w_alltemps),1)) <= tavgdeschist.index(round(mean(w_alltemps),1)) else ""
))
print("Average Max Temperature: {}{}{}".format(
round(mean(w_tmax),1) if len(w_tmax) > 0 else "N/A",
", Rank: {} Warmest".format(rank(tmaxdeschist.index(round(mean(w_tmax),1))+1))
if len(w_tmax) > excludeweek and tmaxdeschist.index(round(mean(w_tmax),1)) <= tmaxaschist.index(round(mean(w_tmax),1)) else "",
", Rank: {} Coolest".format(rank(tmaxaschist.index(round(mean(w_tmax),1))+1))
if len(w_tmax) > excludeweek and tmaxaschist.index(round(mean(w_tmax),1)) <= tmaxdeschist.index(round(mean(w_tmax),1)) else ""
))
#print(tmaxaschist.index(round(mean(w_tmax),1)),tmaxdeschist.index(round(mean(w_tmax),1)))
print("Average Min Temperature: {}{}{}".format(
round(mean(w_tmin),1) if len(w_tmin) > 0 else "N/A",
", Rank: {} Warmest".format(rank(tmindeschist.index(round(mean(w_tmin),1))+1))
if tmindeschist.index(round(mean(w_tmin),1)) <= tminaschist.index(round(mean(w_tmin),1)) else "",
", Rank: {} Coolest".format(rank(tminaschist.index(round(mean(w_tmin),1))+1))
if len(w_tmin) > excludeweek and tminaschist.index(round(mean(w_tmin),1)) <= tmindeschist.index(round(mean(w_tmin),1)) else ""
))
#print(tminaschist.index(round(mean(w_tmin),1)),tmindeschist.index(round(mean(w_tmin),1)))
print("")
def monthStats(y,m):
"""Report on recorded statistics for a month of interest. It accepts only
arguments for the year and month of interest. Passed arguments MUST be
integers.
monthStats(year,month)
EXAMPLE: monthStats(2005,7) -> Returns a printout of month-based
statistics from July 2005.
"""
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
monthExists = checkDate(y,m)
if monthExists:
ranks = ["th","st","nd","rd","th","th","th","th","th","th"]
prcpaschist = sorted(list(set(list(var for var in clmt_vars_months["prcp"] for MONTH in clmt_vars_months["prcp"][var] if MONTH.month == m and clmt[MONTH.year][MONTH.month]["recordqty"] > excludemonth))))
prcpdeschist = sorted(list(set(list(var for var in clmt_vars_months["prcp"] for MONTH in clmt_vars_months["prcp"][var] if MONTH.month == m))),reverse=True)
#prcpDAYSaschist = sorted(set(list(clmt[Y][m]["prcpDAYS"] for Y in [yr for yr in clmt if type(yr) == int] if m in clmt[Y] and clmt[Y][m]["recordqty"] > excludemonth)))
#prcpDAYSdeschist = sorted(list(set(list(clmt[Y][m]["prcpDAYS"] for Y in [yr for yr in clmt if type(yr) == int] if m in clmt[Y]))),reverse=True)
#snowaschist = sorted(list(var for var in clmt_vars_months["snow"] for MONTH in clmt_vars_months["snow"][var] if MONTH.month == m and clmt[MONTH.year][MONTH.month]["recordqty"] > excludemonth))
snowdeschist = sorted(list(set(list(var for var in clmt_vars_months["snow"] for MONTH in clmt_vars_months["snow"][var] if MONTH.month == m))),reverse=True)
#snowDAYSdeschist = sorted(list(set(list(clmt[Y][m]["snowDAYS"] for Y in [yr for yr in clmt if type(yr) == int] if m in clmt[Y]))),reverse=True)
#snwddeschist = sorted(list(set(list(var for var in clmt_vars_months["snwd"] for MONTH in clmt_vars_months["snwd"][var] if MONTH.month == m))),reverse=True)
#snwdDAYSdeschist = sorted(list(set(list(clmt[Y][m]["snwdDAYS"] for Y in [yr for yr in clmt if type(yr) == int] if m in clmt[Y]))),reverse=True)
tmaxaschist = sorted(list(set(list(var for var in clmt_vars_months["tmax"] for MONTH in clmt_vars_months["tmax"][var] if MONTH.month == m))))
tmaxdeschist = sorted(list(set(list(var for var in clmt_vars_months["tmax"] for MONTH in clmt_vars_months["tmax"][var] if MONTH.month == m))),reverse=True)
tminaschist = sorted(list(set(list(var for var in clmt_vars_months["tmin"] for MONTH in clmt_vars_months["tmin"][var] if MONTH.month == m))))
tmindeschist = sorted(list(set(list(var for var in clmt_vars_months["tmin"] for MONTH in clmt_vars_months["tmin"][var] if MONTH.month == m))),reverse=True)
tavgaschist = sorted(list(set(list(var for var in clmt_vars_months["tavg"] for MONTH in clmt_vars_months["tavg"][var] if MONTH.month == m))))
tavgdeschist = sorted(list(set(list(var for var in clmt_vars_months["tavg"] for MONTH in clmt_vars_months["tavg"][var] if MONTH.month == m))),reverse=True)
#print(tavgdeschist)
#for x in [prcphist,snowhist,tmaxaschist,tmaxdeschist,tminaschist,tmindeschist,tavgaschist,tavgdeschist]: print(x)
if clmt[y][m]["recordqty"] <= excludemonth:
print("-------------------------------------")
print("*** MONLTHLY STATS MAY NOT BE COMPLETE FOR RELIANCE ON STATISTICS ***")
print("-------------------------------------")
print("Monthly Statistics for {} {}".format(calendar.month_name[m],y))
print("{}: {}".format(clmt["station"],clmt["station_name"]))
print("Quantity of Records: {}".format(clmt[y][m]["recordqty"]))
print("* Reported rankings are relative to the month of {}".format(calendar.month_name[m]))
print("-----")
# PRCP related
try: print("Total Precipitation: {}{}{}".format(
round(sum(clmt[y][m]["prcp"]),2),
", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(clmt[y][m]["prcp"]),2))+1)) if sum(clmt[y][m]["prcp"]) > 0 and prcpdeschist.index(round(sum(clmt[y][m]["prcp"]),2)) <= prcpaschist.index(round(sum(clmt[y][m]["prcp"]),2)) else "",
", Rank: {} Driest".format(rank(prcpaschist.index(round(sum(clmt[y][m]["prcp"]),2))+1)) if clmt[y][m]["recordqty"] > excludemonth and prcpaschist.index(round(sum(clmt[y][m]["prcp"]),2)) <= prcpdeschist.index(round(sum(clmt[y][m]["prcp"]),2)) else ""))
except: print("Total Precipitation: {}".format(round(sum(clmt[y][m]["prcp"]),2)))
print("Total Precipitation Days (>= T): {}".format(clmt[y][m]["prcpDAYS"]))
if round(sum(clmt[y][m]["prcp"]),2) > 0:
print("-- Highest Daily Precip: {}".format(clmt[y][m]["prcpPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y][m]["prcpPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y][m]["prcpPROP"]["day_max"][1][len(clmt[y][m]["prcpPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
# SNOW related
if sum(clmt[y][m]["snow"]) > 0 or clmt[y][m]["snowDAYS"] > 0:
print("Total Snow: {}{}".format(
round(sum(clmt[y][m]["snow"]),1),
", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(clmt[y][m]["snow"]),2))+1)) if sum(clmt[y][m]["snow"]) > 0 else ", -- ; "
))
print("Total Snow Days (>= T): {}".format(clmt[y][m]["snowDAYS"]))
if round(sum(clmt[y][m]["snow"]),1) > 0:
print("-- Highest Daily Snow Total: {}".format(clmt[y][m]["snowPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y][m]["snowPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y][m]["snowPROP"]["day_max"][1][len(clmt[y][m]["snowPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
# SNWD related
if clmt[y][m]["snwdDAYS"] > 0:
print("Total Days with Snow on the Ground ('snwd' >= T): {}".format(clmt[y][m]["snwdDAYS"]))
if any(v > 0 for v in clmt[y][m]["snwd"]): # If any of the snwd days are > 0
print("-- Highest Daily Snow-Depth Total: {}".format(clmt[y][m]["snwdPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y][m]["snwdPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y][m]["snwdPROP"]["day_max"][1][len(clmt[y][m]["snwdPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
try:
print("Average Temperature: {}{}{}".format(
round(mean(clmt[y][m]["tempAVGlist"]),1),
", Rank: {} Warmest".format(rank(tavgdeschist.index(round(mean(clmt[y][m]["tempAVGlist"]),1))+1)) if len(clmt[y][m]["tempAVGlist"]) > excludemonth*2 and tavgdeschist.index(round(mean(clmt[y][m]["tempAVGlist"]),1)) <= tavgaschist.index(round(mean(clmt[y][m]["tempAVGlist"]),1)) else "",
", Rank: {} Coolest".format(rank(tavgaschist.index(round(mean(clmt[y][m]["tempAVGlist"]),1))+1)) if len(clmt[y][m]["tempAVGlist"]) > excludemonth*2 and tavgaschist.index(round(mean(clmt[y][m]["tempAVGlist"]),1)) <= tavgdeschist.index(round(mean(clmt[y][m]["tempAVGlist"]),1)) else ""
))
except: print("Average Temperature: N/A")
try:
print("Average MAX Temperature: {}{}{}".format(
round(mean(clmt[y][m]["tmax"]),1),
", Rank: {} Warmest".format(rank(tmaxdeschist.index(round(mean(clmt[y][m]["tmax"]),1))+1)) if len(clmt[y][m]["tmax"]) > excludemonth and tmaxdeschist.index(round(mean(clmt[y][m]["tmax"]),1)) <= tmaxaschist.index(round(mean(clmt[y][m]["tmax"]),1)) else "",
", Rank: {} Coolest".format(rank(tmaxaschist.index(round(mean(clmt[y][m]["tmax"]),1))+1)) if len(clmt[y][m]["tmax"]) > excludemonth and tmaxaschist.index(round(mean(clmt[y][m]["tmax"]),1)) <= tmaxdeschist.index(round(mean(clmt[y][m]["tmax"]),1)) else ""
))
if round(sum(clmt[y][m]["tmax"]),1) > 0:
print("-- Warmest Daily TMAX: {}".format(clmt[y][m]["tmaxPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y][m]["tmaxPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y][m]["tmaxPROP"]["day_max"][1][len(clmt[y][m]["tmaxPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if round(sum(clmt[y][m]["tmax"]),1) > 0:
print("-- Coolest Daily TMAX: {}".format(clmt[y][m]["tmaxPROP"]["day_min"][0]),end = " ::: ")
for x in clmt[y][m]["tmaxPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y][m]["tmaxPROP"]["day_min"][1][len(clmt[y][m]["tmaxPROP"]["day_min"][1])-1] else print("{}".format(x.daystr))
except: print("Average MAX Temperature: N/A")
try:
print("Average MIN Temperature: {}{}{}".format(
round(mean(clmt[y][m]["tmin"]),1),
", Rank: {} Warmest".format(rank(tmindeschist.index(round(mean(clmt[y][m]["tmin"]),1))+1)) if len(clmt[y][m]["tmin"]) > excludemonth and tmindeschist.index(round(mean(clmt[y][m]["tmin"]),1)) <= tminaschist.index(round(mean(clmt[y][m]["tmin"]),1)) else "",
", Rank: {} Coolest".format(rank(tminaschist.index(round(mean(clmt[y][m]["tmin"]),1))+1)) if len(clmt[y][m]["tmin"]) > excludemonth and tminaschist.index(round(mean(clmt[y][m]["tmin"]),1)) <= tmindeschist.index(round(mean(clmt[y][m]["tmin"]),1)) else ""
))
if round(sum(clmt[y][m]["tmin"]),1) > 0:
print("-- Warmest Daily TMIN: {}".format(clmt[y][m]["tminPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y][m]["tminPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y][m]["tminPROP"]["day_max"][1][len(clmt[y][m]["tminPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if round(sum(clmt[y][m]["tmin"]),1) > 0:
print("-- Coolest Daily TMIN: {}".format(clmt[y][m]["tminPROP"]["day_min"][0]),end = " ::: ")
for x in clmt[y][m]["tminPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y][m]["tminPROP"]["day_min"][1][len(clmt[y][m]["tminPROP"]["day_min"][1])-1] else print("{}".format(x.daystr))
except: print("Average MIN Temperature: N/A")
if all(len(x) == 0 for x in [clmt[y][m]["tempAVGlist"],clmt[y][m]["tmax"],clmt[y][m]["tmin"]]):
print("*** No Reliable Temperature Data for {} {}".format(calendar.month_abbr[m],y))
print("-----")
def yearStats(y):
"""Report on recorded statistics for a year of interest. It accepts only
an argument for the year. Passed argument MUST be an integer.
yearStats(year)
EXAMPLE: yearStats(1945) -> Returns a printout of year-based statistics
from 1945
"""
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
# clmt[int(each[2][0:4])]["prcpPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]],"month_min":[999,[]]}
# clmt[int(each[2][0:4])]["snowPROP"] = {"day_max":[-1,[]],"month_max":[-1,[]]}
# clmt[int(each[2][0:4])]["tempAVGlist"] = []
# clmt[int(each[2][0:4])]["tmax"] = []
# clmt[int(each[2][0:4])]["tmaxPROP"] = {"day_max":[-999,[]],"day_min":[999,[]],"month_AVG_max":[-999,[]],"month_AVG_min":[999,[]]}
yearExists = checkDate(y)
if yearExists:
prcpaschist, prcpdeschist, prcpDAYSaschist, prcpDAYSdeschist, snowaschist, snowdeschist, snowDAYSaschist, snowDAYSdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist = yearRank("temps",5,yearStatsRun=True)
snwdDAYSdeschist = sorted(set(list(clmt[YR]["snwdDAYS"] for YR in [Y for Y in clmt if type(Y) == int] if clmt[YR]["snwdDAYS"] != 0)),reverse=True)
snwdDAYSaschist = sorted(set(list(clmt[YR]["snwdDAYS"] for YR in [Y for Y in clmt if type(Y) == int] if clmt[YR]["recordqty"] > excludeyear)))
#for x in [prcpaschist, prcpdeschist, snowaschist, snowdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist]: print(len(x))
print("")
print("{:^55}".format("Yearly Statistics for {}".format(y)))
print("{:^55}".format("{}: {}".format(clmt["station"],clmt["station_name"])))
print("{:^55}".format("Quantity of Records: {}".format(clmt[y]["recordqty"])))
if clmt[y]["recordqty"] <= excludeyear:
print("{:-^55}".format(""))
print("*** YEAR STATS MAY NOT BE COMPLETE FOR RELIANCE ON STATISTICS ***")
print("{:-^55}".format(""))
print("{:^6}|{:^7}|{:^7}|{:^7}|{:^7}|{:^7}|{:^7}|".format("","JAN","FEB","MAR","APR","MAY","JUN"))
print("{:-^55}".format(""))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"PRCP",
"{:.2f}".format(round(sum(clmt[y][1]["prcp"]),2)) if 1 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][2]["prcp"]),2)) if 2 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][3]["prcp"]),2)) if 3 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][4]["prcp"]),2)) if 4 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][5]["prcp"]),2)) if 5 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][6]["prcp"]),2)) if 6 in clmt[y] else "",
))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"SNOW",
"{:.1f}".format(round(sum(clmt[y][1]["snow"]),1)) if 1 in clmt[y] and (sum(clmt[y][1]["snow"]) > 0 or clmt[y][1]["snowDAYS"] > 0) else (" -- " if 1 in clmt[y] and sum(clmt[y][1]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][2]["snow"]),1)) if 2 in clmt[y] and (sum(clmt[y][2]["snow"]) > 0 or clmt[y][2]["snowDAYS"] > 0) else (" -- " if 2 in clmt[y] and sum(clmt[y][2]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][3]["snow"]),1)) if 3 in clmt[y] and (sum(clmt[y][3]["snow"]) > 0 or clmt[y][3]["snowDAYS"] > 0) else (" -- " if 3 in clmt[y] and sum(clmt[y][3]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][4]["snow"]),1)) if 4 in clmt[y] and (sum(clmt[y][4]["snow"]) > 0 or clmt[y][4]["snowDAYS"] > 0) else (" -- " if 4 in clmt[y] and sum(clmt[y][4]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][5]["snow"]),1)) if 5 in clmt[y] and (sum(clmt[y][5]["snow"]) > 0 or clmt[y][5]["snowDAYS"] > 0) else (" -- " if 5 in clmt[y] and sum(clmt[y][5]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][6]["snow"]),1)) if 6 in clmt[y] and (sum(clmt[y][6]["snow"]) > 0 or clmt[y][6]["snowDAYS"] > 0) else (" -- " if 6 in clmt[y] and sum(clmt[y][6]["snow"]) == 0 else ""),
))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"TAVG",
"{:.1f}".format(round(mean(clmt[y][1]["tempAVGlist"]),1)) if 1 in clmt[y] and len(clmt[y][1]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][2]["tempAVGlist"]),1)) if 2 in clmt[y] and len(clmt[y][2]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][3]["tempAVGlist"]),1)) if 3 in clmt[y] and len(clmt[y][3]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][4]["tempAVGlist"]),1)) if 4 in clmt[y] and len(clmt[y][4]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][5]["tempAVGlist"]),1)) if 5 in clmt[y] and len(clmt[y][5]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][6]["tempAVGlist"]),1)) if 6 in clmt[y] and len(clmt[y][6]["tempAVGlist"]) > 2 else "",
))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"TMAX",
"{:.1f}".format(round(mean(clmt[y][1]["tmax"]),1)) if 1 in clmt[y] and len(clmt[y][1]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][2]["tmax"]),1)) if 2 in clmt[y] and len(clmt[y][2]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][3]["tmax"]),1)) if 3 in clmt[y] and len(clmt[y][3]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][4]["tmax"]),1)) if 4 in clmt[y] and len(clmt[y][4]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][5]["tmax"]),1)) if 5 in clmt[y] and len(clmt[y][5]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][6]["tmax"]),1)) if 6 in clmt[y] and len(clmt[y][6]["tmax"]) > 1 else "",
))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"TMIN",
"{:.1f}".format(round(mean(clmt[y][1]["tmin"]),1)) if 1 in clmt[y] and len(clmt[y][1]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][2]["tmin"]),1)) if 2 in clmt[y] and len(clmt[y][2]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][3]["tmin"]),1)) if 3 in clmt[y] and len(clmt[y][3]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][4]["tmin"]),1)) if 4 in clmt[y] and len(clmt[y][4]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][5]["tmin"]),1)) if 5 in clmt[y] and len(clmt[y][5]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][6]["tmin"]),1)) if 6 in clmt[y] and len(clmt[y][6]["tmin"]) > 1 else "",
))
print("{:-^55}".format(""))
print("{:^6}|{:^7}|{:^7}|{:^7}|{:^7}|{:^7}|{:^7}|".format("","JUL","AUG","SEP","OCT","NOV","DEC"))
print("{:-^55}".format(""))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"PRCP",
"{:.2f}".format(round(sum(clmt[y][7]["prcp"]),2)) if 7 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][8]["prcp"]),2)) if 8 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][9]["prcp"]),2)) if 9 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][10]["prcp"]),2)) if 10 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][11]["prcp"]),2)) if 11 in clmt[y] else "",
"{:.2f}".format(round(sum(clmt[y][12]["prcp"]),2)) if 12 in clmt[y] else "",
))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"SNOW",
"{:.1f}".format(round(sum(clmt[y][7]["snow"]),1)) if 7 in clmt[y] and (sum(clmt[y][7]["snow"]) > 0 or clmt[y][7]["snowDAYS"] > 0) else (" -- " if 7 in clmt[y] and sum(clmt[y][7]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][8]["snow"]),1)) if 8 in clmt[y] and (sum(clmt[y][8]["snow"]) > 0 or clmt[y][8]["snowDAYS"] > 0) else (" -- " if 8 in clmt[y] and sum(clmt[y][8]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][9]["snow"]),1)) if 9 in clmt[y] and (sum(clmt[y][9]["snow"]) > 0 or clmt[y][9]["snowDAYS"] > 0) else (" -- " if 9 in clmt[y] and sum(clmt[y][9]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][10]["snow"]),1)) if 10 in clmt[y] and (sum(clmt[y][10]["snow"]) > 0 or clmt[y][10]["snowDAYS"] > 0) else (" -- " if 10 in clmt[y] and sum(clmt[y][10]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][11]["snow"]),1)) if 11 in clmt[y] and (sum(clmt[y][11]["snow"]) > 0 or clmt[y][11]["snowDAYS"] > 0) else (" -- " if 11 in clmt[y] and sum(clmt[y][11]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(clmt[y][12]["snow"]),1)) if 12 in clmt[y] and (sum(clmt[y][12]["snow"]) > 0 or clmt[y][12]["snowDAYS"] > 0) else (" -- " if 12 in clmt[y] and sum(clmt[y][12]["snow"]) == 0 else ""),
))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"TAVG",
"{:.1f}".format(round(mean(clmt[y][7]["tempAVGlist"]),1)) if 7 in clmt[y] and len(clmt[y][7]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][8]["tempAVGlist"]),1)) if 8 in clmt[y] and len(clmt[y][8]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][9]["tempAVGlist"]),1)) if 9 in clmt[y] and len(clmt[y][9]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][10]["tempAVGlist"]),1)) if 10 in clmt[y] and len(clmt[y][10]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][11]["tempAVGlist"]),1)) if 11 in clmt[y] and len(clmt[y][11]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(clmt[y][12]["tempAVGlist"]),1)) if 12 in clmt[y] and len(clmt[y][12]["tempAVGlist"]) > 2 else "",
))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"TMAX",
"{:.1f}".format(round(mean(clmt[y][7]["tmax"]),1)) if 7 in clmt[y] and len(clmt[y][7]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][8]["tmax"]),1)) if 8 in clmt[y] and len(clmt[y][8]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][9]["tmax"]),1)) if 9 in clmt[y] and len(clmt[y][9]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][10]["tmax"]),1)) if 10 in clmt[y] and len(clmt[y][10]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][11]["tmax"]),1)) if 11 in clmt[y] and len(clmt[y][11]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][12]["tmax"]),1)) if 12 in clmt[y] and len(clmt[y][12]["tmax"]) > 1 else "",
))
print("{:^6}|{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |{:>6} |".format(
"TMIN",
"{:.1f}".format(round(mean(clmt[y][7]["tmin"]),1)) if 7 in clmt[y] and len(clmt[y][7]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][8]["tmin"]),1)) if 8 in clmt[y] and len(clmt[y][8]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][9]["tmin"]),1)) if 9 in clmt[y] and len(clmt[y][9]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][10]["tmin"]),1)) if 10 in clmt[y] and len(clmt[y][10]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][11]["tmin"]),1)) if 11 in clmt[y] and len(clmt[y][11]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(clmt[y][12]["tmin"]),1)) if 12 in clmt[y] and len(clmt[y][12]["tmin"]) > 1 else "",
))
print("{:-^55}".format(""))
print(" Total Precipitation: {}".format(round(sum(clmt[y]["prcp"]),2)),end="")
try: print(", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(clmt[y]["prcp"]),2))+1)),end="") if sum(clmt[y]["prcp"]) > 0 and prcpdeschist.index(round(sum(clmt[y]["prcp"]),2)) <= prcpaschist.index(round(sum(clmt[y]["prcp"]),2)) else print("",end="")
except: print(", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(clmt[y]["prcp"]),2))+1)),end="")
try: print(", Rank: {} Driest".format(rank(prcpaschist.index(round(sum(clmt[y]["prcp"]),2))+1))) if clmt[y]["recordqty"] > excludeyear and prcpaschist.index(round(sum(clmt[y]["prcp"]),2)) <= prcpdeschist.index(round(sum(clmt[y]["prcp"]),2)) else print("")
except: print("")
print(" Total Precipitation Days (>=T): {}".format(clmt[y]["prcpDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(prcpDAYSdeschist.index(clmt[y]["prcpDAYS"])+1)),end="") if clmt[y]["prcpDAYS"] > 0 and prcpDAYSdeschist.index(clmt[y]["prcpDAYS"]) <= prcpDAYSaschist.index(clmt[y]["prcpDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(prcpDAYSdeschist.index(clmt[y]["prcpDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(prcpDAYSaschist.index(clmt[y]["prcpDAYS"])+1))) if prcpDAYSaschist.index(clmt[y]["prcpDAYS"]) <= prcpDAYSdeschist.index(clmt[y]["prcpDAYS"]) else print("")
except: print("")
if round(sum(clmt[y]["prcp"]),2) > 0:
print(" -- Highest Daily Precip: {}".format(clmt[y]["prcpPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y]["prcpPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y]["prcpPROP"]["day_max"][1][len(clmt[y]["prcpPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
print(" Total Snow: {}".format(round(sum(clmt[y]["snow"]),1)),end="")
try: print(", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(clmt[y]["snow"]),1))+1)),end="") if sum(clmt[y]["snow"]) > 0 and snowdeschist.index(round(sum(clmt[y]["snow"]),1)) <= snowaschist.index(round(sum(clmt[y]["snow"]),1)) else print("",end="")
except: print(", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(clmt[y]["snow"]),1))+1)),end="")
try: print(", Rank: {} Least-Snowiest".format(rank(snowaschist.index(round(sum(clmt[y]["snow"]),1))+1))) if clmt[y]["recordqty"] > excludeyear and snowaschist.index(round(sum(clmt[y]["snow"]),1)) <= snowdeschist.index(round(sum(clmt[y]["snow"]),1)) else print("")
except: print("")
if round(sum(clmt[y]["snow"]),1) > 0:
print(" -- Highest Daily Snow: {}".format(clmt[y]["snowPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y]["snowPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y]["snowPROP"]["day_max"][1][len(clmt[y]["snowPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
print(" Total Snow Days (>=T): {}".format(clmt[y]["snowDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(clmt[y]["snowDAYS"])+1)),end="") if clmt[y]["snowDAYS"] > 0 and snowDAYSdeschist.index(clmt[y]["snowDAYS"]) <= snowDAYSaschist.index(clmt[y]["snowDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(clmt[y]["snowDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(snowDAYSaschist.index(clmt[y]["snowDAYS"])+1))) if clmt[y]["recordqty"] > excludeyear and snowDAYSaschist.index(clmt[y]["snowDAYS"]) <= snowDAYSdeschist.index(clmt[y]["snowDAYS"]) else print("")
except: print("")
if clmt[y]["snwdDAYS"] > 0:
print(" Total Days w/Snow on the Ground (>=T): {}".format(clmt[y]["snwdDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(snwdDAYSdeschist.index(clmt[y]["snwdDAYS"])+1)),end="") if clmt[y]["snwdDAYS"] > 0 and snwdDAYSdeschist.index(clmt[y]["snwdDAYS"]) <= snwdDAYSaschist.index(clmt[y]["snwdDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(snwdDAYSdeschist.index(clmt[y]["snwdDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(snwdDAYSaschist.index(clmt[y]["snwdDAYS"])+1))) if clmt[y]["recordqty"] > excludeyear and snwdDAYSaschist.index(clmt[y]["snwdDAYS"]) <= snwdDAYSdeschist.index(clmt[y]["snwdDAYS"]) else print("")
except: print("")
if round(sum(clmt[y]["snwd"]),1) > 0:
print(" -- Highest Daily Snow-Depth: {}".format(clmt[y]["snwdPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y]["snwdPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y]["snwdPROP"]["day_max"][1][len(clmt[y]["snwdPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
try:
print(" Average Temperature: {}".format(round(mean(clmt[y]["tempAVGlist"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tavgdeschist.index(round(mean(clmt[y]["tempAVGlist"]),1))+1)),end="") if len(clmt[y]["tempAVGlist"]) > excludeyear*2 and tavgdeschist.index(round(mean(clmt[y]["tempAVGlist"]),1)) <= tavgaschist.index(round(mean(clmt[y]["tempAVGlist"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tavgaschist.index(round(mean(clmt[y]["tempAVGlist"]),1))+1))) if len(clmt[y]["tempAVGlist"]) > excludeyear*2 and tavgaschist.index(round(mean(clmt[y]["tempAVGlist"]),1)) <= tavgdeschist.index(round(mean(clmt[y]["tempAVGlist"]),1)) else print("")
except: print(" Average Temperature: N/A")
try:
print(" Avg MAX Temperature: {}".format(round(mean(clmt[y]["tmax"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tmaxdeschist.index(round(mean(clmt[y]["tmax"]),1))+1)),end="") if len(clmt[y]["tmax"]) > excludeyear and tmaxdeschist.index(round(mean(clmt[y]["tmax"]),1)) <= tmaxaschist.index(round(mean(clmt[y]["tmax"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tmaxaschist.index(round(mean(clmt[y]["tmax"]),1))+1))) if len(clmt[y]["tmax"]) > excludeyear and tmaxaschist.index(round(mean(clmt[y]["tmax"]),1)) <= tmaxdeschist.index(round(mean(clmt[y]["tmax"]),1)) else print("")
except: print(" Avg MAX Temperature: N/A")
if clmt[y]["tmaxPROP"]["day_max"][0] != -999:
print(" -- Warmest Daily TMAX: {}".format(clmt[y]["tmaxPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y]["tmaxPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y]["tmaxPROP"]["day_max"][1][len(clmt[y]["tmaxPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if clmt[y]["tmaxPROP"]["day_min"][0] != -999:
print(" -- Coolest Daily TMAX: {}".format(clmt[y]["tmaxPROP"]["day_min"][0]),end = " ::: ")
for x in clmt[y]["tmaxPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y]["tmaxPROP"]["day_min"][1][len(clmt[y]["tmaxPROP"]["day_min"][1])-1] else print("{}".format(x.daystr))
try:
print(" Avg MIN Temperature: {}".format(round(mean(clmt[y]["tmin"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tmindeschist.index(round(mean(clmt[y]["tmin"]),1))+1)),end="") if len(clmt[y]["tmin"]) > excludeyear and tmindeschist.index(round(mean(clmt[y]["tmin"]),1)) <= tminaschist.index(round(mean(clmt[y]["tmin"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tminaschist.index(round(mean(clmt[y]["tmin"]),1))+1))) if len(clmt[y]["tmin"]) > excludeyear and tminaschist.index(round(mean(clmt[y]["tmin"]),1)) <= tmindeschist.index(round(mean(clmt[y]["tmin"]),1)) else print("")
except: print(" Avg MIN Temperature: N/A")
if clmt[y]["tminPROP"]["day_max"][0] != -999:
print(" -- Warmest Daily TMIN: {}".format(clmt[y]["tminPROP"]["day_max"][0]),end = " ::: ")
for x in clmt[y]["tminPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y]["tminPROP"]["day_max"][1][len(clmt[y]["tminPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if clmt[y]["tminPROP"]["day_min"][0] != -999:
print(" -- Coolest Daily TMIN: {}".format(clmt[y]["tminPROP"]["day_min"][0]),end = " ::: ")
for x in clmt[y]["tminPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end=" ") if x != clmt[y]["tminPROP"]["day_min"][1][len(clmt[y]["tminPROP"]["day_min"][1])-1] else print("{}".format(x.daystr))
if all(len(x) == 0 for x in [clmt[y]["tempAVGlist"],clmt[y]["tmax"],clmt[y]["tmin"]]):
print("*** No Reliable Temperature Data for {} {}".format(calendar.month_abbr,y))
print("-----")
def seasonStats(y,season):
"""Report on recorded statistics for a meteorological season of interest
from a specific year. It accepts only arguments for the inquired year,
and season. The year must be an integer while the season must be in string
format.
seasonStats(YYYY,SEASON)
EXAMPLE: seasonStats(1933,"winter") -> Returns a printout of stats from
the Meteorological Winter of 1933
(inclusive of December 1933 -
February of 1934)
"""
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
if y not in metclmt: return print("Meteorological Year {} Not Found! Try again!".format(y))
if season.lower() not in ["spring","summer","fall","autumn","winter"]: return print("'{}' is not a valid season. Try again!".format(season))
if season.lower() == "autumn": season = "fall"
season = season.lower() # Puts season into requisite lower case to match metclmt[y] season dictionaries
m1 = metclmt[y][season]["valid"][0]
m2 = metclmt[y][season]["valid"][1]
m3 = metclmt[y][season]["valid"][2]
prcpaschist, prcpdeschist, prcpDAYSaschist, prcpDAYSdeschist, snowaschist, snowdeschist, snowDAYSaschist, snowDAYSdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist = seasonRank(season,"temp",5,seasonStatsRun=True)
#for x in [prcpaschist, prcpdeschist, snowaschist, snowdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist]: print(len(x))
#for x in [prcpaschist, prcpdeschist, snowaschist, snowdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist]: print(x)
try:
snwdDAYSdeschist = sorted(set(list(metclmt[YR][season]["snwdDAYS"] for YR in [Y for Y in metclmt if type(Y) == int] if metclmt[YR][season]["snwdDAYS"] != 0)),reverse=True)
snwdDAYSaschist = sorted(set(list(metclmt[YR][season]["snwdDAYS"] for YR in [Y for Y in metclmt if type(Y) == int] if metclmt[YR][season]["recordqty"] > excludeyear)))
except Exception as e: print(e)
print("{:-^40}".format(""))
if season == "winter": print("{:^40}".format("Seasonal Statistics for Meteorological {} {}-{}".format(season.capitalize(),y,str(y+1)[2:])))
else: print("{:^40}".format("Seasonal Statistics for Meteorological {} {}".format(season.capitalize(),y)))
print("{:^40}".format("{}: {}".format(metclmt["station"],metclmt["station_name"])))
print("{:^40}".format("Quantity of Records: {}".format(metclmt[y][season]["recordqty"])))
if metclmt[y][season]["recordqty"] <= excludeseason:
print("{:-^40}".format(""))
print("*** SEASONAL STATS LIKELY NOT COMPLETE FOR RELIANCE ON STATISTICS ***")
print("{:-^40}".format(""))
# metclmt[YYYY][s]["valid"] = [3,4,5]
print("{:^6}|{:^10}|{:^10}|{:^10}|".format(
"",
"{} {}".format(calendar.month_abbr[m1].upper(),y) if m1 in [3,4,5,6,7,8,9,10,11,12] else "{} {}".format(calendar.month_abbr[m1].upper(),y+1),
"{} {}".format(calendar.month_abbr[m2].upper(),y) if m2 in [3,4,5,6,7,8,9,10,11,12] else "{} {}".format(calendar.month_abbr[m2].upper(),y+1),
"{} {}".format(calendar.month_abbr[m3].upper(),y) if m3 in [3,4,5,6,7,8,9,10,11,12] else "{} {}".format(calendar.month_abbr[m3].upper(),y+1)
))
print("{:^6}|{:>8} |{:>8} |{:>8} |".format(
"PRCP",
"{:.2f}".format(round(sum(metclmt[y][m1]["prcp"]),2)) if m1 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][m2]["prcp"]),2)) if m2 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][m3]["prcp"]),2)) if m3 in metclmt[y] else ""
))
print("{:^6}|{:>8} |{:>8} |{:>8} |".format(
"SNOW",
"{:.1f}".format(round(sum(metclmt[y][m1]["snow"]),1)) if m1 in metclmt[y] and (sum(metclmt[y][m1]["snow"]) > 0 or metclmt[y][m1]["snowDAYS"] > 0) else (" -- " if m1 in metclmt[y] and sum(metclmt[y][m1]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][m2]["snow"]),1)) if m2 in metclmt[y] and (sum(metclmt[y][m2]["snow"]) > 0 or metclmt[y][m2]["snowDAYS"] > 0) else (" -- " if m2 in metclmt[y] and sum(metclmt[y][m2]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][m3]["snow"]),1)) if m3 in metclmt[y] and (sum(metclmt[y][m3]["snow"]) > 0 or metclmt[y][m3]["snowDAYS"] > 0) else (" -- " if m3 in metclmt[y] and sum(metclmt[y][m3]["snow"]) == 0 else "")
))
print("{:^6}|{:>8} |{:>8} |{:>8} |".format(
"TAVG",
"{:.1f}".format(round(mean(metclmt[y][m1]["tempAVGlist"]),1)) if m1 in metclmt[y] and len(metclmt[y][m1]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][m2]["tempAVGlist"]),1)) if m2 in metclmt[y] and len(metclmt[y][m2]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][m3]["tempAVGlist"]),1)) if m3 in metclmt[y] and len(metclmt[y][m3]["tempAVGlist"]) > 2 else ""
))
print("{:^6}|{:>8} |{:>8} |{:>8} |".format(
"TMAX",
"{:.1f}".format(round(mean(metclmt[y][m1]["tmax"]),1)) if m1 in metclmt[y] and len(metclmt[y][m1]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][m2]["tmax"]),1)) if m2 in metclmt[y] and len(metclmt[y][m2]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][m3]["tmax"]),1)) if m3 in metclmt[y] and len(metclmt[y][m3]["tmax"]) > 1 else ""
))
print("{:^6}|{:>8} |{:>8} |{:>8} |".format(
"TMIN",
"{:.1f}".format(round(mean(metclmt[y][m1]["tmin"]),1)) if m1 in metclmt[y] and len(metclmt[y][m1]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][m2]["tmin"]),1)) if m2 in metclmt[y] and len(metclmt[y][m2]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][m3]["tmin"]),1)) if m3 in metclmt[y] and len(metclmt[y][m3]["tmin"]) > 1 else ""
))
print("{:-^40}".format(""))
print(" Total Precipitation: {}".format(round(sum(metclmt[y][season]["prcp"]),2)),end="")
try: print(", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(metclmt[y][season]["prcp"]),2))+1)),end="") if sum(metclmt[y][season]["prcp"]) > 0 and prcpdeschist.index(round(sum(metclmt[y][season]["prcp"]),2)) <= prcpaschist.index(round(sum(metclmt[y][season]["prcp"]),2)) else print("",end="")
except: print(", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(metclmt[y][season]["prcp"]),2))+1)),end="")
try: print(", Rank: {} Driest".format(rank(prcpaschist.index(round(sum(metclmt[y][season]["prcp"]),2))+1))) if metclmt[y][season]["recordqty"] > excludeseason and prcpaschist.index(round(sum(metclmt[y][season]["prcp"]),2)) <= prcpdeschist.index(round(sum(metclmt[y][season]["prcp"]),2)) else print("")
except: print("")
print(" Total Precipitation Days (>=T): {}".format(metclmt[y][season]["prcpDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(prcpDAYSdeschist.index(metclmt[y][season]["prcpDAYS"])+1)),end="") if metclmt[y][season]["prcpDAYS"] > 0 and prcpDAYSdeschist.index(metclmt[y][season]["prcpDAYS"]) <= prcpDAYSaschist.index(metclmt[y][season]["prcpDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(prcpDAYSdeschist.index(metclmt[y][season]["prcpDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(prcpDAYSaschist.index(metclmt[y][season]["prcpDAYS"])+1))) if prcpDAYSaschist.index(metclmt[y][season]["prcpDAYS"]) <= prcpDAYSdeschist.index(metclmt[y][season]["prcpDAYS"]) else print("")
except: print("")
if round(sum(metclmt[y][season]["prcp"]),2) > 0:
print(" -- Highest Daily Precip: {}".format(metclmt[y][season]["prcpPROP"]["day_max"][0]),end=" ::: ")
for x in range(len(metclmt[y][season]["prcpPROP"]["day_max"][1])):
if x != len(metclmt[y][season]["prcpPROP"]["day_max"][1])-1: print("{},".format(metclmt[y][season]["prcpPROP"]["day_max"][1][x].daystr),end=" ")
else: print("{}".format(metclmt[y][season]["prcpPROP"]["day_max"][1][x].daystr))
if round(sum(metclmt[y][season]["snow"]),1) > 0 or metclmt[y][season]["snowDAYS"] > 0:
print(" Total Snow: {}".format(round(sum(metclmt[y][season]["snow"]),1)),end="")
try: print(", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(metclmt[y][season]["snow"]),1))+1)),end="") if sum(metclmt[y][season]["snow"]) > 0 and snowdeschist.index(round(sum(metclmt[y][season]["snow"]),1)) <= snowaschist.index(round(sum(metclmt[y][season]["snow"]),1)) else print("",end="")
except: print(", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(metclmt[y][season]["snow"]),1))+1)),end="")
try: print(", Rank: {} Least-Snowiest".format(rank(snowaschist.index(round(sum(metclmt[y][season]["snow"]),1))+1))) if metclmt[y][season]["recordqty"] > excludeseason and snowaschist.index(round(sum(metclmt[y][season]["snow"]),1)) <= snowdeschist.index(round(sum(metclmt[y][season]["snow"]),1)) else print("")
except: print("")
print(" Total Snow Days (>=T): {}".format(metclmt[y][season]["snowDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(metclmt[y][season]["snowDAYS"])+1)),end="") if metclmt[y][season]["snowDAYS"] > 0 and snowDAYSdeschist.index(metclmt[y][season]["snowDAYS"]) <= snowDAYSaschist.index(metclmt[y][season]["snowDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(metclmt[y][season]["snowDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(snowDAYSaschist.index(metclmt[y][season]["snowDAYS"])+1))) if metclmt[y][season]["recordqty"] > excludeseason and snowDAYSaschist.index(metclmt[y][season]["snowDAYS"]) <= snowDAYSdeschist.index(metclmt[y][season]["snowDAYS"]) else print("")
except: print("")
if metclmt[y][season]["snowPROP"]["day_max"][0] > 0:
print(" -- Highest Daily Snow: {}".format(metclmt[y][season]["snowPROP"]["day_max"][0]),end=" ::: ")
for x in range(len(metclmt[y][season]["snowPROP"]["day_max"][1])):
if x != len(metclmt[y][season]["snowPROP"]["day_max"][1])-1: print("{},".format(metclmt[y][season]["snowPROP"]["day_max"][1][x].daystr),end=" ")
else: print("{}".format(metclmt[y][season]["snowPROP"]["day_max"][1][x].daystr))
print(" Total Snow Days (>=T): {}".format(metclmt[y][season]["snowDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(metclmt[y][season]["snowDAYS"])+1)),end="") if metclmt[y][season]["snowDAYS"] > 0 and snowDAYSdeschist.index(metclmt[y][season]["snowDAYS"]) <= snowDAYSaschist.index(metclmt[y][season]["snowDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(metclmt[y][season]["snowDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(snowDAYSaschist.index(metclmt[y][season]["snowDAYS"])+1))) if metclmt[y][season]["recordqty"] > excludeyear and snowDAYSaschist.index(metclmt[y][season]["snowDAYS"]) <= snowDAYSdeschist.index(metclmt[y][season]["snowDAYS"]) else print("")
except: print("")
if metclmt[y][season]["snwdDAYS"] > 0:
print(" Total Days w/Snow on the Ground (>=T): {}".format(metclmt[y][season]["snwdDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(snwdDAYSdeschist.index(metclmt[y][season]["snwdDAYS"])+1)),end="") if metclmt[y][season]["snwdDAYS"] > 0 and snwdDAYSdeschist.index(metclmt[y][season]["snwdDAYS"]) <= snwdDAYSaschist.index(metclmt[y][season]["snwdDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(snwdDAYSdeschist.index(metclmt[y][season]["snwdDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(snwdDAYSaschist.index(metclmt[y][season]["snwdDAYS"])+1))) if metclmt[y][season]["recordqty"] > excludeyear and snwdDAYSaschist.index(metclmt[y][season]["snwdDAYS"]) <= snwdDAYSdeschist.index(metclmt[y][season]["snwdDAYS"]) else print("")
except: print("")
if round(sum(metclmt[y][season]["snwd"]),1) > 0:
print(" -- Highest Daily Snow-Depth: {}".format(metclmt[y][season]["snwdPROP"]["day_max"][0]),end = " ::: ")
for x in metclmt[y][season]["snwdPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y][season]["snwdPROP"]["day_max"][1][len(metclmt[y][season]["snwdPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if len(metclmt[y][season]["tempAVGlist"]) <= excludeseason_tavg and metclmt[y][season]["recordqty"] > excludeseason:
print("{:-^55}".format(""))
print("*** INSUFFICIENT TEMPERATURE DATA FOR SEASON LIKELY ***")
print("{:-^55}".format(""))
try:
print(" Average Temperature: {}".format(round(mean(metclmt[y][season]["tempAVGlist"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tavgdeschist.index(round(mean(metclmt[y][season]["tempAVGlist"]),1))+1)),end="") if len(metclmt[y][season]["tempAVGlist"]) > excludeseason*2 and tavgdeschist.index(round(mean(metclmt[y][season]["tempAVGlist"]),1)) <= tavgaschist.index(round(mean(metclmt[y][season]["tempAVGlist"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tavgaschist.index(round(mean(metclmt[y][season]["tempAVGlist"]),1))+1))) if len(metclmt[y][season]["tempAVGlist"]) > excludeseason*2 and tavgaschist.index(round(mean(metclmt[y][season]["tempAVGlist"]),1)) <= tavgdeschist.index(round(mean(metclmt[y][season]["tempAVGlist"]),1)) else print("")
except: print(" Average Temperature: N/A")
try:
print(" Avg MAX Temperature: {}".format(round(mean(metclmt[y][season]["tmax"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tmaxdeschist.index(round(mean(metclmt[y][season]["tmax"]),1))+1)),end="") if len(metclmt[y][season]["tmax"]) > excludeseason and tmaxdeschist.index(round(mean(metclmt[y][season]["tmax"]),1)) <= tmaxaschist.index(round(mean(metclmt[y][season]["tmax"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tmaxaschist.index(round(mean(metclmt[y][season]["tmax"]),1))+1))) if len(metclmt[y][season]["tmax"]) > excludeseason and tmaxaschist.index(round(mean(metclmt[y][season]["tmax"]),1)) <= tmaxdeschist.index(round(mean(metclmt[y][season]["tmax"]),1)) else print("")
except: print(" Avg MAX Temperature: N/A")
if metclmt[y][season]["tmaxPROP"]["day_max"][0] != -999:
print(" -- Warmest Daily TMAX: {}".format(metclmt[y][season]["tmaxPROP"]["day_max"][0]),end = " ::: ")
for x in metclmt[y][season]["tmaxPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y][season]["tmaxPROP"]["day_max"][1][len(metclmt[y][season]["tmaxPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if metclmt[y][season]["tmaxPROP"]["day_min"][0] != -999:
print(" -- Coolest Daily TMAX: {}".format(metclmt[y][season]["tmaxPROP"]["day_min"][0]),end = " ::: ")
for x in metclmt[y][season]["tmaxPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y][season]["tmaxPROP"]["day_min"][1][len(metclmt[y][season]["tmaxPROP"]["day_min"][1])-1] else print("{}".format(x.daystr))
try:
print(" Avg MIN Temperature: {}".format(round(mean(metclmt[y][season]["tmin"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tmindeschist.index(round(mean(metclmt[y][season]["tmin"]),1))+1)),end="") if len(metclmt[y][season]["tmin"]) > excludeseason and tmindeschist.index(round(mean(metclmt[y][season]["tmin"]),1)) <= tminaschist.index(round(mean(metclmt[y][season]["tmin"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tminaschist.index(round(mean(metclmt[y][season]["tmin"]),1))+1))) if len(metclmt[y][season]["tmin"]) > excludeseason and tminaschist.index(round(mean(metclmt[y][season]["tmin"]),1)) <= tmindeschist.index(round(mean(metclmt[y][season]["tmin"]),1)) else print("")
except: print(" Avg MIN Temperature: N/A")
if metclmt[y][season]["tminPROP"]["day_max"][0] != -999:
print(" -- Warmest Daily TMIN: {}".format(metclmt[y][season]["tminPROP"]["day_max"][0]),end = " ::: ")
for x in metclmt[y][season]["tminPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y][season]["tminPROP"]["day_max"][1][len(metclmt[y][season]["tminPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if metclmt[y][season]["tminPROP"]["day_min"][0] != -999:
print(" -- Coolest Daily TMIN: {}".format(metclmt[y][season]["tminPROP"]["day_min"][0]),end = " ::: ")
for x in metclmt[y][season]["tminPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y][season]["tminPROP"]["day_min"][1][len(metclmt[y][season]["tminPROP"]["day_min"][1])-1] else print("{}".format(x.daystr))
print("-----")
def metYearStats(y):
"""Report on recorded statistics for a meteorological year of interest. It
only accepts an argument for the inquired year. Meteorological years run
from March to February of the following year (Spring to Winter).The year
must be an integer.
metYearStats(YYYY)
EXAMPLE: metYearStats(1985) -> Returns a printout of stats from the
Meteorological Year of 1985
(inclusive of March 1985 -
February of 1986)
"""
if len(metclmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
if y not in metclmt: return print("* A record for {} not found in metclmt *".format(y))
prcpaschist, prcpdeschist, prcpDAYSaschist, prcpDAYSdeschist, snowaschist, snowdeschist, snowDAYSaschist, snowDAYSdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist = metYearRank("temps",5,yearStatsRun=True)
try:
snwdDAYSdeschist = sorted(set(list(metclmt[YR]["snwdDAYS"] for YR in [Y for Y in metclmt if type(Y) == int] if metclmt[YR]["snwdDAYS"] != 0)),reverse=True)
snwdDAYSaschist = sorted(set(list(metclmt[YR]["snwdDAYS"] for YR in [Y for Y in metclmt if type(Y) == int] if metclmt[YR]["recordqty"] > excludeyear)))
except Exception as e: print(e)
print("")
print("{:^73}".format("Statistics for Meteorological Year {}".format(y)))
print("{:^73}".format("{}: {}".format(clmt["station"],clmt["station_name"])))
print("{:^73}".format("Quantity of Records: {}".format(clmt[y]["recordqty"])))
if metclmt[y]["recordqty"] <= excludeyear:
print("{:-^73}".format(""))
print("*** MET. YEAR STATS MAY NOT BE COMPLETE FOR RELIANCE ON STATISTICS ***")
print("{:-^73}".format(""))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|".format("","MAR {}".format(y),"APR {}".format(y),"MAY {}".format(y),"JUN {}".format(y),"JUL {}".format(y),"AUG {}".format(y)))
print("{:-^73}".format(""))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"PRCP",
"{:.2f}".format(round(sum(metclmt[y][3]["prcp"]),2)) if 3 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][4]["prcp"]),2)) if 4 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][5]["prcp"]),2)) if 5 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][6]["prcp"]),2)) if 6 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][7]["prcp"]),2)) if 7 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][8]["prcp"]),2)) if 8 in metclmt[y] else "",
))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"SNOW",
"{:.1f}".format(round(sum(metclmt[y][3]["snow"]),1)) if 3 in metclmt[y] and (sum(metclmt[y][3]["snow"]) > 0 or metclmt[y][3]["snowDAYS"] > 0) else (" -- " if 3 in metclmt[y] and sum(metclmt[y][3]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][4]["snow"]),1)) if 4 in metclmt[y] and (sum(metclmt[y][4]["snow"]) > 0 or metclmt[y][4]["snowDAYS"] > 0) else (" -- " if 4 in metclmt[y] and sum(metclmt[y][4]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][5]["snow"]),1)) if 5 in metclmt[y] and (sum(metclmt[y][5]["snow"]) > 0 or metclmt[y][5]["snowDAYS"] > 0) else (" -- " if 5 in metclmt[y] and sum(metclmt[y][5]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][6]["snow"]),1)) if 6 in metclmt[y] and (sum(metclmt[y][6]["snow"]) > 0 or metclmt[y][6]["snowDAYS"] > 0) else (" -- " if 6 in metclmt[y] and sum(metclmt[y][6]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][7]["snow"]),1)) if 7 in metclmt[y] and (sum(metclmt[y][7]["snow"]) > 0 or metclmt[y][7]["snowDAYS"] > 0) else (" -- " if 7 in metclmt[y] and sum(metclmt[y][7]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][8]["snow"]),1)) if 8 in metclmt[y] and (sum(metclmt[y][8]["snow"]) > 0 or metclmt[y][8]["snowDAYS"] > 0) else (" -- " if 8 in metclmt[y] and sum(metclmt[y][8]["snow"]) == 0 else ""),
))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"TAVG",
"{:.1f}".format(round(mean(metclmt[y][3]["tempAVGlist"]),1)) if 3 in metclmt[y] and len(metclmt[y][3]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][4]["tempAVGlist"]),1)) if 4 in metclmt[y] and len(metclmt[y][4]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][5]["tempAVGlist"]),1)) if 5 in metclmt[y] and len(metclmt[y][5]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][6]["tempAVGlist"]),1)) if 6 in metclmt[y] and len(metclmt[y][6]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][7]["tempAVGlist"]),1)) if 7 in metclmt[y] and len(metclmt[y][7]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][8]["tempAVGlist"]),1)) if 8 in metclmt[y] and len(metclmt[y][8]["tempAVGlist"]) > 2 else "",
))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"TMAX",
"{:.1f}".format(round(mean(metclmt[y][3]["tmax"]),1)) if 3 in metclmt[y] and len(metclmt[y][3]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][4]["tmax"]),1)) if 4 in metclmt[y] and len(metclmt[y][4]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][5]["tmax"]),1)) if 5 in metclmt[y] and len(metclmt[y][5]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][6]["tmax"]),1)) if 6 in metclmt[y] and len(metclmt[y][6]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][7]["tmax"]),1)) if 7 in metclmt[y] and len(metclmt[y][7]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][8]["tmax"]),1)) if 8 in metclmt[y] and len(metclmt[y][8]["tmax"]) > 1 else "",
))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"TMIN",
"{:.1f}".format(round(mean(metclmt[y][3]["tmin"]),1)) if 3 in metclmt[y] and len(metclmt[y][3]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][4]["tmin"]),1)) if 4 in metclmt[y] and len(metclmt[y][4]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][5]["tmin"]),1)) if 5 in metclmt[y] and len(metclmt[y][5]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][6]["tmin"]),1)) if 6 in metclmt[y] and len(metclmt[y][6]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][7]["tmin"]),1)) if 7 in metclmt[y] and len(metclmt[y][7]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][8]["tmin"]),1)) if 8 in metclmt[y] and len(metclmt[y][8]["tmin"]) > 1 else "",
))
print("{:-^73}".format(""))
print("{:^6}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|{:^10}|".format("","SEP {}".format(y),"OCT {}".format(y),"NOV {}".format(y),"DEC {}".format(y),"JAN {}".format(y+1),"FEB {}".format(y+1)))
print("{:-^73}".format(""))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"PRCP",
"{:.2f}".format(round(sum(metclmt[y][9]["prcp"]),2)) if 9 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][10]["prcp"]),2)) if 10 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][11]["prcp"]),2)) if 11 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][12]["prcp"]),2)) if 12 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][1]["prcp"]),2)) if 1 in metclmt[y] else "",
"{:.2f}".format(round(sum(metclmt[y][2]["prcp"]),2)) if 2 in metclmt[y] else "",
))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"SNOW",
"{:.1f}".format(round(sum(metclmt[y][9]["snow"]),1)) if 9 in metclmt[y] and (sum(metclmt[y][9]["snow"]) > 0 or metclmt[y][9]["snowDAYS"] > 0) else (" -- " if 9 in metclmt[y] and sum(metclmt[y][9]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][10]["snow"]),1)) if 10 in metclmt[y] and (sum(metclmt[y][10]["snow"]) > 0 or metclmt[y][10]["snowDAYS"] > 0) else (" -- " if 10 in metclmt[y] and sum(metclmt[y][10]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][11]["snow"]),1)) if 11 in metclmt[y] and (sum(metclmt[y][11]["snow"]) > 0 or metclmt[y][11]["snowDAYS"] > 0) else (" -- " if 11 in metclmt[y] and sum(metclmt[y][11]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][12]["snow"]),1)) if 12 in metclmt[y] and (sum(metclmt[y][12]["snow"]) > 0 or metclmt[y][12]["snowDAYS"] > 0) else (" -- " if 12 in metclmt[y] and sum(metclmt[y][12]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][1]["snow"]),1)) if 1 in metclmt[y] and (sum(metclmt[y][1]["snow"]) > 0 or metclmt[y][1]["snowDAYS"] > 0) else (" -- " if 1 in metclmt[y] and sum(metclmt[y][1]["snow"]) == 0 else ""),
"{:.1f}".format(round(sum(metclmt[y][2]["snow"]),1)) if 2 in metclmt[y] and (sum(metclmt[y][2]["snow"]) > 0 or metclmt[y][2]["snowDAYS"] > 0) else (" -- " if 2 in metclmt[y] and sum(metclmt[y][2]["snow"]) == 0 else ""),
))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"TAVG",
"{:.1f}".format(round(mean(metclmt[y][9]["tempAVGlist"]),1)) if 9 in metclmt[y] and len(metclmt[y][9]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][10]["tempAVGlist"]),1)) if 10 in metclmt[y] and len(metclmt[y][10]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][11]["tempAVGlist"]),1)) if 11 in metclmt[y] and len(metclmt[y][11]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][12]["tempAVGlist"]),1)) if 12 in metclmt[y] and len(metclmt[y][12]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][1]["tempAVGlist"]),1)) if 1 in metclmt[y] and len(metclmt[y][1]["tempAVGlist"]) > 2 else "",
"{:.1f}".format(round(mean(metclmt[y][2]["tempAVGlist"]),1)) if 2 in metclmt[y] and len(metclmt[y][2]["tempAVGlist"]) > 2 else "",
))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"TMAX",
"{:.1f}".format(round(mean(metclmt[y][9]["tmax"]),1)) if 9 in metclmt[y] and len(metclmt[y][9]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][10]["tmax"]),1)) if 10 in metclmt[y] and len(metclmt[y][10]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][11]["tmax"]),1)) if 11 in metclmt[y] and len(metclmt[y][11]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][12]["tmax"]),1)) if 12 in metclmt[y] and len(metclmt[y][12]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][1]["tmax"]),1)) if 1 in metclmt[y] and len(metclmt[y][1]["tmax"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][2]["tmax"]),1)) if 2 in metclmt[y] and len(metclmt[y][2]["tmax"]) > 1 else "",
))
print("{:^6}|{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |{:>8} |".format(
"TMIN",
"{:.1f}".format(round(mean(metclmt[y][9]["tmin"]),1)) if 9 in metclmt[y] and len(metclmt[y][9]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][10]["tmin"]),1)) if 10 in metclmt[y] and len(metclmt[y][10]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][11]["tmin"]),1)) if 11 in metclmt[y] and len(metclmt[y][11]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][12]["tmin"]),1)) if 12 in metclmt[y] and len(metclmt[y][12]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][1]["tmin"]),1)) if 1 in metclmt[y] and len(metclmt[y][1]["tmin"]) > 1 else "",
"{:.1f}".format(round(mean(metclmt[y][2]["tmin"]),1)) if 2 in metclmt[y] and len(metclmt[y][2]["tmin"]) > 1 else "",
))
print("{:-^73}".format(""))
print(" Total Precipitation: {}".format(round(sum(metclmt[y]["prcp"]),2)),end="")
try: print(", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(metclmt[y]["prcp"]),2))+1)),end="") if sum(metclmt[y]["prcp"]) > 0 and prcpdeschist.index(round(sum(metclmt[y]["prcp"]),2)) <= prcpaschist.index(round(sum(metclmt[y]["prcp"]),2)) else print("",end="")
except: print(", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(metclmt[y]["prcp"]),2))+1)),end="")
try: print(", Rank: {} Driest".format(rank(prcpaschist.index(round(sum(metclmt[y]["prcp"]),2))+1))) if metclmt[y]["recordqty"] > excludeyear and prcpaschist.index(round(sum(metclmt[y]["prcp"]),2)) <= prcpdeschist.index(round(sum(metclmt[y]["prcp"]),2)) else print("")
except: print("")
print(" Total Precipitation Days (>=T): {}".format(metclmt[y]["prcpDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(prcpDAYSdeschist.index(metclmt[y]["prcpDAYS"])+1)),end="") if metclmt[y]["prcpDAYS"] > 0 and prcpDAYSdeschist.index(metclmt[y]["prcpDAYS"]) <= prcpDAYSaschist.index(metclmt[y]["prcpDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(prcpDAYSdeschist.index(metclmt[y]["prcpDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(prcpDAYSaschist.index(metclmt[y]["prcpDAYS"])+1))) if prcpDAYSaschist.index(metclmt[y]["prcpDAYS"]) <= prcpDAYSdeschist.index(metclmt[y]["prcpDAYS"]) else print("")
except: print("")
if round(sum(metclmt[y]["prcp"]),2) > 0:
print(" -- Highest Daily Precip: {}".format(metclmt[y]["prcpPROP"]["day_max"][0]),end = " ::: ")
for x in metclmt[y]["prcpPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y]["prcpPROP"]["day_max"][1][len(metclmt[y]["prcpPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
print(" Total Snow: {}".format(round(sum(metclmt[y]["snow"]),1)),end="")
try: print(", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(metclmt[y]["snow"]),1))+1)),end="") if sum(metclmt[y]["snow"]) > 0 and snowdeschist.index(round(sum(metclmt[y]["snow"]),1)) <= snowaschist.index(round(sum(metclmt[y]["snow"]),1)) else print("",end="")
except: print(", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(metclmt[y]["snow"]),1))+1)),end="")
try: print(", Rank: {} Least-Snowiest".format(rank(snowaschist.index(round(sum(metclmt[y]["snow"]),1))+1))) if metclmt[y]["recordqty"] > excludeyear and snowaschist.index(round(sum(metclmt[y]["snow"]),1)) <= snowdeschist.index(round(sum(metclmt[y]["snow"]),1)) else print("")
except: print("")
print(" Total Snow Days (>=T): {}".format(metclmt[y]["snowDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(metclmt[y]["snowDAYS"])+1)),end="") if metclmt[y]["snowDAYS"] > 0 and snowDAYSdeschist.index(metclmt[y]["snowDAYS"]) <= snowDAYSaschist.index(metclmt[y]["snowDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(metclmt[y]["snowDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(snowDAYSaschist.index(metclmt[y]["snowDAYS"])+1))) if metclmt[y]["recordqty"] > excludeyear and snowDAYSaschist.index(metclmt[y]["snowDAYS"]) <= snowDAYSdeschist.index(metclmt[y]["snowDAYS"]) else print("")
except: print("")
if metclmt[y]["snwdDAYS"] > 0:
print(" Total Days w/Snow on the Ground (>=T): {}".format(metclmt[y]["snwdDAYS"]),end="")
try: print(", Rank: {} Most".format(rank(snwdDAYSdeschist.index(metclmt[y]["snwdDAYS"])+1)),end="") if metclmt[y]["snwdDAYS"] > 0 and snwdDAYSdeschist.index(metclmt[y]["snwdDAYS"]) <= snwdDAYSaschist.index(metclmt[y]["snwdDAYS"]) else print("",end="")
except: print(", Rank: {} Most".format(rank(snwdDAYSdeschist.index(metclmt[y]["snwdDAYS"])+1)),end="")
try: print(", Rank: {} Least".format(rank(snwdDAYSaschist.index(metclmt[y]["snwdDAYS"])+1))) if metclmt[y]["recordqty"] > excludeyear and snwdDAYSaschist.index(metclmt[y]["snwdDAYS"]) <= snwdDAYSdeschist.index(metclmt[y]["snwdDAYS"]) else print("")
except: print("")
if round(sum(metclmt[y]["snwd"]),1) > 0:
print(" -- Highest Daily Snow-Depth: {}".format(metclmt[y]["snwdPROP"]["day_max"][0]),end = " ::: ")
for x in metclmt[y]["snwdPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y]["snwdPROP"]["day_max"][1][len(metclmt[y]["snwdPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
try:
print(" Average Temperature: {}".format(round(mean(metclmt[y]["tempAVGlist"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tavgdeschist.index(round(mean(metclmt[y]["tempAVGlist"]),1))+1)),end="") if len(metclmt[y]["tempAVGlist"]) > excludeyear*2 and tavgdeschist.index(round(mean(metclmt[y]["tempAVGlist"]),1)) <= tavgaschist.index(round(mean(metclmt[y]["tempAVGlist"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tavgaschist.index(round(mean(metclmt[y]["tempAVGlist"]),1))+1))) if len(metclmt[y]["tempAVGlist"]) > excludeyear*2 and tavgaschist.index(round(mean(metclmt[y]["tempAVGlist"]),1)) <= tavgdeschist.index(round(mean(metclmt[y]["tempAVGlist"]),1)) else print("")
except: print(" Average Temperature: N/A")
try:
print(" Avg MAX Temperature: {}".format(round(mean(metclmt[y]["tmax"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tmaxdeschist.index(round(mean(metclmt[y]["tmax"]),1))+1)),end="") if len(metclmt[y]["tmax"]) > excludeyear and tmaxdeschist.index(round(mean(metclmt[y]["tmax"]),1)) <= tmaxaschist.index(round(mean(metclmt[y]["tmax"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tmaxaschist.index(round(mean(metclmt[y]["tmax"]),1))+1))) if len(metclmt[y]["tmax"]) > excludeyear and tmaxaschist.index(round(mean(metclmt[y]["tmax"]),1)) <= tmaxdeschist.index(round(mean(metclmt[y]["tmax"]),1)) else print("")
except: print(" Avg MAX Temperature: N/A")
if metclmt[y]["tmaxPROP"]["day_max"][0] != -999:
print(" -- Warmest Daily TMAX: {}".format(metclmt[y]["tmaxPROP"]["day_max"][0]),end = " ::: ")
for x in metclmt[y]["tmaxPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y]["tmaxPROP"]["day_max"][1][len(metclmt[y]["tmaxPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if metclmt[y]["tmaxPROP"]["day_min"][0] != -999:
print(" -- Coolest Daily TMAX: {}".format(metclmt[y]["tmaxPROP"]["day_min"][0]),end = " ::: ")
for x in metclmt[y]["tmaxPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y]["tmaxPROP"]["day_min"][1][len(metclmt[y]["tmaxPROP"]["day_min"][1])-1] else print("{}".format(x.daystr))
try:
print(" Avg MIN Temperature: {}".format(round(mean(metclmt[y]["tmin"]),1)),end="")
print(", Rank: {} Warmest".format(rank(tmindeschist.index(round(mean(metclmt[y]["tmin"]),1))+1)),end="") if len(metclmt[y]["tmin"]) > excludeyear and tmindeschist.index(round(mean(metclmt[y]["tmin"]),1)) <= tminaschist.index(round(mean(metclmt[y]["tmin"]),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tminaschist.index(round(mean(metclmt[y]["tmin"]),1))+1))) if len(metclmt[y]["tmin"]) > excludeyear and tminaschist.index(round(mean(metclmt[y]["tmin"]),1)) <= tmindeschist.index(round(mean(metclmt[y]["tmin"]),1)) else print("")
except: print(" Avg MIN Temperature: N/A")
if metclmt[y]["tminPROP"]["day_max"][0] != -999:
print(" -- Warmest Daily TMIN: {}".format(metclmt[y]["tminPROP"]["day_max"][0]),end = " ::: ")
for x in metclmt[y]["tminPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y]["tminPROP"]["day_max"][1][len(metclmt[y]["tminPROP"]["day_max"][1])-1] else print("{}".format(x.daystr))
if metclmt[y]["tminPROP"]["day_min"][0] != -999:
print(" -- Coolest Daily TMIN: {}".format(metclmt[y]["tminPROP"]["day_min"][0]),end = " ::: ")
for x in metclmt[y]["tminPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end=" ") if x != metclmt[y]["tminPROP"]["day_min"][1][len(metclmt[y]["tminPROP"]["day_min"][1])-1] else print("{}".format(x.daystr))
if all(len(x) == 0 for x in [metclmt[y]["tempAVGlist"],metclmt[y]["tmax"],metclmt[y]["tmin"]]):
print("*** No Reliable Temperature Data for {} {}".format(calendar.month_abbr,y))
print("-----")
def customStats(y1,m1,d1,*date2):
"""Report on a custom-length period of recorded statistics. All passed
arguments MUST be integers. If the optional ending arguments are not
included, the default ending will be December 31 of the calendar year,
given by Y1; does not accept values of greater than a year
customStats(Y1,M1,D1,*[Y2,M2,D2])
REQUIRED: Y1,M1,D1 --> Represent the beginning year, month, and date of
the custom period.
OPT *args: Y2,M2,D2 --> These optional entries represent the ending year,
month, and date of the period
EXAMPLE: customStats(1999,8,12) -> Returns a printout of statistics from
August 12th, 1999 to December 31, 1999.
"""
if any(type(x) != int for x in [y1,m1,d1]): return print("*** OOPS! Ensure that only integers are entered ***")
valid1 = checkDate(y1,m1,d1)
if len(date2) == 0: pass
elif len(date2) != 3: return print("*** OOPS! For the 2nd (optional) date, ensure a Year, Month and Date are entered ***")
else:
if any(type(x) != int for x in [date2[0],date2[1],date2[2]]): return print("*** OOPS! Ensure that only integers are entered ***")
valid2 = checkDate(date2[0],date2[1],date2[2])
startday = datetime.date(y1,m1,d1)
incr_day = startday
if len(date2) == 3:
endday = datetime.date(date2[0],date2[1],date2[2])
else:
emo = max(M for M in clmt[startday.year] if type(M) == int)
edy = max(D for D in clmt[startday.year][emo] if type(D) == int)
endday = datetime.date(startday.year,emo,edy)
if endday <= startday: return print("*** OOPS! Pick an earlier start-day or (if applicable) a later end-day ***")
# This handles if the passed time is greater than a year
if endday >= datetime.date(startday.year+1,startday.month,startday.day):
if endday == datetime.date(startday.year+1,startday.month,startday.day):
endday = datetime.date(startday.year+1,startday.month,startday.day)-datetime.timedelta(days=1)
else: return print("*** OOPS! customStats only accepts a temporal scope of a year or less")
c_prcp = []
c_prcpDAYS = 0
c_snow = []
c_snowDAYS = 0
c_snwd = []
c_snwdDAYS = 0
c_temp = []
c_tmax = []
c_tmin = []
records_in_period = 0
c_records = {"prcpPROP":{"day_max":[-1,[]]},
"snowPROP":{"day_max":[-1,[]]},
"snwdPROP":{"day_max":[-1,[]]},
"tempPROP":{"day_max":[-999,[]],"day_min":[999,[]]},
"tmaxPROP":{"day_max":[-999,[]],"day_min":[999,[]]},
"tminPROP":{"day_max":[-999,[]],"day_min":[999,[]]}}
# Determine total length of period (used for exclusion calculation)
s = datetime.date(1900,startday.month,startday.day)
test = datetime.date(1900,endday.month,endday.day)
if test > s: e = test
else: e = datetime.date(1901,endday.month,endday.day)
timelength = (e - s).days + 1
if timelength <= 5: EXCLD = timelength-1
elif timelength == 6: EXCLD = 4
elif timelength == 7: EXCLD = excludeweek
elif timelength == 8: EXCLD = excludeweek
elif timelength in [28,29,30,31]: EXCLD = excludemonth
elif timelength >= 350: EXCLD = excludeyear
else: EXCLD = round(excludecustom * timelength)
while incr_day <= endday:
y = incr_day.year; m = incr_day.month; d = incr_day.day
if y in clmt and m in clmt[y] and d in clmt[y][m]: # If a record for clmt[y][m][d] exists
records_in_period += 1
if clmt[y][m][d].prcpQ in ignoreflags and clmt[y][m][d].prcp not in ["9999","-9999",""]:
c_prcp.append(float(clmt[y][m][d].prcp))
if round(float(clmt[y][m][d].prcp),2) == c_records["prcpPROP"]["day_max"][0]:
c_records["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].prcp),2) > c_records["prcpPROP"]["day_max"][0]:
c_records["prcpPROP"]["day_max"][0] = round(float(clmt[y][m][d].prcp),2)
c_records["prcpPROP"]["day_max"][1] = []
c_records["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
if clmt[y][m][d].prcpQ in ignoreflags and clmt[y][m][d].prcp not in ["9999","-9999",""] and float(clmt[y][m][d].prcp) != 0 or clmt[y][m][d].prcpM == "T":
c_prcpDAYS += 1
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow not in ["9999","-9999",""]:
c_snow.append(float(clmt[y][m][d].snow))
if round(float(clmt[y][m][d].snow),2) == c_records["snowPROP"]["day_max"][0]:
c_records["snowPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(float(clmt[y][m][d].snow),2) > c_records["snowPROP"]["day_max"][0]:
c_records["snowPROP"]["day_max"][0] = round(float(clmt[y][m][d].snow),2)
c_records["snowPROP"]["day_max"][1] = []
c_records["snowPROP"]["day_max"][1].append(clmt[y][m][d])
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow not in ["9999","-9999",""] and float(clmt[y][m][d].snow) != 0 or clmt[y][m][d].snowM == "T":
c_snowDAYS += 1
if clmt[y][m][d].snwdQ in ignoreflags and clmt[y][m][d].snwd not in ["9999","-9999",""]:
if float(clmt[y][m][d].snwd) > 0:
c_snwd.append(float(clmt[y][m][d].snwd))
if round(float(clmt[y][m][d].snwd),1) == c_records["snwdPROP"]["day_max"][0]:
c_records["snwdPROP"]["day_max"][1].append(clmt[y][m][d])
if round(float(clmt[y][m][d].snwd),1) > c_records["snwdPROP"]["day_max"][0]:
c_records["snwdPROP"]["day_max"][0] = round(float(clmt[y][m][d].snwd),1)
c_records["snwdPROP"]["day_max"][1] = [clmt[y][m][d]]
if float(clmt[y][m][d].snwd) > 0 or clmt[y][m][d].snwdM == "T": c_snwdDAYS += 1
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""] and clmt[y][m][d].tmin not in ["9999","-9999",""]:
c_temp.append(int(clmt[y][m][d].tmax))
c_temp.append(int(clmt[y][m][d].tmin))
if round(mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]),1) == c_records["tempPROP"]["day_max"][0]:
c_records["tempPROP"]["day_max"][1].append(clmt[y][m][d])
elif round(mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]),1) > c_records["tempPROP"]["day_max"][0]:
c_records["tempPROP"]["day_max"][0] = round(mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]),1)
c_records["tempPROP"]["day_max"][1] = []
c_records["tempPROP"]["day_max"][1].append(clmt[y][m][d])
if round(mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]),1) == c_records["tempPROP"]["day_min"][0]:
c_records["tempPROP"]["day_min"][1].append(clmt[y][m][d])
elif round(mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]),1) < c_records["tempPROP"]["day_min"][0]:
c_records["tempPROP"]["day_min"][0] = round(mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]),1)
c_records["tempPROP"]["day_min"][1] = []
c_records["tempPROP"]["day_min"][1].append(clmt[y][m][d])
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""]:
c_tmax.append(int(clmt[y][m][d].tmax))
if int(clmt[y][m][d].tmax) == c_records["tmaxPROP"]["day_max"][0]:
c_records["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) > c_records["tmaxPROP"]["day_max"][0]:
c_records["tmaxPROP"]["day_max"][0] = int(clmt[y][m][d].tmax)
c_records["tmaxPROP"]["day_max"][1] = []
c_records["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == c_records["tmaxPROP"]["day_min"][0]:
c_records["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) < c_records["tmaxPROP"]["day_min"][0]:
c_records["tmaxPROP"]["day_min"][0] = int(clmt[y][m][d].tmax)
c_records["tmaxPROP"]["day_min"][1] = []
c_records["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
if clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""]:
c_tmin.append(int(clmt[y][m][d].tmin))
if int(clmt[y][m][d].tmin) == c_records["tminPROP"]["day_max"][0]:
c_records["tminPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) > c_records["tminPROP"]["day_max"][0]:
c_records["tminPROP"]["day_max"][0] = int(clmt[y][m][d].tmin)
c_records["tminPROP"]["day_max"][1] = []
c_records["tminPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == c_records["tminPROP"]["day_min"][0]:
c_records["tminPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) < c_records["tminPROP"]["day_min"][0]:
c_records["tminPROP"]["day_min"][0] = int(clmt[y][m][d].tmin)
c_records["tminPROP"]["day_min"][1] = []
c_records["tminPROP"]["day_min"][1].append(clmt[y][m][d])
incr_day += datetime.timedelta(days=1)
# customRank(attribute,quantity,M1,D1,*[M2,D2])
prcpaschist, prcpdeschist, prcpDAYSaschist, prcpDAYSdeschist, snowaschist, snowdeschist, snowDAYSaschist, snowDAYSdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist = customRank("temp",5,startday.month,startday.day,endday.month,endday.day,customStatsRun=True)
#for x in [prcpaschist, prcpdeschist, snowaschist, snowdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist]: print(len(x))
#for x in [prcpaschist, prcpdeschist, snowaschist, snowdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist]: print(x)
print("")
print("Statistics for {}-{}-{} thru {}-{}-{}".format(startday.year,startday.month,startday.day,
endday.year,endday.month,endday.day))
print("{}: {}".format(clmt["station"],clmt["station_name"]))
print("Quantity of Records: {}".format(records_in_period))
print("-------------------------------------")
"""
c_prcp = []
c_prcpDAYS = 0
c_snow = []
c_snowDAYS = 0
c_snwd = []
c_temp = []
c_tmax = []
c_tmin = []
records_in_period = 0
c_records = {"prcpPROP":{"day_max":[-1,[]]},
"snowPROP":{"day_max":[-1,[]]},
"tempPROP":{"day_max":[-999,[]],"day_min":[999,[]]},
"tmaxPROP":{"day_max":[-999,[]],"day_min":[999,[]]},
"tminPROP":{"day_max":[-999,[]],"day_min":[999,[]]}}
"""
print(" Total Precipitation: {}".format(round(sum(c_prcp),2)),end="")
try: print(", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(c_prcp),2))+1)),end="") if sum(c_prcp) > 0 and prcpdeschist.index(round(sum(c_prcp),2)) <= prcpaschist.index(round(sum(c_prcp),2)) else print("",end="")
except: print(", Rank: {} Wettest".format(rank(prcpdeschist.index(round(sum(c_prcp),2))+1)),end="")
try: print(", Rank: {} Driest".format(rank(prcpaschist.index(round(sum(c_prcp),2))+1))) if records_in_period > EXCLD and prcpaschist.index(round(sum(c_prcp),2)) <= prcpdeschist.index(round(sum(c_prcp),2)) else print("")
except: print("")
print(" Total Precipitation Days (>=T): {}".format(c_prcpDAYS),end="")
try: print(", Rank: {} Most".format(rank(prcpDAYSdeschist.index(c_prcpDAYS)+1)),end="") if c_prcpDAYS > 0 and prcpDAYSdeschist.index(c_prcpDAYS) <= prcpDAYSaschist.index(c_prcpDAYS) else print("",end="")
except: print(", Rank: {} Most".format(rank(prcpDAYSdeschist.index(c_prcpDAYS)+1)),end="")
try: print(", Rank: {} Least".format(rank(prcpDAYSaschist.index(c_prcpDAYS)+1))) if records_in_period > EXCLD and prcpDAYSaschist.index(c_prcpDAYS) <= prcpDAYSdeschist.index(c_prcpDAYS) else print("")
except: print("")
if round(sum(c_prcp),2) > 0:
print(" -- Highest Daily Precip: {}".format(c_records["prcpPROP"]["day_max"][0]),end = " ::: ")
for x in c_records["prcpPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end="") if x != c_records["prcpPROP"]["day_max"][1][-1] else print("{}".format(x.daystr))
if c_snowDAYS > 0:
print(" Total Snow: {}".format(round(sum(c_snow),1)),end="")
try: print(", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(c_snow),1))+1)),end="") if sum(c_snow) > 0 and snowdeschist.index(round(sum(c_snow),1)) <= snowaschist.index(round(sum(c_snow),1)) else print("",end="")
except: print(", Rank: {} Snowiest".format(rank(snowdeschist.index(round(sum(c_snow),1))+1)),end="")
try: print(", Rank: {} Least-Snowiest".format(rank(snowaschist.index(round(sum(c_snow),1))+1))) if records_in_period > EXCLD and snowaschist.index(round(sum(c_snow),1)) <= snowdeschist.index(round(sum(c_snow),1)) else print("")
except: print("")
print(" Total Snow Days (>=T): {}".format(c_snowDAYS),end="")
try: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(c_snowDAYS)+1)),end="") if c_snowDAYS > 0 and snowDAYSdeschist.index(c_snowDAYS) <= snowDAYSaschist.index(c_snowDAYS) else print("",end="")
except: print(", Rank: {} Most".format(rank(snowDAYSdeschist.index(c_snowDAYS)+1)),end="")
try: print(", Rank: {} Least".format(rank(snowDAYSaschist.index(c_snowDAYS)+1))) if records_in_period > EXCLD and snowDAYSaschist.index(c_snowDAYS) <= snowDAYSdeschist.index(c_snowDAYS) else print("")
except: print("")
if c_records["snowPROP"]["day_max"][0] > 0:
print("-- Snowiest Day: {}".format(c_records["snowPROP"]["day_max"][0]),end=" ::: ")
for x in c_records["snowPROP"]["day_max"][1]:
print("{}, ".format(x.daystr),end=" ") if x!= c_records["snowPROP"]["day_max"][1][-1] else print(x.daystr)
if len(c_snwd) > 0:
print(" Total Days w/Snow on the Ground: {}".format(c_snwdDAYS))
print("-- Highest Snow-Depth: {:.1f}".format(c_records["snwdPROP"]["day_max"][0]),end=" ::: ")
for x in c_records["snwdPROP"]["day_max"][1]:
print("{}, ".format(x.daystr),end="") if x != c_records["snwdPROP"]["day_max"][1][-1] else print(x.daystr)
try:
print(" Average Temperature: {}".format(round(mean(c_temp),1)),end="")
print(", Rank: {} Warmest".format(rank(tavgdeschist.index(round(mean(c_temp),1))+1)),end="") if len(c_temp) > EXCLD*2 and tavgdeschist.index(round(mean(c_temp),1)) <= tavgaschist.index(round(mean(c_temp),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tavgaschist.index(round(mean(c_temp),1))+1))) if len(c_temp) > EXCLD*2 and tavgaschist.index(round(mean(c_temp),1)) <= tavgdeschist.index(round(mean(c_temp),1)) else print("")
except: print(" Average Temperature: N/A")
try:
print(" Avg MAX Temperature: {}".format(round(mean(c_tmax),1)),end="")
print(", Rank: {} Warmest".format(rank(tmaxdeschist.index(round(mean(c_tmax),1))+1)),end="") if len(c_tmax) > EXCLD and tmaxdeschist.index(round(mean(c_tmax),1)) <= tmaxaschist.index(round(mean(c_tmax),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tmaxaschist.index(round(mean(c_tmax),1))+1))) if len(c_tmax) > EXCLD and tmaxaschist.index(round(mean(c_tmax),1)) <= tmaxdeschist.index(round(mean(c_tmax),1)) else print("")
except: print(" Avg MAX Temperature: N/A")
if c_records["tmaxPROP"]["day_max"][0] != -999:
print(" -- Warmest Daily TMAX: {}".format(c_records["tmaxPROP"]["day_max"][0]),end = " ::: ")
for x in c_records["tmaxPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end="") if x != c_records["tmaxPROP"]["day_max"][1][-1] else print(x.daystr)
if c_records["tmaxPROP"]["day_min"][0] != -999:
print(" -- Coolest Daily TMAX: {}".format(c_records["tmaxPROP"]["day_min"][0]),end = " ::: ")
for x in c_records["tmaxPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end="") if x != c_records["tmaxPROP"]["day_min"][1][-1] else print(x.daystr)
try:
print(" Avg MIN Temperature: {}".format(round(mean(c_tmin),1)),end="")
print(", Rank: {} Warmest".format(rank(tmindeschist.index(round(mean(c_tmin),1))+1)),end="") if len(c_tmin) > EXCLD and tmindeschist.index(round(mean(c_tmin),1)) <= tminaschist.index(round(mean(c_tmin),1)) else print("",end="")
print(", Rank: {} Coolest".format(rank(tminaschist.index(round(mean(c_tmin),1))+1))) if len(c_tmin) > EXCLD and tminaschist.index(round(mean(c_tmin),1)) <= tmindeschist.index(round(mean(c_tmin),1)) else print("")
except: print(" Avg MIN Temperature: N/A")
if c_records["tminPROP"]["day_max"][0] != -999:
print(" -- Warmest Daily TMIN: {}".format(c_records["tminPROP"]["day_max"][0]),end = " ::: ")
for x in c_records["tminPROP"]["day_max"][1]: print("{}, ".format(x.daystr), end="") if x != c_records["tminPROP"]["day_max"][1][-1] else print(x.daystr)
if c_records["tminPROP"]["day_min"][0] != -999:
print(" -- Coolest Daily TMIN: {}".format(c_records["tminPROP"]["day_min"][0]),end = " ::: ")
for x in c_records["tminPROP"]["day_min"][1]: print("{}, ".format(x.daystr), end="") if x != c_records["tminPROP"]["day_min"][1][-1] else print(x.daystr)
print("-----")
print("")
def dayReport(m,d,climatology=30,increment=5,output=False):
"""Detailed Climatological Report for a given day.
Args (Required):
m: month (int)
d: day (int)
Keyword Args (optional):
climatology = 30: The span of years that averages are calculated
for (ie. '30 year climatology' or '30 year average'). This can be
modified but should always be > the increment.
increment = 5: Tells the script how often to assess/record successive
climatologies. The smaller this is, the longer the report takes
to generate. If kept at the default, for example, it would
capture the 1976-2005, 1981-2010, and 1986-2015 climatologies and
so forth.
output = False: If set to True, the script will output a CSV file of
its findings. This could be opened in a spreadsheet program for
further analysis
Examples:
dayReport(5,1) -> Returns a 30-yr, 5-yr incremented climatological
report for May 1st.
dayReport(1,4,climatology=10) -> Returns a 10-yr,5-yr incremented
climatological report for Jan 4th.
dayReport(12,9,output=True) -> Returns a 30-yr,5-yr incremented
climatological report for Dec 9th and outputs a CSV report of
the findings.
"""
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
valid_yrs = list(range(min([x for x in clmt.keys() if type(x) == int]),max([x for x in clmt.keys() if type(x) == int])+1))
#valid_yrs = [x for x in clmt.keys() if type(x) == int]
valid_yrs.sort()
climo30yrs = {}
for x in range(1811,max(valid_yrs)+1,increment):
if x in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]) and x+climatology-1 in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]+1):
climo30yrs[(x,x+climatology-1)] = {"years":(x,x+climatology-1),
"prcp": [],"prcpPROP":{"days":0,"day_max":[-1,[]]},
"snow": [],"snowPROP":{"days":0,"day_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"day_max":[-999,[]],"day_min":[999,[]]},
"tmax": [],"tmaxPROP":{"day_max":[-999,[]],"day_min":[999,[]]},
"tmin": [],"tminPROP":{"day_max":[-999,[]],"day_min":[999,[]]}}
alltime = {"years":(valid_yrs[0],valid_yrs[len(valid_yrs)-1]),
"prcp": [],"prcpPROP":{"days":0,"day_max":[-1,[]]},
"snow": [],"snowPROP":{"days":0,"day_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"day_max":[-999,[]],"day_min":[999,[]]},
"tmax": [],"tmaxPROP":{"day_max":[-999,[]],"day_min":[999,[]]},
"tmin": [],"tminPROP":{"day_max":[-999,[]],"day_min":[999,[]]}}
for y in valid_yrs:
if checkDate2(y,m,d):
if clmt[y][m][d].prcpQ in ignoreflags and clmt[y][m][d].prcp not in ["9999","-9999",""]:
alltime["prcp"].append(float(clmt[y][m][d].prcp))
if float(clmt[y][m][d].prcp) > 0 or clmt[y][m][d].prcpM == "T": alltime["prcpPROP"]["days"] += 1
if float(clmt[y][m][d].prcp) == alltime["prcpPROP"]["day_max"][0]:
alltime["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
elif float(clmt[y][m][d].prcp) > alltime["prcpPROP"]["day_max"][0]:
alltime["prcpPROP"]["day_max"][0] = float(clmt[y][m][d].prcp)
alltime["prcpPROP"]["day_max"][1] = []
alltime["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["prcp"].append(float(clmt[y][m][d].prcp))
if float(clmt[y][m][d].prcp) > 0 or clmt[y][m][d].prcpM == "T": climo30yrs[c]["prcpPROP"]["days"] += 1
if float(clmt[y][m][d].prcp) == climo30yrs[c]["prcpPROP"]["day_max"][0]:
climo30yrs[c]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
elif float(clmt[y][m][d].prcp) > climo30yrs[c]["prcpPROP"]["day_max"][0]:
climo30yrs[c]["prcpPROP"]["day_max"][0] = float(clmt[y][m][d].prcp)
climo30yrs[c]["prcpPROP"]["day_max"][1] = []
climo30yrs[c]["prcpPROP"]["day_max"][1].append(clmt[y][m][d])
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow not in ["9999","-9999",""]:
alltime["snow"].append(float(clmt[y][m][d].snow))
if float(clmt[y][m][d].snow) > 0 or clmt[y][m][d].snowM == "T": alltime["snowPROP"]["days"] += 1
if float(clmt[y][m][d].snow) == alltime["snowPROP"]["day_max"][0]:
alltime["snowPROP"]["day_max"][1].append(clmt[y][m][d])
elif float(clmt[y][m][d].snow) > alltime["snowPROP"]["day_max"][0]:
alltime["snowPROP"]["day_max"][0] = float(clmt[y][m][d].snow)
alltime["snowPROP"]["day_max"][1] = []
alltime["snowPROP"]["day_max"][1].append(clmt[y][m][d])
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["snow"].append(float(clmt[y][m][d].snow))
if float(clmt[y][m][d].snow) > 0 or clmt[y][m][d].snowM == "T": climo30yrs[c]["snowPROP"]["days"] += 1
if float(clmt[y][m][d].snow) == climo30yrs[c]["snowPROP"]["day_max"][0]:
climo30yrs[c]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
elif float(clmt[y][m][d].snow) > climo30yrs[c]["snowPROP"]["day_max"][0]:
climo30yrs[c]["snowPROP"]["day_max"][0] = float(clmt[y][m][d].snow)
climo30yrs[c]["snowPROP"]["day_max"][1] = []
climo30yrs[c]["snowPROP"]["day_max"][1].append(clmt[y][m][d])
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""] and clmt[y][m][d].tmin not in ["9999","-9999",""] and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin):
alltime["tempAVGlist"].append(int(clmt[y][m][d].tmax))
alltime["tempAVGlist"].append(int(clmt[y][m][d].tmin))
if mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]) == alltime["tavgPROP"]["day_max"][0]:
alltime["tavgPROP"]["day_max"][1].append(clmt[y][m][d])
elif mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]) > alltime["tavgPROP"]["day_max"][0]:
alltime["tavgPROP"]["day_max"][0] = mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)])
alltime["tavgPROP"]["day_max"][1] = []
alltime["tavgPROP"]["day_max"][1].append(clmt[y][m][d])
if mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]) == alltime["tavgPROP"]["day_min"][0]:
alltime["tavgPROP"]["day_min"][1].append(clmt[y][m][d])
elif mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]) < alltime["tavgPROP"]["day_min"][0]:
alltime["tavgPROP"]["day_min"][0] = mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)])
alltime["tavgPROP"]["day_min"][1] = []
alltime["tavgPROP"]["day_min"][1].append(clmt[y][m][d])
for c in climo30yrs:
#if 1906 <= y <= 1915: print(y,c[0],c[1],c,y >= c[0] and y <= c[1])
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["tempAVGlist"].append(int(clmt[y][m][d].tmax))
climo30yrs[c]["tempAVGlist"].append(int(clmt[y][m][d].tmin))
if mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]) == climo30yrs[c]["tavgPROP"]["day_max"][0]:
climo30yrs[c]["tavgPROP"]["day_max"][1].append(clmt[y][m][d])
elif mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]) > climo30yrs[c]["tavgPROP"]["day_max"][0]:
climo30yrs[c]["tavgPROP"]["day_max"][0] = mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)])
climo30yrs[c]["tavgPROP"]["day_max"][1] = []
climo30yrs[c]["tavgPROP"]["day_max"][1].append(clmt[y][m][d])
if mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]) == climo30yrs[c]["tavgPROP"]["day_min"][0]:
climo30yrs[c]["tavgPROP"]["day_min"][1].append(clmt[y][m][d])
elif mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)]) < climo30yrs[c]["tavgPROP"]["day_min"][0]:
climo30yrs[c]["tavgPROP"]["day_min"][0] = mean([int(clmt[y][m][d].tmax),int(clmt[y][m][d].tmin)])
climo30yrs[c]["tavgPROP"]["day_min"][1] = []
climo30yrs[c]["tavgPROP"]["day_min"][1].append(clmt[y][m][d])
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""]:
alltime["tmax"].append(int(clmt[y][m][d].tmax))
if int(clmt[y][m][d].tmax) == alltime["tmaxPROP"]["day_max"][0]:
alltime["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) > alltime["tmaxPROP"]["day_max"][0]:
alltime["tmaxPROP"]["day_max"][0] = int(clmt[y][m][d].tmax)
alltime["tmaxPROP"]["day_max"][1] = []
alltime["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == alltime["tmaxPROP"]["day_min"][0]:
alltime["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) < alltime["tmaxPROP"]["day_min"][0]:
alltime["tmaxPROP"]["day_min"][0] = int(clmt[y][m][d].tmax)
alltime["tmaxPROP"]["day_min"][1] = []
alltime["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["tmax"].append(int(clmt[y][m][d].tmax))
if int(clmt[y][m][d].tmax) == climo30yrs[c]["tmaxPROP"]["day_max"][0]:
climo30yrs[c]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) > climo30yrs[c]["tmaxPROP"]["day_max"][0]:
climo30yrs[c]["tmaxPROP"]["day_max"][0] = int(clmt[y][m][d].tmax)
climo30yrs[c]["tmaxPROP"]["day_max"][1] = []
climo30yrs[c]["tmaxPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmax) == climo30yrs[c]["tmaxPROP"]["day_min"][0]:
climo30yrs[c]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmax) < climo30yrs[c]["tmaxPROP"]["day_min"][0]:
climo30yrs[c]["tmaxPROP"]["day_min"][0] = int(clmt[y][m][d].tmax)
climo30yrs[c]["tmaxPROP"]["day_min"][1] = []
climo30yrs[c]["tmaxPROP"]["day_min"][1].append(clmt[y][m][d])
if clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""]:
alltime["tmin"].append(int(clmt[y][m][d].tmin))
if int(clmt[y][m][d].tmin) == alltime["tminPROP"]["day_max"][0]:
alltime["tminPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) > alltime["tminPROP"]["day_max"][0]:
alltime["tminPROP"]["day_max"][0] = int(clmt[y][m][d].tmin)
alltime["tminPROP"]["day_max"][1] = []
alltime["tminPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == alltime["tminPROP"]["day_min"][0]:
alltime["tminPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) < alltime["tminPROP"]["day_min"][0]:
alltime["tminPROP"]["day_min"][0] = int(clmt[y][m][d].tmin)
alltime["tminPROP"]["day_min"][1] = []
alltime["tminPROP"]["day_min"][1].append(clmt[y][m][d])
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["tmin"].append(int(clmt[y][m][d].tmin))
if int(clmt[y][m][d].tmin) == climo30yrs[c]["tminPROP"]["day_max"][0]:
climo30yrs[c]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) > climo30yrs[c]["tminPROP"]["day_max"][0]:
climo30yrs[c]["tminPROP"]["day_max"][0] = int(clmt[y][m][d].tmin)
climo30yrs[c]["tminPROP"]["day_max"][1] = []
climo30yrs[c]["tminPROP"]["day_max"][1].append(clmt[y][m][d])
if int(clmt[y][m][d].tmin) == climo30yrs[c]["tminPROP"]["day_min"][0]:
climo30yrs[c]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
elif int(clmt[y][m][d].tmin) < climo30yrs[c]["tminPROP"]["day_min"][0]:
climo30yrs[c]["tminPROP"]["day_min"][0] = int(clmt[y][m][d].tmin)
climo30yrs[c]["tminPROP"]["day_min"][1] = []
climo30yrs[c]["tminPROP"]["day_min"][1].append(clmt[y][m][d])
for c in climo30yrs:
print("tavg: ", c, ":", climo30yrs[c]["tempAVGlist"])
print("tmax: ", c, ":", climo30yrs[c]["tmax"])
# PRINT REPORT
print("---------------------------------------------------")
print("Climatology Report for {} {}".format(calendar.month_name[m],d))
print("City: {}, {}".format(clmt["station"],clmt["station_name"]))
print("{}-{}; {}-Year Incremented {}-Year Climatologies".format(min(valid_yrs),max(valid_yrs),increment,climatology))
print("---------------------------------------------------")
print("{:▒^9} {:▒^12} {:▒^12} {:▒^8} {:▒^9} {:▒^9} {:▒^8} {:▒^9} {:▒^9}".format("YEARS","PRCP","SNOW","TMAX","TMAX","TMAX","TMIN","TMIN","TMIN"))
print("{:▒^9} {:▒^12} {:▒^12} {:▒^8} {:▒^9} {:▒^9} {:▒^8} {:▒^9} {:▒^9}".format( "","hi","hi","avg","hi","lo","avg","hi","lo"))
print("{:.^9} {:.^12} {:.^12} {:.^8} {:.^9} {:.^9} {:.^8} {:.^9} {:.^9}".format("","","","","","","","",""))
print("{:^9} {:>6.2f}, {:>4} {:>6.1f}, {:^4} {:^8.1f} {:>3}, {:^4} {:>3}, {:^4} {:^8.1f} {:>3}, {:^4} {:>3}, {:^4}".format("All Time",
alltime["prcpPROP"]["day_max"][0],len(alltime["prcpPROP"]["day_max"][1]) if len(alltime["prcpPROP"]["day_max"][1]) > 1 else alltime["prcpPROP"]["day_max"][1][0].daystr[0:4],
alltime["snowPROP"]["day_max"][0],len(alltime["snowPROP"]["day_max"][1]) if len(alltime["snowPROP"]["day_max"][1]) > 1 else alltime["snowPROP"]["day_max"][1][0].daystr[0:4],
round(mean(alltime["tmax"]),1),
alltime["tmaxPROP"]["day_max"][0],len(alltime["tmaxPROP"]["day_max"][1]) if len(alltime["tmaxPROP"]["day_max"][1]) > 1 else alltime["tmaxPROP"]["day_max"][1][0].daystr[0:4],
alltime["tmaxPROP"]["day_min"][0],len(alltime["tmaxPROP"]["day_min"][1]) if len(alltime["tmaxPROP"]["day_min"][1]) > 1 else alltime["tmaxPROP"]["day_min"][1][0].daystr[0:4],
round(mean(alltime["tmin"]),1),
alltime["tminPROP"]["day_max"][0],len(alltime["tminPROP"]["day_max"][1]) if len(alltime["tminPROP"]["day_max"][1]) > 1 else alltime["tminPROP"]["day_max"][1][0].daystr[0:4],
alltime["tminPROP"]["day_min"][0],len(alltime["tminPROP"]["day_min"][1]) if len(alltime["tminPROP"]["day_min"][1]) > 1 else alltime["tminPROP"]["day_min"][1][0].daystr[0:4]))
for c in climo30yrs:
try:
print("{:^9} {:>6.2f}, {:>4} {:>6.1f}, {:^4} {:^8.1f} {:>3}, {:^4} {:>3}, {:^4} {:^8.1f} {:>3}, {:^4} {:>3}, {:^4}".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
climo30yrs[c]["prcpPROP"]["day_max"][0],
len(climo30yrs[c]["prcpPROP"]["day_max"][1]) if len(climo30yrs[c]["prcpPROP"]["day_max"][1]) > 1 else climo30yrs[c]["prcpPROP"]["day_max"][1][0].daystr[0:4],
climo30yrs[c]["snowPROP"]["day_max"][0],
len(climo30yrs[c]["snowPROP"]["day_max"][1]) if len(climo30yrs[c]["snowPROP"]["day_max"][1]) > 1 else climo30yrs[c]["snowPROP"]["day_max"][1][0].daystr[0:4],
round(mean(climo30yrs[c]["tmax"]),1),
climo30yrs[c]["tmaxPROP"]["day_max"][0],
len(climo30yrs[c]["tmaxPROP"]["day_max"][1]) if len(climo30yrs[c]["tmaxPROP"]["day_max"][1]) > 1 else climo30yrs[c]["tmaxPROP"]["day_max"][1][0].daystr[0:4],
climo30yrs[c]["tmaxPROP"]["day_min"][0],
len(climo30yrs[c]["tmaxPROP"]["day_min"][1]) if len(climo30yrs[c]["tmaxPROP"]["day_min"][1]) > 1 else climo30yrs[c]["tmaxPROP"]["day_min"][1][0].daystr[0:4],
round(mean(climo30yrs[c]["tmin"]),1),
climo30yrs[c]["tminPROP"]["day_max"][0],
len(climo30yrs[c]["tminPROP"]["day_max"][1]) if len(climo30yrs[c]["tminPROP"]["day_max"][1]) > 1 else climo30yrs[c]["tminPROP"]["day_max"][1][0].daystr[0:4],
climo30yrs[c]["tminPROP"]["day_min"][0],
len(climo30yrs[c]["tminPROP"]["day_min"][1]) if len(climo30yrs[c]["tminPROP"]["day_min"][1]) > 1 else climo30yrs[c]["tminPROP"]["day_min"][1][0].daystr[0:4]))
except:
print(c)
print("")
if output == True:
newfn = "dayReport_" + str(calendar.month_abbr[m]) + str(d) + "_" + str(climatology) + "YRclimo_" + str(increment) + "YRincr_" + clmt["station_name"] + ".csv"
with open(newfn,"w") as w:
headers = ["Assessed Period ({} {})".format(calendar.month_abbr[m],d),"PRCP Days","PRCP stdev","PRCP AVG","SNOW Days","SNOW stdev","SNOW AVG","TAVG stdev","TAVG","TMAX stdev","TMAX","TMIN stdev","TMIN"]
# HEADER
for x in range(len(headers)):
if x != len(headers) - 1: w.write(headers[x]); w.write(",")
else: w.write(headers[x]); w.write("\n")
w.write("{}-{}".format(alltime["years"][0],alltime["years"][1])); w.write(",")
w.write("{}".format(alltime["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["prcp"]),1))); w.write(",")
w.write("{}".format(alltime["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tempAVGlist"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tempAVGlist"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmin"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tmin"]),1))); w.write("\n")
for x in climo30yrs:
w.write("{}-{}".format(climo30yrs[x]["years"][0],climo30yrs[x]["years"][1])); w.write(",")
w.write("{}".format(climo30yrs[x]["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{}".format(climo30yrs[x]["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["snow"]),1))); w.write(",")
try:w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tempAVGlist"]),1))); w.write(",")
except: print(x, climo30yrs[x]["tempAVGlist"])
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tempAVGlist"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmin"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tmin"]),1))); w.write("\n")
print("*** csv output successful ***")
def weekReport(m,d,climatology=30,increment=5,output=False):
"""Detailed Climatological Report for a given week where the given day is
the week center (3 days prior + given day + 3 days after = 7 days).
Args (Required):
m: month (int)
d: day (int)
Keyword Args (optional):
climatology = 30: The span of years that averages are calculated
for (ie. '30 year climatology' or '30 year average'). This can be
modified but should always be > the increment.
increment = 5: Tells the script how often to assess/record successive
climatologies. The smaller this is, the longer the report takes
to generate. If kept at the default, for example, it would
capture the 1976-2005, 1981-2010, and 1986-2015 climatologies and
so forth.
output = False: If set to True, the script will output a CSV file of
its findings. This could be opened in a spreadsheet program for
further analysis
Examples:
weekReport(1,7) -> Returns a 30-yr, 5-yr incremented climatological
report for the week of Jan 4 - Jan 10.
weekReport(7,20,climatology=10) -> Returns a 10-yr, 5-yr incremented
climatological report for the week of July 17 - July 23
weekReport(9,6,climatology=15,increment=1,output=True) -> Returns a
5-yr incremented, 15yr climatology report for the week of
Sep 3 - Sep 9. It also outputs a CSV report of the findings.
"""
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
valid_yrs = list(range(min([x for x in clmt.keys() if type(x) == int]),max([x for x in clmt.keys() if type(x) == int])+1))
#valid_yrs = [x for x in clmt.keys() if type(x) == int]
valid_yrs.sort()
climo30yrs = {}
for x in range(1811,max(valid_yrs)+1,increment):
if x in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]) and x+climatology-1 in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]+1):
climo30yrs[(x,x+climatology-1)] = {"years":(x,x+climatology-1),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"week_max":[-1,[]]},
"snow": [],"snowPROP":{"days":0,"week_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"week_max":[-999,[]],"week_min":[999,[]]},
"tmax": [],"tmaxPROP":{"week_max":[-999,[]],"week_min":[999,[]]},
"tmin": [],"tminPROP":{"week_max":[-999,[]],"week_min":[999,[]]}}
alltime = {"years":(valid_yrs[0],valid_yrs[len(valid_yrs)-1]),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"week_max":[-1,[]]},
"snow": [],"snowPROP":{"days":0,"week_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"week_max":[-999,[]],"week_min":[999,[]]},
"tmax": [],"tmaxPROP":{"week_max":[-999,[]],"week_min":[999,[]]},
"tmin": [],"tminPROP":{"week_max":[-999,[]],"week_min":[999,[]]}}
if m == 2 and d == 29: d = 28
for y in valid_yrs:
wkstart = datetime.date(y,m,d) - datetime.timedelta(days=3)
currday = wkstart
wkend = datetime.date(y,m,d) + datetime.timedelta(days=3)
wk = []
wk_prcp = []
wk_snow = []
wk_tempAVGlist = []
wk_tmax = []
wk_tmin = []
for DAY in range(7):
try:
wk.append(clmt[currday.year][currday.month][currday.day])
currday += datetime.timedelta(days=1)
except:
currday += datetime.timedelta(days=1)
alltime["total_days"] += len(wk)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] in clmt and c[1] in clmt:
climo30yrs[c]["total_days"] += len(wk)
if len(wk) > 0:
for day in wk:
if day.prcpQ in ignoreflags and day.prcp not in ["9999","-9999",""]:
#alltime["prcp"].append(float(day.prcp))
if float(day.prcp) > 0 or day.prcpM == "T": alltime["prcpPROP"]["days"] += 1
wk_prcp.append(float(day.prcp))
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
#climo30yrs[c]["prcp"].append(float(day.prcp))
if float(day.prcp) > 0 or day.prcpM == "T": climo30yrs[c]["prcpPROP"]["days"] += 1
if day.snowQ in ignoreflags and day.snow not in ["9999","-9999",""]:
alltime["snow"].append(float(day.snow))
if float(day.snow) > 0 or day.snowM == "T": alltime["snowPROP"]["days"] += 1
wk_snow.append(float(day.snow))
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
#climo30yrs[c]["snow"].append(float(day.snow))
if float(day.snow) > 0 or day.snowM == "T": climo30yrs[c]["snowPROP"]["days"] += 1
if day.tmaxQ in ignoreflags and day.tmax not in ["9999","-9999",""] and day.tminQ in ignoreflags and day.tmin not in ["9999","-9999",""]:
alltime["tempAVGlist_ind"].append(int(day.tmax))
alltime["tempAVGlist_ind"].append(int(day.tmin))
wk_tempAVGlist.append(int(day.tmax))
wk_tempAVGlist.append(int(day.tmin))
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["tempAVGlist_ind"].append(int(day.tmax))
climo30yrs[c]["tempAVGlist_ind"].append(int(day.tmin))
if day.tmaxQ in ignoreflags and day.tmax not in ["9999","-9999",""]:
alltime["tmax"].append(int(day.tmax))
wk_tmax.append(int(day.tmax))
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["tmax"].append(int(day.tmax))
if day.tminQ in ignoreflags and day.tmin not in ["9999","-9999",""]:
alltime["tmin"].append(int(day.tmin))
wk_tmin.append(int(day.tmin))
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["tmin"].append(int(day.tmin))
alltime["prcp"].append(sum(wk_prcp))
alltime["snow"].append(sum(wk_snow))
if len(wk_tempAVGlist) > excludeweek_tavg:
alltime["tempAVGlist"].append(round(mean(wk_tempAVGlist),1))
# CLIMO STATS HERE ON THIS LEVEL
if sum(wk_prcp) == alltime["prcpPROP"]["week_max"][0]: alltime["prcpPROP"]["week_max"][1].append(y)
elif sum(wk_prcp) > alltime["prcpPROP"]["week_max"][0]:
alltime["prcpPROP"]["week_max"][0] = sum(wk_prcp)
alltime["prcpPROP"]["week_max"][1] = []
alltime["prcpPROP"]["week_max"][1].append(y)
if sum(wk_snow) == alltime["snowPROP"]["week_max"][0]: alltime["snowPROP"]["week_max"][1].append(y)
elif sum(wk_snow) > alltime["snowPROP"]["week_max"][0]:
alltime["snowPROP"]["week_max"][0] = sum(wk_snow)
alltime["snowPROP"]["week_max"][1] = []
alltime["snowPROP"]["week_max"][1].append(y)
# "tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"week_max":[-999,[]],"week_min":[999,[]]},
if len(wk_tempAVGlist) > excludeweek_tavg:
alltime["tempAVGlist"].append(round(mean(wk_tempAVGlist),1))
if round(mean(wk_tempAVGlist),1) == alltime["tavgPROP"]["week_max"][0]: alltime["tavgPROP"]["week_max"][1].append(y)
elif round(mean(wk_tempAVGlist),1) > alltime["tavgPROP"]["week_max"][0]:
alltime["tavgPROP"]["week_max"][0] = mean(wk_tempAVGlist)
alltime["tavgPROP"]["week_max"][1] = []
alltime["tavgPROP"]["week_max"][1].append(y)
if round(mean(wk_tempAVGlist),1) == alltime["tavgPROP"]["week_min"][0]: alltime["tavgPROP"]["week_min"][1].append(y)
elif round(mean(wk_tempAVGlist),1) < alltime["tavgPROP"]["week_min"][0]:
alltime["tavgPROP"]["week_min"][0] = round(mean(wk_tempAVGlist),1)
alltime["tavgPROP"]["week_min"][1] = []
alltime["tavgPROP"]["week_min"][1].append(y)
if len(wk_tmax) > excludeweek:
if mean(wk_tmax) == alltime["tmaxPROP"]["week_max"][0]: alltime["tmaxPROP"]["week_max"][1].append(y)
elif mean(wk_tmax) > alltime["tmaxPROP"]["week_max"][0]:
alltime["tmaxPROP"]["week_max"][0] = mean(wk_tmax)
alltime["tmaxPROP"]["week_max"][1] = []
alltime["tmaxPROP"]["week_max"][1].append(y)
if mean(wk_tmax) == alltime["tmaxPROP"]["week_min"][0]: alltime["tmaxPROP"]["week_min"][1].append(y)
elif mean(wk_tmax) < alltime["tmaxPROP"]["week_min"][0]:
alltime["tmaxPROP"]["week_min"][0] = mean(wk_tmax)
alltime["tmaxPROP"]["week_min"][1] = []
alltime["tmaxPROP"]["week_min"][1].append(y)
if len(wk_tmin) > excludeweek:
if mean(wk_tmin) == alltime["tminPROP"]["week_max"][0]: alltime["tminPROP"]["week_max"][1].append(y)
elif mean(wk_tmin) > alltime["tminPROP"]["week_max"][0]:
alltime["tminPROP"]["week_max"][0] = mean(wk_tmin)
alltime["tminPROP"]["week_max"][1] = []
alltime["tminPROP"]["week_max"][1].append(y)
if mean(wk_tmin) == alltime["tminPROP"]["week_min"][0]: alltime["tminPROP"]["week_min"][1].append(y)
elif mean(wk_tmin) < alltime["tminPROP"]["week_min"][0]:
alltime["tminPROP"]["week_min"][0] = mean(wk_tmin)
alltime["tminPROP"]["week_min"][1] = []
alltime["tminPROP"]["week_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["prcp"].append(sum(wk_prcp))
climo30yrs[c]["snow"].append(sum(wk_snow))
if sum(wk_prcp) == climo30yrs[c]["prcpPROP"]["week_max"][0]: climo30yrs[c]["prcpPROP"]["week_max"][1].append(y)
elif sum(wk_prcp) > climo30yrs[c]["prcpPROP"]["week_max"][0]:
climo30yrs[c]["prcpPROP"]["week_max"][0] = sum(wk_prcp)
climo30yrs[c]["prcpPROP"]["week_max"][1] = []
climo30yrs[c]["prcpPROP"]["week_max"][1].append(y)
if sum(wk_snow) == climo30yrs[c]["snowPROP"]["week_max"][0]: climo30yrs[c]["snowPROP"]["week_max"][1].append(y)
elif sum(wk_snow) > climo30yrs[c]["snowPROP"]["week_max"][0]:
climo30yrs[c]["snowPROP"]["week_max"][0] = sum(wk_snow)
climo30yrs[c]["snowPROP"]["week_max"][1] = []
climo30yrs[c]["snowPROP"]["week_max"][1].append(y)
if len(wk_tempAVGlist) > excludeweek_tavg:
climo30yrs[c]["tempAVGlist"].append(round(mean(wk_tempAVGlist),1))
if round(mean(wk_tempAVGlist),1) == climo30yrs[c]["tavgPROP"]["week_max"][0]: climo30yrs[c]["tavgPROP"]["week_max"][1].append(y)
elif round(mean(wk_tempAVGlist),1) > climo30yrs[c]["tavgPROP"]["week_max"][0]:
climo30yrs[c]["tavgPROP"]["week_max"][0] = mean(wk_tempAVGlist)
climo30yrs[c]["tavgPROP"]["week_max"][1] = []
climo30yrs[c]["tavgPROP"]["week_max"][1].append(y)
if round(mean(wk_tempAVGlist),1) == climo30yrs[c]["tavgPROP"]["week_min"][0]: climo30yrs[c]["tavgPROP"]["week_min"][1].append(y)
elif round(mean(wk_tempAVGlist),1) < climo30yrs[c]["tavgPROP"]["week_min"][0]:
climo30yrs[c]["tavgPROP"]["week_min"][0] = round(mean(wk_tempAVGlist),1)
climo30yrs[c]["tavgPROP"]["week_min"][1] = []
climo30yrs[c]["tavgPROP"]["week_min"][1].append(y)
if len(wk_tmax) > excludeweek:
if mean(wk_tmax) == climo30yrs[c]["tmaxPROP"]["week_max"][0]: climo30yrs[c]["tmaxPROP"]["week_max"][1].append(y)
elif mean(wk_tmax) > climo30yrs[c]["tmaxPROP"]["week_max"][0]:
climo30yrs[c]["tmaxPROP"]["week_max"][0] = mean(wk_tmax)
climo30yrs[c]["tmaxPROP"]["week_max"][1] = []
climo30yrs[c]["tmaxPROP"]["week_max"][1].append(y)
if mean(wk_tmax) == climo30yrs[c]["tmaxPROP"]["week_min"][0]: climo30yrs[c]["tmaxPROP"]["week_min"][1].append(y)
elif mean(wk_tmax) < climo30yrs[c]["tmaxPROP"]["week_min"][0]:
climo30yrs[c]["tmaxPROP"]["week_min"][0] = mean(wk_tmax)
climo30yrs[c]["tmaxPROP"]["week_min"][1] = []
climo30yrs[c]["tmaxPROP"]["week_min"][1].append(y)
if len(wk_tmin) > excludeweek:
if mean(wk_tmin) == climo30yrs[c]["tminPROP"]["week_max"][0]: climo30yrs[c]["tminPROP"]["week_max"][1].append(y)
elif mean(wk_tmin) > climo30yrs[c]["tminPROP"]["week_max"][0]:
climo30yrs[c]["tminPROP"]["week_max"][0] = mean(wk_tmin)
climo30yrs[c]["tminPROP"]["week_max"][1] = []
climo30yrs[c]["tminPROP"]["week_max"][1].append(y)
if mean(wk_tmin) == climo30yrs[c]["tminPROP"]["week_min"][0]: climo30yrs[c]["tminPROP"]["week_min"][1].append(y)
elif mean(wk_tmin) < climo30yrs[c]["tminPROP"]["week_min"][0]:
climo30yrs[c]["tminPROP"]["week_min"][0] = mean(wk_tmin)
climo30yrs[c]["tminPROP"]["week_min"][1] = []
climo30yrs[c]["tminPROP"]["week_min"][1].append(y)
wkstart = datetime.date(1999,m,d) - datetime.timedelta(days=3)
currday = wkstart
# PRINT REPORT
print("--------------------------------------------------")
print("Climatology Report for the Week of {:%b} {:%d} - {:%b} {:%d}".format(wkstart,wkstart,wkend,wkend))
print("City: {}, {}".format(clmt["station"],clmt["station_name"]))
print("{}-{}; {}-Year Incremented {}-Year Climatologies".format(min(valid_yrs),max(valid_yrs),increment,climatology))
print("--------------------------------------------------")
print("\nPart 1: Precipitation Stats")
print("{:▒^9} {:▒^11} {:▒^6} {:▒^12} {:▒^11} {:▒^6} {:▒^12}".format("Years","PRCP","PRCP","PRCP","SNOW","SNOW","SNOW"))
print("{:▒^9} {:▒^11} {:▒^6} {:▒^12} {:▒^11} {:▒^6} {:▒^12}".format("","DAYS","AVG", "MAX","DAYS","AVG", "MAX"))
# Y PD PA PM SD SA SM
print("{:-^9} {:-^11} {:-^6} {:-^12} {:-^11} {:-^6} {:-^12}".format("","","","","","",""))
print("{:^9} {:4}:{:>5}% {:^6.2f} {:>5.2f}, {:^5} {:4}:{:>5}% {:^6.1f} {:>5.1f}, {:^5}".format("All Time",
alltime["prcpPROP"]["days"],
round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1),
round(mean(alltime["prcp"]),2),
round(alltime["prcpPROP"]["week_max"][0],2),
alltime["prcpPROP"]["week_max"][1][0] if len(alltime["prcpPROP"]["week_max"][1]) == 1 else len(alltime["prcpPROP"]["week_max"][1]),
alltime["snowPROP"]["days"],
round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1),
round(mean(alltime["snow"]),1),
round(alltime["snowPROP"]["week_max"][0],2),
alltime["snowPROP"]["week_max"][1][0] if len(alltime["snowPROP"]["week_max"][1]) == 1 else len(alltime["snowPROP"]["week_max"][1])))
for c in climo30yrs:
try:
print("{:^9} {:4}:{:>5}% {:^6.2f} {:>5.2f}, {:^5} {:4}:{:>5}% {:^6.1f} {:>5.1f}, {:^5}".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
climo30yrs[c]["prcpPROP"]["days"],
round(100 * climo30yrs[c]["prcpPROP"]["days"] / climo30yrs[c]["total_days"],1),
round(mean(climo30yrs[c]["prcp"]),2),
round(climo30yrs[c]["prcpPROP"]["week_max"][0],2),
climo30yrs[c]["prcpPROP"]["week_max"][1][0] if len(climo30yrs[c]["prcpPROP"]["week_max"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["week_max"][1]),
climo30yrs[c]["snowPROP"]["days"],
round(100 * climo30yrs[c]["snowPROP"]["days"] / climo30yrs[c]["total_days"],1),
round(mean(climo30yrs[c]["snow"]),1),
round(climo30yrs[c]["snowPROP"]["week_max"][0],2),
climo30yrs[c]["snowPROP"]["week_max"][1][0] if len(climo30yrs[c]["snowPROP"]["week_max"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["week_max"][1])))
except:
pass
print("\nPart 2: Temperature Stats")
print("{:▒^9} {:▒^37} | {:▒^37} | {:▒^37}".format("Years","AVG TEMP","TMAX","TMIN"))
print("{:▒^9} {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12}".format("","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN"))
# Y TSTDV TMA TMX TMn TSTDV TMA TMX TMn TSTDV TMA TMX TMn
# "tempAVGlist": [],"tavgPROP":{"week_max":[-999,[]],"week_min":[999,[]]},
print("{:-^9} {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12}".format("","","","","","","","","","","","",""))
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format("All Time",
round(pstdev(alltime["tempAVGlist"]),1),
round(mean(alltime["tempAVGlist_ind"]),1),
round(alltime["tavgPROP"]["week_max"][0],1),
alltime["tavgPROP"]["week_max"][1][0] if len(alltime["tavgPROP"]["week_max"][1]) == 1 else len(alltime["tavgPROP"]["week_max"][1]),
round(alltime["tavgPROP"]["week_min"][0],1),
alltime["tavgPROP"]["week_min"][1][0] if len(alltime["tavgPROP"]["week_min"][1]) == 1 else len(alltime["tavgPROP"]["week_min"][1]),
round(pstdev(alltime["tmax"]),1),
round(mean(alltime["tmax"]),1),
round(alltime["tmaxPROP"]["week_max"][0],1),
alltime["tmaxPROP"]["week_max"][1][0] if len(alltime["tmaxPROP"]["week_max"][1]) == 1 else len(alltime["tmaxPROP"]["week_max"][1]),
round(alltime["tmaxPROP"]["week_min"][0],1),
alltime["tmaxPROP"]["week_min"][1][0] if len(alltime["tmaxPROP"]["week_min"][1]) == 1 else len(alltime["tmaxPROP"]["week_min"][1]),
round(pstdev(alltime["tmin"]),1),
round(mean(alltime["tmin"]),1),
round(alltime["tminPROP"]["week_max"][0],1),
alltime["tminPROP"]["week_max"][1][0] if len(alltime["tminPROP"]["week_max"][1]) == 1 else len(alltime["tminPROP"]["week_max"][1]),
round(alltime["tminPROP"]["week_min"][0],1),
alltime["tminPROP"]["week_min"][1][0] if len(alltime["tminPROP"]["week_min"][1]) == 1 else len(alltime["tminPROP"]["week_min"][1])))
for c in climo30yrs:
try:
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
round(pstdev(climo30yrs[c]["tempAVGlist"]),1),
round(mean(climo30yrs[c]["tempAVGlist_ind"]),1),
round(climo30yrs[c]["tavgPROP"]["week_max"][0],1),
climo30yrs[c]["tavgPROP"]["week_max"][1][0] if len(climo30yrs[c]["tavgPROP"]["week_max"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["week_max"][1]),
round(climo30yrs[c]["tavgPROP"]["week_min"][0],1),
climo30yrs[c]["tavgPROP"]["week_min"][1][0] if len(climo30yrs[c]["tavgPROP"]["week_min"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["week_min"][1]),
round(pstdev(climo30yrs[c]["tmax"]),1),
round(mean(climo30yrs[c]["tmax"]),1),
round(climo30yrs[c]["tmaxPROP"]["week_max"][0],1),
climo30yrs[c]["tmaxPROP"]["week_max"][1][0] if len(climo30yrs[c]["tmaxPROP"]["week_max"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["week_max"][1]),
round(climo30yrs[c]["tmaxPROP"]["week_min"][0],1),
climo30yrs[c]["tmaxPROP"]["week_min"][1][0] if len(climo30yrs[c]["tmaxPROP"]["week_min"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["week_min"][1]),
round(pstdev(climo30yrs[c]["tmin"]),1),
round(mean(climo30yrs[c]["tmin"]),1),
round(climo30yrs[c]["tminPROP"]["week_max"][0],1),
climo30yrs[c]["tminPROP"]["week_max"][1][0] if len(climo30yrs[c]["tminPROP"]["week_max"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["week_max"][1]),
round(climo30yrs[c]["tminPROP"]["week_min"][0],1),
climo30yrs[c]["tminPROP"]["week_min"][1][0] if len(climo30yrs[c]["tminPROP"]["week_min"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["week_min"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("")
if output == True:
newfn = "weekReport_centered_" + str(calendar.month_abbr[m]) + str(d) + "_" + str(climatology) + "YRclimo_" + str(increment) + "YRincr_" + clmt["station_name"] + ".csv"
with open(newfn,"w") as w:
headers = ["Assessed Period ({}-{} thru {}-{})".format(wkstart.month,wkstart.day,wkend.month,wkend.day),"PRCP Days","PRCP % of days","PRCP stdev","PRCP AVG","SNOW Days","SNOW % of days","SNOW stdev","SNOW AVG","TAVG stdev","TAVG","TMAX stdev","TMAX","TMIN stdev","TMIN"]
# HEADER
for x in range(len(headers)):
if x != len(headers) - 1: w.write(headers[x]); w.write(",")
else: w.write(headers[x]); w.write("\n")
w.write("{}-{}".format(alltime["years"][0],alltime["years"][1])); w.write(",")
w.write("{}".format(alltime["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["prcp"]),1))); w.write(",")
w.write("{}".format(alltime["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tempAVGlist"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tempAVGlist_ind"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmin"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tmin"]),1))); w.write("\n")
for x in climo30yrs:
w.write("{}-{}".format(climo30yrs[x]["years"][0],climo30yrs[x]["years"][1])); w.write(",")
w.write("{}".format(climo30yrs[x]["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["prcpPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{}".format(climo30yrs[x]["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["snowPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tempAVGlist"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tempAVGlist_ind"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmin"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tmin"]),1))); w.write("\n")
print("*** csv output successful ***")
def monthReport(m,climatology=30,increment=5,output=False):
"""Detailed Climatological Report for a given month
Args (Required):
m: month (int)
Keyword Args (optional):
climatology = 30: The span of years that averages are calculated
for (ie. '30 year climatology' or '30 year average'). This can be
modified but should always be > the increment.
increment = 5: Tells the script how often to assess/record successive
climatologies. The smaller this is, the longer the report takes
to generate. If kept at the default, for example, it would
capture the 1976-2005, 1981-2010, and 1986-2015 climatologies and
so forth.
output = False: If set to True, the script will output a CSV file of
its findings. This could be opened in a spreadsheet program for
further analysis
Examples:
monthReport(10) -> Returns a 30-yr, 5-yr incremented climatological
report for the month of October.
monthReport(12,climatology=10) -> Returns a 10-yr, 5-yr incremented
climatological report for December.
monthReport(3,climatology=20,increment=1,output=True) -> Returns a
1-yr incremented, 20yr climatology report for March and
outputs a CSV.
"""
valid_yrs = list(range(min([x for x in clmt.keys() if type(x) == int]),max([x for x in clmt.keys() if type(x) == int])+1))
#valid_yrs = [x for x in clmt.keys() if type(x) == int]
valid_yrs.sort()
climo30yrs = {}
for x in range(1811,max(valid_yrs)+1,increment):
if x in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]) and x+climatology-1 in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]+1):
climo30yrs[(x,x+climatology-1)] = {"years":(x,x+climatology-1),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"month_max_days":[-1,[]],"month_min_days":[999,[]],"month_max":[-1,[]],"month_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"month_max_days":[-1,[]],"month_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"month_max":[-999,[]],"month_min":[999,[]]},
"tmax": [],"tmaxPROP":{"month_max":[-999,[]],"month_min":[999,[]]},
"tmin": [],"tminPROP":{"month_max":[-999,[]],"month_min":[999,[]]}}
alltime = {"years":(valid_yrs[0],valid_yrs[len(valid_yrs)-1]),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"month_max_days":[-1,[]],"month_min_days":[999,[]],"month_max":[-1,[]],"month_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"month_max_days":[-1,[]],"month_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"month_max":[-999,[]],"month_min":[999,[]]},
"tmax": [],"tmaxPROP":{"month_max":[-999,[]],"month_min":[999,[]]},
"tmin": [],"tminPROP":{"month_max":[-999,[]],"month_min":[999,[]]}}
# 'recordqty', 'prcp', 'prcpDAYS', 'prcpPROP', 'snow', 'snowDAYS', 'snowPROP', 'tempAVGlist', 'tmax', 'tmaxPROP', 'tmin', 'tminPROP'
for y in valid_yrs:
if y in clmt and m in clmt[y]:
alltime["total_days"] += clmt[y][m]["recordqty"]
# PRCP
alltime["prcp"].append(sum(clmt[y][m]["prcp"]))
alltime["prcpPROP"]["days"] += clmt[y][m]["prcpDAYS"]
if clmt[y][m]["prcpDAYS"] == alltime["prcpPROP"]["month_max_days"][0]: alltime["prcpPROP"]["month_max_days"][1].append(y)
elif clmt[y][m]["prcpDAYS"] > alltime["prcpPROP"]["month_max_days"][0]:
alltime["prcpPROP"]["month_max_days"][0] = clmt[y][m]["prcpDAYS"]
alltime["prcpPROP"]["month_max_days"][1] = []
alltime["prcpPROP"]["month_max_days"][1].append(y)
if sum(clmt[y][m]["prcp"]) == alltime["prcpPROP"]["month_max"][0]: alltime["prcpPROP"]["month_max"][1].append(y)
elif sum(clmt[y][m]["prcp"]) > alltime["prcpPROP"]["month_max"][0]:
alltime["prcpPROP"]["month_max"][0] = sum(clmt[y][m]["prcp"])
alltime["prcpPROP"]["month_max"][1] = []
alltime["prcpPROP"]["month_max"][1].append(y)
if clmt[y][m]["recordqty"] > excludemonth:
if clmt[y][m]["prcpDAYS"] == alltime["prcpPROP"]["month_min_days"][0]: alltime["prcpPROP"]["month_min_days"][1].append(y)
elif clmt[y][m]["prcpDAYS"] < alltime["prcpPROP"]["month_min_days"][0]:
alltime["prcpPROP"]["month_min_days"][0] = clmt[y][m]["prcpDAYS"]
alltime["prcpPROP"]["month_min_days"][1] = []
alltime["prcpPROP"]["month_min_days"][1].append(y)
if sum(clmt[y][m]["prcp"]) == alltime["prcpPROP"]["month_min"][0]: alltime["prcpPROP"]["month_min"][1].append(y)
elif sum(clmt[y][m]["prcp"]) < alltime["prcpPROP"]["month_min"][0]:
alltime["prcpPROP"]["month_min"][0] = sum(clmt[y][m]["prcp"])
alltime["prcpPROP"]["month_min"][1] = []
alltime["prcpPROP"]["month_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["prcp"].append(sum(clmt[y][m]["prcp"]))
climo30yrs[c]["prcpPROP"]["days"] += clmt[y][m]["prcpDAYS"]
climo30yrs[c]["total_days"] += clmt[y][m]["recordqty"]
if clmt[y][m]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["month_max_days"][0]: climo30yrs[c]["prcpPROP"]["month_max_days"][1].append(y)
elif clmt[y][m]["prcpDAYS"] > climo30yrs[c]["prcpPROP"]["month_max_days"][0]:
climo30yrs[c]["prcpPROP"]["month_max_days"][0] = clmt[y][m]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["month_max_days"][1] = []
climo30yrs[c]["prcpPROP"]["month_max_days"][1].append(y)
if sum(clmt[y][m]["prcp"]) == climo30yrs[c]["prcpPROP"]["month_max"][0]: climo30yrs[c]["prcpPROP"]["month_max"][1].append(y)
elif sum(clmt[y][m]["prcp"]) > climo30yrs[c]["prcpPROP"]["month_max"][0]:
climo30yrs[c]["prcpPROP"]["month_max"][0] = sum(clmt[y][m]["prcp"])
climo30yrs[c]["prcpPROP"]["month_max"][1] = []
climo30yrs[c]["prcpPROP"]["month_max"][1].append(y)
if clmt[y][m]["recordqty"] > excludemonth:
if clmt[y][m]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["month_min_days"][0]: climo30yrs[c]["prcpPROP"]["month_min_days"][1].append(y)
elif clmt[y][m]["prcpDAYS"] < climo30yrs[c]["prcpPROP"]["month_min_days"][0]:
climo30yrs[c]["prcpPROP"]["month_min_days"][0] = clmt[y][m]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["month_min_days"][1] = []
climo30yrs[c]["prcpPROP"]["month_min_days"][1].append(y)
if sum(clmt[y][m]["prcp"]) == climo30yrs[c]["prcpPROP"]["month_min"][0]: climo30yrs[c]["prcpPROP"]["month_min"][1].append(y)
elif sum(clmt[y][m]["prcp"]) < climo30yrs[c]["prcpPROP"]["month_min"][0]:
climo30yrs[c]["prcpPROP"]["month_min"][0] = sum(clmt[y][m]["prcp"])
climo30yrs[c]["prcpPROP"]["month_min"][1] = []
climo30yrs[c]["prcpPROP"]["month_min"][1].append(y)
# SNOW
alltime["snow"].append(sum(clmt[y][m]["snow"]))
alltime["snowPROP"]["days"] += clmt[y][m]["snowDAYS"]
if clmt[y][m]["snowDAYS"] == alltime["snowPROP"]["month_max_days"][0]: alltime["snowPROP"]["month_max_days"][1].append(y)
elif clmt[y][m]["snowDAYS"] > alltime["snowPROP"]["month_max_days"][0]:
alltime["snowPROP"]["month_max_days"][0] = clmt[y][m]["snowDAYS"]
alltime["snowPROP"]["month_max_days"][1] = []
alltime["snowPROP"]["month_max_days"][1].append(y)
if sum(clmt[y][m]["snow"]) == alltime["snowPROP"]["month_max"][0]: alltime["snowPROP"]["month_max"][1].append(y)
elif sum(clmt[y][m]["snow"]) > alltime["snowPROP"]["month_max"][0]:
alltime["snowPROP"]["month_max"][0] = sum(clmt[y][m]["snow"])
alltime["snowPROP"]["month_max"][1] = []
alltime["snowPROP"]["month_max"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["snow"].append(sum(clmt[y][m]["snow"]))
climo30yrs[c]["snowPROP"]["days"] += clmt[y][m]["snowDAYS"]
if clmt[y][m]["snowDAYS"] == climo30yrs[c]["snowPROP"]["month_max_days"][0]: climo30yrs[c]["snowPROP"]["month_max_days"][1].append(y)
elif clmt[y][m]["snowDAYS"] > climo30yrs[c]["snowPROP"]["month_max_days"][0]:
climo30yrs[c]["snowPROP"]["month_max_days"][0] = clmt[y][m]["snowDAYS"]
climo30yrs[c]["snowPROP"]["month_max_days"][1] = []
climo30yrs[c]["snowPROP"]["month_max_days"][1].append(y)
if sum(clmt[y][m]["snow"]) == climo30yrs[c]["snowPROP"]["month_max"][0]: climo30yrs[c]["snowPROP"]["month_max"][1].append(y)
elif sum(clmt[y][m]["snow"]) > climo30yrs[c]["snowPROP"]["month_max"][0]:
climo30yrs[c]["snowPROP"]["month_max"][0] = sum(clmt[y][m]["snow"])
climo30yrs[c]["snowPROP"]["month_max"][1] = []
climo30yrs[c]["snowPROP"]["month_max"][1].append(y)
for x in clmt[y][m]["tempAVGlist"]: alltime["tempAVGlist_ind"].append(x)
if len(clmt[y][m]["tempAVGlist"]) > excludemonth_tavg:
alltime["tempAVGlist"].append(mean(clmt[y][m]["tempAVGlist"]))
if mean(clmt[y][m]["tempAVGlist"]) == alltime["tavgPROP"]["month_max"][0]: alltime["tavgPROP"]["month_max"][1].append(y)
elif mean(clmt[y][m]["tempAVGlist"]) > alltime["tavgPROP"]["month_max"][0]:
alltime["tavgPROP"]["month_max"][0] = mean(clmt[y][m]["tempAVGlist"])
alltime["tavgPROP"]["month_max"][1] = []
alltime["tavgPROP"]["month_max"][1].append(y)
if mean(clmt[y][m]["tempAVGlist"]) == alltime["tavgPROP"]["month_min"][0]: alltime["tavgPROP"]["month_min"][1].append(y)
elif mean(clmt[y][m]["tempAVGlist"]) < alltime["tavgPROP"]["month_min"][0]:
alltime["tavgPROP"]["month_min"][0] = mean(clmt[y][m]["tempAVGlist"])
alltime["tavgPROP"]["month_min"][1] = []
alltime["tavgPROP"]["month_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in clmt[y][m]["tempAVGlist"]:climo30yrs[c]["tempAVGlist_ind"].append(x)
if len(clmt[y][m]["tempAVGlist"]) > excludemonth_tavg:
climo30yrs[c]["tempAVGlist"].append(mean(clmt[y][m]["tempAVGlist"]))
if mean(clmt[y][m]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["month_max"][0]: climo30yrs[c]["tavgPROP"]["month_max"][1].append(y)
elif mean(clmt[y][m]["tempAVGlist"]) > climo30yrs[c]["tavgPROP"]["month_max"][0]:
climo30yrs[c]["tavgPROP"]["month_max"][0] = mean(clmt[y][m]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["month_max"][1] = []
climo30yrs[c]["tavgPROP"]["month_max"][1].append(y)
if mean(clmt[y][m]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["month_min"][0]: climo30yrs[c]["tavgPROP"]["month_min"][1].append(y)
elif mean(clmt[y][m]["tempAVGlist"]) < climo30yrs[c]["tavgPROP"]["month_min"][0]:
climo30yrs[c]["tavgPROP"]["month_min"][0] = mean(clmt[y][m]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["month_min"][1] = []
climo30yrs[c]["tavgPROP"]["month_min"][1].append(y)
# TMAX
for x in clmt[y][m]["tmax"]: alltime["tmax"].append(x)
if len(clmt[y][m]["tmax"]) > excludemonth:
if mean(clmt[y][m]["tmax"]) == alltime["tmaxPROP"]["month_max"][0]: alltime["tmaxPROP"]["month_max"][1].append(y)
elif mean(clmt[y][m]["tmax"]) > alltime["tmaxPROP"]["month_max"][0]:
alltime["tmaxPROP"]["month_max"][0] = mean(clmt[y][m]["tmax"])
alltime["tmaxPROP"]["month_max"][1] = []
alltime["tmaxPROP"]["month_max"][1].append(y)
if mean(clmt[y][m]["tmax"]) == alltime["tmaxPROP"]["month_min"][0]: alltime["tmaxPROP"]["month_min"][1].append(y)
elif mean(clmt[y][m]["tmax"]) < alltime["tmaxPROP"]["month_min"][0]:
alltime["tmaxPROP"]["month_min"][0] = mean(clmt[y][m]["tmax"])
alltime["tmaxPROP"]["month_min"][1] = []
alltime["tmaxPROP"]["month_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in clmt[y][m]["tmax"]: climo30yrs[c]["tmax"].append(x)
if len(clmt[y][m]["tmax"]) > excludemonth:
if mean(clmt[y][m]["tmax"]) == climo30yrs[c]["tmaxPROP"]["month_max"][0]: climo30yrs[c]["tmaxPROP"]["month_max"][1].append(y)
elif mean(clmt[y][m]["tmax"]) > climo30yrs[c]["tmaxPROP"]["month_max"][0]:
climo30yrs[c]["tmaxPROP"]["month_max"][0] = mean(clmt[y][m]["tmax"])
climo30yrs[c]["tmaxPROP"]["month_max"][1] = []
climo30yrs[c]["tmaxPROP"]["month_max"][1].append(y)
if mean(clmt[y][m]["tmax"]) == climo30yrs[c]["tmaxPROP"]["month_min"][0]: climo30yrs[c]["tmaxPROP"]["month_min"][1].append(y)
elif mean(clmt[y][m]["tmax"]) < climo30yrs[c]["tmaxPROP"]["month_min"][0]:
climo30yrs[c]["tmaxPROP"]["month_min"][0] = mean(clmt[y][m]["tmax"])
climo30yrs[c]["tmaxPROP"]["month_min"][1] = []
climo30yrs[c]["tmaxPROP"]["month_min"][1].append(y)
# TMIN
for x in clmt[y][m]["tmin"]: alltime["tmin"].append(x)
if len(clmt[y][m]["tmin"]) > excludemonth:
if mean(clmt[y][m]["tmin"]) == alltime["tminPROP"]["month_max"][0]: alltime["tminPROP"]["month_max"][1].append(y)
elif mean(clmt[y][m]["tmin"]) > alltime["tminPROP"]["month_max"][0]:
alltime["tminPROP"]["month_max"][0] = mean(clmt[y][m]["tmin"])
alltime["tminPROP"]["month_max"][1] = []
alltime["tminPROP"]["month_max"][1].append(y)
if mean(clmt[y][m]["tmin"]) == alltime["tminPROP"]["month_min"][0]: alltime["tminPROP"]["month_min"][1].append(y)
elif mean(clmt[y][m]["tmin"]) < alltime["tminPROP"]["month_min"][0]:
alltime["tminPROP"]["month_min"][0] = mean(clmt[y][m]["tmin"])
alltime["tminPROP"]["month_min"][1] = []
alltime["tminPROP"]["month_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in clmt[y][m]["tmin"]: climo30yrs[c]["tmin"].append(x)
if len(clmt[y][m]["tmin"]) > excludemonth:
if mean(clmt[y][m]["tmin"]) == climo30yrs[c]["tminPROP"]["month_max"][0]: climo30yrs[c]["tminPROP"]["month_max"][1].append(y)
elif mean(clmt[y][m]["tmin"]) > climo30yrs[c]["tminPROP"]["month_max"][0]:
climo30yrs[c]["tminPROP"]["month_max"][0] = mean(clmt[y][m]["tmin"])
climo30yrs[c]["tminPROP"]["month_max"][1] = []
climo30yrs[c]["tminPROP"]["month_max"][1].append(y)
if mean(clmt[y][m]["tmin"]) == climo30yrs[c]["tminPROP"]["month_min"][0]: climo30yrs[c]["tminPROP"]["month_min"][1].append(y)
elif mean(clmt[y][m]["tmin"]) < climo30yrs[c]["tminPROP"]["month_min"][0]:
climo30yrs[c]["tminPROP"]["month_min"][0] = mean(clmt[y][m]["tmin"])
climo30yrs[c]["tminPROP"]["month_min"][1] = []
climo30yrs[c]["tminPROP"]["month_min"][1].append(y)
# PRINT REPORT
print("--------------------------------")
print("Climatology Report for {}".format(calendar.month_name[m]))
print("City: {}, {}".format(clmt["station"],clmt["station_name"]))
print("{}-{}; {}-Year Incremented {}-Year Climatologies".format(min(valid_yrs),max(valid_yrs),increment,climatology))
print("--------------------------------")
print("Part 1: {} Precipitation Stats".format(calendar.month_name[m]))
print("{:▒^9} {:▒^11} {:▒^8} {:▒^8} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^8} {:▒^6} {:▒^12} |".format("Years","PRCP","PRCP","PRCP","PRCP","PRCP","PRCP","SNOW","SNOW","SNOW","SNOW"))
print("{:▒^9} {:▒^11} {:▒^8} {:▒^8} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^8} {:▒^6} {:▒^12} |".format("","DAYS","DAYS MAX","DAYS MIN","AVG", "MAX","MIN","DAYS","DAYS MAX","AVG", "MAX"))
# Y PD PDx PDn PA PM Pmin SD SDx SA SM
print("{:-^9} {:-^11} {:-^8} {:-^8} {:-^6} {:-^12} {:-^12} | {:-^11} {:-^8} {:-^6} {:-^12} |".format("","","","","","","","","","",""))
print("{:^9} {:4}:{:>5}% {:>2}, {:^4} {:>2}, {:^4} {:^6.2f} {:>5.2f}, {:^5} {:>5}, {:^5} | {:4}:{:>5}% {:>2}, {:^4} {:^6.1f} {:>5.1f}, {:^5} |".format("All Time",
alltime["prcpPROP"]["days"],
round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1),
alltime["prcpPROP"]["month_max_days"][0],
alltime["prcpPROP"]["month_max_days"][1][0] if len(alltime["prcpPROP"]["month_max_days"][1]) == 1 else len(alltime["prcpPROP"]["month_max_days"][1]),
alltime["prcpPROP"]["month_min_days"][0],
alltime["prcpPROP"]["month_min_days"][1][0] if len(alltime["prcpPROP"]["month_min_days"][1]) == 1 else len(alltime["prcpPROP"]["month_min_days"][1]),
round(mean(alltime["prcp"]),2) if len(alltime["prcp"]) > 0 else "--",
round(alltime["prcpPROP"]["month_max"][0],2),
alltime["prcpPROP"]["month_max"][1][0] if len(alltime["prcpPROP"]["month_max"][1]) == 1 else len(alltime["prcpPROP"]["month_max"][1]),
round(alltime["prcpPROP"]["month_min"][0],2),
alltime["prcpPROP"]["month_min"][1][0] if len(alltime["prcpPROP"]["month_min"][1]) == 1 else len(alltime["prcpPROP"]["month_min"][1]),
alltime["snowPROP"]["days"] if alltime["snowPROP"]["days"] > 0 else "--",
round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1) if alltime["snowPROP"]["days"] > 0 else "--",
alltime["snowPROP"]["month_max_days"][0],
alltime["snowPROP"]["month_max_days"][1][0] if len(alltime["snowPROP"]["month_max_days"][1]) == 1 else len(alltime["snowPROP"]["month_max_days"][1]),
round(mean(alltime["snow"]),1) if len(alltime["snow"]) > 0 else "--",
round(alltime["snowPROP"]["month_max"][0],2),
alltime["snowPROP"]["month_max"][1][0] if len(alltime["snowPROP"]["month_max"][1]) == 1 else len(alltime["snowPROP"]["month_max"][1])))
for c in climo30yrs:
#print(climo30yrs[c]["prcpPROP"]["days"],climo30yrs[c]["total_days"])
#print(climo30yrs[c]["snowPROP"]["days"],climo30yrs[c]["total_days"])
try:
print("{:^9} {:4}:{:>5}% {:>2}, {:^4} {:>2}, {:^4} {:^6.2f} {:>5.2f}, {:^5} {:>5}, {:^5} | {:4}:{:>5}% {:>2}, {:^4} {:^6.1f} {:>5.1f}, {:^5} |".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
climo30yrs[c]["prcpPROP"]["days"],
round(100 * climo30yrs[c]["prcpPROP"]["days"] / climo30yrs[c]["total_days"],1),
climo30yrs[c]["prcpPROP"]["month_max_days"][0],
climo30yrs[c]["prcpPROP"]["month_max_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["month_max_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["month_max_days"][1]),
climo30yrs[c]["prcpPROP"]["month_min_days"][0],
climo30yrs[c]["prcpPROP"]["month_min_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["month_min_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["month_min_days"][1]),
round(mean(climo30yrs[c]["prcp"]),2),
round(climo30yrs[c]["prcpPROP"]["month_max"][0],2),
climo30yrs[c]["prcpPROP"]["month_max"][1][0] if len(climo30yrs[c]["prcpPROP"]["month_max"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["month_max"][1]),
round(climo30yrs[c]["prcpPROP"]["month_min"][0],2),
climo30yrs[c]["prcpPROP"]["month_min"][1][0] if len(climo30yrs[c]["prcpPROP"]["month_min"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["month_min"][1]),
climo30yrs[c]["snowPROP"]["days"] if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
round(100 * climo30yrs[c]["snowPROP"]["days"] / climo30yrs[c]["total_days"],1) if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
climo30yrs[c]["snowPROP"]["month_max_days"][0],
climo30yrs[c]["snowPROP"]["month_max_days"][1][0] if len(climo30yrs[c]["snowPROP"]["month_max_days"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["month_max_days"][1]),
round(mean(climo30yrs[c]["snow"]),1) if len(climo30yrs[c]["snow"]) > 0 else "--",
round(climo30yrs[c]["snowPROP"]["month_max"][0],2),
climo30yrs[c]["snowPROP"]["month_max"][1][0] if len(climo30yrs[c]["snowPROP"]["month_max"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["month_max"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("\nPart 2: {} Temperature Stats".format(calendar.month_name[m]))
print("{:▒^9} {:▒^37} | {:▒^37} | {:▒^37}".format("Years","AVG TEMP","TMAX","TMIN"))
print("{:▒^9} {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12}".format("","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN"))
# Y TSTDV TMA TMX TMn TSTDV TMA TMX TMn TSTDV TMA TMX TMn
# "tempAVGlist": [],"tavgPROP":{"month_max":[-999,[]],"month_min":[999,[]]},
print("{:-^9} {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12}".format("","","","","","","","","","","","",""))
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format("All Time",
round(pstdev(alltime["tempAVGlist"]),1),
round(mean(alltime["tempAVGlist_ind"]),1),
round(alltime["tavgPROP"]["month_max"][0],1),
alltime["tavgPROP"]["month_max"][1][0] if len(alltime["tavgPROP"]["month_max"][1]) == 1 else len(alltime["tavgPROP"]["month_max"][1]),
round(alltime["tavgPROP"]["month_min"][0],1),
alltime["tavgPROP"]["month_min"][1][0] if len(alltime["tavgPROP"]["month_min"][1]) == 1 else len(alltime["tavgPROP"]["month_min"][1]),
round(pstdev(alltime["tmax"]),1),
round(mean(alltime["tmax"]),1),
round(alltime["tmaxPROP"]["month_max"][0],1),
alltime["tmaxPROP"]["month_max"][1][0] if len(alltime["tmaxPROP"]["month_max"][1]) == 1 else len(alltime["tmaxPROP"]["month_max"][1]),
round(alltime["tmaxPROP"]["month_min"][0],1),
alltime["tmaxPROP"]["month_min"][1][0] if len(alltime["tmaxPROP"]["month_min"][1]) == 1 else len(alltime["tmaxPROP"]["month_min"][1]),
round(pstdev(alltime["tmin"]),1),
round(mean(alltime["tmin"]),1),
round(alltime["tminPROP"]["month_max"][0],1),
alltime["tminPROP"]["month_max"][1][0] if len(alltime["tminPROP"]["month_max"][1]) == 1 else len(alltime["tminPROP"]["month_max"][1]),
round(alltime["tminPROP"]["month_min"][0],1),
alltime["tminPROP"]["month_min"][1][0] if len(alltime["tminPROP"]["month_min"][1]) == 1 else len(alltime["tminPROP"]["month_min"][1])))
for c in climo30yrs:
try:
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
round(pstdev(climo30yrs[c]["tempAVGlist"]),1),
round(mean(climo30yrs[c]["tempAVGlist_ind"]),1),
round(climo30yrs[c]["tavgPROP"]["month_max"][0],1),
climo30yrs[c]["tavgPROP"]["month_max"][1][0] if len(climo30yrs[c]["tavgPROP"]["month_max"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["month_max"][1]),
round(climo30yrs[c]["tavgPROP"]["month_min"][0],1),
climo30yrs[c]["tavgPROP"]["month_min"][1][0] if len(climo30yrs[c]["tavgPROP"]["month_min"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["month_min"][1]),
round(pstdev(climo30yrs[c]["tmax"]),1),
round(mean(climo30yrs[c]["tmax"]),1),
round(climo30yrs[c]["tmaxPROP"]["month_max"][0],1),
climo30yrs[c]["tmaxPROP"]["month_max"][1][0] if len(climo30yrs[c]["tmaxPROP"]["month_max"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["month_max"][1]),
round(climo30yrs[c]["tmaxPROP"]["month_min"][0],1),
climo30yrs[c]["tmaxPROP"]["month_min"][1][0] if len(climo30yrs[c]["tmaxPROP"]["month_min"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["month_min"][1]),
round(pstdev(climo30yrs[c]["tmin"]),1),
round(mean(climo30yrs[c]["tmin"]),1),
round(climo30yrs[c]["tminPROP"]["month_max"][0],1),
climo30yrs[c]["tminPROP"]["month_max"][1][0] if len(climo30yrs[c]["tminPROP"]["month_max"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["month_max"][1]),
round(climo30yrs[c]["tminPROP"]["month_min"][0],1),
climo30yrs[c]["tminPROP"]["month_min"][1][0] if len(climo30yrs[c]["tminPROP"]["month_min"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["month_min"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("")
if output == True:
newfn = "monthReport_" + str(calendar.month_name[m]) + "_" + str(climatology) + "YRclimo_" + str(increment) + "YRincr_" + clmt["station_name"] + ".csv"
with open(newfn,"w") as w:
headers = ["Assessed Period ({})".format(str(calendar.month_name[m])),"PRCP Days","PRCP % of days","PRCP stdev","PRCP AVG","SNOW Days","SNOW % of days","SNOW stdev","SNOW AVG","TAVG stdev","TAVG","TMAX stdev","TMAX","TMIN stdev","TMIN"]
# HEADER
for x in range(len(headers)):
if x != len(headers) - 1: w.write(headers[x]); w.write(",")
else: w.write(headers[x]); w.write("\n")
w.write("{}-{}".format(alltime["years"][0],alltime["years"][1])); w.write(",")
w.write("{}".format(alltime["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["prcp"]),1))); w.write(",")
w.write("{}".format(alltime["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tempAVGlist"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tempAVGlist_ind"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmin"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["tmin"]),1))); w.write("\n")
for x in climo30yrs:
w.write("{}-{}".format(climo30yrs[x]["years"][0],climo30yrs[x]["years"][1])); w.write(",")
w.write("{}".format(climo30yrs[x]["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["prcpPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{}".format(climo30yrs[x]["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["snowPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tempAVGlist"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tempAVGlist_ind"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmin"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["tmin"]),1))); w.write("\n")
print("*** csv output successful ***")
def yearReport(climatology=30,increment=5,output=False):
"""Detailed Climatological Report all calendar years on record
* no required arguments *
Keyword Args (optional):
climatology = 30: The span of years that averages are calculated
for (ie. '30 year climatology' or '30 year average'). This can be
modified but should always be > the increment.
increment = 5: Tells the script how often to assess/record successive
climatologies. The smaller this is, the longer the report takes
to generate. If kept at the default, for example, it would
capture the 1976-2005, 1981-2010, and 1986-2015 climatologies and
so forth.
output = False: If set to True, the script will output a CSV file of
its findings. This could be opened in a spreadsheet program for
further analysis
Examples:
yearReport() -> Returns a 30-yr, 5-yr incremented climatological
report for all calendar years on record
yearReport(climatology=10) -> Returns a 10-yr, 5-yr incremented
climatological report for all years.
yearReport(climatology=20,increment=1,output=True) -> Returns a 1-yr
incremented, 20yr climatology report for all years and
outputs a CSV.
"""
valid_yrs = list(range(min([x for x in clmt.keys() if type(x) == int]),max([x for x in clmt.keys() if type(x) == int])+1))
#valid_yrs = [x for x in clmt.keys() if type(x) == int]
valid_yrs.sort()
climo30yrs = {}
for x in range(1811,max(valid_yrs)+1,increment):
if x in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]) and x+climatology-1 in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]+1):
climo30yrs[(x,x+climatology-1)] = {"years":(x,x+climatology-1),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"year_max_days":[-1,[]],"year_min_days":[999,[]],"year_max":[-1,[]],"year_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"year_max_days":[-1,[]],"year_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
"tmax": [],"tmaxPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
"tmin": [],"tminPROP":{"year_max":[-999,[]],"year_min":[999,[]]}}
alltime = {"years":(valid_yrs[0],valid_yrs[len(valid_yrs)-1]),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"year_max_days":[-1,[]],"year_min_days":[999,[]],"year_max":[-1,[]],"year_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"year_max_days":[-1,[]],"year_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
"tmax": [],"tmaxPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
"tmin": [],"tminPROP":{"year_max":[-999,[]],"year_min":[999,[]]}}
print("*** PLEASE WAIT. This will take a few moments ***")
for y in valid_yrs:
alltime["total_days"] += clmt[y]["recordqty"]
# PRCP
alltime["prcp"].append(sum(clmt[y]["prcp"]))
alltime["prcpPROP"]["days"] += clmt[y]["prcpDAYS"]
if clmt[y]["prcpDAYS"] == alltime["prcpPROP"]["year_max_days"][0]: alltime["prcpPROP"]["year_max_days"][1].append(y)
elif clmt[y]["prcpDAYS"] > alltime["prcpPROP"]["year_max_days"][0]:
alltime["prcpPROP"]["year_max_days"][0] = clmt[y]["prcpDAYS"]
alltime["prcpPROP"]["year_max_days"][1] = []
alltime["prcpPROP"]["year_max_days"][1].append(y)
if sum(clmt[y]["prcp"]) == alltime["prcpPROP"]["year_max"][0]: alltime["prcpPROP"]["year_max"][1].append(y)
elif sum(clmt[y]["prcp"]) > alltime["prcpPROP"]["year_max"][0]:
alltime["prcpPROP"]["year_max"][0] = sum(clmt[y]["prcp"])
alltime["prcpPROP"]["year_max"][1] = []
alltime["prcpPROP"]["year_max"][1].append(y)
if clmt[y]["recordqty"] > excludeyear:
if clmt[y]["prcpDAYS"] == alltime["prcpPROP"]["year_min_days"][0]: alltime["prcpPROP"]["year_min_days"][1].append(y)
elif clmt[y]["prcpDAYS"] < alltime["prcpPROP"]["year_min_days"][0]:
alltime["prcpPROP"]["year_min_days"][0] = clmt[y]["prcpDAYS"]
alltime["prcpPROP"]["year_min_days"][1] = []
alltime["prcpPROP"]["year_min_days"][1].append(y)
if sum(clmt[y]["prcp"]) == alltime["prcpPROP"]["year_min"][0]: alltime["prcpPROP"]["year_min"][1].append(y)
elif sum(clmt[y]["prcp"]) < alltime["prcpPROP"]["year_min"][0]:
alltime["prcpPROP"]["year_min"][0] = sum(clmt[y]["prcp"])
alltime["prcpPROP"]["year_min"][1] = []
alltime["prcpPROP"]["year_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["prcp"].append(sum(clmt[y]["prcp"]))
climo30yrs[c]["prcpPROP"]["days"] += clmt[y]["prcpDAYS"]
climo30yrs[c]["total_days"] += clmt[y]["recordqty"]
if clmt[y]["recordqty"] > excludeyear:
if clmt[y]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["year_max_days"][0]: climo30yrs[c]["prcpPROP"]["year_max_days"][1].append(y)
elif clmt[y]["prcpDAYS"] > climo30yrs[c]["prcpPROP"]["year_max_days"][0]:
climo30yrs[c]["prcpPROP"]["year_max_days"][0] = clmt[y]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["year_max_days"][1] = []
climo30yrs[c]["prcpPROP"]["year_max_days"][1].append(y)
if clmt[y]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["year_min_days"][0]: climo30yrs[c]["prcpPROP"]["year_min_days"][1].append(y)
elif clmt[y]["prcpDAYS"] < climo30yrs[c]["prcpPROP"]["year_min_days"][0]:
climo30yrs[c]["prcpPROP"]["year_min_days"][0] = clmt[y]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["year_min_days"][1] = []
climo30yrs[c]["prcpPROP"]["year_min_days"][1].append(y)
if sum(clmt[y]["prcp"]) == climo30yrs[c]["prcpPROP"]["year_max"][0]: climo30yrs[c]["prcpPROP"]["year_max"][1].append(y)
elif sum(clmt[y]["prcp"]) > climo30yrs[c]["prcpPROP"]["year_max"][0]:
climo30yrs[c]["prcpPROP"]["year_max"][0] = sum(clmt[y]["prcp"])
climo30yrs[c]["prcpPROP"]["year_max"][1] = []
climo30yrs[c]["prcpPROP"]["year_max"][1].append(y)
if sum(clmt[y]["prcp"]) == climo30yrs[c]["prcpPROP"]["year_min"][0]: climo30yrs[c]["prcpPROP"]["year_min"][1].append(y)
elif sum(clmt[y]["prcp"]) < climo30yrs[c]["prcpPROP"]["year_min"][0]:
climo30yrs[c]["prcpPROP"]["year_min"][0] = sum(clmt[y]["prcp"])
climo30yrs[c]["prcpPROP"]["year_min"][1] = []
climo30yrs[c]["prcpPROP"]["year_min"][1].append(y)
# SNOW
alltime["snow"].append(sum(clmt[y]["snow"]))
alltime["snowPROP"]["days"] += clmt[y]["snowDAYS"]
if clmt[y]["recordqty"] > excludeyear:
if clmt[y]["snowDAYS"] == alltime["snowPROP"]["year_max_days"][0]: alltime["snowPROP"]["year_max_days"][1].append(y)
elif clmt[y]["snowDAYS"] > alltime["snowPROP"]["year_max_days"][0]:
alltime["snowPROP"]["year_max_days"][0] = clmt[y]["snowDAYS"]
alltime["snowPROP"]["year_max_days"][1] = []
alltime["snowPROP"]["year_max_days"][1].append(y)
if sum(clmt[y]["snow"]) == alltime["snowPROP"]["year_max"][0]: alltime["snowPROP"]["year_max"][1].append(y)
elif sum(clmt[y]["snow"]) > alltime["snowPROP"]["year_max"][0]:
alltime["snowPROP"]["year_max"][0] = sum(clmt[y]["snow"])
alltime["snowPROP"]["year_max"][1] = []
alltime["snowPROP"]["year_max"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["snow"].append(sum(clmt[y]["snow"]))
climo30yrs[c]["snowPROP"]["days"] += clmt[y]["snowDAYS"]
if clmt[y]["recordqty"] > excludeyear:
if clmt[y]["snowDAYS"] == climo30yrs[c]["snowPROP"]["year_max_days"][0]: climo30yrs[c]["snowPROP"]["year_max_days"][1].append(y)
elif clmt[y]["snowDAYS"] > climo30yrs[c]["snowPROP"]["year_max_days"][0]:
climo30yrs[c]["snowPROP"]["year_max_days"][0] = clmt[y]["snowDAYS"]
climo30yrs[c]["snowPROP"]["year_max_days"][1] = []
climo30yrs[c]["snowPROP"]["year_max_days"][1].append(y)
if sum(clmt[y]["snow"]) == climo30yrs[c]["snowPROP"]["year_max"][0]: climo30yrs[c]["snowPROP"]["year_max"][1].append(y)
elif sum(clmt[y]["snow"]) > climo30yrs[c]["snowPROP"]["year_max"][0]:
climo30yrs[c]["snowPROP"]["year_max"][0] = sum(clmt[y]["snow"])
climo30yrs[c]["snowPROP"]["year_max"][1] = []
climo30yrs[c]["snowPROP"]["year_max"][1].append(y)
# 'recordqty', 'prcp', 'prcpDAYS', 'prcpPROP', 'snow', 'snowDAYS', 'snowPROP', 'tempAVGlist', 'tmax', 'tmaxPROP', 'tmin', 'tminPROP'
# TAVG
for x in clmt[y]["tempAVGlist"]: alltime["tempAVGlist_ind"].append(x)
if len(clmt[y]["tempAVGlist"]) > excludeyear_tavg:
alltime["tempAVGlist"].append(mean(clmt[y]["tempAVGlist"]))
if mean(clmt[y]["tempAVGlist"]) == alltime["tavgPROP"]["year_max"][0]: alltime["tavgPROP"]["year_max"][1].append(y)
elif mean(clmt[y]["tempAVGlist"]) > alltime["tavgPROP"]["year_max"][0]:
alltime["tavgPROP"]["year_max"][0] = mean(clmt[y]["tempAVGlist"])
alltime["tavgPROP"]["year_max"][1] = []
alltime["tavgPROP"]["year_max"][1].append(y)
if mean(clmt[y]["tempAVGlist"]) == alltime["tavgPROP"]["year_min"][0]: alltime["tavgPROP"]["year_min"][1].append(y)
elif mean(clmt[y]["tempAVGlist"]) < alltime["tavgPROP"]["year_min"][0]:
alltime["tavgPROP"]["year_min"][0] = mean(clmt[y]["tempAVGlist"])
alltime["tavgPROP"]["year_min"][1] = []
alltime["tavgPROP"]["year_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in clmt[y]["tempAVGlist"]:climo30yrs[c]["tempAVGlist_ind"].append(x)
if len(clmt[y]["tempAVGlist"]) > excludeyear_tavg:
climo30yrs[c]["tempAVGlist"].append(mean(clmt[y]["tempAVGlist"]))
if mean(clmt[y]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["year_max"][0]: climo30yrs[c]["tavgPROP"]["year_max"][1].append(y)
elif mean(clmt[y]["tempAVGlist"]) > climo30yrs[c]["tavgPROP"]["year_max"][0]:
climo30yrs[c]["tavgPROP"]["year_max"][0] = mean(clmt[y]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["year_max"][1] = []
climo30yrs[c]["tavgPROP"]["year_max"][1].append(y)
if mean(clmt[y]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["year_min"][0]: climo30yrs[c]["tavgPROP"]["year_min"][1].append(y)
elif mean(clmt[y]["tempAVGlist"]) < climo30yrs[c]["tavgPROP"]["year_min"][0]:
climo30yrs[c]["tavgPROP"]["year_min"][0] = mean(clmt[y]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["year_min"][1] = []
climo30yrs[c]["tavgPROP"]["year_min"][1].append(y)
# TMAX
for x in clmt[y]["tmax"]: alltime["tmax"].append(x)
if len(clmt[y]["tmax"]) > excludeyear:
if mean(clmt[y]["tmax"]) == alltime["tmaxPROP"]["year_max"][0]: alltime["tmaxPROP"]["year_max"][1].append(y)
elif mean(clmt[y]["tmax"]) > alltime["tmaxPROP"]["year_max"][0]:
alltime["tmaxPROP"]["year_max"][0] = mean(clmt[y]["tmax"])
alltime["tmaxPROP"]["year_max"][1] = []
alltime["tmaxPROP"]["year_max"][1].append(y)
if mean(clmt[y]["tmax"]) == alltime["tmaxPROP"]["year_min"][0]: alltime["tmaxPROP"]["year_min"][1].append(y)
elif mean(clmt[y]["tmax"]) < alltime["tmaxPROP"]["year_min"][0]:
alltime["tmaxPROP"]["year_min"][0] = mean(clmt[y]["tmax"])
alltime["tmaxPROP"]["year_min"][1] = []
alltime["tmaxPROP"]["year_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in clmt[y]["tmax"]: climo30yrs[c]["tmax"].append(x)
if len(clmt[y]["tmax"]) > excludeyear:
if mean(clmt[y]["tmax"]) == climo30yrs[c]["tmaxPROP"]["year_max"][0]: climo30yrs[c]["tmaxPROP"]["year_max"][1].append(y)
elif mean(clmt[y]["tmax"]) > climo30yrs[c]["tmaxPROP"]["year_max"][0]:
climo30yrs[c]["tmaxPROP"]["year_max"][0] = mean(clmt[y]["tmax"])
climo30yrs[c]["tmaxPROP"]["year_max"][1] = []
climo30yrs[c]["tmaxPROP"]["year_max"][1].append(y)
if mean(clmt[y]["tmax"]) == climo30yrs[c]["tmaxPROP"]["year_min"][0]: climo30yrs[c]["tmaxPROP"]["year_min"][1].append(y)
elif mean(clmt[y]["tmax"]) < climo30yrs[c]["tmaxPROP"]["year_min"][0]:
climo30yrs[c]["tmaxPROP"]["year_min"][0] = mean(clmt[y]["tmax"])
climo30yrs[c]["tmaxPROP"]["year_min"][1] = []
climo30yrs[c]["tmaxPROP"]["year_min"][1].append(y)
# TMIN
for x in clmt[y]["tmin"]: alltime["tmin"].append(x)
if len(clmt[y]["tmin"]) > excludeyear:
if mean(clmt[y]["tmin"]) == alltime["tminPROP"]["year_max"][0]: alltime["tminPROP"]["year_max"][1].append(y)
elif mean(clmt[y]["tmin"]) > alltime["tminPROP"]["year_max"][0]:
alltime["tminPROP"]["year_max"][0] = mean(clmt[y]["tmin"])
alltime["tminPROP"]["year_max"][1] = []
alltime["tminPROP"]["year_max"][1].append(y)
if mean(clmt[y]["tmin"]) == alltime["tminPROP"]["year_min"][0]: alltime["tminPROP"]["year_min"][1].append(y)
elif mean(clmt[y]["tmin"]) < alltime["tminPROP"]["year_min"][0]:
alltime["tminPROP"]["year_min"][0] = mean(clmt[y]["tmin"])
alltime["tminPROP"]["year_min"][1] = []
alltime["tminPROP"]["year_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in clmt[y]["tmin"]: climo30yrs[c]["tmin"].append(x)
if len(clmt[y]["tmin"]) > excludeyear:
if mean(clmt[y]["tmin"]) == climo30yrs[c]["tminPROP"]["year_max"][0]: climo30yrs[c]["tminPROP"]["year_max"][1].append(y)
elif mean(clmt[y]["tmin"]) > climo30yrs[c]["tminPROP"]["year_max"][0]:
climo30yrs[c]["tminPROP"]["year_max"][0] = mean(clmt[y]["tmin"])
climo30yrs[c]["tminPROP"]["year_max"][1] = []
climo30yrs[c]["tminPROP"]["year_max"][1].append(y)
if mean(clmt[y]["tmin"]) == climo30yrs[c]["tminPROP"]["year_min"][0]: climo30yrs[c]["tminPROP"]["year_min"][1].append(y)
elif mean(clmt[y]["tmin"]) < climo30yrs[c]["tminPROP"]["year_min"][0]:
climo30yrs[c]["tminPROP"]["year_min"][0] = mean(clmt[y]["tmin"])
climo30yrs[c]["tminPROP"]["year_min"][1] = []
climo30yrs[c]["tminPROP"]["year_min"][1].append(y)
# PRINT REPORT
print("---------------------------------------------------")
print("Climatology Report for All Years on Record")
print("City: {}, {}".format(clmt["station"],clmt["station_name"]))
print("{}-{}; {}-Year Incremented {}-Year Climatologies".format(min(valid_yrs),max(valid_yrs),increment,climatology))
print("---------------------------------------------------")
print("Part 1: Precipitation Stats")
print("{:▒^9} {:▒^12} {:▒^9} {:▒^9} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^9} {:▒^6} {:▒^11} |".format("Years","PRCP","PRCP","PRCP","PRCP","PRCP","PRCP","SNOW","SNOW","SNOW","SNOW"))
print("{:▒^9} {:▒^12} {:▒^9} {:▒^9} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^9} {:▒^6} {:▒^11} |".format("","DAYS","DAYS MAX","DAYS MIN","AVG", "MAX","MIN","DAYS","DAYS MAX","AVG", "MAX"))
# Y PD PDx PDn PA PM Pmin SD SDx SA SM
print("{:-^9} {:-^12} {:-^9} {:-^9} {:-^6} {:-^12} {:-^12} | {:-^11} {:-^9} {:-^6} {:-^11} |".format("","","","","","","","","","",""))
print("{:^9} {:5}:{:>5}% {:>3}, {:^4} {:>3}, {:^4} {:^6.2f} {:>6.2f}, {:^4} {:>6.2f}, {:^4} | {:4}:{:>5}% {:>3}, {:^4} {:^6.1f} {:>5.1f}, {:^4} |".format("All Time",
alltime["prcpPROP"]["days"],
round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1),
alltime["prcpPROP"]["year_max_days"][0],
alltime["prcpPROP"]["year_max_days"][1][0] if len(alltime["prcpPROP"]["year_max_days"][1]) == 1 else len(alltime["prcpPROP"]["year_max_days"][1]),
alltime["prcpPROP"]["year_min_days"][0],
alltime["prcpPROP"]["year_min_days"][1][0] if len(alltime["prcpPROP"]["year_min_days"][1]) == 1 else len(alltime["prcpPROP"]["year_min_days"][1]),
round(mean(alltime["prcp"]),2) if len(alltime["prcp"]) > 0 else "--",
round(alltime["prcpPROP"]["year_max"][0],2),
alltime["prcpPROP"]["year_max"][1][0] if len(alltime["prcpPROP"]["year_max"][1]) == 1 else len(alltime["prcpPROP"]["year_max"][1]),
round(alltime["prcpPROP"]["year_min"][0],2),
alltime["prcpPROP"]["year_min"][1][0] if len(alltime["prcpPROP"]["year_min"][1]) == 1 else len(alltime["prcpPROP"]["year_min"][1]),
alltime["snowPROP"]["days"] if alltime["snowPROP"]["days"] > 0 else "--",
round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1) if alltime["snowPROP"]["days"] > 0 else "--",
alltime["snowPROP"]["year_max_days"][0],
alltime["snowPROP"]["year_max_days"][1][0] if len(alltime["snowPROP"]["year_max_days"][1]) == 1 else len(alltime["snowPROP"]["year_max_days"][1]),
round(mean(alltime["snow"]),1) if len(alltime["snow"]) > 0 else "--",
round(alltime["snowPROP"]["year_max"][0],2),
alltime["snowPROP"]["year_max"][1][0] if len(alltime["snowPROP"]["year_max"][1]) == 1 else len(alltime["snowPROP"]["year_max"][1])))
for c in climo30yrs:
#print(climo30yrs[c]["prcpPROP"]["days"],climo30yrs[c]["total_days"])
#print(climo30yrs[c]["snowPROP"]["days"],climo30yrs[c]["total_days"])
try:
print("{:^9} {:5}:{:>5}% {:>3}, {:^4} {:>3}, {:^4} {:^6.2f} {:>6.2f}, {:^4} {:>6.2f}, {:^4} | {:4}:{:>5}% {:>3}, {:^4} {:^6.1f} {:>5.1f}, {:^4} |".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
climo30yrs[c]["prcpPROP"]["days"],
round(100 * climo30yrs[c]["prcpPROP"]["days"] / climo30yrs[c]["total_days"],1),
climo30yrs[c]["prcpPROP"]["year_max_days"][0],
climo30yrs[c]["prcpPROP"]["year_max_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["year_max_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["year_max_days"][1]),
climo30yrs[c]["prcpPROP"]["year_min_days"][0],
climo30yrs[c]["prcpPROP"]["year_min_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["year_min_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["year_min_days"][1]),
round(mean(climo30yrs[c]["prcp"]),2),
round(climo30yrs[c]["prcpPROP"]["year_max"][0],2),
climo30yrs[c]["prcpPROP"]["year_max"][1][0] if len(climo30yrs[c]["prcpPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["year_max"][1]),
round(climo30yrs[c]["prcpPROP"]["year_min"][0],2),
climo30yrs[c]["prcpPROP"]["year_min"][1][0] if len(climo30yrs[c]["prcpPROP"]["year_min"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["year_min"][1]),
climo30yrs[c]["snowPROP"]["days"] if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
round(100 * climo30yrs[c]["snowPROP"]["days"] / climo30yrs[c]["total_days"],1) if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
climo30yrs[c]["snowPROP"]["year_max_days"][0],
climo30yrs[c]["snowPROP"]["year_max_days"][1][0] if len(climo30yrs[c]["snowPROP"]["year_max_days"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["year_max_days"][1]),
round(mean(climo30yrs[c]["snow"]),1) if len(climo30yrs[c]["snow"]) > 0 else "--",
round(climo30yrs[c]["snowPROP"]["year_max"][0],2),
climo30yrs[c]["snowPROP"]["year_max"][1][0] if len(climo30yrs[c]["snowPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["year_max"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("\nPart 2: Temperature Stats")
print("{:▒^9} {:▒^37} | {:▒^37} | {:▒^37}".format("Years","AVG TEMP","TMAX","TMIN"))
print("{:▒^9} {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12}".format("","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN"))
# Y TSTDV TMA TMX TMn TSTDV TMA TMX TMn TSTDV TMA TMX TMn
# "tempAVGlist": [],"tavgPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
print("{:-^9} {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12}".format("","","","","","","","","","","","",""))
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format("All Time",
round(pstdev(alltime["tempAVGlist"]),1),
round(mean(alltime["tempAVGlist_ind"]),1),
round(alltime["tavgPROP"]["year_max"][0],1),
alltime["tavgPROP"]["year_max"][1][0] if len(alltime["tavgPROP"]["year_max"][1]) == 1 else len(alltime["tavgPROP"]["year_max"][1]),
round(alltime["tavgPROP"]["year_min"][0],1),
alltime["tavgPROP"]["year_min"][1][0] if len(alltime["tavgPROP"]["year_min"][1]) == 1 else len(alltime["tavgPROP"]["year_min"][1]),
round(pstdev(alltime["tmax"]),1),
round(mean(alltime["tmax"]),1),
round(alltime["tmaxPROP"]["year_max"][0],1),
alltime["tmaxPROP"]["year_max"][1][0] if len(alltime["tmaxPROP"]["year_max"][1]) == 1 else len(alltime["tmaxPROP"]["year_max"][1]),
round(alltime["tmaxPROP"]["year_min"][0],1),
alltime["tmaxPROP"]["year_min"][1][0] if len(alltime["tmaxPROP"]["year_min"][1]) == 1 else len(alltime["tmaxPROP"]["year_min"][1]),
round(pstdev(alltime["tmin"]),1),
round(mean(alltime["tmin"]),1),
round(alltime["tminPROP"]["year_max"][0],1),
alltime["tminPROP"]["year_max"][1][0] if len(alltime["tminPROP"]["year_max"][1]) == 1 else len(alltime["tminPROP"]["year_max"][1]),
round(alltime["tminPROP"]["year_min"][0],1),
alltime["tminPROP"]["year_min"][1][0] if len(alltime["tminPROP"]["year_min"][1]) == 1 else len(alltime["tminPROP"]["year_min"][1])))
for c in climo30yrs:
try:
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
round(pstdev(climo30yrs[c]["tempAVGlist"]),1),
round(mean(climo30yrs[c]["tempAVGlist_ind"]),1),
round(climo30yrs[c]["tavgPROP"]["year_max"][0],1),
climo30yrs[c]["tavgPROP"]["year_max"][1][0] if len(climo30yrs[c]["tavgPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["year_max"][1]),
round(climo30yrs[c]["tavgPROP"]["year_min"][0],1),
climo30yrs[c]["tavgPROP"]["year_min"][1][0] if len(climo30yrs[c]["tavgPROP"]["year_min"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["year_min"][1]),
round(pstdev(climo30yrs[c]["tmax"]),1),
round(mean(climo30yrs[c]["tmax"]),1),
round(climo30yrs[c]["tmaxPROP"]["year_max"][0],1),
climo30yrs[c]["tmaxPROP"]["year_max"][1][0] if len(climo30yrs[c]["tmaxPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["year_max"][1]),
round(climo30yrs[c]["tmaxPROP"]["year_min"][0],1),
climo30yrs[c]["tmaxPROP"]["year_min"][1][0] if len(climo30yrs[c]["tmaxPROP"]["year_min"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["year_min"][1]),
round(pstdev(climo30yrs[c]["tmin"]),1),
round(mean(climo30yrs[c]["tmin"]),1),
round(climo30yrs[c]["tminPROP"]["year_max"][0],1),
climo30yrs[c]["tminPROP"]["year_max"][1][0] if len(climo30yrs[c]["tminPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["year_max"][1]),
round(climo30yrs[c]["tminPROP"]["year_min"][0],1),
climo30yrs[c]["tminPROP"]["year_min"][1][0] if len(climo30yrs[c]["tminPROP"]["year_min"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["year_min"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("")
if output == True:
newfn = "yearReport_Jan-Dec_" + str(climatology) + "YRclimo_" + str(increment) + "YRincr_" + clmt["station_name"] + ".csv"
with open(newfn,"w") as w:
headers = ["Assessed Period (Jan 1-Dec 31)","PRCP Days","PRCP % of days","PRCP stdev","PRCP AVG","SNOW Days","SNOW % of days","SNOW stdev","SNOW AVG","TAVG stdev","TAVG","TMAX stdev","TMAX","TMIN stdev","TMIN"]
# HEADER
for x in range(len(headers)):
if x != len(headers) - 1: w.write(headers[x]); w.write(",")
else: w.write(headers[x]); w.write("\n")
w.write("{}-{}".format(alltime["years"][0],alltime["years"][1])); w.write(",")
w.write("{}".format(alltime["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["prcp"]),1))); w.write(",")
w.write("{}".format(alltime["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tempAVGlist"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tempAVGlist_ind"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmax"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tmax"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmin"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tmin"]))); w.write("\n")
for x in climo30yrs:
w.write("{}-{}".format(climo30yrs[x]["years"][0],climo30yrs[x]["years"][1])); w.write(",")
w.write("{}".format(climo30yrs[x]["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["prcpPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{}".format(climo30yrs[x]["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["snowPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tempAVGlist"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tempAVGlist_ind"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tmax"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmin"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tmin"]))); w.write("\n")
print("*** csv output successful ***")
def seasonReport(season,climatology=30,increment=5,output=False):
"""Detailed Climatology Report for a Meteorological Season of interest.
Months included in Meteorological seasons are as follows:
Spring: 3,4,5
Summer: 6,7,8
Fall: 9,10,11
Winter: 12,1,2
Args:
season: Season being inquired about. Accepted entries are: <"spring",
"summer","fall"|"autumn","winter">
Keyword Args (optional):
climatology = 30: The span of years that averages are calculated
for (ie. '30 year climatology' or '30 year average'). This can be
modified but should always be > the increment.
increment = 5: Tells the script how often to assess/record successive
climatologies. The smaller this is, the longer the report takes
to generate. If kept at the default, for example, it would
capture the 1976-2005, 1981-2010, and 1986-2015 climatologies and
so forth.
output = False: If set to True, the script will output a CSV file of
its findings. This could be opened in a spreadsheet program for
further analysis
Examples:
seasonReport("spring") -> Returns a 30-yr, 5-yr incremented
climatological report for all Met. Spring's
on record
seasonReport("winter",climatology=15) -> Returns a 15-yr, 5-yr
incremented climatological report for all
Met. winters on record.
seasonReport("summer",climatology=10,increment=1,output=True) ->
Returns a 1-yr incremented, 10yr
climatology report for all Met. Summers on
record and outputs a CSV report.
"""
if season.lower() not in ["spring","summer","fall","autumn","winter"]: return print("* OOPS! {} is not a valid season. Try again!".format(season.capitalize()))
if season.lower() == "autumn": season = "fall"
season = season.lower()
valid_yrs = list(range(min([x for x in clmt.keys() if type(x) == int]),max([x for x in clmt.keys() if type(x) == int])+1))
#valid_yrs = [x for x in metclmt.keys() if type(x) == int]
valid_yrs.sort()
climo30yrs = {}
for x in range(1811,max(valid_yrs)+1,increment):
if x in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]) and x+climatology-1 in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]+1):
climo30yrs[(x,x+climatology-1)] = {"years":(x,x+climatology-1),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"season_max_days":[-1,[]],"season_min_days":[999,[]],"season_max":[-1,[]],"season_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"season_max_days":[-1,[]],"season_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"season_max":[-999,[]],"season_min":[999,[]]},
"tmax": [],"tmaxPROP":{"season_max":[-999,[]],"season_min":[999,[]]},
"tmin": [],"tminPROP":{"season_max":[-999,[]],"season_min":[999,[]]}}
alltime = {"years":(valid_yrs[0],valid_yrs[len(valid_yrs)-1]),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"season_max_days":[-1,[]],"season_min_days":[999,[]],"season_max":[-1,[]],"season_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"season_max_days":[-1,[]],"season_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"season_max":[-999,[]],"season_min":[999,[]]},
"tmax": [],"tmaxPROP":{"season_max":[-999,[]],"season_min":[999,[]]},
"tmin": [],"tminPROP":{"season_max":[-999,[]],"season_min":[999,[]]}}
print("*** PLEASE WAIT. This will take a few moments ***")
for y in valid_yrs:
# 'recordqty', 'prcp', 'prcpDAYS', 'prcpPROP', 'snow', 'snowDAYS', 'snowPROP', 'tempAVGlist', 'tmax', 'tmaxPROP', 'tmin', 'tminPROP'
alltime["total_days"] += metclmt[y][season]["recordqty"]
# PRCP
alltime["prcp"].append(sum(metclmt[y][season]["prcp"]))
alltime["prcpPROP"]["days"] += metclmt[y][season]["prcpDAYS"]
if metclmt[y][season]["prcpDAYS"] == alltime["prcpPROP"]["season_max_days"][0]: alltime["prcpPROP"]["season_max_days"][1].append(y)
elif metclmt[y][season]["prcpDAYS"] > alltime["prcpPROP"]["season_max_days"][0]:
alltime["prcpPROP"]["season_max_days"][0] = metclmt[y][season]["prcpDAYS"]
alltime["prcpPROP"]["season_max_days"][1] = []
alltime["prcpPROP"]["season_max_days"][1].append(y)
if sum(metclmt[y][season]["prcp"]) == alltime["prcpPROP"]["season_max"][0]: alltime["prcpPROP"]["season_max"][1].append(y)
elif sum(metclmt[y][season]["prcp"]) > alltime["prcpPROP"]["season_max"][0]:
alltime["prcpPROP"]["season_max"][0] = sum(metclmt[y][season]["prcp"])
alltime["prcpPROP"]["season_max"][1] = []
alltime["prcpPROP"]["season_max"][1].append(y)
if metclmt[y][season]["recordqty"] > excludeseason:
if metclmt[y][season]["prcpDAYS"] == alltime["prcpPROP"]["season_min_days"][0]: alltime["prcpPROP"]["season_min_days"][1].append(y)
elif metclmt[y][season]["prcpDAYS"] < alltime["prcpPROP"]["season_min_days"][0]:
alltime["prcpPROP"]["season_min_days"][0] = metclmt[y][season]["prcpDAYS"]
alltime["prcpPROP"]["season_min_days"][1] = []
alltime["prcpPROP"]["season_min_days"][1].append(y)
if sum(metclmt[y][season]["prcp"]) == alltime["prcpPROP"]["season_min"][0]: alltime["prcpPROP"]["season_min"][1].append(y)
elif sum(metclmt[y][season]["prcp"]) < alltime["prcpPROP"]["season_min"][0]:
alltime["prcpPROP"]["season_min"][0] = sum(metclmt[y][season]["prcp"])
alltime["prcpPROP"]["season_min"][1] = []
alltime["prcpPROP"]["season_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
climo30yrs[c]["prcp"].append(sum(metclmt[y][season]["prcp"]))
climo30yrs[c]["prcpPROP"]["days"] += metclmt[y][season]["prcpDAYS"]
climo30yrs[c]["total_days"] += metclmt[y][season]["recordqty"]
if metclmt[y][season]["recordqty"] > excludeseason:
if metclmt[y][season]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["season_max_days"][0]: climo30yrs[c]["prcpPROP"]["season_max_days"][1].append(y)
elif metclmt[y][season]["prcpDAYS"] > climo30yrs[c]["prcpPROP"]["season_max_days"][0]:
climo30yrs[c]["prcpPROP"]["season_max_days"][0] = metclmt[y][season]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["season_max_days"][1] = []
climo30yrs[c]["prcpPROP"]["season_max_days"][1].append(y)
if metclmt[y][season]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["season_min_days"][0]: climo30yrs[c]["prcpPROP"]["season_min_days"][1].append(y)
elif metclmt[y][season]["prcpDAYS"] < climo30yrs[c]["prcpPROP"]["season_min_days"][0]:
climo30yrs[c]["prcpPROP"]["season_min_days"][0] = metclmt[y][season]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["season_min_days"][1] = []
climo30yrs[c]["prcpPROP"]["season_min_days"][1].append(y)
if sum(metclmt[y][season]["prcp"]) == climo30yrs[c]["prcpPROP"]["season_max"][0]: climo30yrs[c]["prcpPROP"]["season_max"][1].append(y)
elif sum(metclmt[y][season]["prcp"]) > climo30yrs[c]["prcpPROP"]["season_max"][0]:
climo30yrs[c]["prcpPROP"]["season_max"][0] = sum(metclmt[y][season]["prcp"])
climo30yrs[c]["prcpPROP"]["season_max"][1] = []
climo30yrs[c]["prcpPROP"]["season_max"][1].append(y)
if sum(metclmt[y][season]["prcp"]) == climo30yrs[c]["prcpPROP"]["season_min"][0]: climo30yrs[c]["prcpPROP"]["season_min"][1].append(y)
elif sum(metclmt[y][season]["prcp"]) < climo30yrs[c]["prcpPROP"]["season_min"][0]:
climo30yrs[c]["prcpPROP"]["season_min"][0] = sum(metclmt[y][season]["prcp"])
climo30yrs[c]["prcpPROP"]["season_min"][1] = []
climo30yrs[c]["prcpPROP"]["season_min"][1].append(y)
# SNOW
alltime["snow"].append(sum(metclmt[y][season]["snow"]))
alltime["snowPROP"]["days"] += metclmt[y][season]["snowDAYS"]
if metclmt[y][season]["recordqty"] > excludeseason:
if metclmt[y][season]["snowDAYS"] == alltime["snowPROP"]["season_max_days"][0]: alltime["snowPROP"]["season_max_days"][1].append(y)
elif metclmt[y][season]["snowDAYS"] > alltime["snowPROP"]["season_max_days"][0]:
alltime["snowPROP"]["season_max_days"][0] = metclmt[y][season]["snowDAYS"]
alltime["snowPROP"]["season_max_days"][1] = []
alltime["snowPROP"]["season_max_days"][1].append(y)
if sum(metclmt[y][season]["snow"]) == alltime["snowPROP"]["season_max"][0]: alltime["snowPROP"]["season_max"][1].append(y)
elif sum(metclmt[y][season]["snow"]) > alltime["snowPROP"]["season_max"][0]:
alltime["snowPROP"]["season_max"][0] = sum(metclmt[y][season]["snow"])
alltime["snowPROP"]["season_max"][1] = []
alltime["snowPROP"]["season_max"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
climo30yrs[c]["snow"].append(sum(metclmt[y][season]["snow"]))
climo30yrs[c]["snowPROP"]["days"] += metclmt[y][season]["snowDAYS"]
if metclmt[y][season]["recordqty"] > excludeseason:
if metclmt[y][season]["snowDAYS"] == climo30yrs[c]["snowPROP"]["season_max_days"][0]: climo30yrs[c]["snowPROP"]["season_max_days"][1].append(y)
elif metclmt[y][season]["snowDAYS"] > climo30yrs[c]["snowPROP"]["season_max_days"][0]:
climo30yrs[c]["snowPROP"]["season_max_days"][0] = metclmt[y][season]["snowDAYS"]
climo30yrs[c]["snowPROP"]["season_max_days"][1] = []
climo30yrs[c]["snowPROP"]["season_max_days"][1].append(y)
if sum(metclmt[y][season]["snow"]) == climo30yrs[c]["snowPROP"]["season_max"][0]: climo30yrs[c]["snowPROP"]["season_max"][1].append(y)
elif sum(metclmt[y][season]["snow"]) > climo30yrs[c]["snowPROP"]["season_max"][0]:
climo30yrs[c]["snowPROP"]["season_max"][0] = sum(metclmt[y][season]["snow"])
climo30yrs[c]["snowPROP"]["season_max"][1] = []
climo30yrs[c]["snowPROP"]["season_max"][1].append(y)
# 'recordqty', 'prcp', 'prcpDAYS', 'prcpPROP', 'snow', 'snowDAYS', 'snowPROP', 'tempAVGlist', 'tmax', 'tmaxPROP', 'tmin', 'tminPROP'
# TAVG
for x in metclmt[y][season]["tempAVGlist"]: alltime["tempAVGlist_ind"].append(x)
if len(metclmt[y][season]["tempAVGlist"]) > excludeseason_tavg:
alltime["tempAVGlist"].append(mean(metclmt[y][season]["tempAVGlist"]))
if mean(metclmt[y][season]["tempAVGlist"]) == alltime["tavgPROP"]["season_max"][0]: alltime["tavgPROP"]["season_max"][1].append(y)
elif mean(metclmt[y][season]["tempAVGlist"]) > alltime["tavgPROP"]["season_max"][0]:
alltime["tavgPROP"]["season_max"][0] = mean(metclmt[y][season]["tempAVGlist"])
alltime["tavgPROP"]["season_max"][1] = []
alltime["tavgPROP"]["season_max"][1].append(y)
if mean(metclmt[y][season]["tempAVGlist"]) == alltime["tavgPROP"]["season_min"][0]: alltime["tavgPROP"]["season_min"][1].append(y)
elif mean(metclmt[y][season]["tempAVGlist"]) < alltime["tavgPROP"]["season_min"][0]:
alltime["tavgPROP"]["season_min"][0] = mean(metclmt[y][season]["tempAVGlist"])
alltime["tavgPROP"]["season_min"][1] = []
alltime["tavgPROP"]["season_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
for x in metclmt[y][season]["tempAVGlist"]:climo30yrs[c]["tempAVGlist_ind"].append(x)
if len(metclmt[y][season]["tempAVGlist"]) > excludeseason_tavg:
climo30yrs[c]["tempAVGlist"].append(mean(metclmt[y][season]["tempAVGlist"]))
if mean(metclmt[y][season]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["season_max"][0]: climo30yrs[c]["tavgPROP"]["season_max"][1].append(y)
elif mean(metclmt[y][season]["tempAVGlist"]) > climo30yrs[c]["tavgPROP"]["season_max"][0]:
climo30yrs[c]["tavgPROP"]["season_max"][0] = mean(metclmt[y][season]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["season_max"][1] = []
climo30yrs[c]["tavgPROP"]["season_max"][1].append(y)
if mean(metclmt[y][season]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["season_min"][0]: climo30yrs[c]["tavgPROP"]["season_min"][1].append(y)
elif mean(metclmt[y][season]["tempAVGlist"]) < climo30yrs[c]["tavgPROP"]["season_min"][0]:
climo30yrs[c]["tavgPROP"]["season_min"][0] = mean(metclmt[y][season]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["season_min"][1] = []
climo30yrs[c]["tavgPROP"]["season_min"][1].append(y)
# TMAX
for x in metclmt[y][season]["tmax"]: alltime["tmax"].append(x)
if len(metclmt[y][season]["tmax"]) > excludeseason:
if mean(metclmt[y][season]["tmax"]) == alltime["tmaxPROP"]["season_max"][0]: alltime["tmaxPROP"]["season_max"][1].append(y)
elif mean(metclmt[y][season]["tmax"]) > alltime["tmaxPROP"]["season_max"][0]:
alltime["tmaxPROP"]["season_max"][0] = mean(metclmt[y][season]["tmax"])
alltime["tmaxPROP"]["season_max"][1] = []
alltime["tmaxPROP"]["season_max"][1].append(y)
if mean(metclmt[y][season]["tmax"]) == alltime["tmaxPROP"]["season_min"][0]: alltime["tmaxPROP"]["season_min"][1].append(y)
elif mean(metclmt[y][season]["tmax"]) < alltime["tmaxPROP"]["season_min"][0]:
alltime["tmaxPROP"]["season_min"][0] = mean(metclmt[y][season]["tmax"])
alltime["tmaxPROP"]["season_min"][1] = []
alltime["tmaxPROP"]["season_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
for x in metclmt[y][season]["tmax"]: climo30yrs[c]["tmax"].append(x)
if len(metclmt[y][season]["tmax"]) > excludeseason:
if mean(metclmt[y][season]["tmax"]) == climo30yrs[c]["tmaxPROP"]["season_max"][0]: climo30yrs[c]["tmaxPROP"]["season_max"][1].append(y)
elif mean(metclmt[y][season]["tmax"]) > climo30yrs[c]["tmaxPROP"]["season_max"][0]:
climo30yrs[c]["tmaxPROP"]["season_max"][0] = mean(metclmt[y][season]["tmax"])
climo30yrs[c]["tmaxPROP"]["season_max"][1] = []
climo30yrs[c]["tmaxPROP"]["season_max"][1].append(y)
if mean(metclmt[y][season]["tmax"]) == climo30yrs[c]["tmaxPROP"]["season_min"][0]: climo30yrs[c]["tmaxPROP"]["season_min"][1].append(y)
elif mean(metclmt[y][season]["tmax"]) < climo30yrs[c]["tmaxPROP"]["season_min"][0]:
climo30yrs[c]["tmaxPROP"]["season_min"][0] = mean(metclmt[y][season]["tmax"])
climo30yrs[c]["tmaxPROP"]["season_min"][1] = []
climo30yrs[c]["tmaxPROP"]["season_min"][1].append(y)
# TMIN
for x in metclmt[y][season]["tmin"]: alltime["tmin"].append(x)
if len(metclmt[y][season]["tmin"]) > excludeseason:
if mean(metclmt[y][season]["tmin"]) == alltime["tminPROP"]["season_max"][0]: alltime["tminPROP"]["season_max"][1].append(y)
elif mean(metclmt[y][season]["tmin"]) > alltime["tminPROP"]["season_max"][0]:
alltime["tminPROP"]["season_max"][0] = mean(metclmt[y][season]["tmin"])
alltime["tminPROP"]["season_max"][1] = []
alltime["tminPROP"]["season_max"][1].append(y)
if mean(metclmt[y][season]["tmin"]) == alltime["tminPROP"]["season_min"][0]: alltime["tminPROP"]["season_min"][1].append(y)
elif mean(metclmt[y][season]["tmin"]) < alltime["tminPROP"]["season_min"][0]:
alltime["tminPROP"]["season_min"][0] = mean(metclmt[y][season]["tmin"])
alltime["tminPROP"]["season_min"][1] = []
alltime["tminPROP"]["season_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
for x in metclmt[y][season]["tmin"]: climo30yrs[c]["tmin"].append(x)
if len(metclmt[y][season]["tmin"]) > excludeseason:
if mean(metclmt[y][season]["tmin"]) == climo30yrs[c]["tminPROP"]["season_max"][0]: climo30yrs[c]["tminPROP"]["season_max"][1].append(y)
elif mean(metclmt[y][season]["tmin"]) > climo30yrs[c]["tminPROP"]["season_max"][0]:
climo30yrs[c]["tminPROP"]["season_max"][0] = mean(metclmt[y][season]["tmin"])
climo30yrs[c]["tminPROP"]["season_max"][1] = []
climo30yrs[c]["tminPROP"]["season_max"][1].append(y)
if mean(metclmt[y][season]["tmin"]) == climo30yrs[c]["tminPROP"]["season_min"][0]: climo30yrs[c]["tminPROP"]["season_min"][1].append(y)
elif mean(metclmt[y][season]["tmin"]) < climo30yrs[c]["tminPROP"]["season_min"][0]:
climo30yrs[c]["tminPROP"]["season_min"][0] = mean(metclmt[y][season]["tmin"])
climo30yrs[c]["tminPROP"]["season_min"][1] = []
climo30yrs[c]["tminPROP"]["season_min"][1].append(y)
# PRINT REPORT
print("---------------------------------------------------")
print("Climatology Report for Meteorological {}".format(season.capitalize()))
print("City: {}, {}".format(metclmt["station"],metclmt["station_name"]))
print("{}-{}; {}-Year Incremented {}-Year Climatologies".format(min(valid_yrs),max(valid_yrs),increment,climatology))
print("---------------------------------------------------")
print("Part 1: Precipitation Stats")
print("{:▒^9} {:▒^12} {:▒^9} {:▒^9} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^9} {:▒^6} {:▒^11} |".format("Years","PRCP","PRCP","PRCP","PRCP","PRCP","PRCP","SNOW","SNOW","SNOW","SNOW"))
print("{:▒^9} {:▒^12} {:▒^9} {:▒^9} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^9} {:▒^6} {:▒^11} |".format("","DAYS","DAYS MAX","DAYS MIN","AVG", "MAX","MIN","DAYS","DAYS MAX","AVG", "MAX"))
# Y PD PDx PDn PA PM Pmin SD SDx SA SM
print("{:-^9} {:-^12} {:-^9} {:-^9} {:-^6} {:-^12} {:-^12} | {:-^11} {:-^9} {:-^6} {:-^11} |".format("","","","","","","","","","",""))
print("{:^9} {:5}:{:>5}% {:>3}, {:^4} {:>3}, {:^4} {:^6.2f} {:>6.2f}, {:^4} {:>6.2f}, {:^4} | {:4}:{:>5}% {:>3}, {:^4} {:^6.1f} {:>5.1f}, {:^4} |".format("All Time",
alltime["prcpPROP"]["days"],
round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1),
alltime["prcpPROP"]["season_max_days"][0],
alltime["prcpPROP"]["season_max_days"][1][0] if len(alltime["prcpPROP"]["season_max_days"][1]) == 1 else len(alltime["prcpPROP"]["season_max_days"][1]),
alltime["prcpPROP"]["season_min_days"][0],
alltime["prcpPROP"]["season_min_days"][1][0] if len(alltime["prcpPROP"]["season_min_days"][1]) == 1 else len(alltime["prcpPROP"]["season_min_days"][1]),
round(mean(alltime["prcp"]),2) if len(alltime["prcp"]) > 0 else "--",
round(alltime["prcpPROP"]["season_max"][0],2),
alltime["prcpPROP"]["season_max"][1][0] if len(alltime["prcpPROP"]["season_max"][1]) == 1 else len(alltime["prcpPROP"]["season_max"][1]),
round(alltime["prcpPROP"]["season_min"][0],2),
alltime["prcpPROP"]["season_min"][1][0] if len(alltime["prcpPROP"]["season_min"][1]) == 1 else len(alltime["prcpPROP"]["season_min"][1]),
alltime["snowPROP"]["days"] if alltime["snowPROP"]["days"] > 0 else "--",
round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1) if alltime["snowPROP"]["days"] > 0 else "--",
alltime["snowPROP"]["season_max_days"][0],
alltime["snowPROP"]["season_max_days"][1][0] if len(alltime["snowPROP"]["season_max_days"][1]) == 1 else len(alltime["snowPROP"]["season_max_days"][1]),
round(mean(alltime["snow"]),1) if len(alltime["snow"]) > 0 else "--",
round(alltime["snowPROP"]["season_max"][0],2),
alltime["snowPROP"]["season_max"][1][0] if len(alltime["snowPROP"]["season_max"][1]) == 1 else len(alltime["snowPROP"]["season_max"][1])))
for c in climo30yrs:
#print(climo30yrs[c]["prcpPROP"]["days"],climo30yrs[c]["total_days"])
#print(climo30yrs[c]["snowPROP"]["days"],climo30yrs[c]["total_days"])
try:
print("{:^9} {:5}:{:>5}% {:>3}, {:^4} {:>3}, {:^4} {:^6.2f} {:>6.2f}, {:^4} {:>6.2f}, {:^4} | {:4}:{:>5}% {:>3}, {:^4} {:^6.1f} {:>5.1f}, {:^4} |".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
climo30yrs[c]["prcpPROP"]["days"],
round(100 * climo30yrs[c]["prcpPROP"]["days"] / climo30yrs[c]["total_days"],1),
climo30yrs[c]["prcpPROP"]["season_max_days"][0],
climo30yrs[c]["prcpPROP"]["season_max_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["season_max_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["season_max_days"][1]),
climo30yrs[c]["prcpPROP"]["season_min_days"][0],
climo30yrs[c]["prcpPROP"]["season_min_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["season_min_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["season_min_days"][1]),
round(mean(climo30yrs[c]["prcp"]),2),
round(climo30yrs[c]["prcpPROP"]["season_max"][0],2),
climo30yrs[c]["prcpPROP"]["season_max"][1][0] if len(climo30yrs[c]["prcpPROP"]["season_max"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["season_max"][1]),
round(climo30yrs[c]["prcpPROP"]["season_min"][0],2),
climo30yrs[c]["prcpPROP"]["season_min"][1][0] if len(climo30yrs[c]["prcpPROP"]["season_min"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["season_min"][1]),
climo30yrs[c]["snowPROP"]["days"] if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
round(100 * climo30yrs[c]["snowPROP"]["days"] / climo30yrs[c]["total_days"],1) if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
climo30yrs[c]["snowPROP"]["season_max_days"][0],
climo30yrs[c]["snowPROP"]["season_max_days"][1][0] if len(climo30yrs[c]["snowPROP"]["season_max_days"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["season_max_days"][1]),
round(mean(climo30yrs[c]["snow"]),1) if len(climo30yrs[c]["snow"]) > 0 else "--",
round(climo30yrs[c]["snowPROP"]["season_max"][0],2),
climo30yrs[c]["snowPROP"]["season_max"][1][0] if len(climo30yrs[c]["snowPROP"]["season_max"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["season_max"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("\nPart 2: Temperature Stats")
print("{:▒^9} {:▒^37} | {:▒^37} | {:▒^37}".format("Years","AVG TEMP","TMAX","TMIN"))
print("{:▒^9} {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12}".format("","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN"))
# Y TSTDV TMA TMX TMn TSTDV TMA TMX TMn TSTDV TMA TMX TMn
# "tempAVGlist": [],"tavgPROP":{"season_max":[-999,[]],"season_min":[999,[]]},
print("{:-^9} {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12}".format("","","","","","","","","","","","",""))
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format("All Time",
round(pstdev(alltime["tempAVGlist"]),1),
round(mean(alltime["tempAVGlist_ind"]),1),
round(alltime["tavgPROP"]["season_max"][0],1),
alltime["tavgPROP"]["season_max"][1][0] if len(alltime["tavgPROP"]["season_max"][1]) == 1 else len(alltime["tavgPROP"]["season_max"][1]),
round(alltime["tavgPROP"]["season_min"][0],1),
alltime["tavgPROP"]["season_min"][1][0] if len(alltime["tavgPROP"]["season_min"][1]) == 1 else len(alltime["tavgPROP"]["season_min"][1]),
round(pstdev(alltime["tmax"]),1),
round(mean(alltime["tmax"]),1),
round(alltime["tmaxPROP"]["season_max"][0],1),
alltime["tmaxPROP"]["season_max"][1][0] if len(alltime["tmaxPROP"]["season_max"][1]) == 1 else len(alltime["tmaxPROP"]["season_max"][1]),
round(alltime["tmaxPROP"]["season_min"][0],1),
alltime["tmaxPROP"]["season_min"][1][0] if len(alltime["tmaxPROP"]["season_min"][1]) == 1 else len(alltime["tmaxPROP"]["season_min"][1]),
round(pstdev(alltime["tmin"]),1),
round(mean(alltime["tmin"]),1),
round(alltime["tminPROP"]["season_max"][0],1),
alltime["tminPROP"]["season_max"][1][0] if len(alltime["tminPROP"]["season_max"][1]) == 1 else len(alltime["tminPROP"]["season_max"][1]),
round(alltime["tminPROP"]["season_min"][0],1),
alltime["tminPROP"]["season_min"][1][0] if len(alltime["tminPROP"]["season_min"][1]) == 1 else len(alltime["tminPROP"]["season_min"][1])))
for c in climo30yrs:
try:
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
round(pstdev(climo30yrs[c]["tempAVGlist"]),1),
round(mean(climo30yrs[c]["tempAVGlist_ind"]),1),
round(climo30yrs[c]["tavgPROP"]["season_max"][0],1),
climo30yrs[c]["tavgPROP"]["season_max"][1][0] if len(climo30yrs[c]["tavgPROP"]["season_max"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["season_max"][1]),
round(climo30yrs[c]["tavgPROP"]["season_min"][0],1),
climo30yrs[c]["tavgPROP"]["season_min"][1][0] if len(climo30yrs[c]["tavgPROP"]["season_min"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["season_min"][1]),
round(pstdev(climo30yrs[c]["tmax"]),1),
round(mean(climo30yrs[c]["tmax"]),1),
round(climo30yrs[c]["tmaxPROP"]["season_max"][0],1),
climo30yrs[c]["tmaxPROP"]["season_max"][1][0] if len(climo30yrs[c]["tmaxPROP"]["season_max"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["season_max"][1]),
round(climo30yrs[c]["tmaxPROP"]["season_min"][0],1),
climo30yrs[c]["tmaxPROP"]["season_min"][1][0] if len(climo30yrs[c]["tmaxPROP"]["season_min"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["season_min"][1]),
round(pstdev(climo30yrs[c]["tmin"]),1),
round(mean(climo30yrs[c]["tmin"]),1),
round(climo30yrs[c]["tminPROP"]["season_max"][0],1),
climo30yrs[c]["tminPROP"]["season_max"][1][0] if len(climo30yrs[c]["tminPROP"]["season_max"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["season_max"][1]),
round(climo30yrs[c]["tminPROP"]["season_min"][0],1),
climo30yrs[c]["tminPROP"]["season_min"][1][0] if len(climo30yrs[c]["tminPROP"]["season_min"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["season_min"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("")
if output == True:
newfn = "seasonReport_met" + season.lower().capitalize() + "_" + str(climatology) + "YRclimo_" + str(increment) + "YRincr_" + clmt["station_name"] + ".csv"
with open(newfn,"w") as w:
headers = ["Assessed Period (Meteorological {})".format(season.lower().capitalize()),"PRCP Days","PRCP % of days","PRCP stdev","PRCP AVG","SNOW Days","SNOW % of days","SNOW stdev","SNOW AVG","TAVG stdev","TAVG","TMAX stdev","TMAX","TMIN stdev","TMIN"]
# HEADER
for x in range(len(headers)):
if x != len(headers) - 1: w.write(headers[x]); w.write(",")
else: w.write(headers[x]); w.write("\n")
w.write("{}-{}".format(alltime["years"][0],alltime["years"][1])); w.write(",")
w.write("{}".format(alltime["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["prcp"]),1))); w.write(",")
w.write("{}".format(alltime["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tempAVGlist"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tempAVGlist_ind"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmax"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tmax"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmin"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tmin"]))); w.write("\n")
for x in climo30yrs:
w.write("{}-{}".format(climo30yrs[x]["years"][0],climo30yrs[x]["years"][1])); w.write(",")
w.write("{}".format(climo30yrs[x]["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["prcpPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{}".format(climo30yrs[x]["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["snowPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tempAVGlist"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tempAVGlist_ind"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tmax"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmin"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tmin"]))); w.write("\n")
print("*** csv output successful ***")
def metYearReport(climatology=30,increment=5,output=False):
"""Detailed Climatological Report all Meteorological years on record. A
meteorological year goes from March to February of the following year.
* no required arguments *
Keyword Args (optional):
climatology = 30: The span of years that averages are calculated
for (ie. '30 year climatology' or '30 year average'). This can be
modified but should always be > the increment.
increment = 5: Tells the script how often to assess/record successive
climatologies. The smaller this is, the longer the report takes
to generate. If kept at the default, for example, it would
capture the 1976-2005, 1981-2010, and 1986-2015 climatologies and
so forth.
output = False: If set to True, the script will output a CSV file of
its findings. This could be opened in a spreadsheet program for
further analysis
Examples:
metYearReport() -> Returns a 30-yr, 5-yr incremented climatological
report for all meteorological years on record
metYearReport(climatology=10) -> Returns a 10-yr, 5-yr incremented
climatological report for all Meteorological years.
metYearReport(climatology=10,increment=4,output=True) -> Returns a
4-yr incremented, 10yr climatology report for all years and
outputs a CSV.
"""
valid_yrs = list(range(min([x for x in clmt.keys() if type(x) == int]),max([x for x in clmt.keys() if type(x) == int])+1))
#valid_yrs = [x for x in metclmt.keys() if type(x) == int]
valid_yrs.sort()
climo30yrs = {}
for x in range(1811,max(valid_yrs)+1,increment):
if x in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]) and x+climatology-1 in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]+1):
climo30yrs[(x,x+climatology-1)] = {"years":(x,x+climatology-1),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"year_max_days":[-1,[]],"year_min_days":[999,[]],"year_max":[-1,[]],"year_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"year_max_days":[-1,[]],"year_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
"tmax": [],"tmaxPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
"tmin": [],"tminPROP":{"year_max":[-999,[]],"year_min":[999,[]]}}
alltime = {"years":(valid_yrs[0],valid_yrs[len(valid_yrs)-1]),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"year_max_days":[-1,[]],"year_min_days":[999,[]],"year_max":[-1,[]],"year_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"year_max_days":[-1,[]],"year_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
"tmax": [],"tmaxPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
"tmin": [],"tminPROP":{"year_max":[-999,[]],"year_min":[999,[]]}}
print("*** PLEASE WAIT. This will take a few moments ***")
for y in valid_yrs:
# 'recordqty', 'prcp', 'prcpDAYS', 'prcpPROP', 'snow', 'snowDAYS', 'snowPROP', 'tempAVGlist', 'tmax', 'tmaxPROP', 'tmin', 'tminPROP'
alltime["total_days"] += metclmt[y]["recordqty"]
# PRCP
alltime["prcp"].append(sum(metclmt[y]["prcp"]))
alltime["prcpPROP"]["days"] += metclmt[y]["prcpDAYS"]
if metclmt[y]["prcpDAYS"] == alltime["prcpPROP"]["year_max_days"][0]: alltime["prcpPROP"]["year_max_days"][1].append(y)
elif metclmt[y]["prcpDAYS"] > alltime["prcpPROP"]["year_max_days"][0]:
alltime["prcpPROP"]["year_max_days"][0] = metclmt[y]["prcpDAYS"]
alltime["prcpPROP"]["year_max_days"][1] = []
alltime["prcpPROP"]["year_max_days"][1].append(y)
if sum(metclmt[y]["prcp"]) == alltime["prcpPROP"]["year_max"][0]: alltime["prcpPROP"]["year_max"][1].append(y)
elif sum(metclmt[y]["prcp"]) > alltime["prcpPROP"]["year_max"][0]:
alltime["prcpPROP"]["year_max"][0] = sum(metclmt[y]["prcp"])
alltime["prcpPROP"]["year_max"][1] = []
alltime["prcpPROP"]["year_max"][1].append(y)
if metclmt[y]["recordqty"] > excludeyear:
if metclmt[y]["prcpDAYS"] == alltime["prcpPROP"]["year_min_days"][0]: alltime["prcpPROP"]["year_min_days"][1].append(y)
elif metclmt[y]["prcpDAYS"] < alltime["prcpPROP"]["year_min_days"][0]:
alltime["prcpPROP"]["year_min_days"][0] = metclmt[y]["prcpDAYS"]
alltime["prcpPROP"]["year_min_days"][1] = []
alltime["prcpPROP"]["year_min_days"][1].append(y)
if sum(metclmt[y]["prcp"]) == alltime["prcpPROP"]["year_min"][0]: alltime["prcpPROP"]["year_min"][1].append(y)
elif sum(metclmt[y]["prcp"]) < alltime["prcpPROP"]["year_min"][0]:
alltime["prcpPROP"]["year_min"][0] = sum(metclmt[y]["prcp"])
alltime["prcpPROP"]["year_min"][1] = []
alltime["prcpPROP"]["year_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
climo30yrs[c]["prcp"].append(sum(metclmt[y]["prcp"]))
climo30yrs[c]["prcpPROP"]["days"] += metclmt[y]["prcpDAYS"]
climo30yrs[c]["total_days"] += metclmt[y]["recordqty"]
if metclmt[y]["recordqty"] > excludeyear:
if metclmt[y]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["year_max_days"][0]: climo30yrs[c]["prcpPROP"]["year_max_days"][1].append(y)
elif metclmt[y]["prcpDAYS"] > climo30yrs[c]["prcpPROP"]["year_max_days"][0]:
climo30yrs[c]["prcpPROP"]["year_max_days"][0] = metclmt[y]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["year_max_days"][1] = []
climo30yrs[c]["prcpPROP"]["year_max_days"][1].append(y)
if metclmt[y]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["year_min_days"][0]: climo30yrs[c]["prcpPROP"]["year_min_days"][1].append(y)
elif metclmt[y]["prcpDAYS"] < climo30yrs[c]["prcpPROP"]["year_min_days"][0]:
climo30yrs[c]["prcpPROP"]["year_min_days"][0] = metclmt[y]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["year_min_days"][1] = []
climo30yrs[c]["prcpPROP"]["year_min_days"][1].append(y)
if sum(metclmt[y]["prcp"]) == climo30yrs[c]["prcpPROP"]["year_max"][0]: climo30yrs[c]["prcpPROP"]["year_max"][1].append(y)
elif sum(metclmt[y]["prcp"]) > climo30yrs[c]["prcpPROP"]["year_max"][0]:
climo30yrs[c]["prcpPROP"]["year_max"][0] = sum(metclmt[y]["prcp"])
climo30yrs[c]["prcpPROP"]["year_max"][1] = []
climo30yrs[c]["prcpPROP"]["year_max"][1].append(y)
if sum(metclmt[y]["prcp"]) == climo30yrs[c]["prcpPROP"]["year_min"][0]: climo30yrs[c]["prcpPROP"]["year_min"][1].append(y)
elif sum(metclmt[y]["prcp"]) < climo30yrs[c]["prcpPROP"]["year_min"][0]:
climo30yrs[c]["prcpPROP"]["year_min"][0] = sum(metclmt[y]["prcp"])
climo30yrs[c]["prcpPROP"]["year_min"][1] = []
climo30yrs[c]["prcpPROP"]["year_min"][1].append(y)
# SNOW
alltime["snow"].append(sum(metclmt[y]["snow"]))
alltime["snowPROP"]["days"] += metclmt[y]["snowDAYS"]
if metclmt[y]["recordqty"] > excludeyear:
if metclmt[y]["snowDAYS"] == alltime["snowPROP"]["year_max_days"][0]: alltime["snowPROP"]["year_max_days"][1].append(y)
elif metclmt[y]["snowDAYS"] > alltime["snowPROP"]["year_max_days"][0]:
alltime["snowPROP"]["year_max_days"][0] = metclmt[y]["snowDAYS"]
alltime["snowPROP"]["year_max_days"][1] = []
alltime["snowPROP"]["year_max_days"][1].append(y)
if sum(metclmt[y]["snow"]) == alltime["snowPROP"]["year_max"][0]: alltime["snowPROP"]["year_max"][1].append(y)
elif sum(metclmt[y]["snow"]) > alltime["snowPROP"]["year_max"][0]:
alltime["snowPROP"]["year_max"][0] = sum(metclmt[y]["snow"])
alltime["snowPROP"]["year_max"][1] = []
alltime["snowPROP"]["year_max"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
climo30yrs[c]["snow"].append(sum(metclmt[y]["snow"]))
climo30yrs[c]["snowPROP"]["days"] += metclmt[y]["snowDAYS"]
if metclmt[y]["recordqty"] > excludeyear:
if metclmt[y]["snowDAYS"] == climo30yrs[c]["snowPROP"]["year_max_days"][0]: climo30yrs[c]["snowPROP"]["year_max_days"][1].append(y)
elif metclmt[y]["snowDAYS"] > climo30yrs[c]["snowPROP"]["year_max_days"][0]:
climo30yrs[c]["snowPROP"]["year_max_days"][0] = metclmt[y]["snowDAYS"]
climo30yrs[c]["snowPROP"]["year_max_days"][1] = []
climo30yrs[c]["snowPROP"]["year_max_days"][1].append(y)
if sum(metclmt[y]["snow"]) == climo30yrs[c]["snowPROP"]["year_max"][0]: climo30yrs[c]["snowPROP"]["year_max"][1].append(y)
elif sum(metclmt[y]["snow"]) > climo30yrs[c]["snowPROP"]["year_max"][0]:
climo30yrs[c]["snowPROP"]["year_max"][0] = sum(metclmt[y]["snow"])
climo30yrs[c]["snowPROP"]["year_max"][1] = []
climo30yrs[c]["snowPROP"]["year_max"][1].append(y)
# 'recordqty', 'prcp', 'prcpDAYS', 'prcpPROP', 'snow', 'snowDAYS', 'snowPROP', 'tempAVGlist', 'tmax', 'tmaxPROP', 'tmin', 'tminPROP'
# TAVG
for x in metclmt[y]["tempAVGlist"]: alltime["tempAVGlist_ind"].append(x)
if len(metclmt[y]["tempAVGlist"]) > excludeyear_tavg:
alltime["tempAVGlist"].append(mean(metclmt[y]["tempAVGlist"]))
if mean(metclmt[y]["tempAVGlist"]) == alltime["tavgPROP"]["year_max"][0]: alltime["tavgPROP"]["year_max"][1].append(y)
elif mean(metclmt[y]["tempAVGlist"]) > alltime["tavgPROP"]["year_max"][0]:
alltime["tavgPROP"]["year_max"][0] = mean(metclmt[y]["tempAVGlist"])
alltime["tavgPROP"]["year_max"][1] = []
alltime["tavgPROP"]["year_max"][1].append(y)
if mean(metclmt[y]["tempAVGlist"]) == alltime["tavgPROP"]["year_min"][0]: alltime["tavgPROP"]["year_min"][1].append(y)
elif mean(metclmt[y]["tempAVGlist"]) < alltime["tavgPROP"]["year_min"][0]:
alltime["tavgPROP"]["year_min"][0] = mean(metclmt[y]["tempAVGlist"])
alltime["tavgPROP"]["year_min"][1] = []
alltime["tavgPROP"]["year_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
for x in metclmt[y]["tempAVGlist"]:climo30yrs[c]["tempAVGlist_ind"].append(x)
if len(metclmt[y]["tempAVGlist"]) > excludeyear_tavg:
climo30yrs[c]["tempAVGlist"].append(mean(metclmt[y]["tempAVGlist"]))
if mean(metclmt[y]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["year_max"][0]: climo30yrs[c]["tavgPROP"]["year_max"][1].append(y)
elif mean(metclmt[y]["tempAVGlist"]) > climo30yrs[c]["tavgPROP"]["year_max"][0]:
climo30yrs[c]["tavgPROP"]["year_max"][0] = mean(metclmt[y]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["year_max"][1] = []
climo30yrs[c]["tavgPROP"]["year_max"][1].append(y)
if mean(metclmt[y]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["year_min"][0]: climo30yrs[c]["tavgPROP"]["year_min"][1].append(y)
elif mean(metclmt[y]["tempAVGlist"]) < climo30yrs[c]["tavgPROP"]["year_min"][0]:
climo30yrs[c]["tavgPROP"]["year_min"][0] = mean(metclmt[y]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["year_min"][1] = []
climo30yrs[c]["tavgPROP"]["year_min"][1].append(y)
# TMAX
for x in metclmt[y]["tmax"]: alltime["tmax"].append(x)
if len(metclmt[y]["tmax"]) > excludeyear:
if mean(metclmt[y]["tmax"]) == alltime["tmaxPROP"]["year_max"][0]: alltime["tmaxPROP"]["year_max"][1].append(y)
elif mean(metclmt[y]["tmax"]) > alltime["tmaxPROP"]["year_max"][0]:
alltime["tmaxPROP"]["year_max"][0] = mean(metclmt[y]["tmax"])
alltime["tmaxPROP"]["year_max"][1] = []
alltime["tmaxPROP"]["year_max"][1].append(y)
if mean(metclmt[y]["tmax"]) == alltime["tmaxPROP"]["year_min"][0]: alltime["tmaxPROP"]["year_min"][1].append(y)
elif mean(metclmt[y]["tmax"]) < alltime["tmaxPROP"]["year_min"][0]:
alltime["tmaxPROP"]["year_min"][0] = mean(metclmt[y]["tmax"])
alltime["tmaxPROP"]["year_min"][1] = []
alltime["tmaxPROP"]["year_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
for x in metclmt[y]["tmax"]: climo30yrs[c]["tmax"].append(x)
if len(metclmt[y]["tmax"]) > excludeyear:
if mean(metclmt[y]["tmax"]) == climo30yrs[c]["tmaxPROP"]["year_max"][0]: climo30yrs[c]["tmaxPROP"]["year_max"][1].append(y)
elif mean(metclmt[y]["tmax"]) > climo30yrs[c]["tmaxPROP"]["year_max"][0]:
climo30yrs[c]["tmaxPROP"]["year_max"][0] = mean(metclmt[y]["tmax"])
climo30yrs[c]["tmaxPROP"]["year_max"][1] = []
climo30yrs[c]["tmaxPROP"]["year_max"][1].append(y)
if mean(metclmt[y]["tmax"]) == climo30yrs[c]["tmaxPROP"]["year_min"][0]: climo30yrs[c]["tmaxPROP"]["year_min"][1].append(y)
elif mean(metclmt[y]["tmax"]) < climo30yrs[c]["tmaxPROP"]["year_min"][0]:
climo30yrs[c]["tmaxPROP"]["year_min"][0] = mean(metclmt[y]["tmax"])
climo30yrs[c]["tmaxPROP"]["year_min"][1] = []
climo30yrs[c]["tmaxPROP"]["year_min"][1].append(y)
# TMIN
for x in metclmt[y]["tmin"]: alltime["tmin"].append(x)
if len(metclmt[y]["tmin"]) > excludeyear:
if mean(metclmt[y]["tmin"]) == alltime["tminPROP"]["year_max"][0]: alltime["tminPROP"]["year_max"][1].append(y)
elif mean(metclmt[y]["tmin"]) > alltime["tminPROP"]["year_max"][0]:
alltime["tminPROP"]["year_max"][0] = mean(metclmt[y]["tmin"])
alltime["tminPROP"]["year_max"][1] = []
alltime["tminPROP"]["year_max"][1].append(y)
if mean(metclmt[y]["tmin"]) == alltime["tminPROP"]["year_min"][0]: alltime["tminPROP"]["year_min"][1].append(y)
elif mean(metclmt[y]["tmin"]) < alltime["tminPROP"]["year_min"][0]:
alltime["tminPROP"]["year_min"][0] = mean(metclmt[y]["tmin"])
alltime["tminPROP"]["year_min"][1] = []
alltime["tminPROP"]["year_min"][1].append(y)
for c in climo30yrs:
if y >= c[0] and y <= c[1] and c[0] >= min(YR for YR in metclmt if type(YR) == int) and c[1] <= max(YR for YR in metclmt if type(YR) == int):
for x in metclmt[y]["tmin"]: climo30yrs[c]["tmin"].append(x)
if len(metclmt[y]["tmin"]) > excludeyear:
if mean(metclmt[y]["tmin"]) == climo30yrs[c]["tminPROP"]["year_max"][0]: climo30yrs[c]["tminPROP"]["year_max"][1].append(y)
elif mean(metclmt[y]["tmin"]) > climo30yrs[c]["tminPROP"]["year_max"][0]:
climo30yrs[c]["tminPROP"]["year_max"][0] = mean(metclmt[y]["tmin"])
climo30yrs[c]["tminPROP"]["year_max"][1] = []
climo30yrs[c]["tminPROP"]["year_max"][1].append(y)
if mean(metclmt[y]["tmin"]) == climo30yrs[c]["tminPROP"]["year_min"][0]: climo30yrs[c]["tminPROP"]["year_min"][1].append(y)
elif mean(metclmt[y]["tmin"]) < climo30yrs[c]["tminPROP"]["year_min"][0]:
climo30yrs[c]["tminPROP"]["year_min"][0] = mean(metclmt[y]["tmin"])
climo30yrs[c]["tminPROP"]["year_min"][1] = []
climo30yrs[c]["tminPROP"]["year_min"][1].append(y)
# PRINT REPORT
print("---------------------------------------------------")
print("Climatology Report for All Meteorological Years on Record")
print("City: {}, {}".format(metclmt["station"],metclmt["station_name"]))
print("{}-{}; {}-Year Incremented {}-Year Climatologies".format(min(valid_yrs),max(valid_yrs),increment,climatology))
print("---------------------------------------------------")
print("Part 1: Precipitation Stats")
print("{:▒^9} {:▒^12} {:▒^9} {:▒^9} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^9} {:▒^6} {:▒^11} |".format("Years","PRCP","PRCP","PRCP","PRCP","PRCP","PRCP","SNOW","SNOW","SNOW","SNOW"))
print("{:▒^9} {:▒^12} {:▒^9} {:▒^9} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^9} {:▒^6} {:▒^11} |".format("","DAYS","DAYS MAX","DAYS MIN","AVG", "MAX","MIN","DAYS","DAYS MAX","AVG", "MAX"))
# Y PD PDx PDn PA PM Pmin SD SDx SA SM
print("{:-^9} {:-^12} {:-^9} {:-^9} {:-^6} {:-^12} {:-^12} | {:-^11} {:-^9} {:-^6} {:-^11} |".format("","","","","","","","","","",""))
print("{:^9} {:5}:{:>5}% {:>3}, {:^4} {:>3}, {:^4} {:^6.2f} {:>6.2f}, {:^4} {:>6.2f}, {:^4} | {:4}:{:>5}% {:>3}, {:^4} {:^6.1f} {:>5.1f}, {:^4} |".format("All Time",
alltime["prcpPROP"]["days"],
round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1),
alltime["prcpPROP"]["year_max_days"][0],
alltime["prcpPROP"]["year_max_days"][1][0] if len(alltime["prcpPROP"]["year_max_days"][1]) == 1 else len(alltime["prcpPROP"]["year_max_days"][1]),
alltime["prcpPROP"]["year_min_days"][0],
alltime["prcpPROP"]["year_min_days"][1][0] if len(alltime["prcpPROP"]["year_min_days"][1]) == 1 else len(alltime["prcpPROP"]["year_min_days"][1]),
round(mean(alltime["prcp"]),2) if len(alltime["prcp"]) > 0 else "--",
round(alltime["prcpPROP"]["year_max"][0],2),
alltime["prcpPROP"]["year_max"][1][0] if len(alltime["prcpPROP"]["year_max"][1]) == 1 else len(alltime["prcpPROP"]["year_max"][1]),
round(alltime["prcpPROP"]["year_min"][0],2),
alltime["prcpPROP"]["year_min"][1][0] if len(alltime["prcpPROP"]["year_min"][1]) == 1 else len(alltime["prcpPROP"]["year_min"][1]),
alltime["snowPROP"]["days"] if alltime["snowPROP"]["days"] > 0 else "--",
round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1) if alltime["snowPROP"]["days"] > 0 else "--",
alltime["snowPROP"]["year_max_days"][0],
alltime["snowPROP"]["year_max_days"][1][0] if len(alltime["snowPROP"]["year_max_days"][1]) == 1 else len(alltime["snowPROP"]["year_max_days"][1]),
round(mean(alltime["snow"]),1) if len(alltime["snow"]) > 0 else "--",
round(alltime["snowPROP"]["year_max"][0],2),
alltime["snowPROP"]["year_max"][1][0] if len(alltime["snowPROP"]["year_max"][1]) == 1 else len(alltime["snowPROP"]["year_max"][1])))
for c in climo30yrs:
#print(climo30yrs[c]["prcpPROP"]["days"],climo30yrs[c]["total_days"])
#print(climo30yrs[c]["snowPROP"]["days"],climo30yrs[c]["total_days"])
try:
print("{:^9} {:5}:{:>5}% {:>3}, {:^4} {:>3}, {:^4} {:^6.2f} {:>6.2f}, {:^4} {:>6.2f}, {:^4} | {:4}:{:>5}% {:>3}, {:^4} {:^6.1f} {:>5.1f}, {:^4} |".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
climo30yrs[c]["prcpPROP"]["days"],
round(100 * climo30yrs[c]["prcpPROP"]["days"] / climo30yrs[c]["total_days"],1),
climo30yrs[c]["prcpPROP"]["year_max_days"][0],
climo30yrs[c]["prcpPROP"]["year_max_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["year_max_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["year_max_days"][1]),
climo30yrs[c]["prcpPROP"]["year_min_days"][0],
climo30yrs[c]["prcpPROP"]["year_min_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["year_min_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["year_min_days"][1]),
round(mean(climo30yrs[c]["prcp"]),2),
round(climo30yrs[c]["prcpPROP"]["year_max"][0],2),
climo30yrs[c]["prcpPROP"]["year_max"][1][0] if len(climo30yrs[c]["prcpPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["year_max"][1]),
round(climo30yrs[c]["prcpPROP"]["year_min"][0],2),
climo30yrs[c]["prcpPROP"]["year_min"][1][0] if len(climo30yrs[c]["prcpPROP"]["year_min"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["year_min"][1]),
climo30yrs[c]["snowPROP"]["days"] if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
round(100 * climo30yrs[c]["snowPROP"]["days"] / climo30yrs[c]["total_days"],1) if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
climo30yrs[c]["snowPROP"]["year_max_days"][0],
climo30yrs[c]["snowPROP"]["year_max_days"][1][0] if len(climo30yrs[c]["snowPROP"]["year_max_days"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["year_max_days"][1]),
round(mean(climo30yrs[c]["snow"]),1) if len(climo30yrs[c]["snow"]) > 0 else "--",
round(climo30yrs[c]["snowPROP"]["year_max"][0],2),
climo30yrs[c]["snowPROP"]["year_max"][1][0] if len(climo30yrs[c]["snowPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["year_max"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("\nPart 2: Temperature Stats")
print("{:▒^9} {:▒^37} | {:▒^37} | {:▒^37}".format("Years","AVG TEMP","TMAX","TMIN"))
print("{:▒^9} {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12}".format("","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN"))
# Y TSTDV TMA TMX TMn TSTDV TMA TMX TMn TSTDV TMA TMX TMn
# "tempAVGlist": [],"tavgPROP":{"year_max":[-999,[]],"year_min":[999,[]]},
print("{:-^9} {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12}".format("","","","","","","","","","","","",""))
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format("All Time",
round(pstdev(alltime["tempAVGlist"]),1),
round(mean(alltime["tempAVGlist_ind"]),1),
round(alltime["tavgPROP"]["year_max"][0],1),
alltime["tavgPROP"]["year_max"][1][0] if len(alltime["tavgPROP"]["year_max"][1]) == 1 else len(alltime["tavgPROP"]["year_max"][1]),
round(alltime["tavgPROP"]["year_min"][0],1),
alltime["tavgPROP"]["year_min"][1][0] if len(alltime["tavgPROP"]["year_min"][1]) == 1 else len(alltime["tavgPROP"]["year_min"][1]),
round(pstdev(alltime["tmax"]),1),
round(mean(alltime["tmax"]),1),
round(alltime["tmaxPROP"]["year_max"][0],1),
alltime["tmaxPROP"]["year_max"][1][0] if len(alltime["tmaxPROP"]["year_max"][1]) == 1 else len(alltime["tmaxPROP"]["year_max"][1]),
round(alltime["tmaxPROP"]["year_min"][0],1),
alltime["tmaxPROP"]["year_min"][1][0] if len(alltime["tmaxPROP"]["year_min"][1]) == 1 else len(alltime["tmaxPROP"]["year_min"][1]),
round(pstdev(alltime["tmin"]),1),
round(mean(alltime["tmin"]),1),
round(alltime["tminPROP"]["year_max"][0],1),
alltime["tminPROP"]["year_max"][1][0] if len(alltime["tminPROP"]["year_max"][1]) == 1 else len(alltime["tminPROP"]["year_max"][1]),
round(alltime["tminPROP"]["year_min"][0],1),
alltime["tminPROP"]["year_min"][1][0] if len(alltime["tminPROP"]["year_min"][1]) == 1 else len(alltime["tminPROP"]["year_min"][1])))
for c in climo30yrs:
try:
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
round(pstdev(climo30yrs[c]["tempAVGlist"]),1),
round(mean(climo30yrs[c]["tempAVGlist_ind"]),1),
round(climo30yrs[c]["tavgPROP"]["year_max"][0],1),
climo30yrs[c]["tavgPROP"]["year_max"][1][0] if len(climo30yrs[c]["tavgPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["year_max"][1]),
round(climo30yrs[c]["tavgPROP"]["year_min"][0],1),
climo30yrs[c]["tavgPROP"]["year_min"][1][0] if len(climo30yrs[c]["tavgPROP"]["year_min"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["year_min"][1]),
round(pstdev(climo30yrs[c]["tmax"]),1),
round(mean(climo30yrs[c]["tmax"]),1),
round(climo30yrs[c]["tmaxPROP"]["year_max"][0],1),
climo30yrs[c]["tmaxPROP"]["year_max"][1][0] if len(climo30yrs[c]["tmaxPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["year_max"][1]),
round(climo30yrs[c]["tmaxPROP"]["year_min"][0],1),
climo30yrs[c]["tmaxPROP"]["year_min"][1][0] if len(climo30yrs[c]["tmaxPROP"]["year_min"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["year_min"][1]),
round(pstdev(climo30yrs[c]["tmin"]),1),
round(mean(climo30yrs[c]["tmin"]),1),
round(climo30yrs[c]["tminPROP"]["year_max"][0],1),
climo30yrs[c]["tminPROP"]["year_max"][1][0] if len(climo30yrs[c]["tminPROP"]["year_max"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["year_max"][1]),
round(climo30yrs[c]["tminPROP"]["year_min"][0],1),
climo30yrs[c]["tminPROP"]["year_min"][1][0] if len(climo30yrs[c]["tminPROP"]["year_min"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["year_min"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("")
if output == True:
newfn = "metYearReport_Mar-Feb_" + str(climatology) + "YRclimo_" + str(increment) + "YRincr_" + clmt["station_name"] + ".csv"
with open(newfn,"w") as w:
headers = ["Assessed Period (March to February)","PRCP Days","PRCP % of days","PRCP stdev","PRCP AVG","SNOW Days","SNOW % of days","SNOW stdev","SNOW AVG","TAVG stdev","TAVG","TMAX stdev","TMAX","TMIN stdev","TMIN"]
# HEADER
for x in range(len(headers)):
if x != len(headers) - 1: w.write(headers[x]); w.write(",")
else: w.write(headers[x]); w.write("\n")
w.write("{}-{}".format(alltime["years"][0],alltime["years"][1])); w.write(",")
w.write("{}".format(alltime["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["prcp"]),1))); w.write(",")
w.write("{}".format(alltime["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tempAVGlist"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tempAVGlist_ind"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmax"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tmax"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmin"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tmin"]))); w.write("\n")
for x in climo30yrs:
w.write("{}-{}".format(climo30yrs[x]["years"][0],climo30yrs[x]["years"][1])); w.write(",")
w.write("{}".format(climo30yrs[x]["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["prcpPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{}".format(climo30yrs[x]["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["snowPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tempAVGlist"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tempAVGlist_ind"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tmax"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmin"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tmin"]))); w.write("\n")
print("*** csv output successful ***")
def customReport(m1,d1,*date2,climatology=30,increment=5,output=False):
"""Detailed Climatological Report a defined custom period of time and can
be of variable length.
Args:
m1: The start month of the custom period.
d1: The start day of the custom period.
Args (optional; represented by *date2)
m2: The end month of the custom period
d2: The end day of the custom period
* If these variables are not given, the end date defaults to Dec. 31.
Keyword Args (optional):
climatology = 30: The span of years that averages are calculated
for (ie. '30 year climatology' or '30 year average'). This can be
modified but should always be > the increment.
increment = 5: Tells the script how often to assess/record successive
climatologies. The smaller this is, the longer the report takes
to generate. If kept at the default, for example, it would
capture the 1976-2005, 1981-2010, and 1986-2015 climatologies and
so forth.
output = False: If set to True, the script will output a CSV file of
its findings. This could be opened in a spreadsheet program for
further analysis
Examples:
customReport(2,14,5,31) -> Returns a 30-yr, 5-yr incremented
climatological report records between Feb 14 and May 31.
customReport(7,1,climatology=10) -> Returns a 5-yr incremented, 10yr
climatological report for records between July 1 and Dec 31
(the latter-half of the year, essentially).
customReport(3,21,3,20,increment=1) -> Returns a 1-yr incremented,
30-yr climatology report for the period of Mar 21 thru Mar 20
of the following year. This would be a good substitute for
assessing astronomical years on the basis of the Spring
Equinox.
customReport(1,1,6,31,output=True) -> Returns a 5-yr incremented,
30 yr climatology for dates between Jan 1 and Jun 30 (the
first half of the calendar year). It also outputs a CSV
report of the findings.
"""
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
valid_yrs = list(range(min([x for x in clmt.keys() if type(x) == int]),max([x for x in clmt.keys() if type(x) == int])+1))
#valid_yrs = [x for x in metclmt.keys() if type(x) == int]
valid_yrs.sort()
if any(type(x) != int for x in [m1,d1]): return print("*** OOPS! Ensure that only integers are entered ***")
if len(date2) == 0: pass
elif len(date2) != 2: return print("*** OOPS! For the 2nd (optional) date, ensure only a Month and Date are entered ***")
elif any(type(x) != int for x in [date2[0],date2[1]]): return print("*** OOPS! Ensure that only integers are entered ***")
if len(date2) == 2:
m2 = date2[0]
d2 = date2[1]
else:
m2 = 12
d2 = 31
if m2 == m1:
if d2 == d1: return print("*** OOPS! Ensure different dates! ***")
if m1 == 2 and d1 == 29: d1 = 28
if m2 == 2 and d2 == 29: d2 = 28
# Determine total length of period (used for exclusion calculation)
s = datetime.date(1900,m1,d1)
test = datetime.date(1900,m2,d2)
if test > s: e = test
else: e = datetime.date(1901,m2,d2)
timelength = (e - s).days + 1
if timelength < 7: EXCLD = 1
elif timelength == 7: EXCLD = excludeweek
elif timelength in [28,29,30,31]: EXCLD = excludemonth
elif timelength >= 350: EXCLD = excludeyear
else: EXCLD = round(excludecustom * timelength)
print("EXCLUDING PERIODS OF <= {} DAYS".format(EXCLD))
climo30yrs = {}
for x in range(1811,max(valid_yrs)+1,increment):
if x in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]) and x+climatology-1 in range(valid_yrs[0],valid_yrs[len(valid_yrs)-1]+1):
climo30yrs[(x,x+climatology-1)] = {"years":(x,x+climatology-1),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"e_max_days":[-1,[]],"e_min_days":[999,[]],"e_max":[-1,[]],"e_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"e_max_days":[-1,[]],"e_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"e_max":[-999,[]],"e_min":[999,[]]},
"tmax": [],"tmaxPROP":{"e_max":[-999,[]],"e_min":[999,[]]},
"tmin": [],"tminPROP":{"e_max":[-999,[]],"e_min":[999,[]]}}
alltime = {"years":(valid_yrs[0],valid_yrs[len(valid_yrs)-1]),"total_days":0,
"prcp": [],"prcpPROP":{"days":0,"e_max_days":[-1,[]],"e_min_days":[999,[]],"e_max":[-1,[]],"e_min":[999,[]]},
"snow": [],"snowPROP":{"days":0,"e_max_days":[-1,[]],"e_max":[-1,[]]},
"tempAVGlist": [],"tempAVGlist_ind":[],"tavgPROP":{"e_max":[-999,[]],"e_min":[999,[]]},
"tmax": [],"tmaxPROP":{"e_max":[-999,[]],"e_min":[999,[]]},
"tmin": [],"tminPROP":{"e_max":[-999,[]],"e_min":[999,[]]}}
e = {} # Will hold the date-to-date (represented by a parent year) stats
print("*** Be Patient. This could take a few moments ***")
for YYYY in valid_yrs:
startday = datetime.date(YYYY,m1,d1)
incr_day = startday
if m2 < m1: endday = datetime.date(YYYY+1,m2,d2) # if end month is less, the results will bleed into the following year
elif m2 == m1: # Deals with if the months of the dates are exactly the same
if d2 < d1: endday = datetime.date(YYYY+1,m2,d2) # like above, if month is the same, but date is less, results will bleed into following year
else: endday = datetime.date(YYYY,m2,d2) # OTHERWISE, it is assumed the same year
else: endday = datetime.date(YYYY,m2,d2) # If month2 is > than month 1, the active year will be used
if endday.year > max(valid_yrs): break
#if YYYY not in e:
e[YYYY] = {"recordqty":0,
"prcp":[],"prcpDAYS":0,"snow":[],"snowDAYS":0,
"tempAVGlist":[],"tmax":[],"tmin":[]}
while incr_day <= endday:
y = incr_day.year; m = incr_day.month; d = incr_day.day
if y in clmt and m in clmt[y] and d in clmt[y][m]:
e[YYYY]["recordqty"] += 1
# PRCP
if clmt[y][m][d].prcpQ in ignoreflags and clmt[y][m][d].prcp not in ["9999","-9999",""]:
if float(clmt[y][m][d].prcp) > 0: e[YYYY]["prcp"].append(round(float(clmt[y][m][d].prcp),2))
if float(clmt[y][m][d].prcp) > 0 or clmt[y][m][d].prcpM == "T": e[YYYY]["prcpDAYS"] += 1
if clmt[y][m][d].prcpQ in ignoreflags and clmt[y][m][d].prcp == "" and clmt[y][m][d].prcpM == "T": e[YYYY]["prcpDAYS"] += 1
# SNOW
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow not in ["9999","-9999",""]:
if float(clmt[y][m][d].snow) > 0: e[YYYY]["snow"].append(round(float(clmt[y][m][d].snow),2))
if float(clmt[y][m][d].snow) > 0 or clmt[y][m][d].snowM == "T": e[YYYY]["snowDAYS"] += 1
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow == "" and clmt[y][m][d].snowM == "T": e[YYYY]["snowDAYS"] += 1
# TAVG
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""] and clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""] and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin):
e[YYYY]["tempAVGlist"].append(int(clmt[y][m][d].tmax))
e[YYYY]["tempAVGlist"].append(int(clmt[y][m][d].tmin))
# TMAX
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""]:
if clmt[y][m][d].tmin != "" and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin):
e[YYYY]["tmax"].append(int(clmt[y][m][d].tmax))
# TMIN
if clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""]:
if clmt[y][m][d].tmax != "" and int(clmt[y][m][d].tmin) <= int(clmt[y][m][d].tmax):
e[YYYY]["tmin"].append(int(clmt[y][m][d].tmin))
incr_day += datetime.timedelta(days=1) # GO ON TO TEST NEXT DAY
for YYYY in e:
#print('e[{}]["prcpDAYS"] = {}'.format(YYYY,e[YYYY]["prcpDAYS"]))
#print('sum(e[{}]["prcp"] = {})'.format(YYYY,sum(e[YYYY]["prcp"])))
#print("----")
#print('alltime["prcpPROP"]["e_max_days"][0] = {}'.format(alltime["prcpPROP"]["e_max_days"][0]))
#print('alltime["prcpPROP"]["e_max_days"][1] = {}'.format(alltime["prcpPROP"]["e_max_days"][1]))
#print('alltime["prcpPROP"]["e_max"][0] = {}'.format(alltime["prcpPROP"]["e_max"][0]))
#print('alltime["prcpPROP"]["e_max"][1] = {}'.format(alltime["prcpPROP"]["e_max"][1]))
#input("----")
alltime["total_days"] += e[YYYY]["recordqty"]
# PRCP
alltime["prcp"].append(sum(e[YYYY]["prcp"]))
alltime["prcpPROP"]["days"] += e[YYYY]["prcpDAYS"]
if e[YYYY]["prcpDAYS"] == alltime["prcpPROP"]["e_max_days"][0]: alltime["prcpPROP"]["e_max_days"][1].append(YYYY)
elif e[YYYY]["prcpDAYS"] > alltime["prcpPROP"]["e_max_days"][0]:
alltime["prcpPROP"]["e_max_days"][0] = e[YYYY]["prcpDAYS"]
alltime["prcpPROP"]["e_max_days"][1] = []
alltime["prcpPROP"]["e_max_days"][1].append(YYYY)
if sum(e[YYYY]["prcp"]) == alltime["prcpPROP"]["e_max"][0]: alltime["prcpPROP"]["e_max"][1].append(YYYY)
elif sum(e[YYYY]["prcp"]) > alltime["prcpPROP"]["e_max"][0]:
alltime["prcpPROP"]["e_max"][0] = sum(e[YYYY]["prcp"])
alltime["prcpPROP"]["e_max"][1] = []
alltime["prcpPROP"]["e_max"][1].append(YYYY)
if e[YYYY]["recordqty"] > EXCLD:
if e[YYYY]["prcpDAYS"] == alltime["prcpPROP"]["e_min_days"][0]: alltime["prcpPROP"]["e_min_days"][1].append(YYYY)
elif e[YYYY]["prcpDAYS"] < alltime["prcpPROP"]["e_min_days"][0]:
alltime["prcpPROP"]["e_min_days"][0] = e[YYYY]["prcpDAYS"]
alltime["prcpPROP"]["e_min_days"][1] = []
alltime["prcpPROP"]["e_min_days"][1].append(YYYY)
if sum(e[YYYY]["prcp"]) == alltime["prcpPROP"]["e_min"][0]: alltime["prcpPROP"]["e_min"][1].append(YYYY)
elif sum(e[YYYY]["prcp"]) < alltime["prcpPROP"]["e_min"][0]:
alltime["prcpPROP"]["e_min"][0] = sum(e[YYYY]["prcp"])
alltime["prcpPROP"]["e_min"][1] = []
alltime["prcpPROP"]["e_min"][1].append(YYYY)
for c in climo30yrs:
if YYYY >= c[0] and YYYY <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["prcp"].append(sum(e[YYYY]["prcp"]))
climo30yrs[c]["prcpPROP"]["days"] += e[YYYY]["prcpDAYS"]
climo30yrs[c]["total_days"] += e[YYYY]["recordqty"]
if e[YYYY]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["e_max_days"][0]: climo30yrs[c]["prcpPROP"]["e_max_days"][1].append(YYYY)
elif e[YYYY]["prcpDAYS"] > climo30yrs[c]["prcpPROP"]["e_max_days"][0]:
climo30yrs[c]["prcpPROP"]["e_max_days"][0] = e[YYYY]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["e_max_days"][1] = []
climo30yrs[c]["prcpPROP"]["e_max_days"][1].append(YYYY)
if sum(e[YYYY]["prcp"]) == climo30yrs[c]["prcpPROP"]["e_max"][0]: climo30yrs[c]["prcpPROP"]["e_max"][1].append(YYYY)
elif sum(e[YYYY]["prcp"]) > climo30yrs[c]["prcpPROP"]["e_max"][0]:
climo30yrs[c]["prcpPROP"]["e_max"][0] = sum(e[YYYY]["prcp"])
climo30yrs[c]["prcpPROP"]["e_max"][1] = []
climo30yrs[c]["prcpPROP"]["e_max"][1].append(YYYY)
if e[YYYY]["recordqty"] > EXCLD:
if e[YYYY]["prcpDAYS"] == climo30yrs[c]["prcpPROP"]["e_min_days"][0]: climo30yrs[c]["prcpPROP"]["e_min_days"][1].append(YYYY)
elif e[YYYY]["prcpDAYS"] < climo30yrs[c]["prcpPROP"]["e_min_days"][0]:
climo30yrs[c]["prcpPROP"]["e_min_days"][0] = e[YYYY]["prcpDAYS"]
climo30yrs[c]["prcpPROP"]["e_min_days"][1] = []
climo30yrs[c]["prcpPROP"]["e_min_days"][1].append(YYYY)
if sum(e[YYYY]["prcp"]) == climo30yrs[c]["prcpPROP"]["e_min"][0]: climo30yrs[c]["prcpPROP"]["e_min"][1].append(YYYY)
elif sum(e[YYYY]["prcp"]) < climo30yrs[c]["prcpPROP"]["e_min"][0]:
climo30yrs[c]["prcpPROP"]["e_min"][0] = sum(e[YYYY]["prcp"])
climo30yrs[c]["prcpPROP"]["e_min"][1] = []
climo30yrs[c]["prcpPROP"]["e_min"][1].append(YYYY)
# SNOW
alltime["snow"].append(sum(e[YYYY]["snow"]))
alltime["snowPROP"]["days"] += e[YYYY]["snowDAYS"]
if e[YYYY]["snowDAYS"] == alltime["snowPROP"]["e_max_days"][0]: alltime["snowPROP"]["e_max_days"][1].append(YYYY)
elif e[YYYY]["snowDAYS"] > alltime["snowPROP"]["e_max_days"][0]:
alltime["snowPROP"]["e_max_days"][0] = e[YYYY]["snowDAYS"]
alltime["snowPROP"]["e_max_days"][1] = []
alltime["snowPROP"]["e_max_days"][1].append(YYYY)
if sum(e[YYYY]["snow"]) == alltime["snowPROP"]["e_max"][0]: alltime["snowPROP"]["e_max"][1].append(YYYY)
elif sum(e[YYYY]["snow"]) > alltime["snowPROP"]["e_max"][0]:
alltime["snowPROP"]["e_max"][0] = sum(e[YYYY]["snow"])
alltime["snowPROP"]["e_max"][1] = []
alltime["snowPROP"]["e_max"][1].append(YYYY)
for c in climo30yrs:
if YYYY >= c[0] and YYYY <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
climo30yrs[c]["snow"].append(sum(e[YYYY]["snow"]))
climo30yrs[c]["snowPROP"]["days"] += e[YYYY]["snowDAYS"]
if e[YYYY]["snowDAYS"] == climo30yrs[c]["snowPROP"]["e_max_days"][0]: climo30yrs[c]["snowPROP"]["e_max_days"][1].append(YYYY)
elif e[YYYY]["snowDAYS"] > climo30yrs[c]["snowPROP"]["e_max_days"][0]:
climo30yrs[c]["snowPROP"]["e_max_days"][0] = e[YYYY]["snowDAYS"]
climo30yrs[c]["snowPROP"]["e_max_days"][1] = []
climo30yrs[c]["snowPROP"]["e_max_days"][1].append(YYYY)
if sum(e[YYYY]["snow"]) == climo30yrs[c]["snowPROP"]["e_max"][0]: climo30yrs[c]["snowPROP"]["e_max"][1].append(YYYY)
elif sum(e[YYYY]["snow"]) > climo30yrs[c]["snowPROP"]["e_max"][0]:
climo30yrs[c]["snowPROP"]["e_max"][0] = sum(e[YYYY]["snow"])
climo30yrs[c]["snowPROP"]["e_max"][1] = []
climo30yrs[c]["snowPROP"]["e_max"][1].append(YYYY)
# 'recordqty', 'prcp', 'prcpDAYS', 'prcpPROP', 'snow', 'snowDAYS', 'snowPROP', 'tempAVGlist', 'tmax', 'tmaxPROP', 'tmin', 'tminPROP'
# TAVG
for x in e[YYYY]["tempAVGlist"]: alltime["tempAVGlist_ind"].append(x)
if len(e[YYYY]["tempAVGlist"]) > EXCLD * 2:
alltime["tempAVGlist"].append(mean(e[YYYY]["tempAVGlist"]))
if mean(e[YYYY]["tempAVGlist"]) == alltime["tavgPROP"]["e_max"][0]: alltime["tavgPROP"]["e_max"][1].append(YYYY)
elif mean(e[YYYY]["tempAVGlist"]) > alltime["tavgPROP"]["e_max"][0]:
alltime["tavgPROP"]["e_max"][0] = mean(e[YYYY]["tempAVGlist"])
alltime["tavgPROP"]["e_max"][1] = []
alltime["tavgPROP"]["e_max"][1].append(YYYY)
if mean(e[YYYY]["tempAVGlist"]) == alltime["tavgPROP"]["e_min"][0]: alltime["tavgPROP"]["e_min"][1].append(YYYY)
elif mean(e[YYYY]["tempAVGlist"]) < alltime["tavgPROP"]["e_min"][0]:
alltime["tavgPROP"]["e_min"][0] = mean(e[YYYY]["tempAVGlist"])
alltime["tavgPROP"]["e_min"][1] = []
alltime["tavgPROP"]["e_min"][1].append(YYYY)
for c in climo30yrs:
if YYYY >= c[0] and YYYY <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in e[YYYY]["tempAVGlist"]:climo30yrs[c]["tempAVGlist_ind"].append(x)
if len(e[YYYY]["tempAVGlist"]) > EXCLD * 2:
climo30yrs[c]["tempAVGlist"].append(mean(e[YYYY]["tempAVGlist"]))
if mean(e[YYYY]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["e_max"][0]: climo30yrs[c]["tavgPROP"]["e_max"][1].append(YYYY)
elif mean(e[YYYY]["tempAVGlist"]) > climo30yrs[c]["tavgPROP"]["e_max"][0]:
climo30yrs[c]["tavgPROP"]["e_max"][0] = mean(e[YYYY]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["e_max"][1] = []
climo30yrs[c]["tavgPROP"]["e_max"][1].append(YYYY)
if mean(e[YYYY]["tempAVGlist"]) == climo30yrs[c]["tavgPROP"]["e_min"][0]: climo30yrs[c]["tavgPROP"]["e_min"][1].append(YYYY)
elif mean(e[YYYY]["tempAVGlist"]) < climo30yrs[c]["tavgPROP"]["e_min"][0]:
climo30yrs[c]["tavgPROP"]["e_min"][0] = mean(e[YYYY]["tempAVGlist"])
climo30yrs[c]["tavgPROP"]["e_min"][1] = []
climo30yrs[c]["tavgPROP"]["e_min"][1].append(YYYY)
# TMAX
for x in e[YYYY]["tmax"]: alltime["tmax"].append(x)
if len(e[YYYY]["tmax"]) > EXCLD:
if mean(e[YYYY]["tmax"]) == alltime["tmaxPROP"]["e_max"][0]: alltime["tmaxPROP"]["e_max"][1].append(YYYY)
elif mean(e[YYYY]["tmax"]) > alltime["tmaxPROP"]["e_max"][0]:
alltime["tmaxPROP"]["e_max"][0] = mean(e[YYYY]["tmax"])
alltime["tmaxPROP"]["e_max"][1] = []
alltime["tmaxPROP"]["e_max"][1].append(YYYY)
if mean(e[YYYY]["tmax"]) == alltime["tmaxPROP"]["e_min"][0]: alltime["tmaxPROP"]["e_min"][1].append(YYYY)
elif mean(e[YYYY]["tmax"]) < alltime["tmaxPROP"]["e_min"][0]:
alltime["tmaxPROP"]["e_min"][0] = mean(e[YYYY]["tmax"])
alltime["tmaxPROP"]["e_min"][1] = []
alltime["tmaxPROP"]["e_min"][1].append(YYYY)
for c in climo30yrs:
if YYYY >= c[0] and YYYY <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in e[YYYY]["tmax"]: climo30yrs[c]["tmax"].append(x)
if len(e[YYYY]["tmax"]) > EXCLD:
if mean(e[YYYY]["tmax"]) == climo30yrs[c]["tmaxPROP"]["e_max"][0]: climo30yrs[c]["tmaxPROP"]["e_max"][1].append(YYYY)
elif mean(e[YYYY]["tmax"]) > climo30yrs[c]["tmaxPROP"]["e_max"][0]:
climo30yrs[c]["tmaxPROP"]["e_max"][0] = mean(e[YYYY]["tmax"])
climo30yrs[c]["tmaxPROP"]["e_max"][1] = []
climo30yrs[c]["tmaxPROP"]["e_max"][1].append(YYYY)
if mean(e[YYYY]["tmax"]) == climo30yrs[c]["tmaxPROP"]["e_min"][0]: climo30yrs[c]["tmaxPROP"]["e_min"][1].append(YYYY)
elif mean(e[YYYY]["tmax"]) < climo30yrs[c]["tmaxPROP"]["e_min"][0]:
climo30yrs[c]["tmaxPROP"]["e_min"][0] = mean(e[YYYY]["tmax"])
climo30yrs[c]["tmaxPROP"]["e_min"][1] = []
climo30yrs[c]["tmaxPROP"]["e_min"][1].append(YYYY)
# TMIN
for x in e[YYYY]["tmin"]: alltime["tmin"].append(x)
if len(e[YYYY]["tmin"]) > EXCLD:
if mean(e[YYYY]["tmin"]) == alltime["tminPROP"]["e_max"][0]: alltime["tminPROP"]["e_max"][1].append(YYYY)
elif mean(e[YYYY]["tmin"]) > alltime["tminPROP"]["e_max"][0]:
alltime["tminPROP"]["e_max"][0] = mean(e[YYYY]["tmin"])
alltime["tminPROP"]["e_max"][1] = []
alltime["tminPROP"]["e_max"][1].append(YYYY)
if mean(e[YYYY]["tmin"]) == alltime["tminPROP"]["e_min"][0]: alltime["tminPROP"]["e_min"][1].append(YYYY)
elif mean(e[YYYY]["tmin"]) < alltime["tminPROP"]["e_min"][0]:
alltime["tminPROP"]["e_min"][0] = mean(e[YYYY]["tmin"])
alltime["tminPROP"]["e_min"][1] = []
alltime["tminPROP"]["e_min"][1].append(YYYY)
for c in climo30yrs:
if YYYY >= c[0] and YYYY <= c[1] and c[0] >= min(YR for YR in clmt if type(YR) == int) and c[1] <= max(YR for YR in clmt if type(YR) == int):
for x in e[YYYY]["tmin"]: climo30yrs[c]["tmin"].append(x)
if len(e[YYYY]["tmin"]) > EXCLD:
if mean(e[YYYY]["tmin"]) == climo30yrs[c]["tminPROP"]["e_max"][0]: climo30yrs[c]["tminPROP"]["e_max"][1].append(YYYY)
elif mean(e[YYYY]["tmin"]) > climo30yrs[c]["tminPROP"]["e_max"][0]:
climo30yrs[c]["tminPROP"]["e_max"][0] = mean(e[YYYY]["tmin"])
climo30yrs[c]["tminPROP"]["e_max"][1] = []
climo30yrs[c]["tminPROP"]["e_max"][1].append(YYYY)
if mean(e[YYYY]["tmin"]) == climo30yrs[c]["tminPROP"]["e_min"][0]: climo30yrs[c]["tminPROP"]["e_min"][1].append(YYYY)
elif mean(e[YYYY]["tmin"]) < climo30yrs[c]["tminPROP"]["e_min"][0]:
climo30yrs[c]["tminPROP"]["e_min"][0] = mean(e[YYYY]["tmin"])
climo30yrs[c]["tminPROP"]["e_min"][1] = []
climo30yrs[c]["tminPROP"]["e_min"][1].append(YYYY)
# PRINT REPORT
print("---------------------------------------------------")
print("Climatology Report for {} {} thru {} {}".format(calendar.month_abbr[startday.month],startday.day,calendar.month_abbr[endday.month],endday.day))
print("City: {}, {}".format(clmt["station"],clmt["station_name"]))
print("{}-{}; {}-Year Incremented {}-Year Climatologies".format(min(valid_yrs),max(valid_yrs),increment,climatology))
print("---------------------------------------------------")
print("Part 1: Precipitation Stats")
print("{:▒^9} {:▒^12} {:▒^9} {:▒^9} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^9} {:▒^6} {:▒^12} |".format("Years","PRCP","PRCP","PRCP","PRCP","PRCP","PRCP","SNOW","SNOW","SNOW","SNOW"))
print("{:▒^9} {:▒^12} {:▒^9} {:▒^9} {:▒^6} {:▒^12} {:▒^12} | {:▒^11} {:▒^9} {:▒^6} {:▒^12} |".format("","DAYS","DAYS MAX","DAYS MIN","AVG", "MAX","MIN","DAYS","DAYS MAX","AVG", "MAX"))
# Y PD PDx PDn PA PM Pmin SD SDx SA SM
print("{:-^9} {:-^12} {:-^9} {:-^9} {:-^6} {:-^12} {:-^12} | {:-^11} {:-^9} {:-^6} {:-^12} |".format("","","","","","","","","","",""))
print("{:^9} {:5}:{:>5}% {:>3}, {:^4} {:>3}, {:^4} {:^6.2f} {:>5.2f}, {:^5} {:>5}, {:^5} | {:4}:{:>5}% {:>3}, {:^4} {:^6.1f} {:>5.1f}, {:^5} |".format("All Time",
alltime["prcpPROP"]["days"],
round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1),
alltime["prcpPROP"]["e_max_days"][0],
alltime["prcpPROP"]["e_max_days"][1][0] if len(alltime["prcpPROP"]["e_max_days"][1]) == 1 else len(alltime["prcpPROP"]["e_max_days"][1]),
alltime["prcpPROP"]["e_min_days"][0],
alltime["prcpPROP"]["e_min_days"][1][0] if len(alltime["prcpPROP"]["e_min_days"][1]) == 1 else len(alltime["prcpPROP"]["e_min_days"][1]),
round(mean(alltime["prcp"]),2) if len(alltime["prcp"]) > 0 else "--",
round(alltime["prcpPROP"]["e_max"][0],2),
alltime["prcpPROP"]["e_max"][1][0] if len(alltime["prcpPROP"]["e_max"][1]) == 1 else len(alltime["prcpPROP"]["e_max"][1]),
round(alltime["prcpPROP"]["e_min"][0],2),
alltime["prcpPROP"]["e_min"][1][0] if len(alltime["prcpPROP"]["e_min"][1]) == 1 else len(alltime["prcpPROP"]["e_min"][1]),
alltime["snowPROP"]["days"] if alltime["snowPROP"]["days"] > 0 else "--",
round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1) if alltime["snowPROP"]["days"] > 0 else "--",
alltime["snowPROP"]["e_max_days"][0],
alltime["snowPROP"]["e_max_days"][1][0] if len(alltime["snowPROP"]["e_max_days"][1]) == 1 else len(alltime["snowPROP"]["e_max_days"][1]),
round(mean(alltime["snow"]),1) if len(alltime["snow"]) > 0 else "--",
round(alltime["snowPROP"]["e_max"][0],2),
alltime["snowPROP"]["e_max"][1][0] if len(alltime["snowPROP"]["e_max"][1]) == 1 else len(alltime["snowPROP"]["e_max"][1])))
for c in climo30yrs:
try:
print("{:^9} {:5}:{:>5}% {:>3}, {:^4} {:>3}, {:^4} {:^6.2f} {:>5.2f}, {:^5} {:>5}, {:^5} | {:4}:{:>5}% {:>3}, {:^4} {:^6.1f} {:>5.1f}, {:^5} |".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
climo30yrs[c]["prcpPROP"]["days"],
round(100 * climo30yrs[c]["prcpPROP"]["days"] / climo30yrs[c]["total_days"],1),
climo30yrs[c]["prcpPROP"]["e_max_days"][0],
climo30yrs[c]["prcpPROP"]["e_max_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["e_max_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["e_max_days"][1]),
climo30yrs[c]["prcpPROP"]["e_min_days"][0],
climo30yrs[c]["prcpPROP"]["e_min_days"][1][0] if len(climo30yrs[c]["prcpPROP"]["e_min_days"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["e_min_days"][1]),
round(mean(climo30yrs[c]["prcp"]),2),
round(climo30yrs[c]["prcpPROP"]["e_max"][0],2),
climo30yrs[c]["prcpPROP"]["e_max"][1][0] if len(climo30yrs[c]["prcpPROP"]["e_max"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["e_max"][1]),
round(climo30yrs[c]["prcpPROP"]["e_min"][0],2),
climo30yrs[c]["prcpPROP"]["e_min"][1][0] if len(climo30yrs[c]["prcpPROP"]["e_min"][1]) == 1 else len(climo30yrs[c]["prcpPROP"]["e_min"][1]),
climo30yrs[c]["snowPROP"]["days"] if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
round(100 * climo30yrs[c]["snowPROP"]["days"] / climo30yrs[c]["total_days"],1) if climo30yrs[c]["snowPROP"]["days"] > 0 else "--",
climo30yrs[c]["snowPROP"]["e_max_days"][0],
climo30yrs[c]["snowPROP"]["e_max_days"][1][0] if len(climo30yrs[c]["snowPROP"]["e_max_days"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["e_max_days"][1]),
round(mean(climo30yrs[c]["snow"]),1) if len(climo30yrs[c]["snow"]) > 0 else "--",
round(climo30yrs[c]["snowPROP"]["e_max"][0],2),
climo30yrs[c]["snowPROP"]["e_max"][1][0] if len(climo30yrs[c]["snowPROP"]["e_max"][1]) == 1 else len(climo30yrs[c]["snowPROP"]["e_max"][1])))
except Exception as e:
print("ERROR: Era = {}; Exception = {}".format(c,e))
print("\nPart 2: Temperature Stats")
print("{:▒^9} {:▒^37} | {:▒^37} | {:▒^37}".format("Years","AVG TEMP","TMAX","TMIN"))
print("{:▒^9} {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12} | {:▒<5} {:▒^5} {:▒^12} {:▒^12}".format("","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN","STDEV","AVG","MAX","MIN"))
# Y TSTDV TMA TMX TMn TSTDV TMA TMX TMn TSTDV TMA TMX TMn
# "tempAVGlist": [],"tavgPROP":{"e_max":[-999,[]],"e_min":[999,[]]},
print("{:-^9} {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12} | {:-^5} {:-^5} {:-^12} {:-^12}".format("","","","","","","","","","","","",""))
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format("All Time",
round(pstdev(alltime["tempAVGlist"]),1),
round(mean(alltime["tempAVGlist_ind"]),1),
round(alltime["tavgPROP"]["e_max"][0],1),
alltime["tavgPROP"]["e_max"][1][0] if len(alltime["tavgPROP"]["e_max"][1]) == 1 else len(alltime["tavgPROP"]["e_max"][1]),
round(alltime["tavgPROP"]["e_min"][0],1),
alltime["tavgPROP"]["e_min"][1][0] if len(alltime["tavgPROP"]["e_min"][1]) == 1 else len(alltime["tavgPROP"]["e_min"][1]),
round(pstdev(alltime["tmax"]),1),
round(mean(alltime["tmax"]),1),
round(alltime["tmaxPROP"]["e_max"][0],1),
alltime["tmaxPROP"]["e_max"][1][0] if len(alltime["tmaxPROP"]["e_max"][1]) == 1 else len(alltime["tmaxPROP"]["e_max"][1]),
round(alltime["tmaxPROP"]["e_min"][0],1),
alltime["tmaxPROP"]["e_min"][1][0] if len(alltime["tmaxPROP"]["e_min"][1]) == 1 else len(alltime["tmaxPROP"]["e_min"][1]),
round(pstdev(alltime["tmin"]),1),
round(mean(alltime["tmin"]),1),
round(alltime["tminPROP"]["e_max"][0],1),
alltime["tminPROP"]["e_max"][1][0] if len(alltime["tminPROP"]["e_max"][1]) == 1 else len(alltime["tminPROP"]["e_max"][1]),
round(alltime["tminPROP"]["e_min"][0],1),
alltime["tminPROP"]["e_min"][1][0] if len(alltime["tminPROP"]["e_min"][1]) == 1 else len(alltime["tminPROP"]["e_min"][1])))
for c in climo30yrs:
try:
print("{:^9} {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5} | {:^5.1f} {:^5.1f} {:>5.1f}, {:^5} {:>5.1f}, {:^5}".format(str(climo30yrs[c]["years"][0])+"-"+str(climo30yrs[c]["years"][1]),
round(pstdev(climo30yrs[c]["tempAVGlist"]),1),
round(mean(climo30yrs[c]["tempAVGlist_ind"]),1),
round(climo30yrs[c]["tavgPROP"]["e_max"][0],1),
climo30yrs[c]["tavgPROP"]["e_max"][1][0] if len(climo30yrs[c]["tavgPROP"]["e_max"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["e_max"][1]),
round(climo30yrs[c]["tavgPROP"]["e_min"][0],1),
climo30yrs[c]["tavgPROP"]["e_min"][1][0] if len(climo30yrs[c]["tavgPROP"]["e_min"][1]) == 1 else len(climo30yrs[c]["tavgPROP"]["e_min"][1]),
round(pstdev(climo30yrs[c]["tmax"]),1),
round(mean(climo30yrs[c]["tmax"]),1),
round(climo30yrs[c]["tmaxPROP"]["e_max"][0],1),
climo30yrs[c]["tmaxPROP"]["e_max"][1][0] if len(climo30yrs[c]["tmaxPROP"]["e_max"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["e_max"][1]),
round(climo30yrs[c]["tmaxPROP"]["e_min"][0],1),
climo30yrs[c]["tmaxPROP"]["e_min"][1][0] if len(climo30yrs[c]["tmaxPROP"]["e_min"][1]) == 1 else len(climo30yrs[c]["tmaxPROP"]["e_min"][1]),
round(pstdev(climo30yrs[c]["tmin"]),1),
round(mean(climo30yrs[c]["tmin"]),1),
round(climo30yrs[c]["tminPROP"]["e_max"][0],1),
climo30yrs[c]["tminPROP"]["e_max"][1][0] if len(climo30yrs[c]["tminPROP"]["e_max"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["e_max"][1]),
round(climo30yrs[c]["tminPROP"]["e_min"][0],1),
climo30yrs[c]["tminPROP"]["e_min"][1][0] if len(climo30yrs[c]["tminPROP"]["e_min"][1]) == 1 else len(climo30yrs[c]["tminPROP"]["e_min"][1])))
except Exception as er:
print("ERROR: Era = {}; Exception = {}".format(c,er))
print("")
if output == True:
newfn = "customReport_{}{}to{}{}_".format(calendar.month_abbr[m1],d1,calendar.month_abbr[m2],d2) + str(climatology) + "YRclimo_" + str(increment) + "YRincr_" + clmt["station_name"] + ".csv"
with open(newfn,"w") as w:
headers = ["Assessed Period ({}{} to {}{})".format(calendar.month_abbr[m1],d1,calendar.month_abbr[m2],d2),"PRCP Days","PRCP % of days","PRCP stdev","PRCP AVG","SNOW Days","SNOW % of days","SNOW stdev","SNOW AVG","TAVG stdev","TAVG","TMAX stdev","TMAX","TMIN stdev","TMIN"]
# HEADER
for x in range(len(headers)):
if x != len(headers) - 1: w.write(headers[x]); w.write(",")
else: w.write(headers[x]); w.write("\n")
w.write("{}-{}".format(alltime["years"][0],alltime["years"][1])); w.write(",")
w.write("{}".format(alltime["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["prcpPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["prcp"]),1))); w.write(",")
w.write("{}".format(alltime["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * alltime["snowPROP"]["days"] / alltime["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(alltime["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tempAVGlist"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tempAVGlist_ind"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmax"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tmax"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(alltime["tmin"]),1))); w.write(",")
w.write("{:.2f}".format(mean(alltime["tmin"]))); w.write("\n")
for x in climo30yrs:
w.write("{}-{}".format(climo30yrs[x]["years"][0],climo30yrs[x]["years"][1])); w.write(",")
w.write("{}".format(climo30yrs[x]["prcpPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["prcpPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["prcp"]),1))); w.write(",")
w.write("{}".format(climo30yrs[x]["snowPROP"]["days"])); w.write(",")
w.write("{:.1f}".format(round(100 * climo30yrs[x]["snowPROP"]["days"] / climo30yrs[x]["total_days"],1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(mean(climo30yrs[x]["snow"]),1))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tempAVGlist"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tempAVGlist_ind"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmax"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tmax"]))); w.write(",")
w.write("{:.1f}".format(round(pstdev(climo30yrs[x]["tmin"]),1))); w.write(",")
w.write("{:.2f}".format(mean(climo30yrs[x]["tmin"]))); w.write("\n")
print("*** csv output successful ***")
def dayRank(m,d,qty):
"""Returns a list of rankings (maxs and mins) based on a specific day of a
specific month. It only accepts arguments for the month, day, and the how
many rankings you want to list (ie, top 10; 15; etc). Passed arguments
MUST be integers.
dayRank(month,day,quantity)
EXAMPLE: dayRank(6,27) -> Returns rankings for June 27
"""
class day_attr:
def __init__(self,y,number):
self.year = y
self.number = number
if type(m) != int or type(d) != int or type(qty) != int: return print("* SORRY! Month AND Day need to be submitted as integers")
if m < 1 or m > 12: return print("* Sorry! Make sure month entry is in the range [1,12]")
if d < 1 or d > 31: return print("* Sorry! Invalid Day entered.")
if m in [4,6,9,11] and d == 31: return print("*Sorry! Only months numbered 1,3,5,7,8,10,12 have 31 days")
if m == 2 and d > 29: return print("* Sorry! February never has 30+ days")
if type(qty) != int or qty > 50 or qty < 5: return print("* SORRY! Ensure desired quantity is an integer in the range [5,50]")
DAYS_prcp = []
DAYS_snow = []
DAYS_snwd = []
DAYS_tmax = []
DAYS_tmin = []
DAYS_tavg = []
# YEARS.append(year_attr(y,round(mean(clmt[y][attribute]),1)))
DAYS_prcp = [day_attr(D.year,V) for V in clmt_vars_days["prcp"] for D in clmt_vars_days["prcp"][V] if D.month == m and D.day == d]
DAYS_snow = [day_attr(D.year,V) for V in clmt_vars_days["snow"] for D in clmt_vars_days["snow"][V] if D.month == m and D.day == d]
DAYS_snwd = [day_attr(D.year,V) for V in clmt_vars_days["snwd"] for D in clmt_vars_days["snwd"][V] if D.month == m and D.day == d]
DAYS_tmax = [day_attr(D.year,V) for V in clmt_vars_days["tmax"] for D in clmt_vars_days["tmax"][V] if D.month == m and D.day == d]
DAYS_tmin = [day_attr(D.year,V) for V in clmt_vars_days["tmin"] for D in clmt_vars_days["tmin"][V] if D.month == m and D.day == d]
DAYS_tavg = [day_attr(D.year,V) for V in clmt_vars_days["tavg"] for D in clmt_vars_days["tavg"][V] if D.month == m and D.day == d]
DAYS_prcp.sort(key=lambda x:x.number,reverse=True)
DAYS_snow.sort(key=lambda x:x.number,reverse=True)
DAYS_snwd.sort(key=lambda x:x.number,reverse=True)
DAYS_tmax_asc = DAYS_tmax.copy()
DAYS_tmax.sort(key=lambda x:x.number,reverse=True)
DAYS_tmax_asc.sort(key=lambda x:x.number)
DAYS_tmin_asc = DAYS_tmin.copy()
DAYS_tmin.sort(key=lambda x:x.number,reverse=True)
DAYS_tmin_asc.sort(key=lambda x:x.number)
DAYS_tavg_asc = DAYS_tavg.copy()
DAYS_tavg.sort(key=lambda x:x.number,reverse=True)
DAYS_tavg_asc.sort(key=lambda x:x.number)
# This block will control if one of the above lists happen to have a length of zero; it's to avoid error
if len(DAYS_prcp) == 0: DAYS_prcp = [day_attr(9999,0)]
if len(DAYS_snow) == 0: DAYS_snow = [day_attr(9999,0)]
if len(DAYS_snwd) == 0: DAYS_snwd = [day_attr(9999,0)]
# 15|17|17|15|19|16
# print("{:2}{} {:4} {:3} | {:2}{} {:4} {:3} | {:2}{} {:4} {:3} | {:2}{} {:4} {:3}" TMAX and TMIN
# print(" {:2}{} {:4} {:5} | {:2}{} {:4} {:4}" PRCP and SNOW
print("")
print("{:^59}".format("Precipitation Records for {} {}".format(calendar.month_name[m],d)))
print("{:^59}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:-^59}".format(""))
print("{:^19}|{:^19}|{:^19}".format("Rain","Snow","Snow Depth"))
print("{:-^19}|{:-^19}|{:-^19}".format("","",""))
i = 0; j = 0; k = 0
ranked_i = []; ranked_j = []; ranked_k = []
for x in range(max(len(DAYS_prcp),len(DAYS_snow),len(DAYS_snwd))):
if x == 0:
i += 1; j += 1; k += 1
else:
try:
if DAYS_prcp[x].number != DAYS_prcp[x-1].number: i += 1
if DAYS_prcp[x].number == 0: i = qty + 1
except: i = qty + 1
try:
if DAYS_snow[x].number != DAYS_snow[x-1].number: j += 1
if DAYS_snow[x].number == 0: j = qty + 1
except: j = qty + 1
try:
if DAYS_snwd[x].number != DAYS_snwd[x-1].number: k += 1
if DAYS_snwd[x].number == 0: k = qty + 1
except: k = qty + 1
#print(i,j,k)
if all(QTY > qty for QTY in [i,j,k]): break
else:
try:
print(" {} | {} | {} ".format(
"{:2}{} {:4} {}".format(
i if i not in ranked_i and i <= qty and DAYS_prcp[x].number > 0 else "",
"." if i not in ranked_i and i <= qty and DAYS_prcp[x].number > 0 else " ",
DAYS_prcp[x].year if i <= qty and x <= len(DAYS_prcp)-1 and DAYS_prcp[x].number > 0 else "",
"{:5.2f}".format(DAYS_prcp[x].number) if i <= qty and x <= len(DAYS_prcp)-1 and DAYS_prcp[x].number > 0 else " "
),
"{:2}{} {:4} {}".format(
j if j not in ranked_j and j <= qty and DAYS_snow[x].number > 0 else "",
"." if j not in ranked_j and j <= qty and DAYS_snow[x].number > 0 else " ",
DAYS_snow[x].year if j <= qty and x <= len(DAYS_snow)-1 and DAYS_snow[x].number > 0 else "",
"{:5.1f}".format(DAYS_snow[x].number) if j <= qty and x <= len(DAYS_snow)-1 and DAYS_snow[x].number > 0 else " "
),
"{:2}{} {:4} {}".format(
k if k not in ranked_k and k <= qty and DAYS_snwd[x].number > 0 else "",
"." if k not in ranked_k and k <= qty and DAYS_snwd[x].number > 0 else " ",
DAYS_snwd[x].year if k <= qty and x <= len(DAYS_snwd)-1 and DAYS_snwd[x].number > 0 else "",
"{:5.1f}".format(DAYS_snwd[x].number) if k <= qty and x <= len(DAYS_snwd)-1 and DAYS_snwd[x].number > 0 else " "
)
))
except Exception as e:
print(x,i,j,k)
traceback.print_tb(e)
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
print("\n{:^102}".format("Temperature Records for {} {}".format(calendar.month_name[m],d)))
print("{:^102}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:-^102}".format(""))
print("{:^34}|{:^33}|{:^33}".format("TAVG","TMAX","TMIN"))
print("{:-^34}|{:-^33}|{:-^33}".format("","",""))
print("{:^16}|{:^17}|{:^16}|{:^16}|{:^16}|{:^16}".format("Warmest","Coolest","Warmest","Coolest","Warmest","Coolest"))
print("{:-^16}|{:-^17}|{:-^16}|{:-^16}|{:-^16}|{:-^16}".format("","","","","",""))
i = 0; j = 0; k = 0; l = 0; m = 0; n = 0
ranked_i = []; ranked_j = []; ranked_k = []; ranked_l = []; ranked_m = []; ranked_n = []
for x in range(max(len(DAYS_tavg),len(DAYS_tmax),len(DAYS_tmin))):
if x == 0:
i += 1; j += 1; k += 1; l += 1; m += 1; n += 1
else:
try:
if DAYS_tavg[x].number != DAYS_tavg[x-1].number: i += 1
except: i = qty + 1
try:
if DAYS_tavg_asc[x].number != DAYS_tavg_asc[x-1].number: j += 1
except: j = qty + 1
try:
if DAYS_tmax[x].number != DAYS_tmax[x-1].number: k += 1
except: k = qty + 1
try:
if DAYS_tmax_asc[x].number != DAYS_tmax_asc[x-1].number: l += 1
except: l = qty + 1
try:
if DAYS_tmin[x].number != DAYS_tmin[x-1].number: m += 1
except: m = qty + 1
try:
if DAYS_tmin_asc[x].number != DAYS_tmin_asc[x-1].number: n += 1
except: n = qty + 1
if all(QTY > qty for QTY in [i,j,k,l,m,n]): break
else:
print("{} | {} | {} | {} | {} | {} ".format(
"{:2}{} {:4} {}".format(
i if i not in ranked_i and i <= qty else "",
"." if i not in ranked_i and i <= qty else " ",
DAYS_tavg[x].year if i <= qty else "",
"{:5.1f}".format(DAYS_tavg[x].number) if i <= qty else " "
),
"{:2}{} {:4} {}".format(
j if j not in ranked_j and j <= qty else "",
"." if j not in ranked_j and j <= qty else " ",
DAYS_tavg_asc[x].year if j <= qty else "",
"{:5.1f}".format(DAYS_tavg_asc[x].number) if j <= qty else " "
),
"{:2}{} {:4} {}".format(
k if k not in ranked_k and k <= qty else "",
"." if k not in ranked_k and k <= qty else " ",
DAYS_tmax[x].year if k <= qty else "",
"{:4}".format(DAYS_tmax[x].number) if k <= qty else " "
),
"{:2}{} {:4} {}".format(
l if l not in ranked_l and l <= qty else "",
"." if l not in ranked_l and l <= qty else " ",
DAYS_tmax_asc[x].year if l <= qty else "",
"{:4}".format(DAYS_tmax_asc[x].number) if l <= qty else " "
),
"{:2}{} {:4} {}".format(
m if m not in ranked_m and m <= qty else "",
"." if m not in ranked_m and m <= qty else " ",
DAYS_tmin[x].year if m <= qty else "",
"{:4}".format(DAYS_tmin[x].number) if m <= qty else " "
),
"{:2}{} {:4} {}".format(
n if n not in ranked_n and n <= qty else "",
"." if n not in ranked_n and n <= qty else " ",
DAYS_tmin_asc[x].year if n <= qty else "",
"{:4}".format(DAYS_tmin_asc[x].number) if n <= qty else " "
)
))
#print("---",i,j,k,l,m,n,"---")
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
print("")
def weekRank(mo,d,qty):
"""Returns a list of rankings (maxs and mins) based on a specific week.
The passed arguments of month and day will be the center of the week. It
only accepts arguments for the month, day, and the how many rankings you
want to list (ie, top 10; 15; etc). Passed arguments MUST be integers.
weekRank(month,day,quantity)
EXAMPLE: weekRank(1,30) -> Returns rankings for the week centered on
January 30 (from Jan 27 to Feb 2)
"""
class week_attr:
def __init__(self,y,number):
self.year = y
self.number = number
if type(mo) != int or type(d) != int or type(qty) != int: return print("* SORRY! Month AND Day need to be submitted as integers")
if mo < 1 or mo > 12: return print("* Sorry! Make sure month entry is in the range [1,12]")
if d < 1 or d > 31: return print("* Sorry! Invalid Day entered.")
if mo in [4,6,9,11] and d == 31: return print("*Sorry! Only months numbered 1,3,5,7,8,10,12 have 31 days")
if mo == 2 and d > 29: return print("* Sorry! February never has 30+ days")
if type(qty) != int or qty > 50 or qty < 5: return print("* SORRY! Ensure desired quantity is an integer in the range [5,50]")
WEEKS_prcp = []
WEEKS_snow = []
WEEKS_snwd = []
WEEKS_tavg = []
WEEKS_tmax = []
WEEKS_tmin = []
if mo == 2 and d == 29: d = 28
wkorig = datetime.date(1999,mo,d) - datetime.timedelta(days=3)
for y in [YR for YR in clmt if type(YR) == int]:
wkstart = datetime.date(y,mo,d) - datetime.timedelta(days=3)
wklist = []
wk_prcp = []
wk_snow = []
wk_snwd = []
wk_tavg = []
wk_tmax = []
wk_tmin = []
for DAY in range(7):
wklist.append(wkstart)
wkstart += datetime.timedelta(days=1)
for DAY in wklist:
#input(clmt[y][DAY.month][DAY.day].daystr)
#if y == 1984:
#print("HI TEMP: {}; DAY: {}".format(clmt[y][DAY.month][DAY.day].tmax,clmt[y][DAY.month][DAY.day].daystr))
try:
#print(clmt[y][DAY.month][DAY.day].prcpQ in ignoreflags)
if clmt[DAY.year][DAY.month][DAY.day].prcpQ in ignoreflags:
wk_prcp.append(float(clmt[DAY.year][DAY.month][DAY.day].prcp))
except:
pass
try:
if clmt[DAY.year][DAY.month][DAY.day].snowQ in ignoreflags:
wk_snow.append(float(clmt[DAY.year][DAY.month][DAY.day].snow))
except:
pass
try:
if clmt[DAY.year][DAY.month][DAY.day].snwdQ in ignoreflags:
wk_snwd.append(float(clmt[DAY.year][DAY.month][DAY.day].snwd))
except:
pass
try:
if clmt[DAY.year][DAY.month][DAY.day].tmaxQ in ignoreflags and clmt[DAY.year][DAY.month][DAY.day].tmax not in ["9999","-9999",""] and clmt[DAY.year][DAY.month][DAY.day].tminQ in ignoreflags and clmt[DAY.year][DAY.month][DAY.day].tmin not in ["9999","-9999",""]:
wk_tavg.append(int(clmt[DAY.year][DAY.month][DAY.day].tmax))
wk_tavg.append(int(clmt[DAY.year][DAY.month][DAY.day].tmin))
except:
pass
try:
if clmt[DAY.year][DAY.month][DAY.day].tmaxQ in ignoreflags:
wk_tmax.append(int(clmt[DAY.year][DAY.month][DAY.day].tmax))
except:
pass
try:
if clmt[DAY.year][DAY.month][DAY.day].tminQ in ignoreflags:
wk_tmin.append(int(clmt[DAY.year][DAY.month][DAY.day].tmin))
except:
pass
try:
WEEKS_prcp.append(week_attr(y,round(sum(wk_prcp),2)))
except:
pass
try:
WEEKS_snow.append(week_attr(y,round(sum(wk_snow),1)))
except:
pass
if len(wk_snwd) > 0:
try:
WEEKS_snwd.append(week_attr(y,round(sum(wk_snwd)/7,1)))
except:
pass
if len(wk_tavg) > excludeweek_tavg:
try:
WEEKS_tavg.append(week_attr(y,round(mean(wk_tavg),1)))
except:
pass
if len(wk_tmax) > excludeweek:
try:
WEEKS_tmax.append(week_attr(y,round(mean(wk_tmax),1)))
#if y == 1984: print(round(mean(wk_tmax),1))
except:
pass
if len(wk_tmin) > excludeweek:
try:
WEEKS_tmin.append(week_attr(y,round(mean(wk_tmin),1)))
except:
pass
#print(len(WEEKS_tavg),len(WEEKS_tmax),len(WEEKS_tmin),len(WEEKS_prcp),len(WEEKS_snow))
#input()
WEEKS_prcp.sort(key=lambda x:x.number,reverse=True)
WEEKS_snow.sort(key=lambda x:x.number,reverse=True)
WEEKS_snwd.sort(key=lambda x:x.number,reverse=True)
WEEKS_tavg_asc = WEEKS_tavg.copy()
WEEKS_tavg.sort(key=lambda x:x.number,reverse=True)
WEEKS_tavg_asc.sort(key=lambda x:x.number)
WEEKS_tmax_asc = WEEKS_tmax.copy()
WEEKS_tmax.sort(key=lambda x:x.number,reverse=True)
WEEKS_tmax_asc.sort(key=lambda x:x.number)
WEEKS_tmin_asc = WEEKS_tmin.copy()
WEEKS_tmin.sort(key=lambda x:x.number,reverse=True)
WEEKS_tmin_asc.sort(key=lambda x:x.number)
#for x in WEEKS_tavg:
#print(x.year,"-",x.number)
#input()
print("")
print("{:^59}".format("Precipitation Records for the Week of {} {} - {} {}".format(calendar.month_abbr[wkorig.month],wkorig.day,
calendar.month_abbr[(wkorig + datetime.timedelta(days=6)).month],(wkorig + datetime.timedelta(days=6)).day)))
print("{:^59}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:^59}".format("Weeks with >= {} Day(s) of Data".format(excludeweek+1)))
print("{:-^59}".format(""))
print("{:^19}|{:^19}|{:^19}".format("Rain","Snow","Avg Snow Depth"))
print("{:-^19}|{:-^19}|{:-^19}".format("","",""))
i = 0; j = 0; k = 0
ranked_i = []; ranked_j = []; ranked_k = []
for x in range(max(len(WEEKS_prcp),len(WEEKS_snow),len(WEEKS_snwd))):
if x == 0:
i += 1; j += 1; k += 1
else:
try:
if WEEKS_prcp[x].number != WEEKS_prcp[x-1].number: i += 1
if WEEKS_prcp[x].number == 0: i = qty + 1
except: i = qty + 1
try:
if WEEKS_snow[x].number != WEEKS_snow[x-1].number: j += 1
if WEEKS_snow[x].number == 0: j = qty + 1
except: j = qty + 1
try:
if WEEKS_snwd[x].number != WEEKS_snwd[x-1].number: k += 1
if WEEKS_snwd[x].number == 0: k = qty + 1
except: k = qty + 1
#print(i,j,k)
if all(QTY > qty for QTY in [i,j,k]): break
else:
print(" {} | {} | {} ".format(
"{:2}{} {:4} {}".format(
i if i not in ranked_i and i <= qty and x <= len(WEEKS_prcp)-1 and WEEKS_prcp[x].number > 0 else "",
"." if i not in ranked_i and i <= qty and x <= len(WEEKS_prcp)-1 and WEEKS_prcp[x].number > 0 else " ",
WEEKS_prcp[x].year if i <= qty and x <= len(WEEKS_prcp)-1 and WEEKS_prcp[x].number > 0 else "",
"{:5.2f}".format(WEEKS_prcp[x].number) if i <= qty and x <= len(WEEKS_prcp)-1 and WEEKS_prcp[x].number > 0 else " "
),
"{:2}{} {:4} {}".format(
j if j not in ranked_j and j <= qty and x <= len(WEEKS_snow)-1 and WEEKS_snow[x].number > 0 else "",
"." if j not in ranked_j and j <= qty and x <= len(WEEKS_snow)-1 and WEEKS_snow[x].number > 0 else " ",
WEEKS_snow[x].year if j <= qty and x <= len(WEEKS_snow)-1 and WEEKS_snow[x].number > 0 else "",
"{:5.1f}".format(WEEKS_snow[x].number) if j <= qty and x <= len(WEEKS_snow)-1 and WEEKS_snow[x].number > 0 else " "
),
"{:2}{} {:4} {}".format(
k if k not in ranked_k and k <= qty and x <= len(WEEKS_snwd)-1 and WEEKS_snwd[x].number > 0 else "",
"." if k not in ranked_k and k <= qty and x <= len(WEEKS_snwd)-1 and WEEKS_snwd[x].number > 0 else " ",
WEEKS_snwd[x].year if k <= qty and x <= len(WEEKS_snwd)-1 and WEEKS_snwd[x].number > 0 else "",
"{:5.1f}".format(WEEKS_snwd[x].number) if k <= qty and x <= len(WEEKS_snwd)-1 and WEEKS_snwd[x].number > 0 else " "
)
))
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
print("\n{:^106}".format("Temperature Records for the Week of {} {} - {} {}".format(calendar.month_abbr[wkorig.month],wkorig.day,
calendar.month_abbr[(wkorig + datetime.timedelta(days=6)).month],(wkorig + datetime.timedelta(days=6)).day)))
print("{:^106}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:^106}".format("Weeks with >= {} Day(s) of Data".format(excludeweek+1)))
print("{:-^106}".format(""))
print("{:^34}|{:^35}|{:^35}".format("TAVG","TMAX","TMIN"))
print("{:-^34}|{:-^35}|{:-^35}".format("","",""))
print("{:^16}|{:^17}|{:^17}|{:^17}|{:^17}|{:^17}".format("Warmest","Coolest","Warmest","Coolest","Warmest","Coolest"))
print("{:-^16}|{:-^17}|{:-^17}|{:-^17}|{:-^17}|{:-^17}".format("","","","","",""))
i = 0; j = 0; k = 0; l = 0; m = 0; n = 0
ranked_i = []; ranked_j = []; ranked_k = []; ranked_l = []; ranked_m = []; ranked_n = []
for x in range(max(len(WEEKS_tavg),len(WEEKS_tmax),len(WEEKS_tmin))):
if x == 0:
i += 1; j += 1; k += 1; l += 1; m += 1; n += 1
else:
try:
if WEEKS_tavg[x].number != WEEKS_tavg[x-1].number: i += 1
except: i = qty + 1
try:
if WEEKS_tavg_asc[x].number != WEEKS_tavg_asc[x-1].number: j += 1
except: j = qty + 1
try:
if WEEKS_tmax[x].number != WEEKS_tmax[x-1].number: k += 1
except: k = qty + 1
try:
if WEEKS_tmax_asc[x].number != WEEKS_tmax_asc[x-1].number: l += 1
except: l = qty + 1
try:
if WEEKS_tmin[x].number != WEEKS_tmin[x-1].number: m += 1
except: m = qty + 1
try:
if WEEKS_tmin_asc[x].number != WEEKS_tmin_asc[x-1].number: n += 1
except: n = qty + 1
if all(QTY > qty for QTY in [i,j,k,l,m,n]): break
else:
print("{} | {} | {} | {} | {} | {} ".format(
"{:2}{} {:4} {}".format(
i if i not in ranked_i and i <= qty else "",
"." if i not in ranked_i and i <= qty else " ",
WEEKS_tavg[x].year if i <= qty else "",
"{:5.1f}".format(WEEKS_tavg[x].number) if i <= qty else " "
),
"{:2}{} {:4} {}".format(
j if j not in ranked_j and j <= qty else "",
"." if j not in ranked_j and j <= qty else " ",
WEEKS_tavg_asc[x].year if j <= qty else "",
"{:5.1f}".format(WEEKS_tavg_asc[x].number) if j <= qty else " "
),
"{:2}{} {:4} {}".format(
k if k not in ranked_k and k <= qty else "",
"." if k not in ranked_k and k <= qty else " ",
WEEKS_tmax[x].year if k <= qty else "",
"{:5.1f}".format(WEEKS_tmax[x].number) if k <= qty else " "
),
"{:2}{} {:4} {}".format(
l if l not in ranked_l and l <= qty else "",
"." if l not in ranked_l and l <= qty else " ",
WEEKS_tmax_asc[x].year if l <= qty else "",
"{:5.1f}".format(WEEKS_tmax_asc[x].number) if l <= qty else " "
),
"{:2}{} {:4} {}".format(
m if m not in ranked_m and m <= qty else "",
"." if m not in ranked_m and m <= qty else " ",
WEEKS_tmin[x].year if m <= qty else "",
"{:5.1f}".format(WEEKS_tmin[x].number) if m <= qty else " "
),
"{:2}{} {:4} {}".format(
n if n not in ranked_n and n <= qty else "",
"." if n not in ranked_n and n <= qty else " ",
WEEKS_tmin_asc[x].year if n <= qty else "",
"{:5.1f}".format(WEEKS_tmin_asc[x].number) if n <= qty else " "
)
))
#print("---",i,j,k,l,m,n,"---")
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
print("")
def monthRank(mo,attribute,qty):
"""Returns a list of rankings (maxs and mins) based on a specific month.
It only accepts arguments for the month, the kind of stats ("prcp" or
"temps"), and how many rankings you want to list (ie, top 10; 15; etc).
The attribute MUST be in string format, while the month and quantity MUST
be integers.
monthRank(month,attribute,quantity)
EXAMPLE: monthRank(3,"rain",20) -> Returns the "Top 20" Precipitation
Rankings for March
"""
class month_attr:
def __init__(self,y,mo,number):
self.year = y
self.month = mo
self.number = number
if type(mo) != int or mo < 1 or mo > 12: return print("* OOPS! {} is an invalid month. Ensure type(m) == int and is range [1,12]".format(mo))
if attribute not in ["temp","temps","temperature","temperatures","tmax","tmin","tavg","prcp","precip","rain","snow"]:
return print("* OOPS! Attribute must be 'temp' or 'prcp'. Try again!")
if type(qty) != int or qty > 50 or qty < 5: return print("* SORRY! Ensure desired quantity is an integer in the range [5,50]")
if attribute in ["prcp","precip","rain","snow"]: attribute = "prcp"
if attribute in ["temp","temps","temperature","temperatures","tmax","tmin","tavg"]: attribute = "temp"
MONTHS_prcp = []
MONTHS_prcp_asc = [] # Declared here bc it will be compiled with in for-loop
MONTHS_prcpDAYS = []
MONTHS_prcpDAYS_asc = [] # Declared here bc it will be compiled with in for-loop
MONTHS_snow = []
MONTHS_snowDAYS = []
MONTHS_tavg = []
MONTHS_tmax = []
MONTHS_tmin = []
for y in [YR for YR in clmt if type(YR) == int]:
try:
MONTHS_prcp.append(month_attr(y,mo,round(sum(clmt[y][mo]["prcp"]),2)))
MONTHS_prcpDAYS.append(month_attr(y,mo,clmt[y][mo]["prcpDAYS"]))
if clmt[y][mo]["recordqty"] > excludemonth:
MONTHS_prcp_asc.append(month_attr(y,mo,round(sum(clmt[y][mo]["prcp"]),2)))
MONTHS_prcpDAYS_asc.append(month_attr(y,mo,clmt[y][mo]["prcpDAYS"]))
MONTHS_snow.append(month_attr(y,mo,round(sum(clmt[y][mo]["snow"]),1)))
MONTHS_snowDAYS.append(month_attr(y,mo,clmt[y][mo]["snowDAYS"]))
except:
pass
try:
if len(clmt[y][mo]["tempAVGlist"]) > excludemonth_tavg:
MONTHS_tavg.append(month_attr(y,mo,round(mean(clmt[y][mo]["tempAVGlist"]),1)))
except:
pass
try:
if len(clmt[y][mo]["tmax"]) > excludemonth:
MONTHS_tmax.append(month_attr(y,mo,round(mean(clmt[y][mo]["tmax"]),1)))
except:
pass
try:
if len(clmt[y][mo]["tmin"]) > excludemonth:
MONTHS_tmin.append(month_attr(y,mo,round(mean(clmt[y][mo]["tmin"]),1)))
except:
pass
#MONTHS_prcp_asc = MONTHS_prcp.copy()
MONTHS_prcp.sort(key=lambda x:x.number,reverse=True)
MONTHS_prcp_asc.sort(key=lambda x:x.number)
#MONTHS_prcpDAYS_asc = MONTHS_prcpDAYS.copy()
MONTHS_prcpDAYS.sort(key=lambda x:x.number,reverse=True)
MONTHS_prcpDAYS_asc.sort(key=lambda x:x.number)
MONTHS_snow.sort(key=lambda x:x.number,reverse=True)
MONTHS_snowDAYS.sort(key=lambda x:x.number,reverse=True)
MONTHS_tavg_asc = MONTHS_tavg.copy()
MONTHS_tavg.sort(key=lambda x:x.number,reverse=True)
MONTHS_tavg_asc.sort(key=lambda x:x.number)
MONTHS_tmax_asc = MONTHS_tmax.copy()
MONTHS_tmax.sort(key=lambda x:x.number,reverse=True)
MONTHS_tmax_asc.sort(key=lambda x:x.number)
MONTHS_tmin_asc = MONTHS_tmin.copy()
MONTHS_tmin.sort(key=lambda x:x.number,reverse=True)
MONTHS_tmin_asc.sort(key=lambda x:x.number)
# print("{:67}|{:32}")
# print("{:18}|{:18}|{:14}|{:14}|{:17}|{:14}")
# print(" {:2}{} {:4} {:6} | {:2}{} {:4} {:6} | {:2}{} {:4} {:2} | {:2}{} {:4} {:2} | {:2}{} {:4} {:5} | {:2}{} {:4} {:2} "
# print(" {:2}{} {:4} {:2} | {:2}{} {:4} {:2} "
print("")
if attribute == "prcp":
print("{:^100}".format("Ranked {} Monthly Precipitation Amounts and Days".format(calendar.month_name[mo])))
print("{:^100}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:^100}".format("Months with >= {} Day(s) of Data".format(excludemonth+1)))
print("{:-^100}".format(""))
print("{:^67}|{:^32}".format("Rain","Snow"))
print("{:-^67}|{:-^32}".format("",""))
print("{:^18}|{:^18}|{:^14}|{:^14}|{:^17}|{:^14}".format("Wettest","Driest","Most Days","Least Days","Snowiest","Most Days"))
print("{:-^18}|{:-^18}|{:-^14}|{:-^14}|{:-^17}|{:-^14}".format("","","","","",""))
i = 1;j = 1;k = 1;l = 1;m = 1;n = 1
ranked_i = [];ranked_j = [];ranked_k = [];ranked_l = [];ranked_m = [];ranked_n = []
for x in range(min(len(MONTHS_prcp),len(MONTHS_prcp_asc),len(MONTHS_prcpDAYS_asc),len(MONTHS_prcpDAYS),len(MONTHS_snow),len(MONTHS_snowDAYS))):
if x == 0:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:2} | {:2}{} {:4} {:2} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>2} ".format(
1,".",MONTHS_prcp[x].year,"{:.2f}".format(MONTHS_prcp[x].number),
1,".",MONTHS_prcp_asc[x].year,"{:.2f}".format(MONTHS_prcp_asc[x].number),
1,".",MONTHS_prcpDAYS[x].year,MONTHS_prcpDAYS[x].number,
1,".",MONTHS_prcpDAYS_asc[x].year,MONTHS_prcpDAYS_asc[x].number,
1 if MONTHS_snow[x].number else "","." if MONTHS_snow[x].number > 0 else " ",
MONTHS_snow[x].year if MONTHS_snow[x].number > 0 else "","{:.1f}".format(MONTHS_snow[x].number) if MONTHS_snow[x].number > 0 else "",
1 if MONTHS_snowDAYS[x].number > 0 else "","." if MONTHS_snowDAYS[x].number > 0 else " ",
MONTHS_snowDAYS[x].year if MONTHS_snowDAYS[x].number > 0 else "",MONTHS_snowDAYS[x].number if MONTHS_snowDAYS[x].number > 0 else ""))
ranked_i.append(i);ranked_j.append(j);ranked_k.append(k);ranked_l.append(l);ranked_m.append(m);ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if MONTHS_prcp[x].number != MONTHS_prcp[x-1].number: i += 1
if MONTHS_prcp_asc[x].number != MONTHS_prcp_asc[x-1].number: j += 1
if MONTHS_prcpDAYS[x].number != MONTHS_prcpDAYS[x-1].number: k += 1
if MONTHS_prcpDAYS_asc[x].number != MONTHS_prcpDAYS_asc[x-1].number: l += 1
if MONTHS_snow[x].number != MONTHS_snow[x-1].number: m += 1
if MONTHS_snowDAYS[x].number != MONTHS_snowDAYS[x-1].number: n += 1
if MONTHS_prcp[x].number == 0: i = qty + 1
if MONTHS_prcpDAYS[x].number == 0: k = qty + 1
if MONTHS_snow[x].number == 0: m = qty + 1
if MONTHS_snowDAYS[x].number == 0: n = qty + 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:2} | {:2}{} {:4} {:2} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>2} ".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
MONTHS_prcp[x].year if i <= qty else "","{:.2f}".format(MONTHS_prcp[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
MONTHS_prcp_asc[x].year if j <= qty else "","{:.2f}".format(MONTHS_prcp_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
MONTHS_prcpDAYS[x].year if k <= qty else "",MONTHS_prcpDAYS[x].number if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
MONTHS_prcpDAYS_asc[x].year if l <= qty else "",MONTHS_prcpDAYS_asc[x].number if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
MONTHS_snow[x].year if m <= qty else "","{:.1f}".format(MONTHS_snow[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
MONTHS_snowDAYS[x].year if n <= qty else "",MONTHS_snowDAYS[x].number if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
if attribute == "temp":
print("{:^111}".format("Ranked {} Monthly Temperatures".format(calendar.month_name[mo])))
print("{:^111}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:^111}".format("Months with >= {} Day(s) of Data".format(excludemonth+1)))
print("{:-^111}".format(""))
print("{:^36}|{:^37}|{:^36}".format("AVG TEMP","TMAX","TMIN"))
print("{:-^36}|{:-^37}|{:-^36}".format("","",""))
print("{:^17}|{:^18}|{:^18}|{:^18}|{:^18}|{:^17}".format("Warmest","Coolest","Warmest","Coolest","Warmest","Coolest"))
print("{:-^17}|{:-^18}|{:-^18}|{:-^18}|{:-^18}|{:-^17}".format("","","","","",""))
i = 1; j = 1; k = 1; l = 1; m = 1; n = 1
ranked_i = []; ranked_j = []; ranked_k = []; ranked_l = []; ranked_m = []; ranked_n = []
for x in range(len(MONTHS_tmax)):
if x == 0:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
1,".",MONTHS_tavg[x].year,"{:.1f}".format(MONTHS_tavg[x].number),
1,".",MONTHS_tavg_asc[x].year,"{:.1f}".format(MONTHS_tavg_asc[x].number),
1,".",MONTHS_tmax[x].year,"{:.1f}".format(MONTHS_tmax[x].number),
1,".",MONTHS_tmax_asc[x].year,"{:.1f}".format(MONTHS_tmax_asc[x].number),
1,".",MONTHS_tmin[x].year,"{:.1f}".format(MONTHS_tmin[x].number),
1,".",MONTHS_tmin_asc[x].year,"{:.1f}".format(MONTHS_tmin_asc[x].number)))
ranked_i.append(i); ranked_j.append(j); ranked_k.append(k); ranked_l.append(l); ranked_m.append(m); ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if MONTHS_tavg[x].number != MONTHS_tavg[x-1].number: i += 1
if MONTHS_tavg_asc[x].number != MONTHS_tavg_asc[x-1].number: j += 1
if MONTHS_tmax[x].number != MONTHS_tmax[x-1].number: k += 1
if MONTHS_tmax_asc[x].number != MONTHS_tmax_asc[x-1].number: l += 1
if MONTHS_tmin[x].number != MONTHS_tmin[x-1].number: m += 1
if MONTHS_tmin_asc[x].number != MONTHS_tmin_asc[x-1].number: n += 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
MONTHS_tavg[x].year if i <= qty else "","{:.1f}".format(MONTHS_tavg[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
MONTHS_tavg_asc[x].year if j <= qty else "","{:.1f}".format(MONTHS_tavg_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
MONTHS_tmax[x].year if k <= qty else "","{:.1f}".format(MONTHS_tmax[x].number) if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
MONTHS_tmax_asc[x].year if l <= qty else "","{:.1f}".format(MONTHS_tmax_asc[x].number) if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
MONTHS_tmin[x].year if m <= qty else "","{:.1f}".format(MONTHS_tmin[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
MONTHS_tmin_asc[x].year if n <= qty else "","{:.1f}".format(MONTHS_tmin_asc[x].number) if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
print("")
def yearRank(attribute,qty,**kwargs):
"""Returns a list of rankings (maxs and mins) for all years on record. It
only accepts arguments for the kind of stats ("prcp" or "temps") desired,
and how many rankings you want to list (ie, top 10; 15; etc). The
attribute MUST be in string format, while the quantity MUST be an integer.
yearRank(attribute,quantity)
EXAMPLE: yearRank("temp",15) -> Returns the "Top 15" Temperature-based
Rankings for all calendar years on record
* The kwargs option is not available to the user. it is used internally
by yearStats
"""
class month_attr:
def __init__(self,y,number):
self.year = y
self.number = number
if attribute not in ["temp","temps","temperature","temperatures","tmax","tmin","tavg","prcp","precip","rain","snow"]:
return print("* OOPS! Attribute must be 'temp' or 'prcp'. Try again!")
if type(qty) != int or qty > 50 or qty < 5: return print("* SORRY! Ensure desired quantity is an integer in the range [5,50]")
if attribute in ["prcp","precip","rain","snow"]: attribute = "prcp"
if attribute in ["temp","temps","temperature","temperatures","tmax","tmin","tavg"]: attribute = "temp"
YEARS_prcp = []
YEARS_prcp_asc = []
YEARS_prcpDAYS = []
YEARS_prcpDAYS_asc = []
YEARS_snow = []
YEARS_snow_asc = []
YEARS_snowDAYS = []
YEARS_snowDAYS_asc = []
YEARS_tavg = []
YEARS_tmax = []
YEARS_tmin = []
for y in [YR for YR in clmt if type(YR) == int]:
try:
YEARS_prcp.append(month_attr(y,round(sum(clmt[y]["prcp"]),2)))
YEARS_prcpDAYS.append(month_attr(y,clmt[y]["prcpDAYS"]))
if clmt[y]["recordqty"] > excludeyear:
YEARS_prcp_asc.append(month_attr(y,round(sum(clmt[y]["prcp"]),2)))
YEARS_prcpDAYS_asc.append(month_attr(y,clmt[y]["prcpDAYS"]))
YEARS_snow.append(month_attr(y,round(sum(clmt[y]["snow"]),1)))
if clmt[y]["recordqty"] > excludeyear: YEARS_snow_asc.append(month_attr(y,round(sum(clmt[y]["snow"]),1)))
YEARS_snowDAYS.append(month_attr(y,clmt[y]["snowDAYS"]))
if clmt[y]["recordqty"] > excludeyear: YEARS_snowDAYS_asc.append(month_attr(y,clmt[y]["snowDAYS"]))
except:
pass
try:
if len(clmt[y]["tempAVGlist"]) > excludeyear_tavg:
YEARS_tavg.append(month_attr(y,round(mean(clmt[y]["tempAVGlist"]),1)))
except:
pass
try:
if len(clmt[y]["tmax"]) > excludeyear:
YEARS_tmax.append(month_attr(y,round(mean(clmt[y]["tmax"]),1)))
except:
pass
try:
if len(clmt[y]["tmin"]) > excludeyear:
YEARS_tmin.append(month_attr(y,round(mean(clmt[y]["tmin"]),1)))
except:
pass
#YEARS_prcp_asc = YEARS_prcp.copy()
YEARS_prcp.sort(key=lambda x:x.number,reverse=True)
YEARS_prcp_asc.sort(key=lambda x:x.number)
#YEARS_prcpDAYS_asc = YEARS_prcpDAYS.copy()
YEARS_prcpDAYS.sort(key=lambda x:x.number,reverse=True)
YEARS_prcpDAYS_asc.sort(key=lambda x:x.number)
YEARS_snow.sort(key=lambda x:x.number,reverse=True)
YEARS_snow_asc.sort(key=lambda x:x.number)
YEARS_snowDAYS.sort(key=lambda x:x.number,reverse=True)
YEARS_snowDAYS_asc.sort(key=lambda x:x.number)
YEARS_tavg_asc = YEARS_tavg.copy()
YEARS_tavg.sort(key=lambda x:x.number,reverse=True)
YEARS_tavg_asc.sort(key=lambda x:x.number)
YEARS_tmax_asc = YEARS_tmax.copy()
YEARS_tmax.sort(key=lambda x:x.number,reverse=True)
YEARS_tmax_asc.sort(key=lambda x:x.number)
YEARS_tmin_asc = YEARS_tmin.copy()
YEARS_tmin.sort(key=lambda x:x.number,reverse=True)
YEARS_tmin_asc.sort(key=lambda x:x.number)
if "yearStatsRun" in kwargs and kwargs["yearStatsRun"] == True:
prcpaschist = sorted(list(set([x.number for x in YEARS_prcp_asc])))
prcpdeschist = sorted(list(set([x.number for x in YEARS_prcp])),reverse=True)
prcpDAYSaschist = sorted(list(set([x.number for x in YEARS_prcpDAYS_asc])))
prcpDAYSdeschist = sorted(list(set([x.number for x in YEARS_prcpDAYS])),reverse=True)
snowaschist = sorted(list(set([x.number for x in YEARS_snow_asc])))
snowdeschist = sorted(list(set([x.number for x in YEARS_snow])),reverse=True)
snowDAYSaschist = sorted(list(set([x.number for x in YEARS_snowDAYS_asc])))
snowDAYSdeschist = sorted(list(set([x.number for x in YEARS_snowDAYS])),reverse=True)
tmaxaschist = sorted(list(set([x.number for x in YEARS_tmax_asc])))
tmaxdeschist = sorted(list(set([x.number for x in YEARS_tmax])),reverse=True)
tminaschist = sorted(list(set([x.number for x in YEARS_tmin_asc])))
tmindeschist = sorted(list(set([x.number for x in YEARS_tmin])),reverse=True)
tavgaschist = sorted(list(set([x.number for x in YEARS_tavg_asc])))
tavgdeschist = sorted(list(set([x.number for x in YEARS_tavg])),reverse=True)
return prcpaschist, prcpdeschist, prcpDAYSaschist, prcpDAYSdeschist, snowaschist, snowdeschist, snowDAYSaschist, snowDAYSdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist
else:
print("")
if attribute == "prcp":
print("{:^103}".format("Ranked Yearly Precipitation Amounts and Days"))
print("{:^103}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:^103}".format("Years with >= {} day(s) of data".format(excludeyear+1)))
print("{:-^103}".format(""))
print("{:^69}|{:^33}".format("Rain","Snow"))
print("{:-^69}|{:-^33}".format("",""))
print("{:^18}|{:^18}|{:^15}|{:^15}|{:^17}|{:^15}".format("Wettest","Driest","Most Days","Least Days","Snowiest","Most Days"))
print("{:-^18}|{:-^18}|{:-^15}|{:-^15}|{:-^17}|{:-^15}".format("","","","","",""))
i = 1;j = 1;k = 1;l = 1;m = 1;n = 1
ranked_i = [];ranked_j = [];ranked_k = [];ranked_l = [];ranked_m = [];ranked_n = []
for x in range(min(len(YEARS_prcp),len(YEARS_prcp_asc),len(YEARS_prcpDAYS_asc),len(YEARS_prcpDAYS),len(YEARS_snow),len(YEARS_snowDAYS))):
if x == 0:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>3} ".format(
1,".",YEARS_prcp[x].year,"{:.2f}".format(YEARS_prcp[x].number),
1,".",YEARS_prcp_asc[x].year,"{:.2f}".format(YEARS_prcp_asc[x].number),
1,".",YEARS_prcpDAYS[x].year,YEARS_prcpDAYS[x].number,
1,".",YEARS_prcpDAYS_asc[x].year,YEARS_prcpDAYS_asc[x].number,
1 if YEARS_snow[x].number else "","." if YEARS_snow[x].number > 0 else " ",
YEARS_snow[x].year if YEARS_snow[x].number > 0 else "","{:.1f}".format(YEARS_snow[x].number) if YEARS_snow[x].number > 0 else "",
1 if YEARS_snowDAYS[x].number > 0 else "","." if YEARS_snowDAYS[x].number > 0 else " ",
YEARS_snowDAYS[x].year if YEARS_snowDAYS[x].number > 0 else "",YEARS_snowDAYS[x].number if YEARS_snowDAYS[x].number > 0 else ""))
ranked_i.append(i);ranked_j.append(j);ranked_k.append(k);ranked_l.append(l);ranked_m.append(m);ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if YEARS_prcp[x].number != YEARS_prcp[x-1].number: i += 1
if YEARS_prcp_asc[x].number != YEARS_prcp_asc[x-1].number: j += 1
if YEARS_prcpDAYS[x].number != YEARS_prcpDAYS[x-1].number: k += 1
if YEARS_prcpDAYS_asc[x].number != YEARS_prcpDAYS_asc[x-1].number: l += 1
if YEARS_snow[x].number != YEARS_snow[x-1].number: m += 1
if YEARS_snowDAYS[x].number != YEARS_snowDAYS[x-1].number: n += 1
if YEARS_prcp[x].number == 0: i = qty + 1
if YEARS_prcpDAYS[x].number == 0: k = qty + 1
if YEARS_snow[x].number == 0: m = qty + 1
if YEARS_snowDAYS[x].number == 0: n = qty + 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>3} ".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
YEARS_prcp[x].year if i <= qty else "","{:.2f}".format(YEARS_prcp[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
YEARS_prcp_asc[x].year if j <= qty else "","{:.2f}".format(YEARS_prcp_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
YEARS_prcpDAYS[x].year if k <= qty else "",YEARS_prcpDAYS[x].number if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
YEARS_prcpDAYS_asc[x].year if l <= qty else "",YEARS_prcpDAYS_asc[x].number if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
YEARS_snow[x].year if m <= qty else "","{:.1f}".format(YEARS_snow[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
YEARS_snowDAYS[x].year if n <= qty else "",YEARS_snowDAYS[x].number if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
if attribute == "temp":
print("{:^111}".format("Ranked Yearly Temperatures"))
print("{:^111}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:^111}".format("Years with >= {} day(s) of data".format(excludeyear+1)))
print("{:-^111}".format(""))
print("{:^36}|{:^37}|{:^36}".format("AVG TEMP","TMAX","TMIN"))
print("{:-^36}|{:-^37}|{:-^36}".format("","",""))
print("{:^17}|{:^18}|{:^18}|{:^18}|{:^18}|{:^17}".format("Warmest","Coolest","Warmest","Coolest","Warmest","Coolest"))
print("{:-^17}|{:-^18}|{:-^18}|{:-^18}|{:-^18}|{:-^17}".format("","","","","",""))
i = 1; j = 1; k = 1; l = 1; m = 1; n = 1
ranked_i = []; ranked_j = []; ranked_k = []; ranked_l = []; ranked_m = []; ranked_n = []
for x in range(len(YEARS_tmax)):
if x == 0:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
1,".",YEARS_tavg[x].year,"{:.1f}".format(YEARS_tavg[x].number),
1,".",YEARS_tavg_asc[x].year,"{:.1f}".format(YEARS_tavg_asc[x].number),
1,".",YEARS_tmax[x].year,"{:.1f}".format(YEARS_tmax[x].number),
1,".",YEARS_tmax_asc[x].year,"{:.1f}".format(YEARS_tmax_asc[x].number),
1,".",YEARS_tmin[x].year,"{:.1f}".format(YEARS_tmin[x].number),
1,".",YEARS_tmin_asc[x].year,"{:.1f}".format(YEARS_tmin_asc[x].number)))
ranked_i.append(i); ranked_j.append(j); ranked_k.append(k); ranked_l.append(l); ranked_m.append(m); ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if YEARS_tavg[x].number != YEARS_tavg[x-1].number: i += 1
if YEARS_tavg_asc[x].number != YEARS_tavg_asc[x-1].number: j += 1
if YEARS_tmax[x].number != YEARS_tmax[x-1].number: k += 1
if YEARS_tmax_asc[x].number != YEARS_tmax_asc[x-1].number: l += 1
if YEARS_tmin[x].number != YEARS_tmin[x-1].number: m += 1
if YEARS_tmin_asc[x].number != YEARS_tmin_asc[x-1].number: n += 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
YEARS_tavg[x].year if i <= qty else "","{:.1f}".format(YEARS_tavg[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
YEARS_tavg_asc[x].year if j <= qty else "","{:.1f}".format(YEARS_tavg_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
YEARS_tmax[x].year if k <= qty else "","{:.1f}".format(YEARS_tmax[x].number) if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
YEARS_tmax_asc[x].year if l <= qty else "","{:.1f}".format(YEARS_tmax_asc[x].number) if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
YEARS_tmin[x].year if m <= qty else "","{:.1f}".format(YEARS_tmin[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
YEARS_tmin_asc[x].year if n <= qty else "","{:.1f}".format(YEARS_tmin_asc[x].number) if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
print("")
def seasonRank(season,attribute,qty,**kwargs):
"""Returns a list of rankings (maxs and mins) for all specified
meteorological seasons on record. The season ("spring", "summer", "fall",
"winter") and attribute ("prcp" or "temp") must be in string format. The
quantity, denoting how many rankings you desire, must be an integer.
seasonRank(season,attribute,quantity)
EXAMPLE: seasonRank("Spring","temp",5) -> Returns the "Top 5" Temperature-
based Rankings for all
Meteorological Springs on record
"""
class month_attr:
def __init__(self,y,number):
self.year = y
self.number = number
if attribute not in ["temp","temps","temperature","temperatures","tmax","tmin","tavg","prcp","precip","rain","snow"]:
return print("* OOPS! Attribute must be 'temp' or 'prcp'. Try again!")
if type(qty) != int or qty > 50 or qty < 5: return print("* SORRY! Ensure desired quantity is an integer in the range [5,50]")
if attribute in ["prcp","precip","rain","snow"]: attribute = "prcp"
if attribute in ["temp","temps","temperature","temperatures","tmax","tmin","tavg"]: attribute = "temp"
SEASON_prcp = []
SEASON_prcp_asc = []
SEASON_prcpDAYS = []
SEASON_prcpDAYS_asc = []
SEASON_snow = []
SEASON_snow_asc = []
SEASON_snowDAYS = []
SEASON_snowDAYS_asc = []
SEASON_tavg = []
SEASON_tmax = []
SEASON_tmin = []
for y in [YR for YR in metclmt if type(YR) == int]:
try:
SEASON_prcp.append(month_attr(y,round(sum(metclmt[y][season]["prcp"]),2)))
SEASON_prcpDAYS.append(month_attr(y,metclmt[y][season]["prcpDAYS"]))
if metclmt[y][season]["recordqty"] > excludeseason:
SEASON_prcp_asc.append(month_attr(y,round(sum(metclmt[y][season]["prcp"]),2)))
SEASON_prcpDAYS_asc.append(month_attr(y,metclmt[y][season]["prcpDAYS"]))
SEASON_snow.append(month_attr(y,round(sum(metclmt[y][season]["snow"]),1)))
if metclmt[y][season]["recordqty"] > excludeseason: SEASON_snow_asc.append(month_attr(y,round(sum(metclmt[y][season]["snow"]),1)))
SEASON_snowDAYS.append(month_attr(y,metclmt[y][season]["snowDAYS"]))
if metclmt[y][season]["recordqty"] > excludeseason: SEASON_snowDAYS_asc.append(month_attr(y,metclmt[y][season]["snowDAYS"]))
except:
pass
try:
if len(metclmt[y][season]["tempAVGlist"]) > excludeseason_tavg:
SEASON_tavg.append(month_attr(y,round(mean(metclmt[y][season]["tempAVGlist"]),1)))
except:
pass
try:
if len(metclmt[y][season]["tmax"]) > excludeseason:
SEASON_tmax.append(month_attr(y,round(mean(metclmt[y][season]["tmax"]),1)))
except:
pass
try:
if len(metclmt[y][season]["tmin"]) > excludeseason:
SEASON_tmin.append(month_attr(y,round(mean(metclmt[y][season]["tmin"]),1)))
except:
pass
#SEASON_prcp_asc = SEASON_prcp.copy()
SEASON_prcp.sort(key=lambda x:x.number,reverse=True)
SEASON_prcp_asc.sort(key=lambda x:x.number)
#SEASON_prcpDAYS_asc = SEASON_prcpDAYS.copy()
SEASON_prcpDAYS.sort(key=lambda x:x.number,reverse=True)
SEASON_prcpDAYS_asc.sort(key=lambda x:x.number)
SEASON_snow.sort(key=lambda x:x.number,reverse=True)
SEASON_snow_asc.sort(key=lambda x:x.number)
SEASON_snowDAYS.sort(key=lambda x:x.number,reverse=True)
SEASON_snowDAYS_asc.sort(key=lambda x:x.number)
SEASON_tavg_asc = SEASON_tavg.copy()
SEASON_tavg.sort(key=lambda x:x.number,reverse=True)
SEASON_tavg_asc.sort(key=lambda x:x.number)
SEASON_tmax_asc = SEASON_tmax.copy()
SEASON_tmax.sort(key=lambda x:x.number,reverse=True)
SEASON_tmax_asc.sort(key=lambda x:x.number)
SEASON_tmin_asc = SEASON_tmin.copy()
SEASON_tmin.sort(key=lambda x:x.number,reverse=True)
SEASON_tmin_asc.sort(key=lambda x:x.number)
if "seasonStatsRun" in kwargs and kwargs["seasonStatsRun"] == True:
prcpaschist = sorted(list(set([x.number for x in SEASON_prcp_asc])))
prcpdeschist = sorted(list(set([x.number for x in SEASON_prcp])),reverse=True)
prcpDAYSaschist = sorted(list(set([x.number for x in SEASON_prcpDAYS_asc])))
prcpDAYSdeschist = sorted(list(set([x.number for x in SEASON_prcpDAYS])),reverse=True)
snowaschist = sorted(list(set([x.number for x in SEASON_snow_asc])))
snowdeschist = sorted(list(set([x.number for x in SEASON_snow])),reverse=True)
snowDAYSaschist = sorted(list(set([x.number for x in SEASON_snowDAYS_asc])))
snowDAYSdeschist = sorted(list(set([x.number for x in SEASON_snowDAYS])),reverse=True)
tmaxaschist = sorted(list(set([x.number for x in SEASON_tmax_asc])))
tmaxdeschist = sorted(list(set([x.number for x in SEASON_tmax])),reverse=True)
tminaschist = sorted(list(set([x.number for x in SEASON_tmin_asc])))
tmindeschist = sorted(list(set([x.number for x in SEASON_tmin])),reverse=True)
tavgaschist = sorted(list(set([x.number for x in SEASON_tavg_asc])))
tavgdeschist = sorted(list(set([x.number for x in SEASON_tavg])),reverse=True)
return prcpaschist, prcpdeschist, prcpDAYSaschist, prcpDAYSdeschist, snowaschist, snowdeschist, snowDAYSaschist, snowDAYSdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist
else:
print("")
if attribute == "prcp":
print("{:^103}".format("Meteorological {} Ranked Precipitation Amounts and Days".format(season.capitalize())))
print("{:^103}".format("{}, {}".format(metclmt["station"],metclmt["station_name"])))
print("{:^103}".format("Seasons with >= {} day(s) of data".format(excludeseason+1)))
print("{:-^103}".format(""))
print("{:^69}|{:^33}".format("Rain","Snow"))
print("{:-^69}|{:-^33}".format("",""))
print("{:^18}|{:^18}|{:^15}|{:^15}|{:^17}|{:^15}".format("Wettest","Driest","Most Days","Least Days","Snowiest","Most Days"))
print("{:-^18}|{:-^18}|{:-^15}|{:-^15}|{:-^17}|{:-^15}".format("","","","","",""))
i = 1;j = 1;k = 1;l = 1;m = 1;n = 1
ranked_i = [];ranked_j = [];ranked_k = [];ranked_l = [];ranked_m = [];ranked_n = []
for x in range(min(len(SEASON_prcp),len(SEASON_prcp_asc),len(SEASON_prcpDAYS_asc),len(SEASON_prcpDAYS),len(SEASON_snow),len(SEASON_snowDAYS))):
if x == 0:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>3} ".format(
1,".",SEASON_prcp[x].year,"{:.2f}".format(SEASON_prcp[x].number),
1,".",SEASON_prcp_asc[x].year,"{:.2f}".format(SEASON_prcp_asc[x].number),
1,".",SEASON_prcpDAYS[x].year,SEASON_prcpDAYS[x].number,
1,".",SEASON_prcpDAYS_asc[x].year,SEASON_prcpDAYS_asc[x].number,
1 if SEASON_snow[x].number else "","." if SEASON_snow[x].number > 0 else " ",
SEASON_snow[x].year if SEASON_snow[x].number > 0 else "","{:.1f}".format(SEASON_snow[x].number) if SEASON_snow[x].number > 0 else "",
1 if SEASON_snowDAYS[x].number > 0 else "","." if SEASON_snowDAYS[x].number > 0 else " ",
SEASON_snowDAYS[x].year if SEASON_snowDAYS[x].number > 0 else "",SEASON_snowDAYS[x].number if SEASON_snowDAYS[x].number > 0 else ""))
ranked_i.append(i);ranked_j.append(j);ranked_k.append(k);ranked_l.append(l);ranked_m.append(m);ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if SEASON_prcp[x].number != SEASON_prcp[x-1].number: i += 1
if SEASON_prcp_asc[x].number != SEASON_prcp_asc[x-1].number: j += 1
if SEASON_prcpDAYS[x].number != SEASON_prcpDAYS[x-1].number: k += 1
if SEASON_prcpDAYS_asc[x].number != SEASON_prcpDAYS_asc[x-1].number: l += 1
if SEASON_snow[x].number != SEASON_snow[x-1].number: m += 1
if SEASON_snowDAYS[x].number != SEASON_snowDAYS[x-1].number: n += 1
if SEASON_prcp[x].number == 0: i = qty + 1
if SEASON_prcpDAYS[x].number == 0: k = qty + 1
if SEASON_snow[x].number == 0: m = qty + 1
if SEASON_snowDAYS[x].number == 0: n = qty + 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>3} ".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
SEASON_prcp[x].year if i <= qty else "","{:.2f}".format(SEASON_prcp[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
SEASON_prcp_asc[x].year if j <= qty else "","{:.2f}".format(SEASON_prcp_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
SEASON_prcpDAYS[x].year if k <= qty else "",SEASON_prcpDAYS[x].number if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
SEASON_prcpDAYS_asc[x].year if l <= qty else "",SEASON_prcpDAYS_asc[x].number if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
SEASON_snow[x].year if m <= qty else "","{:.1f}".format(SEASON_snow[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
SEASON_snowDAYS[x].year if n <= qty else "",SEASON_snowDAYS[x].number if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
if attribute == "temp":
print("{:^111}".format("Meteorological {} Ranked Temperatures".format(season.capitalize())))
print("{:^111}".format("{}, {}".format(metclmt["station"],metclmt["station_name"])))
print("{:^111}".format("Seasons with >= {} day(s) of data".format(excludeseason+1)))
print("{:-^111}".format(""))
print("{:^36}|{:^37}|{:^36}".format("AVG TEMP","TMAX","TMIN"))
print("{:-^36}|{:-^37}|{:-^36}".format("","",""))
print("{:^17}|{:^18}|{:^18}|{:^18}|{:^18}|{:^17}".format("Warmest","Coolest","Warmest","Coolest","Warmest","Coolest"))
print("{:-^17}|{:-^18}|{:-^18}|{:-^18}|{:-^18}|{:-^17}".format("","","","","",""))
i = 1; j = 1; k = 1; l = 1; m = 1; n = 1
ranked_i = []; ranked_j = []; ranked_k = []; ranked_l = []; ranked_m = []; ranked_n = []
for x in range(len(SEASON_tmax)):
if x == 0:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
1,".",SEASON_tavg[x].year,"{:.1f}".format(SEASON_tavg[x].number),
1,".",SEASON_tavg_asc[x].year,"{:.1f}".format(SEASON_tavg_asc[x].number),
1,".",SEASON_tmax[x].year,"{:.1f}".format(SEASON_tmax[x].number),
1,".",SEASON_tmax_asc[x].year,"{:.1f}".format(SEASON_tmax_asc[x].number),
1,".",SEASON_tmin[x].year,"{:.1f}".format(SEASON_tmin[x].number),
1,".",SEASON_tmin_asc[x].year,"{:.1f}".format(SEASON_tmin_asc[x].number)))
ranked_i.append(i); ranked_j.append(j); ranked_k.append(k); ranked_l.append(l); ranked_m.append(m); ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if SEASON_tavg[x].number != SEASON_tavg[x-1].number: i += 1
if SEASON_tavg_asc[x].number != SEASON_tavg_asc[x-1].number: j += 1
if SEASON_tmax[x].number != SEASON_tmax[x-1].number: k += 1
if SEASON_tmax_asc[x].number != SEASON_tmax_asc[x-1].number: l += 1
if SEASON_tmin[x].number != SEASON_tmin[x-1].number: m += 1
if SEASON_tmin_asc[x].number != SEASON_tmin_asc[x-1].number: n += 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
SEASON_tavg[x].year if i <= qty else "","{:.1f}".format(SEASON_tavg[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
SEASON_tavg_asc[x].year if j <= qty else "","{:.1f}".format(SEASON_tavg_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
SEASON_tmax[x].year if k <= qty else "","{:.1f}".format(SEASON_tmax[x].number) if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
SEASON_tmax_asc[x].year if l <= qty else "","{:.1f}".format(SEASON_tmax_asc[x].number) if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
SEASON_tmin[x].year if m <= qty else "","{:.1f}".format(SEASON_tmin[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
SEASON_tmin_asc[x].year if n <= qty else "","{:.1f}".format(SEASON_tmin_asc[x].number) if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
print("")
def metYearRank(attribute,qty,**kwargs):
"""Returns a list of rankings (maxs and mins) for all meteorological years
(March to February) on record. The attribute ("prcp" or "temp") must be in
string format. The quantity, denoting how many rankings you desire, must
be an integer.
metYearRank(attribute,quantity)
EXAMPLE: metYearRank("rain",12) -> Returns the "Top 12" Precip-based
Rankings for all Meteorological Years
on record
"""
class month_attr:
def __init__(self,y,number):
self.year = y
self.number = number
if attribute not in ["temp","temps","temperature","temperatures","tmax","tmin","tavg","prcp","precip","rain","snow"]:
return print("* OOPS! Attribute must be 'temp' or 'prcp'. Try again!")
if type(qty) != int or qty > 50 or qty < 5: return print("* SORRY! Ensure desired quantity is an integer in the range [5,50]")
if attribute in ["prcp","precip","rain","snow"]: attribute = "prcp"
if attribute in ["temp","temps","temperature","temperatures","tmax","tmin","tavg"]: attribute = "temp"
YEARS_prcp = []
YEARS_prcp_asc = []
YEARS_prcpDAYS = []
YEARS_prcpDAYS_asc = []
YEARS_snow = []
YEARS_snow_asc = []
YEARS_snowDAYS = []
YEARS_snowDAYS_asc = []
YEARS_tavg = []
YEARS_tmax = []
YEARS_tmin = []
for y in [YR for YR in clmt if type(YR) == int]:
try:
YEARS_prcp.append(month_attr(y,round(sum(metclmt[y]["prcp"]),2)))
YEARS_prcpDAYS.append(month_attr(y,metclmt[y]["prcpDAYS"]))
if metclmt[y]["recordqty"] > excludeyear:
YEARS_prcp_asc.append(month_attr(y,round(sum(metclmt[y]["prcp"]),2)))
YEARS_prcpDAYS_asc.append(month_attr(y,metclmt[y]["prcpDAYS"]))
YEARS_snow.append(month_attr(y,round(sum(metclmt[y]["snow"]),1)))
if metclmt[y]["recordqty"] > excludeyear: YEARS_snow_asc.append(month_attr(y,round(sum(metclmt[y]["snow"]),1)))
YEARS_snowDAYS.append(month_attr(y,metclmt[y]["snowDAYS"]))
if metclmt[y]["recordqty"] > excludeyear: YEARS_snowDAYS_asc.append(month_attr(y,metclmt[y]["snowDAYS"]))
except:
pass
try:
if len(metclmt[y]["tempAVGlist"]) > excludeyear_tavg:
YEARS_tavg.append(month_attr(y,round(mean(metclmt[y]["tempAVGlist"]),1)))
except:
pass
try:
if len(metclmt[y]["tmax"]) > excludeyear:
YEARS_tmax.append(month_attr(y,round(mean(metclmt[y]["tmax"]),1)))
except:
pass
try:
if len(metclmt[y]["tmin"]) > excludeyear:
YEARS_tmin.append(month_attr(y,round(mean(metclmt[y]["tmin"]),1)))
except:
pass
#YEARS_prcp_asc = YEARS_prcp.copy()
YEARS_prcp.sort(key=lambda x:x.number,reverse=True)
YEARS_prcp_asc.sort(key=lambda x:x.number)
#YEARS_prcpDAYS_asc = YEARS_prcpDAYS.copy()
YEARS_prcpDAYS.sort(key=lambda x:x.number,reverse=True)
YEARS_prcpDAYS_asc.sort(key=lambda x:x.number)
YEARS_snow.sort(key=lambda x:x.number,reverse=True)
YEARS_snow_asc.sort(key=lambda x:x.number)
YEARS_snowDAYS.sort(key=lambda x:x.number,reverse=True)
YEARS_snowDAYS_asc.sort(key=lambda x:x.number)
YEARS_tavg_asc = YEARS_tavg.copy()
YEARS_tavg.sort(key=lambda x:x.number,reverse=True)
YEARS_tavg_asc.sort(key=lambda x:x.number)
YEARS_tmax_asc = YEARS_tmax.copy()
YEARS_tmax.sort(key=lambda x:x.number,reverse=True)
YEARS_tmax_asc.sort(key=lambda x:x.number)
YEARS_tmin_asc = YEARS_tmin.copy()
YEARS_tmin.sort(key=lambda x:x.number,reverse=True)
YEARS_tmin_asc.sort(key=lambda x:x.number)
if "yearStatsRun" in kwargs and kwargs["yearStatsRun"] == True:
prcpaschist = sorted(list(set([x.number for x in YEARS_prcp_asc])))
prcpdeschist = sorted(list(set([x.number for x in YEARS_prcp])),reverse=True)
prcpDAYSaschist = sorted(list(set([x.number for x in YEARS_prcpDAYS_asc])))
prcpDAYSdeschist = sorted(list(set([x.number for x in YEARS_prcpDAYS])),reverse=True)
snowaschist = sorted(list(set([x.number for x in YEARS_snow_asc])))
snowdeschist = sorted(list(set([x.number for x in YEARS_snow])),reverse=True)
snowDAYSaschist = sorted(list(set([x.number for x in YEARS_snowDAYS_asc])))
snowDAYSdeschist = sorted(list(set([x.number for x in YEARS_snowDAYS])),reverse=True)
tmaxaschist = sorted(list(set([x.number for x in YEARS_tmax_asc])))
tmaxdeschist = sorted(list(set([x.number for x in YEARS_tmax])),reverse=True)
tminaschist = sorted(list(set([x.number for x in YEARS_tmin_asc])))
tmindeschist = sorted(list(set([x.number for x in YEARS_tmin])),reverse=True)
tavgaschist = sorted(list(set([x.number for x in YEARS_tavg_asc])))
tavgdeschist = sorted(list(set([x.number for x in YEARS_tavg])),reverse=True)
return prcpaschist, prcpdeschist, prcpDAYSaschist, prcpDAYSdeschist, snowaschist, snowdeschist, snowDAYSaschist, snowDAYSdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist
else:
print("")
if attribute == "prcp":
print("{:^103}".format("Meteorological Annual Ranked Precipitation Amounts and Days"))
print("{:^103}".format("{}, {}".format(metclmt["station"],metclmt["station_name"])))
print("{:^103}".format("Years with >= {} day(s) of data".format(excludeyear+1)))
print("{:-^103}".format(""))
print("{:^69}|{:^33}".format("Rain","Snow"))
print("{:-^69}|{:-^33}".format("",""))
print("{:^18}|{:^18}|{:^15}|{:^15}|{:^17}|{:^15}".format("Wettest","Driest","Most Days","Least Days","Snowiest","Most Days"))
print("{:-^18}|{:-^18}|{:-^15}|{:-^15}|{:-^17}|{:-^15}".format("","","","","",""))
i = 1;j = 1;k = 1;l = 1;m = 1;n = 1
ranked_i = [];ranked_j = [];ranked_k = [];ranked_l = [];ranked_m = [];ranked_n = []
for x in range(min(len(YEARS_prcp),len(YEARS_prcp_asc),len(YEARS_prcpDAYS_asc),len(YEARS_prcpDAYS),len(YEARS_snow),len(YEARS_snowDAYS))):
if x == 0:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>3} ".format(
1,".",YEARS_prcp[x].year,"{:.2f}".format(YEARS_prcp[x].number),
1,".",YEARS_prcp_asc[x].year,"{:.2f}".format(YEARS_prcp_asc[x].number),
1,".",YEARS_prcpDAYS[x].year,YEARS_prcpDAYS[x].number,
1,".",YEARS_prcpDAYS_asc[x].year,YEARS_prcpDAYS_asc[x].number,
1 if YEARS_snow[x].number else "","." if YEARS_snow[x].number > 0 else " ",
YEARS_snow[x].year if YEARS_snow[x].number > 0 else "","{:.1f}".format(YEARS_snow[x].number) if YEARS_snow[x].number > 0 else "",
1 if YEARS_snowDAYS[x].number > 0 else "","." if YEARS_snowDAYS[x].number > 0 else " ",
YEARS_snowDAYS[x].year if YEARS_snowDAYS[x].number > 0 else "",YEARS_snowDAYS[x].number if YEARS_snowDAYS[x].number > 0 else ""))
ranked_i.append(i);ranked_j.append(j);ranked_k.append(k);ranked_l.append(l);ranked_m.append(m);ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if YEARS_prcp[x].number != YEARS_prcp[x-1].number: i += 1
if YEARS_prcp_asc[x].number != YEARS_prcp_asc[x-1].number: j += 1
if YEARS_prcpDAYS[x].number != YEARS_prcpDAYS[x-1].number: k += 1
if YEARS_prcpDAYS_asc[x].number != YEARS_prcpDAYS_asc[x-1].number: l += 1
if YEARS_snow[x].number != YEARS_snow[x-1].number: m += 1
if YEARS_snowDAYS[x].number != YEARS_snowDAYS[x-1].number: n += 1
if YEARS_prcp[x].number == 0: i = qty + 1
if YEARS_prcpDAYS[x].number == 0: k = qty + 1
if YEARS_snow[x].number == 0: m = qty + 1
if YEARS_snowDAYS[x].number == 0: n = qty + 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>3} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>3} ".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
YEARS_prcp[x].year if i <= qty else "","{:.2f}".format(YEARS_prcp[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
YEARS_prcp_asc[x].year if j <= qty else "","{:.2f}".format(YEARS_prcp_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
YEARS_prcpDAYS[x].year if k <= qty else "",YEARS_prcpDAYS[x].number if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
YEARS_prcpDAYS_asc[x].year if l <= qty else "",YEARS_prcpDAYS_asc[x].number if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
YEARS_snow[x].year if m <= qty else "","{:.1f}".format(YEARS_snow[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
YEARS_snowDAYS[x].year if n <= qty else "",YEARS_snowDAYS[x].number if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
if attribute == "temp":
print("{:^111}".format("Meteorological Annual Ranked Temperatures"))
print("{:^111}".format("{}, {}".format(metclmt["station"],metclmt["station_name"])))
print("{:^111}".format("Years with >= {} day(s) of data".format(excludeyear+1)))
print("{:-^111}".format(""))
print("{:^36}|{:^37}|{:^36}".format("AVG TEMP","TMAX","TMIN"))
print("{:-^36}|{:-^37}|{:-^36}".format("","",""))
print("{:^17}|{:^18}|{:^18}|{:^18}|{:^18}|{:^17}".format("Warmest","Coolest","Warmest","Coolest","Warmest","Coolest"))
print("{:-^17}|{:-^18}|{:-^18}|{:-^18}|{:-^18}|{:-^17}".format("","","","","",""))
i = 1; j = 1; k = 1; l = 1; m = 1; n = 1
ranked_i = []; ranked_j = []; ranked_k = []; ranked_l = []; ranked_m = []; ranked_n = []
for x in range(len(YEARS_tmax)):
if x == 0:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
1,".",YEARS_tavg[x].year,"{:.1f}".format(YEARS_tavg[x].number),
1,".",YEARS_tavg_asc[x].year,"{:.1f}".format(YEARS_tavg_asc[x].number),
1,".",YEARS_tmax[x].year,"{:.1f}".format(YEARS_tmax[x].number),
1,".",YEARS_tmax_asc[x].year,"{:.1f}".format(YEARS_tmax_asc[x].number),
1,".",YEARS_tmin[x].year,"{:.1f}".format(YEARS_tmin[x].number),
1,".",YEARS_tmin_asc[x].year,"{:.1f}".format(YEARS_tmin_asc[x].number)))
ranked_i.append(i); ranked_j.append(j); ranked_k.append(k); ranked_l.append(l); ranked_m.append(m); ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if YEARS_tavg[x].number != YEARS_tavg[x-1].number: i += 1
if YEARS_tavg_asc[x].number != YEARS_tavg_asc[x-1].number: j += 1
if YEARS_tmax[x].number != YEARS_tmax[x-1].number: k += 1
if YEARS_tmax_asc[x].number != YEARS_tmax_asc[x-1].number: l += 1
if YEARS_tmin[x].number != YEARS_tmin[x-1].number: m += 1
if YEARS_tmin_asc[x].number != YEARS_tmin_asc[x-1].number: n += 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
YEARS_tavg[x].year if i <= qty else "","{:.1f}".format(YEARS_tavg[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
YEARS_tavg_asc[x].year if j <= qty else "","{:.1f}".format(YEARS_tavg_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
YEARS_tmax[x].year if k <= qty else "","{:.1f}".format(YEARS_tmax[x].number) if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
YEARS_tmax_asc[x].year if l <= qty else "","{:.1f}".format(YEARS_tmax_asc[x].number) if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
YEARS_tmin[x].year if m <= qty else "","{:.1f}".format(YEARS_tmin[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
YEARS_tmin_asc[x].year if n <= qty else "","{:.1f}".format(YEARS_tmin_asc[x].number) if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
print("")
def customRank(attribute,qty,m1,d1,*date2,**kwargs):
"""Returns a list of rankings (maxs and mins) for all specified custom
period of time. Note that the order of the passed arguments are different
with this function than similar ranking functions. The attribute ("prcp"
or "temp") must be a string; the quantity (how many rankings you want), M1
(month), and D1 (day), and the optional M2 and D2 must be integers. If M2
and D2 are not given, 12-31 will be considered the final date of the
custom-period. The attribute ("prcp" or "temp") must be in string format.
The quantity, denoting how many rankings you desire, must be an integer.
If the end day given occurs before the start day in the calendar year, the
end day of the following year will be used.
customRank(attribute,quantity,M1,D1,*[M2,D2])
OPT *args: M2,D2 --> These optional entries represent the ending month,
and day of the period
EXAMPLE: customRank("temp",10,11,1) -> Returns the "Top 10" Temperature-
based Rankings for the custom
period of Nov 1 thru Dec 31.
EXAMPLE: customRank("prcp",10,9,1,3,31) -> Returns the "Top 10"
Temperature-based Rankings for
the frame of Sept 1 thru Mar 31
"""
class e_attr:
def __init__(self,y,number):
self.year = y
self.number = number
if len(clmt) == 0: return print("* OOPS! Run the clmtAnalyze function first.")
valid_yrs = [x for x in clmt.keys() if type(x) == int]
valid_yrs.sort()
if any(type(x) != int for x in [m1,d1]): return print("*** OOPS! Ensure that only integers are entered ***")
if len(date2) == 0: pass
elif len(date2) != 2: return print("*** OOPS! For the 2nd (optional) date, ensure only a Month and Date are entered ***")
elif any(type(x) != int for x in [date2[0],date2[1]]): return print("*** OOPS! Ensure that only integers are entered ***")
if attribute not in ["temp","temps","temperature","temperatures","tmax","tmin","tavg","prcp","precip","rain","snow"]:
return print("* OOPS! Attribute must be 'temp' or 'prcp'. Try again!")
if type(qty) != int or qty > 50 or qty < 5: return print("* SORRY! Ensure desired quantity is an integer in the range [5,50]")
if attribute in ["prcp","precip","rain","snow"]: attribute = "prcp"
if attribute in ["temp","temps","temperature","temperatures","tmax","tmin","tavg"]: attribute = "temp"
if len(date2) == 2:
m2 = date2[0]
d2 = date2[1]
else:
m2 = 12
d2 = 31
if m2 == m1:
if d2 == d1: return print("*** OOPS! Ensure different dates! ***")
if m1 == 2 and d1 == 29: d1 = 28
if m2 == 2 and d2 == 29: d2 = 28
# Determine total length of period (used for exclusion calculation)
s = datetime.date(1900,m1,d1)
test = datetime.date(1900,m2,d2)
if test > s: e = test
else: e = datetime.date(1901,m2,d2)
timelength = (e - s).days + 1
if timelength <= 5: EXCLD = timelength-1
elif timelength == 6: EXCLD = 4
elif timelength == 7: EXCLD = excludeweek
elif timelength == 8: EXCLD = excludeweek
elif timelength in [28,29,30,31]: EXCLD = excludemonth
elif timelength >= 350: EXCLD = excludeyear
else: EXCLD = round(excludecustom * timelength)
e = {} # Will hold the date-to-date (represented by a parent year) stats
for YYYY in valid_yrs:
startday = datetime.date(YYYY,m1,d1)
incr_day = startday
if m2 < m1: endday = datetime.date(YYYY+1,m2,d2) # if end month is less, the results will bleed into the following year
elif m2 == m1: # Deals with if the months of the dates are exactly the same
if d2 < d1: endday = datetime.date(YYYY+1,m2,d2) # like above, if month is the same, but date is less, results will bleed into following year
else: endday = datetime.date(YYYY,m2,d2) # OTHERWISE, it is assumed the same year
else: endday = datetime.date(YYYY,m2,d2) # If month2 is > than month 1, the active year will be used
if endday.year > max(valid_yrs): break
#if YYYY not in e:
e[YYYY] = {"recordqty":0,
"prcp":[],"prcpDAYS":0,"snow":[],"snowDAYS":0,
"tempAVGlist":[],"tmax":[],"tmin":[]}
while incr_day <= endday:
y = incr_day.year; m = incr_day.month; d = incr_day.day
if y in clmt and m in clmt[y] and d in clmt[y][m]:
e[YYYY]["recordqty"] += 1
# PRCP
if clmt[y][m][d].prcpQ in ignoreflags and clmt[y][m][d].prcp not in ["9999","-9999",""]:
if float(clmt[y][m][d].prcp) > 0: e[YYYY]["prcp"].append(round(float(clmt[y][m][d].prcp),2))
if float(clmt[y][m][d].prcp) > 0 or clmt[y][m][d].prcpM == "T": e[YYYY]["prcpDAYS"] += 1
if clmt[y][m][d].prcpQ in ignoreflags and clmt[y][m][d].prcp == "" and clmt[y][m][d].prcpM == "T": e[YYYY]["prcpDAYS"] += 1
# SNOW
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow not in ["9999","-9999",""]:
if float(clmt[y][m][d].snow) > 0: e[YYYY]["snow"].append(round(float(clmt[y][m][d].snow),2))
if float(clmt[y][m][d].snow) > 0 or clmt[y][m][d].snowM == "T": e[YYYY]["snowDAYS"] += 1
if clmt[y][m][d].snowQ in ignoreflags and clmt[y][m][d].snow == "" and clmt[y][m][d].snowM == "T": e[YYYY]["snowDAYS"] += 1
# TAVG
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""] and clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""] and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin):
e[YYYY]["tempAVGlist"].append(int(clmt[y][m][d].tmax))
e[YYYY]["tempAVGlist"].append(int(clmt[y][m][d].tmin))
# TMAX
if clmt[y][m][d].tmaxQ in ignoreflags and clmt[y][m][d].tmax not in ["9999","-9999",""]:
if clmt[y][m][d].tmin != "" and int(clmt[y][m][d].tmax) >= int(clmt[y][m][d].tmin):
e[YYYY]["tmax"].append(int(clmt[y][m][d].tmax))
# TMIN
if clmt[y][m][d].tminQ in ignoreflags and clmt[y][m][d].tmin not in ["9999","-9999",""]:
if clmt[y][m][d].tmax != "" and int(clmt[y][m][d].tmin) <= int(clmt[y][m][d].tmax):
e[YYYY]["tmin"].append(int(clmt[y][m][d].tmin))
incr_day += datetime.timedelta(days=1) # GO ON TO TEST NEXT DAY
E_prcp = []
E_prcp_asc = []
E_prcpDAYS = []
E_prcpDAYS_asc = []
E_snow = []
E_snow_asc = []
E_snowDAYS = []
E_snowDAYS_asc = []
E_tavg = []
E_tmax = []
E_tmin = []
for YYYY in e:
try:
E_prcp.append(e_attr(YYYY,round(sum(e[YYYY]["prcp"]),2)))
E_prcpDAYS.append(e_attr(YYYY,e[YYYY]["prcpDAYS"]))
if e[YYYY]["recordqty"] > EXCLD:
E_prcp_asc.append(e_attr(YYYY,round(sum(e[YYYY]["prcp"]),2)))
E_prcpDAYS_asc.append(e_attr(YYYY,e[YYYY]["prcpDAYS"]))
E_snow.append(e_attr(YYYY,round(sum(e[YYYY]["snow"]),1)))
if e[YYYY]["recordqty"] > EXCLD: E_snow_asc.append(e_attr(YYYY,round(sum(e[YYYY]["snow"]),1)))
E_snowDAYS.append(e_attr(YYYY,e[YYYY]["snowDAYS"]))
if e[YYYY]["recordqty"] > EXCLD: E_snowDAYS_asc.append(e_attr(YYYY,e[YYYY]["snowDAYS"]))
except:
pass
try:
if len(e[YYYY]["tempAVGlist"]) > EXCLD * 2:
E_tavg.append(e_attr(YYYY,round(mean(e[YYYY]["tempAVGlist"]),1)))
except:
pass
try:
if len(e[YYYY]["tmax"]) > EXCLD:
E_tmax.append(e_attr(YYYY,round(mean(e[YYYY]["tmax"]),1)))
except:
pass
try:
if len(e[YYYY]["tmin"]) > EXCLD:
E_tmin.append(e_attr(YYYY,round(mean(e[YYYY]["tmin"]),1)))
except:
pass
E_LENGTHS_OF_ALL = []
#E_prcp_asc = E_prcp.copy()
E_prcp.sort(key=lambda x:x.number,reverse=True); E_LENGTHS_OF_ALL.append(len(E_prcp))
E_prcp_asc.sort(key=lambda x:x.number); E_LENGTHS_OF_ALL.append(len(E_prcp_asc))
#E_prcpDAYS_asc = E_prcpDAYS.copy()
E_prcpDAYS.sort(key=lambda x:x.number,reverse=True); E_LENGTHS_OF_ALL.append(len(E_prcpDAYS))
E_prcpDAYS_asc.sort(key=lambda x:x.number); E_LENGTHS_OF_ALL.append(len(E_prcpDAYS_asc))
E_snow.sort(key=lambda x:x.number,reverse=True); E_LENGTHS_OF_ALL.append(len(E_snow))
E_snow_asc.sort(key=lambda x:x.number); E_LENGTHS_OF_ALL.append(len(E_snow_asc))
E_snowDAYS.sort(key=lambda x:x.number,reverse=True); E_LENGTHS_OF_ALL.append(len(E_snowDAYS))
E_snowDAYS_asc.sort(key=lambda x:x.number); E_LENGTHS_OF_ALL.append(len(E_snowDAYS_asc))
E_tavg_asc = E_tavg.copy()
E_tavg.sort(key=lambda x:x.number,reverse=True); E_LENGTHS_OF_ALL.append(len(E_tavg))
E_tavg_asc.sort(key=lambda x:x.number); E_LENGTHS_OF_ALL.append(len(E_tavg_asc))
E_tmax_asc = E_tmax.copy()
E_tmax.sort(key=lambda x:x.number,reverse=True); E_LENGTHS_OF_ALL.append(len(E_tmax))
E_tmax_asc.sort(key=lambda x:x.number); E_LENGTHS_OF_ALL.append(len(E_tmax_asc))
E_tmin_asc = E_tmin.copy()
E_tmin.sort(key=lambda x:x.number,reverse=True); E_LENGTHS_OF_ALL.append(len(E_tmin))
E_tmin_asc.sort(key=lambda x:x.number); E_LENGTHS_OF_ALL.append(len(E_tmin_asc))
if "customStatsRun" in kwargs and kwargs["customStatsRun"] == True:
prcpaschist = sorted(list(set([x.number for x in E_prcp_asc])))
prcpdeschist = sorted(list(set([x.number for x in E_prcp])),reverse=True)
prcpDAYSaschist = sorted(list(set([x.number for x in E_prcpDAYS_asc])))
prcpDAYSdeschist = sorted(list(set([x.number for x in E_prcpDAYS])),reverse=True)
snowaschist = sorted(list(set([x.number for x in E_snow_asc])))
snowdeschist = sorted(list(set([x.number for x in E_snow])),reverse=True)
snowDAYSaschist = sorted(list(set([x.number for x in E_snowDAYS_asc])))
snowDAYSdeschist = sorted(list(set([x.number for x in E_snowDAYS])),reverse=True)
tmaxaschist = sorted(list(set([x.number for x in E_tmax_asc])))
tmaxdeschist = sorted(list(set([x.number for x in E_tmax])),reverse=True)
tminaschist = sorted(list(set([x.number for x in E_tmin_asc])))
tmindeschist = sorted(list(set([x.number for x in E_tmin])),reverse=True)
tavgaschist = sorted(list(set([x.number for x in E_tavg_asc])))
tavgdeschist = sorted(list(set([x.number for x in E_tavg])),reverse=True)
return prcpaschist, prcpdeschist, prcpDAYSaschist, prcpDAYSdeschist, snowaschist, snowdeschist, snowDAYSaschist, snowDAYSdeschist, tmaxaschist, tmaxdeschist, tminaschist, tmindeschist, tavgaschist, tavgdeschist
else:
print("")
if attribute == "prcp":
print("{:^100}".format("Ranked Precipitation Amounts and Days for {} {} thru {} {}".format(calendar.month_abbr[startday.month],startday.day,calendar.month_abbr[endday.month],endday.day)))
print("{:^103}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
if EXCLD <= 5: print("{:^103}".format("Periods with {} Total days of Data".format(EXCLD+1)))
else: print("{:^103}".format("Periods with >= {} Day(s) of Data".format(EXCLD+1)))
print("{:-^103}".format(""))
print("{:^70} {:^33}".format("Rain","Snow"))
print("{:-^70} {:-^33}".format("",""))
print("{:^18}|{:^18}|{:^15}|{:^15}|{:^17}|{:^15}".format("Wettest","Driest","Most Days","Least Days","Snowiest","Most Days"))
print("{:-^18}|{:-^18}|{:-^15}|{:-^15}|{:-^17}|{:-^15}".format("","","","","",""))
i = 1;j = 1;k = 1;l = 1;m = 1;n = 1
printed_j = 0; printed_l = 0
ranked_i = [];ranked_j = [];ranked_k = [];ranked_l = [];ranked_m = [];ranked_n = []
for x in range(min(E_LENGTHS_OF_ALL)):
if x == 0:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:3} | {:2}{} {:4} {:3} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>3} ".format(
1,".",E_prcp[x].year,"{:.2f}".format(E_prcp[x].number),
1,".",E_prcp_asc[x].year,"{:.2f}".format(E_prcp_asc[x].number),
1,".",E_prcpDAYS[x].year,E_prcpDAYS[x].number,
1,".",E_prcpDAYS_asc[x].year,E_prcpDAYS_asc[x].number,
1 if E_snow[x].number else "","." if E_snow[x].number > 0 else " ",
E_snow[x].year if E_snow[x].number > 0 else "","{:.1f}".format(E_snow[x].number) if E_snow[x].number > 0 else "",
1 if E_snowDAYS[x].number > 0 else "","." if E_snowDAYS[x].number > 0 else " ",
E_snowDAYS[x].year if E_snowDAYS[x].number > 0 else "",E_snowDAYS[x].number if E_snowDAYS[x].number > 0 else ""))
ranked_i.append(i);ranked_j.append(j);ranked_k.append(k);ranked_l.append(l);ranked_m.append(m);ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty:
ranked_j.append(j)
#printed_j += 1
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty:
ranked_l.append(l)
#printed_l += 1
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if E_prcp[x].number != E_prcp[x-1].number: i += 1
if E_prcp_asc[x].number != E_prcp_asc[x-1].number: j += 1
if E_prcpDAYS[x].number != E_prcpDAYS[x-1].number: k += 1
if E_prcpDAYS_asc[x].number != E_prcpDAYS_asc[x-1].number: l += 1
if E_snow[x].number != E_snow[x-1].number: m += 1
if E_snowDAYS[x].number != E_snowDAYS[x-1].number: n += 1
if E_prcp[x].number == 0: i = qty + 1
#if printed_j == len(valid_yrs)-10: j = qty + 1
if E_prcpDAYS[x].number == 0: k = qty + 1
#if printed_l == len(valid_yrs)-10: l = qty + 1
if E_snow[x].number == 0: m = qty + 1
if E_snowDAYS[x].number == 0: n = qty + 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print(" {:2}{} {:4} {:>6} | {:2}{} {:4} {:>6} | {:2}{} {:4} {:3} | {:2}{} {:4} {:3} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>3} ".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
E_prcp[x].year if i <= qty else "","{:.2f}".format(E_prcp[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
E_prcp_asc[x].year if j <= qty else "","{:.2f}".format(E_prcp_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
E_prcpDAYS[x].year if k <= qty else "",E_prcpDAYS[x].number if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
E_prcpDAYS_asc[x].year if l <= qty else "",E_prcpDAYS_asc[x].number if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
E_snow[x].year if m <= qty else "","{:.1f}".format(E_snow[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
E_snowDAYS[x].year if n <= qty else "",E_snowDAYS[x].number if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
if attribute == "temp":
print("{:^111}".format("Ranked Temperatures for {} {} thru {} {}".format(calendar.month_abbr[startday.month],startday.day,calendar.month_abbr[endday.month],endday.day)))
print("{:^111}".format("{}, {}".format(clmt["station"],clmt["station_name"])))
print("{:^111}".format("Periods with >= {} Day(s) of Data".format(EXCLD+1)))
print("{:-^111}".format(""))
print("{:^36}|{:^37}|{:^36}".format("AVG TEMP","TMAX","TMIN"))
print("{:-^36}|{:-^37}|{:-^36}".format("","",""))
print("{:^17}|{:^18}|{:^18}|{:^18}|{:^18}|{:^17}".format("Warmest","Coolest","Warmest","Coolest","Warmest","Coolest"))
print("{:-^17}|{:-^18}|{:-^18}|{:-^18}|{:-^18}|{:-^17}".format("","","","","",""))
i = 1; j = 1; k = 1; l = 1; m = 1; n = 1
ranked_i = []; ranked_j = []; ranked_k = []; ranked_l = []; ranked_m = []; ranked_n = []
for x in range(len(E_tmax)):
if x == 0:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
1,".",E_tavg[x].year,"{:.1f}".format(E_tavg[x].number),
1,".",E_tavg_asc[x].year,"{:.1f}".format(E_tavg_asc[x].number),
1,".",E_tmax[x].year,"{:.1f}".format(E_tmax[x].number),
1,".",E_tmax_asc[x].year,"{:.1f}".format(E_tmax_asc[x].number),
1,".",E_tmin[x].year,"{:.1f}".format(E_tmin[x].number),
1,".",E_tmin_asc[x].year,"{:.1f}".format(E_tmin_asc[x].number)))
ranked_i.append(i); ranked_j.append(j); ranked_k.append(k); ranked_l.append(l); ranked_m.append(m); ranked_n.append(n)
else:
if i not in ranked_i and i <= qty: ranked_i.append(i)
if j not in ranked_j and j <= qty: ranked_j.append(j)
if k not in ranked_k and k <= qty: ranked_k.append(k)
if l not in ranked_l and l <= qty: ranked_l.append(l)
if m not in ranked_m and m <= qty: ranked_m.append(m)
if n not in ranked_n and n <= qty: ranked_n.append(n)
if E_tavg[x].number != E_tavg[x-1].number: i += 1
if E_tavg_asc[x].number != E_tavg_asc[x-1].number: j += 1
if E_tmax[x].number != E_tmax[x-1].number: k += 1
if E_tmax_asc[x].number != E_tmax_asc[x-1].number: l += 1
if E_tmin[x].number != E_tmin[x-1].number: m += 1
if E_tmin_asc[x].number != E_tmin_asc[x-1].number: n += 1
if i <= qty or j <= qty or k <= qty or l <= qty or m <= qty or n <= qty:
print("{:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5} | {:2}{} {:4} {:>5}".format(
i if i not in ranked_i and i <= qty else "","." if i not in ranked_i and i <= qty else " ",
E_tavg[x].year if i <= qty else "","{:.1f}".format(E_tavg[x].number) if i <= qty else "",
j if j not in ranked_j and j <= qty else "","." if j not in ranked_j and j <= qty else " ",
E_tavg_asc[x].year if j <= qty else "","{:.1f}".format(E_tavg_asc[x].number) if j <= qty else "",
k if k not in ranked_k and k <= qty else "","." if k not in ranked_k and k <= qty else " ",
E_tmax[x].year if k <= qty else "","{:.1f}".format(E_tmax[x].number) if k <= qty else "",
l if l not in ranked_l and l <= qty else "","." if l not in ranked_l and l <= qty else " ",
E_tmax_asc[x].year if l <= qty else "","{:.1f}".format(E_tmax_asc[x].number) if l <= qty else "",
m if m not in ranked_m and m <= qty else "","." if m not in ranked_m and m <= qty else " ",
E_tmin[x].year if m <= qty else "","{:.1f}".format(E_tmin[x].number) if m <= qty else "",
n if n not in ranked_n and n <= qty else "","." if n not in ranked_n and n <= qty else " ",
E_tmin_asc[x].year if n <= qty else "","{:.1f}".format(E_tmin_asc[x].number) if n <= qty else ""))
if i > qty and j > qty and k > qty and l > qty and m > qty and n > qty: break
print("")
def allDayRank(attribute,qty,**kw):
"""Returns a list of rankings, comparing only specific days to one
another. If season keyword is present, month keyword will be ignored. If
season and year are specified, only results from the season from the
specific year will be used. If year and month are specified, only data
from that time period will be used. If only month is specified, all data
occurring from that month, regardless of year, will be used.
allDayRank(attribute,quantity,**kwargs)
Accepted Attributes:
"prcp", "snow", "snwd", "tmax", "tmin", "tavg"
Keyword Arguments (displayed in heirarchal order):
season="season" -> limit season <"spring"|"summer"|"fall"|"winter">
year=YYYY -> limit results to a specific year
month=M -> limit results to a specific month
ascending=False -> alters order of data (only affects temp attrs)
custom=[m1,d1,m2,d2] -> limits results if the record falls within
the date-range given
EXAMPLE: allDayRank("snow",10)
-> top 10 ranks all days acc. to snow
allDayRank("prcp",15,season="summer")
-> top 15 rain days in summer
allDayRank("tmax",10,season="fall",year=2005)
-> top 10 warmest daily highs from Fall 2005
allDayRank("tmin",10,year=2009,ascending=True)
-> top 10 coolest daily lows in 2009
allDayRank("prcp",20,custom=[12,3,5,1])
-> top 20 rain-days between Dec3 and May1
"""
# clmt_vars_days = {"prcp":{},"snow":{},"snwd":{},"tavg":{},"tmax":{},"tmin":{}}
# clmt_vars_days["prcp"][amount] = [list, of, days, that, had, that, value]
# consider adding a "finite" kwarg. This setting would only report the quantity of days that a match was made rather than a potentially long list of days
# consider adding an "order" or "reverse" kwarg
valid_yrs = sorted([x for x in clmt.keys() if type(x) == int])
valid_metyrs = sorted([x for x in metclmt.keys() if type(x) == int])
hascustom = False
hasseason = False
hasyear = False
hasmonth = False
daysinmonths = ["_",31,28,31,30,31,30,31,31,30,31,30,31] # used to quickly determine validity of dates entered with custom keyword
#ERROR CHECKS
if attribute not in ["prcp","snow","snwd","tmax","tmin","tavg"]: return print('OOPS! "{}" is an Invalid Attribute. Try Again! Valid Attributes: "prcp","snow","snwd","tmax","tmin","tavg"'.format(attribute))
if type(qty) != int: return print("OOPS! Ensure the quantity is an integer! Try again!")
# Custom Date Range
if "custom" in kw:
try:
m1 = kw["custom"][0]
d1 = kw["custom"][1]
m2 = kw["custom"][2]
d2 = kw["custom"][3]
except:
return print("OOPS! Something is wrong with the dates. Ensure a format of [m1,d1,m2,d2]")
if type(kw["custom"]) not in [list,tuple]: return print("OOPS! Pass your custom range in a list. ex: [m1,d1,m2,d2]")
elif any(type(x) != int for x in kw["custom"]) or len(kw["custom"]) != 4: return print("OOPS! Ensure all variables passed in your list are integers representing month/dates of interest and that a start/end month day sets are included, ex: [m1,d1,m2,d2]")
elif (1 <= m1 <= 12) == False or (1 <= m2 <= 12) == False: return print("OOPS! An invalid month was entered.")
elif (d1 <= 0 or d1 > daysinmonths[m1]) or (d2 <= 0 or d2 > daysinmonths[m2]): return print("OOPS! One or both of the dates are invalid.")
elif m1 == m2 and d1 == d2: return print("OOPS! The first and second dates cannot be alike.")
hascustom = True
# If February 29, we want to default to the 28th
if m1 == 2 and d1 == 29: d1 = 28
if m2 == 2 and d2 == 29: d2 = 28
# Specified Season
elif "season" in kw:
if kw["season"].lower() not in ["spring","summer","fall","winter"]: return print('OOPS! "{}" is an invalid season. Try again! Valid Seasons (all lower case):"spring","summer","fall","winter"'.format(kw["season"]))
hasseason = True
# for specifying a year of a season
if "year" in kw:
hasyear = True
YEAR = int(kw["year"])
if YEAR not in valid_yrs: return print("OOPS! No data for the year {} found. Try again!".format(YEAR))
# Specifying a year
elif "year" in kw:
hasyear = True
YEAR = int(kw["year"])
if YEAR not in clmt: return print("OOPS! No data for the year {} found. Try again!".format(YEAR))
# Focusing on a specific month in a specific year
if "month" in kw:
hasmonth = True
MONTH = int(kw["month"])
if MONTH not in range(1,12+1): return print("OOPS! Invalid Month. Try again!")
if MONTH not in clmt[YEAR]: return print("OOPS! No data for {} {} found. Try again!".format(calendar.month_name[MONTH],YEAR))
# Specifying a month
elif "month" in kw:
hasmonth = True
MONTH = int(kw["month"])
if MONTH not in range(1,12+1): return print("OOPS! Invalid Month. Try again!")
##########################
r = 0
printed = [] # Will hold the printed rankings
print("\n-----------------------------------------------")
# HEADER ------------------
if hascustom == True: print("Top {} Daily {} Records for the Range of {} {} thru {} {}".format(
qty,attribute.upper(),d1,calendar.month_abbr[m1].upper(),
d2,calendar.month_abbr[m2].upper()
))
elif hasseason == True:
if hasyear == True: print("Top {} Daily {} Records for {} {}".format(qty,attribute.upper(),kw["season"].capitalize(),YEAR))
else: print("Top {} Daily {} Records for {}".format(qty,attribute.upper(),kw["season"].capitalize()))
elif hasyear == True:
if hasmonth == True: print("Top {} Daily {} Records for {} {}".format(qty,attribute.upper(),calendar.month_name[MONTH],YEAR))
else: print("Top {} Daily {} Records for {}".format(qty,attribute.upper(),YEAR))
elif hasmonth == True: print("Top {} Daily {} Records for {}".format(qty,attribute.upper(),calendar.month_name[MONTH]))
else: print("Top {} Daily {} Records for All-Time".format(qty,attribute.upper()))
# -------------------------
# -------------------------
print("{}, {}".format(clmt["station"],clmt["station_name"]))
if "ascending" in kw and attribute in ["tmax","tmin","tavg"]:
if kw["ascending"] == True:
keys = sorted([key for key in clmt_vars_days[attribute].keys()])
print("--- Coolest to Warmest ---")
else:
keys = sorted([key for key in clmt_vars_days[attribute].keys()],reverse=True)
if attribute in ["tmax","tmin","tavg"]: print("--- Warmest to Coolest ---")
print("-----------------------------------------------")
# -------------------------
validated = {}
# 12-3 to 1,10
# (1959,1,7)
if hascustom == True:
for x in keys:
for y in range(len(clmt_vars_days[attribute][x])):
# When the 2nd month refers to an earlier month(or the same)
if datetime.date(2100,m2,d2) < datetime.date(2100,m1,d1):
try:
if (clmt_vars_days[attribute][x][y] >= datetime.date(clmt_vars_days[attribute][x][y].year,m1,d1)) or (clmt_vars_days[attribute][x][y] <= datetime.date(clmt_vars_days[attribute][x][y].year,m2,d2)):
if x not in validated: validated[x] = [clmt_vars_days[attribute][x][y]]
else: validated[x].append(clmt_vars_days[attribute][x][y])
except Exception as e:
pass
# When the 2nd month is later than the first month
else:
if datetime.date(clmt_vars_days[attribute][x][y].year,m1,d1) <= clmt_vars_days[attribute][x][y] <= datetime.date(clmt_vars_days[attribute][x][y].year,m2,d2):
if x not in validated: validated[x] = [clmt_vars_days[attribute][x][y]]
else: validated[x].append(clmt_vars_days[attribute][x][y])
elif hasseason == True and hasyear == False: # Only assess a season
# metclmt[y][s]["valid"] = [3,4,5]
# clmt_vars_days[attribute][x][y]
for x in keys:
for y in range(len(clmt_vars_days[attribute][x])):
if clmt_vars_days[attribute][x][y].month <= 2 and clmt_vars_days[attribute][x][y].year-1 in metclmt and clmt_vars_days[attribute][x][y].month in metclmt[clmt_vars_days[attribute][x][y].year-1][kw["season"]]["valid"]:
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
elif clmt_vars_days[attribute][x][y].month >= 3 and clmt_vars_days[attribute][x][y].month in metclmt[clmt_vars_days[attribute][x][y].year][kw["season"]]["valid"]:
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
elif hasseason == True and hasyear == True: # Only assess a season of a particular year
# metclmt[y][s]["valid"] = [3,4,5]
# clmt_vars_days[attribute][x][y]
for x in keys:
for y in range(len(clmt_vars_days[attribute][x])):
if kw["season"].lower() == "winter":
if clmt_vars_days[attribute][x][y].month in metclmt[clmt_vars_days[attribute][x][y].year][kw["season"]]["valid"]:
if clmt_vars_days[attribute][x][y].month in [1,2] and clmt_vars_days[attribute][x][y].year == YEAR+1:
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
if clmt_vars_days[attribute][x][y].month == 12 and clmt_vars_days[attribute][x][y].year == YEAR:
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
else:
if clmt_vars_days[attribute][x][y].year == YEAR and clmt_vars_days[attribute][x][y].month in metclmt[clmt_vars_days[attribute][x][y].year][kw["season"]]["valid"]:
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
elif hasyear == True and hasmonth == False: # Only assess a particular year
for x in keys:
for y in range(len(clmt_vars_days[attribute][x])):
if clmt_vars_days[attribute][x][y].year == YEAR:
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
elif hasyear == True and hasmonth == True: # Only assess a particular month of a particular year
for x in keys:
for y in range(len(clmt_vars_days[attribute][x])):
if clmt_vars_days[attribute][x][y].year == YEAR and clmt_vars_days[attribute][x][y].month == MONTH:
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
elif hasmonth == True: # Only assess data from a particular month
for x in keys:
for y in range(len(clmt_vars_days[attribute][x])):
if clmt_vars_days[attribute][x][y].month == MONTH:
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
else: # Assesses data from the entire record
for x in keys:
for y in range(len(clmt_vars_days[attribute][x])):
if x not in validated:
validated[x] = [clmt_vars_days[attribute][x][y]]
else:
validated[x].append(clmt_vars_days[attribute][x][y])
for x in validated:
r += 1
if r > qty: break
for y in range(len(validated[x])):
if attribute == "prcp": print("{:>2}{} {:>5.2f} - {}".format(r if r not in printed else " ","." if r not in printed else " ",x,validated[x][y]))
elif attribute in ["snow","snwd","tavg"]: print("{:>2}{} {:>5.1f} - {}".format(r if r not in printed else " ","." if r not in printed else " ",x,validated[x][y]))
else: print("{:>2}{} {:>3} - {}".format(r if r not in printed else " ","." if r not in printed else " ",x,validated[x][y]))
if r not in printed: printed.append(r)
#-------------------------------------------
print("")
def allMonthRank(attribute,qty,**kw):
"""Returns a list of rankings, comparing only specific months to one
another. Optional season kewyord included to limit results to a specific
season. Optional ascending keyword, if set to True, will reverse the
order of results
allMonthRank(attribute,quantity,**kwargs)
Accepted Attributes:
"prcp", "prcpDAYS", "snow", "snowDAYS", "snwd", "snwdDAYS",
"tmax","tmin", "tavg"
Keyword Arguments (Optional):
season="season" -> limit season <"spring"|"summer"|"fall"|"winter">
ascending=False -> alters order of data (only affects temp or prcp
attrs)
EXAMPLE: allMonthRank("snow",10)
-> top 10 ranks all months acc. to snow
allMonthRank("prcp",15,season="summer")
-> top 15 rain months in summer
allMonthRank("tmin",10,ascending=True)
-> top 10 coolest months based on avg lows
"""
valid_yrs = sorted([x for x in clmt.keys() if type(x) == int])
valid_metyrs = sorted([x for x in metclmt.keys() if type(x) == int])
valid_season = {"spring":[3,4,5],"summer":[6,7,8],"fall":[9,10,11],"winter":[12,1,2]}
hasseason = False
#ERROR CHECKS
if attribute not in ["prcp","prcpDAYS","snow","snowDAYS","snwd","snwdDAYS","tmax","tmin","tavg"]: return print('OOPS! "{}" is an Invalid Attribute. Try Again! Valid Attributes: "prcp","snow",,"snowDAYS","snwd","snwdDAYS","tmax","tmin","tavg"'.format(attribute))
if type(qty) != int: return print("OOPS! Ensure the quantity is an integer! Try again!")
# Specified Season
if "season" in kw:
if kw["season"].lower() not in ["spring","summer","fall","winter"]: return print('OOPS! "{}" is an invalid season. Try again! Valid Seasons (all lower case):"spring","summer","fall","winter"'.format(kw["season"]))
hasseason = True
##########################
r = 0
printed = [] # Will hold the printed rankings
appendr = False
print("\n-----------------------------------------------")
# HEADER ------------------
if hasseason == True:
print("Top {} Monthly {} Records Inclusive of {} Months Only".format(qty,attribute.upper(),kw["season"].capitalize()))
else: print("Top {} Monthly {} Records for All-Time".format(qty,attribute.upper()))
# -------------------------
print("{}, {}".format(clmt["station"],clmt["station_name"]))
if "ascending" in kw and kw["ascending"] == True and attribute not in ["snow","snowDAYS","snwd","snwdDAYS"]:
keys = sorted([key for key in clmt_vars_months[attribute].keys()])
if attribute in ["tmax","tmin","tavg"]: print("--- Coolest to Warmest ---")
if attribute in ["prcp"]: print("--- Driest to Wettest ---")
else:
keys = sorted([key for key in clmt_vars_months[attribute].keys()],reverse=True)
if attribute in ["tmax","tmin","tavg"]: print("--- Warmest to Coolest ---")
if attribute in ["prcp"]: print("--- Wettest to Driest ---")
if attribute in ["prcpDAYS","snow","snowDAYS","snwd","snwdDAYS"]: print("--- Greatest to Least ---")
print("-----------------------------------------------")
# -------------------------
if hasseason == True: # Only assess a season
# metclmt[y][s]["valid"] = [3,4,5]
# clmt_vars_days[attribute][x][y]
metkeys = {}
for x in keys:
for y in range(len(clmt_vars_months[attribute][x])):
if clmt_vars_months[attribute][x][y].month in valid_season[kw["season"]]:
if x not in metkeys:
metkeys[x] = [clmt_vars_months[attribute][x][y]]
else:
metkeys[x].append(clmt_vars_months[attribute][x][y])
#for x in metkeys:
#print("{} - {}".format(x,metkeys[x]))
for x in metkeys:
r += 1
if r > qty: break
for y in range(len(metkeys[x])):
if metkeys[x][y].month <= 2:
if attribute == "tavg":
if "ascending" not in kw or "ascending" in kw and kw["ascending"] == False or "ascending" in kw and kw["ascending"] == True and clmt[metkeys[x][y].year][metkeys[x][y].month]["recordqty"] > excludemonth * 2:
appendr = True
print("{:>2}{} {:6.1f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[metkeys[x][y].month],metkeys[x][y].year))
else:
if "ascending" not in kw or "ascending" in kw and kw["ascending"] == False or "ascending" in kw and kw["ascending"] == True and clmt[metkeys[x][y].year][metkeys[x][y].month]["recordqty"] > excludemonth:
appendr = True
if attribute == "prcp":
print("{:>2}{} {:6.2f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[metkeys[x][y].month],metkeys[x][y].year))
elif attribute in ["prcpDAYS","snowDAYS","snwdDAYS"]:
print("{:>2}{} {:2} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[metkeys[x][y].month],metkeys[x][y].year))
else:
print("{:>2}{} {:6.1f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[metkeys[x][y].month],metkeys[x][y].year))
else:
if attribute == "tavg":
if "ascending" not in kw or "ascending" in kw and kw["ascending"] == False or "ascending" in kw and kw["ascending"] == True and clmt[metkeys[x][y].year][metkeys[x][y].month]["recordqty"] > excludemonth * 2:
appendr = True
print("{:>2}{} {:6.1f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[metkeys[x][y].month],metkeys[x][y].year))
else:
if "ascending" not in kw or "ascending" in kw and kw["ascending"] == False or "ascending" in kw and kw["ascending"] == True and clmt[metkeys[x][y].year][metkeys[x][y].month]["recordqty"] > excludemonth:
appendr = True
if attribute == "prcp":
print("{:>2}{} {:6.2f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[metkeys[x][y].month],metkeys[x][y].year))
elif attribute in ["prcpDAYS","snowDAYS","snwdDAYS"]:
print("{:>2}{} {:2} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[metkeys[x][y].month],metkeys[x][y].year))
else:
print("{:>2}{} {:6.1f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[metkeys[x][y].month],metkeys[x][y].year))
if r not in printed and appendr == True:
printed.append(r)
appendr = False
else: # Assesses data from the entire record
for x in keys:
r += 1
if r > qty: break
for y in range(len(clmt_vars_months[attribute][x])):
if attribute == "tavg":
if "ascending" not in kw or ("ascending" in kw and kw["ascending"] == False) or ("ascending" in kw and kw["ascending"] == True and clmt[clmt_vars_months[attribute][x][y].year][clmt_vars_months[attribute][x][y].month]["recordqty"] > excludemonth * 2):
appendr = True
print("{:>2}{} {:6.1f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[clmt_vars_months[attribute][x][y].month],clmt_vars_months[attribute][x][y].year))
else:
if "ascending" not in kw or ("ascending" in kw and kw["ascending"] == False) or ("ascending" in kw and kw["ascending"] == True and clmt[clmt_vars_months[attribute][x][y].year][clmt_vars_months[attribute][x][y].month]["recordqty"] > excludemonth):
appendr = True
if attribute == "prcp":
print("{:>2}{} {:6.2f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[clmt_vars_months[attribute][x][y].month],clmt_vars_months[attribute][x][y].year))
elif attribute in ["prcpDAYS","snowDAYS","snwdDAYS"]:
print("{:>2}{} {:2} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[clmt_vars_months[attribute][x][y].month],clmt_vars_months[attribute][x][y].year))
else:
print("{:>2}{} {:6.1f} - {} {}".format(r if r not in printed else " ","." if r not in printed else " ",x,calendar.month_abbr[clmt_vars_months[attribute][x][y].month],clmt_vars_months[attribute][x][y].year))
if r not in printed and appendr == True:
printed.append(r)
appendr = False
#-------------------------------------------
print("")
def valueSearch(stat_type,op,value,**kwargs):
"""Quick function to designate a value, and the days or months where the
attribute of interest exceeded, equalled, or was less than the passed
value
valueSearch("attribute","operator",value,**{sortmonth=False})
* "attribute" must be in ["prcp","snow","snwd","tavg","tmax","tmin"] (other
values are accepted, but these are what are assessed
* "operator" must be in ["<=","<","==","!=",">",">="]
* value must be an integer or a float
OPT **kwarg: sortmonth = True --> If set to true, it will do a value
search based on monthly data instead of
daily (no snwd data is available for
months though)
EXAMPLE: valueSearch("prcp",">=",5) --> returns a list of all days on
record where 5+ inches of rain
fell
"""
#operator=">", year=1984, month=12,season="winter"
# v, args[rain,prcp,snow,temp,avgtemp,tmax,avgtmax,tmin,avgtmin], kwargs[condition,year,metyear,season,month]
valid_yrs = sorted([x for x in clmt.keys() if type(x) == int])
valid_metyrs = sorted([x for x in metclmt.keys() if type(x) == int])
# ERROR HANDLING
if stat_type.lower() not in ["rain","prcp","precip","snow","snwd","temp","temps","temperature","temperatures","avgtemp","tavg","tempavglist","tmax","hi","high","tmin","lo","low"]:
return print("OOPS! {} is not a supported stat category. Try again!".format(stat_type))
if op not in ["<","<=","==",">",">="]: return print("OOPS! '{}' is not a supported operator. Try again!".format(op))
if type(value) not in [int,float]: return print("OOPS! Only integers or floats are supported for value intake")
# Format passed variables
stat_type = stat_type.lower() # Convert to lower-case for homogeniety
if stat_type in ["rain","prcp","precip"]: stat_type = "prcp"
if stat_type in ["snow"]: stat_type = "snow"
if stat_type in ["snwd"]: stat_type = "snwd"
if stat_type in ["avgtemp","tavg","tempavglist","temp","temps","temperature","temperatures"]: stat_type = "tavg"
if stat_type in ["tmax","hi","high"]: stat_type = "tmax"
if stat_type in ["tmin","lo","low"]: stat_type = "tmin"
if "sortmonth" in kwargs and kwargs["sortmonth"] == True:
CLMTDICT = clmt_vars_months
stype = "month"
else: # Just sorting indv days
CLMTDICT = clmt_vars_days
stype = "day"
results = []
for VAR in CLMTDICT[stat_type]:
for DAY in CLMTDICT[stat_type][VAR]:
if op == "<":
if stype == "month":
if VAR < value and clmt[DAY.year][DAY.month]["recordqty"] > excludemonth: results.append(DAY)
else:
if VAR < value: results.append(DAY)
elif op == "<=":
if stype == "month":
if VAR <= value and clmt[DAY.year][DAY.month]["recordqty"] > excludemonth: results.append(DAY)
else:
if VAR <= value: results.append(DAY)
elif op == "!=":
if VAR != value: results.append(DAY)
elif op == "==":
if VAR == value: results.append(DAY)
elif op == ">=":
if VAR >= value: results.append(DAY)
elif op == ">":
if VAR > value: results.append(DAY)
results.sort()
if "sortmonth" in kwargs and kwargs["sortmonth"] == True:
if stat_type == "prcp": print("Total months where the Total Rainfall {} {}: {}".format(op,value,len(results)))
elif stat_type == "snow": print("Total months where the Total Snowfall {} {}: {}".format(op,value,len(results)))
elif stat_type in ["tmax","tmin"]:
print("Total months where the Average {} {} {}: {}".format(stat_type.upper(),op,value,len(results)))
elif stat_type == "tavg":
print("Total months where the Average Temperature {} {}: {}".format(op,value,len(results)))
else:
return print("*** valueSearch does not report on monthly variations of {} ***".format(stat_type))
if len(results) <= 50: stillprint = True
else:
stillpr = input("print results? ('y'/'n'): ")
if stillpr == "y": stillprint = True
else: stillprint = False
if stillprint == True:
if stat_type == "prcp":
for x in results: print("{:6.2f}: {} {}".format(round(sum(clmt[x.year][x.month]["prcp"]),2),calendar.month_abbr[x.month],x.year))
if stat_type == "snow":
for x in results: print("{:5.1f}: {} {}".format(round(sum(clmt[x.year][x.month]["snow"]),1),calendar.month_abbr[x.month],x.year))
#if stat_type == "snwd":
#for x in results: print("{:5.1f}: {} {}".format(round(sum(clmt[x.year][x.month]["snwd"]),1),calendar.month_abbr[x.month],x.year))
if stat_type == "tavg":
for x in results: print("{:5.1f}: {} {}".format(round(mean(clmt[x.year][x.month]["tempAVGlist"]),1),calendar.month_abbr[x.month],x.year))
if stat_type == "tmax":
for x in results: print("{:5.1f}: {} {}".format(round(mean(clmt[x.year][x.month]["tmax"]),1),calendar.month_abbr[x.month],x.year))
if stat_type == "tmin":
for x in results: print("{:5.1f}: {} {}".format(round(mean(clmt[x.year][x.month]["tmin"]),1),calendar.month_abbr[x.month],x.year))
else: # Just assessing individual days
print("Total days where '{}' {} {}: {}".format(stat_type,op,value,len(results)))
if len(results) <= 50: stillprint = True
else:
stillpr = input("print results? ('y'/'n'): ")
if stillpr == "y": stillprint = True
else: stillprint = False
if stillprint == True:
if stat_type == "prcp":
for x in results: print("{:>5.2f}: {}".format(float(clmt[x.year][x.month][x.day].prcp),x))
if stat_type == "snow":
for x in results: print("{:>5.1f}: {}".format(float(clmt[x.year][x.month][x.day].snow),x))
if stat_type == "snwd":
for x in results: print("{:>5.1f}: {}".format(float(clmt[x.year][x.month][x.day].snwd),x))
if stat_type == "tmax":
for x in results: print("{:>3}: {}".format(clmt[x.year][x.month][x.day].tmax,x))
if stat_type == "tmin":
for x in results: print("{:>3}: {}".format(clmt[x.year][x.month][x.day].tmin,x))
print("")
def corrections():
"""Activates correction mode"""
print("CORRECTIONS MODE ACTIVATED - {}".format(clmt["station_name"]))
print("------------------------------------------------")
print("* Input a comma-separated list of the Year, Month, Date, Attribute, and new reading")
print("* Ex: INPUT CORRECTION: 1899,1,30,\"prcp\",2.02")
print("* When finished, type DONE and press enter")
fix = []
while True:
inp = input("INPUT CORRECTION: ").split(",")
if inp[0].upper() == "DONE" or inp[0] == "": break
elif len(inp) != 5: print("* not enough data given. Try again *")
elif any(x.isdigit() == False for x in inp[0:3]): print("* Dates entered must be numeric. Try again.")
elif inp[3].strip('"') not in ["prcp","snow","snwd","tmax","tmin"]:
print("* Invalid Attr. Valid Attributes: '{}','{}','{}','{}'".format("prcp","snow","snwd","tmax","tmin"))
else:
y = int(inp[0])
m = int(inp[1])
d = int(inp[2])
if y not in clmt or m not in clmt[y] or d not in clmt[y][m]:
print("* No valid entry for {}-{}-{} exists. Try again".format(int(inp[0]),int(inp[1]),int(inp[2])))
else:
try:
if inp[3].strip('"') == "prcp":
testvalue = round(float(inp[4]),2)
if clmt[int(inp[0])][int(inp[1])][int(inp[2])].prcpQ == "":
print("HEADS UP! {} already had no PRCP quality flag".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr))
clmt[int(inp[0])][int(inp[1])][int(inp[2])].prcp = inp[4]
clmt[int(inp[0])][int(inp[1])][int(inp[2])].prcpQ = ""
fix.append("{},{},,,,".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
print(" Amendment for {} PRCP successful: {}".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
if inp[3].strip('"') == "snow":
testvalue = round(float(inp[4]),1)
if clmt[int(inp[0])][int(inp[1])][int(inp[2])].snowQ == "":
print("HEADS UP! {} already had no SNOW quality flag".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr))
clmt[int(inp[0])][int(inp[1])][int(inp[2])].snow = inp[4]
clmt[int(inp[0])][int(inp[1])][int(inp[2])].snowQ = ""
fix.append("{},,{},,,".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
print(" Amendment for {} SNOW successful: {}".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
if inp[3].strip('"') == "snwd":
testvalue = round(float(inp[4]),1)
if clmt[int(inp[0])][int(inp[1])][int(inp[2])].snwdQ == "":
print("HEADS UP! {} already had no SNWD quality flag".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr))
clmt[int(inp[0])][int(inp[1])][int(inp[2])].snwd = inp[4]
clmt[int(inp[0])][int(inp[1])][int(inp[2])].snwdQ = ""
fix.append("{},,,{},,".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
print(" Amendment for {} SNWD successful: {}".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
if inp[3].strip('"') == "tmax":
testvalue = int(inp[4])
if clmt[int(inp[0])][int(inp[1])][int(inp[2])].tmaxQ == "":
print("HEADS UP! {} already had no TMAX quality flag".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr))
clmt[int(inp[0])][int(inp[1])][int(inp[2])].tmax = inp[4]
clmt[int(inp[0])][int(inp[1])][int(inp[2])].tmaxQ = ""
fix.append("{},,,,{},".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
print(" Amendment for {} TMAX successful: {}".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
if inp[3].strip('"') == "tmin":
testvalue = int(inp[4])
if clmt[int(inp[0])][int(inp[1])][int(inp[2])].tminQ == "":
print("HEADS UP! {} already had no TMIN quality flag".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr))
clmt[int(inp[0])][int(inp[1])][int(inp[2])].tmin = inp[4]
clmt[int(inp[0])][int(inp[1])][int(inp[2])].tminQ = ""
fix.append("{},,,,,{}".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
print(" Amendment for {} TMIN successful: {}".format(clmt[int(inp[0])][int(inp[1])][int(inp[2])].daystr,inp[4]))
except:
print("Hmm. Double check your input value. Try again")
if len(fix) > 0:
with open("APPENDED_" + FILE,"w") as f:
f.write('"STATION","NAME","LATITUDE","LONGITUDE","ELEVATION","DATE","PRCP","PRCP_ATTRIBUTES","SNOW","SNOW_ATTRIBUTES","SNWD","SNWD_ATTRIBUTES","TMAX","TMAX_ATTRIBUTES","TMIN","TMIN_ATTRIBUTES"\n')
for yr in [YR for YR in clmt if type(YR) == int]:
for mo in [MO for MO in clmt[yr] if type(MO) == int]:
for dy in [DY for DY in clmt[yr][mo] if type(DY) == int]:
f.write('"{}",'.format(clmt[yr][mo][dy].stationid))
f.write('"{}",'.format(clmt[yr][mo][dy].station_name))
f.write('"{}",'.format(clmt[yr][mo][dy].station_lat))
f.write('"{}",'.format(clmt[yr][mo][dy].station_lon))
f.write('"{}",'.format(clmt[yr][mo][dy].station_elev))
f.write('"{}",'.format(clmt[yr][mo][dy].daystr))
f.write('"{}",'.format(clmt[yr][mo][dy].prcp))
f.write('"{},{},{},{}",'.format(clmt[yr][mo][dy].prcpM,clmt[yr][mo][dy].prcpQ,clmt[yr][mo][dy].prcpS,clmt[yr][mo][dy].prcpT))
f.write('"{}",'.format(clmt[yr][mo][dy].snow))
f.write('"{},{},{},{}",'.format(clmt[yr][mo][dy].snowM,clmt[yr][mo][dy].snowQ,clmt[yr][mo][dy].snowS,clmt[yr][mo][dy].snowT))
f.write('"{}",'.format(clmt[yr][mo][dy].snwd))
f.write('"{},{},{},{}",'.format(clmt[yr][mo][dy].snwdM,clmt[yr][mo][dy].snwdQ,clmt[yr][mo][dy].snwdS,clmt[yr][mo][dy].snwdT))
f.write('"{}",'.format(clmt[yr][mo][dy].tmax))
f.write('"{},{},{},{}",'.format(clmt[yr][mo][dy].tmaxM,clmt[yr][mo][dy].tmaxQ,clmt[yr][mo][dy].tmaxS,clmt[yr][mo][dy].tmaxT))
f.write('"{}",'.format(clmt[yr][mo][dy].tmin))
f.write('"{},{},{},{}"\n'.format(clmt[yr][mo][dy].tminM,clmt[yr][mo][dy].tminQ,clmt[yr][mo][dy].tminS,clmt[yr][mo][dy].tminT))
print("Output of '{}' finished!".format("AMENDED_" + FILE))
else: return print("::: NO VALUES CHANGED :::")
if len(fix) > 0:
timenow = datetime.datetime.now()
timestr = "{:%Y%m%d_%H%M}".format(timenow)
with open("CHG_" + timestr + "_" + FILE,"w") as f:
f.write("{},{},{},{},{},{}\n".format("DAY","PRCP","SNOW","SNWD","TMAX","TMIN"))
for each in fix:
f.write(each); f.write("\n")
print("Output of '{}' finished!".format("CHG_" + timestr + "_" + FILE))
def clmthelp():
"""An extensive list within the script of available functions to the user
""" #
print("* PLEASE SEE README.md FOR A FULL BREAKDOWN OF PROGRAM'S CAPABILITIES *")
for x in wrap("* TO START: -When you start, the clmtmenu() function automatically runs. If canceled, simply run the function again. it displays all csv's in the folder",width=78,subsequent_indent=" "): print(x)
print(" -takes optional keyword argument <city>")
for x in wrap("CLIMATOLOGY VARIABLES: At the end of the script, you'll see two variables: climatology and increment. These are strictly used in the Report functions. The former is to allow the user to modify the length of climatologies (so if you want to assess them at 10, 20, or even 50-yr); the latter controls the frequency of the assessment",width=78,subsequent_indent=" "): print(x)
print(" climatology = 30 # Default Climatology Length in reports")
print(" increment = 5 # Default running-mean increment")
for x in wrap("RECORD THRESHOLDS: At the end of the script, you'll find record thresholds. These are controls employed whilst running report/rank functions to prevent partial years/months/weeks from polluting the overall data if it would affect it",width=78,subsequent_indent=" "): print(x)
print(" DEFAULT VALUES (can be modified before or after compiling the data):")
print(" excludeyear = 300 # Exclude years from ranking/reports if ")
print(" year recordqty <= to this threshold")
print(" excludemonth = 20 # Exclude months from ranking/reports if")
print(" month recordqty <= to this threshold")
print(" excludeweek = 4 # Exclude weeks from ranking/reports if")
print(" week recordqty <= to this threshold")
print(" excludecustom = .75 # Exclude custom periods from ranking or")
print(" reports if week recordqty <= 75% of a")
print(" threshold")
print("DAILY SUMMARIES:")
print(" -- daySummary(y1,m1,d1,*[y2,m2,d2]) :: Dumps a list of day-by-day data in a given range of dates")
print("ERRORS OVERVIEW:")
print(" -- Run qflagCheck() to get the code and definition for various quality flags in the record")
print(" -- Run errorStats() to get get a report on errors that might be worth veryfying the data for.")
print(" * this function will report on every error unless it is a temperature with an 'I' flag.")
print(" - These can be quite numerous. So won't be included in the report")
print(" * by default, data with any type of quality flag will NOT be included in stats/reports")
print(" * User can change these settings by one of two ways:")
print(" - Find where the 'ignoreflags' list is in the script, and add or take away from the list")
print(" - On the fly, with the command ignoreflags.append('<flag>') or ignoreflags.remove('<flag>')")
print(" * using corrections(), It is possible to verify the data and remove the quality flag so it will be included")
print(" - this process amends the data and outputs a new file; reload using clmtAnalyze() for best results")
print(" * Please see README.md to read more about this process")
print("BUILT-IN FUNCTIONS: (these won't work until you run the clmtAnalyze function)")
print(" -- dayStats(year,month,day) :: Returns a basic report for the specified day")
print(" -- weekStats(year,month,day) :: Returns a basic weekly report; the included day will be the ")
print(" center of the week")
print(" -- monthStats(year,month) :: Returns a basic report for the specified month")
print(" -- yearStats(year) :: Returns a basic report for the specified year")
print(" -- metYearStats(year) :: Returns a basic report for the specified meteorological year")
print(" -- seasonStats(year,season) :: Returns a basic report for the specified meteorological ")
print(" season ('spring','summer','fall','winter')")
print(" -- customStats(y1,m1,d1,*y2,*m2,*d2)")
print(" Climatology Functions :: Detailed stats based on 30-yr climatologies incremented by")
print(" 5 years and enables basic climatological tendency analysis. These defaults can change as needed.")
print(" see README for more details or use the help function on one of the variables")
print(" -- dayReport(month,day) :: Returns detailed statistics and climatology for all specified")
print(" days in the record")
print(" -- weekReport(month,day) :: Returns detailed statistics and climatology for determined 7-day")
print(" period and the included day will be the center of the week")
print(" -- monthReport(month) :: Returns detailed statistics and climatology for the specified month")
print(" -- yearReport() :: NOTHING is passed to this function. It returns detailed statistics based ")
print(" on data for all years")
print(" -- metYearReport() :: NOTHING is passed to this function. It returns detailed statistics based ")
print(" on data for all meteorological years")
print(" -- seasonReport(season) :: Returns detailed statistics and climatology for the specified season")
print(" -- customReport(M1,D1,*[M2,D2]) :: Returns detailed statistics and climatology for the specified,")
print(" custom period of time. The ending month and date are optional")
print(" Rank/Record Functions")
print(" -- dayRank(month,day,howmany) :: Prints daily records from the climate data.")
print(" -- weekRank(month,day,howmany) :: Prints records based on a week's period, centered on the ")
print(" day entered (3 days before; 3 after)")
print(" -- monthRank(month,'<temps>|<rain>',howmany) :: Prints month-based records for the given month")
print(" -- yearRank('<temps>|<rain>',howmany) :: Prints yearly-based records for the entire record (Jan-Dec)")
print(" -- metYearRank('<temps>|<rain>',howmany) :: Prints meteorological-yearly-based records for the ")
print(" entire record (Jan-Dec)")
print(" -- seasonRank(season,'<temps>|<rain>',howmany) :: Prints season-based records for the inquired season")
print(" -- customRank(attribute,quantity,M1,D1,*[M2,D2]) :: Prints ranked-records for the inquired period of time")
print(" The ending date is optional. This is a good function for proxy of a YTD function")
print(" -- allDayRank('attribute',quantity,**{season,year,month,ascending}) :: compares all daily data on record.")
print(" optional temporal keyword arguments accepted")
print(" -- allMonthRank(attribute,quantity,**{season,ascending}) :: compares all monthly data on record to one")
print(" another. Optional keyword arguments of <season> or <ascending=True> are accepted")
def clmtmenu():
"""Enables the user to select which csv file (as such, which city) that
they'd like to load/mount into the program; automatically ran at
initilization of the script, but can be ran at anytime; replaces the
csvFileList() function.
clmtmenu()
"""
tempcsvlist = os.listdir()
csvs_in_dir = [x for x in tempcsvlist if x[len(x)-3:] == "csv" and x[0:9] not in ["dayReport","weekRepor","monthRepo","yearRepor","seasonRep","metYearRe","customRep"]]
selection = False # Will cause the function to wait until an accepted answer is input
print("**********************************************************")
print(" CLIMATE PARSER (clmt-parser.py) v2.9x")
print(" by K. Gentry (ksgwxfan)")
print("**********************************************************")
print("- Make selection and press <ENTER>; type-in cancel to exit function")
print("- Run this function again by entering clmtmenu()")
print("- OPTIONAL: enter in a custom city name (useful if the file has")
print(" multiple stations). Just separate by a comma.")
print(" Example --> Enter Selection: 2, CITY")
print("-----------------------------------------------------------")
for each in csvs_in_dir:
print("{:>3}. {}".format(csvs_in_dir.index(each) + 1,each))
print("-----------------------------------------------------------")
while selection == False: # only jumps out of while-loop if answer is valids
userselection = input("Enter Selection: ")
userselection = userselection.split(",")
if userselection[0].isnumeric() and int(userselection[0]) > 0 and int(userselection[0]) <= len(csvs_in_dir) or userselection[0].lower() == "cancel":
selection = True
else: print("OOPS! Invalid selection. Try again!")
if len(userselection) >= 2:
citystr = userselection[1].strip(" ")
for x in range(2,len(userselection)):
citystr = citystr + ", " + userselection[x].strip(" ")
if userselection[0].lower() != "cancel":
if len(userselection) == 1: clmtAnalyze(csvs_in_dir[int(userselection[0])-1])
else:
#citystr = userselection[1].strip(" ") + ", " + userselection[2].strip(" ")
clmtAnalyze(csvs_in_dir[int(userselection[0])-1],city=citystr)
# MAIN PROGRAM --------------------------------------------------------------
clmt = {}
metclmt = {}
clmt_vars_days = {"prcp":{},"snow":{},"snwd":{},"tavg":{},"tmax":{},"tmin":{}}
clmt_vars_months = {"prcp":{},"prcpDAYS":{},"snow":{},"snowDAYS":{},"snwd":{},"snwdDAYS":{},"tavg":{},"tmax":{},"tmin":{}}
station_ids = []
FILE = None
# Threshold Quantities
ignoreflags = [""] # If there are Quality Flags that you wish to ignore, place them here (or append upon starting; see README)
excludeyear = 300 # Exclude years from ranking/reports if year recordqty <= to this threshold
excludeseason = 70 # Exclude season from rankings/reports if season recordqty <= to this threshold
excludemonth = 20 # Exclude months from ranking/reports if month recordqty <= to this threshold
excludeweek = 4 # Exclude weeks from ranking/reports if week recordqty <= to this threshold
excludecustom = .75 # Excludes custom periods if recordqty isn't at least this percentage of threshold
# tempAVGlist Threshold Quantities (DO NOT TOUCH!!! these are handled from above variables)
excludeyear_tavg = excludeyear * 2
excludeseason_tavg = excludeseason * 2
excludemonth_tavg = excludemonth * 2
excludeweek_tavg = excludeweek * 2
clmtmenu()
# li = sorted([{"year":y,"month":m,"snwdDAYS":clmt[y][m]["snwdDAYS"]} for y in clmt if type(y) == int for m in clmt[y] if type(m) == int and clmt[y][m]["snwdDAYS"] > 0],key=lambda x:x["snwdDAYS"],reverse=True)
| 79.613121
| 409
| 0.539487
| 80,256
| 578,867
| 3.821322
| 0.015164
| 0.02752
| 0.019682
| 0.014129
| 0.892303
| 0.864033
| 0.835016
| 0.790703
| 0.74071
| 0.690848
| 0
| 0.035555
| 0.234651
| 578,867
| 7,271
| 410
| 79.613121
| 0.656129
| 0.072291
| 0
| 0.459629
| 0
| 0.021273
| 0.200796
| 0.008703
| 0
| 0
| 0
| 0
| 0
| 1
| 0.008058
| false
| 0.008703
| 0.001773
| 0
| 0.014021
| 0.1639
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
1af65582e33d661350f89fb423af1d29e91ecbdb
| 1,487
|
py
|
Python
|
main/views.py
|
nishantc7/iterapi-web
|
515e43a45b1459baa5a05dcb5446ed1524d37998
|
[
"MIT"
] | 4
|
2020-05-05T14:12:42.000Z
|
2020-06-13T11:15:52.000Z
|
main/views.py
|
nishantc7/iterapi-web
|
515e43a45b1459baa5a05dcb5446ed1524d37998
|
[
"MIT"
] | 6
|
2020-05-05T13:19:48.000Z
|
2021-09-22T18:58:20.000Z
|
main/views.py
|
nishantc7/iterapi-web
|
515e43a45b1459baa5a05dcb5446ed1524d37998
|
[
"MIT"
] | 1
|
2020-06-13T11:16:36.000Z
|
2020-06-13T11:16:36.000Z
|
from rest_framework import generics
from rest_framework.response import Response
from iterapi import Student
from rest_framework.parsers import JSONParser
from main.serializer import UserSerializer
class MainView(generics.CreateAPIView):
parser_classes = [JSONParser]
serializer_class = UserSerializer
def post(self, request):
user_id = request.data['user_id']
password = request.data['password']
st = Student(user_id, password)
return Response(st.getAttendance())
class ResultView(generics.CreateAPIView):
parser_classes = [JSONParser]
serializer_class = UserSerializer
def post(self, request):
user_id = request.data['user_id']
password = request.data['password']
sem = request.data['sem']
st = Student(user_id, password)
return Response(st.getDetailedResult(sem))
class InfoView(generics.CreateAPIView):
parser_classes = [JSONParser]
serializer_class = UserSerializer
def post(self, request):
user_id = request.data['user_id']
password = request.data['password']
st = Student(user_id, password)
return Response(st.getInfo())
class CgpaView(generics.CreateAPIView):
parser_classes = [JSONParser]
serializer_class = UserSerializer
def post(self, request):
user_id = request.data['user_id']
password = request.data['password']
st = Student(user_id, password)
return Response(st.getResult())
| 29.156863
| 50
| 0.696032
| 163
| 1,487
| 6.208589
| 0.220859
| 0.071146
| 0.110672
| 0.134387
| 0.711462
| 0.711462
| 0.711462
| 0.711462
| 0.672925
| 0.672925
| 0
| 0
| 0.209146
| 1,487
| 50
| 51
| 29.74
| 0.860544
| 0
| 0
| 0.631579
| 0
| 0
| 0.042367
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.105263
| false
| 0.210526
| 0.131579
| 0
| 0.657895
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 6
|
2128761b912dafc74f58f16adbf28832a7b51fe6
| 12,064
|
py
|
Python
|
test/test_3_rules.py
|
nick-killeen/demuxfb
|
9c9a89c3b3116add018f98ef9e11ae335395692a
|
[
"MIT"
] | null | null | null |
test/test_3_rules.py
|
nick-killeen/demuxfb
|
9c9a89c3b3116add018f98ef9e11ae335395692a
|
[
"MIT"
] | null | null | null |
test/test_3_rules.py
|
nick-killeen/demuxfb
|
9c9a89c3b3116add018f98ef9e11ae335395692a
|
[
"MIT"
] | null | null | null |
"""
Test a subset of chat construction rules against *my* current expectations.
These should not be considered formal tests. They are just an artifact of
exploratory sanity testing, distrubted only for completeness. There is no formal
spec.
This file should not be maintained. Throw it out when the Facebook exporter
updates
"""
import sys
from .helpers import SpoofChatFeed
sys.path.append('src/')
import demuxfb # nopep8 pylint: disable=wrong-import-position
def test_match_media_message():
chat_feed = SpoofChatFeed()
chat_feed.push(photos=[{'uri': 'messages/inbox/convo/photos/blah.png',
'creation_timestamp': 1000}])
chat_feed.push(content='What do these mean?',
photos=[{'uri': 'messages/inbox/convo/photos/blah.png',
'creation_timestamp': 1000},
{'uri': 'messages/inbox/convo/photos/blah1.png',
'creation_timestamp': 2000}])
chat_feed.push(gifs=[{'uri': 'messages/inbox/convo/gifs/blah.gif'}])
chat_feed.push(audio_files=[{'uri': 'messages/inbox/convo/audio/blah.mp4',
'creation_timestamp': 1000}])
chat_feed.push(videos=[{'uri': 'messages/inbox/convo/videos/blah.mp4',
'creation_timestamp': 1000,
'thumbnail': {
'uri': 'messages/inbox/convo//videos/thumbnails'
'/blarg.jpg'
}}])
chat_feed.push(files=[{'uri': 'messages/inbox/convo/videos/blah.mp4',
'creation_timestamp': 1000}])
chat_feed.push(sticker={'uri': 'messages/stickers_used/blah.png'})
chat = demuxfb.build_chat(chat_feed, 'John Smith')
messages = chat.messages
message = messages.pop(0)
assert isinstance(message, demuxfb.message.MediaMessage)
assert message.content is None
assert len(message.photos) == 1
assert len(message.gifs) == 0
assert len(message.audio_files) == 0
assert len(message.videos) == 0
assert len(message.attachment_files) == 0
assert len(message.stickers) == 0
message = messages.pop(0)
assert isinstance(message, demuxfb.message.MediaMessage)
assert message.content == 'What do these mean?'
assert len(message.photos) == 2
message = messages.pop(0)
assert isinstance(message, demuxfb.message.MediaMessage)
assert len(message.photos) == 0
assert len(message.gifs) == 1
message = messages.pop(0)
assert isinstance(message, demuxfb.message.MediaMessage)
assert len(message.audio_files) == 1
message = messages.pop(0)
assert isinstance(message, demuxfb.message.MediaMessage)
assert len(message.videos) == 1
message = messages.pop(0)
assert isinstance(message, demuxfb.message.MediaMessage)
assert len(message.attachment_files) == 1
message = messages.pop(0)
assert isinstance(message, demuxfb.message.MediaMessage)
assert len(message.stickers) == 1
def test_match_empty_message():
chat_feed = SpoofChatFeed()
chat_feed.push()
chat = demuxfb.build_chat(chat_feed, 'John Smith')
messages = chat.messages
message = messages.pop(0)
assert isinstance(message, demuxfb.message.EmptyMessage)
def test_call_messages():
chat_feed = SpoofChatFeed()
chat_feed.push(content='John started a video chat.')
chat_feed.push(content='John joined the video chat.')
chat_feed.push(content='The video chat ended.')
chat_feed.push(content='John started a call.')
chat_feed.push(content='John joined the call.')
chat_feed.push(content='The call ended.')
chat_feed.push(content='John started a call.')
chat_feed.push(content='John joined the call.')
chat_feed.push(content='The call ended.')
chat = demuxfb.build_chat(chat_feed, 'Jake Smith')
messages = chat.messages
message = messages.pop(0)
assert isinstance(message, demuxfb.message.CallStartMessage)
assert message.call_type == demuxfb.message.CallType.VIDEO
message = messages.pop(0)
assert isinstance(message, demuxfb.message.CallJoinMessage)
assert message.call_type == demuxfb.message.CallType.VIDEO
message = messages.pop(0)
assert isinstance(message, demuxfb.message.CallEndMessage)
assert message.call_type == demuxfb.message.CallType.VIDEO
message = messages.pop(0)
assert isinstance(message, demuxfb.message.CallStartMessage)
assert message.call_type == demuxfb.message.CallType.AUDIO
message = messages.pop(0)
assert isinstance(message, demuxfb.message.CallJoinMessage)
assert message.call_type == demuxfb.message.CallType.AUDIO
message = messages.pop(0)
assert isinstance(message, demuxfb.message.CallEndMessage)
assert message.call_type == demuxfb.message.CallType.AUDIO
def test_match_nickname_change_message():
chat_feed = SpoofChatFeed()
chat_feed.push(sender_name='Joseph',
content='Joseph cleared his own nickname.')
chat_feed.push(sender_name='Joseph',
content='Joseph cleared your nickname.')
chat_feed.push(sender_name='Joseph',
content='Joseph cleared the nickname for Jacob.')
chat_feed.push(sender_name='Joseph',
content='Joseph set the nickname for Jacob to Jake.')
chat_feed.push(sender_name='Joseph',
content='Joseph set your nickname to John.')
chat_feed.push(sender_name='Joseph',
content='Joseph set their own nickname to Joe.')
chat_feed.push(content='You cleared your nickname.')
chat_feed.push(content='You cleared the nickname for Joseph.')
chat_feed.push(content='You set the nickname for Joseph to Joe.')
chat_feed.push(content='You set your nickname to John.')
chat = demuxfb.build_chat(chat_feed, 'John Smith')
messages = chat.messages
joseph = chat.get_participant('Joseph')
jacob = chat.get_participant('Jacob')
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter == joseph
assert message.subject == joseph
assert message.new_nickname is None
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter == joseph
assert message.subject.is_me()
assert message.new_nickname is None
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter == joseph
assert message.subject == jacob
assert message.new_nickname is None
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter == joseph
assert message.subject == jacob
assert message.new_nickname == 'Jake'
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter == joseph
assert message.subject.is_me()
assert message.new_nickname == 'John'
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter == joseph
assert message.subject == joseph
assert message.new_nickname == 'Joe'
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter.is_me()
assert message.subject.is_me()
assert message.new_nickname is None
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter.is_me()
assert message.subject == joseph
assert message.new_nickname is None
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter.is_me()
assert message.subject == joseph
assert message.new_nickname == 'Joe'
message = messages.pop(0)
assert isinstance(message, demuxfb.message.NicknameChangeMessage)
assert message.setter.is_me()
assert message.subject.is_me()
assert message.new_nickname == 'John'
def test_match_chat_settings_change_message():
chat_feed = SpoofChatFeed()
chat_feed.push(content='Jacob named the group Saturday Hangout.')
chat_feed.push(content='Jacob changed the group photo.')
chat_feed.push(content='Jacob changed the chat theme.')
chat_feed.push(content=r'Jacob set the emoji to \u00f0\u009f\u008d\u00ba.')
chat_feed.push(content='Jacob turned on member approval and will review'
' requests to join the group.')
chat_feed.push(content='Jacob turned off member approval. Anyone with the'
' link can join the group.')
chat = demuxfb.build_chat(chat_feed, 'John Smith')
messages = chat.messages
message = messages.pop(0)
assert isinstance(message, demuxfb.message.ChatSettingsChangeMessage)
assert message.settings_type == demuxfb.message.ChatSettingsType.CHANGE_NAME
assert message.new_name == 'Saturday Hangout'
assert message.new_emoji is None
assert message.new_approval_is_required_policy is None
message = messages.pop(0)
assert isinstance(message, demuxfb.message.ChatSettingsChangeMessage)
assert message.settings_type == \
demuxfb.message.ChatSettingsType.CHANGE_PHOTO
assert message.new_name is None
message = messages.pop(0)
assert isinstance(message, demuxfb.message.ChatSettingsChangeMessage)
assert message.settings_type == \
demuxfb.message.ChatSettingsType.CHANGE_THEME
message = messages.pop(0)
assert isinstance(message, demuxfb.message.ChatSettingsChangeMessage)
assert message.settings_type == \
demuxfb.message.ChatSettingsType.CHANGE_EMOJI
assert message.new_emoji == r'\u00f0\u009f\u008d\u00ba'
message = messages.pop(0)
assert isinstance(message, demuxfb.message.ChatSettingsChangeMessage)
assert message.settings_type == \
demuxfb.message.ChatSettingsType.CHANGE_MEMBERSHIP_POLICY
assert message.new_approval_is_required_policy
message = messages.pop(0)
assert isinstance(message, demuxfb.message.ChatSettingsChangeMessage)
assert message.settings_type == \
demuxfb.message.ChatSettingsType.CHANGE_MEMBERSHIP_POLICY
assert message.new_approval_is_required_policy is not None
assert not message.new_approval_is_required_policy
def test_plan_messages():
chat_feed = SpoofChatFeed()
chat_feed.push(content='Joseph responded ')
chat_feed.push(content='Jacob started a plan.')
chat_feed.push(content='Jacob named the plan Saturday Hangout.')
chat_feed.push(content='Jacob updated the plan to Sat, Aug 5 at 12 PM.')
chat_feed.push(content='Joseph responded ')
chat_feed.push(content='Jacob deleted the plan Saturday Hangout for Sat,'
' Aug 5 at 12 PM.')
chat_feed.push(content='Joseph responded ')
chat = demuxfb.build_chat(chat_feed, 'John Smith')
messages = chat.messages
message = messages.pop(0)
assert isinstance(message, demuxfb.message.TextMessage)
message = messages.pop(0)
assert isinstance(message, demuxfb.message.PlanCreationMessage)
message = messages.pop(0)
assert isinstance(message, demuxfb.message.PlanUpdateMessage)
assert message.new_plan_title == 'Saturday Hangout'
assert message.new_plan_time is None
message = messages.pop(0)
assert isinstance(message, demuxfb.message.PlanUpdateMessage)
assert message.new_plan_title is None
assert message.new_plan_time == 'Sat, Aug 5 at 12 PM'
message = messages.pop(0)
assert isinstance(message, demuxfb.message.PlanRespondencyMessage)
message = messages.pop(0)
assert isinstance(message, demuxfb.message.PlanDeletionMessage)
assert message.plan_title == 'Saturday Hangout'
assert message.plan_time == 'Sat, Aug 5 at 12 PM'
message = messages.pop(0)
assert isinstance(message, demuxfb.message.TextMessage)
| 38.666667
| 80
| 0.704824
| 1,453
| 12,064
| 5.738472
| 0.13214
| 0.08887
| 0.057568
| 0.084313
| 0.830295
| 0.794195
| 0.752459
| 0.710242
| 0.679539
| 0.644519
| 0
| 0.011648
| 0.195872
| 12,064
| 311
| 81
| 38.790997
| 0.847851
| 0.030421
| 0
| 0.609959
| 0
| 0
| 0.153478
| 0.031568
| 0
| 0
| 0
| 0
| 0.448133
| 1
| 0.024896
| false
| 0
| 0.012448
| 0
| 0.037344
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
213266dedf1be75a442f2d2d047405334de761d6
| 241
|
py
|
Python
|
code/library/daily_crawler.py
|
chosunghyun18/Stock_trading_bot
|
15223e4aff5f4c4ff064f09c161100dd649a79e7
|
[
"MIT"
] | 3
|
2020-12-24T10:16:09.000Z
|
2022-03-02T16:17:58.000Z
|
code/library/daily_crawler.py
|
chosunghyun18/Stock_trading_bot
|
15223e4aff5f4c4ff064f09c161100dd649a79e7
|
[
"MIT"
] | null | null | null |
code/library/daily_crawler.py
|
chosunghyun18/Stock_trading_bot
|
15223e4aff5f4c4ff064f09c161100dd649a79e7
|
[
"MIT"
] | null | null | null |
from library.daily_craw_config import *
class daily_crawler():
def __init__(self, db_name, daily_craw_db_name, daily_buy_list_db_name):
self.cc = daily_craw_config(db_name, daily_craw_db_name, daily_buy_list_db_name)
| 26.777778
| 89
| 0.763485
| 39
| 241
| 4.076923
| 0.410256
| 0.226415
| 0.27673
| 0.188679
| 0.490566
| 0.490566
| 0.490566
| 0.490566
| 0.490566
| 0.490566
| 0
| 0
| 0.165975
| 241
| 8
| 90
| 30.125
| 0.791045
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.75
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 6
|
2152ac5ce747f783cca177369fadf7289001def4
| 544
|
py
|
Python
|
tests/test_decode_spec.py
|
Cologler/jsonxx-python
|
5a203b61d677085df1fcf8bb0146da9896bf840f
|
[
"MIT"
] | null | null | null |
tests/test_decode_spec.py
|
Cologler/jsonxx-python
|
5a203b61d677085df1fcf8bb0146da9896bf840f
|
[
"MIT"
] | null | null | null |
tests/test_decode_spec.py
|
Cologler/jsonxx-python
|
5a203b61d677085df1fcf8bb0146da9896bf840f
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
#
# Copyright (c) 2021~2999 - Cologler <skyoflw@gmail.com>
# ----------
#
# ----------
from jsonxx import loads
def test_null():
assert loads('null') == None
def test_false():
assert loads('false') == False
def test_true():
assert loads('true') == True
def test_int():
assert loads('123') == 123
def test_str():
assert loads('"123"') == "123"
def test_array():
assert loads('["123", 123, false]') == ["123", 123, False]
def test_object():
assert loads('{"123": 123}') == {"123": 123}
| 18.133333
| 62
| 0.564338
| 70
| 544
| 4.285714
| 0.385714
| 0.163333
| 0.186667
| 0.226667
| 0.16
| 0.16
| 0
| 0
| 0
| 0
| 0
| 0.10274
| 0.194853
| 544
| 29
| 63
| 18.758621
| 0.582192
| 0.180147
| 0
| 0
| 0
| 0
| 0.138952
| 0
| 0
| 0
| 0
| 0
| 0.466667
| 1
| 0.466667
| true
| 0
| 0.066667
| 0
| 0.533333
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 6
|
215c18211d0ea463f59a3a00c355a288c23a8ff7
| 87
|
py
|
Python
|
Python/Tests/TestData/DebuggerProject/UnhandledException5.py
|
nanshuiyu/pytools
|
9f9271fe8cf564b4f94e9456d400f4306ea77c23
|
[
"Apache-2.0"
] | null | null | null |
Python/Tests/TestData/DebuggerProject/UnhandledException5.py
|
nanshuiyu/pytools
|
9f9271fe8cf564b4f94e9456d400f4306ea77c23
|
[
"Apache-2.0"
] | null | null | null |
Python/Tests/TestData/DebuggerProject/UnhandledException5.py
|
nanshuiyu/pytools
|
9f9271fe8cf564b4f94e9456d400f4306ea77c23
|
[
"Apache-2.0"
] | null | null | null |
def A():
return ValueError
try: raise ValueError() # breaks
except A(): pass
| 14.5
| 33
| 0.632184
| 11
| 87
| 5
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.252874
| 87
| 5
| 34
| 17.4
| 0.846154
| 0.068966
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| true
| 0.25
| 0
| 0.25
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
|
0
| 6
|
2166d0a2bf1e7a466d4dd60309db4af4e7a7d64c
| 44
|
py
|
Python
|
Face_rec/__init__.py
|
SOUHARDYAADHIKARY1999/Face_rev_pip
|
65bdb76612b960349bfd3038a02883aa09a7f99a
|
[
"MIT"
] | null | null | null |
Face_rec/__init__.py
|
SOUHARDYAADHIKARY1999/Face_rev_pip
|
65bdb76612b960349bfd3038a02883aa09a7f99a
|
[
"MIT"
] | null | null | null |
Face_rec/__init__.py
|
SOUHARDYAADHIKARY1999/Face_rev_pip
|
65bdb76612b960349bfd3038a02883aa09a7f99a
|
[
"MIT"
] | null | null | null |
from Face_rec.FaceClass import FaceIndentity
| 44
| 44
| 0.909091
| 6
| 44
| 6.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.068182
| 44
| 1
| 44
| 44
| 0.95122
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
dcc9b73c34092a6b70af02c32dae9efec5b5d1a2
| 36
|
py
|
Python
|
tests/selenium_tests/jbrowse_selenium/__init__.py
|
rbuels/jbrowse
|
a4cfc3234f4708ee86b719f9f10a2b6c606c03ff
|
[
"Artistic-2.0"
] | 319
|
2015-01-05T14:42:43.000Z
|
2022-03-30T12:55:07.000Z
|
tests/selenium_tests/jbrowse_selenium/__init__.py
|
rbuels/jbrowse
|
a4cfc3234f4708ee86b719f9f10a2b6c606c03ff
|
[
"Artistic-2.0"
] | 1,065
|
2015-01-06T08:50:10.000Z
|
2022-03-25T21:01:48.000Z
|
tests/selenium_tests/jbrowse_selenium/__init__.py
|
Julboteroc/csmb
|
90991f64ed86a018a40910a83df00585e8e70ee5
|
[
"Artistic-2.0"
] | 191
|
2015-01-20T03:41:12.000Z
|
2022-03-09T03:32:17.000Z
|
from JBrowseTest import JBrowseTest
| 18
| 35
| 0.888889
| 4
| 36
| 8
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 36
| 1
| 36
| 36
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
dccb701273674683e54722dc115503efec6f6227
| 14
|
py
|
Python
|
pyth/plugins/xhtml/__init__.py
|
eriol/pyth
|
f2a06fc8dc9b1cfc439ea14252d39b9845a7fa4b
|
[
"MIT"
] | 47
|
2015-01-26T22:06:53.000Z
|
2022-01-04T15:11:14.000Z
|
pyth/plugins/xhtml/__init__.py
|
eriol/pyth
|
f2a06fc8dc9b1cfc439ea14252d39b9845a7fa4b
|
[
"MIT"
] | 16
|
2015-02-20T18:12:22.000Z
|
2021-12-17T09:49:19.000Z
|
pyth/plugins/xhtml/__init__.py
|
eriol/pyth
|
f2a06fc8dc9b1cfc439ea14252d39b9845a7fa4b
|
[
"MIT"
] | 45
|
2015-01-29T02:47:39.000Z
|
2022-01-26T12:50:27.000Z
|
"""
XHTML
"""
| 3.5
| 5
| 0.357143
| 1
| 14
| 5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214286
| 14
| 3
| 6
| 4.666667
| 0.454545
| 0.357143
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
0d0490c1dd27fbb9dc31b3e3c4f160a8d649b483
| 35
|
py
|
Python
|
src/__init__.py
|
Vasco-jofra/format-string-finder-binja
|
a02d1501ca1db1c4ea0ced65c01af0d5ad1c8712
|
[
"MIT"
] | 19
|
2019-07-15T21:17:07.000Z
|
2021-04-25T12:52:11.000Z
|
src/__init__.py
|
Vasco-jofra/format-string-finder-binja
|
a02d1501ca1db1c4ea0ced65c01af0d5ad1c8712
|
[
"MIT"
] | null | null | null |
src/__init__.py
|
Vasco-jofra/format-string-finder-binja
|
a02d1501ca1db1c4ea0ced65c01af0d5ad1c8712
|
[
"MIT"
] | 1
|
2020-12-29T20:56:34.000Z
|
2020-12-29T20:56:34.000Z
|
from .format_string_finder import *
| 35
| 35
| 0.857143
| 5
| 35
| 5.6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.085714
| 35
| 1
| 35
| 35
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
0d4ea72b0ecfdbd782e0e8275750f111f3c836c5
| 87
|
py
|
Python
|
words_memo/domain/dictionary.py
|
senpay/words_memo
|
7fb6463f32481e4d4dc3700c6af18ef073a1cd9a
|
[
"Unlicense"
] | null | null | null |
words_memo/domain/dictionary.py
|
senpay/words_memo
|
7fb6463f32481e4d4dc3700c6af18ef073a1cd9a
|
[
"Unlicense"
] | null | null | null |
words_memo/domain/dictionary.py
|
senpay/words_memo
|
7fb6463f32481e4d4dc3700c6af18ef073a1cd9a
|
[
"Unlicense"
] | null | null | null |
class Dictionary:
def get_sub_dictionary(self):
return Dictionary
pass
| 17.4
| 33
| 0.689655
| 10
| 87
| 5.8
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.264368
| 87
| 4
| 34
| 21.75
| 0.90625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0.25
| 0
| 0.25
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 6
|
b4f83a89b5bdfc79d43aec7f8dd11856fce58d65
| 167
|
py
|
Python
|
07RDDExamples/pythoncodes/lambdademo.py
|
sharonwoo/BEADSEP20
|
77f9031d1373320a7aecbe9cfe9c8e90e604c34e
|
[
"MIT"
] | 2
|
2022-01-16T04:30:00.000Z
|
2022-01-23T08:04:47.000Z
|
07RDDExamples/pythoncodes/lambdademo.py
|
sharonwoo/BEADSEP20
|
77f9031d1373320a7aecbe9cfe9c8e90e604c34e
|
[
"MIT"
] | null | null | null |
07RDDExamples/pythoncodes/lambdademo.py
|
sharonwoo/BEADSEP20
|
77f9031d1373320a7aecbe9cfe9c8e90e604c34e
|
[
"MIT"
] | 5
|
2020-09-01T01:11:43.000Z
|
2022-01-21T10:32:32.000Z
|
mult_3_5 = lambda x: x%3==0 or x%5==0
print(mult_3_5(3))
print(mult_3_5(4))
print(mult_3_5(5))
def add1():
return lambda x: x + 1
f = add1()
print(f(2))
| 16.7
| 38
| 0.592814
| 39
| 167
| 2.333333
| 0.384615
| 0.21978
| 0.263736
| 0.362637
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.145038
| 0.215569
| 167
| 9
| 39
| 18.555556
| 0.549618
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.125
| false
| 0
| 0
| 0.125
| 0.25
| 0.5
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
|
0
| 6
|
2ea0c21b1e8dbf9eafbda61beb50c5c176ed442f
| 80
|
py
|
Python
|
services/security.py
|
stuartcampbell/nsls2-api
|
8175e524279f51d9b43ad0f8f08b8b3f54eceae0
|
[
"BSD-3-Clause"
] | null | null | null |
services/security.py
|
stuartcampbell/nsls2-api
|
8175e524279f51d9b43ad0f8f08b8b3f54eceae0
|
[
"BSD-3-Clause"
] | null | null | null |
services/security.py
|
stuartcampbell/nsls2-api
|
8175e524279f51d9b43ad0f8f08b8b3f54eceae0
|
[
"BSD-3-Clause"
] | null | null | null |
from fastapi import Security
from fastapi.security.api_key import APIKeyHeader
| 20
| 49
| 0.8625
| 11
| 80
| 6.181818
| 0.636364
| 0.323529
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1125
| 80
| 3
| 50
| 26.666667
| 0.957746
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
2ea6ef9e64d8e0592d8256aee3f6f66b86ce6fe1
| 29
|
py
|
Python
|
demo.py
|
mainsail-org/RustPython
|
5d2d87c24f1ff7201fcc8d4fcffadb0ec12dc127
|
[
"CC-BY-4.0",
"MIT"
] | 11,058
|
2018-05-29T07:40:06.000Z
|
2022-03-31T11:38:42.000Z
|
demo.py
|
mainsail-org/RustPython
|
5d2d87c24f1ff7201fcc8d4fcffadb0ec12dc127
|
[
"CC-BY-4.0",
"MIT"
] | 2,105
|
2018-06-01T10:07:16.000Z
|
2022-03-31T14:56:42.000Z
|
demo.py
|
mainsail-org/RustPython
|
5d2d87c24f1ff7201fcc8d4fcffadb0ec12dc127
|
[
"CC-BY-4.0",
"MIT"
] | 914
|
2018-07-27T09:36:14.000Z
|
2022-03-31T19:56:34.000Z
|
print("Hello, RustPython!")
| 9.666667
| 27
| 0.689655
| 3
| 29
| 6.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.103448
| 29
| 2
| 28
| 14.5
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0.642857
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
2c176d2b0a2c61369a1dc4302550a8e839bae2ba
| 11,494
|
py
|
Python
|
openmdao/components/tests/test_exec_comp.py
|
ryanfarr01/blue
|
a9aac98c09cce0f7cadf26cf592e3d978bf4e3ff
|
[
"Apache-2.0"
] | null | null | null |
openmdao/components/tests/test_exec_comp.py
|
ryanfarr01/blue
|
a9aac98c09cce0f7cadf26cf592e3d978bf4e3ff
|
[
"Apache-2.0"
] | null | null | null |
openmdao/components/tests/test_exec_comp.py
|
ryanfarr01/blue
|
a9aac98c09cce0f7cadf26cf592e3d978bf4e3ff
|
[
"Apache-2.0"
] | null | null | null |
import unittest
import math
import numpy as np
from openmdao.api import IndepVarComp, Group, Problem, ExecComp
from openmdao.devtools.testutil import assert_rel_error
class TestExecComp(unittest.TestCase):
def test_colon_vars(self):
prob = Problem(model=Group())
prob.model.add_subsystem('C1', ExecComp('y=foo:bar+1.'))
with self.assertRaises(Exception) as context:
prob.setup(check=False)
self.assertEqual(str(context.exception),
"C1: failed to compile expression 'y=foo:bar+1.'.")
def test_bad_kwargs(self):
prob = Problem(model=Group())
prob.model.add_subsystem('C1', ExecComp('y=x+1.', xx=2.0))
with self.assertRaises(Exception) as context:
prob.setup(check=False)
self.assertEqual(str(context.exception),
"C1: arg 'xx' in call to ExecComp() does not refer to any variable in the expressions ['y=x+1.']")
def test_bad_kwargs_meta(self):
prob = Problem(model=Group())
prob.model.add_subsystem('C1', ExecComp('y=x+1.', x={'val': 2.0, 'low': 0.0, 'high': 10.0, 'units': 'ft'}))
with self.assertRaises(Exception) as context:
prob.setup(check=False)
self.assertEqual(str(context.exception),
"C1: the following metadata names were not recognized for variable 'x': ['high', 'low', 'val']")
def test_name_collision_const(self):
prob = Problem(model=Group())
prob.model.add_subsystem('C1', ExecComp('e=x+1.'))
with self.assertRaises(Exception) as context:
prob.setup(check=False)
self.assertEqual(str(context.exception),
"C1: cannot assign to variable 'e' because it's already defined as an internal function or constant.")
def test_name_collision_func(self):
prob = Problem(model=Group())
prob.model.add_subsystem('C1', ExecComp('sin=x+1.'))
with self.assertRaises(Exception) as context:
prob.setup(check=False)
self.assertEqual(str(context.exception),
"C1: cannot assign to variable 'sin' because it's already defined as an internal function or constant.")
def test_func_as_rhs_var(self):
prob = Problem(model=Group())
prob.model.add_subsystem('C1', ExecComp('y=sin+1.'))
with self.assertRaises(Exception) as context:
prob.setup(check=False)
self.assertEqual(str(context.exception),
"C1: cannot use 'sin' as a variable because it's already defined as an internal function.")
def test_mixed_type(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp('y=numpy.sum(x)',
x=np.arange(10,dtype=float)))
prob.setup(check=False)
self.assertTrue('x' in C1._inputs)
self.assertTrue('y' in C1._outputs)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], 45.0, 0.00001)
def test_simple(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp('y=x+1.', x=2.0))
prob.setup(check=False)
self.assertTrue('x' in C1._inputs)
self.assertTrue('y' in C1._outputs)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], 3.0, 0.00001)
def test_for_spaces(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp('y = pi * x', x=2.0))
prob.setup(check=False)
self.assertTrue('x' in C1._inputs)
self.assertTrue('y' in C1._outputs)
self.assertTrue('pi' not in C1._inputs)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], 2 * math.pi, 0.00001)
def test_units(self):
prob = Problem(model=Group())
prob.model.add_subsystem('indep', IndepVarComp('x', 100.0, units='cm'))
C1 = prob.model.add_subsystem('C1', ExecComp('y=x+z+1.',
x={'value': 2.0, 'units': 'm'},
y={'units': 'm'},
z=2.0))
prob.model.connect('indep.x', 'C1.x')
prob.setup(check=False)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], 4.0, 0.00001)
def test_math(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp('y=sin(x)', x=2.0))
prob.setup(check=False)
self.assertTrue('x' in C1._inputs)
self.assertTrue('y' in C1._outputs)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], math.sin(2.0), 0.00001)
def test_array(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp('y=x[1]',
x=np.array([1.,2.,3.]),
y=0.0))
prob.setup(check=False)
self.assertTrue('x' in C1._inputs)
self.assertTrue('y' in C1._outputs)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], 2.0, 0.00001)
def test_array_lhs(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp(['y[0]=x[1]', 'y[1]=x[0]'],
x=np.array([1.,2.,3.]),
y=np.array([0.,0.])))
prob.setup(check=False)
self.assertTrue('x' in C1._inputs)
self.assertTrue('y' in C1._outputs)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], np.array([2.,1.]), 0.00001)
def test_simple_array_model(self):
prob = Problem()
prob.model = Group()
prob.model.add_subsystem('p1', IndepVarComp('x', np.ones([2])))
prob.model.add_subsystem('comp', ExecComp(['y[0]=2.0*x[0]+7.0*x[1]',
'y[1]=5.0*x[0]-3.0*x[1]'],
x=np.zeros([2]), y=np.zeros([2])))
prob.model.connect('p1.x', 'comp.x')
prob.setup(check=False)
prob.set_solver_print(level=0)
prob.run_model()
data = prob.check_partials(out_stream=None)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][0], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][1], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][2], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][0], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][1], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][2], 0.0, 1e-5)
def test_simple_array_model2(self):
prob = Problem()
prob.model = Group()
prob.model.add_subsystem('p1', IndepVarComp('x', np.ones([2])))
prob.model.add_subsystem('comp', ExecComp('y = mat.dot(x)',
x=np.zeros((2,)), y=np.zeros((2,)),
mat=np.array([[2.,7.],[5.,-3.]])))
prob.model.connect('p1.x', 'comp.x')
prob.setup(check=False)
prob.set_solver_print(level=0)
prob.run_model()
data = prob.check_partials(out_stream=None)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][0], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][1], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['abs error'][2], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][0], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][1], 0.0, 1e-5)
assert_rel_error(self, data['comp'][('y','x')]['rel error'][2], 0.0, 1e-5)
def test_complex_step(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp(['y=2.0*x+1.'], x=2.0))
prob.setup(check=False)
self.assertTrue('x' in C1._inputs)
self.assertTrue('y' in C1._outputs)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], 5.0, 0.00001)
C1._linearize()
assert_rel_error(self, C1.jacobian[('y','x')], [[-2.0]], 0.00001)
def test_complex_step2(self):
prob = Problem(Group())
prob.model.add_subsystem('p1', IndepVarComp('x', 2.0))
prob.model.add_subsystem('comp', ExecComp('y=x*x + x*2.0'))
prob.model.connect('p1.x', 'comp.x')
prob.set_solver_print(level=0)
prob.setup(check=False, mode='fwd')
prob.run_model()
J = prob.compute_total_derivs(['comp.y'], ['p1.x'], return_format='flat_dict')
assert_rel_error(self, J['comp.y', 'p1.x'], np.array([[6.0]]), 0.00001)
prob.setup(check=False, mode='rev')
prob.run_model()
J = prob.compute_total_derivs(['comp.y'], ['p1.x'], return_format='flat_dict')
assert_rel_error(self, J['comp.y', 'p1.x'], np.array([[6.0]]), 0.00001)
def test_abs_complex_step(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp('y=2.0*abs(x)', x=-2.0))
prob.setup(check=False)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], 4.0, 0.00001)
# any negative C1.x should give a 2.0 derivative for dy/dx
C1._inputs['x'] = -1.0e-10
C1._linearize()
assert_rel_error(self, C1.jacobian['y','x'], [[2.0]], 0.00001)
C1._inputs['x'] = 3.0
C1._linearize()
assert_rel_error(self, C1.jacobian['y','x'], [[-2.0]], 0.00001)
C1._inputs['x'] = 0.0
C1._linearize()
assert_rel_error(self, C1.jacobian['y','x'], [[-2.0]], 0.00001)
def test_abs_array_complex_step(self):
prob = Problem(model=Group())
C1 = prob.model.add_subsystem('C1', ExecComp('y=2.0*abs(x)',
x=np.ones(3)*-2.0, y=np.zeros(3)))
prob.setup(check=False)
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, C1._outputs['y'], np.ones(3)*4.0, 0.00001)
# any negative C1.x should give a 2.0 derivative for dy/dx
C1._inputs['x'] = np.ones(3)*-1.0e-10
C1._linearize()
assert_rel_error(self, C1.jacobian['y','x'], np.eye(3)*2.0, 0.00001)
C1._inputs['x'] = np.ones(3)*3.0
C1._linearize()
assert_rel_error(self, C1.jacobian['y','x'], np.eye(3)*-2.0, 0.00001)
C1._inputs['x'] = np.zeros(3)
C1._linearize()
assert_rel_error(self, C1.jacobian['y','x'], np.eye(3)*-2.0, 0.00001)
C1._inputs['x'] = np.array([1.5, -0.6, 2.4])
C1._linearize()
expect = np.zeros((3,3))
expect[0,0] = -2.0
expect[1,1] = 2.0
expect[2,2] = -2.0
assert_rel_error(self, C1.jacobian['y','x'], expect, 0.00001)
if __name__ == "__main__":
unittest.main()
| 37.439739
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| false
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| null | 0
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0
| 6
|
2596e05d2a9716d2c3d88428dd880f441aa74095
| 85,981
|
py
|
Python
|
apps/cookbook/cookbook.py
|
bibbityjibbity/LLL-TAO
|
4073ba412f71bf27d21fd297497a7c276ebd2d67
|
[
"MIT"
] | null | null | null |
apps/cookbook/cookbook.py
|
bibbityjibbity/LLL-TAO
|
4073ba412f71bf27d21fd297497a7c276ebd2d67
|
[
"MIT"
] | null | null | null |
apps/cookbook/cookbook.py
|
bibbityjibbity/LLL-TAO
|
4073ba412f71bf27d21fd297497a7c276ebd2d67
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
#
# cookbook.py - Nexus API Lesson Cook Book
#
# This program teaches you how to use the Nexus APIs. It is an interactive
# walk through of each API that is supported by Nexus Tritium and what
# parameters you need to for a restful call.
#
# The user interface will also use the python SDK but allows the user to
# curl directly to any Nexus node on the network.
#
# Usage: python cookbook.py [<port>]
#
# This program has depends on the nexus_sdk.py SDK library where the master
# copy is in LLL-TAO/sdk/nexus_sdk.py. A shadow copy is in a peer
# directory in TAO-App/sdk/nexus_sdk.py and this application directory
# symlinks to the sdk library (via "import nexus_sdk as nexus")..
#
#------------------------------------------------------------------------------
import commands
import bottle
import sys
import json
import socket
import os
try:
sdk_dir = os.getcwd().split("/")[0:-2]
sdk_dir = "/".join(sdk_dir) + "/sdk"
sys.path.append(sdk_dir)
import nexus_sdk as nexus
except:
print "Need to place nexus_sdk.py in this directory"
exit(0)
#endtry
#
# Did command line have a port number to listen to?
#
cookbook_port = int(sys.argv[1]) if (len(sys.argv) == 2) else 1111
#
# Nexus node to query for API. A change to the SDK URL needs a call to
# nexus_sdk.change_sdk_url().
#
nexus_api_node = "http://localhost:8080"
nexus_sdk_node = "http://localhost:8080"
#
# Keep track of last username logged in.
#
nexus_api_last_username = None
nexus_sdk_last_username = None
#------------------------------------------------------------------------------
def green(string):
output = '<font color="green">{}</font>'.format(string)
return(output)
#enddef
def red(string):
output = '<font color="red">{}</font>'.format(string)
return(output)
#enddef
def blue(string):
output = '<font color="blue">{}</font>'.format(string)
return(output)
#enddef
def bold(string):
string = string.replace("[1m", "<b>")
string = string.replace("[0m", "</b>")
return(string)
#enddef
#
# hl - highlight string
#
# Take the string "{}<method>/<verb>/<noun>?" or "{}<method>/<verb>/<noun>{}"
# and replacae the occurence of "<verb/<noun>" in blue.
#
def hl(string):
left = string.find("/")
right = string.find("?")
if (right == -1): right = string.find("{", 2)
s = string[left+1:right]
s = string.replace(s, blue(s))
return(s)
#enddef
#
# curl
#
# Call curl and return json.
#
def curl(api_command):
global nexus_api_node
url = "{}/{}".format(nexus_api_node, api_command)
output = commands.getoutput('curl --silent "{}"'.format(url))
if (output == "" or output == None):
return({"error" : "curl failed, nexus daemon may not be running"})
#endif
return(json.loads(output))
#enddef
#
# sid_to_sdd
#
# To keep session continuity across web pages.
#
contexts = {}
def sid_to_sdk(sid):
global contexts
if (contexts.has_key(sid)): return(contexts[sid], "")
output = ('"error": Login session {} does not exist - ' + \
'login using users/login/user and click the SDK button').format(sid)
return(None, show(output))
#enddef
#
# format_transactions
#
# Put a line per array element so the eyes can parse each transaction record
# just a tad better. Used for most */list/* methods.
#
def format_transactions(data):
if (data.has_key("result") == False): return(json.dumps(data))
if (data["result"] == None): return('{"error": "no json returned"}')
output = json.dumps(data)
return(output)
#enddef
#
# no_parms
#
# Checks that any supplied arg in the variable list of arguments is "" or None.
#
def no_parms(*args):
for a in args:
if (a == "" or a == None): return(True)
#endfor
return(False)
#enddef
#------------------------------------------------------------------------------
show_html = '''
<br><table align="left" style="word-break:break-all;">
<tr><td>{}</td></tr>
</table><br> <br><hr size="5">
'''
#
# show
#
# This is JSON output returned from Nexus API.
#
def show(msg, sid="", genid=""):
msg = red(msg) if (msg.find('"error":') != -1) else green(msg)
output = show_html.format(bold(msg)) + build_body_page(sid, genid)
hostname = blue(socket.gethostname())
sdk = blue(nexus_sdk_last_username)
api = blue(nexus_api_last_username)
return(landing_page.format(hostname, sdk, api, output))
#enddef
#
# Wrapper to make all web pages look alike, from a format perspective.
#
landing_page = '''
<html>
<title>Nexus Interactive SDK/API Cook Book</title>
<body bgcolor="gray">
<div style="margin:20px;background-color:#F5F5F5;padding:15px;
border-radius:20px;border:5px solid #666666;">
<font face="verdana"><center>
<br><head><a href="/" style="text-decoration:none;"><font color="black">
<b>Nexus Interactive SDK/API Cook Book</b></a></head><br>
<font size="2""><br>Running on {}, last logged in SDK/API user {}/{}</font>
<br><br><hr size="5">
{}
<hr size="5"></center></font></body></html>
'''
#
# Used as a generic template for all API calls. Used for form input from
# the web interface.
#
form_header = '<form action="/{}" method="post">'
form_parm = '<input type="text" name="{}" value="{}" size="15" />'
form_footer = '''
<input type="submit" value="SDK" name="action" />
<input type="submit" value="API" name="action" />
</form>
'''
#------------------------------------------------------------------------------
#
# build_url_html
#
# Put in two form lines for user to change SDK or API URL.
#
def build_url_html(o):
global nexus_api_node, nexus_sdk_node
o += "<br><b>Nexus Node URLs</b><br><br><table>"
o += '''
<form action="/url/sdk" method="post">
SDK:
<input type="text" name="url" value="{}" size="30" />
<input type="submit" value="Change URL" name="action" />
</form>
<form action="/url/api" method="post">
API:
<input type="text" name="url" value="{}" size="30" />
<input type="submit" value="Change URL" name="action" />
</form>
<br><br><hr size="5">
'''.format(nexus_sdk_node, nexus_api_node)
return(o)
#enddef
#
# build_system_html
#
system_get_info = '{}system/get/info{}'
system_list_peers = '{}system/list/peers{}'
system_list_lisp_eids = '{}system/list/lisp-eids{}'
def build_system_html(sid, genid, o):
f = form_footer
o += "<br><b>System API</b><br><br><table>"
o += "<tr><td>"
h = form_header.format("system-get-info")
o += hl(system_get_info).format(h, "<br><br>" + f)
o += "</td>"
o += "<td> </td>"
o += "<td>"
h = form_header.format("system-list-peers")
o += hl(system_list_peers).format(h, "<br><br>" + f)
o += "</td>"
o += "<td> </td>"
o += "<td>"
h = form_header.format("system-list-lisp-eids")
o += hl(system_list_lisp_eids).format(h, "<br><br>" + f)
o += "</td></tr>"
o += '</table><br><hr size="5">'
return(o)
#enddef
@bottle.route('/system-get-info', method="post")
def do_system_get_info():
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk = nexus.sdk_init("system", "get/info", "")
if (sdk == None): return(show(red("Could not initialize SDK")))
output = sdk.nexus_system_get_info()
del(sdk)
else:
output = curl(system_get_info.format("", ""))
#endif
output = json.dumps(output)
return(show(output))
#enddef
@bottle.route('/system-list-peers', method="post")
def do_system_list_peers():
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk = nexus.sdk_init("system", "list/peers", "")
if (sdk == None): return(show(red("Could not initialize SDK")))
output = sdk.nexus_system_list_peers()
del(sdk)
else:
output = curl(system_list_peers.format("", ""))
#endif
output = json.dumps(output)
return(show(output))
#enddef
@bottle.route('/system-list-lisp-eids', method="post")
def do_system_list_lisp_eids():
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk = nexus.sdk_init("system", "lisp/lisp-eids", "")
if (sdk == None): return(show(red("Could not initialize SDK")))
output = sdk.nexus_system_list_lisp_eids()
del(sdk)
else:
output = curl(system_list_lisp_eids.format("", ""))
#endif
output = json.dumps(output)
return(show(output))
#enddef
#------------------------------------------------------------------------------
#
# build_users_html
#
users_create_user = '{}users/create/user?username={}&password={}&pin={}{}'
users_login_user = '{}users/login/user?username={}&password={}&pin={}{}'
users_logout_user = '{}users/logout/user?session={}{}'
users_lock_user = '{}users/lock/user?session={}{}'
users_unlock_user = '{}users/unlock/user?session={}&pin={}{}'
users_list_transactions = \
'{}users/list/transactions?genesis={}&page={}&limit={}&verbose={}{}'
users_list_notifications = \
'{}users/list/notifications?genesis={}&page={}&limit={}{}'
users_list_items = '{}users/list/items?genesis={}&page={}&limit={}{}'
users_list_assets = '{}users/list/assets?genesis={}&page={}&limit={}{}'
users_list_tokens = '{}users/list/tokens?genesis={}&page={}&limit={}{}'
users_list_accounts = '{}users/list/accounts?genesis={}&page={}&limit={}{}'
def build_users_html(sid, genid, o):
f = form_footer
o += "<br><b>Users API</b><br><br><table>"
o += "<tr><td>"
h = form_header.format("users-login-user")
username = form_parm.format("username", "")
password = form_parm.format("password", "")
pin = form_parm.format("pin", "")
o += hl(users_login_user).format(h, username, password, pin, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("users-logout-user")
session = form_parm.format("session", sid)
o += hl(users_logout_user).format(h, session, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("users-create-user")
username = form_parm.format("username", "")
password = form_parm.format("password", "")
pin = form_parm.format("pin", "")
o += hl(users_create_user).format(h, username, password, pin, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("users-lock-user")
session = form_parm.format("session", sid)
o += hl(users_lock_user).format(h, session, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("users-unlock-user")
session = form_parm.format("session", sid)
pin = form_parm.format("pin", "")
o += hl(users_unlock_user).format(h, session, pin, f)
o += "</td></tr>"
o += "<tr><td>"
h = "users-list-transactions"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
genesis = form_parm.format("genesis", genid)
page = form_parm.format("page", "0")
limit = form_parm.format("limit", "100")
verbose = form_parm.format("verbose", "default")
o += hl(users_list_transactions).format(h, genesis, page, limit, verbose,
f)
o += "</td></tr>"
o += "<tr><td>"
h = "users-list-notifications"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
genesis = form_parm.format("genesis", genid)
page = form_parm.format("page", "0")
limit = form_parm.format("limit", "100")
o += hl(users_list_notifications).format(h, genesis, page, limit, f)
o += "</td></tr>"
o += "<tr><td>"
h = "users-list-items"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
genesis = form_parm.format("genesis", genid)
page = form_parm.format("page", "0")
limit = form_parm.format("limit", "100")
o += hl(users_list_items).format(h, genesis, page, limit, f)
o += "</td></tr>"
o += "<tr><td>"
h = "users-list-assets"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
genesis = form_parm.format("genesis", genid)
page = form_parm.format("page", "0")
limit = form_parm.format("limit", "100")
o += hl(users_list_assets).format(h, genesis, page, limit, f)
o += "</td></tr>"
o += "<tr><td>"
h = "users-list-tokens"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
genesis = form_parm.format("genesis", genid)
page = form_parm.format("page", "0")
limit = form_parm.format("limit", "100")
o += hl(users_list_tokens).format(h, genesis, page, limit, f)
o += "</td></tr>"
o += "<tr><td>"
h = "users-list-accounts"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
genesis = form_parm.format("genesis", genid)
page = form_parm.format("page", "0")
limit = form_parm.format("limit", "100")
o += hl(users_list_accounts).format(h, genesis, page, limit, f)
o += "</td></tr>"
o += '</table><br><hr size="5">'
return(o)
#enddef
@bottle.route('/users-create-user', method="post")
def do_users_create_user():
username = bottle.request.forms.get("username")
password = bottle.request.forms.get("password")
pin = bottle.request.forms.get("pin")
if (no_parms(username, password, pin)):
m = red("users/create/user needs more input parameters")
return(show(m))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk = nexus.sdk_init(username, password, pin)
output = sdk.nexus_users_create_user()
else:
output = curl(users_create_user.format("", username, password, pin,
""))
#endif
output = json.dumps(output)
return(show(output))
#enddef
@bottle.route('/users-login-user', method="post")
def do_users_login_user():
global contexts
global nexus_api_last_username, nexus_sdk_last_username
username = bottle.request.forms.get("username")
password = bottle.request.forms.get("password")
pin = bottle.request.forms.get("pin")
if (no_parms(username, password, pin)):
m = red("users/login/user needs more input parameters")
return(show(m))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk = nexus.sdk_init(username, password, pin)
output = sdk.nexus_users_login_user()
sid, genid = [sdk.session_id, sdk.genesis_id]
contexts[sid] = sdk
if (output.has_key("error") == False):
nexus_sdk_last_username = username
#endif
else:
output = curl(users_login_user.format("", username, password, pin, ""))
sid = output["result"]["session"] if output.has_key("result") else ""
genid = output["result"]["genesis"] if output.has_key("result") else ""
if (output.has_key("error") == False):
nexus_api_last_username = username
#endif
#endif
output = json.dumps(output)
return(show(output, sid, genid))
#enddef
@bottle.route('/users-logout-user', method="post")
def do_users_logout_user():
session = bottle.request.forms.get("session")
if (no_parms(session)):
m = red("users/logout/user needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_users_logout_user()
genid = sdk.genesis_id
else:
output = curl(users_logout_user.format("", session, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/users-lock-user', method="post")
def do_users_lock_user():
session = bottle.request.forms.get("session")
if (no_parms(session)):
m = red("users/lock/user needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_users_lock_user()
genid = sdk.genesis_id
else:
output = curl(users_lock_user.format("", session, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/users-unlock-user', method="post")
def do_users_unlock_user():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
if (no_parms(pin, session)):
m = red("users/unlock/user needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_users_unlock_user()
genid = sdk.genesis_id
else:
output = curl(users_unlock_user.format("", session, pin, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/users-list-transactions', method="post")
@bottle.route('/users-list-transactions/<sid>', method="post")
def do_users_list_transactions(sid=""):
genesis = bottle.request.forms.get("genesis")
page = bottle.request.forms.get("page")
limit = bottle.request.forms.get("limit")
verbose = bottle.request.forms.get("verbose")
if (no_parms(genesis, page, limit, verbose)):
m = red("users/list/transactions needs more input parameters")
return(show(m, sid, genesis))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_users_list_transactions_by_genesis(page, limit,
verbose)
else:
output = curl(users_list_transactions.format("", genesis, page, limit,
verbose, ""))
#endif
output = format_transactions(output)
return(show(output, sid, genesis))
#enddef
@bottle.route('/users-list-notifications', method="post")
@bottle.route('/users-list-notifications/<sid>', method="post")
def do_users_list_notifications(sid=""):
genesis = bottle.request.forms.get("genesis")
page = bottle.request.forms.get("page")
limit = bottle.request.forms.get("limit")
if (no_parms(genesis, page, limit)):
m = red("users/list/notifications needs more input parameters")
return(show(m, sid, genesis))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_users_list_notifications_by_genesis(page, limit)
else:
output= curl(users_list_notifications.format("", genesis, page, limit,
""))
#endif
output = format_transactions(output)
return(show(output, sid, genesis))
#enddef
@bottle.route('/users-list-items', method="post")
@bottle.route('/users-list-items/<sid>', method="post")
def do_users_list_items(sid=""):
genesis = bottle.request.forms.get("genesis")
page = bottle.request.forms.get("page")
limit = bottle.request.forms.get("limit")
if (no_parms(genesis, page, limit)):
m = red("users/list/items needs more input parameters")
return(show(m, sid, genesis))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_users_list_items_by_genesis(page, limit)
else:
output= curl(users_list_items.format("", genesis, page, limit, ""))
#endif
output = format_transactions(output)
return(show(output, sid, genesis))
#enddef
@bottle.route('/users-list-assets', method="post")
@bottle.route('/users-list-assets/<sid>', method="post")
def do_users_list_assets(sid=""):
genesis = bottle.request.forms.get("genesis")
page = bottle.request.forms.get("page")
limit = bottle.request.forms.get("limit")
if (no_parms(genesis, page, limit)):
m = red("users/list/assets needs more input parameters")
return(show(m, sid, genesis))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_users_list_assets_by_genesis(page, limit)
else:
output= curl(users_list_assets.format("", genesis, page, limit, ""))
#endif
output = format_transactions(output)
return(show(output, sid, genesis))
#enddef
@bottle.route('/users-list-tokens', method="post")
@bottle.route('/users-list-tokens/<sid>', method="post")
def do_users_list_tokens(sid=""):
genesis = bottle.request.forms.get("genesis")
page = bottle.request.forms.get("page")
limit = bottle.request.forms.get("limit")
if (no_parms(genesis, page, limit)):
m = red("users/list/tokens needs more input parameters")
return(show(m, sid, genesis))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_users_list_tokens_by_genesis(page, limit)
else:
output= curl(users_list_tokens.format("", genesis, page, limit, ""))
#endif
output = format_transactions(output)
return(show(output, sid, genesis))
#enddef
@bottle.route('/users-list-accounts', method="post")
@bottle.route('/users-list-accounts/<sid>', method="post")
def do_users_list_accounts(sid=""):
genesis = bottle.request.forms.get("genesis")
page = bottle.request.forms.get("page")
limit = bottle.request.forms.get("limit")
if (no_parms(genesis, page, limit)):
m = red("users/list/accounts needs more input parameters")
return(show(m, sid, genesis))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_users_list_accounts_by_genesis(page, limit)
else:
output= curl(users_list_accounts.format("", genesis, page, limit, ""))
#endif
output = format_transactions(output)
return(show(output, sid, genesis))
#enddef
#------------------------------------------------------------------------------
#
# build_supply_html
#
supply_create_item = \
'{}supply/create/item?pin={}&session={}&name={}&data={}{}'
supply_get_item_name = '{}supply/get/item?session={}&name={}{}'
supply_get_item_address = '{}supply/get/item?session={}&address={}{}'
supply_update_item = \
'{}supply/update/item?pin={}&session={}&address={}&data={}{}'
supply_transfer_item = ('{}supply/transfer/item?pin={}&session={}' + \
'&address={}&destination={}{}')
supply_claim_item = '{}supply/claim/item?pin={}&session={}&txid={}{}'
supply_list_item_history_name = \
'{}supply/list/item/history?session={}&name={}{}'
supply_list_item_history_address = \
'{}supply/list/item/history?session={}&address={}{}'
def build_supply_html(sid, genid, o):
f = form_footer
o += "<br><b>Supply Chain API</b><br><br><table>"
o += "<tr><td>"
h = "supply-get-item-name"
h = form_header.format(h)
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
o += hl(supply_get_item_name).format(h, session, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "supply-get-item-address"
h = form_header.format(h)
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
o += hl(supply_get_item_address).format(h, session, address, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("supply-create-item")
pin = form_parm.format("pin", "")
name = form_parm.format("name", "")
data = form_parm.format("data", "")
session = form_parm.format("session", sid)
o += hl(supply_create_item).format(h, pin, session, name, data, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("supply-update-item")
pin = form_parm.format("pin", "")
data = form_parm.format("data", "")
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
o += hl(supply_update_item).format(h, pin, session, address, data, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("supply-transfer-item")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
d = form_parm.format("destination", "")
o += hl(supply_transfer_item).format(h, pin, session, address, d, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("supply-claim-item")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
txid = form_parm.format("txid", "")
o += hl(supply_claim_item).format(h, pin, session, txid, f)
o += "</td></tr>"
o += "<tr><td>"
h = "supply-list-item-history-name"
h = form_header.format(h)
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
o += hl(supply_list_item_history_name).format(h, session, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "supply-list-item-history-address"
h = form_header.format(h)
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
o += hl(supply_list_item_history_address).format(h, session, address, f)
o += "</td></tr>"
o += '</table><br><hr size="5">'
return(o)
#enddef
@bottle.route('/supply-create-item', method="post")
def do_supply_create_item():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
data = bottle.request.forms.get("data")
if (no_parms(pin, session, data)):
m = red("supply/create/item needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_supply_create_item(name, data)
genid = sdk.genesis_id
else:
output = curl(supply_create_item.format("", pin, session, name, data,
""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/supply-get-item-name', method="post")
def do_supply_get_item_name():
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
if (no_parms(session, name)):
m = red("supply/get/item needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_supply_get_item_by_name(name)
genid = sdk.genesis_id
else:
output = curl(supply_get_item_name.format("", session, name, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/supply-get-item-address', method="post")
def do_supply_get_item_address():
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
if (no_parms(session, address)):
m = red("supply/get/item needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_supply_get_item_by_address(address)
genid = sdk.genesis_id
else:
output = curl(supply_get_item_address.format("", session, address, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/supply-update-item', method="post")
def do_supply_update_item():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
data = bottle.request.forms.get("data")
if (no_parms(pin, session, address, data)):
m = red("supply/update/item needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_supply_update_item_by_address(address, data)
genid = sdk.genesis_id
else:
output = curl(supply_update_item.format("", pin, session, address,
data, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/supply-transfer-item', method="post")
def do_supply_transfer_item():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
dest = bottle.request.forms.get("destination")
if (no_parms(pin, session, address, dest)):
m = red("supply/transfer/item needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_supply_transfer_item_by_address(address, dest)
genid = sdk.genesis_id
else:
output = curl(supply_transfer_item.format("", pin, session, address,
dest, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/supply-claim-item', method="post")
def do_supply_claim_item():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
txid = bottle.request.forms.get("txid")
if (no_parms(pin, session, txid)):
m = red("supply/claim/item needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_supply_claim_item(txid)
genid = sdk.genesis_id
else:
output = curl(supply_claim_item.format("", pin, session, txid, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/supply-list-item-history-name', method="post")
def do_supply_list_item_history_name():
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
if (no_parms(session, name)):
m = red("supply/list/item/history needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_supply_list_item_history_by_name(name)
genid = sdk.genesis_id
else:
output = curl(supply_list_item_history_name.format("", session, name,
""))
genid = ""
#endif
output = format_transactions(output)
return(show(output, session, genid))
#enddef
@bottle.route('/supply-list-item-history-address', method="post")
def do_supply_list_item_history_address():
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
if (no_parms(session, address)):
m = red("supply/list/item/history needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_supply_list_item_history_by_address(address)
genid = sdk.genesis_id
else:
output = curl(supply_list_item_history_address.format("", session,
address, ""))
genid = ""
#endif
output = format_transactions(output)
return(show(output, session, genid))
#enddef
#------------------------------------------------------------------------------
#
# build_assets_html
#
assets_create_asset = \
'{}assets/create/asset?pin={}&session={}&name={}&format=raw&data={}{}'
assets_get_asset_name = '{}assets/get/asset?session={}&name={}{}'
assets_get_asset_address = '{}assets/get/asset?session={}&address={}{}'
assets_update_asset = \
'{}assets/update/asset?pin={}&session={}&address={}&data={}{}'
assets_transfer_asset = \
'{}assets/transfer/asset?pin={}&session={}&address={}&destination={}{}'
assets_claim_asset = '{}assets/claim/asset?pin={}&session={}&txid={}{}'
assets_tokenize_asset = \
'{}assets/tokenize/asset?pin={}&session={}&token_name={}&asset_name={}{}'
assets_list_asset_history_name = \
'{}assets/list/asset/history?session={}&name={}{}'
assets_list_asset_history_address = \
'{}assets/list/asset/history?session={}&address={}{}'
def build_assets_html(sid, genid, o):
f = form_footer
o += "<br><b>Assets API</b><br><br><table>"
o += "<tr><td>"
h = "assets-get-asset-name"
h = form_header.format(h)
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
o += hl(assets_get_asset_name).format(h, session, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "assets-get-asset-address"
h = form_header.format(h)
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
o += hl(assets_get_asset_address).format(h, session, address, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("assets-create-asset")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
data = form_parm.format("data", "")
name = form_parm.format("name", "")
o += hl(assets_create_asset).format(h, pin, session, name, data, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("assets-update-asset")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
data = form_parm.format("data", "")
address = form_parm.format("address", sid)
o += hl(assets_update_asset).format(h, pin, session, data, address, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("assets-transfer-asset")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
d = form_parm.format("destination", "")
o += hl(assets_transfer_asset).format(h, pin, session, address, d, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("assets-claim-asset")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
txid = form_parm.format("txid", "")
o += hl(assets_claim_asset).format(h, pin, session, txid, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("assets-tokenize-asset")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
token_name = form_parm.format("token_name", "")
asset_name = form_parm.format("asset_name", "")
o += hl(assets_tokenize_asset).format(h, pin, session, token_name,
asset_name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "assets-list-asset-history-name"
h = form_header.format(h)
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
o += hl(assets_list_asset_history_name).format(h, session, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "assets-list-asset-history-address"
h = form_header.format(h)
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
o += hl(assets_list_asset_history_address).format(h, session, address, f)
o += "</td></tr>"
o += '</table><br><hr size="5">'
return(o)
#enddef
@bottle.route('/assets-create-asset', method="post")
def do_assets_create_asset():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
data = bottle.request.forms.get("data")
if (no_parms(pin, session, name, data)):
m = red("assets/create/asset needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_create_asset(name, data)
genid = sdk.genesis_id
else:
output = curl(assets_create_asset.format("", pin, session, name, data,
""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/assets-update-asset', method="post")
def do_assets_update_asset():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
data = bottle.request.forms.get("data")
if (no_parms(pin, session, address, data)):
m = red("assets/update/asset needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_update_asset_by_address(address, data)
genid = sdk.genesis_id
else:
output = curl(assets_update_asset.format("", pin, session, address,
data, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/assets-get-asset-name', method="post")
def do_assets_get_asset_name():
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
if (no_parms(session, name)):
m = red("assets/get/asset needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_get_asset_by_name(name)
genid = sdk.genesis_id
else:
output = curl(assets_get_asset_name.format("", session, name, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/assets-get-asset-address', method="post")
def do_assets_get_asset_address():
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
if (no_parms(session, address)):
m = red("assets/get/asset needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_get_asset_by_address(address)
genid = sdk.genesis_id
else:
output = curl(assets_get_asset_address.format("", session, address,
""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/assets-transfer-asset', method="post")
def do_assets_transfer_asset():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
dest = bottle.request.forms.get("destination")
if (no_parms(pin, session, address, dest)):
m = red("assets/transfer/asset needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_transfer_asset_by_address(address, dest)
genid = sdk.genesis_id
else:
output = curl(assets_transfer_asset.format("", pin, session, address,
dest, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/assets-claim-asset', method="post")
def do_assets_claim_asset():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
txid = bottle.request.forms.get("txid")
if (no_parms(session, txid)):
m = red("assets/claim/asset needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_claim_asset(txid)
genid = sdk.genesis_id
else:
output = curl(assets_claim_asset.format("", pin, session, txid, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/assets-tokenize-asset', method="post")
def do_assets_tokenize_asset():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
token_name = bottle.request.forms.get("token_name")
asset_name = bottle.request.forms.get("asset_name")
if (no_parms(pin, session, token_name, asset_name)):
m = red("assets/tokenize/asset needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_tokenize_asset_by_name(asset_name,
token_name)
genid = sdk.genesis_id
else:
output = curl(assets_tokenize_asset.format("", pin, session,
token_name, asset_name, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/assets-list-asset-history-name', method="post")
def do_assets_list_asset_history_name():
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
if (no_parms(session, name)):
m = red("assets/list/asset/history needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_list_asset_history_by_name(name)
genid = sdk.genesis_id
else:
output = curl(assets_list_asset_history_name.format("", session, name,
""))
genid = ""
#endif
output = format_transactions(output)
return(show(output, session, genid))
#enddef
@bottle.route('/assets-list-asset-history-address', method="post")
def do_assets_list_asset_history_address():
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
if (no_parms(session, address)):
m = red("assets/list/asset/history needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_assets_list_asset_history_by_address(address)
genid = sdk.genesis_id
else:
output = curl(assets_list_asset_history_address.format("", session,
address, ""))
genid = ""
#endif
output = format_transactions(output)
return(show(output, session, genid))
#enddef
#------------------------------------------------------------------------------
#
# build_accounts_html
#
tokens_create_token = \
'{}tokens/create/token?pin={}&session={}&name={}&supply={}&decimals={}{}'
tokens_create_account = \
'{}tokens/create/account?pin={}&session={}&name={}&token_name={}{}'
tokens_get_token_name = '{}tokens/get/token?session={}&name={}{}'
tokens_get_token_address = '{}tokens/get/token?session={}&address={}{}'
tokens_get_account_name = '{}tokens/get/account?session={}&name={}{}'
tokens_get_account_address = '{}tokens/get/account?session={}&address={}{}'
tokens_debit_token = ('{}tokens/debit/token?pin={}&session={}&name={}' + \
'&name_to={}&amount={}{}')
tokens_credit_token = ('{}tokens/credit/token?pin={}&session={}&name={}' + \
'&amount={}&txid={}{}')
tokens_debit_account = ('{}tokens/debit/account?pin={}&session={}' + \
'&amount={}&name={}&name_to={}{}')
tokens_credit_account = ('{}tokens/credit/account?pin={}&session={}' + \
'&txid={}&amount={}&name={}&name_proof={}{}')
def build_tokens_html(sid, genid, o):
f = form_footer
o += "<br><b>Tokens API</b><br><br><table>"
o += "<tr><td>"
h = "tokens-get-token-name"
h = form_header.format(h)
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
o += hl(tokens_get_token_name).format(h, session, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "tokens-get-token-address"
h = form_header.format(h)
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
o += hl(tokens_get_token_address).format(h, session, address, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("tokens-create-token")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
supply = form_parm.format("supply", "")
d = form_parm.format("decimals", "2")
o += hl(tokens_create_token).format(h, pin, session, name, supply, d, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("tokens-debit-token")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
amount = form_parm.format("amount", "")
name = form_parm.format("name", "")
name_to = form_parm.format("name_to", "")
o += hl(tokens_debit_token).format(h, pin, session, name, name_to, amount,
f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("tokens-credit-token")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
amount = form_parm.format("amount", "")
txid = form_parm.format("txid", "")
o += hl(tokens_credit_token).format(h, pin, session, name, amount, txid, f)
o += "</td></tr>"
o += "<tr><td>"
h = "tokens-get-account-name"
h = form_header.format(h)
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
o += hl(tokens_get_account_name).format(h, session, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "tokens-get-account-address"
h = form_header.format(h)
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
o += hl(tokens_get_account_address).format(h, session, address, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("tokens-create-account")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
token_name = form_parm.format("token_name", "")
o += hl(tokens_create_account).format(h, pin, session, name, token_name, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("tokens-debit-account")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
amount = form_parm.format("amount", "")
name = form_parm.format("name", "")
name_to = form_parm.format("name_to", "")
o += hl(tokens_debit_account).format(h, pin, session, amount, name,
name_to, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("tokens-credit-account")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
txid = form_parm.format("txid", "")
amount = form_parm.format("amount", "")
name = form_parm.format("name", "")
proof = form_parm.format("name_proof", "")
o += hl(tokens_credit_account).format(h, pin, session, txid, amount, name,
proof, f)
o += "</td></tr>"
o += '</table><br><hr size="5">'
return(o)
#enddef
@bottle.route('/tokens-create-token', method="post")
def do_tokens_create_token():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
supply = bottle.request.forms.get("supply")
decimals = bottle.request.forms.get("decimals")
if (no_parms(pin, session, name, supply, decimals)):
m = red("tokens/create/token needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_create_token(name, supply, decimals)
genid = sdk.genesis_id
else:
output = curl(tokens_create_token.format("", pin, session, name,
supply, decimals, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-create-account', method="post")
def do_tokens_create_account():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
token_name = bottle.request.forms.get("token_name")
if (no_parms(pin, session, name, token_name)):
m = red("tokens/create/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_create_account(name, token_name)
genid = sdk.genesis_id
else:
output = curl(tokens_create_account.format("", pin, session, name,
token_name, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-get-token-name', method="post")
def do_tokens_get_token_name():
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
if (no_parms(session, name)):
m = red("tokens/get/token needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_get_token_by_name(name)
genid = sdk.genesis_id
else:
output = curl(tokens_get_token_name.format("", session, name, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-get-token-address', method="post")
def do_tokens_get_token_address():
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
if (no_parms(session, address)):
m = red("tokens/get/token needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_get_token_by_address(address)
genid = sdk.genesis_id
else:
output = curl(tokens_get_token_address.format("", session, address,
""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-get-account-name', method="post")
def do_tokens_get_account_name():
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
if (no_parms(session, name)):
m = red("tokens/get/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_get_account_by_name(name)
genid = sdk.genesis_id
else:
output = curl(tokens_get_account_name.format("", session, name, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-get-account-address', method="post")
def do_tokens_get_account_address():
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
if (no_parms(session, address)):
m = red("tokens/get/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_get_account_by_address(address)
genid = sdk.genesis_id
else:
output = curl(tokens_get_account_address.format("", session, address,
""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-debit-token', method="post")
def do_tokens_debit_token():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
amount = bottle.request.forms.get("amount")
name = bottle.request.forms.get("name")
name_to = bottle.request.forms.get("name_to")
if (no_parms(pin, session, amount, name, name_to)):
return(show(red("tokens/debit/token needs more input parameters"),
session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_debit_token_by_name(name, name_to, amount)
genid = sdk.genesis_id
else:
output = curl(tokens_debit_token.format("", pin, session, name,
name_to, amount, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-credit-token', method="post")
def do_tokens_credit_token():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
amount = bottle.request.forms.get("amount")
name = bottle.request.forms.get("name")
txid = bottle.request.forms.get("txid")
if (no_parms(pin, session, name, amount, txid)):
m = red("tokens/credit/token needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_credit_token_by_name(name, amount, txid)
genid = sdk.genesis_id
else:
output = curl(tokens_debit_account.format("", pin, session, name,
amount, txid, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-debit-account', method="post")
def do_tokens_debit_account():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
amount = bottle.request.forms.get("amount")
name = bottle.request.forms.get("name")
name_to = bottle.request.forms.get("name_to")
if (no_parms(pin, session, amount, name, name_to)):
m = red("tokens/debit/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_debit_account_by_name(name, name_to, amount)
genid = sdk.genesis_id
else:
output = curl(tokens_debit_account.format("", pin, session, amount,
name, name_to, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/tokens-credit-account', method="post")
def do_tokens_credit_account():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
txid = bottle.request.forms.get("txid")
amount = bottle.request.forms.get("amount")
name = bottle.request.forms.get("name")
name_proof = bottle.request.forms.get("name_proof")
if (no_parms(pin, session, txid, amount, name, name_proof)):
m = red("tokens/credit/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_tokens_credit_account_by_name(name, amount, txid)
genid = sdk.genesis_id
else:
output = curl(tokens_credit_account.format("", pin, session, txid,
amount, name, name_proof, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
#------------------------------------------------------------------------------
#
# build_finance_html
#
finance_create_account = '{}finance/create/account?pin={}&session={}&name={}{}'
finance_get_account_name = '{}finance/get/account?session={}&name={}{}'
finance_get_account_address = '{}finance/get/account?session={}&address={}{}'
finance_debit_account = ('{}finance/debit/account?pin={}&session={}' + \
'&amount={}&name_from={}&name_to={}{}')
finance_credit_account = ('{}finance/credit/account?pin={}&session={}' + \
'&txid={}&amount={}&name_to={}&name_proof={}{}')
finance_list_accounts = '{}finance/list/accounts?session={}{}'
finance_get_stakeinfo = '{}finance/get/stakeinfo?session={}{}'
finance_set_stake = '{}finance/set/stake?pin={}&session={}&amount={}{}'
def build_finance_html(sid, genid, o):
f = form_footer
o += "<br><b>Finance API</b><br><br><table>"
o += "<tr><td>"
h = "finance-get-account-name"
h = form_header.format(h)
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
o += hl(finance_get_account_name).format(h, session, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "finance-get-account-address"
h = form_header.format(h)
session = form_parm.format("session", sid)
address = form_parm.format("address", "")
o += hl(finance_get_account_address).format(h, session, address, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("finance-create-account")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
o += hl(finance_create_account).format(h, pin, session, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("finance-debit-account")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
amount = form_parm.format("amount", "")
name_from = form_parm.format("name_from", "")
name_to = form_parm.format("name_to", "")
o += hl(finance_debit_account).format(h, pin, session, amount, name_from,
name_to, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("finance-credit-account")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
txid = form_parm.format("txid", "")
amount = form_parm.format("amount", "")
name_to = form_parm.format("name_to", "")
proof = form_parm.format("name_proof", "")
o += hl(finance_credit_account).format(h, pin, session, txid, amount,
name_to, proof, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("finance-get-stakeinfo")
session = form_parm.format("session", sid)
o += hl(finance_get_stakeinfo).format(h, session, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("finance-set-stake")
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
amount = form_parm.format("amount", "")
o += hl(finance_set_stake).format(h, pin, session, amount, f)
o += "</td></tr>"
o += "<tr><td>"
h = form_header.format("finance-list-accounts")
session = form_parm.format("session", sid)
o += hl(finance_list_accounts).format(h, session, f)
o += "</td></tr>"
o += '</table><br><hr size="5">'
return(o)
#enddef
@bottle.route('/finance-get-account-name', method="post")
def do_finance_get_account_name():
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
if (no_parms(session, name)):
m = red("finance/get/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_finance_get_account_by_name(name)
genid = sdk.genesis_id
else:
output = curl(finance_get_account_name.format("", session, name, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/finance-get-account-address', method="post")
def do_finance_get_account_address():
session = bottle.request.forms.get("session")
address = bottle.request.forms.get("address")
if (no_parms(session, address)):
m = red("finance/get/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_finance_get_account_by_address(address)
genid = sdk.genesis_id
else:
output = curl(finance_get_account_address.format("", session, address,
""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/finance-create-account', method="post")
def do_finance_create_account():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
if (no_parms(pin, session, name)):
m = red("finance/create/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_finance_create_account(name)
genid = sdk.genesis_id
else:
output = curl(finance_create_account.format("", pin, session, name,
""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/finance-debit-account', method="post")
def do_finance_debit_account():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
amount = bottle.request.forms.get("amount")
name_from = bottle.request.forms.get("name_from")
name_to = bottle.request.forms.get("name_to")
if (no_parms(pin, session, amount, name_from, name_to)):
return(show(red("finance/debit/account needs more input parameters"),
session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_finance_debit_account_by_name(name_from, name_to,
amount)
genid = sdk.genesis_id
else:
output = curl(finance_debit_account.format("", pin, session, amount,
name_from, name_to, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/finance-credit-account', method="post")
def do_finance_credit_account():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
txid = bottle.request.forms.get("txid")
amount = bottle.request.forms.get("amount")
name_to = bottle.request.forms.get("name_to")
name_proof = bottle.request.forms.get("name_proof")
if (no_parms(pin, session, txid, amount, name_to, name_proof)):
m = red("finance/credit/account needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_finance_credit_account_by_name(name_to, amount,
txid)
genid = sdk.genesis_id
else:
output = curl(finance_credit_account.format("", pin, session, txid,
amount, name_to, name_proof, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/finance-list-accounts', method="post")
def do_list_accounts():
session = bottle.request.forms.get("session")
if (no_parms(session)):
m = red("finance/list/acccounts needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_finance_list_accounts()
genid = sdk.genesis_id
else:
output = curl(finance_list_accounts.format("", session, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/finance-get-stakeinfo', method="post")
def do_get_stakeinfo():
session = bottle.request.forms.get("session")
if (no_parms(session)):
m = red("finance/get/stakeinfo needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_finance_get_stakeinfo()
genid = sdk.genesis_id
else:
output = curl(finance_get_stakeinfo.format("", session, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/finance-set-stake', method="post")
def do_set_stake():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
amount = bottle.request.forms.get("amount")
if (no_parms(pin, session, amount)):
m = red("finance/set/stake needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_finance_set_stake(amount)
genid = sdk.genesis_id
else:
output = curl(finance_set_stake.format("", pin, session, amount, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
#------------------------------------------------------------------------------
#
# build_ledger_html
#
ledger_get_blockhash = '{}ledger/get/blockhash?height={}{}'
ledger_get_block_height = '{}ledger/get/block?height={}&verbose={}{}'
ledger_get_block_hash = '{}ledger/get/block?hash={}&verbose={}{}'
ledger_get_transaction = '{}ledger/get/transaction?hash={}&verbose={}{}'
ledger_get_mininginfo = '{}ledger/get/mininginfo{}'
ledger_submit_transaction = '{}ledger/submit/transaction?data={}{}'
ledger_list_blocks_height = \
'{}ledger/list/blocks?height={}&limit={}&verbose={}{}'
ledger_list_blocks_hash = '{}ledger/list/blocks?hash={}&limit={}&verbose={}{}'
def build_ledger_html(sid, genid, o):
f = form_footer
o += "<br><b>Ledger API</b><br><br><table>"
o += "<tr><td>"
h = "ledger-get-transaction"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
hsh = form_parm.format("hash", "")
v = form_parm.format("verbose", "1")
o += hl(ledger_get_transaction).format(h, hsh, v, f)
o += "</td></tr>"
o += "<tr><td>"
h = "ledger-get-block-height"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
height = form_parm.format("height", "")
v = form_parm.format("verbose", "1")
o += hl(ledger_get_block_height).format(h, height, v, f)
o += "</td></tr>"
o += "<tr><td>"
h = "ledger-get-block-hash"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
hsh = form_parm.format("hash", "")
v = form_parm.format("verbose", "1")
o += hl(ledger_get_block_hash).format(h, hsh, v, f)
o += "</td></tr>"
o += "<tr><td>"
h = "ledger-get-blockhash"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
height = form_parm.format("height", "")
o += hl(ledger_get_blockhash).format(h, height, f)
o += "</td></tr>"
o += "<tr><td>"
h = "ledger-submit-transaction"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
d = form_parm.format("data", "")
o += hl(ledger_submit_transaction).format(h, d, f)
o += "</td></tr>"
o += "<tr><td>"
h = "ledger-list-blocks-height"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
height = form_parm.format("height", "")
l = form_parm.format("limit", "100")
v = form_parm.format("verbose", "1")
o += hl(ledger_list_blocks_height).format(h, height, l, v, f)
o += "</td></tr>"
o += "<tr><td>"
h = "ledger-list-blocks-hash"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
hsh = form_parm.format("hash", "")
l = form_parm.format("limit", "100")
v = form_parm.format("verbose", "1")
o += hl(ledger_list_blocks_hash).format(h, hsh, l, v, f)
o += "</td></tr>"
o += '</table><br><hr size="5">'
return(o)
#enddef
@bottle.route('/ledger-get-blockhash', method="post")
@bottle.route('/ledger-get-blockhash/<sid>', method="post")
def do_ledger_get_blockhash(sid=""):
height = bottle.request.forms.get("height")
if (no_parms(height)):
m = red("ledger/get/blockhash needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_ledger_get_blockhash(height)
genid = sdk.genesis_id
else:
output = curl(ledger_get_blockhash.format("", height, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, sid, genid))
#enddef
@bottle.route('/ledger-get-block-height', method="post")
@bottle.route('/ledger-get-block-height/<sid>', method="post")
def do_ledger_get_block_height(sid=""):
height = bottle.request.forms.get("height")
verbose = bottle.request.forms.get("verbose")
if (no_parms(height, verbose)):
m = red("ledger/get/block needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_ledger_get_block_by_height(height, verbose)
genid = sdk.genesis_id
else:
output = curl(ledger_get_block_height.format("", height, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, sid, genid))
#enddef
@bottle.route('/ledger-get-block-hash', method="post")
@bottle.route('/ledger-get-block-hash/<sid>', method="post")
def do_ledger_get_block_hash(sid=""):
hsh = bottle.request.forms.get("hash")
verbose = bottle.request.forms.get("verbose")
if (no_parms(hsh, verbose)):
m = red("ledger/get/block needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_ledger_get_block_by_hash(hsh, verbose)
genid = sdk.genesis_id
else:
output = curl(ledger_get_block_hash.format("", hsh, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, sid, genid))
#enddef
@bottle.route('/ledger-get-transaction', method="post")
@bottle.route('/ledger-get-transaction/<sid>', method="post")
def do_ledger_get_transaction(sid=""):
hsh = bottle.request.forms.get("hash")
verbose = bottle.request.forms.get("verbose")
if (no_parms(hsh, verbose)):
m = red("ledger/get/transaction needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_ledger_get_transaction(hsh, verbose)
genid = sdk.genesis_id
else:
output = curl(ledger_get_transaction.format("", hsh, verbose, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, sid, genid))
#enddef
@bottle.route('/ledger-submit-transaction', method="post")
@bottle.route('/ledger-submit-transaction/<sid>', method="post")
def do_ledger_submit_transaction(sid=""):
data = bottle.request.forms.get("data")
if (no_parms(data)):
m = red("ledger/submit/transaction needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_ledger_submit_transaction(data)
genid = sdk.genesis_id
else:
output = curl(ledger_submit_transaction.format("", data, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, sid, genid))
#enddef
@bottle.route('/ledger-list-blocks-height', method="post")
@bottle.route('/ledger-list-blocks-height/<sid>', method="post")
def do_ledger_list_blocks_height(sid=""):
height = bottle.request.forms.get("height")
l = bottle.request.forms.get("limit")
verbose = bottle.request.forms.get("limit")
if (no_parms(height, l, verbose)):
m = red("ledger/list/blocks needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_ledger_list_blocks_by_height(height, l, verbose)
genid = sdk.genesis_id
else:
output = curl(ledger_list_blocks_height.format("", height, l, verbose,
""))
genid = ""
#endif
output = format_transactions(output)
return(show(output, sid, genid))
#enddef
@bottle.route('/ledger-list-blocks-hash', method="post")
@bottle.route('/ledger-list-blocks-hash/<sid>', method="post")
def do_ledger_list_blocks_hash(sid=""):
hsh = bottle.request.forms.get("hash")
l = bottle.request.forms.get("limit")
verbose = bottle.request.forms.get("limit")
if (no_parms(hsh, l, verbose)):
m = red("ledger/list/blocks needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_ledger_list_blocks_by_hash(hsh, l, verbose)
genid = sdk.genesis_id
else:
output = curl(ledger_list_blocks_hash.format("", hsh, l, verbose, ""))
genid = ""
#endif
output = format_transactions(output)
return(show(output, sid, genid))
#enddef
#------------------------------------------------------------------------------
#
# build_objects_html
#
objects_create_schema = ('{}objects/create/schema?pin={}&session={}' +\
'&name={}&format=json&json={}{}')
objects_get_schema_name = '{}objects/get/schema?name={}&format=json{}'
objects_get_schema_address = '{}objects/get/schema?address={}&format=json{}'
def build_objects_html(sid, genid, o):
f = form_footer
o += "<br><b>Objects API</b><br><br><table>"
o += "<tr><td>"
h = "objects-get-schema-name"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
name = form_parm.format("name", "")
o += hl(objects_get_schema_name).format(h, name, f)
o += "</td></tr>"
o += "<tr><td>"
h = "objects-get-schema-address"
if (sid != ""): h += "/{}".format(sid)
h = form_header.format(h)
address = form_parm.format("address", "")
o += hl(objects_get_schema_address).format(h, address, f)
o += "</td></tr>"
o += "<tr><td>"
h = "objects-create-schema"
h = form_header.format(h)
pin = form_parm.format("pin", "")
session = form_parm.format("session", sid)
name = form_parm.format("name", "")
j = form_parm.format("json", "")
o += hl(objects_create_schema).format(h, pin, session, name, j, f)
o += "</td></tr>"
o += '</table><br><hr size="5">'
return(o)
#enddef
@bottle.route('/objects-create-schema', method="post")
def do_objects_create_schema():
pin = bottle.request.forms.get("pin")
session = bottle.request.forms.get("session")
name = bottle.request.forms.get("name")
j = bottle.request.forms.get("json")
if (no_parms(pin, session, name, j)):
m = red("objects/create/schema needs more input parameters")
return(show(m, session))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(session)
if (sdk == None): return(output)
output = sdk.nexus_objects_create_schema(name, j)
genid = sdk.genesis_id
else:
output = curl(objects_create_schema.format("", pin, session, name, j,
""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, session, genid))
#enddef
@bottle.route('/objects-get-schema-name', method="post")
@bottle.route('/objects-get-schema-name/<sid>', method="post")
def do_objects_get_schema_name(sid=""):
name = bottle.request.forms.get("name")
if (no_parms(name)):
m = red("objects/get/schema needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_objects_get_schema_by_name(name)
genid = sdk.genesis_id
else:
output = curl(objects_get_schema_name.format("", name, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, sid, genid))
#enddef
@bottle.route('/objects-get-schema-address', method="post")
@bottle.route('/objects-get-schema-address/<sid>', method="post")
def do_objects_get_schema_address(sid=""):
address = bottle.request.forms.get("address")
if (no_parms(address)):
m = red("objects/get/schema needs more input parameters")
return(show(m, sid))
#endif
action = bottle.request.forms.get("action")
sdk_or_api = (action.find("SDK") != -1)
if (sdk_or_api):
sdk, output = sid_to_sdk(sid)
if (sdk == None): return(output)
output = sdk.nexus_objects_get_schema_by_address(address)
genid = sdk.genesis_id
else:
output = curl(objects_get_schema_address.format("", address, ""))
genid = ""
#endif
output = json.dumps(output)
return(show(output, sid, genid))
#enddef
#------------------------------------------------------------------------------
#
# build_body_page
#
# Fill in all API calls into body page.
#
def build_body_page(sid="", genid=""):
output = ""
output = build_url_html(output)
output = build_system_html(sid, genid, output)
output = build_users_html(sid, genid, output)
output = build_ledger_html(sid, genid, output)
output = build_tokens_html(sid, genid, output)
output = build_assets_html(sid, genid, output)
output = build_supply_html(sid, genid, output)
output = build_finance_html(sid, genid, output)
#
# Back end for objects API is not done yet. Don't show user.
#
# output = build_objects_html(sid, genid, output)
return(output)
#enddef
@bottle.route('/')
def do_landing():
output = build_body_page()
hostname = blue(socket.gethostname())
sdk = blue(nexus_sdk_last_username)
api = blue(nexus_api_last_username)
return(landing_page.format(hostname, sdk, api, output))
#enddef
@bottle.route('/url/<api_or_sdk>', method="post")
def do_url(api_or_sdk):
global nexus_api_node, nexus_sdk_node
url = bottle.request.forms.get("url")
if (api_or_sdk == "api"):
nexus_api_node = url
#endif
if (api_or_sdk == "sdk"):
nexus.sdk_change_url(url)
nexus_sdk_node = url
#endif
output = build_body_page()
hostname = blue(socket.gethostname())
sdk = blue(nexus_sdk_last_username)
api = blue(nexus_api_last_username)
return(landing_page.format(hostname, sdk, api, output))
#enddef
#------------------------------------------------------------------------------
#
# ---------- Main program entry point. ----------
#
date = commands.getoutput("date")
print "cookbook starting up at {}".format(date)
#
# Run web server.
#
bottle.run(host="0.0.0.0", port=cookbook_port, debug=True)
exit(0)
#------------------------------------------------------------------------------
| 32.942912
| 79
| 0.608204
| 11,195
| 85,981
| 4.506833
| 0.033497
| 0.056685
| 0.078487
| 0.091569
| 0.823879
| 0.780989
| 0.741705
| 0.706604
| 0.684168
| 0.658659
| 0
| 0.002327
| 0.210326
| 85,981
| 2,609
| 80
| 32.955539
| 0.740769
| 0.056675
| 0
| 0.645279
| 0
| 0.001043
| 0.187398
| 0.076987
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0.007303
| 0.003652
| null | null | 0.001043
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 0
| 1
| 0
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| 0
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| 0
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| 0
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| 0
| 0
| 0
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| null | 0
| 0
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| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
25ad660c2b19cabb23bb404bf035f8e5eb6b271c
| 48
|
py
|
Python
|
GUI/__init__.py
|
LANCEREN/Graduation-Design_Py
|
7c636867efba91cb6a828fb9fd96046d5f844bce
|
[
"MIT"
] | null | null | null |
GUI/__init__.py
|
LANCEREN/Graduation-Design_Py
|
7c636867efba91cb6a828fb9fd96046d5f844bce
|
[
"MIT"
] | 4
|
2021-09-08T01:48:52.000Z
|
2022-03-12T00:21:26.000Z
|
GUI/__init__.py
|
LANCEREN/Graduation-Design_Py
|
7c636867efba91cb6a828fb9fd96046d5f844bce
|
[
"MIT"
] | null | null | null |
# GUi设计
print("Loading GUI design Module ...")
| 12
| 38
| 0.666667
| 6
| 48
| 5.333333
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 48
| 4
| 38
| 12
| 0.8
| 0.104167
| 0
| 0
| 0
| 0
| 0.707317
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
d32d495d9fe838f99ae4048f433eb0c411043f83
| 103
|
py
|
Python
|
DockerIntro/src/DjangoApp/views.py
|
Py-Himanshu-Patel/Learn-Docker
|
c8505a9b36c42269e8566c9368657463024a6fa6
|
[
"MIT"
] | null | null | null |
DockerIntro/src/DjangoApp/views.py
|
Py-Himanshu-Patel/Learn-Docker
|
c8505a9b36c42269e8566c9368657463024a6fa6
|
[
"MIT"
] | null | null | null |
DockerIntro/src/DjangoApp/views.py
|
Py-Himanshu-Patel/Learn-Docker
|
c8505a9b36c42269e8566c9368657463024a6fa6
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render
def home(request):
return render(request, 'DjangoApp/home.html')
| 20.6
| 46
| 0.786408
| 14
| 103
| 5.785714
| 0.785714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106796
| 103
| 4
| 47
| 25.75
| 0.880435
| 0
| 0
| 0
| 0
| 0
| 0.184466
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
d3827ffa6a2c67ee2f13bb5c08aefe57a24118d4
| 54
|
py
|
Python
|
tests/core/test_import.py
|
vaporyproject/eth-rlp
|
a7f785aaf866ab6a40960034d05cb6439e8a9d74
|
[
"MIT"
] | 13
|
2018-02-25T06:38:38.000Z
|
2021-11-04T14:09:39.000Z
|
tests/core/test_import.py
|
vaporyproject/eth-rlp
|
a7f785aaf866ab6a40960034d05cb6439e8a9d74
|
[
"MIT"
] | 5
|
2018-04-25T23:02:28.000Z
|
2022-01-23T19:50:37.000Z
|
tests/core/test_import.py
|
vaporyproject/eth-rlp
|
a7f785aaf866ab6a40960034d05cb6439e8a9d74
|
[
"MIT"
] | 13
|
2018-03-01T21:42:05.000Z
|
2022-03-28T18:34:20.000Z
|
def test_import():
import eth_rlp # noqa: F401
| 10.8
| 32
| 0.648148
| 8
| 54
| 4.125
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075
| 0.259259
| 54
| 4
| 33
| 13.5
| 0.75
| 0.185185
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0
| 1
| 0
| 1.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
d390482b69ab7b0bac12fe13826f4074792a79e4
| 158
|
py
|
Python
|
gpn/experiments/__init__.py
|
WodkaRHR/Graph-Posterior-Network
|
139e7c45c37324c9286e0cca60360a4978b3f411
|
[
"MIT"
] | 23
|
2021-11-16T01:31:55.000Z
|
2022-03-04T05:49:03.000Z
|
gpn/experiments/__init__.py
|
WodkaRHR/Graph-Posterior-Network
|
139e7c45c37324c9286e0cca60360a4978b3f411
|
[
"MIT"
] | 1
|
2021-12-17T01:25:16.000Z
|
2021-12-20T10:38:30.000Z
|
gpn/experiments/__init__.py
|
WodkaRHR/Graph-Posterior-Network
|
139e7c45c37324c9286e0cca60360a4978b3f411
|
[
"MIT"
] | 7
|
2021-12-03T11:13:44.000Z
|
2022-02-06T03:12:10.000Z
|
from .transductive_experiment import TransductiveExperiment
from .multiple_run_experiment import MultipleRunExperiment
from .dataset import ExperimentDataset
| 39.5
| 59
| 0.905063
| 15
| 158
| 9.333333
| 0.666667
| 0.228571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075949
| 158
| 3
| 60
| 52.666667
| 0.958904
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
6cf082254965c857b7ee0ffc75acc66c811d99bd
| 186
|
py
|
Python
|
src/babylon/schemas/__init__.py
|
Bl4ck4/babylon
|
4c3f98be799d232b78d0bd4b4aa831f19338da37
|
[
"MIT"
] | null | null | null |
src/babylon/schemas/__init__.py
|
Bl4ck4/babylon
|
4c3f98be799d232b78d0bd4b4aa831f19338da37
|
[
"MIT"
] | null | null | null |
src/babylon/schemas/__init__.py
|
Bl4ck4/babylon
|
4c3f98be799d232b78d0bd4b4aa831f19338da37
|
[
"MIT"
] | 1
|
2021-10-02T10:28:24.000Z
|
2021-10-02T10:28:24.000Z
|
try:
from .recipe import Recipe
except AssertionError:
pass
from .measured_in import MeasuredIn
from .ingredient import Ingredient
from .tag import Tag
from .fridge import Fridge
| 23.25
| 35
| 0.795699
| 25
| 186
| 5.88
| 0.52
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 186
| 8
| 36
| 23.25
| 0.948387
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 1
| 0
| true
| 0.125
| 0.625
| 0
| 0.625
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
9fa2171b79ac2271ddd15536e9951063c8378512
| 39
|
py
|
Python
|
machine_learning_course/common/__init__.py
|
arekmula/MachineLearningCourse
|
5966dd2ad0ee23ef8f84d218a9f64e345900402e
|
[
"MIT"
] | null | null | null |
machine_learning_course/common/__init__.py
|
arekmula/MachineLearningCourse
|
5966dd2ad0ee23ef8f84d218a9f64e345900402e
|
[
"MIT"
] | null | null | null |
machine_learning_course/common/__init__.py
|
arekmula/MachineLearningCourse
|
5966dd2ad0ee23ef8f84d218a9f64e345900402e
|
[
"MIT"
] | null | null | null |
from common.utils import read_csv_file
| 19.5
| 38
| 0.871795
| 7
| 39
| 4.571429
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102564
| 39
| 1
| 39
| 39
| 0.914286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
9fbcef75adcbf8eb68953245cbe70f0ee359685e
| 20
|
py
|
Python
|
EJ.py
|
kimty103/dataPreprocessing
|
1aa4078d70076c4dc46fd389aa4b6b98a1637718
|
[
"MIT"
] | null | null | null |
EJ.py
|
kimty103/dataPreprocessing
|
1aa4078d70076c4dc46fd389aa4b6b98a1637718
|
[
"MIT"
] | null | null | null |
EJ.py
|
kimty103/dataPreprocessing
|
1aa4078d70076c4dc46fd389aa4b6b98a1637718
|
[
"MIT"
] | null | null | null |
import sys
print(1)
| 6.666667
| 10
| 0.75
| 4
| 20
| 3.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0.15
| 20
| 3
| 11
| 6.666667
| 0.823529
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 1
|
0
| 6
|
9fcdb9e3f40d27ed8ffb94172501cf3d58a48754
| 43
|
py
|
Python
|
skrl/agents/torch/trpo/__init__.py
|
Toni-SM/skrl
|
15b429d89e3b8a1828b207d88463bf7090288d18
|
[
"MIT"
] | 43
|
2021-12-19T07:47:43.000Z
|
2022-03-31T05:24:42.000Z
|
skrl/agents/torch/trpo/__init__.py
|
Toni-SM/skrl
|
15b429d89e3b8a1828b207d88463bf7090288d18
|
[
"MIT"
] | 5
|
2022-01-05T07:54:13.000Z
|
2022-03-08T21:00:39.000Z
|
skrl/agents/torch/trpo/__init__.py
|
Toni-SM/skrl
|
15b429d89e3b8a1828b207d88463bf7090288d18
|
[
"MIT"
] | 1
|
2022-01-31T17:53:52.000Z
|
2022-01-31T17:53:52.000Z
|
from .trpo import TRPO, TRPO_DEFAULT_CONFIG
| 43
| 43
| 0.860465
| 7
| 43
| 5
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.093023
| 43
| 1
| 43
| 43
| 0.897436
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
4c89754bb0149c421f20ef67695096e6ae91114c
| 42
|
py
|
Python
|
functions/__init__.py
|
vlee489/AC31009-Client
|
71252f38c7bf4426ff84676cad517f66c3e6cb65
|
[
"CC-BY-4.0"
] | null | null | null |
functions/__init__.py
|
vlee489/AC31009-Client
|
71252f38c7bf4426ff84676cad517f66c3e6cb65
|
[
"CC-BY-4.0"
] | null | null | null |
functions/__init__.py
|
vlee489/AC31009-Client
|
71252f38c7bf4426ff84676cad517f66c3e6cb65
|
[
"CC-BY-4.0"
] | null | null | null |
from .REST import *
from .windows import *
| 21
| 22
| 0.738095
| 6
| 42
| 5.166667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 42
| 2
| 22
| 21
| 0.885714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
981cee6f97ee483a4c2fa12d53754803c07eb730
| 6,163
|
py
|
Python
|
prediction_flow/pytorch/tests/test_dien.py
|
dydcfg/prediction-flow
|
332068f521bba51acc8600fe72e36e92c331bef1
|
[
"MIT"
] | 211
|
2019-08-02T23:04:40.000Z
|
2022-03-18T06:36:25.000Z
|
prediction_flow/pytorch/tests/test_dien.py
|
dydcfg/prediction-flow
|
332068f521bba51acc8600fe72e36e92c331bef1
|
[
"MIT"
] | 18
|
2019-08-10T07:13:05.000Z
|
2022-03-17T10:45:30.000Z
|
prediction_flow/pytorch/tests/test_dien.py
|
dydcfg/prediction-flow
|
332068f521bba51acc8600fe72e36e92c331bef1
|
[
"MIT"
] | 51
|
2019-08-02T23:04:41.000Z
|
2021-12-24T02:48:58.000Z
|
from prediction_flow.features import Number, Category, Sequence, Features
from prediction_flow.transformers.column import (
StandardScaler, CategoryEncoder, SequenceEncoder)
from prediction_flow.pytorch import AttentionGroup, DIEN
from .utils import prepare_dataloader
def create_test_data():
number_features = [
Number('userAge', StandardScaler()),
Number('rating', StandardScaler())]
category_features = [
Category('userId', CategoryEncoder(min_cnt=1)),
Category('movieId', CategoryEncoder(min_cnt=1)),
Category('topGenre', CategoryEncoder(min_cnt=1))]
sequence_features = [
Sequence('title', SequenceEncoder(sep='|', min_cnt=1)),
Sequence('genres', SequenceEncoder(sep='|', min_cnt=1)),
Sequence('clickedMovieIds',
SequenceEncoder(sep='|', min_cnt=1, max_len=5)),
Sequence('clickedMovieTopGenres',
SequenceEncoder(sep='|', min_cnt=1, max_len=5)),
Sequence('noClickedMovieIds',
SequenceEncoder(sep='|', min_cnt=1, max_len=5)),
Sequence('noClickedMovieTopGenres',
SequenceEncoder(sep='|', min_cnt=1, max_len=5))]
attention_groups = [
AttentionGroup(
name='group1',
pairs=[{'ad': 'movieId',
'pos_hist': 'clickedMovieIds',
'neg_hist': 'noClickedMovieIds'},
{'ad': 'topGenre',
'pos_hist': 'clickedMovieTopGenres',
'neg_hist': 'noClickedMovieTopGenres'}],
hidden_layers=[8, 4])]
features = Features(
number_features=number_features,
category_features=category_features,
sequence_features=sequence_features)
dataloader, _ = prepare_dataloader(features)
return dataloader, features, attention_groups
def test_gru_gru_att():
dataloader, features, attention_groups = create_test_data()
attention_groups[0].gru_type = 'GRU'
model = DIEN(
features, attention_groups=attention_groups,
num_classes=2, embedding_size=4, hidden_layers=(16, 8),
final_activation='sigmoid', dropout=0.3)
model(next(iter(dataloader)))
def test_gru_att_gru():
dataloader, features, attention_groups = create_test_data()
attention_groups[0].gru_type = 'AIGRU'
model = DIEN(
features, attention_groups=attention_groups,
num_classes=2, embedding_size=4, hidden_layers=(16, 8),
final_activation='sigmoid', dropout=0.3)
model(next(iter(dataloader)))
def test_gru_agru():
dataloader, features, attention_groups = create_test_data()
attention_groups[0].gru_type = 'AGRU'
model = DIEN(
features, attention_groups=attention_groups,
num_classes=2, embedding_size=4, hidden_layers=(16, 8),
final_activation='sigmoid', dropout=0.3)
model(next(iter(dataloader)))
def test_gru_augru():
dataloader, features, attention_groups = create_test_data()
attention_groups[0].gru_type = 'AUGRU'
model = DIEN(
features, attention_groups=attention_groups,
num_classes=2, embedding_size=4, hidden_layers=(16, 8),
final_activation='sigmoid', dropout=0.3)
model(next(iter(dataloader)))
def test_gru_augru_neg():
dataloader, features, attention_groups = create_test_data()
attention_groups[0].gru_type = 'AUGRU'
model = DIEN(
features, attention_groups=attention_groups,
use_negsampling=True,
num_classes=2, embedding_size=4, hidden_layers=(16, 8),
final_activation='sigmoid', dropout=0.3)
model(next(iter(dataloader)))
def create_test_data_with_sharing_emb():
number_features = [
Number('userAge', StandardScaler()),
Number('rating', StandardScaler())]
# provide word to index mapping
movie_word2idx = {
'__PAD__': 0,
'4226': 1,
'5971': 2,
'6291': 3,
'7153': 4,
'30707': 5,
'3242': 6,
'42': 7,
'32': 8,
'34': 9,
'233': 10,
'291': 11,
'324': 12,
'325': 13,
'3542': 14,
'322': 15,
'33': 16,
'45': 17,
'__UNKNOWN__': 18}
movie_idx2word = {
index: word for word, index in movie_word2idx.items()}
category_features = [
Category('movieId',
CategoryEncoder(
word2idx=movie_word2idx,
idx2word=movie_idx2word),
embedding_name='movieId'),
Category('topGenre', CategoryEncoder(min_cnt=1))]
sequence_features = [
Sequence('title', SequenceEncoder(sep='|', min_cnt=1)),
Sequence('genres', SequenceEncoder(sep='|', min_cnt=1)),
Sequence('clickedMovieIds',
SequenceEncoder(
sep='|', max_len=5,
word2idx=movie_word2idx, idx2word=movie_idx2word),
embedding_name='movieId'),
Sequence('noClickedMovieIds',
SequenceEncoder(
sep='|', max_len=5,
word2idx=movie_word2idx, idx2word=movie_idx2word),
embedding_name='movieId')]
attention_groups = [
AttentionGroup(
name='group1',
pairs=[{'ad': 'movieId',
'pos_hist': 'clickedMovieIds',
'neg_hist': 'noClickedMovieIds'}],
hidden_layers=[8, 4])]
features = Features(
number_features=number_features,
category_features=category_features,
sequence_features=sequence_features)
dataloader, _ = prepare_dataloader(features)
return dataloader, features, attention_groups
def test_gru_augru_neg_with_sharing_emb():
dataloader, features, attention_groups = (
create_test_data_with_sharing_emb())
attention_groups[0].gru_type = 'AUGRU'
model = DIEN(
features, attention_groups=attention_groups,
use_negsampling=True,
num_classes=2, embedding_size=4, hidden_layers=(16, 8),
final_activation='sigmoid', dropout=0.3)
model(next(iter(dataloader)))
| 30.509901
| 73
| 0.616096
| 627
| 6,163
| 5.779904
| 0.196172
| 0.115894
| 0.088852
| 0.05298
| 0.81181
| 0.786976
| 0.775386
| 0.762417
| 0.716611
| 0.671358
| 0
| 0.037274
| 0.264319
| 6,163
| 201
| 74
| 30.661692
| 0.76202
| 0.004706
| 0
| 0.633333
| 0
| 0
| 0.091324
| 0.014351
| 0
| 0
| 0
| 0
| 0
| 1
| 0.053333
| false
| 0
| 0.026667
| 0
| 0.093333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
e218563c19d985ad4ad32ed850a098be4c71ce93
| 123
|
py
|
Python
|
interface/models/errors.py
|
Flatlooker/simple_ml
|
468e86792a14bc8b7d432f36bfda11e581d5c40d
|
[
"Unlicense"
] | null | null | null |
interface/models/errors.py
|
Flatlooker/simple_ml
|
468e86792a14bc8b7d432f36bfda11e581d5c40d
|
[
"Unlicense"
] | null | null | null |
interface/models/errors.py
|
Flatlooker/simple_ml
|
468e86792a14bc8b7d432f36bfda11e581d5c40d
|
[
"Unlicense"
] | null | null | null |
class ModelUnknown(Exception):
pass
class AsyncMismatch(Exception):
pass
class InvalidInput(Exception):
pass
| 13.666667
| 31
| 0.739837
| 12
| 123
| 7.583333
| 0.5
| 0.428571
| 0.395604
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.186992
| 123
| 8
| 32
| 15.375
| 0.91
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
e21c7642d4d9e3a1483af7b1371441ad4590cae6
| 146
|
py
|
Python
|
tdd_python_code_samples/BestPractices_Example/DependencyTest.py
|
masayas/-Hands-on-Test-Driven-Development-with-Python
|
4879e2a26327ee766da1ae3245685e5f47bdc821
|
[
"MIT"
] | 23
|
2018-05-30T05:11:17.000Z
|
2022-02-12T20:23:25.000Z
|
tdd_python_code_samples/BestPractices_Example/DependencyTest.py
|
masayas/-Hands-on-Test-Driven-Development-with-Python
|
4879e2a26327ee766da1ae3245685e5f47bdc821
|
[
"MIT"
] | null | null | null |
tdd_python_code_samples/BestPractices_Example/DependencyTest.py
|
masayas/-Hands-on-Test-Driven-Development-with-Python
|
4879e2a26327ee766da1ae3245685e5f47bdc821
|
[
"MIT"
] | 12
|
2018-06-24T04:12:04.000Z
|
2021-11-18T09:42:00.000Z
|
import TestVariables
def test_one():
TestVariables.test_value = 1
assert True
def test_two():
assert TestVariables.test_value == 1
| 14.6
| 40
| 0.719178
| 19
| 146
| 5.315789
| 0.526316
| 0.138614
| 0.435644
| 0.455446
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.017241
| 0.205479
| 146
| 9
| 41
| 16.222222
| 0.853448
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| true
| 0
| 0.166667
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
2c3bc7bb5e241bc7902972b07f52fde7dfb822a8
| 2,106
|
py
|
Python
|
Joy_QA_Platform/frame/utils/forms.py
|
bzc128/Joy_QA_Platform
|
d3325331cd832a22e91ad895ab793577609aabc4
|
[
"Apache-2.0"
] | 123
|
2019-03-01T06:07:43.000Z
|
2021-12-11T07:59:20.000Z
|
Joy_QA_Platform/frame/utils/forms.py
|
bzc128/Joy_QA_Platform
|
d3325331cd832a22e91ad895ab793577609aabc4
|
[
"Apache-2.0"
] | 8
|
2019-03-06T06:33:34.000Z
|
2021-06-10T21:13:55.000Z
|
Joy_QA_Platform/frame/utils/forms.py
|
bzc128/Joy_QA_Platform
|
d3325331cd832a22e91ad895ab793577609aabc4
|
[
"Apache-2.0"
] | 54
|
2019-03-01T02:25:13.000Z
|
2021-12-23T16:55:17.000Z
|
from django import forms
# 验证登录表单
class LoginForm(forms.Form):
account = forms.CharField(required=True, error_messages={'required': "账号不能为空"})
password = forms.CharField(required=True, error_messages={'required': "密码不能为空"})
# 验证注册表单
class RegisterForm(forms.Form):
email = forms.EmailField(required=True,
error_messages={'required': "邮箱不能为空",
'invalid': "邮箱格式错误"})
password = forms.CharField(required=True,
min_length=6,
error_messages={'required': "密码不能为空",
'min_length': "密码至少6位"})
repassword = forms.CharField(required=True,
min_length=6,
error_messages={'required': "密码不能为空",
'min_length': "密码至少6位"})
username = forms.CharField(required=True,
max_length=20,
error_messages={'required': "用户名不能为空",
'max_length': "用户名最多为20位"})
emailcapture = forms.CharField(required=True,
error_messages={'required': "验证码不能为空"})
# 验证重置密码表单
class ResetForm(forms.Form):
email = forms.EmailField(required=True,
error_messages={'required': "邮箱不能为空",
'invalid': "邮箱格式错误"})
password = forms.CharField(required=True,
min_length=6,
error_messages={'required': "密码不能为空",
'min_length': "密码至少6位"})
repassword = forms.CharField(required=True,
min_length=6,
error_messages={'required': "密码不能为空",
'min_length': "密码至少6位"})
emailcapture = forms.CharField(required=True,
error_messages={'required': "验证码不能为空"})
| 45.782609
| 84
| 0.460589
| 152
| 2,106
| 6.243421
| 0.25
| 0.139094
| 0.243414
| 0.246575
| 0.783983
| 0.775553
| 0.775553
| 0.676502
| 0.676502
| 0.537408
| 0
| 0.010076
| 0.434473
| 2,106
| 45
| 85
| 46.8
| 0.786734
| 0.010446
| 0
| 0.722222
| 0
| 0
| 0.127885
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.138889
| 0.027778
| 0
| 0.416667
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
2c59ee6579970269fc8253537adaf274e897f948
| 58
|
py
|
Python
|
src/tests/testModules/partialModuleVariables/TrueNegative/customTypes.py
|
Trimatix/carica
|
074be16bdf50541eb3ba92ca42d0ad901cc51bd0
|
[
"Apache-2.0"
] | 5
|
2021-09-08T07:29:23.000Z
|
2021-11-24T00:18:22.000Z
|
src/tests/testModules/partialModuleVariables/TrueNegative/customTypes.py
|
Trimatix/Carica
|
074be16bdf50541eb3ba92ca42d0ad901cc51bd0
|
[
"Apache-2.0"
] | 42
|
2021-09-08T07:31:25.000Z
|
2022-01-16T17:39:34.000Z
|
src/tests/testModules/partialModuleVariables/TrueNegative/customTypes.py
|
Trimatix/carica
|
074be16bdf50541eb3ba92ca42d0ad901cc51bd0
|
[
"Apache-2.0"
] | null | null | null |
class MyType:
pass
MyType
MyType()
MyType == MyType()
| 9.666667
| 18
| 0.672414
| 7
| 58
| 5.571429
| 0.428571
| 0.923077
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206897
| 58
| 6
| 18
| 9.666667
| 0.847826
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.2
| 0
| 0
| 0.2
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
2c80979a9e74cc0360696b441cc420756888a3db
| 31
|
py
|
Python
|
fhlb/__init__.py
|
Solaxun/FHLB
|
3a54902c3f7ca12d734f8bf455fdac419f345739
|
[
"MIT"
] | null | null | null |
fhlb/__init__.py
|
Solaxun/FHLB
|
3a54902c3f7ca12d734f8bf455fdac419f345739
|
[
"MIT"
] | null | null | null |
fhlb/__init__.py
|
Solaxun/FHLB
|
3a54902c3f7ca12d734f8bf455fdac419f345739
|
[
"MIT"
] | null | null | null |
from fhlb.client import Client
| 15.5
| 30
| 0.83871
| 5
| 31
| 5.2
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.129032
| 31
| 2
| 30
| 15.5
| 0.962963
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
2cbc11fb4ac78e7ac2c3838cf8f1fcd552325091
| 84
|
py
|
Python
|
db/injection.py
|
Mhs-220/NetworkSecurityProject
|
20dc7fcafc4647a15670a813cbdfefa66b7cda56
|
[
"MIT"
] | null | null | null |
db/injection.py
|
Mhs-220/NetworkSecurityProject
|
20dc7fcafc4647a15670a813cbdfefa66b7cda56
|
[
"MIT"
] | null | null | null |
db/injection.py
|
Mhs-220/NetworkSecurityProject
|
20dc7fcafc4647a15670a813cbdfefa66b7cda56
|
[
"MIT"
] | null | null | null |
import re
def escape_sql_injection(text):
return re.sub(r"(\\*)'", r"''", text)
| 21
| 41
| 0.619048
| 13
| 84
| 3.846154
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 84
| 4
| 41
| 21
| 0.694444
| 0
| 0
| 0
| 0
| 0
| 0.094118
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 6
|
2cbfe488434ade7751bef8b11777d84701d15cc4
| 2,207
|
py
|
Python
|
test_case01.py
|
mliezun/sudoku-solver
|
18b638b200be360ee6e8af0c7e612eb086924b98
|
[
"MIT"
] | null | null | null |
test_case01.py
|
mliezun/sudoku-solver
|
18b638b200be360ee6e8af0c7e612eb086924b98
|
[
"MIT"
] | null | null | null |
test_case01.py
|
mliezun/sudoku-solver
|
18b638b200be360ee6e8af0c7e612eb086924b98
|
[
"MIT"
] | null | null | null |
import pytest
from solver import Board, SudokuSolver
def test_case01_easy():
b = Board([
[1, 0, 6, 0, 0, 2, 3, 0, 0],
[0, 5, 0, 0, 0, 6, 0, 9, 1],
[0, 0, 9, 5, 0, 1, 4, 6, 2],
[0, 3, 7, 9, 0, 5, 0, 0, 0],
[5, 8, 1, 0, 2, 7, 9, 0, 0],
[0, 0, 0, 4, 0, 8, 1, 5, 7],
[0, 0, 0, 2, 6, 0, 5, 4, 0],
[0, 0, 4, 1, 5, 0, 6, 0, 9],
[9, 0, 0, 8, 7, 4, 2, 1, 0],
])
assert repr(SudokuSolver.solve(b)) == repr([[1, 4, 6, 7, 9, 2, 3, 8, 5], [2, 5, 8, 3, 4, 6, 7, 9, 1], [3, 7, 9, 5, 8, 1, 4, 6, 2], [4, 3, 7, 9, 1, 5, 8, 2, 6], [
5, 8, 1, 6, 2, 7, 9, 3, 4], [6, 9, 2, 4, 3, 8, 1, 5, 7], [7, 1, 3, 2, 6, 9, 5, 4, 8], [8, 2, 4, 1, 5, 3, 6, 7, 9], [9, 6, 5, 8, 7, 4, 2, 1, 3]]), "Wrong answer"
def test_case01_hard():
b = Board([
[4, 0, 9, 3, 7, 0, 0, 0, 0],
[1, 0, 0, 4, 2, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 9, 0, 1, 0],
[5, 0, 0, 0, 0, 6, 0, 7, 0],
[0, 6, 2, 0, 0, 0, 5, 8, 0],
[0, 1, 0, 2, 0, 0, 0, 0, 3],
[0, 2, 0, 8, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 5, 2, 0, 0, 8],
[0, 0, 0, 0, 9, 7, 6, 0, 5],
])
assert repr(SudokuSolver.solve(b)) == repr([[4, 8, 9, 3, 7, 1, 2, 5, 6], [1, 5, 6, 4, 2, 8, 9, 3, 7], [2, 7, 3, 5, 6, 9, 8, 1, 4], [5, 4, 8, 9, 3, 6, 1, 7, 2], [
3, 6, 2, 7, 1, 4, 5, 8, 9], [9, 1, 7, 2, 8, 5, 4, 6, 3], [6, 2, 5, 8, 4, 3, 7, 9, 1], [7, 9, 1, 6, 5, 2, 3, 4, 8], [8, 3, 4, 1, 9, 7, 6, 2, 5]]), "Wrong answer"
def test_case01_empty():
b = Board([
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0],
])
assert repr(SudokuSolver.solve(b)) == repr([[1, 2, 3, 4, 5, 8, 9, 6, 7], [4, 5, 8, 6, 7, 9, 1, 2, 3], [9, 6, 7, 1, 2, 3, 8, 4, 5], [2, 1, 9, 8, 3, 4, 5, 7, 6], [
3, 8, 4, 5, 6, 7, 2, 1, 9], [5, 7, 6, 9, 1, 2, 3, 8, 4], [8, 9, 1, 3, 4, 6, 7, 5, 2], [6, 3, 2, 7, 8, 5, 4, 9, 1], [7, 4, 5, 2, 9, 1, 6, 3, 8]]), "Wrong answer"
| 41.641509
| 168
| 0.333484
| 535
| 2,207
| 1.364486
| 0.052336
| 0.358904
| 0.452055
| 0.526027
| 0.443836
| 0.282192
| 0.227397
| 0.227397
| 0.135616
| 0.110959
| 0
| 0.352941
| 0.368373
| 2,207
| 52
| 169
| 42.442308
| 0.170732
| 0
| 0
| 0.340909
| 0
| 0
| 0.016312
| 0
| 0
| 0
| 0
| 0
| 0.068182
| 1
| 0.068182
| false
| 0
| 0.045455
| 0
| 0.113636
| 0
| 0
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
39099f5b26a911c9bd75338a623c20b4123debfd
| 179
|
py
|
Python
|
categorical_encoding/__init__.py
|
isabella232/categorical_encoding
|
090e8d207aa14dd278e03209b4663cf9af0cad45
|
[
"BSD-3-Clause"
] | 36
|
2019-08-14T22:01:24.000Z
|
2021-04-09T00:56:37.000Z
|
categorical_encoding/__init__.py
|
pplonski/categorical_encoding
|
a8ec786863cd69dabd03af440299075192fdc9b9
|
[
"BSD-3-Clause"
] | 19
|
2019-08-22T19:10:10.000Z
|
2021-03-03T23:12:01.000Z
|
categorical_encoding/__init__.py
|
pplonski/categorical_encoding
|
a8ec786863cd69dabd03af440299075192fdc9b9
|
[
"BSD-3-Clause"
] | 10
|
2019-09-23T19:34:42.000Z
|
2021-02-03T11:16:32.000Z
|
# flake8: noqa
from .encoders import Encoder
import categorical_encoding.encoders
import categorical_encoding.primitives
import categorical_encoding.tests
__version__ = '0.4.1'
| 19.888889
| 38
| 0.837989
| 22
| 179
| 6.5
| 0.636364
| 0.356643
| 0.524476
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.024845
| 0.100559
| 179
| 8
| 39
| 22.375
| 0.863354
| 0.067039
| 0
| 0
| 0
| 0
| 0.030303
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.8
| 0
| 0.8
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
1a3778486414af97113c607aae1b449e7bff1602
| 255
|
py
|
Python
|
forks/baselines/baselines/common/__init__.py
|
AndrewPaulChester/sage-code
|
9fe676bfbcbc6f642eca29b30a1027fba2a426a0
|
[
"MIT"
] | null | null | null |
forks/baselines/baselines/common/__init__.py
|
AndrewPaulChester/sage-code
|
9fe676bfbcbc6f642eca29b30a1027fba2a426a0
|
[
"MIT"
] | null | null | null |
forks/baselines/baselines/common/__init__.py
|
AndrewPaulChester/sage-code
|
9fe676bfbcbc6f642eca29b30a1027fba2a426a0
|
[
"MIT"
] | null | null | null |
# flake8: noqa F403
from forks.baselines.baselines.common.console_util import *
from forks.baselines.baselines.common.dataset import Dataset
from forks.baselines.baselines.common.math_util import *
from forks.baselines.baselines.common.misc_util import *
| 42.5
| 60
| 0.839216
| 35
| 255
| 6.028571
| 0.371429
| 0.170616
| 0.341232
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0
| 6
|
1a4914741250fd215a30dadded8acd09c42b5cca
| 12,407
|
py
|
Python
|
ifa_smeargle/testing/test_numerical_filters.py
|
scottwedge/IfA_Smeargle
|
d46a378e534020f8920a801880912aa973daec3b
|
[
"MIT"
] | null | null | null |
ifa_smeargle/testing/test_numerical_filters.py
|
scottwedge/IfA_Smeargle
|
d46a378e534020f8920a801880912aa973daec3b
|
[
"MIT"
] | 5
|
2020-06-08T22:19:37.000Z
|
2020-08-25T09:10:41.000Z
|
ifa_smeargle/testing/test_numerical_filters.py
|
scottwedge/IfA_Smeargle
|
d46a378e534020f8920a801880912aa973daec3b
|
[
"MIT"
] | 1
|
2020-06-25T02:57:42.000Z
|
2020-06-25T02:57:42.000Z
|
"""
This tests the filter functions to ensure that they are
appropriately calculating the filters as expected.
These filter tests operate on the principle that the product of
single power prime integers is always unique, and by extension,
so are their logarithms. Prime number arrays are filtered,
multiplied together, and compared against an expected hard-coded
result.
"""
import numpy as np
import numpy.ma as np_ma
import pytest
import sympy as sy
import math
import ifa_smeargle.core as core
import ifa_smeargle.masking as mask
import ifa_smeargle.testing as test
def test_filter_sigma_value():
""" This tests the filtering of sigma boundaries."""
# Creating the testing array.
test_array = test.base.create_prime_test_array(shape=(10,10), index=50)
# Prescribed filtering parameters
# 1 Sigma
sigma_multiple = 1
sigma_iterations = 2
# Create the filter.
test_filter = mask.filter_sigma_value(data_array=test_array,
sigma_multiple=sigma_multiple,
sigma_iterations=sigma_iterations)
# Create a filtered array for both convince and testing.
test_filtered_array = np_ma.array(test_array, mask=test_filter, dtype=int)
# A properly completed filter should have the same product value
# as this number. This is how the filter is checked.
CHECK_STRING = '92.7429789714003440708375243748487223136051046'
CHECK_LOGARITHM = sy.Float(CHECK_STRING)
__, __, product_log10 = core.math.ifas_large_integer_array_product(
integer_array=test_filtered_array.compressed())
# Finally, check. As we are dealing with large single power
# prime composite numbers and long decimals, and the smallest
# factor change of removing the 2 product still changes the
# logarithm enough, checking if the logs are close is good
# enough.
assert_message = ("The check logarithm is: {check} "
"The product logarithm is: {log} "
"The filtered array is: \n {array}"
.format(check=CHECK_LOGARITHM, log=product_log10,
array=test_filtered_array))
assert math.isclose(product_log10, CHECK_LOGARITHM), assert_message
# All done.
return None
def test_filter_percent_truncation():
""" This tests the filtering of percent truncations."""
# Creating the testing array.
test_array = test.base.create_prime_test_array(shape=(7,7))
# Prescribed filtering parameters
# The top 35% and bottom 10%.
top_percent = 0.35
bottom_percent = 0.10
# Create the filter.
test_filter = mask.filter_percent_truncation(
data_array=test_array, top_percent=top_percent,
bottom_percent=bottom_percent)
# Create a filtered array for both convince and testing.
test_filtered_array = np_ma.array(test_array, mask=test_filter, dtype=int)
# A properly completed filter should have the same product value
# as this number. This is how the filter is checked.
CHECK_STRING = '48.3986809684295405908025212823332315778806862'
CHECK_LOGARITHM = sy.Float(CHECK_STRING)
__, __, product_log10 = core.math.ifas_large_integer_array_product(
integer_array=test_filtered_array.compressed())
# Finally, check. As we are dealing with large single power
# prime composite numbers and long decimals, and the smallest
# factor change of removing the 2 product still changes the
# logarithm enough, checking if the logs are close is good
# enough.
assert_message = ("The check logarithm is: {check} "
"The product logarithm is: {log} "
"The filtered array is: \n {array}"
.format(check=CHECK_LOGARITHM, log=product_log10,
array=test_filtered_array))
assert math.isclose(product_log10, CHECK_LOGARITHM), assert_message
# All done.
return None
def test_filter_pixel_truncation():
""" This tests the filtering of pixel boundaries."""
# Creating the testing array.
test_array = test.base.create_prime_test_array(shape=(7,7))
# Prescribed filtering parameters
# Top 13 pixels and bottom 9.
top_count = 13
bottom_count = 9
# Create the filter.
test_filter = mask.filter_pixel_truncation(data_array=test_array,
top_count=top_count,
bottom_count=bottom_count)
# Create a filtered array for both convince and testing.
test_filtered_array = np_ma.array(test_array, mask=test_filter, dtype=int)
# A properly completed filter should have the same product value
# as this number. This is how the filter is checked.
CHECK_STRING = '51.0043131557317283360473320982116998982267737'
CHECK_LOGARITHM = sy.Float(CHECK_STRING)
__, __, product_log10 = core.math.ifas_large_integer_array_product(
integer_array=test_filtered_array.compressed())
# Finally, check. As we are dealing with large single power
# prime composite numbers and long decimals, and the smallest
# factor change of removing the 2 product still changes the
# logarithm enough, checking if the logs are close is good
# enough.
assert_message = ("The check logarithm is: {check} "
"The product logarithm is: {log} "
"The filtered array is: \n {array}"
.format(check=CHECK_LOGARITHM, log=product_log10,
array=test_filtered_array))
assert math.isclose(product_log10, CHECK_LOGARITHM), assert_message
# All done.
return None
def test_filter_maximum_value():
""" This tests the filtering of values above a maximum."""
# Creating the testing array.
test_array = test.base.create_prime_test_array(shape=(7,7))
# Prescribed filtering parameters
# The value 113 should not be masked.
maximum_value = 113
# Create the filter.
test_filter = mask.filter_maximum_value(data_array=test_array,
maximum_value=maximum_value)
# Create a filtered array for both convince and testing.
test_filtered_array = np_ma.array(test_array, mask=test_filter, dtype=int)
# A properly completed filter should have the same product value
# as this number. This is how the filter is checked.
CHECK_STRING = '46.4998252465517387337527237516559582272076600'
CHECK_LOGARITHM = sy.Float(CHECK_STRING)
__, __, product_log10 = core.math.ifas_large_integer_array_product(
integer_array=test_filtered_array.compressed())
# Finally, check. As we are dealing with large single power
# prime composite numbers and long decimals, and the smallest
# factor change of removing the 2 product still changes the
# logarithm enough, checking if the logs are close is good
# enough.
assert_message = ("The check logarithm is: {check} "
"The product logarithm is: {log} "
"The filtered array is: \n {array}"
.format(check=CHECK_LOGARITHM, log=product_log10,
array=test_filtered_array))
assert math.isclose(product_log10, CHECK_LOGARITHM), assert_message
# All done.
return None
def test_filter_minimum_value():
""" This tests the filtering of values below a minimum."""
# Creating the testing array.
test_array = test.base.create_prime_test_array(shape=(7,7))
# Prescribed filtering parameters.
# The value 101 itself should not be masked.
minimum_value = 101
# Create the filter.
test_filter = mask.filter_minimum_value(data_array=test_array,
minimum_value=minimum_value)
# Create a filter array for both convince and testing.
test_filtered_array = np_ma.array(test_array, mask=test_filter, dtype=int)
# A properly completed filter should have the same product value
# as this number. This is how the filter is checked.
CHECK_STRING = '52.5579255086291590806495158287835916351211866'
CHECK_LOGARITHM = sy.Float(CHECK_STRING)
__, __, product_log10 = core.math.ifas_large_integer_array_product(
integer_array=test_filtered_array.compressed())
# Finally, check. As we are dealing with large single power
# prime composite numbers and long decimals, and the smallest
# factor change of removing the 2 product still changes the
# logarithm enough, checking if the logs are close is good
# enough.
assert_message = ("The check logarithm is: {check} "
"The product logarithm is: {log} "
"The filtered array is: \n {array}"
.format(check=CHECK_LOGARITHM, log=product_log10,
array=test_filtered_array))
assert math.isclose(product_log10, CHECK_LOGARITHM), assert_message
# All done.
return None
def test_filter_exact_value():
""" This tests the filtering of exact values."""
# Creating the testing array.
test_array = test.base.create_prime_test_array(shape=(7,7))
# Prescribed filtering parameters
exact_value = 101
# Create the filter.
test_filter = mask.filter_exact_value(data_array=test_array,
exact_value=exact_value)
# Create a filtered array for both convince and testing.
test_filtered_array = np_ma.array(test_array, mask=test_filter, dtype=int)
# A properly completed filter should have the same product value
# as this number. This is how the filter is checked.
CHECK_STRING = '86.9163820638011874618505104537286754939523446'
CHECK_LOGARITHM = sy.Float(CHECK_STRING)
__, __, product_log10 = core.math.ifas_large_integer_array_product(
integer_array=test_filtered_array.compressed())
# Finally, check. As we are dealing with large single power
# prime composite numbers and long decimals, and the smallest
# factor change of removing the 2 product still changes the
# logarithm enough, checking if the logs are close is good
# enough.
assert_message = ("The check logarithm is: {check} "
"The product logarithm is: {log} "
"The filtered array is: \n {array}"
.format(check=CHECK_LOGARITHM, log=product_log10,
array=test_filtered_array))
assert math.isclose(product_log10, CHECK_LOGARITHM), assert_message
# All done.
return None
def test_filter_invalid_value():
""" This tests the filtering of invalid values."""
# Creating the testing array.
test_array = test.base.create_prime_test_array(shape=(7,7))
# We need to force invalid values as the prime test creation
# does not have them.
test_array = np.array(test_array,dtype=float)
test_array[1:3,2] = np.inf
test_array[2,4:6] = -np.inf
test_array[5,1:6] = np.nan
# Prescribed filtering parameters
pass
# Create the filter.
test_filter = mask.filter_invalid_value(data_array=test_array)
# Create a filtered array for both convince and testing.
test_filtered_array = np_ma.array(test_array, mask=test_filter)
print(test_filtered_array)
# A properly completed filter should have the same product value
# as this number. This is how the filter is checked.
CHECK_STRING = '70.8884174145533646297736729939104459590381610'
CHECK_LOGARITHM = sy.Float(CHECK_STRING)
__, __, product_log10 = core.math.ifas_large_integer_array_product(
integer_array=test_filtered_array.compressed())
# Finally, check. As we are dealing with large single power
# prime composite numbers and long decimals, and the smallest
# factor change of removing the 2 product still changes the
# logarithm enough, checking if the logs are close is good
# enough.
assert_message = ("The check logarithm is: {check} "
"The product logarithm is: {log} "
"The filtered array is: \n {array}"
.format(check=CHECK_LOGARITHM, log=product_log10,
array=test_filtered_array))
assert math.isclose(product_log10, CHECK_LOGARITHM), assert_message
# All done.
return None
| 43.68662
| 78
| 0.682679
| 1,583
| 12,407
| 5.149716
| 0.116867
| 0.047473
| 0.037782
| 0.037782
| 0.805201
| 0.791094
| 0.765088
| 0.73528
| 0.73528
| 0.72473
| 0
| 0.045694
| 0.250343
| 12,407
| 283
| 79
| 43.840989
| 0.830771
| 0.357782
| 0
| 0.59854
| 0
| 0
| 0.128769
| 0.041134
| 0
| 0
| 0
| 0
| 0.10219
| 1
| 0.051095
| false
| 0.007299
| 0.058394
| 0
| 0.160584
| 0.007299
| 0
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| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
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| null | 0
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| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
46b81ea07da63066f9d258dbea466680c469be8c
| 124
|
py
|
Python
|
netsquid_executor/src/__init__.py
|
qis-unipr/dqc-executor
|
842f907830f557e506793553338eecf669e5ed32
|
[
"Apache-2.0"
] | null | null | null |
netsquid_executor/src/__init__.py
|
qis-unipr/dqc-executor
|
842f907830f557e506793553338eecf669e5ed32
|
[
"Apache-2.0"
] | null | null | null |
netsquid_executor/src/__init__.py
|
qis-unipr/dqc-executor
|
842f907830f557e506793553338eecf669e5ed32
|
[
"Apache-2.0"
] | 1
|
2021-08-05T13:30:53.000Z
|
2021-08-05T13:30:53.000Z
|
import os
import sys
from .network import *
sys.path.append(os.path.join(os.path.dirname(__file__), '../../dqc-circuit'))
| 17.714286
| 77
| 0.709677
| 19
| 124
| 4.421053
| 0.631579
| 0.214286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 124
| 6
| 78
| 20.666667
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0.137097
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.75
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
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| null | 0
| 0
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| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
46bc1f403cedc6023a0b25ab9b1e9661581190c2
| 161
|
py
|
Python
|
ex47_bc/tests/test_language.py
|
techieguy007/learn-more-python-the-hard-way-solutions
|
7886c860f69d69739a41d6490b8dc3fa777f227b
|
[
"Zed",
"Unlicense"
] | 466
|
2016-11-01T19:40:59.000Z
|
2022-03-23T16:34:13.000Z
|
ex47_bc/tests/test_language.py
|
Desperaaado/learn-more-python-the-hard-way-solutions
|
7886c860f69d69739a41d6490b8dc3fa777f227b
|
[
"Zed",
"Unlicense"
] | 2
|
2017-09-20T09:01:53.000Z
|
2017-09-21T15:03:56.000Z
|
ex47_bc/tests/test_language.py
|
Desperaaado/learn-more-python-the-hard-way-solutions
|
7886c860f69d69739a41d6490b8dc3fa777f227b
|
[
"Zed",
"Unlicense"
] | 241
|
2017-06-17T08:02:26.000Z
|
2022-03-30T09:09:39.000Z
|
from calc.run import run
def test_simple_function():
run(open("test1.calc").readlines())
def test_simple_script():
run(open("test2.calc").readlines())
| 20.125
| 39
| 0.708075
| 23
| 161
| 4.782609
| 0.565217
| 0.127273
| 0.236364
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0.014184
| 0.124224
| 161
| 7
| 40
| 23
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| 0.124224
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| 0.4
| true
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| 0.6
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| 0
|
0
| 6
|
20224c44d1636245b5d3e65fc4cfe887eb1054bd
| 91
|
py
|
Python
|
getnet/services/payments/__init__.py
|
7bruno/getnet-py
|
590db2f19e0c7f98ffdfbb27f4c6ffd7fb1f47ed
|
[
"MIT"
] | 2
|
2021-04-09T20:17:41.000Z
|
2021-04-09T20:18:06.000Z
|
getnet/services/payments/__init__.py
|
7bruno/getnet-py
|
590db2f19e0c7f98ffdfbb27f4c6ffd7fb1f47ed
|
[
"MIT"
] | null | null | null |
getnet/services/payments/__init__.py
|
7bruno/getnet-py
|
590db2f19e0c7f98ffdfbb27f4c6ffd7fb1f47ed
|
[
"MIT"
] | null | null | null |
from .order import Order
from .customer import Customer
from .order_items import OrderItem
| 22.75
| 34
| 0.835165
| 13
| 91
| 5.769231
| 0.461538
| 0.24
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0
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| 91
| 3
| 35
| 30.333333
| 0.949367
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| 1
| 0
| 1
| 0
|
0
| 6
|
203d8d3640d5f61cc6184a7f7fcd72ee159a148a
| 81
|
py
|
Python
|
lab-1/tempCodeRunnerFile.py
|
HITOfficial/python-laboratories
|
ae727563c95d1a5d5921566a3267594139d377bd
|
[
"MIT"
] | null | null | null |
lab-1/tempCodeRunnerFile.py
|
HITOfficial/python-laboratories
|
ae727563c95d1a5d5921566a3267594139d377bd
|
[
"MIT"
] | null | null | null |
lab-1/tempCodeRunnerFile.py
|
HITOfficial/python-laboratories
|
ae727563c95d1a5d5921566a3267594139d377bd
|
[
"MIT"
] | null | null | null |
# print(check_expr("01>"))
# print(check_expr("10>"))
# print(check_expr("11>"))
| 20.25
| 26
| 0.62963
| 12
| 81
| 4
| 0.5
| 0.625
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 0.074074
| 81
| 4
| 27
| 20.25
| 0.56
| 0.91358
| 0
| null | 0
| null | 0
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| null | 0
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| null | 1
| null | true
| 0
| 0
| null | null | null | 1
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| null | 1
| 1
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| null | 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
64466165c213dfc2a84ac0ba65fde11639e42804
| 2,907
|
py
|
Python
|
mapss/static/packages/arches/arches/app/models/migrations/4679_resource_editor_permissions.py
|
MPI-MAPSS/MAPSS
|
3a5c0109758801717aaa8de1125ca5e98f83d3b4
|
[
"CC0-1.0"
] | null | null | null |
mapss/static/packages/arches/arches/app/models/migrations/4679_resource_editor_permissions.py
|
MPI-MAPSS/MAPSS
|
3a5c0109758801717aaa8de1125ca5e98f83d3b4
|
[
"CC0-1.0"
] | null | null | null |
mapss/static/packages/arches/arches/app/models/migrations/4679_resource_editor_permissions.py
|
MPI-MAPSS/MAPSS
|
3a5c0109758801717aaa8de1125ca5e98f83d3b4
|
[
"CC0-1.0"
] | null | null | null |
# -*- coding: utf-8 -*-
# Generated by Django 1.9.2 on 2017-04-25 11:36
import os
import uuid
import django.db.models.deletion
import django.contrib.postgres.fields.jsonb
from django.db import migrations, models
from django.core import management
from arches.app.models.system_settings import settings
def add_permissions(apps, schema_editor, with_create_permissions=True):
db_alias = schema_editor.connection.alias
Group = apps.get_model("auth", "Group")
Permission = apps.get_model("auth", "Permission")
write_nodegroup = Permission.objects.get(codename='write_nodegroup', content_type__app_label='models', content_type__model='nodegroup')
delete_nodegroup = Permission.objects.get(codename='delete_nodegroup', content_type__app_label='models', content_type__model='nodegroup')
resource_editor_group = Group.objects.using(db_alias).get(name='Resource Editor')
resource_editor_group.permissions.add(write_nodegroup)
resource_editor_group.permissions.add(delete_nodegroup)
resource_editor_group = Group.objects.using(db_alias).get(name='Resource Reviewer')
resource_editor_group.permissions.add(write_nodegroup)
resource_editor_group.permissions.add(delete_nodegroup)
resource_editor_group = Group.objects.using(db_alias).get(name='Crowdsource Editor')
resource_editor_group.permissions.add(write_nodegroup)
resource_editor_group.permissions.add(delete_nodegroup)
def remove_permissions(apps, schema_editor, with_create_permissions=True):
db_alias = schema_editor.connection.alias
Group = apps.get_model("auth", "Group")
Permission = apps.get_model("auth", "Permission")
write_nodegroup = Permission.objects.get(codename='write_nodegroup', content_type__app_label='models', content_type__model='nodegroup')
delete_nodegroup = Permission.objects.get(codename='delete_nodegroup', content_type__app_label='models', content_type__model='nodegroup')
resource_editor_group = Group.objects.using(db_alias).get(name='Resource Editor')
resource_editor_group.permissions.remove(write_nodegroup)
resource_editor_group.permissions.remove(delete_nodegroup)
resource_editor_group = Group.objects.using(db_alias).get(name='Resource Reviewer')
resource_editor_group.permissions.remove(write_nodegroup)
resource_editor_group.permissions.remove(delete_nodegroup)
resource_editor_group = Group.objects.using(db_alias).get(name='Crowdsource Editor')
resource_editor_group.permissions.remove(write_nodegroup)
resource_editor_group.permissions.remove(delete_nodegroup)
class Migration(migrations.Migration):
dependencies = [
('models', '4384_adds_rerender_widget_config'),
]
operations = [
## the following command has to be run after the previous RunSQL commands that update the domain datatype values
migrations.RunPython(add_permissions,remove_permissions),
]
| 46.887097
| 141
| 0.79257
| 365
| 2,907
| 6.00274
| 0.243836
| 0.127796
| 0.156093
| 0.153355
| 0.77864
| 0.77864
| 0.77864
| 0.77864
| 0.77864
| 0.77864
| 0
| 0.007725
| 0.109391
| 2,907
| 61
| 142
| 47.655738
| 0.838548
| 0.060888
| 0
| 0.636364
| 1
| 0
| 0.112294
| 0.011743
| 0
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| 0
| 1
| 0.045455
| false
| 0
| 0.159091
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| 0.272727
| 0
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| null | 0
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| 1
| 1
| 1
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| 0
| 0
| 0
| 0
|
0
| 6
|
644b944e0d13595ffcbbae8fec0a3e61ba471ec9
| 34
|
py
|
Python
|
crabs/options.py
|
tor4z/crabs
|
7d525ebe8a0791a82635fad744ec5c92adc19cf0
|
[
"MIT"
] | null | null | null |
crabs/options.py
|
tor4z/crabs
|
7d525ebe8a0791a82635fad744ec5c92adc19cf0
|
[
"MIT"
] | 4
|
2021-01-07T22:41:11.000Z
|
2021-06-01T22:10:14.000Z
|
crabs/options.py
|
tor4z/crabs
|
7d525ebe8a0791a82635fad744ec5c92adc19cf0
|
[
"MIT"
] | null | null | null |
from .http_client.options import *
| 34
| 34
| 0.823529
| 5
| 34
| 5.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.088235
| 34
| 1
| 34
| 34
| 0.870968
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| null | 0
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| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
6454dde4728a4809c9dc82544950d5d84329e67c
| 7,393
|
py
|
Python
|
Toolkits/Discovery/meta/searx/tests/unit/engines/test_google_news.py
|
roscopecoltran/SniperKit-Core
|
4600dffe1cddff438b948b6c22f586d052971e04
|
[
"MIT"
] | null | null | null |
Toolkits/Discovery/meta/searx/tests/unit/engines/test_google_news.py
|
roscopecoltran/SniperKit-Core
|
4600dffe1cddff438b948b6c22f586d052971e04
|
[
"MIT"
] | null | null | null |
Toolkits/Discovery/meta/searx/tests/unit/engines/test_google_news.py
|
roscopecoltran/SniperKit-Core
|
4600dffe1cddff438b948b6c22f586d052971e04
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from collections import defaultdict
import mock
from searx.engines import google_news
from searx.testing import SearxTestCase
class TestGoogleNewsEngine(SearxTestCase):
def test_request(self):
query = 'test_query'
dicto = defaultdict(dict)
dicto['pageno'] = 1
dicto['language'] = 'fr_FR'
dicto['time_range'] = 'w'
params = google_news.request(query, dicto)
self.assertIn('url', params)
self.assertIn(query, params['url'])
self.assertIn('fr', params['url'])
dicto['language'] = 'all'
params = google_news.request(query, dicto)
self.assertIn('url', params)
self.assertNotIn('fr', params['url'])
def test_response(self):
self.assertRaises(AttributeError, google_news.response, None)
self.assertRaises(AttributeError, google_news.response, [])
self.assertRaises(AttributeError, google_news.response, '')
self.assertRaises(AttributeError, google_news.response, '[]')
response = mock.Mock(text='{}')
self.assertEqual(google_news.response(response), [])
response = mock.Mock(text='{"data": []}')
self.assertEqual(google_news.response(response), [])
html = u"""
<div class="g">
<div class="ts _V6c _Zmc _XO _knc _d7c"><a class="top _vQb _mnc" href="http://this.is.the.url" onmousedown="return rwt(this,'','','','5','AFQjCNGixEtJGC3qTB9pYFLXlRj8XXwdiA','','0ahUKEwiG7O_M5-rQAhWDtRoKHd0RD5QQvIgBCCwwBA','','',event)"><img class="th _lub" id="news-thumbnail-image-52779299683347" src="data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEAAkGBwgHBgkIBwgKCgkLDRYPDQwMDRsUFRAWIB0iIiAdHx8kKDQsJCYxJx8fLT0tMTU3Ojo6Iys/RD84QzQ5OjcBCgoKDQwNGg8PGjclHyU3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3Nzc3N//AABEIAGQAZAMBIgACEQEDEQH/xAAbAAACAwEBAQAAAAAAAAAAAAAFBgADBAIBB//EADsQAAIBAwIEAwUGBAUFAAAAAAECAwAEEQUhBhIxURNBYRQiMnGBFSORobHBB1Ji4UKS0fDxFiQzNYL/xAAYAQEBAQEBAAAAAAAAAAAAAAACAwEEAP/EACERAAMBAAICAgMBAAAAAAAAAAABAhEhMQMSE2EEQVEi/9oADAMBAAIRAxEAPwDSkKr8JFWIzwnMTlSepFdiBgMiuxEdid6B7QbrEr8qE4L4wGNCIT7u/WifE0eIosHBz0oWnugCjQ4BfEipJHbpK/JG0gDP/KO9XT6Lw7BGDHrofIBIJQ4NXalAs8IDJnFLepS21pmOOFXl679FoY66ZTcNwWxtGzaaqwOf8JFcXupSSr4cupSOp6gnGaDQahJESQwU/wBIxXbX0l0jl+VgduYjJrfj/ofc9MluueV1z3xV2jlX1AlDkY61TY3MAk5LuJSnm4G4+nnTFb2ltEweFRvuCO1ebw8uTYNnQ9iDTtDKJYY8DflFJgXLp8xT5FbJHBGx/lFFM9a4MrQFjnFSilvPGiYaItv1zUrTnwHljgLViqwUDyNFEskKlmIDCs08JMWHfl32INZ8hnIscWII4oWPmdqCg9KLccsUtLZM596g6HmVT6Um9WlvGeXk/gWruCObGFz3pb0/R59Y1D2WDYk5lmfpGP3PpW7iK4aIxY3CqWA7t5UxcG3SQWxsZI2VI0MxM6hedj1Oeo9Kc5M6PPagQ3DdjpcpWeHx2U7s+9LuvPCsr+yoETIwAOgpq1DV59RmuJIpbS2hhOG5zvmlLVXE4OCpcnBKdDRW7ptZgMEuCCPrTJwteGYS2z78vvpnt5j/AH3pWIxRbhZ+XV4h5Orj8s/tTtcE5fI6xKWmjVepYfrX0trQrbxLICDyDavm0EvgXEU2M8jhsfI033fHiyxxSfZkwj+EtjP6VzpPR0E8ICQR0qUuT8Y2DSExxtj69alVwOINy3Esye7zKfnXdpZzzMjSfAO1KGm8UX99qNvbm1SNZZApYnoPOimr6rf2crBLmQoTsFIwo8htUHDRk+N0Zv4nQi2itMHALUAiP3SH0oxJrUtyqJcKk4GDiZeb9a0LqkOADY2nz8FaSeLCkxgsWUVrecWQRXwDQW8DzMpGckdNvPr0orxZfpa2if8AYywPIfDkY4YDYHbHbcVgucf9YWd3CqR+MxUgDC5C7bDy2FecRzXQsxJd3lmJN8wCPCvgkZBBOc1Vr2kccaA7PkuBOm6qzD3+XZh1/UflWG+isoGAgMjPzb8x2Jz2r37Sm8AouynqKFyOQxkk8unqa9KYKawolI529CRRLhr/ANxb46AOT/lNBgSTTPwTL7PqMlwpHOkXKuR3IzTvonPY2WqCa6hiPR3VT9TTfx3pzaRb2IskUJICpBPUgUvDXphjLR5HQ8oq6bii9uOUXExmC/CJBzY/GoTWFXOiKV1BZpvEjJYyEkgbb1Kdvt19j9zk9fuk/wBKlL5foz0Zk0vTWa0N/hyVYqiKcZ26/jSvdX81pqET+0PJCX8Nw3l6H5b19H0pccPWpxu2WO/9R3pQ4s0yzi1K4gcFGuW8WN+b3STny8t6xr9lU+MRe2AQVPukZGKq9qTxzCGJcLzbHIqm2uILSCO2uiyvF7pdh1HUNjtQO0uootbLSmQ25kIfwyOYrnyztmvT/oL4C91M3NHIh96GRZB9D+/T61xxNf6XqbBrC2LSbkhVyfypk1Cew1SP7F0exNjbW8LXeovKwMx5VJCs3/0vToT6EUhcHTqOIEfConIyLy+QNX9MWElYOmkYHDKVx5EYrFIrSNk7imriCFrm7kt+TM8R5ie696y6Do41G5naUlLa2TnkxjJ7L9TR3BOdeCzgbg82fntRvR1mtbpGYe5IvUdiP7isrWDSTuIwFIyewA+tbraC7js4J7WVpYz92VUZMTdeUr28wenX1rXyg+rTC7TkHrXonPeiGk6TFeWeNQuWsLot7kkihoXHrj3l+e4oZJbSxzTxY5mgcrJyHmAx57eXrXOVc1Pawt8dq8rPv5VKww+jWUgbhGymTO8QIPod6y8cadHfaQsgws8GWUjrjO4/erXxa8M2cETZCW6bEdNq513UlsbSO6mh9oRXXmh5+UPkk4Jx54NdUrQ08Qj2cQ1ezMDkpexA7k/EBQ+C3ubOVXliICts3l1rXqEr3+qPeWASK7n55vZ7bHhxDGeQf1coJP4dc13Y8SMiPDeRBiRjp19DUaiofBs3NLkKahcwcNaLJaQMtzquspz3jhuYRRE5EYPc9W/4oDDYGyvLO4upLdB4YzFFJmRQq5HMvcj9qtvI7SPXpGguxqFvFysZSvKHON167gdM1a/EUb6fLYz2FvI01yJZrphmVlyCVHYfLue9dTWyRisotfVpLm8D272suB0mURtjtkV3p2qwWF5P7VbmETAK6ZyrD0odrtq+nTiy1PT47Oc4mWWPBflYbA4OMenWsdnd3FusqxOkyMpVkYdR9a5nLXBer2tQyxRWcjznT5CpfDBMbtjoPl6VlN+sCLNbwMZjIysoAGPQj8OtBre5dJeaPKN5ods0aGoW2o2rQ3i/eHYSpsw+dTc4dng/L9J9WjSsK3Og3V/JeQWvhL4cUcr5Zj5j0JGw9aG6Jpst3NDFLcmzNzA8ts2ATIyZ265Xz/vtWbVbOzgQCW4eJ4oT4I8MkSHyUYHmepJAHY0PWGSbT11CFFSGKQwM6EhmYjOTv2OM7darCyeDl/J8r8nk1sIwXDSRK7jDHrnY586lNuh6Pouu6Xb3ZvE06ZV8KaFCFUuvVgD0zsa8oNE9CmpA/YtoRkhrdPptWPidZ5dGuIraETSye6V64jQB3IH82QD8gcb1gvuIDJp9vaW8JVkRYyZN8kDyArBbXx1XXLO2vb2SKI8yyGBSFRSu+MZJzhc/6V1QsYLeo1R3Oh3dnby6RYvDcWcQE1wUVRM3KASQCd/n39aUkhN7rltFJ1muI0OP6mA/ejeqX1jYaxLpOmzmfT4IQgmOMu5PMzbAdwPpS+l37Pq8NzGvM0Myui9yrAgfpXrfIZ6CkmjXWpa9qcPD9s3hQvIyoGGBGrcvmfP96OcI8YaTpelw2mp6MJkR2cThVkEj9dww28umdsVm0HSotb1O6tbK5v8ATp1R2dmcOo94Aqccp8/yoHxBbrpt39lLMswtCweRVwGdt2/ABR9KbWAX2aNX1231DiCXVru3M5kkLmGR/cIxhV+QAH4UHvbqC5lMsFvFa7Y5Yc4P4k0X1vS7XS9E0znwb+6BmkXkX3E8t8ZzuOpxsawXEa6Td3MKrHLJ4JhdiPgYgc2PUbrn51Nz/WPfoxpOcY8QEjbB3q2KUswzjbzWt+t3Ftcw2Hh28cKwRLCzqP8AydMtjA32rnUtG9jiS4srhJ7OT4JUYZ+TDqDQpCVFpmW/g9llYArvGxHwmrNX0v2HQdKkjcxx3HOZk5jhnGMk9+woRFKUO/Uedbprye8tGiZs28Eikcx+FmBG3ocfkKKWcG1zyPv8PLi2Xh3wpbOSQxTuodFHvA4PbuTUpG07XtW0qA29lMYoy3MVx5kD07AVKxzyZphmvZnWViR/KMeQrvQ4lutQm8bJ8G0lmUZ/xKuRn61KldDACoHYzu7MSx6sepo9pFtE/vMMloyT9cj8sV7UoPsS6G7+HX3Wm6jdLvM0ioWPYLn9SaQFka91NHuTzme4Bkz58zb/AK17Uq1dImg5rcrXPGcUU2GSIxqq+QGA36ml+bMkaXEjM0kw8R89yd6lSpiCfCcEV7fXdpcxq8TWUjjujAggr2NXcJ3k08F9pcpDWslpJNyEfA6gEFe29SpQZqAgbmAY9TvXAY5YZOCRUqV79ifRthucRhXgglxsGkTmIHbNSpUrAn//2Q==" alt="A(z) south témájának képe a következőből: CBC.ca" data-deferred="1" onload="google.aft&&google.aft(this)"></a><div class="_cnc"><h3 class="r _U6c"><a class="l _HId" href="http://this.is.the.url" onmousedown="return rwt(this,'','','','5','AFQjCNGixEtJGC3qTB9pYFLXlRj8XXwdiA','','0ahUKEwiG7O_M5-rQAhWDtRoKHd0RD5QQqQIILSgAMAQ','','',event)">Meet Thuli Madonsela — <em>South</em> Africa's conscience</a></h3><div class="slp"><span class="_tQb _IId">CBC.ca</span><span class="_v5">-</span><span class="f nsa _uQb">9 órával ezelőtt</span></div><div class="st"><em>South</em> African Public Protector</div></div><div class="_Xmc card-section"><a class="_sQb" href="http://www.news24.com/Columnists/Mpumelelo_Mkhabela/who-really-governs-south-africa-20161209" onmousedown="return rwt(this,'','','','5','AFQjCNHhc2MnYSZ5T4COqInzvgoju5k5bA','','0ahUKEwiG7O_M5-rQAhWDtRoKHd0RD5QQuogBCC4oATAE','','',event)">Who really governs <em>South</em> Africa?</a><br><span class="_Wmc _GId">Vélemény</span><span class="_v5">-</span><span class="_tQb _IId">News24</span><span class="_v5">-</span><span class="f nsa _uQb">2016. dec. 8.</span></div><div class="_Vmc"></div></div>
</div>
""" # noqa
response = mock.Mock(text=html)
results = google_news.response(response)
self.assertEqual(type(results), list)
self.assertEqual(len(results), 1)
self.assertEqual(results[0]['title'], u'Meet Thuli Madonsela \u2014 South Africa\'s conscience')
self.assertEqual(results[0]['url'], 'http://this.is.the.url')
self.assertEqual(results[0]['content'], 'South African Public Protector')
| 144.960784
| 5,644
| 0.843906
| 499
| 7,393
| 12.416834
| 0.492986
| 0.016139
| 0.020336
| 0.023241
| 0.12153
| 0.108457
| 0.087476
| 0.082957
| 0.082957
| 0.082957
| 0
| 0.102852
| 0.061004
| 7,393
| 50
| 5,645
| 147.86
| 0.789542
| 0.003517
| 0
| 0.15
| 0
| 0.025
| 0.797257
| 0.668387
| 0
| 1
| 0
| 0
| 0.4
| 1
| 0.05
| false
| 0
| 0.1
| 0
| 0.175
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 1
| 1
| 0
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| 1
| 1
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
648696ea1dd02801d739e6e534a41a0641b1a7c6
| 48
|
py
|
Python
|
super_taxi/controllers/registration.py
|
sanjayatb/taxi-booking-system
|
b78f8ab00a7f6d12c786331880242ce0306480bb
|
[
"MIT"
] | null | null | null |
super_taxi/controllers/registration.py
|
sanjayatb/taxi-booking-system
|
b78f8ab00a7f6d12c786331880242ce0306480bb
|
[
"MIT"
] | null | null | null |
super_taxi/controllers/registration.py
|
sanjayatb/taxi-booking-system
|
b78f8ab00a7f6d12c786331880242ce0306480bb
|
[
"MIT"
] | 1
|
2021-09-17T18:23:13.000Z
|
2021-09-17T18:23:13.000Z
|
"Registation controller implementaion goes here"
| 48
| 48
| 0.875
| 5
| 48
| 8.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 48
| 1
| 48
| 48
| 0.954545
| 0.958333
| 0
| 0
| 0
| 0
| 0.938776
| 0
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| 0
| 0
| 0
| 0
| 1
| 0
| true
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| 0
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| 0
| 0
| 0
| 0
| 1
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
64c2c94603cdbaefe677a154621a4b1aae942632
| 798
|
py
|
Python
|
2421.py
|
ErFer7/URI-Python
|
94c36985852204e34806650e4ffec48d4d9e9ab1
|
[
"MIT"
] | 1
|
2022-02-06T19:36:33.000Z
|
2022-02-06T19:36:33.000Z
|
2421.py
|
ErFer7/URI-Python
|
94c36985852204e34806650e4ffec48d4d9e9ab1
|
[
"MIT"
] | null | null | null |
2421.py
|
ErFer7/URI-Python
|
94c36985852204e34806650e4ffec48d4d9e9ab1
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
xy = list(map(int, input().split()))
lh0 = list(map(int, input().split()))
lh1 = list(map(int, input().split()))
if lh0[1] + lh1[1] <= xy[1] and max(lh0[0], lh1[0]) <= xy[0]:
print("S")
elif lh0[0] + lh1[1] <= xy[1] and max(lh0[1], lh1[0]) <= xy[0]:
print("S")
elif lh0[1] + lh1[0] <= xy[1] and max(lh0[0], lh1[1]) <= xy[0]:
print("S")
elif lh0[0] + lh1[0] <= xy[1] and max(lh0[1], lh1[1]) <= xy[0]:
print("S")
elif lh0[0] + lh1[0] <= xy[0] and max(lh0[1], lh1[1]) <= xy[1]:
print("S")
elif lh0[0] + lh1[1] <= xy[0] and max(lh0[1], lh1[0]) <= xy[1]:
print("S")
elif lh0[1] + lh1[0] <= xy[0] and max(lh0[0], lh1[1]) <= xy[1]:
print("S")
elif lh0[1] + lh1[1] <= xy[0] and max(lh0[0], lh1[0]) <= xy[1]:
print("S")
else:
print("N")
| 24.181818
| 63
| 0.488722
| 160
| 798
| 2.4375
| 0.13125
| 0.082051
| 0.14359
| 0.233333
| 0.923077
| 0.769231
| 0.741026
| 0.466667
| 0.138462
| 0.138462
| 0
| 0.130298
| 0.201754
| 798
| 33
| 64
| 24.181818
| 0.481947
| 0.026316
| 0
| 0.380952
| 0
| 0
| 0.011598
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.428571
| 0
| 0
| 0
| null | 0
| 0
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 6
|
b37e7e6a89913cc627e09496f52ed5a1a3d32964
| 77
|
py
|
Python
|
ttools/modules/__init__.py
|
IlyaBizyaev/ttools
|
b1435b19f397ce1baff9daed3cb287e52a029fdb
|
[
"MIT"
] | 11
|
2018-11-15T05:33:35.000Z
|
2022-01-11T16:18:35.000Z
|
ttools/modules/__init__.py
|
IlyaBizyaev/ttools
|
b1435b19f397ce1baff9daed3cb287e52a029fdb
|
[
"MIT"
] | 2
|
2019-10-02T16:20:31.000Z
|
2021-06-28T06:57:17.000Z
|
ttools/modules/__init__.py
|
IlyaBizyaev/ttools
|
b1435b19f397ce1baff9daed3cb287e52a029fdb
|
[
"MIT"
] | 6
|
2019-06-28T00:07:24.000Z
|
2021-08-22T15:51:07.000Z
|
from .networks import *
from .image_operators import *
from .losses import *
| 19.25
| 30
| 0.766234
| 10
| 77
| 5.8
| 0.6
| 0.344828
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.155844
| 77
| 3
| 31
| 25.666667
| 0.892308
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
374c8ab766a49cd3f6988ec8679ae3c5ef1576ae
| 38
|
py
|
Python
|
tests/python-reference/lists/test_list_assign.py
|
jpolitz/lambda-py-paper
|
746ef63fc1123714b4adaf78119028afbea7bd76
|
[
"Apache-2.0"
] | 25
|
2015-04-16T04:31:49.000Z
|
2022-03-10T15:53:28.000Z
|
tests/python-reference/lists/test_list_assign.py
|
jpolitz/lambda-py-paper
|
746ef63fc1123714b4adaf78119028afbea7bd76
|
[
"Apache-2.0"
] | 1
|
2018-11-21T22:40:02.000Z
|
2018-11-26T17:53:11.000Z
|
tests/python-reference/lists/test_list_assign.py
|
jpolitz/lambda-py-paper
|
746ef63fc1123714b4adaf78119028afbea7bd76
|
[
"Apache-2.0"
] | 1
|
2021-03-26T03:36:19.000Z
|
2021-03-26T03:36:19.000Z
|
l = [1,2]
l[0] = 4
assert(l == [4,2])
| 9.5
| 18
| 0.394737
| 10
| 38
| 1.5
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.206897
| 0.236842
| 38
| 3
| 19
| 12.666667
| 0.310345
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
375cc5649fcefb26d518c5b7395cb92b88dafb52
| 76
|
py
|
Python
|
py_tdlib/constructors/request_password_recovery.py
|
Mr-TelegramBot/python-tdlib
|
2e2d21a742ebcd439971a32357f2d0abd0ce61eb
|
[
"MIT"
] | 24
|
2018-10-05T13:04:30.000Z
|
2020-05-12T08:45:34.000Z
|
py_tdlib/constructors/request_password_recovery.py
|
MrMahdi313/python-tdlib
|
2e2d21a742ebcd439971a32357f2d0abd0ce61eb
|
[
"MIT"
] | 3
|
2019-06-26T07:20:20.000Z
|
2021-05-24T13:06:56.000Z
|
py_tdlib/constructors/request_password_recovery.py
|
MrMahdi313/python-tdlib
|
2e2d21a742ebcd439971a32357f2d0abd0ce61eb
|
[
"MIT"
] | 5
|
2018-10-05T14:29:28.000Z
|
2020-08-11T15:04:10.000Z
|
from ..factory import Method
class requestPasswordRecovery(Method):
pass
| 12.666667
| 38
| 0.802632
| 8
| 76
| 7.625
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131579
| 76
| 5
| 39
| 15.2
| 0.924242
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.666667
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 6
|
375dafd5c943336a42c523a676b8a24a7290832f
| 27
|
py
|
Python
|
src/euler_python_package/euler_python/medium/p359.py
|
wilsonify/euler
|
5214b776175e6d76a7c6d8915d0e062d189d9b79
|
[
"MIT"
] | null | null | null |
src/euler_python_package/euler_python/medium/p359.py
|
wilsonify/euler
|
5214b776175e6d76a7c6d8915d0e062d189d9b79
|
[
"MIT"
] | null | null | null |
src/euler_python_package/euler_python/medium/p359.py
|
wilsonify/euler
|
5214b776175e6d76a7c6d8915d0e062d189d9b79
|
[
"MIT"
] | null | null | null |
def problem359():
pass
| 9
| 17
| 0.62963
| 3
| 27
| 5.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15
| 0.259259
| 27
| 2
| 18
| 13.5
| 0.7
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 6
|
379a24c2dc9b4a6c5f50a37897f6f29edf3b6bd6
| 25
|
py
|
Python
|
src/pyoram/crypto/__init__.py
|
ghackebeil/PyORAM
|
53e109dfb1ecec52348a70ddc64fae65eea7490a
|
[
"MIT"
] | 24
|
2016-04-14T14:27:37.000Z
|
2022-03-13T13:53:18.000Z
|
src/pyoram/crypto/__init__.py
|
ghackebeil/PyORAM
|
53e109dfb1ecec52348a70ddc64fae65eea7490a
|
[
"MIT"
] | 4
|
2016-03-14T04:40:23.000Z
|
2016-06-01T04:37:18.000Z
|
src/pyoram/crypto/__init__.py
|
ghackebeil/PyORAM
|
53e109dfb1ecec52348a70ddc64fae65eea7490a
|
[
"MIT"
] | 4
|
2016-03-16T23:53:24.000Z
|
2020-05-27T19:27:37.000Z
|
import pyoram.crypto.aes
| 12.5
| 24
| 0.84
| 4
| 25
| 5.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 25
| 1
| 25
| 25
| 0.913043
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
37a4da46a3c687b596eeb192889b847bb0d9da4c
| 83
|
py
|
Python
|
switchingtime/__init__.py
|
xinyufei/Quantum-Control-qutip
|
bd8a119b9ff8ac0929ffb1f706328759d89fcb5e
|
[
"BSD-3-Clause"
] | 1
|
2021-08-31T02:28:54.000Z
|
2021-08-31T02:28:54.000Z
|
switchingtime/__init__.py
|
xinyufei/Quantum-Control-qutip
|
bd8a119b9ff8ac0929ffb1f706328759d89fcb5e
|
[
"BSD-3-Clause"
] | null | null | null |
switchingtime/__init__.py
|
xinyufei/Quantum-Control-qutip
|
bd8a119b9ff8ac0929ffb1f706328759d89fcb5e
|
[
"BSD-3-Clause"
] | null | null | null |
from switchingtime.switch_time import *
from switchingtime.obtain_switches import *
| 41.5
| 43
| 0.86747
| 10
| 83
| 7
| 0.7
| 0.485714
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.084337
| 83
| 2
| 43
| 41.5
| 0.921053
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 6
|
37ac4eb84271a591d983d4b957d57fd5fec029b6
| 11,951
|
py
|
Python
|
tensorflow_text/python/numpy/viterbi_decode_test.py
|
fsx950223/text
|
24ea0a43ef21a33c3f3f2f526530d23ad3ff7d90
|
[
"Apache-2.0"
] | 1
|
2020-10-10T14:10:07.000Z
|
2020-10-10T14:10:07.000Z
|
tensorflow_text/python/numpy/viterbi_decode_test.py
|
fsx950223/text
|
24ea0a43ef21a33c3f3f2f526530d23ad3ff7d90
|
[
"Apache-2.0"
] | 1
|
2021-02-24T01:09:21.000Z
|
2021-02-24T01:09:21.000Z
|
tensorflow_text/python/numpy/viterbi_decode_test.py
|
fsx950223/text
|
24ea0a43ef21a33c3f3f2f526530d23ad3ff7d90
|
[
"Apache-2.0"
] | null | null | null |
# coding=utf-8
# Copyright 2020 TF.Text Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for tensorflow_text.python.numpy.viterbi_decode."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from absl.testing import absltest
import numpy as np
from tensorflow_text.python.numpy import viterbi_decode
class ViterbiDecodeTest(absltest.TestCase):
def test_viterbi_in_log_space(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = -float('inf')
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[-1.0, 1.0, -2.0, 2.0],
[ 3.0, -3.0, 4.0, -4.0],
[ 5.0, x, 10.0, x],
[-7.0, 7.0, -8.0, 8.0]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {10.0, 12.0, 6.0, 4.0}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# To get the weighted scores, add the column of the final state to
# the raw score.
#
# Final state 0: (13.0) Weighted scores are {12.0, 16.0, 18.0, 6.0}
# New totals are {22, 28, 24, 10} [max 28 from 1]
#
# Final state 1: (12.0) Weighted scores are {13.0, 9.0, X, 19.0},
# New totals are {23, 21, X, 23} [max 23 from 3]
#
# Final state 2: (11.0) Weighted scores are {9, 15, 21, 3},
# New totals are {19, 27, 27, 7} [max 27 from 2]
#
# Final state 3: (10.0) Weighted scores are {12, 6, X, 18},
# New totals are {19, 18, X, 22} [max 25 from 3]
#
# Top scores are [28, 26, 27, 25] from [1, 3, 2, 3].
# Final state is [0] with a sequence of [1->0].
sequence, score = viterbi_decode.decode(scores, transition_params)
self.assertAlmostEqual(28.0, score)
self.assertEqual([1, 0], sequence)
def test_viterbi_with_allowed_transitions(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[-1.0, 1.0, -2.0, 2.0],
[ 3.0, -3.0, 4.0, -4.0],
[ 5.0, 100.0, 10.0, 200.0],
[-7.0, 7.0, -8.0, 8.0]])
allowed_transitions = np.array([[ True, True, True, True],
[ True, True, True, True],
[ True, False, True, False],
[ True, True, True, True]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {10.0, 12.0, 6.0, 4.0}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {12.0, 16.0, 18.0, 6.0}
# New totals are {22, 28, 24, 10} [max 28 from 1]
#
# Final state 1: (12.0) Weighted scores are {13.0, 9.0, X, 19.0},
# New totals are {23, 21, X, 23} [max 23 from 3]
#
# Final state 2: (11.0) Weighted scores are {9, 15, 21, 3},
# New totals are {19, 27, 27, 7} [max 27 from 2]
#
# Final state 3: (10.0) Weighted scores are {12, 6, X, 18},
# New totals are {19, 18, X, 22} [max 22 from 3]
#
# Top scores are [28, 26, 27, 25] from [1, 3, 2, 3].
# Final state is [0] with a sequence of [1->0].
sequence, score = viterbi_decode.decode(scores, transition_params,
allowed_transitions)
self.assertAlmostEqual(28.0, score)
self.assertEqual([1, 0], sequence)
def test_viterbi_in_log_space_with_start_and_end(self):
scores = np.array([[10.0, 12.0, 7.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = -float('inf')
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[-1.0, 1.0, -2.0, 2.0, 0.0],
[ 3.0, -3.0, 4.0, -4.0, 0.0],
[ 5.0, x, 10.0, x, x],
[-7.0, 7.0, -8.0, 8.0, 0.0],
[ 0.0, x, 2.0, 3.0, 0.0]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# All scores should be summed with the last row in the weight tensor, so the
# 'real' scores are:
# B0: { 10.0, X, 9.0, 7.0}
#
# STEP 2:
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {12.0, 16.0, 18.0, 6.0}
# New totals are {22, X, 27, 18} [max 27 from 2]
#
# Final state 1: (12.0) Weighted scores are {13.0, 9.0, X, 19.0},
# New totals are {23, X, X, 26} [max 26 from 3]
#
# Final state 2: (11.0) Weighted scores are {9, 15, 21, 3},
# New totals are {19, X, 30, 10} [max 30 from 2]
#
# Final state 3: (10.0) Weighted scores are {12, 6, X, 18},
# New totals are {19, X, X, 25} [max 25 from 3]
#
# Top scores are [27, 26, 30, 25] from [2, 3, 2, 3].
# 2->OUT is X, so final scores are [27, 26, X, 25] for a
# final state of [0] with a sequence of [2->0].
sequence, score = viterbi_decode.decode(
scores, transition_params, use_start_and_end_states=True)
self.assertAlmostEqual(27.0, score)
self.assertEqual([2, 0], sequence)
def test_viterbi_in_exp_space(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = 0.0
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[ .1, .2, .3, .4],
[ .5, .6, .7, .8],
[ .9, x, .15, x],
[.25, .35, .45, .55]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {10.0, 12.0, 6.0, 4.0}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {1.3, 6.5, 11.7, 3.25}
# New totals are {13, 78, 70.2, 13} [max 78 from 1]
#
# Final state 1: (12.0) Weighted scores are {2.4, 7.2, 0, 4.2},
# New totals are {24, 86.4, 0, 16.8} [max 86.4 from 1]
#
# Final state 2: (11.0) Weighted scores are {3.3, 7.7, 1.65, 4.95},
# New totals are {33, 92.4, 9.9, 19.8} [max 92.4 from 1]
#
# Final state 3: (10.0) Weighted scores are {4, 8, 0, 5.5},
# New totals are {40, 96, 0, 22} [max 96 from 1]
#
# Top scores are [78, 86.4, 92.4, 96] from [1, 1, 1, 1].
# Final state is [3] with a sequence of [1->3].
sequence, score = viterbi_decode.decode(
scores, transition_params, use_log_space=False)
self.assertAlmostEqual(96.0, score)
self.assertEqual([1, 3], sequence)
def test_viterbi_in_exp_space_with_allowed_transitions(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[ .1, .2, .3, .4],
[ .5, .6, .7, .8],
[ .9, .5, .15, .5],
[.25, .35, .45, .55]])
allowed_transitions = np.array([[ True, True, True, True],
[ True, True, True, True],
[ True, False, True, False],
[ True, True, True, True]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {10.0, 12.0, 6.0, 4.0}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {1.3, 6.5, 11.7, 3.25}
# New totals are {13, 78, 70.2, 13} [max 78 from 1]
#
# Final state 1: (12.0) Weighted scores are {2.4, 7.2, 0, 4.2},
# New totals are {24, 86.4, 0, 16.8} [max 86.4 from 1]
#
# Final state 2: (11.0) Weighted scores are {3.3, 7.7, 1.65, 4.95},
# New totals are {33, 92.4, 9.9, 19.8} [max 92.4 from 1]
#
# Final state 3: (10.0) Weighted scores are {4, 8, 0, 5.5},
# New totals are {40, 96, 0, 22} [max 96 from 1]
#
# Top scores are [78, 86.4, 92.4, 96] from [1, 1, 1, 1].
# Final state is [3] with a sequence of [1->3].
sequence, score = viterbi_decode.decode(
scores, transition_params, allowed_transitions, use_log_space=False)
self.assertAlmostEqual(96.0, score)
self.assertEqual([1, 3], sequence)
def test_viterbi_in_exp_space_with_start_and_end(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = 0.0
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[ .1, .2, .3, .4, .1],
[ .5, .6, .7, .8, .1],
[ .9, x, .15, x, .1],
[.25, .35, .45, .55, .5],
[ .1, .5, .1, .1, x]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
# STEP 1:
# Starting scores are {.5, 6.0, .6, .4}
# Raw scores are: {13.0, 12.0, 11.0, 10.0}
#
# Final state 0: (13.0) Weighted scores are {1.3, 6.5, 11.7, 3.25}
# New totals are {0.13, 39, 7.02, 1.3} [max 39 from 1]
#
# Final state 1: (12.0) Weighted scores are {2.4, 7.2, 0, 4.2},
# New totals are {0.24, 43.2, 0, 1.68} [max 43.2 from 1]
#
# Final state 2: (11.0) Weighted scores are {3.3, 7.7, 1.65, 4.95},
# New totals are {0.33, 46.2, 0.99, 1.98} [max 46.2 from 1]
#
# Final state 3: (10.0) Weighted scores are {4, 8, 0, 5.5},
# New totals are {0.4, 48, 0, 2.2} [max 48 from 1]
#
# Top scores are [39, 43.2, 46.2, 48] from [1, 1, 1, 1].
# Final multiplication results in [3.9, 4.32, 4.62, 24]
# Final state is [3] with a sequence of [1->3].
sequence, score = viterbi_decode.decode(
scores,
transition_params,
use_log_space=False,
use_start_and_end_states=True)
self.assertAlmostEqual(24.0, score)
self.assertEqual([1, 3], sequence)
def test_viterbi_in_exp_space_with_negative_weights_fails(self):
scores = np.array([[10.0, 12.0, 6.0, 4.0], [13.0, 12.0, 11.0, 10.0]])
x = 0.0
# pyformat: disable
# pylint: disable=bad-whitespace
# pylint: disable=bad-continuation
transition_params = np.array([[ .1, .2, .3, .4],
[ .5, -.6, .7, .8],
[ .9, x, .15, x],
[.25, .35, .45, .55]])
# pyformat: enable
# pylint: enable=bad-whitespace
# pylint: enable=bad-continuation
with self.assertRaises(ValueError):
_, _ = viterbi_decode.decode(
scores, transition_params, use_log_space=False)
if __name__ == '__main__':
absltest.main()
| 39.704319
| 80
| 0.527655
| 1,869
| 11,951
| 3.314072
| 0.108079
| 0.06248
| 0.015499
| 0.069745
| 0.803358
| 0.797385
| 0.789635
| 0.779464
| 0.764127
| 0.750565
| 0
| 0.145191
| 0.318802
| 11,951
| 300
| 81
| 39.836667
| 0.615649
| 0.503389
| 0
| 0.526316
| 0
| 0
| 0.002432
| 0
| 0
| 0
| 0
| 0
| 0.136842
| 1
| 0.073684
| false
| 0
| 0.063158
| 0
| 0.147368
| 0.010526
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 6
|
8089c667c4daaa8c51834b68d3b66f30ea2a837c
| 230
|
py
|
Python
|
cs1006-IntroPython/HW4-ObjectInheritance/teacher/teacher.py
|
ecahern16/AcademicCode
|
cf95a65545e7054604c23d4830f709323eeb81f5
|
[
"Apache-2.0"
] | null | null | null |
cs1006-IntroPython/HW4-ObjectInheritance/teacher/teacher.py
|
ecahern16/AcademicCode
|
cf95a65545e7054604c23d4830f709323eeb81f5
|
[
"Apache-2.0"
] | null | null | null |
cs1006-IntroPython/HW4-ObjectInheritance/teacher/teacher.py
|
ecahern16/AcademicCode
|
cf95a65545e7054604c23d4830f709323eeb81f5
|
[
"Apache-2.0"
] | null | null | null |
from person.person import Person
class Teacher(Person):
def __init__(self, name, pay=None):
Person.__init__(self, name)
self.pay = 0
def __repr__(self):
return self.name
| 19.166667
| 39
| 0.569565
| 27
| 230
| 4.407407
| 0.518519
| 0.201681
| 0.201681
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006623
| 0.343478
| 230
| 12
| 40
| 19.166667
| 0.781457
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.285714
| false
| 0
| 0.142857
| 0.142857
| 0.714286
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 6
|
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