Python time.year() Examples
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Example #1
Source File: visual_cortex.py From rpi_ai with MIT License | 6 votes |
def saveImage(): keepDiskSpaceFree(config.diskSpaceToReserve) time = datetime.datetime.now() filenameFull = config.filepath + config.filenamePrefix + "-%04d%02d%02d%02d%02d%02d" % (time.year, time.month, time.day, time.hour, time.minute, time.second)+ "." + config.fileType # save onto webserver filename = "/var/www/temp.jpg" subprocess.call("sudo raspistill -w "+ str(config.saveWidth) +" -h "+ str(config.saveHeight) + " -t 1 -n -vf -e " + config.fileType + " -q 15 -o %s" % filename, shell=True) print "Captured image: %s" % filename theSpeech = recognizeFace(filename,filenameFull) if len(theSpeech)>2: print theSpeech saySomething(theSpeech,"en") config.lookForFaces = 0 # Keep free space above given level
Example #2
Source File: frequency_estimators.py From augur with GNU Affero General Public License v3.0 | 6 votes |
def timestamp_to_float(time): """Convert a pandas timestamp to a floating point date. >>> import datetime >>> time = datetime.date(2010, 10, 1) >>> timestamp_to_float(time) 2010.75 >>> time = datetime.date(2011, 4, 1) >>> timestamp_to_float(time) 2011.25 >>> timestamp_to_float(datetime.date(2011, 1, 1)) 2011.0 >>> timestamp_to_float(datetime.date(2011, 12, 1)) == (2011.0 + 11.0 / 12) True """ return time.year + ((time.month - 1) / 12.0)
Example #3
Source File: spa.py From fluids with MIT License | 6 votes |
def julian_day_dt(year, month, day, hour, minute, second, microsecond): """This is the original way to calculate the julian day from the NREL paper. However, it is much faster to convert to unix/epoch time and then convert to julian day. Note that the date must be UTC.""" # Not used anywhere! if month <= 2: year = year-1 month = month+12 a = int(year/100) b = 2 - a + int(a * 0.25) frac_of_day = (microsecond + (second + minute * 60 + hour * 3600) ) * 1.0 / (3600*24) d = day + frac_of_day jd = (int(365.25 * (year + 4716)) + int(30.6001 * (month + 1)) + d + b - 1524.5) return jd
Example #4
Source File: extract_features.py From Build-CNN-or-LSTM-or-CNNLSTM-with-speech-features with MIT License | 5 votes |
def get_date(): ''' This creates a string of the day, hour, minute and second I use this to make folder names unique For the files themselves, I generate genuinely unique names (i.e. name001.csv, name002.csv, etc.) ''' time = datetime.datetime.now() time_str = "{}y{}m{}d{}h{}m{}s".format(time.year,time.month,time.day,time.hour,time.minute,time.second) return(time_str)
Example #5
Source File: frequency_estimators.py From augur with GNU Affero General Public License v3.0 | 5 votes |
def float_to_datestring(time): """Convert a floating point date to a date string >>> float_to_datestring(2010.75) '2010-10-01' >>> float_to_datestring(2011.25) '2011-04-01' >>> float_to_datestring(2011.0) '2011-01-01' >>> float_to_datestring(2011.0 + 11.0 / 12) '2011-12-01' In some cases, the given float value can be truncated leading to unexpected conversion between floating point and integer values. This function should account for these errors by rounding months to the nearest integer. >>> float_to_datestring(2011.9166666666665) '2011-12-01' >>> float_to_datestring(2016.9609856262834) '2016-12-01' """ year = int(time) # After accounting for the current year, extract the remainder and convert # it to a month using the inverse of the logic used to create the floating # point date. If the float date is sufficiently close to the end of the # year, rounding can produce a 13th month. month = min(int(np.rint(((time - year) * 12) + 1)), 12) # Floating point dates do not encode day information, so we always assume # they refer to the start of a given month. day = 1 return "%s-%02d-%02d" % (year, month, day)
Example #6
Source File: frequency_estimators.py From augur with GNU Affero General Public License v3.0 | 5 votes |
def __init__(self, sigma_narrow=1 / 12.0, sigma_wide=3 / 12.0, proportion_wide=0.2, pivot_frequency=1, start_date=None, end_date=None, weights=None, weights_attribute=None, node_filters=None, max_date=None, include_internal_nodes=False, censored=False): """Define parameters for KDE-based frequency estimation. Args: sigma_narrow (float): Bandwidth for first of two Gaussians composing the KDEs sigma_wide (float): Bandwidth for second of two Gaussians composing the KDEs proportion_wide (float): Proportion of the second Gaussian to include in each KDE pivot_frequency (int): Number of months between pivots start_date (float): start of the pivots interval end_date (float): end of the pivots interval weights (dict): Numerical weights indexed by attribute values and applied to individual tips weights_attribute (str): Attribute annotated on tips of a tree to use for weighting node_filters (dict): Mapping of node attribute names (keys) to a list of valid values to keep max_date (float): Maximum year beyond which tips are excluded from frequency estimation and are assigned frequencies of zero include_internal_nodes (bool): Whether internal (non-tip) nodes should have their frequencies estimated censored (bool): Whether future observations should be censored at each pivot Returns: KdeFrequencies """ self.sigma_narrow = sigma_narrow self.sigma_wide = sigma_wide self.proportion_wide = proportion_wide self.pivot_frequency = pivot_frequency self.start_date = start_date self.end_date = end_date self.weights = weights self.weights_attribute = weights_attribute self.node_filters = node_filters self.max_date = max_date self.include_internal_nodes = include_internal_nodes self.censored = censored
Example #7
Source File: get_data.py From Malicious_Domain_Whois with GNU General Public License v3.0 | 5 votes |
def update_redis(): get_black_name(1) get_black_tel(1) get_black_email(1) get_malicious_domain_whois(1) get_malicious_sponsoring_registrar() get_malicious_tld() get_ip_frequency() get_exist_situation() get_update_situation() for year in range(2007, 2018): get_c_e_data(year)
Example #8
Source File: test_utils.py From oggm with BSD 3-Clause "New" or "Revised" License | 4 votes |
def test_date_to_floatyear(self): r = utils.date_to_floatyear(0, 1) self.assertEqual(r, 0) r = utils.date_to_floatyear(1, 1) self.assertEqual(r, 1) r = utils.date_to_floatyear([0, 1], [1, 1]) np.testing.assert_array_equal(r, [0, 1]) yr = utils.date_to_floatyear([1998, 1998], [6, 7]) y, m = utils.floatyear_to_date(yr) np.testing.assert_array_equal(y, [1998, 1998]) np.testing.assert_array_equal(m, [6, 7]) yr = utils.date_to_floatyear([1998, 1998], [2, 3]) y, m = utils.floatyear_to_date(yr) np.testing.assert_array_equal(y, [1998, 1998]) np.testing.assert_array_equal(m, [2, 3]) time = pd.date_range('1/1/1800', periods=300*12-11, freq='MS') yr = utils.date_to_floatyear(time.year, time.month) y, m = utils.floatyear_to_date(yr) np.testing.assert_array_equal(y, time.year) np.testing.assert_array_equal(m, time.month) myr = utils.monthly_timeseries(1800, 2099) y, m = utils.floatyear_to_date(myr) np.testing.assert_array_equal(y, time.year) np.testing.assert_array_equal(m, time.month) myr = utils.monthly_timeseries(1800, ny=300) y, m = utils.floatyear_to_date(myr) np.testing.assert_array_equal(y, time.year) np.testing.assert_array_equal(m, time.month) time = pd.period_range('0001-01', '6000-1', freq='M') myr = utils.monthly_timeseries(1, 6000) y, m = utils.floatyear_to_date(myr) np.testing.assert_array_equal(y, time.year) np.testing.assert_array_equal(m, time.month) time = pd.period_range('0001-01', '6000-12', freq='M') myr = utils.monthly_timeseries(1, 6000, include_last_year=True) y, m = utils.floatyear_to_date(myr) np.testing.assert_array_equal(y, time.year) np.testing.assert_array_equal(m, time.month) with self.assertRaises(ValueError): utils.monthly_timeseries(1)
Example #9
Source File: test_utils.py From oggm with BSD 3-Clause "New" or "Revised" License | 4 votes |
def test_hydro_convertion(self): # October y, m = utils.hydrodate_to_calendardate(1, 1, start_month=10) assert (y, m) == (0, 10) y, m = utils.hydrodate_to_calendardate(1, 4, start_month=10) assert (y, m) == (1, 1) y, m = utils.hydrodate_to_calendardate(1, 12, start_month=10) assert (y, m) == (1, 9) y, m = utils.hydrodate_to_calendardate([1, 1, 1], [1, 4, 12], start_month=10) np.testing.assert_array_equal(y, [0, 1, 1]) np.testing.assert_array_equal(m, [10, 1, 9]) y, m = utils.calendardate_to_hydrodate(1, 1, start_month=10) assert (y, m) == (1, 4) y, m = utils.calendardate_to_hydrodate(1, 9, start_month=10) assert (y, m) == (1, 12) y, m = utils.calendardate_to_hydrodate(1, 10, start_month=10) assert (y, m) == (2, 1) y, m = utils.calendardate_to_hydrodate([1, 1, 1], [1, 9, 10], start_month=10) np.testing.assert_array_equal(y, [1, 1, 2]) np.testing.assert_array_equal(m, [4, 12, 1]) # Roundtrip time = pd.period_range('0001-01', '1000-12', freq='M') y, m = utils.calendardate_to_hydrodate(time.year, time.month, start_month=10) y, m = utils.hydrodate_to_calendardate(y, m, start_month=10) np.testing.assert_array_equal(y, time.year) np.testing.assert_array_equal(m, time.month) # April y, m = utils.hydrodate_to_calendardate(1, 1, start_month=4) assert (y, m) == (0, 4) y, m = utils.hydrodate_to_calendardate(1, 4, start_month=4) assert (y, m) == (0, 7) y, m = utils.hydrodate_to_calendardate(1, 9, start_month=4) assert (y, m) == (0, 12) y, m = utils.hydrodate_to_calendardate(1, 10, start_month=4) assert (y, m) == (1, 1) y, m = utils.hydrodate_to_calendardate(1, 12, start_month=4) assert (y, m) == (1, 3) y, m = utils.hydrodate_to_calendardate([1, 1, 1], [1, 4, 12], start_month=4) np.testing.assert_array_equal(y, [0, 0, 1]) np.testing.assert_array_equal(m, [4, 7, 3]) # Roundtrip time = pd.period_range('0001-01', '1000-12', freq='M') y, m = utils.calendardate_to_hydrodate(time.year, time.month, start_month=4) y, m = utils.hydrodate_to_calendardate(y, m, start_month=4) np.testing.assert_array_equal(y, time.year) np.testing.assert_array_equal(m, time.month)
Example #10
Source File: get_data1.py From Malicious_Domain_Whois with GNU General Public License v3.0 | 4 votes |
def get_c_e_data(chooseyear): date_data = dict(year=[{"name":"一月", "cValue":0, "eValue":0}, {"name":"二月", "cValue":0, "eValue":0}, {"name":"三月", "cValue":0, "eValue":0}, {"name":"四月", "cValue":0, "eValue":0}, {"name":"五月", "cValue":0, "eValue":0}, {"name":"六月", "cValue":0, "eValue":0}, {"name":"七月", "cValue":0, "eValue":0}, {"name":"八月", "cValue":0, "eValue":0}, {"name":"九月", "cValue":0, "eValue":0}, {"name":"十月", "cValue":0, "eValue":0}, {"name":"十一月", "cValue":0, "eValue":0}, {"name":"十二月", "cValue":0, "eValue":0}], c_date=[], e_date=[]) standard_year = 2003 for year in range(standard_year, chooseyear+1): date_data['c_date'].append({"name": year,"value":0}) date_data['e_date'].append({"name": year, "value": 0}) data = whois.select(whois.creation_date).where(whois.creation_date != '') for date in data: try: try: time = arrow.get(date.creation_date, 'DD-MMM-YYYY') date_data['c_date'][time.year-standard_year]['value'] += 1 if time.year == chooseyear: date_data['year'][time.month-1]["cValue"] += 1 except: time = arrow.get(date.creation_date) date_data['c_date'][time.year - standard_year]['value'] += 1 if time.year == chooseyear: date_data['year'][time.month - 1]["cValue"] += 1 except: pass data1 = whois.select(whois.expiration_date).where(whois.expiration_date != '') for date in data1: try: try: time = arrow.get(date.expiration_date, 'DD-MMM-YYYY') date_data['e_date'][time.year - standard_year]['value'] += 1 if time.year == chooseyear: date_data['year'][time.month - 1]["eValue"] += 1 except: time = arrow.get(date.expiration_date) date_data['e_date'][time.year - standard_year]['value'] += 1 if time.year == chooseyear: date_data['year'][time.month - 1]["eValue"] += 1 except: pass return json.dumps(date_data, ensure_ascii=False) # 4.2恶意域名总体生存时间分布展示 横轴动态定