martinvonk / spei Goto Github PK

I have a monthly data, but I don't konw hw to use this code. Thanks

Hi there,

I encountered an issue while using the 'spei' package. Here's a summary:

Problem:
When attempting to execute the following code snippet:
spei_fisk = si.SI(pe, dist=scs.fisk, fit_freq="ME") spei_fisk.fit_distribution()

I received the following error message:
AttributeError: module 'spei' has no attribute 'SI'

Please let me know if you need any further information to address this issue. Thanks for your attention to this matter.

Best regards,
Simón.

Hi, I with spei_series = si.spei(input, timescale=30, dist=scs.fisk, fit_freq="MS")
I get
Exception has occurred: ValueError
No objects to concatenate. What is wrong with my input ?

Here is a view of my input series
1961-01-01 897.0
1961-02-01 -69.0
1961-03-01 -706.0
1961-04-01 86.0
1961-05-01 -380.0
...
2020-08-01 -960.0
2020-09-01 -363.0
2020-10-01 1067.0
2020-11-01 -215.0
2020-12-01 1849.0

The original setup was functional. But it is better to transform to SI class and save all data and fitted distributions and logic there.

What is the time scale of the calculated SPEI?

Invalid frequency string passed to pd.Grouper.

The group_yearly_df function passes either "YE" or "Y" to pd.Grouper, depending on the pandas version. Using pandas version '2.1.4', the frequency passed to pd.Grouper is invalid. The correct string is "Y", but "YE" is passed.

The following error was caused:

File ~/.local/lib/python3.10/site-packages/spei/utils.py:85, in group_yearly_df(series)
83 grs = {}
84 freq = "YE" if pd_version >= "2.1.0" else "Y"
---> 85 for year_timestamp, gry in series.groupby(Grouper(freq=freq)):
86 index = validate_index(gry.index)
87 gry.index = to_datetime(
88 "2000-" + index.strftime(strfstr), format="%Y-" + strfstr
89 )

File /g/data/hh5/public/apps/miniconda3/envs/analysis3-23.10/lib/python3.10/site-packages/pandas/core/resample.py:2046, in TimeGrouper.init(self, freq, closed, label, how, axis, fill_method, limit, kind, convention, origin, offset, group_keys, **kwargs)
2043 if convention not in {None, "start", "end", "e", "s"}:
2044 raise ValueError(f"Unsupported value {convention} for convention")
-> 2046 freq = to_offset(freq)
2048 end_types = {"M", "A", "Q", "BM", "BA", "BQ", "W"}
2049 rule = freq.rule_code

File offsets.pyx:4460, in pandas._libs.tslibs.offsets.to_offset()

File offsets.pyx:4557, in pandas._libs.tslibs.offsets.to_offset()

ValueError: Invalid frequency: YE

Hello,

I am having the following error when running si.spei() with a series without any missing value and the index as datetimeindex: ValueError: cannot set using a list-like indexer with a different length than the value

Here is the traceback:
`File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/spei/si.py:170, in spei(series, dist)
143 def spei(series: Series, dist: ContinuousDist = fisk) -> Series:
144 """Method to compute the Standardized Precipitation Evaporation Index
145 [spei_2010]_.
146
(...)
167 Journal of Climate, 23, 1696-1718, 2010.
168 """
--> 170 return compute_si_ppf(series=series, dist=dist)

File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/spei/si.py:56, in compute_si_ppf(series, dist, index, sgi, prob_zero)
54 cdf = compute_cdf_nsf(data=data)
55 ppf = norm.ppf(cdf)
---> 56 si.loc[data.index] = ppf
57 return si

File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/pandas/core/indexing.py:849, in _LocationIndexer.setitem(self, key, value)
846 self._has_valid_setitem_indexer(key)
848 iloc = self if self.name == "iloc" else self.obj.iloc
--> 849 iloc._setitem_with_indexer(indexer, value, self.name)

File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/pandas/core/indexing.py:1837, in _iLocIndexer._setitem_with_indexer(self, indexer, value, name)
1835 self._setitem_with_indexer_split_path(indexer, value, name)
1836 else:
-> 1837 self._setitem_single_block(indexer, value, name)

File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/pandas/core/indexing.py:2077, in _iLocIndexer._setitem_single_block(self, indexer, value, name)
2074 self.obj._check_is_chained_assignment_possible()
2076 # actually do the set
-> 2077 self.obj._mgr = self.obj._mgr.setitem(indexer=indexer, value=value)
2078 self.obj._maybe_update_cacher(clear=True, inplace=True)

File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/pandas/core/internals/managers.py:394, in BaseBlockManager.setitem(self, indexer, value)
389 if using_copy_on_write() and not self._has_no_reference(0):
390 # if being referenced -> perform Copy-on-Write and clear the reference
391 # this method is only called if there is a single block -> hardcoded 0
392 self = self.copy()
--> 394 return self.apply("setitem", indexer=indexer, value=value)

File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/pandas/core/internals/managers.py:352, in BaseBlockManager.apply(self, f, align_keys, **kwargs)
350 applied = b.apply(f, **kwargs)
351 else:
--> 352 applied = getattr(b, f)(**kwargs)
353 result_blocks = extend_blocks(applied, result_blocks)
355 out = type(self).from_blocks(result_blocks, self.axes)

File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/pandas/core/internals/blocks.py:1041, in Block.setitem(self, indexer, value, using_cow)
1038 values = values.T
1040 # length checking
-> 1041 check_setitem_lengths(indexer, value, values)
1043 value = extract_array(value, extract_numpy=True)
1044 try:

File ~/miniconda3/envs/FluxNet/lib/python3.8/site-packages/pandas/core/indexers/utils.py:168, in check_setitem_lengths(indexer, value, values)
162 indexer = np.array(indexer)
163 if not (
164 isinstance(indexer, np.ndarray)
165 and indexer.dtype == np.bool_
166 and indexer.sum() == len(value)
167 ):
--> 168 raise ValueError(
169 "cannot set using a list-like indexer "
170 "with a different length than the value"
171 )
172 if not len(indexer):
173 no_op = True

ValueError: cannot set using a list-like indexer with a different length than the value`

I am running Python 3.8, Numpy 1.24.3, Pandas 2.0.3 and Scipy 1.10.1

Hello!

I've been trying several datasets and I keep getting the same error:

Traceback (most recent call last):

Cell In[31], line 3
si.ssfi(pd.Series(df_mean_month['vazao']), dist=scs.fisk)

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/spei/si.py:251 in ssfi
ssfi.fit_distribution()

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/spei/si.py:394 in fit_distribution
fd = Dist(

File :7 in init

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/spei/dist.py:66 in post_init
pars, loc, scale = self.fit_dist(data=data_fit, dist=self.dist)

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/spei/dist.py:93 in fit_dist
fit_tuple = dist.fit(data, scale=std(data))

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/scipy/stats/_distn_infrastructure.py:2620 in fit
start = self._fitstart(data)

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/scipy/stats/_distn_infrastructure.py:2366 in _fitstart
loc, scale = self._fit_loc_scale_support(data, *args)

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/scipy/stats/_distn_infrastructure.py:2703 in _fit_loc_scale_support
data_a = np.min(data)

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/numpy/core/fromnumeric.py:2953 in min
return _wrapreduction(a, np.minimum, 'min', axis, None, out,

File ~/miniconda3/envs/spyder-env/lib/python3.12/site-packages/numpy/core/fromnumeric.py:88 in _wrapreduction
return ufunc.reduce(obj, axis, dtype, out, **passkwargs)

ValueError: zero-size array to reduction operation minimum which has no identity